Frédéric Célerse,
Veronika Juraskova,
Shubhajit Das,
Matthew D. Wodrich,
Clémence Corminboeuf
- Simulations of chemical reactivity in condensed phase systems represent an ongoing challenge in computational chemistry, where traditional quantum chemical approaches typically struggle with both the size of the system and the potential complexity of the reaction. Here, we introduce a workflow aimed at efficiently training neural network potentials (NNPs) to explore energy barriers in solution at the hybrid density functional theory level. The computational burden associated with training at the PBE0-D3(BJ) level is bypassed through the use of active and transfer learning techniques, whereas extensive sampling of the transition state region is accelerated by well-tempered metadynamics simulations using multiple time-step integration. These NNPs serve to explore a puzzling solute--solvent reactivity route involving the ring opening of N-enoxyphthalimide experimentally observed in methanol but not in 2,2,2-trifluoroethanol (TFE). This reaction represents a challenging example ...
Latest version: v1
Publication date: Sep 09, 2024
Jiaqi Zhou,
Samuel Poncé,
Jean-Christophe Charlier
- The conversion efficiency from charge current to spin current via spin Hall effect is evaluated by the spin Hall ratio (SHR). Through state-of-the-art ab initio calculations involving both charge conductivity and spin Hall conductivity, we report the SHRs of the III-V monolayer family, revealing an ultrahigh ratio of 0.58 in the hole-doped GaAs monolayer. In order to find more promising 2D materials, a descriptor for high SHR is proposed and applied to a high-throughput database, which provides the fully-relativistic band structures and Wannier Hamiltonians of 216 exfoliable monolayer semiconductors and has been released to the community. Among potential candidates for high SHR, the MXene monolayer Sc₂CCl₂ is identified with the proposed descriptor and confirmed by computation, demonstrating the descriptor validity for high SHR materials discovery.
Latest version: v2
Publication date: Sep 06, 2024
Nanchen Dongfang,
Marcella Iannuzzi,
Yasmine Al-Hamdani
- The presence of defects, such as copper and oxygen vacancies, in cuprous oxide films determines their characteristic carrier conductivity and consequently their application as semiconducting systems. There are still open questions on the induced electronic re-distribution, including the formation of polarons. Indeed, to accurately reproduce the structural and electronic properties at the cuprous oxide surface, very large slab models and theoretical approaches that go beyond the standard generalized gradient corrected density functional theory are needed. In this work we investigate oxygen vacancies formed in proximity of a reconstructed Cu₂O(111) surface, where the outermost unsaturated copper atoms are removed, thus forming non-stoichiometric surface layers with copper vacancies. We address simultaneously surface and bulk properties by modelling a thick and symmetric slab, to find that hybrid exchange-correlation functionals are needed to describe the oxygen vacancy in this ...
Latest version: v2
Publication date: Sep 04, 2024
Ifeanyi J. Onuorah,
Miki Bonacci,
Muhammad M. Isah,
Marcello Mazzani,
Roberto De Renzi,
Giovanni Pizzi,
Pietro Bonfà
- Muon spin rotation and relaxation spectroscopy is a powerful tool for studying magnetic materials, offering a local probe that complements scattering techniques and provides advantages in cases of strong incoherent scattering or neutron absorption. By integrating computational methods (DFT+μ), the microscopic interactions driving the observed signals can be precisely quantified, enhancing the technique’s predictive power. We present a set of efficient algorithms and workflows - implemented in the AiiDA framework - that automate the DFT+μ procedure, where the muon is treated as a hydrogen impurity within the density functional theory framework. Our approach automates the identification of muon stopping sites, dipolar interactions, and hyperfine interactions. In this record we share the result of our calculations on well-known compounds, to demonstrate the accuracy and ease of use of our protocol.
Latest version: v1
Publication date: Aug 30, 2024
Chenyu Wang,
Wei Tian,
Ke Zhou
- Comprehending the structure and dynamics of water is crucial in various fields such as water desalination, ion separation, electrocatalysis, and biochemical processes. While reported works show that the ab-initio molecular dynamics (AIMD) can accu- rately portray water’s structure, the artificial high temperature (AHT) from 120K to 30K is needed to mimic the quantum nature of hydrogen-bond network from GGA, metaGGA to hybrid functionals. The AHT proves to be an inadequate approach for systems involving aqueous multiphase mixtures, such as water-solid interfaces and aque- ous solutions. This is due to the activation of additional phonons in other phases, which can lead to an overestimation of the dynamics for nearby water molecules. In this work, we find the regularized SCAN (rSCAN) functional can well capture both the structure and dynamics of liquid water at ambient conditions without AHT. Moreover, rSCAN can well match the experimental results of hydration structures for alkali, ...
Latest version: v1
Publication date: Aug 29, 2024
Sanggyu Chong,
Filippo Bigi,
Federico Grasselli,
Philip Loche,
Matthias Kellner,
Michele Ceriotti
- The widespread application of machine learning (ML) to the chemical sciences is making it very important to understand how the ML models learn to correlate chemical structures with their properties, and what can be done to improve the training efficiency whilst guaranteeing interpretability and transferability. In this work, we demonstrate the wide utility of prediction rigidities, a family of metrics derived from the loss function, in understanding the robustness of ML model predictions. We show that the prediction rigidities allow the assessment of the model not only at the global level, but also on the local or the component-wise level at which the intermediate (e.g. atomic, body-ordered, or range-separated) predictions are made. We leverage these metrics to understand the learning behavior of different ML models, and to guide efficient dataset construction for model training. We finally implement the formalism for a ML model targeting a coarse-grained system to demonstrate the ...
Latest version: v1
Publication date: Aug 28, 2024
Michelle A. Nolen,
Sean A. Tacey,
Martha A. Arellano-Treviño,
Kurt M. Van Allsburg,
Carrie A. Farberow
- An extensive dataset consisting of adsorption energies of pernicious impurities present in biomass upgrading processes on common catalysts and support materials has been generated. This work aims to inform catalyst and process development for the conversion of biomass-derived feedstocks to fuels and chemicals. A high-throughput workflow was developed to execute density functional theory calculations for a diverse set of atomic (Al, B, Ca, Cl, Fe, K, Mg, Mn, N, Na, P, S, Si, Zn) and molecular (COS, H₂S, HCl, HCN, K₂O, KCl, NH₃) species on 35 unique surfaces for transition-metal (Ag, Au, Co, Cu, Fe, Ir, Ni, Pd, Pt, Re, Rh, Ru) and metal-oxide (Al₂O₃, MgO, anatase-TiO₂, rutile-TiO₂, ZnO, ZrO₂) catalysts and supports. Approximately 3,000 unique adsorption geometries were obtained. The data record includes structure and calculation output files for each unique adsorbate geometry on each surface.
Latest version: v2
Publication date: Aug 27, 2024
Austin Zadoks,
Antimo Marrazzo,
Nicola Marzari
- Materials are often represented in machine learning applications by (chemical-)geometric descriptions of their atomic structure. In this work, we propose an alternative framework for representing materials using descriptions of their electronic structure called Spectral Operator Representations (SOREPs). This record contains the code and data used to study carbon nanotubes (CNTs), barium titanate polymorphs, and the accelerated screening of transparent conducting materials with SOREPs. A data set for each application is provided: pz tight binding band structures for the three CNT configurations studied; the structures, band dispersions, and SOREP features of 127 BaTiO₃ polymorphs; and the SOREP features and ML targets for the MC3D materials considered in the accelerated screening. Additionally, code including patch files for Quantum ESPRESSO, the "sorep" python package, and the set of scripts used to prepare these data, train ML models, and plot results is provided.
Latest version: v1
Publication date: Aug 26, 2024
Chenxiao Zhao,
Gonçalo Catarina,
Jin-Jiang Zhang,
João Henriques,
Lin Yang,
Ji Ma,
Xinliang Feng,
Oliver Gröning,
Pascal Ruffieux,
Joaquín Rossier,
Roman Fasel
- Unlocking the potential of topological order within many-body spin systems has long been a central pursuit in the realm of quantum materials. Despite extensive efforts, the quest for a versatile platform enabling site-selective spin manipulation, essential for tuning and probing diverse topological phases, has persisted. Here, we utilize on-surface synthesis to construct spin-1/2 alternating-exchange Heisenberg (AH) chains with antiferromagnetic couplings J1 and J2 by covalently linking Clar's goblets -- nanographenes each hosting two antiferromagnetically-coupled unpaired electrons. In a recent work, utilizing scanning tunneling microscopy, we exert atomic-scale control over the spin chain lengths, parities and exchange-coupling terminations, and probe their magnetic response by means of inelastic tunneling spectroscopy. Our investigation confirms the gapped nature of bulk excitations in the chains, known as triplons. Besides, the triplon dispersion relation is successfully ...
Latest version: v1
Publication date: Aug 22, 2024
Elizaveta Sidler,
Raffaela Cabriolu
- Calcium carbonate (CaCO₃) plays a crucial role in the global carbon cycle, and its phase diagram is of significant scientific interest. We used molecular dynamics to investigate selected structural phase transitions of calcium carbonate. Using the Raiteri potential, we explored the structural transitions occurring at the constant pressure of 1 bar, with temperatures ranging from 300 to 2500 K, and at the constant temperature of 1600 K, with pressures ranging from 0 to 13 GPa. With increasing temperature, the transitions between calcite, CaCO₃-IV, and CaCO₃-V were characterized. In the calcite structure, the carbonate ions are ordered in a planar triangular arrangement, alternating with layers of calcium ions. As the temperature increases, the transition from calcite to CaCO₃-IV occurs, leading to partial disordering of the carbonate ions. At higher temperatures, CaCO₃-IV transforms into CaCO₃-V. Through free energy analysis, we classified the latter transition as a continuous ...
Latest version: v2
Publication date: Aug 21, 2024
Arslan Mazitov,
Ivan Kruglov,
Alexey V. Yanilkin,
Aleksey V. Arsenin,
Valentyn S. Volkov,
Dmitry G. Kvashnin,
Artem R. Oganov,
Kostya S. Novoselov
- Two-dimensional (2D) materials have attracted considerable attention due to their remarkable electronic, mechanical and optical properties, making them prime candidates for next-generation electronic and optoelectronic applications. Despite their widespread use in combination with substrates in practical applications, including the fabrication process and final device assembly, computational studies often neglect the effects of substrate interactions for simplicity.
In this record, we provide the results of the computational study of the stable 2D molybdenum-sulfur (Mo-S) structures on a c-cut sapphire (Al₂O₃). In particular, we provide the results of the evolutionary search in the Mo-S / Al₂O₃ (0001) system, the machine learning interatomic potential (MLIP) used for local relaxation of the systems during the evolutionary search together with its training set, post-processing data on electronic and phonon band structures of the stable 2D Mo-S structures, and the predicted stability patterns from the perspective of CVD synthesis.
Latest version: v1
Publication date: Aug 19, 2024
Arthur Lin,
Kevin Huguenin-Dumittan,
Yong-Cheol Cho,
Jigyasa Nigam,
Rose Cersonsky
- This record contains three datasets and the scripts used to generate figures in "Expanding density-correlation machine learning representations for anisotropic coarse-grained particles." This paper explores the theory and implementation of machine-learning descriptors for ellipsoidal bodies, extending the popular "Smooth Overlap of Atomic Positions" (SOAP) formalism. These case studies serve to demonstrate the different use cases of this technology. The three datasets are:
- Generated configurations of nematic and smectic liquid crystal systems, with a range of orientational order, characterized by the nematic order parameter
- Dimers of (1, 1.5, 2) ellipsoids at different interaction cutoffs and rotations, with computed Gay-Berne type energies
- Crystalline configurations of planar benzene molecules, with energetics computed using QuantumEspresso v7.046 using Perdew–Burke–Ernzerhof (PBE) pseudopotentials and cutoff parameters reported by Prandini et al., Grimme D3-dispersion correction, and a 3 × 3 Monkhorst–Pack k-point grid.
Latest version: v1
Publication date: Aug 14, 2024
Simon Gramatte,
Olivier Politano,
Claudia Cancellieri,
Ivo Utke,
Lars Jeurgens,
Vladyslav Turlo
- This study discloses the effect of hydrogen impurities on the local chemical bonding states and structure of amorphous alumina films by predicting measured Auger parameter shifts using a combination of atomistic and electrostatic modeling. Different amorphous alumina polymorphs with variable H-content and density, as grown by atomic layer deposition, were successfully modeled using a universal machine learning interatomic potential. The annealing of highly defective crystalline hydroxide structures with experimental H-contents at the corresponding atomic layer deposition temperatures led to excellent agreement between theory and experiment in the density and structure of the resulting amorphous alumina polymorphs. The measured Auger parameter shifts of Al cations in such polymorphs were accurately predicted with respect to the H content by assuming that all H atoms are present in the form of hydroxyl ligands in the randomly interconnected 4-fold, 5-fold, and 6-fold ...
Latest version: v1
Publication date: Aug 12, 2024
Leonid Kahle,
Benoit Minisini,
Tai Bui,
Jeremy First,
Corneliu Buda,
Thomas Goldman,
Erich Wimmer
- Machine-learned potentials (MLPs) trained on ab initio data combine the computational efficiency of classical interatomic potentials with the accuracy and generality of the first-principles method used in the creation of the respective training set. In this work, we implement and train a MLP to obtain an accurate description of the potential energy surface and property predictions for organic compounds, as both single molecules and in the condensed phase. We devise a dual descriptor, based on the atomic cluster expansion (ACE), that couples an information-rich short-range description with a coarser long-range description that captures weak intermolecular interactions. We employ uncertainty-guided active learning for the training set generation, creating a dataset that is comparatively small for the breadth of application and consists of alcohols, alkanes, and an adipate. Utilizing that MLP, we calculate densities of those systems of varying chain lengths as a function of ...
Latest version: v1
Publication date: Aug 12, 2024
Marcin Kępa,
Łukasz Cywiński,
Jan A. Krzywda
- Fluctuations of electric fields can change the position of a gate-defined quantum dot in a semiconductor heterostructure. In the presence of magnetic field gradient, these stochastic shifts of electron's wavefunction lead to fluctuations of electron's spin splitting. The resulting spin dephasing due to charge noise limits the coherence times of spin qubits in isotopically purified Si/SiGe quantum dots. We investigate the spin splitting noise caused by such process caused by microscopic motion of charges at the semiconductor-oxide interface. We compare effects of isotropic and planar displacement of the charges, and estimate their densities and typical displacement magnitudes that can reproduce experimentally observed spin splitting noise spectra. We predict that for defect density of 10¹⁰ cm⁻², visible correlations between noises in spin splitting and in energy of electron's ground state in the quantum dot, are expected.
Latest version: v1
Publication date: Aug 07, 2024
Shuonan Chen,
Yongtao Bai*,
Xuhong Zhou*,
Ao Yang
- In this work, we present a comprehensive dataset designed to facilitate the prediction of metal fatigue life using deep learning techniques. The dataset includes detailed experimental data from 40 different metallic materials, comprising a total of 1195 data points under 48 distinct loading paths. Each data point is stored in a CSV file, capturing the loading path as a time-series with axial and tangential stress or strain values.The primary purpose of this dataset is to support the development and validation of deep learning models aimed at accurately predicting the fatigue life of metals under various loading conditions. This dataset includes stress-controlled and strain-controlled data, ensuring a broad representation of experimental scenarios. Additionally, an Excel file accompanies the dataset, providing detailed mechanical properties of each material, such as elastic modulus, tensile strength, yield strength, and Poisson's ratio, along with references to the original ...
Latest version: v2
Publication date: Aug 07, 2024
Marcin Kępa,
Niels Focke,
Łukasz Cywiński,
Jan A. Krzywda
- Due to presence of magnetic field gradient needed for coherent spin control, dephasing of single-electron spin qubits in silicon quantum dots is often dominated by 1/f charge noise. We investigate theoretically fluctuations of ground state energy of an electron in gated quantum dot in realistic Si/SiGe structure. We assume that the charge noise is caused by motion of charges trapped at the semiconductor-oxide interface. We consider a realistic range of trapped charge densities, ρ∼10¹⁰ cm⁻², and typical lenghtscales of isotropically distributed displacements of these charges, δr≤1 nm, and identify pairs (ρ,δr) for which the amplitude and shape of the noise spectrum is in good agreement with spectra reconstructed in recent experiments on similar structures.
Latest version: v1
Publication date: Aug 07, 2024
Juan D. Jiménez,
Pablo G. Lustemberg,
Maila Danielis,
Estefanía Fernández-Villanueva,
Sooyeon Hwang,
Iradwikanari Waluyo,
Adrian Hunt,
Dominik Wierzbicki,
Jie Zhang,
Long Qi,
Alessandro Trovarelli,
Jose A. Rodriguez,
Sara Colussi,
M. Verónica Ganduglia-Pirovano,
Sanjaya D. Senanayake
- In the pursuit of selective conversion of methane directly to methanol in the liquid phase, a common challenge is the concurrent formation of undesirable liquid oxygenates or combustion byproducts. However, we demonstrate that monometallic Pd-CeO2 catalysts, modified by carbon, created by a simple mechanochemical synthesis method exhibit 100% selectivity towards methanol at 75°C, using hydrogen peroxide as oxidizing agent. The solvent-free synthesis yields a distinctive Pd-iC-CeO2 interface, where interfacial carbon (iC) modulates metal-oxide interactions and facilitates tandem methane activation and peroxide decomposition, thus resulting in an exclusive methanol selectivity of 100% with a rate of 117 µmol/gcat at 75°C. Notably, solvent interactions of H2O2 (aq) were found to be critical for methanol selectivity through a DFT-simulated Eley-Rideal-like mechanism. This mechanism uniquely enables the direct conversion of methane into methanol via a solid-liquid-gas process.
Latest version: v1
Publication date: Aug 06, 2024
Mohammad Bagheri,
Hannu-Pekka Komsa
- Raman spectroscopy is a widely-used non-destructive material characterization method, which provides information about the vibrational modes of the material and therefore of its atomic structure and chemical composition. Raman spectra can be simulated using atomistic first-principles methods but these are computationally demanding and thus the existing databases of computational Raman spectra are fairly small. We developed an optimized workflow to efficiently calculate the Raman tensors, from which the Raman spectra can be straightforwardly simulated. The workflow was benchmarked and validated by comparison to experiments and previous computational methods for select technologically relevant material systems. Using the workflow, we performed high-throughput calculations for a large set of materials (5099) belonging to many different material classes, and collected the results to a database.
Latest version: v2
Publication date: Aug 05, 2024
Yao Zhang,
Chunyan Li,
Haiyan Zhao,
Zhongxun Yu,
Xiaoan Tang,
Jixiang Zhang,
Zhenhua Chen,
Jianrong Zeng,
Peng Zhang,
Liyuan Han,
Han Chen
- Tin-lead halide perovskites with a bandgap near 1.2 electron-volt hold great promise for thin-film photovoltaics. However, the film quality of solution-processed Sn-Pb perovskites is compromised by the asynchronous crystallization behavior between Sn and Pb components, where the crystallization of Sn-based perovskites tends to occur faster than that of Pb. Here we show that the rapid crystallization of Sn is rooted in its stereochemically active lone pair, which impedes coordination between the metal ion and Lewis base ligands in the perovskite precursor. From this perspective, we introduce a noncovalent binding agent targeting the open metal site of coordinatively unsaturated Sn(II) solvates, thereby synchronizing crystallization kinetics and homogenizing Sn-Pb alloying. The resultant single-junction Sn-Pb perovskite solar cells achieve a certified power conversion efficiency of 24.13 per cent. The encapsulated device retains 90 per cent of the initial efficiency after 795 hours ...
Latest version: v2
Publication date: Aug 05, 2024
Victor Trinquet,
Matthew L. Evans,
Cameron Hargreaves,
Pierre-Paul De Breuck,
Gian-Marco Rignanese
- Combinatorial and guided screening of materials space with density-functional theory and related approaches has provided a wealth of hypothetical inorganic materials, which are increasingly tabulated in open databases. The OPTIMADE API is a standardised format for representing crystal structures, their measured and computed properties, and the methods for querying and filtering them from remote resources. Currently, the OPTIMADE federation spans over 20 data providers, rendering over 30 million structures accessible in this way, many of which are novel and have only recently been suggested by machine learning-based approaches. In this work, we outline our approach to non-exhaustively screen this dynamic trove of structures for the next-generation of optical materials. By applying MODNet, a neural network-based model for property prediction that has been shown to perform especially well for small materials datasets, within a combined active learning and high-throughput computation ...
Latest version: v1
Publication date: Aug 05, 2024
Arzoo Hassan,
Andleeb Mehmood,
Umer Younis,
Mahmood Ahmad Ghazanfar,
Yong Wang,
Xiaoqing Tian,
Qing-Feng Sun
- The deposited structure models of DNA adsorbed on prisitne PG/p-Si and metal (Au/W) doped PG/p-Si sheets, have been subjected to first principles calculations based on DFT (PBE+vdW). The calculated binding affinity on PG and p-Si surface by M062X/6-31G* level of theory and adsorption energies by DFT predicts that PG has higher sensitivity towards DNA nucleic bases compared to p-Si with evident changes in their band structure properties.
Latest version: v1
Publication date: Jul 26, 2024
Shun Tian,
Ke Zhou,
Wanjian Yin,
Yilun Liu
- Materials demonstrating positive thermal expansion (PTE) or negative thermal expansion (NTE) are quite common, whereas those exhibiting zero thermal expansion (ZTE) are notably scarce. In this work, we identify the mechanical descriptors, namely in-plane tensile stiffness and out-of-plane bending stiffness, that can effectively classify PTE and NTE 2D crystals. By utilizing high throughput calculations and the state-of-the-art symbolic regression method, these descriptors aid in the discovery of ZTE or 2D Invar monolayers with the linear thermal expansion coefficient (LTEC) within ±2×10⁻⁶ K⁻¹ in the middle range of temperatures. Additionally, the descriptors assist the discovery of large PTE and NTE 2D monolayers with the LTEC larger than ±15×10⁻⁶ K⁻¹, which are so-called 2D anti-Invar monolayers. Advancing our understanding of materials with exceptionally low or high thermal expansion is of substantial scientific and technological interest, particularly in developing next-generation electronics at the nanometer even Ångstrom scale.
Latest version: v1
Publication date: Jul 25, 2024
Wei Zhang,
Zhijun Wu,
Yin-xiao Sheng,
Fu-li Sun,
Wen-xian Chen,
Gui-lin Zhuang
- Efficient O₂ reduction to H₂O₂, vital for energy conversion and environmental cleanup, relies on precise control of heterogeneous catalysts interacting with reaction species. Through high-throughput density functional theory calculations, consisting of 369 single atom catalysts, we identified the polarized descriptor (electric dipole strength) on two-dimensional carbon materials, revealing insights into the catalytic effect of support polarization. Surprisingly, this descriptor exhibits advanced scaling relationships towards H₂O₂ synthesis, incorporating factors such as active metals, coordination environments, and surface curvatures, highlighting its widespread significance. Furthermore, it demonstrates reliable predictability for O₂ adsorption in dynamic water environments, with optimal reactivity observed within the range of -1.40 to -1.00 e·Å, as confirmed by dynamic and static simulations of the 2e- pathway of O₂ reduction. In essence, these findings offer valuable insights ...
Latest version: v1
Publication date: Jul 23, 2024
Xia Liu,
Berke Erbas,
Ana Conde Rubio,
Norma Rivano,
Zhenyu Wang,
Jin Jiang,
Siiri Bienz,
Naresh Kumar,
Thibault Sohier,
Marcos Penedo,
Mitali Banerjee,
Georg Fantner,
Renato Zenobi,
Nicola Marzari,
Andras Kis,
Giovanni Boero,
Juergen Brugger
- Field-effect transistors (FETs) based on two-dimensional materials (2DMs) with atomically thin channels have emerged as a promising platform for beyond-silicon electronics. However, low carrier mobility in 2DM transistors driven by phonon scattering remains a critical challenge. To address this issue, we propose the controlled introduction of localized tensile strain as an effective mean to inhibit electron-phonon scattering in 2DM. Strain is achieved by conformally adhering the 2DM via van-der-Waals forces to a dielectric layer previously nanoengineered with a gray-tone topography. Our results show that monolayer MoS₂ FETs under tensile strain achieve an 8-fold increase in on-state current, reaching mobilities of 185 cm²/Vs at room temperature, in good agreement with theoretical calculations. The present work on nanotopographic grayscale surface engineering and the use of high-quality dielectric materials has the potential to find application in the nanofabrication of photonic ...
Latest version: v1
Publication date: Jul 22, 2024
Nicolas Roisin,
Guillaume Brunin,
Gian-Marco Rignanese,
Denis Flandre,
Jean-Pierre Raskin,
Samuel Poncé
- Strain engineering is a widely used technique for enhancing the mobility of charge carriers in semiconductors, but its effect is not fully understood. In this work, we perform first-principles calculations to explore the variations of the mobility of electrons and holes in silicon upon deformation by uniaxial strain up to 2% in the [100] crystal direction. We compute the π₁₁ and π₁₂ electron piezoresistances based on the low-strain change of resistivity with temperature in the range 200 K to 400 K, in excellent agreement with experiment. We also predict them for holes which were only measured at room temperature. Remarkably, for electrons in the transverse direction, we predict a minimum room-temperature mobility about 1200 cm²/Vs at 0.3% uniaxial tensile strain while we observe a monotonous increase of the longitudinal transport, reaching a value of 2200 cm²/Vs at high strain. We confirm these findings experimentally using four-point bending measurements, establishing the ...
Latest version: v4
Publication date: Jul 19, 2024
Manura Liyanage,
Vladyslav Turlo,
W. A. Curtin
- Combining the excellent thermal and electrical properties of Cu with the high abrasion resistance and thermal stability of W, Cu-W nanoparticle-reinforced metal matrix composites and nano-multilayers (NMLs) are finding applications as brazing fillers and shielding material for plasma and radiation. Due to the large lattice mismatch between fcc Cu and bcc W, these systems have complex interfaces that are beyond the scales suitable for ab initio methods, thus motivating the development of chemically accurate interatomic potentials. Here, a neural network potential (NNP) for Cu-W is developed within the Behler-Parrinello framework using a curated training dataset that captures metallurgically-relevant local atomic environments. The Cu-W NNP accurately predicts (i) the metallurgical properties (elasticity, stacking faults, dislocations, thermodynamic behavior) in elemental Cu and W, (ii) energies and structures of Cu-W intermetallics and solid solutions, and (iii) a range of fcc ...
Latest version: v1
Publication date: Jul 18, 2024
Eduárd Zsurka,
Cheng Wang,
Julian Legendre,
Daniele Di Miceli,
Llorenç Serra,
Detlev Grützmacher,
Thomas L. Schmidt,
Philipp Rüßmann,
Kristof Moors
- We develop an accurate nanoelectronic modeling approach for realistic three-dimensional topological insulator nanostructures and investigate their low-energy surface-state spectrum. Starting from the commonly considered four-band k·p bulk model Hamiltonian for the Bi₂Se₃ family of topological insulators, we derive new parameter sets for Bi₂Se₃, Bi₂Te₃ and Sb₂Te₃. We consider a fitting strategy applied to ab initio band structures around the Γ point that ensures a quantitatively accurate description of the low-energy bulk and surface states, while avoiding the appearance of unphysical low-energy states at higher momenta, something that is not guaranteed by the commonly considered perturbative approach. We analyze the effects that arise in the low-energy spectrum of topological surface states due to band anisotropy and electron-hole asymmetry, yielding Dirac surface states that naturally localize on different side facets. In the thin-film limit, when surface states hybridize ...
Latest version: v1
Publication date: Jul 05, 2024
Luca Schaufelberger,
J. Terence Blaskovits,
Ruben Laplaza,
Clemence Corminboeuf,
Kjell Jorner
- Singlet fission has shown potential for boosting the power conversion efficiency of solar cells, but the scarcity of suitable molecular materials hinders its implementation. We introduce an uncertainty-controlled genetic algorithm (ucGA) based on ensemble machine learning predictions from different molecular representations that concurrently optimizes excited state energies, synthesizability, and singlet exciton size for the discovery of singlet fission materials. We show that uncertainty in the model predictions can control how far the genetic optimization moves away from previously known molecules.
Running the ucGA in an exploitative setup performs local optimization on variations of known singlet fission scaffolds, such as acenes. In an explorative mode, hitherto unknown candidates displaying excellent excited state properties for singlet fission are generated. We suggest a class of heteroatom-rich mesoionic compounds as acceptors for charge-transfer mediated singlet fission. ...
Latest version: v1
Publication date: Jul 04, 2024
Rubel Mozumder,
Johannes Wasmer,
David Antognini Silva,
Stefan Blügel,
Philipp Rüßmann
- Using high-throughput automation of ab-initio impurity-embedding simulations we created a database of 3d and 4d transition metal defects embedded into the prototypical topological insulator (TI) Bi₂Te₃. We simulate both single impurities as well as impurity dimers at different impurity-impurity distances inside the topological insulator matrix. We extract changes to magnetic moments, analyze the polarizability of non-magnetic impurity atoms via nearby magnetic impurity atoms and calculate the exchange coupling constants for a Heisenberg Hamiltonian.
We uncover chemical trends in the exchange coupling constants and discuss the impurities' potential with respect to magnetic order in the fields of quantum anomalous Hall insulators. In particular, we predict that co-doping of different magnetic dopants is a viable strategy to engineer the magnetic ground state in magnetic TIs.
Latest version: v1
Publication date: Jul 04, 2024
Wei Bin How,
Sanggyu Chong,
Federico Grasselli,
Kevin K. Huguenin-Dumittan,
Michele Ceriotti
- The electronic density of states (DOS) provides information regarding the distribution of electronic states in a material, and can be used to approximate its optical and electronic properties and therefore guide computational material design. Given its usefulness and relative simplicity, it has been one of the first electronic properties used as target for machine-learning approaches going beyond interatomic potentials. A subtle but important point, well-appreciated in the condensed matter community but usually overlooked in the construction of data-driven models, is that for bulk configurations the absolute energy reference of single-particle energy levels is ill-defined. Only energy differences matter, and quantities derived from the DOS are typically independent on the absolute alignment. We introduce an adaptive scheme that optimizes the energy reference of each structure as part of training, and show that it consistently improves the quality of ML models compared to ...
Latest version: v1
Publication date: Jul 04, 2024
Feifei Xiang,
Lysander Huberich,
Preston A. Vargas,
Riccardo Torsi,
Jonas Allerbeck,
Anne Marie Z. Tan,
Chengye Dong,
Pascal Ruffieux,
Roman Fasel,
Oliver Gröning,
Yu-Chuan Lin,
Richard G. Hennig,
Joshua A. Robinson,
Bruno Schuler
- The functionality of atomic quantum emitters is intrinsically linked to their host lattice coordination. Structural distortions that spontaneously break the lattice symmetry strongly impact their optical emission properties and spin-photon interface. In a recent manuscript, we report on the direct imaging of charge state-dependent symmetry breaking of two prototypical atomic quantum emitters in mono- and bilayer MoS₂ by scanning tunneling microscopy (STM) and non-contact atomic force microscopy (nc-AFM). By changing the built-in substrate chemical potential, different charge states of sulfur vacancies (VacS) and substitutional rhenium dopants (ReMo) can be stabilized. VacS⁻¹ as well as ReMo⁰ and ReMo⁻¹ exhibit local lattice distortions and symmetry-broken defect orbitals attributed to a Jahn-Teller effect (JTE) and pseudo-JTE, respectively. By mapping the electronic and geometric structure of single point defects, we ...
Latest version: v1
Publication date: Jul 03, 2024
Yuri Cho,
Ruben Laplaza,
Sergi Vela,
Clemence Corminboeuf
- Predicting the ground state spin of transition metal complexes is a challenging task. Previous attempts have been focused on specific regions of chemical space, whereas a more general automated approach is required to process crystallographic structures for high-throughput quantum chemistry computations. In this work, we developed a method to predict ground state spins of transition metal complexes. We started by constructing a dataset which contains 2,063 first row transition metal complexes taken from experimental crystal structures and their computed ground state spins. This dataset showed large chemical diversity in terms of metals, metal oxidation states, coordination geometries, and ligands. Then, we analyzed the trends between structural and electronic features of the complexes and their ground state spins, and put forward an empirical spin state assignment model. We also used simple descriptors to build a statistical model with >95% predictive accuracy across the board. ...
Latest version: v2
Publication date: Jul 01, 2024
Longze Li,
John Merickel,
Yalei Tang,
Rongjie Song,
Joshua Rittenhouse,
Aleksandar Vakanski,
Fei Xu
- The dataset provides records of tensile properties of nuclear structural materials. The focus is on studying the influence of specimen dimensions and geometry on mechanical properties such as yield strength, ultimate tensile strength, uniform elongation, and total elongation. The dataset was created through an extensive literature review of scientific articles and databases. The search inclusion criteria targeted peer-reviewed studies on tensile testing of sub-sized specimens, providing quantitative data on tensile properties relative to specimen size. The extracted data points from the literature review were organized into a tabular format database containing 1,070 tensile testing records with 54 parameters, including material type and composition, manufacturing information, irradiation conditions, specimen size and dimensions, and tensile properties. Materials science experts conducted systematic checks to validate the collected data, ensuring accuracy in the material type, ...
Latest version: v1
Publication date: Jun 25, 2024
Letizia Tavagnacco,
Marco Zanatta,
Elena Buratti,
Monica Bertoldo,
Ester Chiessi,
Markus Appel,
Francesca Natali,
Andrea Orecchini,
Emanuela Zaccarelli
- The protein dynamical transition marks an increase in atomic mobility and the onset of anharmonic motions at a critical temperature, which is considered relevant for protein functionality. This phenomenon is ubiquitous, regardless of protein composition, structure and biological function and typically occurs at large protein content, to avoid water crystallization. Recently, a dynamical transition has also been reported in non-biological macromolecules, such as poly(N-isopropyl acrylamide) (PNIPAM) microgels, bearing many similarities to proteins. While the generality of this phenomenon is well-established, the role of water in the transition remains a subject of debate. In this study, we use atomistic molecular dynamics simulations and elastic incoherent neutron scattering (EINS) experiments with selective deuteration to investigate the microscopic origin of the dynamical transition and distinguish water and PNIPAM roles. While a standard analysis of EINS experiments would ...
Latest version: v1
Publication date: Jun 24, 2024
O. Fedchenko,
F. K. Diekmann,
P. Rüßmann,
M. Kallmayer,
L. Odenbreit,
S. M. Souliou,
M. Frachet,
A. Winkelmann,
M. Merz,
S. Chernov,
D. Vasilyev,
D. Kutnyakhov,
O. Tkach,
Ya. Lytvynenko,
K. Medjanik,
C. Schlueter,
A. Gloskovskii,
T. R. F. Peixoto,
M. Hoesch,
M. Le Tacon,
Y. Mokrousov,
K. Roßnagel,
G. Schönhense,
H.-J. Elmers
- A comprehensive study of the electronic and structural phase transition from 1T` to Td in the bulk Weyl semimetal Mo1-xWxTe2 at different doping concentrations has been carried out using time-of-flight momentum microscopy (including circular and linear dichroism), X-ray photoelectron spectroscopy, X-ray photoelectron diffraction, X-ray diffraction (XRD), angle-resolved Raman spectroscopy, transport measurements (including longitudinal elastoresistance), density functional theory (DFT) and Kikuchi pattern calculations. High-resolution, angle-resolved photoemission spectroscopy at 20 K reveals surface electronic states, which are indicative for topological Fermi arcs. Their dispersion agrees with the position of Weyl points predicted by DFT calculations based on the precise crystal structure of our samples obtained from XRD measurements. Raman spectroscopy confirms the inversion symmetry breaking for the Td-phase, which is a ...
Latest version: v1
Publication date: Jun 24, 2024
Yannick Schubert,
Sandra Luber,
Nicola Marzari,
Edward Linscott
- Koopmans spectral functionals represent a powerful extension of Kohn-Sham density-functional theory (DFT), enabling accurate predictions of spectral properties with state-of-the-art accuracy. The success of these functionals relies on capturing the effects of electronic screening through scalar, orbital-dependent parameters. These parameters have to be computed for every calculation, making Koopmans spectral functionals more expensive than their DFT counterparts. In a manuscript of the same title, we present a machine-learning model that — with minimal training — can predict these screening parameters directly from orbital densities calculated at the DFT level. We show on two prototypical use cases that using the screening parameters predicted by this model, instead of those calculated from linear response, leads to orbital energies that differ by less than 20 meV on average. Since this approach dramatically reduces run-times with minimal loss of accuracy, it will enable the ...
Latest version: v1
Publication date: Jun 24, 2024
Casey E. Beall,
Emiliana Fabbri,
Adam H. Clark,
Vivian Meier,
Nur Sena Yüzbasi,
Thomas Graule,
Sayaka Takahashi,
Yuto Shirase,
Makoto Uchida,
Thomas J. Schmidt
- The development of unified regenerative fuel cells (URFC) necessitates an active and stable bifunctional oxygen electrocatalyst. The unique challenge of possessing high activity for both the oxygen reduction (ORR) and oxygen evolution (OER) reactions, while maintaining stability over a wide potential window impedes the design of bifunctional oxygen electrocatalysts. Herein, two design strategies are explored to optimize their performance. The first incorporates active sites for ORR and OER, Mn and Co, into a single perovskite structure, which is achieved with the perovskites Ba0.5Sr0.5Co0.8Mn0.2O3-δ (BSCM) and La0.5Ba0.25Sr0.25Co0.5Mn0.5O3-δ (LBSCM). The second combines an active ORR perovskite catalyst (La0.4Sr0.6MnO3-δ (LSM)) with an OER active perovskite catalyst ...
Latest version: v1
Publication date: Jun 21, 2024
Yang Hu,
Giacomo Lorenzin,
Jeyun Yeom,
Manura Liyanage,
William Curtin,
Lars Jeurgens,
Jolanta Janczak-Rusch,
Claudia Cancellieri,
Vladyslav Turlo
- The intrinsic stress in nanomultilayers (NMLs) is typically dominated by interface stress, which is particularly high in immiscible Cu/W NMLs. Here, atomistic simulations with a chemically-accurate neural network potential reveal the role of interfacial intermixing and metastable phase formation on the interface stress levels. These results rationalize an experimentally-reported compressive-to-tensile transition as a function of NML deposition conditions and the extremely high interface stresses under some conditions.
Latest version: v1
Publication date: Jun 21, 2024
Tara Niamh Tosic,
Yuting Chen,
Nicola Ann Spaldin
- We use first-principles density functional theory to investigate how the polar distortion is affected by doping in multiferroic hexagonal yttrium manganite, h-YMnO₃. While the introduction of charge carriers tends to suppress the polar distortion in conventional ferroelectrics, the behavior in improper geometric ferroelectrics, of which h-YMnO₃ is the prototype, has not been studied to date. Using both background charge doping and atomic substitution, we find an approximately linear dependence of the polar distortion on doping concentration, with hole doping reducing and electron doping enhancing it. We show that this behavior is a direct consequence of the improper geometric nature of the ferroelectricity. In addition to its doping effect, atomic substitution can further suppress or enhance the polar distortion through changes in the local chemistry and geometry.
Latest version: v1
Publication date: Jun 21, 2024
Tenghua Gao,
Philipp Rüßmann,
Qianwen Wang,
Hiroki Hayashi,
Dongwook Go,
Song Zhang,
Takashi Harumoto,
Rong Tu,
Lianmeng Zhang,
Yuriy Mokrousov,
Ji Shi,
Kazuya Ando
- Spintronics applications for high-density non-volatile memories require simultaneous optimization of the perpendicular magnetic anisotropy (PMA) and current-induced magnetization switching. These properties determine, respectively, the thermal stability of a ferromagnetic memory cell and a low operation power consumption, which are mutually incompatible with the spin transfer torque as the driving force for the switching. Here, we demonstrate a strategy of alloy engineering to overcome this obstacle by using electrically induced orbital currents instead of spin currents. A non-equilibrium orbital density generated in paramagnetic γ-FeMn flows into CoPt coupled to the magnetization through spin-orbit interaction, ultimately creating an orbital torque. Controlling the atomic arrangement of Pt and Co by structural phase transition, we show that the propagation length of the transferred angular momentum can be modified concurrently with the PMA strength. We find a strong correlation ...
Latest version: v2
Publication date: Jun 20, 2024
Margaret Berrens,
Arpan Kundu,
Marcos F. Calegari Andrade,
Tuan Anh Pham,
Giulia Galli,
Davide Donadio
- The electronic properties and optical response of ice and water are intricately shaped by their molecular structure, including the quantum mechanical nature of hydrogen atoms. Despite numerous former studies, a comprehensive understanding of nuclear quantum effects (NQE) on the electronic structure of water and ice at finite temperatures remains elusive. Here, we utilize molecular simulations that harness efficient machine-learning potentials and many-body perturbation theory to assess how NQEs impact the electronic bands of water and hexagonal ice. By comparing path-integral and classical simulations, we find that NQEs lead to a larger renormalization of the fundamental gap of ice, compared to that of water, ultimately yielding similar bandgaps in the two systems, consistent with experimental estimates. Our calculations suggest that the increased quantum mechanical delocalization of protons in ice, relative to water, is a key factor leading to the enhancement of NQEs on the electronic structure of ice.
Latest version: v1
Publication date: Jun 17, 2024
Thanapat Worakul,
Boodsarin Sawatlon,
Panida Surawatanawong
- The C-F activation is one of the important processes in chemical synthesis. Here, we studied the hydrodefluorination of PhCF3 with SiMe2Ph-H catalyzed by Ni(0) complexes. The mechanisms involve three main steps: C-F bond cleavage of PhCF3 on the nickel complex, transmetalation of Ni-F with SiMe2Ph-H to form a nickel hydride complex, and C-H reductive elimination of PhCF2H. We performed density functional calculations on nickel complexes with thirty carbene and phosphine ligands to obtain the relative free energy profiles. Then, linear free energy scaling relationships were determined and molecular volcano plots were constructed. To accurately describe catalytic activity, we found that multiple reference states must be considered. Thus, the concept of "reference-generalized volcano plots (RGVPs)" was introduced to assist with the selection of the appropriate reference state to determine catalytic activity. Our regression models indicate that electronic properties of ligands ...
Latest version: v1
Publication date: Jun 14, 2024
Victor Trinquet,
Francesco Naccarato,
Guillaume Brunin,
Guido Petretto,
Ludger Wirtz,
Geoffroy Hautier,
Gian-Marco Rignanese
- Optical materials play a key role in enabling modern optoelectronic technologies in a wide variety of domains such as the medical or the energy sector. Among them, nonlinear optical crystals are of primary importance to achieve a broader range of electromagnetic waves in the devices. However, numerous and contradicting requirements significantly limit the discovery of new potential candidates, which, in turn, hinders the technological development. In the present work, the static nonlinear susceptibility and dielectric tensor are computed via density functional perturbation theory for a set of 579 inorganic semiconductors. The aim of this work is to provide a relevant dataset to foster the identification of promising nonlinear optical crystals in order to motivate their subsequent experimental investigation.
Latest version: v1
Publication date: Jun 13, 2024
Jiaqi Zhou,
Samuel Poncé,
Jean-Christophe Charlier
- Emerging two-dimensional (2D) materials bring unprecedented opportunities for electronic applications. The design of high-performance devices requires an accurate prediction of carrier mobility in 2D materials, which can be obtained using state-of-the-art ab initio calculations. However, various factors impact the computational accuracy, leading to contradictory estimations for the mobility. In this work, targeting accurate and efficient ab initio calculations, transport properties in III-V monolayers are reported using the Boltzmann transport equation, and the influences of pseudopotential, quadrupole correction, Berry connection, and spin-orbit coupling (SOC) on mobilities are systematically investigated. Our findings are as follows: (1) The inclusion of semi-core states in pseudopotentials is important to obtain accurate calculations. (2) The variations induced by dynamical quadrupole and Berry connection when treating long range fields can be respectively 40% and 10%. (3) The ...
Latest version: v1
Publication date: Jun 13, 2024
Giacomo Lorenzin,
Fedor Klimashin,
Jeyun Jeom,
Yang Hu,
Johann Michler,
Jolanta Janczak-Rusch,
Vladyslav Turlo,
Claudia Cancellieri
- The combination of the high wear resistance and mechanical strength of W with the high thermal conductivity of Cu makes the Cu/W system an attractive candidate material for heat sink plasma and radiation tolerance applications. However, the resulting mechanical properties of multilayers and coatings strongly depend on the microstructure of the layers.
In this work, the mechanical properties of Cu/W nanomultilayers with different densities of internal interfaces are systematically investigated for two opposite in-plane stress states and critically discussed in comparison with literature. Atomistic simulations with the state-of-the-art neural network potential are used to explain the experimental findings. The results suggest that the microstructure, specifically the excess free volume associated with porosity and interface disorder interconnected with the stress state, has a great impact on the mechanical properties, notably Young's modulus of Cu/W nanomultilayers.
Latest version: v1
Publication date: Jun 07, 2024
Michele Simoncelli,
Daniele Fournier,
Massimiliano Marangolo,
Etienne Balan,
Keevin Béneut,
Benoit Baptiste,
Béatrice Doisneau,
Nicola Marzari,
Francesco Mauri
- The thermal conductivities of crystals and glasses vary strongly and with opposite trends upon heating, decreasing in crystals and increasing in glasses. Here, we show---with first-principles predictions based on the Wigner transport equation and thermoreflectance experiments---that the dominant transport mechanisms of crystals (particle-like propagation) and glasses (wave-like tunnelling) can coexist and compensate in materials with crystalline bond order and nearly glassy bond geometry. We demonstrate that ideal compensation emerges in silica tridymite, carved from a meteorite found in Steinbach (Germany) in 1724, and yields a ‘Propagation-Tunneling-Invariant’ (PTI) conductivity that is independent of temperature and intermediate between the opposite trends of α-quartz crystal and silica glass. We show how such PTI conductivity occurs in the quantum regime below the Debye temperature, and can largely persist at high temperatures in a geometrically amorphous tridymite phase found ...
Latest version: v1
Publication date: Jun 07, 2024
Antimo Marrazzo,
Nicola Colonna
- The presence of spin-orbit coupling or non-collinear magnetic spin states can have dramatic effects on the ground-state and spectral properties of materials, in particular on the band structure. Here, we develop non-collinear Koopmans-compliant functionals based on Wannier functions and density-functional perturbation theory, targeting accurate spectral properties in the quasiparticle approximation. Our non-collinear Koopmans-compliant theory involves functionals of four-component orbitals densities, that can be obtained from the charge and spin-vector densities of Wannier functions. We validate our approach on four emblematic non-magnetic and magnetic semiconductors where the effect of spin-orbit coupling goes from small to very large: the III-IV semiconductor GaAs, the transition-metal dichalcogenide WSe₂, the cubic perovskite CsPbBr₃, and the ferromagnetic semiconductor CrI₃.
The predicted band gaps are comparable in accuracy to state-of-the-art many-body perturbation theory ...
Latest version: v1
Publication date: Jun 03, 2024
Norma Rivano,
Nicola Marzari,
Thibault Sohier
- The electronic and vibrational properties and electron-phonon couplings of one-dimensional materials will be key to many prospective applications in nanotechnology. Dimensionality strongly affects these properties and has to be correctly accounted for in first-principles calculations. Here we develop and implement a formulation of density-functional and density-functional perturbation theory that is tailored for one-dimensional systems. A key ingredient is the inclusion of a Coulomb cutoff, a reciprocal-space technique designed to correct for the spurious interactions between periodic images in periodic-boundary conditions. This restores the proper one-dimensional open-boundary conditions, letting the true response of the isolated one-dimensional system emerge. In addition to total energies, forces and stress tensors, phonons and electron-phonon interactions are also properly accounted for. We demonstrate the relevance of the present method on a portfolio of realistic systems: BN ...
Latest version: v1
Publication date: May 31, 2024
Sara Marchio,
Francesco Buonocore,
Simone Giusepponi,
Massimo Celino
- Functionalizing Silicon Nanowires (SiNWs) through covalent attachment of organic molecules offers diverse advantages, including surface passivation, introduction of new functionalities, and enhanced material performance in applications like electronic devices and biosensors. Given the wide range of available functional molecules, systematic large-scale screening is crucial. Therefore, we developed an automated computational workflow using Python scripts in conjunction with the AiiDa framework to explore structural configurations of functional molecules adsorbed onto silicon surfaces. This workflow generates multiple adhesion configurations corresponding to different binding orientations using surface and functional molecule structures as inputs.
This dataset contains data related to the structural optimization of molecules with single, double, and triple carbon-carbon bonds attached to the nanowire surface in various adhesion configurations. We describe the chemisorption on ...
Latest version: v1
Publication date: May 29, 2024
Nicephore Bonnet,
Nicola Marzari
- In this paper, we propose an extension to the approach of [Xi, C; et al. J. Chem. Theory Comput. 2022, 18, 6878] to calculate ion solvation free energies from first-principles (FP) molecular dynamics (MD) simulations of a hybrid solvation model. The approach is first re-expressed within the quasi-chemical theory of solvation. Then, to allow for longer simulation times than the original first-principles molecular dynamics approach and thus improve the convergence of statistical averages at a fraction of the original computational cost, a machine-learned (ML) energy function is trained on FP energies and forces and used in the MD simulations. The ML workflow and MD simulation times (≈200 ps) are adjusted to converge the predicted solvation energies within a chemical accuracy of 0.04 eV. The extension is successfully benchmarked on the same set of alkaline and alkaline-earth ions.
The record includes all molecular-dynamics trajectories, energies and forces used to obtain the ...
Latest version: v1
Publication date: May 27, 2024
Chenxiao Zhao,
Qiang Huang,
Leoš Valenta,
Kristjan Eimre,
Lin Yang,
Aliaksandr V. Yakutovich,
Wangwei Xu,
Xinliang Feng,
Michal Juríček,
Roman Fasel,
Pascal Ruffieux,
Carlo A. Pignedoli
- Atomically precise graphene nanoflakes called nanographenes have emerged as a promising platform to realize carbon magnetism. Their ground state spin configuration can be anticipated by Ovchinnikov-Lieb rules based on the mismatch of π electrons from two sublattices. While rational geometrical design achieves specific spin configurations, further direct control over the π electrons offers a desirable extension for efficient spin manipulations and potential quantum device operations. To this end, in a recent publication, we applied a site-specific dehydrogenation using a scanning tunneling microscope tip to nanographenes deposited on a Au(111) substrate, which showed the capability of precisely tailoring the underlying π-electron system and therefore efficiently manipulating their magnetism. Through first-principles calculations and tight-binding meanfield-Hubbard modeling, we demonstrated that the dehydrogenation-induced Au—C bond formation along with the resulting hybridization ...
Latest version: v1
Publication date: May 23, 2024
Fabrizio Cossu,
Jùlio Alves Do Nascimento,
Stuart A. Cavill,
Igor Di Marco,
Vlado K. Lazarov,
Heung-Sik Kim
- Using first-principles techniques, we study the structural, magnetic, and electronic properties of (111)-oriented (LaMnO₃)₂ₙ|(SrMnO₃)ₙ superlattices of varying thickness (n=2,4,6). We find that the properties of the thinnest superlattice (n=2) are similar to the celebrated half-metallic ferromagnetic alloy La2/3Sr1/3MnO₃, with quenched Jahn-Teller distortions. At intermediate thickness (n=4), the a⁻a⁻a⁻ tilting pattern transitions to the a⁻a⁻c⁺ tilting pattern, driven by the lattice degrees of freedom in the LaMnO₃ region. The emergence of the Jahn-Teller modes and the spatial extent needed for their development play a key role in this structural transition. For the largest thickness considered (n=6), we unveil an emergent separation of Jahn-Teller and volume-breathing orders in the ground-state structure with the a⁻a⁻c⁺ tilting pattern, whereas it vanishes in the antiferromagnetic configurations. The ground state of all superlattices is half-metallic ...
Latest version: v1
Publication date: May 23, 2024
Alfredo Fiorentino,
Enrico Drigo,
Stefano Baroni,
Paolo Pegolo
- The time-honored Allen-Feldman theory of heat transport in glasses is generally assumed to predict a finite value for the thermal conductivity, even if it neglects the anharmonic broadening of vibrational normal modes. We demonstrate that the harmonic approximation predicts that the bulk lattice thermal conductivity of harmonic solids inevitably diverges at any temperature, irrespective of configurational disorder, and that its ability to represent the heat-transport properties observed experimentally in most glasses is implicitly due to finite-size effects. Our theoretical analysis is thoroughly benchmarked against careful numerical simulations. Our findings thus reveal that a proper account of anharmonic effects is indispensable to predict a finite value for the bulk thermal conductivity in any solid material, be it crystalline or glassy. This record contains data and scripts to support the findings of the manuscript and ensure their reproducibility.
Latest version: v1
Publication date: May 23, 2024
Louis Ponet,
Enrico Di Lucente,
Nicola Marzari
- Magnetic materials can display many solutions to the electronic-structure problem, corresponding to different local or global minima of the energy functional. In Hartree-Fock or density-functional theory different single-determinant solutions lead to different magnetizations, ionic oxidation states, hybridizations, and inter-site magnetic couplings. The vast majority of these states can be fingerprinted through their projection on the atomic orbitals of the magnetic ions. We have devised an approach that provides an effective control over these occupation matrices, allowing us to systematically explore the landscape of the potential energy surface. We showcase the emergence of a complex zoology of self-consistent states; even more so when semi-local density-functional theory is augmented - and typically made more accurate - by Hubbard corrections. Such extensive explorations allow to robustly identify the ground state of magnetic systems, and to assess the accuracy (or not) of current functionals and approximations
Latest version: v1
Publication date: May 23, 2024
Chenxiao Zhao,
Carlo A. Pignedoli,
Dayanni D. Bhagwandin,
Wangwei Xu,
Pascal Rufieux,
Roman Fasel,
Yves Rubin
- Hopf et al. first reported the high-temperature 6π-electrocyclization of cis-hexa-1,3-diene-5-yne to benzene in 1969. Subsequent studies using this cyclization have been limited by its very high reaction barrier. Here, we show that the reaction barrier for two model systems, (E)-1,3,4,6-tetraphenyl-3-hexen-1,5-diyne (1a) and (E)-3,4-bis(4-iodophenyl)-1,6-diphenyl-3-hexen-1,5-diyne 1b, is decreased by nearly half on a Au(111) surface. In recent work, we have used scanning tunneling microscopy (STM) and non-contact atomic force microscopy (nc-AFM) to monitor the Hopf cyclization of enediynes 1a,b on Au(111). Enediyne 1a undergoes two sequential, quantitative Hopf cyclizations, first to naphthalene derivative 2, and finally to chrysene 3. Density functional theory (DFT) calculations reveal that a gold atom from the Au(111) surface is involved in all steps of this reaction, and that it is crucial to lowering the reaction barrier. Our findings have important implications for the ...
Latest version: v1
Publication date: May 21, 2024
Amogh Kinikar,
Thorsten G. Englmann,
Marco Di Giovannantonio,
Nicolò Bassi,
Feifei Xiang,
Samuel Stolz,
Roland Widmer,
Gabriela Borin Barin,
Elia Turco,
Néstor Merino Díez,
Kristjan Eimre,
Andres Ortega-Guerrero,
Xinliang Feng,
Oliver Gröning,
Carlo Antonio Pignedoli,
Roman Fasel,
Pascal Ruffieux
- In this record we provide the data to support our recent finding on the intercalation of gold chloride underneath atomically precise graphene nanoribbons (GNRs). GNRs have a wide range of electronic properties that depend sensitively on their chemical structure. Several types of GNRs have been synthesized on metal surfaces through selective surface-catalyzed reactions. The resulting GNRs are adsorbed on the metal surface, which may lead to hybridization between the GNR orbitals and those of the substrate. This makes investigation of the intrinsic electronic properties of GNRs more difficult, and also rules out capacitive gating. In the manuscript where the data presented here is discussed, we demonstrate the formation of a dielectric gold chloride adlayer that can intercalate underneath GNRs on the Au(111) surface. The intercalated gold chloride adlayer electronically decouples the GNRs from the metal and leads to a substantial hole doping of the GNRs. Our results introduce an ...
Latest version: v1
Publication date: May 16, 2024
Simon K. Steensen,
Monika Vogler,
Francisco Fernando Ramirez,
Leon Merker,
Jonas Busk,
Johan M. Carlsson,
Laura Hannemose Rieger,
Bojing Zhang,
Francois Liot,
Giovanni Pizzi,
Felix Hanke,
Eibar Flores,
Hamidreza Hajiyani,
Stefan Fuchs,
Alexey Sanin,
Miran Gaberšček,
Ivano E. Castelli,
Simon Clark,
Tejs Vegge,
Arghya Bhowmik,
Helge S. Stein
- This study investigates an electrolyte system composed of lithium hexafluorophosphate (LiPF6), ethylene carbonate (EC) and ethyl methyl carbonate (EMC). For the assembly of full cells, electrodes based on graphite and lithium nickel dioxide (LNO) are used. This work provides insight into the similarity of formulations of an electrolyte optimized for maximum conductivity and another one optimized for maximum cycle life are expected to be in this chemical system. The goal is to assess whether it is promising to target research efforts on finding an electrolyte formulation within this chemical space which can fulfill both requirements.
A campaign utilizing the latest version of FINALES is designed to determine conductivity values and predict end of life for various electrolyte formulations containing the aforementioned chemicals. The campaigns were able to reproducibly identify regions of high ionic conductivity of the aforementioned chemical composition. The ML methodology applied ...
Latest version: v1
Publication date: May 14, 2024
Yann Lorris Müller,
Anirudh Raju Natarajan
- Materials for high-temperature environments are actively being investigated for deployment in aerospace and nuclear applications. This study uses computational approaches to unravel the crystallography, and thermodynamics of a promising class of refractory alloys containing aluminum. Accurate first-principles calculations, cluster expansion models, and statistical mechanics techniques are employed to rigorously analyze precipitation in a prototypical senary Al-Nb-Ta-Ti-V-Zr alloy. Finite-temperature calculations reveal a strong tendency for aluminum to segregate to a single sublattice at elevated temperatures. Precipitate and matrix compositions computed with our ab-initio model are in excellent agreement with previous experimental measurements (Soni et al., 2020). Surprisingly, conventional B2-like orderings are found to be both thermodynamically and mechanically unstable in this alloy system. Complex anti-site defects are essential to forming a stable ordered precipitate. Our ...
Latest version: v1
Publication date: May 14, 2024
Enrico Drigo,
Stefano Baroni,
Paolo Pegolo
- We propose a novel approach to evaluating the ionic Seebeck coefficient in electrolytes from relatively short equilibrium molecular dynamics simulations, based on the Green-Kubo theory of linear response and Bayesian regression analysis. By exploiting the probability distribution of the off-diagonal elements of a Wishart matrix, we develop a consistent and unbiased estimator for the Seebeck coefficient, whose statistical uncertainty can be arbitrarily reduced in the long-time limit. We assess the efficacy of our method by benchmarking it against extensive equilibrium molecular dynamics simulations conducted on molten CsF using empirical force fields. We then employ this procedure to calculate the Seebeck coefficient of molten NaCl, KCl and LiCl using neural network force fields trained on ab initio data over a range of pressure-temperature conditions.
Latest version: v1
Publication date: May 13, 2024
Moloud Kaviani,
Chiara Ricca,
Ulrich Aschauer
- Super-exchange most often leads to antiferromagnetism in transition-metal perovskite oxides, yet ferromagnetism or ferrimagnetism would be preferred for many applications, for example in data storage. While alloying, epitaxial strain and defects were shown to lead to ferromagnetism, engineering this magnetic order remains a challenge. We propose, based on density functional theory calculations, a novel route to defect-engineer ferrimagnetism, which is based on preferential displacements of oxygen vacancies due to finite temperature vibrations. This mechanism has an unusual temperature dependence, as it is absent at 0K, strengthens with increasing temperature before vanishing once oxygen vacancies disorder, giving it a unique experimentally detectable signature.
Latest version: v1
Publication date: May 13, 2024
Yusen Su,
Andy Berbille,
Xiao-Fen Li,
Jinyang Zhang,
MohammadJavad PourhosseiniAsl,
Huifan Li,
Zhanqi Liu,
Shunning Li,
Jian-Bo Liu,
Laipan Zhu,
Zhong Lin Wang
- Contact-Electro-Catalysis is an emerging catalytic principle that takes advantage of exchanges of electrons occurring through contact electrification events at solid-liquid interfaces to initiate or drive the catalysis of redox reactions. In this publication, the authors have proven the ability of various polymer insulators to catalyze the reduction of a wide variety of metal ions in aqueous solution, in both aerobic and anaerobic conditions. This property of the dielectric polymers was employed to design a 1-step method to selectively extract gold from e-waste leachates. In anaerobic conditions, the rate of the reactions increase due to the absence of competition form oxygen for the electrons. The influence of metal ions in solution on the distance between O₂ and the polymer chain of polytetrafluoroethylene was evaluated, as well as the resulting adsorption energy. The effect of tacticity on the ability of polymers such as PP to perform the contact-electro-catalytic reduction of ...
Latest version: v1
Publication date: May 08, 2024
Manura Liyanage,
David Reith,
Volker Eyert,
W. A. Curtin
- The introduction of Hydrogen (H) into Zirconium (Zr) influences many mechanical properties, especially due to low H solubility and easy formation of Zirconium hydride phases. Understanding the various effects of H requires studies with atomistic resolution but at scales that incorporate defects such as cracks, interfaces, and dislocations. Such studies thus demand accurate interatomic potentials. Here, a neural network potential (NNP) for the Zr-H system is developed within the Behler-Parrinello framework. The Zr-H NNP retains the accuracy of a recent NNP for hcp Zr and exhibits excellent agreement with first-principles density functional theory (DFT) for (i) H interstitials and their diffusion in hcp Zr, (ii) formation energies, elastic constants, and surface energies of relevant Zr hydrides, and (iii) energetics of a common Zr/Zr-H interface. The Zr-H NNP shows physical behavior for many different crack orientations in the most-stable ε-hydride and structures and reasonable ...
Latest version: v1
Publication date: May 03, 2024
Rui Zeng,
Ming Zhang,
Xiaodong Wang,
Lei Zhu,
Bonan Hao,
Wenkai Zhong,
Guanqing Zhou,
Jiawei Deng,
Senke Tan,
Jiaxing Zhuang,
Fei Han,
Anyang Zhang,
Zichun Zhou,
Xiaonan Xue,
Shengjie Xu,
Jinqiu Xu,
Yahui Liu,
Hao Lu,
Xuefei Wu,
Cheng Wang,
Zachary Fink,
Thomas P. Russell,
Hao Jing,
Yongming Zhang,
Zhishan Bo,
Feng Liu
- Nonfused ring electron acceptors (NFREAs) are interesting n-type near infrared (NIR) photoactive semiconductors with strong molecular absorption and easy synthetic route. However, the low backbone planarity and bulky substitution make NFREA less crystalline, which significantly retards charge transport and the formation of bicontinuous morphology in organic photovoltaic device. Donor and acceptor solubility in different solvents is studied, and the created solubility hysteresis can induce the formation of the highly crystalline donor polymer fibril to purify the NFREA phase, thus a better bicontinuous morphology with improved crystallinity. Based on these results, a general solubility hysteresis sequential condensation (SHSC) thin film fabrication methodology is established to produce highly uniform and smooth photoactive layer. The well-defined interpenetrating network morphology afforded a record efficiency of 19.02%, which is ~22% improvement comparing to conventional device ...
Latest version: v2
Publication date: Apr 29, 2024
Stefano Battaglia,
Max Rossmannek,
Vladimir V. Rybkin,
Ivano Tavernelli,
Juerg Hutter
- We developed a general framework for hybrid quantum-classical computing of molecular and periodic embedding calculations based on an orbital space separation of the fragment and environment degrees of freedom. We show its potential by presenting a specific implementation of periodic range-separated DFT coupled to a quantum circuit ansatz, whereby the variational quantum eigensolver and the quantum equation-of-motion approach are used to obtain the low-lying spectrum of the embedded fragment Hamiltonian.
Application of this scheme to study strongly correlated molecular systems and localized electronic states in materials is showcased through the accurate prediction of the optical properties for the neutral oxygen vacancy in magnesium oxide (MgO). Despite some discrepancies in absorption predictions, the method demonstrates competitive performance with state-of-the-art ab initio approaches, particularly evidenced by the accurate prediction of the photoluminescence emission peak.
Latest version: v1
Publication date: Apr 26, 2024
Leonid Kahle,
Aris Marcolongo,
Nicola Marzari
- We present a computational screening of experimental structural repositories for fast Li-ion conductors, with the goal of finding new candidate materials for application as solid-state electrolytes in next-generation batteries. We start from ~1400 unique Li-containing materials, of which ~900 are insulators at the level of density-functional theory. For those, we calculate the diffusion coefficient in a highly automated fashion, using extensive molecular dynamics simulations on a potential energy surface (the recently published pinball model) fitted on first-principles forces. The ~130 most promising candidates are studied with full first-principles molecular dynamics, first at high temperature and then more extensively for the 78 most promising candidates. The results of the first-principles simulations of the candidate solid-state electrolytes found are discussed in detail.
Update April 2024:
Files are added that facilitate the Materials Cloud Archive OPTIMADE service to serve ...
Latest version: v2
Publication date: Apr 26, 2024
Han-Pu Liang,
Chuan-Nan Li,
Ran Zhou,
Xun Xu,
Xie Zhang,
Jingxiu Yang,
Su-Huai Wei
- The crystal structure of a material is essentially determined by the nature of its chemical bonding. Consequently, the atomic coordination intimately correlates with the degree of ionicity or covalency of the material. Based on this principle, materials with similar chemical compositions can be successfully categorized into different coordination groups. However, counterexamples recently emerged in complex ternary compounds. For instance, strongly covalent IB-IIIA-VIA₂ compounds, such as AgInS₂, prefer tetrahedrally coordinated structure (TCS), while strongly ionic IA-VA-VIA₂ compounds, such as NaBiS₂, would favor octahedrally coordinated structure (OCS). One naturally expects that IB-VA-VIA₂ compounds with intermediate ionicity or covalency, such as AgBiS₂, should then have a mix-coordinated structure (MCS) consisting of covalent AgS₄ tetrahedra and ionic BiS₆ octahedra. Surprisingly, only OCS was observed experimentally for AgBiS₂. To resolve this puzzle, we perform ...
Latest version: v1
Publication date: Apr 24, 2024
Michele Kotiuga,
Karin M. Rabe
- This work explores hydrogen-doped samarium nickelate from first-principles calculations. At a concentration of 1/4 hydrogen per formula unit we find a number of polar states due to the presence of the interstitial hydrogen. Physically, the polarization of the material arises from the localization of the hydrogen's valence electron on a nearby nickel-oxygen octahedron leading to a local dipole. Due to the inherent tilt pattern present in samarium nickelate, a perovskite with an a-a-c+ tilt pattern, there is an insurmountable energy barrier to switch a given polar state the structure related by inversion symmetry. Instead, we use an in-plane epitaxial constraint to tune the total energy of two structures to be equal. These two structures, unrelated by a cell-symmetry operation, have similar a similar position of the interstitial hydrogen atom, but the valence electron localizes on a different nickel-oxygen octahedron leading to different polarizations. We find that there is a ...
Latest version: v1
Publication date: Apr 23, 2024
Haiyuan Wang,
Runhai Ouyang,
Wei Chen,
Alfredo Pasquarello
- Extensive machine-learning assisted research has been dedicated to predicting band gaps for perovskites, driven by their immense potential in photovoltaics. Yet, the effectiveness is often hampered by the lack of high-quality band-gap datasets, particularly for perovskites involving d orbitals. In this work, we consistently calculate a large dataset of band gaps with a high level of accuracy, which is rigorously validated by experimental and state-of-the-art GW band gaps. Leveraging this achievement, our machine-learning derived descriptor exhibits exceptional universality and robustness, proving effectiveness not only for single and double, halide and oxide perovskites regardless of the underlying atomic structures, but also for hybrid organic-inorganic perovskites. With this approach, we comprehensively explore up to 15,659 materials, unveiling 14 unreported lead-free perovskites with suitable band gaps for photovoltaics. Notably, MASnBr₃, FA₂SnGeBr₆, MA₂AuAuBr₆, FA₂AuAuBr₆, ...
Latest version: v1
Publication date: Apr 23, 2024
Julien Leuenberger,
Kristiāns Čerņevičs,
Oleg V. Yazyev
- As Moore's law approaches its fundamental limits, the development of nanoelectronic devices using low-dimension materials has become a promising avenue for further miniaturization and performance improvements. Among the various novel materials, graphene nanoribbons (GNRs) have emerged as particularly attractive candidates due to their unique electronic properties, opening up a whole new nanoelectronics paradigm consisting of circuits made entirely of graphene. However, due to the technical constraints that naturally arise when working on a two-dimensional plane, the design of efficient nanoelectronic components with a minimal spatial footprint remains a significant challenge. This dataset provides a comprehensive dataset of over 1'500 armchair GNR junctions or various sizes and shapes.
Latest version: v1
Publication date: Apr 18, 2024
Daniele Lanzoni,
Fabrizio Rovaris,
Luis Martín-Encinar,
Andrea Fantasia,
Roberto Bergamaschini,
Francesco Montalenti
- Machine Learning (ML) can be conveniently applied to continuum materials simulations, allowing for the investigation of larger systems and longer timescales, pushing the limits of tractable systems. Here we provide a comprehensive dataset of strained Ge films on Si and their corresponding strain states, which can be used to train a ML model capable of such acceleration. Approximately 80k 2D cases are included, reporting the profiles h(x) and the corresponding elastic energy densities and strain fields. The profiles are conveniently sampled using Perlin-noise and pure-sine waves. A 100nm-large computational domain is considered. The mechanical equilibrium problem is solved using Finite Element Method (FEM). Ge is modeled as an isotropic material and an eigenstrain of 3.99% is used, as in Ge/Si(001).
The database has been exploited for training a (fully) Convolutional Neural Network (CNN) which maps the free surface profile h(x) to the corresponding energy density. If plugged into ...
Latest version: v1
Publication date: Apr 18, 2024
Shubhajit Das,
Ruben Laplaza,
J. Terence Blaskovits,
Clemence Corminboeuf
- Frustrated Lewis pairs (FLPs), featuring reactive combinations of Lewis acids and Lewis bases, have been utilized for myriad metal-free homogeneous catalytic processes. Immobilizing the active Lewis sites to a solid support, especially to porous scaffolds, has shown great potential to ameliorate FLP catalysis by circumventing some of its inherent drawbacks, such as product separation and catalyst recyclability. Nevertheless, designing immobilized Lewis pair active sites (LPASs) is challenging due to the requirement of placing the donor and acceptor centers in appropriate geometric arrangements while maintaining the necessary chemical environment to perform catalysis, and clear design rules have not yet been established. In this work, we formulate simple guidelines to build highly active LPASs for direct catalytic hydrogenation of CO₂ through a large-scale screening of a diverse library of 25,000 immobilized FLPs.
The library is built by introducing boron-containing acidic sites ...
Latest version: v3
Publication date: Apr 17, 2024
Davide Tisi,
Federico Grasselli,
Lorenzo Gigli,
Michele Ceriotti
- The vast amount of computational studies on electrical conduction in solid-state electrolytes is not mirrored by comparable efforts addressing thermal conduction, which has been scarcely investigated despite its relevance to thermal management and (over)heating of batteries. The reason for this lies in the complexity of the calculations: on one hand, the diffusion of ionic charge carriers makes lattice methods formally unsuitable due to the lack of equilibrium atomic positions needed for normal-mode expansion. On the other hand, the prohibitive cost of large-scale molecular dynamics (MD) simulations of heat transport in large systems at ab initio levels has hindered the use of MD-based methods. In this work, we leverage recently developed machine-learning potentials targeting different ab initio functionals (PBEsol, r2SCAN, PBE0) and a state-of-the-art formulation of the Green-Kubo theory of heat transport in multicomponent systems to compute the thermal conductivity of a ...
Latest version: v1
Publication date: Apr 16, 2024
Yixiu Luo,
Juan Wang,
Luchao Sun,
Jingyang Wang
- Understanding the phononic origin of the infrared dielectric properties of yttria (Y₂O₃) and other rare-earth sesquioxides (RE₂O₃) is a fundamental task in the search of appropriate RE₂O₃ materials that serve particular infrared optical applications. We herein investigate the infrared dielectric properties of RE₂O₃ (RE = Y, Gd, Ho, Lu) using DFT-based phonon calculations and Lorentz oscillator model. The abundant IR-active optical phonon modes that are available for effective absorption of photons result in high reflectance of RE₂O₃, among which four IR-active modes originated from large distortions of REO₆ octahedra are found to contribute dominantly to the phonon dielectric constants. Particularly, the present calculation method by considering one-phonon absorption process is demonstrated with good reliability in predicting the infrared dielectric parameters of RE₂O₃ at the far-infrared as well as the vicinity of mid-infrared region, and the potential cutoff frequency/wavelength ...
Latest version: v1
Publication date: Apr 15, 2024
Andrea Fantasia,
F. Rovaris,
O. Abou El Kheir,
A. Marzegalli,
D. Lanzoni,
L. Pessina,
P. Xiao,
C. Zhou,
L. Li,
G. Henkelman,
E. Scalise,
F. Montalenti
- In a recent preprint, entitled: "Development of a machine learning interatomic potential for exploring pressure-dependent kinetics of phase transitions in Germanium", we presented a novel Neural-Network (NN) interatomic potential for Ge. We recall that Ge phases different from the cubic-diamond one are of particular interest for applications. Hexagonal Ge, for instance, displays superior optical properties. It is therefore important to investigate how, exploiting pressure, Ge can be transformed into different allotropes. In order to build a potential tackling kinetics of pressure-induced phase transformations, several kinetic paths (mainly sampled using the solid-state Nudged Elastic Band method) were added to the database, following a suitable active-learning procedure. Energies, forces, and stressed relative to the various configurations were computed ab initio using VASP with the PBE functional. The NN potential was trained using the Deep Potential Molecular Dynamic package ...
Latest version: v1
Publication date: Apr 11, 2024
Lorenzo Gigli,
Alexander Goscinski,
Michele Ceriotti,
Gareth A. Tribello
- The accurate description of the structural and thermodynamic properties of ferroelectrics has been one of the most remarkable achievements of Density Functional Theory (DFT). However, running large simulation cells with DFT is computationally demanding, while simulations of small cells are often plagued with non-physical effects that are a consequence of the system's finite size. Therefore, one is often forced to use empirical models that describe the physics of the material in terms of effective interaction terms, that are fitted using the results from DFT, to perform simulations that do not suffer from finite size effects. In this study we use a machine-learning (ML) potential trained on DFT, in combination with accelerated sampling techniques, to converge the thermodynamic properties of Barium Titanate (BTO) with first-principles accuracy and a full atomistic description. Our results indicate that the predicted Curie temperature depends strongly on the choice of DFT functional ...
Latest version: v1
Publication date: Apr 10, 2024
Eric Macke,
Iurii Timrov,
Nicola Marzari,
Lucio Colombi Ciacchi
- We present an orbital-resolved extension of the Hubbard U correction to density-functional theory (DFT). Compared to the conventional shell-averaged approach, the prediction of energetic, electronic and structural properties is strongly improved, particularly for compounds characterized by both localized and hybridized states in the Hubbard manifold. The numerical values of all Hubbard parameters are readily obtained from linear-response calculations. The relevance of this more refined approach is showcased by its application to bulk solids pyrite (FeS₂) and pyrolusite (β-MnO₂), as well as to six Fe(II) molecular complexes. Our findings indicate that a careful definition of Hubbard manifolds is indispensable for extending the applicability of DFT+U beyond its current boundaries. The present orbital-resolved scheme aims to provide a computationally undemanding yet accurate tool for electronic structure calculations of charge-transfer insulators, transition-metal (TM) complexes and ...
Latest version: v1
Publication date: Apr 08, 2024
Jinzhen Huang,
Adam H. Clark,
Natasha Natasha Hales,
Camelia Nicoleta Borca,
Thomas Huthwelker,
Thomas J. Schmidt,
Emiliana Fabbri
- Doping and compositing are two universal design strategies used to engineer the electronic state of a material and mitigate its disadvantages. These two strategies have been extensively applied to the design of efficient electrocatalysts for water splitting. Using cobalt oxide (CoO) as a model catalyst, we prove that the oxygen evolution reaction (OER) performance could be progressively improved, first by Fe-doping to form Fe-CoO solid solution, and further by the addition of CeO2 to produce a Fe-CoO/CeO2 composite. X-ray adsorption spectroscopy (XAS) reveals that distinct electronic interactions are induced by the processes of doping and compositing. Fe-doping of CoO can break down the structural symmetry in the pristine material, changing the electronic structure of both Co and O species at the surface and decreasing the flat-band potential (Vfb). In comparison, subsequent compositing of Fe-CoO with CeO2 induces negligible electronic changes in the as-synthesized Fe-CoO (as seen ...
Latest version: v1
Publication date: Mar 26, 2024
Lorenzo Bastonero,
Nicola Marzari
- Infrared and Raman spectroscopies are ubiquitous techniques employed in many experimental laboratories, thanks to their fast and non-destructive nature able to capture materials' features as spectroscopic fingerprints. Nevertheless, these measurements frequently need theoretical support in order to unambiguously decipher and assign complex spectra. Linear-response theory provides an effective way to obtain the higher-order derivatives needed, but its applicability to modern exchange-correlation functionals remains limited. Here, we devise an automated, open-source, user-friendly approach based on ground-state density-functional theory and the electric enthalpy functional to allow seamless calculations of first-principles infrared and Raman spectra. By employing a finite-displacement and finite-field approach, we allow for the use of any functional, as well as an efficient treatment of large low-symmetry structures. Additionally, we propose a simple scheme for efficiently sampling ...
Latest version: v2
Publication date: Mar 22, 2024
Cameron Owen,
Steven Torrisi,
Yu Xie,
Simon Batzner,
Kyle Bystrom,
Jennifer Coulter,
Albert Musaelian,
Lixin Sun,
Boris Kozinsky
- This work examines challenges associated with the accuracy of machine-learned force fields (MLFFs) for bulk solid and liquid phases of d-block elements. In exhaustive detail, we contrast the performance of force, energy, and stress predictions across the transition metals for two leading MLFF models: a kernel-based atomic cluster expansion method implemented using sparse Gaussian processes (FLARE), and an equivariant message-passing neural network (NequIP). Early transition metals present higher relative errors and are more difficult to learn relative to late platinum- and coinage-group elements, and this trend persists across model architectures. Trends in complexity of interatomic interactions for different metals are revealed via comparison of the performance of representations with different many-body order and angular resolution. Using arguments based on perturbation theory on the occupied and unoccupied d states near the Fermi level, we determine that the large, sharp d ...
Latest version: v1
Publication date: Mar 22, 2024
Stefano Falletta,
Alfredo Pasquarello
- Through the use of the piecewise-linearity condition of the total energy, we correct the self-interaction for the study of polarons by constructing nonempirical functionals at the semilocal level of theory. We consider two functionals, the γDFT and the μDFT functionals, both of which are based on the addition of a weak local potential to the semilocal Hamiltonian to enforce the piecewise-linearity condition. We show that the resulting polaron properties are in good agreement with reference hybrid functional calculations. This supports the use of semilocal functionals for calculating polaron properties.
Latest version: v1
Publication date: Mar 19, 2024
Pengjie Shi,
Shizhe Feng,
Zhiping Xu
- A high-fidelity neural network-based force field (NN-F³) is developed to cover the space of strain states up to material failure and the non-equilibrium, intermediate nature of fracture. Simulations of fracture in 2D crystals using NN-F³ reveal spatial complexities from lattice-scale kinks to sample-scale patterns. We find that the fracture resistance cannot be captured by the energy densities of relaxed edges as used in the literature. Instead, the fracture patterns, critical stress intensity factors at the kinks, and energy densities of edges in the intermediate, unrelaxed states offer reasonable measures for the fracture toughness and its anisotropy.
Latest version: v4
Publication date: Mar 12, 2024
Xinhang Xu,
Chongchong Qi,
Xabier M. Aretxabaleta,
Chundi Ma,
Dino Spagnoli,
Hegoi Manzano
- Cement hydration is crucial for the strength development of cement-based materials; however, the mechanism that underlies this complex reaction remains poorly understood at the molecular level. An in-depth understanding of cement hydration is required for the development of environmentally friendly cement and consequently the reduction of carbon emissions in the cement industry. Here, we use molecular dynamics simulations with a reactive force field to investigate the initial hydration processes of tricalcium silicate (C₃S) and dicalcium silicate (C₂S) up to 40 ns. Our simulations provide theoretical support for the rapid initial hydration of C₃S compared to C₂S at the molecular level. The dissolution pathways of calcium ions in C₃S and C₂S are revealed, showing that, two dissolution processes are required for the complete dissolution of calcium ions in C₃S. Our findings promote the understanding of the calcium dissolution stage and serve as a valuable reference for the investigation of the initial cement hydration.
Latest version: v1
Publication date: Mar 11, 2024
Shilin Mao,
Yuting Cao,
Wei Chen,
Dongke Sun
- In this paper, we proposed a model coupling the lattice Boltzmann and the phase field methods with anisotropic effects is proposed, which is used to numerically describe the growth and movement of dendrites in rapid solidification of alloys. The model was applied to investigate the effects of dendrite movement and interfacial non-equilibrium on evolution of dendritic patterns for Si-9.0at%As and the CET for Al-3.0wt%Cu alloys. Both the growth and remelt processes of isolated dendrites are studied, and the result reveals the remelting influences on dendrite growth and solute micro-segregation in the condition of directional solidification. This dataset contains the underlying data for the above. This work demonstrates that the proposed model has a wide range of applicability and great potential to simulate the microstructure evolution with various solidification conditions.
Latest version: v1
Publication date: Mar 06, 2024
Arslan Mazitov,
Maximilian A. Springer,
Nataliya Lopanitsyna,
Guillaume Fraux,
Sandip De,
Michele Ceriotti
- High-entropy alloys (HEAs), containing several metallic elements in near-equimolar proportions, have long been of interest for their unique mechanical properties. More recently, they have emerged as a promising platform for the development of novel heterogeneous catalysts, because of the large design space, and the synergistic effects between their components. In this work we use a machine-learning potential that can model simultaneously up to 25 transition metals (d-block transition metals, excluding Tc, Cd, Re, Os and Hg) to study the tendency of different elements to segregate at the surface of a HEA.
In this record, we provide a dataset HEA25S, containing 10000 bulk HEA structures (Dataset O), 2640 HEA surface slabs (Dataset A), together with 1000 bulk and 1000 surface slabs snapshots from the molecular dynamics (MD) runs (Datasets B and C), and 500 MD snapshots of the 25 elements Cantor-style alloy surface slabs.
We also provide the HEA25-4-NN and HEA25S-4-NN final models, ...
Latest version: v2
Publication date: Mar 04, 2024
Yong Hu,
Junzhang Ma,
Yinxiang Li,
Yuxiao Jiang,
Dariusz Jakub Gawryluk,
Tianchen Hu,
Jérémie Teyssier,
Volodymyr Multian,
Zhouyi Yin,
Shuxiang Xu,
Soohyeon Shin,
Igor Plokhikh,
Xinloong Han,
Nicholas C. Plumb,
Yang Liu,
Jia-Xin Yin,
Zurab Guguchia,
Yue Zhao,
Andreas P. Schnyder,
Xianxin Wu,
Ekaterina Pomjakushina,
M. Zahid Hasan,
Nanlin Wang,
Ming Shi
- Charge density wave (CDW) orders in vanadium-based kagome metals have recently received tremendous attention, yet their origin remains a topic of debate. The discovery of ScV₆Sn₆, a bilayer kagome metal featuring an intriguing √3 x √3 x 3 CDW order, offers a novel platform to explore the underlying mechanism behind the unconventional CDW. Here, we combine high-resolution angle-resolved photoemission spectroscopy, Raman scattering and density functional theory to investigate the electronic structure and phonon modes of ScV₆Sn₆. We identify topologically nontrivial surface states and multiple van Hove singularities (VHSs) in the vicinity of the Fermi level, with one VHS aligning with the in-plane component of the CDW vector near the K ̅ point. Additionally, Raman measurements indicate a strong electron-phonon coupling, as evidenced by a two-phonon mode and new emergent modes. Our findings highlight the fundamental role of lattice degrees of freedom in promoting the CDW in ScV₆Sn₆.
Latest version: v1
Publication date: Mar 03, 2024
Lorenzo Gigli,
Davide Tisi,
Federico Grasselli,
Michele Ceriotti
- Lithium ortho-thiophosphate (Li₃PS₄) has emerged as a promising candidate for solid-state-electrolyte batteries, thanks to its highly conductive phases, cheap components, and large electrochemical stability range. Nonetheless, the microscopic mechanisms of Li-ion transport in Li₃PS₄ are far to be fully understood, the role of PS₄ dynamics in charge transport still being controversial. We build machine learning potentials targeting state-of-the-art DFT references (PBEsol, r²SCAN, and PBE0) to tackle this problem in all known phases of Li₃PS₄ (α, β and γ), for large system sizes and timescales. We discuss the physical origin of the observed superionic behavior of Li₃PS₄: the activation of PS₄ flipping drives a structural transition to a highly conductive phase, characterized by an increase of Li-site availability and by a drastic reduction in the activation energy of Li-ion diffusion. We also rule out any paddle-wheel effects of PS₄ tetrahedra in the superionic phases–previously ...
Latest version: v2
Publication date: Mar 01, 2024
Brenda S. Ferrari,
Matteo Manica,
Ronaldo Giro,
Teodoro Laino,
Mathias B. Steiner
- Polymers are candidate materials for a wide range of sustainability applications such as carbon capture and energy storage. However, computational polymer discovery lacks automated analysis of reaction pathways and stability assessment through retro-synthesis. Here, we report the first extension of transformer-based language models to polymerization reactions for both forward and retrosynthesis tasks. We curated a polymerization dataset for vinyl polymers covering reactions and retrosynthesis for representative homo-polymers and co-polymers. Overall, we report a forward model accuracy of 80% and a backward model accuracy of 60%. We further analyse the model performance on a set of case studies by providing polymerization and retro-synthesis examples and evaluating the model’s predictions quality from a materials science perspective.
Latest version: v2
Publication date: Feb 29, 2024
Cameron Owen,
Yu Xie,
Anders Johansson,
Lixin Sun,
Boris Kozinsky
- Metal surfaces have long been known to reconstruct, significantly influencing their structural and catalytic properties. Many key mechanistic aspects of these subtle transformations remain poorly understood due to limitations of previous simulation approaches. Using active learning of Bayesian machine-learned force fields trained from ab initio calculations, we enable large-scale molecular dynamics simulations to describe the thermodynamics and time evolution of the low-index mesoscopic surface reconstructions of Au (e.g., the Au(111)-`Herringbone,' Au(110)-(1x2)-`Missing-Row,' and Au(100)-`Quasi-Hexagonal' reconstructions). This capability yields direct atomistic understanding of the dynamic emergence of these surface states from their initial facets, providing previously inaccessible information such as nucleation kinetics and a complete mechanistic interpretation of reconstruction under the effects of strain and local deviations from the original stoichiometry. We successfully ...
Latest version: v1
Publication date: Feb 29, 2024
Peter Kraus,
Edan Bainglass,
Francisco F. Ramirez,
Enea Svaluto-Ferro,
Loris Ercole,
Benjamin Kunz,
Sebastiaan P. Huber,
Nukorn Plainpan,
Nicola Marzari,
Corsin Battaglia,
Giovanni Pizzi
- Compliance with good research data management practices means trust in the integrity of the data, and it is achievable by a full control of the data gathering process. In this work, we demonstrate tooling which bridges these two aspects, and illustrate its use in a case study of automated battery cycling. We successfully interface off-the-shelf battery cycling hardware with the computational workflow management software AiiDA, allowing us to control experiments, while ensuring trust in the data by tracking its provenance. We design user interfaces compatible with this tooling, which span the inventory, experiment design, and result analysis stages. Other features, including monitoring of workflows and import of externally generated and legacy data are also implemented. Finally, the full software stack required for this work is made available in a set of open-source packages.
Latest version: v2
Publication date: Feb 29, 2024
Omar Abou El Kheir,
Luigi Bonati,
Michele Parrinello,
Marco Bernasconi
- The phase change compound Ge₂Sb₂Te₅ (GST225) is exploited in advanced non-volatile electronic memories and in neuromorphic devices which both rely on a fast and reversible transition between the crystalline and amorphous phases induced by Joule heating. The crystallization kinetics of GST225 is a key functional feature for the operation of these devices. We report here on the development of a machine-learned interatomic potential for GST225 that allowed us to perform large scale molecular dynamics simulations (over 10000 atoms for over 100 ns) to uncover the details of the crystallization kinetics in a wide range of temperatures of interest for the programming of the devices. The potential is obtained by fitting with a deep neural network (NN) scheme a large quantum-mechanical database generated within Density Functional Theory. The availability of a highly efficient and yet highly accurate NN potential opens the possibility to simulate phase change materials at the length and time scales of the real devices.
Latest version: v2
Publication date: Feb 22, 2024
Maximilian E. Merkel,
Aria Mansouri Tehrani,
Claude Ederer
- We investigate the interplay of spin-orbit coupling, electronic correlations, and lattice distortions in the 5d¹ double perovskite Ba₂MgReO₆. Combining density-functional theory (DFT) and dynamical mean-field theory (DMFT), we establish the Mott-insulating character of Ba₂MgReO₆ in both its cubic and tetragonal paramagnetic phases. Despite substantial spin-orbit coupling, its impact on the formation of the insulating state is minimal, consistent with theoretical expectations for d¹ systems. We further characterize the electronic properties of the cubic and tetragonal phases by analyzing spectral functions and local occupations in terms of multipole moments centered on the Re sites. Our results confirm the presence of ferroically ordered z² quadrupoles in addition to the antiferroic x²-y²-type order. We compare two equivalent but complementary descriptions in terms of either effective Re-t2g frontier orbitals or more localized atomic-like Re-d and O-p orbitals. The former maps ...
Latest version: v1
Publication date: Feb 22, 2024
Edoardo Cignoni,
Divya Suman,
Jigyasa Nigam,
Lorenzo Cupellini,
Benedetta Mennucci,
Michele Ceriotti
- Data-driven techniques are increasingly used to replace electronic-structure calculations of matter. In this context, a relevant question is whether machine learning (ML) should be applied directly to predict the desired properties or be combined explicitly with physically-grounded operations. We present an example of an integrated modeling approach, in which a symmetry-adapted ML model of an effective Hamiltonian is trained to reproduce electronic excitations from a quantum-mechanical calculation. The resulting model can make predictions for molecules that are much larger and more complex than those that it is trained on, and allows for dramatic computational savings by indirectly targeting the outputs of well-converged calculations while using a parameterization corresponding to a minimal atom-centered basis. Our results on a comprehensive dataset of hydrocarbons emphasize the merits of intertwining data-driven techniques with physical approximations, improving the ...
Latest version: v2
Publication date: Feb 20, 2024
Dushko Kuzmanovski,
Jonathan Schmidt,
Nicola A. Spaldin,
Hendrik M. Rønnow,
Gabriel Aeppli,
Alexander V. Balatsky
- Dynamical perturbations modify the states of classical systems in surprising ways and give rise to important applications in science and technology. For example, Floquet engineering exploits the possibility of band formation in the frequency domain when a strong, periodic variation is imposed on parameters such as spring constants. We describe here Kapitza engineering, where a drive field oscillating at a frequency much higher than the characteristic frequencies for the linear response of a system changes the potential energy surface so much that maxima found at equilibrium become local minima, in precise analogy to the celebrated Kapitza pendulum where the unstable inverted configuration, with the mass above rather than below the fulcrum, actually becomes stable. Our starting point is a quantum field theory of the Ginzburg-Devonshire type, suitable for many condensed matter systems, including particularly ferroelectrics and quantum paralectrics such as the common substrate (for ...
Latest version: v1
Publication date: Feb 20, 2024
Chiara Cignarella,
Davide Campi,
Nicola Marzari
- One-dimensional materials have gained much attention in the last decades: from carbon nanotubes to ultrathin nanowires, to few-atom atomic chains, these can all display unique electronic properties and great potential for next-generation applications. Exfoliable bulk materials could naturally provide a source for one-dimensional wires with well defined structure and electronics. Here, we explore a database of one-dimensional materials that could be exfoliated from experimentally known three-dimensional Van-der-Waals compounds, searching metallic wires that are resilient to Peierls distortions and could act as vias or interconnects for future downscaled electronic devices. As the one-dimensional nature makes these wires particularly susceptible to dynamical instabilities, we carefully characterise vibrational properties to identify stable phases and characterize electronic and dynamical properties. Our search identifies several novel and stable wires; notably, we identify what ...
Latest version: v2
Publication date: Feb 15, 2024
Marco Di Giovannantonio,
Zijie Qiu,
Carlo A. Pignedoli,
Sobi Asako,
Pascal Ruffieux,
Klaus Müllen,
Akimitsu Narita,
Roman Fasel
- On-surface synthesis relies on carefully designed molecular precursors that are thermally activated to afford desired, covalently coupled architectures. In a recent publication, we studied the reactions of vinyl groups on poly-para-phenylene and provided a comprehensive description of all the reaction steps taking place on the Au(111) surface under ultrahigh vacuum conditions. We find that vinyl groups successfully cyclize with the phenylene rings in the ortho positions, forming a dimethyl-dihydroindenofluorene as the repeating unit, which can be further dehydrogenated to a dimethylene-dihydroindenofluorene structure. Interestingly, the obtained polymer can be transformed cleanly into thermodynamically stable polybenzo[k]tetraphene at higher temperature, involving a previously elusive pentagon-to-hexagon transformation via ring opening and rearrangement on a metal surface. Our insights into the reaction cascade unveil fundamental chemical processes involving vinyl groups on ...
Latest version: v1
Publication date: Feb 15, 2024
J.N. Graham,
C. Mielke III,
D. Das,
T. Morresi,
V. Ardakani,
A. Suter,
T. Prokscha,
H. Deng,
R. Khasanov,
S. D. Wilson,
A. C. Salinas,
Y. Zhong,
K. Okazaki,
Z. Wang,
M. Z. Hasan,
M. Fisher,
T. Neupert,
J.-X. Yin,
S. Sanna,
H. Luetkens,
Z. Salman,
P. Bonfà,
Z. Guguchia
- The AV₃Sb₅ kagome superconductors series are of intense interest due to their diverse and intricate properties. The breaking of time-reversal symmetry (TRS) in the normal state of these superconductors stands as a significant feature, yet the extent to which this effect can be tuned remains uncertain. Here, we employ a unique low-energy muon spin rotation technique combined with local field numerical analysis to study the TRS breaking response as a function of depth from the surface in single crystals of RbV₃Sb₅ with charge order and Cs(V0.86Ta0.14)₃Sb₅ without charge order. In the bulk (specifically above 30 nm from the sur face) of RbV₃Sb₅, we have detected a notable increase in the internal field width experienced by the muon ensemble. This increase occurs within the charge ordered state. Intriguingly, the muon spin relaxation rate is significantly enhanced near the surface of RbV₃Sb₅ (specifically within a depth range of 30-40 nm from the surface), and ...
Latest version: v1
Publication date: Feb 15, 2024
Kevin Janßen,
Philipp Rüßmann,
Sergej Liberda,
Michael Schleenvoigt,
Xiao Hou,
Abdur Rehman Jalil,
Florian Lentz,
Stefan Trellenkamp,
Benjamin Bennemann,
Erik Zimmermann,
Gregor Mussler,
Peter Schüffelgen,
Claus-Michael Schneider,
Stefan Blügel,
Detlev Grützmacher,
Lukasz Plucinski,
Thomas Schäpers
- With increasing interest in Majorana physics for possible quantum bit applications, a large interest has been developed to understand the properties of the interface between a s-type superconductor and a topological insulator. Up to this point the interface analysis was mainly focused on in-situ prepared Josephson junctions, which consist of two coupled single interfaces or to ex-situ fabricated single interface devices. In our work we utilize a novel fabrication process, combining selective area growth and shadow evaporation which allows the characterization of a single in-situ fabricated Nb/(Bi0.15Sb0.85)2Te3 nano interface. The resulting high interface transparency, is apparent by a zero bias conductance increase by a factor of 1.7. Furthermore, we present a comprehensive differential conductance analysis of our single in-situ interface for various magnetic fields, temperatures and gate voltages. Additionally, density functional ...
Latest version: v3
Publication date: Feb 15, 2024
Alexey Tal,
Thomas Bischoff,
Alfredo Pasquarello
- We demonstrate the importance of addressing the 𝚪 vertex and thus going beyond the GW approximation for achieving the energy levels of liquid water in many- body perturbation theory. In particular, we consider an effective vertex function in both the polarizability and the self-energy, which does not produce any computational overhead compared with the GW approximation. We yield the band gap, the ionization potential, and the electron affinity in good agreement with experiment and with a hybrid functional description. The achieved electronic structure and dielectric screening further lead to a good description of the optical absorption spectrum, as obtained through the solution of the Bethe–Salpeter equation. In particular, the experimental peak position of the exciton is accurately reproduced.
Latest version: v1
Publication date: Feb 14, 2024
Debdipto Acharya,
Omar Abou El Kheir,
Davide Campi,
Marco Bernasconi
- Superlattices made of alternating blocks of the phase change compound Sb₂Te₃ and of TiTe₂ confining layers have been recently proposed for applications in neuromorphic devices. The Sb₂Te₃/TiTe₂ heterostructure allows for a better control of multiple intermediate resistance states and for a lower drift with time of the electrical resistance of the amorphous phase. However, Sb₂Te₃ suffers from a low data retention due to a low crystallization temperature Tx. Substituting Sb₂Te₃ with a phase change compound with a higher Tx, such as GeTe, seems an interesting option in this respect. Nanoconfinement might, however, alters the crystallization kinetics with respect to the bulk. In this work, we investigated the crystallization process of GeTe nanoconfined in geometries mimicking GeTe/TiTe₂ superlattices by means of molecular dynamics simulations with a machine learning potential. The simulations reveal that nanoconfinement induces a mild reduction in the crystal ...
Latest version: v2
Publication date: Feb 12, 2024
