A5084420654- X-ray Diffraction in Crystallography
- Machine Learning in Materials Science
- Crystallography and molecular interactions
- Various Chemistry Research Topics
- Crystallization and Solubility Studies
- Inorganic Chemistry and Materials
- Thermal properties of materials
- Thermal Expansion and Ionic Conductivity
- Catalysis and Oxidation Reactions
- Advanced Thermoelectric Materials and Devices
- Advanced Chemical Physics Studies
- Nuclear Physics and Applications
- Electronic and Structural Properties of Oxides
- Luminescence Properties of Advanced Materials
- Thermal and Kinetic Analysis
- Acoustic Wave Resonator Technologies
- Ultrasonics and Acoustic Wave Propagation
- Thermodynamic and Structural Properties of Metals and Alloys
- Ferroelectric and Piezoelectric Materials
- Computational Drug Discovery Methods
- Inorganic Fluorides and Related Compounds
- Magnesium Oxide Properties and Applications
- Multiferroics and related materials
- Chemical Thermodynamics and Molecular Structure
- Solid-state spectroscopy and crystallography
Federal Institute For Materials Research and Testing
2021-2025
Friedrich Schiller University Jena
2021-2025
UCLouvain
2018-2022
Bluegrass Advanced Materials (United States)
2022
Institute for Condensed Matter Physics of the National Academy of Sciences of Ukraine
2019
Institut des Arts de Diffusion
2019
RWTH Aachen University
2012-2018
Jülich Aachen Research Alliance
2017
FH Aachen
2015-2016
Research Complex at Harwell
1967
Abstract We present an update on recently developed methodology and functionality in the computer program Local Orbital Basis Suite Toward Electronic‐Structure Reconstruction (LOBSTER) for chemical‐bonding analysis periodic systems. LOBSTER is based analytic projection from projector‐augmented wave (PAW) density‐functional theory (DFT) computations (Maintz et al., J. Comput. Chem. 2013 , 34 2557), reconstructing chemical information terms of local, auxiliary atomic orbitals thereby opening...
Machine-learned force fields have transformed the atomistic modelling of materials by enabling simulations ab initio quality on unprecedented time and length scales. However, they are currently limited by: (i) significant computational human effort that must go into development validation potentials for each particular system interest; (ii) a general lack transferability from one chemical to next. Here, using state-of-the-art MACE architecture we introduce single general-purpose ML model,...
The Pauling rules have been used for decades to rationalise the crystal structures of ionic compounds. Despite their importance, there has no statistical assessment performances these five empirical so far. Here, we rigorously and automatically test all a large data set around 5000 known oxides. We discuss each rule separately, stressing limits range application in terms chemistries structures. conclude that only 13 % oxides simultaneously satisfy last four rules, indicating much lower...
The physics of heat conduction puts practical limits on many technological fields such as energy production, storage, and conversion. It is now widely appreciated that the phonon-gas model does not describe full vibrational spectrum in amorphous materials, since this picture likely breaks down at higher frequencies. A two-channel model, which uses harmonic states lattice dynamics a basis, has recently been shown to capture both crystal-like (phonon-gas channel) amorphous-like (diffuson...
Abstract Next‐generation thermal management requires the development of low lattice conductivity materials, as observed in ionic conductors. For example, thermoelectric efficiency is increased when decreased. Detrimentally, high leads to device degradation. Battery safety and design also require an understanding transport Ion mobility, structural complexity, anharmonicity have been used explain properties However, are rarely discussed direct comparison. Herein, Ag + argyrodites found change...
We present Jobflow, a domain-agnostic Python package for writing computational workflows tailored high-throughput computing applications.With its simple decorator-based approach, functions and class methods can be transformed into compute jobs that stitched together complex workflows.Jobflow fully supports dynamic where the full acyclic graph of is not known until runtime, such as launch other based on results previous steps in workflow.The all Jobflow easily stored variety filesystem-and...
High-throughput density functional theory (DFT) calculations have become a vital element of computational materials science, enabling screening, property database generation, and training “universal” machine learning models. While several software frameworks emerged to support these efforts, new developments such as learned force fields increased demands for more flexible programmable workflow solutions. This manuscript introduces atomate2, comprehensive evolution our original atomate...
Halogen bonds (XBs) are intriguing noncovalent interactions that frequently being exploited for crystal engineering. Recently, similar bonding mechanisms have been proposed adjacent main-group elements, and "chalcogen bonds" "pnictogen identified in structures. A fundamental question, largely unresolved thus far, is how XBs related contacts interact with each other crystals; to hydrogen bonding, one might expect "cooperativity" (bonds amplifying other), but evidence has sparse. Here, we...
In the past, traditional chemical heuristics have been very important for discovery of new materials. Machine learning approaches started to replace those in recent years, and they offer opportunities materials science. Both are strongly interconnected.Classical typically rely on less data than machine approaches. There two different types science: one relies features inspired by classical heuristics, other purely relationships within analyzed data.The growing amount offers an opportunity...
Understanding crystalline structures based on their chemical bonding is growing in importance. In this context, can be studied with the Crystal Orbital Hamilton Population (COHP), allowing for quantifying interatomic bond strength. Here we present a new set of tools to automate calculation COHP and analyze results. We use program packages VASP LOBSTER, Python atomate pymatgen. The analysis produced by our includes plots, textual description, key data machine-readable format. To illustrate...
ConspectusMolecular compounds, organic and inorganic, crystallize in diverse complex structures. They continue to inspire synthetic efforts "crystal engineering", with implications ranging from fundamental questions pharmaceutical research. The structural complexity of molecular solids is linked intermolecular interactions: hydrogen bonding all its facets, halogen bonding, other secondary mechanisms recent interest (and debate). Today, high-resolution diffraction experiments allow...
Machine learning driven interatomic potentials, including Gaussian approximation potential (GAP) models, are emerging tools for atomistic simulations. Here, we address the methodological question of how one can fit GAP models that accurately predict vibrational properties in specific regions configuration space while retaining flexibility and transferability to others. We use an adaptive regularization scales with absolute force magnitude on any given atom, thereby exploring Bayesian...
We present an ab initio high-throughput screening approach to search for new high-efficiency photovoltaic absorbers taking into account carrier lifetime and recombination through defects.
Abstract Materials combining strong ferromagnetism and good semiconducting properties are highly desirable for spintronic applications (e.g., in spin-filtering devices). In this work, we conduct a search concentrated ferromagnetic semiconductors through high-throughput computational screening. Our screening reveals the limited availability of low effective mass. We identify manganese pyrochlore oxide 2 Mn O 7 as especially promising spin transport it combines electron mass (0.29 m 0 ), large...
Abstract The Pauling rules have been used for decades to rationalise the crystal structures of ionic compounds. Despite their importance, there has no statistical assessment performances these five empirical so far. Here, we rigorously and automatically test all a large data set around 5000 known oxides. We discuss each rule separately, stressing limits range application in terms chemistries structures. conclude that only 13 % oxides simultaneously satisfy last four rules, indicating much...
SynCoTrain is a PU-learning framework using dual GNN classifiers to predict material synthesizability. It leverages co-training mitigate model bias and enhance generalizability.
Quaternary tantalum-based oxynitrides ATa(O,N)3, with electronic band gaps between 1.8 and 2.4 eV, are promising materials for photochemical water-splitting. The tailoring of their surface properties is a critical aspect to obtain efficient hole extraction. We report on the origin improved photoelectrochemical (PEC) water oxidation by means acidic treatment this class compounds example cubic CaTaO2N particles. address effect using complementary physical characterization techniques, such as...
Coordination or local environments have been used to describe, analyze and understand crystal structures for more than a century. Here, new tool called ChemEnv , which can identify coordination in fast robust manner, is presented. In contrast previous tools, the assessment of not biased by small distortions structure. Its implementation enables analysis large databases structures. The code available open source within pymatgen package software also be through web app on...
Abstract An unexpected polymorph of the highly energetic phase CuN 3 has been synthesized and crystallizes in orthorhombic space group Cmcm with a=3.3635(7), b=10.669(2), c=5.5547(11) Å V=199.34(7) . The layered structure resembles graphite an interlayer distance 2.777(1) (=1/2 c). Within a single layer, considering N − as one structural unit, there are 10‐membered almost hexagonal rings heterographene‐like motif. Copper nitrogen atoms covalently bonded CuN bonds lengths 1.91 2.00 Å, is...
The experimentally known perovskite-like materials BaYMn2O5+δ (δ = 0, 0.5, 1) are characterized by a remarkably reversible oxygen-storage capacity at moderate 500 °C. We try to elucidate the local structures of vacancy arrangements in these compounds taking place after an oxygen release. This is done for three with help both ab initio total-energy calculations density-functional quality and using classical structure rationale. Our results compared experimental findings. further calculate...
How reliably can anisotropic displacement parameters be derived from theory? Experiments and computations on pentachloropyridine shed new light this question.
Thermal properties of solid-state materials are a fundamental topic study with important practical implications. For example, anisotropic displacement parameters (ADPs) routinely used in physics, chemistry, and crystallography to quantify the thermal motion atoms crystals. ADPs commonly derived from diffraction experiments, but recent developments have also enabled their first-principles prediction using periodic density-functional theory (DFT). Here, we combine experiments...
software aids in extracting quantum-chemical bonding information from materials by projecting the plane-wave based wave functions density functional theory (DFT) onto an atomic orbital basis.LobsterEnv, a module implemented pymatgen (Ong et al., 2013) some of authors this package, facilitates use obtained LOBSTER calculations to identify neighbors and coordination environments.LobsterPy is Python package that offers set convenient tools further analyze summarize LobsterEnv outputs form JSONs...