A5009772815- Various Chemistry Research Topics
- X-ray Diffraction in Crystallography
- Machine Learning in Materials Science
- Crystallography and molecular interactions
- Nuclear Physics and Applications
- Luminescence Properties of Advanced Materials
- Rare-earth and actinide compounds
- Molecular spectroscopy and chirality
- Nuclear Materials and Properties
- Computational Drug Discovery Methods
- Inorganic Chemistry and Materials
- Sports injuries and prevention
- Medical Imaging and Analysis
- Biomedical and Engineering Education
- Software System Performance and Reliability
- Orthopedic Infections and Treatments
- Scientific Computing and Data Management
- Advanced biosensing and bioanalysis techniques
- Advanced Photocatalysis Techniques
- Radiation Detection and Scintillator Technologies
- Software Engineering Research
- Face and Expression Recognition
- Magnetic and transport properties of perovskites and related materials
- 2D Materials and Applications
- Video Surveillance and Tracking Methods
Federal Institute For Materials Research and Testing
2022-2025
Friedrich Schiller University Jena
2022-2025
Paderborn University
2021
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,...
Potassium poly (heptazine imide) (K-PHI), a crystalline two-dimensional carbon–nitride material, is an active photocatalyst for water splitting. The potassium ions in K-PHI can be exchanged with other to change the properties of material and eventually design catalysts. We report here electronic structures several ion-exchanged salts (K, H, Au, Ru, Mg) their feasibility as splitting photocatalysts, which were determined by density functional theory (DFT) calculations. DFT results are...
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...
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...
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...
Finding criminals or hunting for people, in a CCTV video footage, after crime scene major attack takes place, is time consuming task. As informed to us by cyber cell members of Goa branch, they make multiple the department sit with laptops and computers literally search through footage find trace guilty, as don't have automated system doing this task them. This process both labor intensive. In research paper we tried survey existing technologies well propose new criminal Detection &...
Abstract Understanding the origin of low thermal conductivities in ionic conductors is essential for improving their thermoelectric efficiency, although accompanying high conduction may present challenges maintaining device integrity. This study investigates and transport Cu 7 PSe 6 , aiming to elucidate fundamental origins correlation with structural dynamic properties. Through a comprehensive approach including various characterization techniques computational analyses, it demonstrated...
A recent approach to measure electron radiation doses in the kGy range is use of phosphors with an irradiation dose-dependent luminescence decay time.
Abstract Invited for this month′s cover are researchers from Bundesanstalt für Materialforschung und ‐prüfung (Federal Institute Materials Research and Testing) in Germany, Friedrich Schiller University Jena, Université catholique de Louvain, of Oregon, Science & Technology Facilities Council, RWTH Aachen University, Hoffmann Advanced Materials, Dartmouth College. The picture shows a workflow automatic bonding analysis with Python tools (green python). itself is performed the program...
Here, we present the outcomes from second Large Language Model (LLM) Hackathon for Applications in Materials Science and Chemistry, which engaged participants across global hybrid locations, resulting 34 team submissions. The submissions spanned seven key application areas demonstrated diverse utility of LLMs applications (1) molecular material property prediction; (2) design; (3) automation novel interfaces; (4) scientific communication education; (5) research data management automation;...
Machine learning has become ubiquitous in materials modelling and now routinely enables large-scale atomistic simulations with quantum-mechanical accuracy. However, developing machine-learned interatomic potentials requires high-quality training data, the manual generation curation of such data can be a major bottleneck. Here, we introduce an automated framework for exploration fitting potential-energy surfaces, implemented openly available software package that call autoplex (`automatic...
We demonstrate a strategy for simulating wide-range X-ray scattering patterns, which spans the small- and wide angles as well typically used Pair Distribution Function (PDF) analysis. Such simulated patterns can be to test holistic analysis models, and, since diffraction intensity is on same scale intensity, may offer novel pathway determining degree of crystallinity. The "Ultima Ratio" demonstrated 64-nm Metal Organic Framework (MOF) particle, calculated from Q < 0.01 1/nm up 150 1/nm, with...
An in-depth insight into the chemistry and nature of individual chemical bonds is essential for understanding materials. Bonding analysis thus expected to provide important features large-scale data machine learning material properties. Such bonding information can be computed using LOBSTER software package, which post-processes modern density functional theory by projecting plane wave-based wave functions onto a local, atomic orbital basis. With help fully automatic workflow, VASP packages...