A5068217246- Aluminum Alloys Composites Properties
- Machine Learning in Materials Science
- Advanced Welding Techniques Analysis
- Intermetallics and Advanced Alloy Properties
- nanoparticles nucleation surface interactions
- Aluminum Alloy Microstructure Properties
- Metallurgy and Material Science
- Advanced Materials Characterization Techniques
- Electron and X-Ray Spectroscopy Techniques
- Surface and Thin Film Phenomena
- Metallic Glasses and Amorphous Alloys
- Material Dynamics and Properties
- Titanium Alloys Microstructure and Properties
- Nuclear Materials and Properties
- Metal Forming Simulation Techniques
- High-Temperature Coating Behaviors
- High Temperature Alloys and Creep
- Microstructure and mechanical properties
- Metallurgical and Alloy Processes
- Theoretical and Computational Physics
- Nanoporous metals and alloys
- Advanced Chemical Physics Studies
- High Entropy Alloys Studies
- Welding Techniques and Residual Stresses
- Crystallization and Solubility Studies
Max-Planck-Institut für Nachhaltige Materialien
2022-2024
Ruhr University Bochum
2019-2022
Naval Postgraduate School
2010-2018
Lawrence Berkeley National Laboratory
1991-2007
UES (United States)
2002-2006
University of California, Berkeley
1990-1991
Los Alamos National Laboratory
1986
Bhabha Atomic Research Centre
1978
Abstract The atomic cluster expansion is a general polynomial of the energy in multi-atom basis functions. Here we implement performant C++ code that suitable for use large-scale atomistic simulations. We briefly review and give detailed expressions energies forces as well efficient algorithms their evaluation. demonstrate implemented shifts previously established Pareto front machine learning interatomic potentials toward faster more accurate calculations. Moreover, purpose...
The atomic cluster expansion (ACE) provides a general, local, and complete representation of energies. Here we present an efficient framework for parametrization ACE models elements, alloys, molecules. To this end, first introduce general requirements physically meaningful description the interaction, in addition to usual equivariance requirements. We then demonstrate that can be converged systematically with respect two fundamental characteristics---the number complexity basis functions...
Organic-walled microfossils provide the best insights into composition and evolution of biosphere through first 80 percent Earth history. The mechanism microfossil preservation affects quality biological information retained informs understanding early palaeo-environments. We here show that 1 billion-year-old from non-marine Torridon Group are remarkably preserved by a combination clay minerals phosphate, with providing highest fidelity preservation. Fe-rich mostly occurs in narrow zones...
The structural characterization of local atomic environments is essential in our understanding and design materials with customized properties.Atomistic simulations have become a powerful tool to provide insight into the patterns mechanisms that signify transformations between different crystalline liquid phases, or formation dynamics point extended defects.The development availability methods reliable accurate analysis atomistic simulation data constitute an indispensable task continues be...
Abstract We present a comprehensive and user-friendly framework built upon the integrated development environment (IDE), enabling researchers to perform entire Machine Learning Potential (MLP) cycle consisting of (i) creating systematic DFT databases, (ii) fitting Density Functional Theory (DFT) data empirical potentials or MLPs, (iii) validating in largely automatic approach. The power performance this are demonstrated for three conceptually very different classes interatomic potentials: an...
With the aim to develop a new generation of materials that combine either known energy absorbing properties carbon nanofibers (CNF), or carbon-carbon bond strength graphene sheets (G), with shock resistance reported for Inorganic Fullerene type WS2 structures (IF-WS2), hybrid CNF/IF-WS2 and G/IF-WS2 were generated, characterized tested. Experimentation revealed in situ growth nanostructures inorganic fullerene tungsten disulfide particulates had be performed from particular precursors...
Microstructure evolution in an as-cast Na modified Al–7%Si (wt. pct.) alloy was examined during redundant and monotonic straining by repetitive equi-channel angular pressing (ECAP) under ambient temperature conditions, friction stir processing (FSP). Redundant ECAP accomplished following route BC while employed A. Single- multi-pass FSP conducted on this same material using tool having a threaded pin. The microstructure comprises equiaxed primary α dendrite cells embedded the Al–Si eutectic...
Abstract Microstructures produced by isothermal hot rolling of a NiAl bronze material were evaluated quantitative microscopy methods and parameters describing the contributions precipitate dispersions, grain size, solute content, dislocation density to yield strengths individual constituents microstructure determined. Models for combined predict temperature dependence strength as function temperature, prediction was found be in good agreement with measured strengths. The models applied...
We present a comprehensive and user-friendly framework built upon the pyiron integrated development environment (IDE), enabling researchers to perform entire Machine Learning Potential (MLP) cycle consisting of (i) creating systematic DFT databases, (ii) fitting Density Functional Theory (DFT) data empirical potentials or MLPs, (iii) validating in largely automatic approach. The power performance this are demonstrated for three conceptually very different classes interatomic potentials: an...
We devise automated workflows for the calculation of Helmholtz and Gibbs free energies their temperature pressure dependence provide corresponding computational tools. employ nonequilibrium thermodynamics evaluating energy solid liquid phases at a given reversible scaling computing over wide range temperatures, including direct integration $P\text{\ensuremath{-}}T$ coexistence lines. By changing chemistry interatomic potential, alchemical upscaling calculations are possible. Several examples...
Equivalent strains up to a value of ≈2.7 were determined by evaluation the shape changes phases in duplex α(fcc)/β(bcc) microstructure formed ahead pin tool extraction site during friction stir processing (FSP) thermomechanical cycle cast NiAl bronze alloy. Correlation local with volume fractions various constituents this alloy shows that concurrent straining FSP results acceleration α + β → reaction thermomechanically affected zone (TMAZ) site. The resulting fraction (as its transformation...
The atomic cluster expansion is a general polynomial of the energy in multi-atom basis functions. Here we implement performant C++ code \verb+PACE+ that suitable for use large scale atomistic simulations. We briefly review and give detailed expressions energies forces as well efficient algorithms their evaluation. demonstrate implemented shifts previously established Pareto front machine learning interatomic potentials towards faster more accurate calculations. Moreover, purpose...
Observing nonclassical nucleation pathways remains challenging in simulations of complex materials with technological interests. This is because it requires very accurate force fields that can capture the whole complexity their underlying interatomic interactions and an advanced structural analysis able to discriminate between competing crystalline phases. Here, we first report construction particularly thorough validation a machine-learning field for zinc oxide using Physical LassoLars...