Siamak Attarian

ORCID: 0000-0001-9275-2020
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About
Contact & Profiles
Research Areas
  • Machine Learning in Materials Science
  • Molten salt chemistry and electrochemical processes
  • Superconductivity in MgB2 and Alloys
  • High-pressure geophysics and materials
  • Titanium Alloys Microstructure and Properties
  • Advanced Electron Microscopy Techniques and Applications
  • Metallurgical Processes and Thermodynamics
  • Composite Material Mechanics
  • Boron and Carbon Nanomaterials Research
  • Metal and Thin Film Mechanics
  • Nuclear Materials and Properties
  • Ion-surface interactions and analysis
  • Nuclear Physics and Applications
  • MXene and MAX Phase Materials
  • Metallurgy and Material Forming
  • Glass properties and applications
  • Nuclear reactor physics and engineering
  • Microstructure and mechanical properties
  • Iron and Steelmaking Processes
  • Force Microscopy Techniques and Applications
  • Advanced Materials Characterization Techniques
  • Hydrogen embrittlement and corrosion behaviors in metals
  • Electron and X-Ray Spectroscopy Techniques
  • Rare-earth and actinide compounds
  • Advanced materials and composites

University of Wisconsin–Madison
2022-2025

University of Iowa
2018-2022

Engineering Arts (United States)
2020

<title>Abstract</title> Molten salts are crucial for clean energy applications, yet exploring their thermophysical properties across diverse chemical spaces remains challenging. We present the development of a machine learning interatomic potential (MLIP) called SuperSalt, which targets 11-cation chloride melts and captures essential physics molten with near-DFT accuracy. Using an efficient workflow that integrates systems one, two, 11 components, SuperSalt can accurately predict such as...

10.21203/rs.3.rs-5664807/v1 preprint EN cc-by Research Square (Research Square) 2025-01-15

10.1016/j.molliq.2022.120803 article EN publisher-specific-oa Journal of Molecular Liquids 2022-11-15

There is a boundary effect due to incomplete horizons of or near-boundary points in peridynamics. In this paper, we propose attach “fictitious walls” surfaces so that the can be reduced eliminated. Differing from concept material layers”, which only attached displacement surfaces, are both and force surfaces. Three types fictitious walls considered paper: undeformed, deformed, periodic. It recommended “undeformed boundaries “deformed boundaries. “Periodic suggested for use peristatics only....

10.1142/s1756973718410032 article EN Journal of Multiscale Modelling 2018-11-09

In this paper, we present the first work in developing a second nearest-neighbor modified embedded atom method (2NN-MEAM) potential function that can be used to model interatomic interactions both [Formula: see text] boron and polymorphs. To fit parameters by optimization, some physical properties elastic constants of boron, calculated from density functional theory, are adopted as targets objective function. The developed is utilized molecular dynamics (MD) simulations calculate physical,...

10.1142/s2424913020500083 article EN Journal of Micromechanics and Molecular Physics 2020-09-01

Molten salts are crucial for clean energy applications, yet exploring their thermophysical properties across diverse chemical space remains challenging. We present the development of a machine learning interatomic potential (MLIP) called SuperSalt, which targets 11-cation chloride melts and captures essential physics molten with near-DFT accuracy. Using an efficient workflow that integrates systems one, two, 11 components, SuperSalt can accurately predict such as density, bulk modulus,...

10.48550/arxiv.2412.19353 preprint EN arXiv (Cornell University) 2024-12-26

10.26226/morressier.5f5f8e69aa777f8ba5bd5f81 preprint EN 2020-09-21
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