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A. Daramola

Publications and source records attributed to A. Daramola.

2 recordsLinked to original sources

High-Temperature Deformation Behavior of Co-Free Non-Equiatomic CrMnFeNi Alloy

Cobalt-free high-entropy alloys (HEAs) have garnered interest for nuclear structural applications due to their good mechanical performance, thermal stability, and resistance to radiation-induced degradation, while avoiding long-lived Co radioisotopes. This study presents an experimental and computational investigation of the plastic deformation behavior of a non-equatomic CrMnFeNi alloy, designed to maintain a stability of fcc phase in a large domain of temperatures and to balance stacking fault (SF) energies for enhanced strain hardening and ductility. Tensile tests reveal a temperature-dependent reduction in mechanical strength, attributed to thermally activated deformation mechanisms and microstructural evolution. Molecular dynamics simulations of single- and polycrystals capture dislocation activity, SF formation, and twin nucleation as a function of strain and temperature. Electron backscatter diffraction (EBSD) confirms twin formation and grain boundary activity. The Schmid factor mapping is drawn to interpret local slip activity and anisotropic deformation behavior. The absence of Co leads to enhanced high-temperature strength compared to the Cantor alloy.

cond-mat.mtrl-sci

Tadah! A Swiss Army Knife for Developing and Deployment of Machine Learning Interatomic Potentials

The Tadah! code provides a versatile platform for developing and optimizing Machine Learning Interatomic Potentials (MLIPs). By integrating composite descriptors, it allows for a nuanced representation of system interactions, customized with unique cutoff functions and interaction distances. Tadah! supports Bayesian Linear Regression (BLR) and Kernel Ridge Regression (KRR) to enhance model accuracy and uncertainty management. A key feature is its hyperparameter optimization cycle, iteratively refining model architecture to improve transferability. This approach incorporates performance constraints, aligning predictions with experimental and theoretical data. Tadah! provides an interface for LAMMPS, enabling the deployment of MLIPs in molecular dynamics simulations. It is designed for broad accessibility, supporting parallel computations on desktop and HPC systems. Tadah! leverages a modular C++ codebase, utilizing both compile-time and runtime polymorphism for flexibility and efficiency. Neural network support and predefined bonding schemes are potential future developments, and Tadah! remains open to community-driven feature expansion. Comprehensive documentation and command-line tools further streamline the development and application of MLIPs.

physics.comp-ph