Predicting Defect Stability and Annealing Kinetics in Two-Dimensional PtSe$_2$ Using Steepest Entropy Ascent Quantum Thermodynamics
Aimen Younis (1), Fazel Baniasadi (1), Michael R. von Spakovsky (1),, and William T. Reynolds Jr (1) ((1) Virginia Tech)

TL;DR
This paper applies the steepest-entropy-ascent quantum thermodynamic framework to predict defect stability and annealing kinetics in 2D PtSe$_2$, integrating experimental defect identification, DFT energy calculations, and Monte Carlo degeneracy estimations.
Contribution
It introduces a non-equilibrium quantum thermodynamic approach to model defect dynamics in 2D materials, linking quantum mechanics, thermodynamics, and statistical methods.
Findings
Predicted defect rearrangement during annealing.
Mapped energy landscape and defect degeneracies.
Validated defect stability with experimental data.
Abstract
The steepest-entropy-ascent quantum thermodynamic (SEAQT) framework was used to calculate the stability of a collection of point defects in 2D PtSe and predict the kinetics with which defects rearrange during thermal annealing. The framework provides a non-equilibrium, ensemble-based framework with a self-consistent link between mechanics (both quantum and classical) and thermodynamics. It employs an equation of motion derived from the principle of steepest entropy ascent (maximum entropy production) to predict the time evolution of a set of occupation probabilities that define the states of a system undergoing a non-equilibrium process. The system is described by a degenerate energy landscape of eigenvalues, and the entropy is found from the occupation probabilities and the eigenlevel degeneracies. Scanning tunneling microscopy was used to identify the structure and distribution of…
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Taxonomy
TopicsAdvanced Thermodynamics and Statistical Mechanics · Machine Learning in Materials Science · Advanced Thermoelectric Materials and Devices
