4 papers
Alleviating Community Fear in Disasters via Multi-Agent Actor-Critic Reinforcement Learning
Yashodhan D. Hakke, Almuatazbellah M. Boker, Lamine Mili +2
During disasters, cascading failures across power grids, communication networks, and social behavior amplify community fear and undermine cooperation. Existing cyber-physical-socia…
Steepest-Entropy-Ascent Framework for Predicting Arsenic Adsorption on Graphene Oxide Surfaces -- A Case Study
Adriana Saldana-Robles, Cesar Damian, Michael R. von Spakovsky +1
Water contamination by arsenic(V) constitutes a major public-health concern, underscoring the need for models that capture both equilibrium and transient adsorption behaviour. A fr…
Predicting Coupled Electron and Phonon Transport Using Steepest-Entropy-Ascent Quantum Thermodynamics
J. A. Worden, M. R. von Spakovsky, C. Hin
The principal paradigm for determining the thermoelectric properties of materials is based on the Boltzmann transport equations (BTEs) or Landauer equivalent. These equations depen…
Model for Predicting Adsorption Isotherms and the Kinetics of Adsorption via Steepest-Entropy-Ascent Quantum Thermodynamics
Adriana Saldana-Robles, Cesar Damian, William T. Reynolds +1
This work outlines the foundations for being able to do a first-principle study of the adsorption process using the steepest-entropy-ascent quantum thermodynamic (SEAQT) framework,…