Data-Driven Molecular Dynamics and TEM Analysis of Crystal Growth and Hydrogen Sensing in Pt-Functionalized Graphene Chemiresistive Sensors

Documents similaires

• Modeling Chemical Exfoliation of Non-van der Waals Chromium Sulfides by Machine Learning Interatomic Potentials and Monte Carlo Simulations
  par: Ibrahim, Akram, et autres
  Publié: (2023)
• Linear-Scaling Potential-Free Data-Driven Molecular Dynamics for Arbitrary-Sized Water Clusters $(\text{H}_2\text{O})_n$
  par: Yan, Hongyu, et autres
  Publié: (2024)
• Collective excitations in Hydrogen across the pressure-induced transition from molecular to atomic fluid
  par: Ilenkov, I. -M., et autres
  Publié: (2025)
• Developing a Neural Network Machine Learning Interatomic Potential for Molecular Dynamics Simulations of La-Si-P Systems
  par: Tang, Ling, et autres
  Publié: (2025)
• Specific Heat Anomalies and Local Symmetry Breaking in (Anti-)Fluorite Materials: A Machine Learning Molecular Dynamics Study
  par: Kobayashi, Keita, et autres
  Publié: (2024)