physics.chem-ph

Papers

• On the importance of graph search algorithms for DRGEP-based mechanism reduction methods (2016)
  Kyle E. Niemeyer and Chih-Jen Sung
  —
• FragmentNet: Adaptive Graph Fragmentation for Graph-to-Sequence Molecular Representation Learning (2026)
  Ankur Samanta et al.
  —
• Energy-Guided Generative Modeling for Low-Energy Molecular Structure Discovery (2026)
  Guikun Xu et al.
  —
• Coarse-Grained Boltzmann Generators (2026)
  Weilong Chen et al.
  —
• Faster Molecular Dynamics with Neural Network Potentials via Distilled Multiple Time-Stepping and Non-Conservative Forces (2026)
  Nicola\"i Gouraud et al.
  —
• Advancing multi-site emission control: A physics-informed transfer learning framework with mixture of experts for carbon-pollutant synergy (2026)
  Yuxuan Ying et al.
  —
• CompleteRXN: Toward Completing Open Chemical Reaction Databases (2026)
  Gabriel Vogel et al.
  —
• Physics-Guided Concentration Inference from Resistance Transients in a Mixed-Phase SnO-SnO$_2$ Carbon Monoxide Sensor with p-n Switching (2026)
  Sani Biswas et al.
  —
• Multitask learning with semiempirical orbital charges enables sample-efficient MLIPs (2026)
  Ihor Neporozhnii et al.
  —
• Machine Learning Multiscale Interactions (2026)
  \`Alex Sol\'e et al.
  —
• M\=oLe-{\Lambda}: Learning the Coupled-Cluster Response State for Energies, Gradients, and Properties (2026)
  Andreas Burger et al.
  —
• A Systematic Evaluation of Molecular Mixture Behavior Prediction (2026)
  Roel J. Leenhouts et al.
  —