Chemical Physics
Foundation ML Potentials to Displace DFT in Computational Chemistry
Computational chemistry heavily relies on potential energy hypersurfaces, traditionally computed via DFT, which is computationally expensive. A new class of machine learning interatomic potentials offers quantum accuracy at force-field speeds. Recent advancements, specifically "foundation machine le…
Methane Pyrolysis for Hydrogen and Carbon Black: Experimental Benchmarking of Reaction Models
Methane pyrolysis offers a cleaner method for co-producing hydrogen and carbon black. This study provides experimental data from shock tube experiments, including gas-phase species concentrations, particle formation, and morphology. The findings serve as a benchmark for refining models that describe…
N-Mode Quantized Anharmonic Vibronic Hamiltonians Enhance Photochemical Dynamics Simulations
The paper introduces a novel approach for simulating photochemical processes by quantizing n-mode anharmonic vibronic Hamiltonian terms. This framework integrates a second-quantized perspective with the density matrix renormalization group algorithm, enabling accurate and reliable quantum dynamics c…