Δ-Machine learning for quantum chemistry prediction of solution-phase molecular properties at the ground and excited states

X Chen, P Li, E Hruska, F Liu - Physical Chemistry Chemical Physics, 2023 - pubs.rsc.org
Due to the limitation of solvent models, quantum chemistry calculation of solution-phase
molecular properties often deviates from experimental measurements. Recently, Δ-machine …

Δ-Machine learning for quantum chemistry prediction of solution-phase molecular properties at the ground and excited states

X Chen, P Li, E Hruska, F Liu - Physical Chemistry Chemical …, 2023 - ui.adsabs.harvard.edu
We investigated the various factors impacting the performance of Δ-machine learning (Δ-ML)
solution phase molecular properties. Due to the limitation of solvent models, quantum …

Δ-Machine learning for quantum chemistry prediction of solution-phase molecular properties at the ground and excited states

X Chen, P Li, E Hruska, F Liu - Physical chemistry …, 2023 - pubmed.ncbi.nlm.nih.gov
Due to the limitation of solvent models, quantum chemistry calculation of solution-phase
molecular properties often deviates from experimental measurements. Recently, Δ-machine …

Δ-Machine learning for quantum chemistry prediction of solution-phase molecular properties at the ground and excited states.

X Chen, P Li, E Hruska, F Liu - Physical Chemistry Chemical …, 2023 - europepmc.org
Due to the limitation of solvent models, quantum chemistry calculation of solution-phase
molecular properties often deviates from experimental measurements. Recently, Δ-machine …

∆-Machine Learning for Quantum Chemistry Prediction of Solution-phase Molecular Properties at the Ground and Excited States

X Chen, P Li, E Hruska, F Liu - 2023 - chemrxiv.org
Due to the limitation of solvent models, quantum chemistry calculated solution-phase
molecular properties often deviates from experimental measurements. Recently,∆-machine …