Xin@QuantumChem

@xinquantum.bsky.social

Computational Chemist @NJ/NYC Github: https://github.com/XinChenQC

Testing three LLM models (Opus 4.7, Sonnet 4.6, Gemma 4) on LogP prediction. The pairwise ranking is the most important thing, 76% accuracy is acceptable. Accurate numerical prediction still relies on dedicated models, this test is more about how well LLMs understand chemistry. #compchemsky

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Yesterday I posted an incorrect comparison. I accidentally copied the TS3 structure into TS1 for UMA and Orb-V3, so the MLIP results for TS1 were wrong. Really sorry about that misleading! In the next post I will share IRC of DFT calculation and wB97M-V/def2-TZVPD results. #compchem #compchemsky

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Xin@QuantumChem@xinquantum.bsky.social · 9mo ago

A failure case for deep-learning potential: the TS1 geometry is so weird that UMA and Orb-v3 underestimate the barrier by ~15 kcal/mol, likely because it far from the training set. Handling chemical reactions is extremely hard for general deep learning models. #compchem #compchemsky

This old theory is revitalized by deep learning. Building accurate kinetic energy functionals (< 0.5 kcal/mol) may be harder than climbing to the top of exchange-correlation Jacob's ladder.🪜

IOPP Machine Learning and AI@iopp-mlresearch.bsky.social · last yr.

#MachineLearning (ML) for orbital-free density functional theory (OF-DFT) and OF-DFT for ML. Manzhos and coworkers tackle the kinetic energy functional in this new #MachineLearningScienceandTechnology article. #compchem #CompChemSky Read it here: bit.ly/45eGM0f