First analytic nuclear gradients derived and implemented for BSE@G0W0, validated on excited-state geometries and adiabatic energies against wavefunction benchmarks.
\ Wang \ and\ author C
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Skala is a neural XC functional trained on wavefunction data that beats state-of-the-art hybrids on main-group chemistry benchmarks at semi-local computational cost.
A structure-preserving low-rank factorization of 2RDMs achieves linear rank scaling with system size and ~99% compression while retaining chemical accuracy for correlated states.
COLTRIMS experiment shows sequential fragmentation of CH4^2+ via metastable CH3^2+, CH2^2+, and CH^2+ intermediates with estimated half-rotational periods from Newton diagrams.
THEMol is a new large dataset of torsion, Hessian, energy, and multipole data from DFT for closed-shell organic molecules, organized into five subsets for use in molecular potential development.
CovAngelo implements a QM/QM/MM embedding model using quantum-information metrics to compute reaction energy profiles and barriers for covalent drug binding at lower cost than conventional methods, demonstrated on zanubrutinib to BTK.
RI-CC2 simulations of pyrazine internal conversion match the experimental 22 fs decay time, identify Q9a and Q8a modes as drivers, and show the dark A1u state participates actively.
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CovAngelo: A hybrid quantum-classical computing platform for accurate and scalable drug discovery
CovAngelo implements a QM/QM/MM embedding model using quantum-information metrics to compute reaction energy profiles and barriers for covalent drug binding at lower cost than conventional methods, demonstrated on zanubrutinib to BTK.