arXiv subjects

Pablo A. Unzueta

Publications and source records attributed to Pablo A. Unzueta.

3 recordsLinked to original sources

arXiv2026

Machine-Learned NMR Shieldings in Molecular Solids with Built-In Hybrid-Functional Molecular Corrections

Fast and accurate chemical shielding estimators are essential for shielding-driven Nuclear Magnetic Resonance (NMR) crystallography. Machine-learning models for shielding predictions have matured significantly and today are primarily limited by the electronic structure reference data they are trained on. Here, we introduce ShiftML4, a shielding-tensor model trained directly on monomer-corrected calculations that approximate PBE0, rather than the PBE reference targeted by earlier ShiftML models. ShiftML4 is trained on a diverse set of structures containing 12 of the most common NMR nuclei in molecular organic solids. On experimental benchmark sets, the 13C isotropic RMSE against experiment is 1.67 ppm, compared with 2.34 ppm for GIPAW-PBE on the same geometries. ShiftML4 gives a similar 1H prediction RMSE to ShiftML3 (0.5 ppm) and improves the 15N RMSE from 7.24 to 6.08 ppm. The model also reduces errors in the shielding-tensor anisotropy, with an RMSE of 4.63 ppm on 13C CSA principal components against 5.85 ppm for GIPAW. The improvements in prediction accuracy are retained on better geometries. Basing shift predictions on structures relaxed with PET-MOLS, a recent machine-learned interatomic potential that reaches approximate hybrid-DFT geometries in seconds, lowers the ShiftML4 errors further to 0.48 ppm (1H), 1.49 ppm (13C) and 3.66 ppm (15N).

physics.chem-ph↗

arXiv2024

Fast and Scalable GPU-Accelerated Quantum Chemistry for Periodic Systems with Gaussian Orbitals: Implementation and Hybrid Density Functional Theory Calculations

Efficient hybrid DFT simulations of solid state materials would be extremely beneficial for computational chemistry and materials science, but is presently bottlenecked by difficulties in computing Hartree-Fock (HF) exchange with plane wave orbital bases. We present a GPU-accelerated, Gaussian orbital based integral algorithm for systems with periodic boundary conditions, which takes advantage of Ewald summation to efficiently compute electrostatic interactions. We have implemented this approach into the TeraChem software package within the $Γ$ point approximation, enabling simulation of unit cells with hundreds or thousands of atoms at the HF or hybrid DFT level on a single GPU card. Our implementation readily parallelizes over multiple GPUs and paves the road to accurate simulation of the properties and dynamics of extended materials in both the ground and excited states.

physics.chem-ph↗

arXiv2024

Prediction of Photodynamics of 200 nm Excited Cyclobutanone with Linear Response Electronic Structure and Ab Initio Multiple Spawning

Simulations of photochemical reaction dynamics have been a challenge to the theoretical chemistry community for some time. In an effort to determine the predictive character of current approaches, we predict the results of an upcoming ultrafast diffraction experiment on the photodynamics of cyclobutanone after excitation to the lowest lying Rydberg state (S$_2$). A picosecond of nonadiabatic dynamics is described with ab initio multiple spawning. We use both time dependent density functional theory and equation-of-motion coupled cluster for the underlying electronic structure theory. We find that the lifetime of the S$_2$ state is more than a picosecond (with both TDDFT and EOM-CCSD). The predicted UED spectrum exhibits numerous structural features, but weak time dependence over the course of the simulations.

physics.chem-ph↗