Journal of Chemical Theory and Computation最新文献

The integration of quantum chemical methods with high-performance computing is indispensable for handling large systems with modest accuracy or even small systems but with high accuracy. Continuing with the unified implementation of nonrelativistic and relativistic wave function methods within the MetaWave platform (J. Phys. Chem. A 2025, 129, 5170), we present here a unified MPI parallelization of the methods by abstracting every computational step of a method as a dynamically scheduled loop via ghost process, followed by a global reduction of local results from each node. The algorithmic abstraction enables the use of a single MPI template in various steps of different methods. Taking iCIPT2 [J. Chem. Theory Comput. 2021, 17, 949] as a showcase, the parallel efficiencies achieve 94% and 89% on 16 nodes (1024 cores) for the perturbation and whole calculations, respectively. Further combined with an improved algorithm for the matrix-vector product in the matrix diagonalization and an orbital-configuration-based semistochastic estimator for the perturbation correction, this renders large active space calculations possible, so as to obtain benchmarks for the automerization of cyclobutadiene, ground-state energy of benzene, and potential energy profile of ozone. It is also shown that the error of iCIPT2 follows a power law with respect to the number of configuration state functions.

Rydberg excited states of molecules pose a challenge for electronic structure calculations because of their highly diffuse electron distribution. Even large and elaborate atomic basis sets tend to underrepresent the long-range tail, overly confining the Rydberg state. An approach is presented here where the molecular orbitals are variationally optimized for the excited state using a plane wave basis set in a Hartree-Fock calculation, followed by a configuration interaction calculation. The use of excited state optimized orbitals greatly enhances the convergence of the many-body calculation, as illustrated by a full configuration interaction calculation of the 2s Rydberg state of H₂. A neural-network-based selective configuration interaction approach is then applied to calculations of 3s and 3p states of H₂O and NH₃. The obtained values of excitation energy are in close agreement with experimental measurements as well as previous many-body calculations where sufficiently diffuse atomic basis sets were used. Calculations using atomic basis sets lacking extra diffuse functions, such as aug-cc-pVTZ, give significantly higher estimates due to confinement of the Rydberg states.

QC Lab is an open-source Python package for quantum-classical (QC) dynamics simulations aimed to promote the development of QC algorithms, and their application to a wide variety of relevant model problems. It follows a modular design that facilitates cross-compatibility between algorithms and models. By decomposing algorithms and models into a series of tasks and ingredients that can be substituted and reused, it minimizes development efforts and code redundancy. In this Paper, we introduce the first stable version of QC Lab, and describe its design philosophy.

We introduce pyEF, a software package for computing molecular electric fields, electrostatic interaction energies, and electrostatic potentials from quantum mechanical (QM) atom-centered multipole expansions with atom-wise decomposable contributions. We demonstrate the computational efficiency and accuracy of this QM-derived electric field evaluation tool through several tests. To assess the influence of the underlying QM method and charge partitioning scheme on these electrostatic quantities, we analyze over 250 configurations of an acetone solute molecule in five solvents of variable polarity. We find that electric field calculations are highly sensitive to the choice of charge partitioning method. Even among real-space charge schemes, acetone Stark tuning rates differ by up to a factor of 2. Benchmarking computed solvent dipole moments against experimental bulk values, we conclude that the CM5, ADCH, and Hirshfeld-I charge schemes most reliably capture solvent electrostatics and therefore provide a more faithful foundation for computing electric fields. When constructed from these real-space charges, electric fields are nearly insensitive to basis set size and monotonically increase in magnitude with higher Fock exchange. We also demonstrate efficient convergence of QM electrostatics when more distant molecules are represented solely by MM point charges, reducing computational overhead. Leveraging these findings, we demonstrate the use of pyEF to deduce environmental effects on a transition metal complex from a Ga₄L₆^12- nanocage and quantify the dominant role of organic linkers in orchestrating electrostatic preorganization.

Large atomic-orbital (AO) basis sets of at least triple and preferably quadruple-ζ (QZ) size are required to adequately converge Kohn-Sham density functional theory (DFT) calculations toward the complete basis set limit. However, incrementing the cardinal number by one nearly doubles the AO basis dimension, and the computational cost scales as the cube of the AO dimension, so this is very computationally demanding. In this work, we develop and test a threshold-based natural atomic orbital (NAO) scheme in which ϵ-NAOs are obtained as eigenfunctions of atomic blocks of the density matrix in a one-center orthogonalized representation. This enables compression of the AO basis that is optimal for a given threshold, 10^-ϵ, by discarding NAOs with occupation numbers below that threshold. Extensive pilot test calculations using the Hartree-Fock functional and taking the converged density matrix as input suggest that a threshold of 10^-5 can yield a compression factor (ratio of AO to compressed ϵ-NAO dimension) between 2.5 and 4.5 for the QZ pc-3 basis. The errors in relative energies are typically less than 0.1 kcal/mol when the compressed basis is used instead of the uncompressed basis. Between 10 and 100 times smaller errors (i.e., usually less than 0.01 kcal/mol) can be obtained with a threshold 10^-7, while the compression factor is typically between 2 and 2.5.