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Open Computational Chemistry - Quantum chemistry calculations in your browser

Nonadiabatic molecular dynamics simulations provide a theoretical understanding of various excited-state processes in photochemistry, offering access to band widths, radiative or nonradiative relaxation and corresponding lifetimes, excited-state energies, and charge transfer. The range of method developments within the framework of time-dependent density functional theory is exceedingly large for molecular quantum chemistry. Still, it shrinks significantly when aiming to treat periodic boundary conditions. To address this gap and complement existing software packages for solid-state nonadiabatic molecular dynamics, we present an interface between the CP2K electronic structure and the NEWTON-X surface hopping codes. The interface features the generation of initial conditions, as well as adiabatic and nonadiabatic molecular dynamics, based on phenomenological or numerical time-derivative couplings. Setups are validated on gas-phase pyrazine, with electronic absorption spectra and excited-state populations for transitions between the lowest singlet states being in agreement with established molecular quantum chemistry methods. Extending the system size to crystalline pyrazine, limitations of approximate couplings are discussed, and the efficiency and applicability of the interface are demonstrated by computing broad spectra over several eV and 100 fs trajectories, considering couplings between all 80th lowest excited states, at low computational cost with a mixed semiempirical density functional theory setup.

The Bethe–Salpeter equation (BSE) formalism, combined with the GW approximation for ionization energies and electron affinities, is emerging as an efficient and accurate method for predicting optical excitations in molecules. In this Letter, we present the first derivation and implementation of fully analytic nuclear gradients for the BSE@G0W0 method. Building on recent developments for G0W0 nuclear gradients, we derive analytic nuclear gradients for several BSE@G0W0 variants. We validate our implementation against numerical gradients and compare excited-state geometries and adiabatic excitation energies obtained from different BSE@G0W0 variants with those from state-of-the-art wave function methods.

We describe an efficient algorithm to compute the bridge length estimating the size of a complete isoset invariant, which classifies all periodic point sets under Euclidean motion.

Accurate and scalable machine-learned inter-atomic potentials (MLIPs) are essential for molecular simulations ranging from drug discovery to new material design. Current state-of-the-art models enforc...

Run LAMMPS molecular dynamics simulations in your browser

Machine learning is revolutionising materials modelling but requires high-quality training data. Here, the authors introduce autoplex, an open framework automating exploration and fitting of potential...

Simulating molecular adsorption on surfaces presents considerable challenges, as computational methods typically suffer from either insufficient accuracy or prohibitive computational costs. Now, with ...

Apply for the Research Fellow in Theoretical Quantum Chemistry role on jobs.ac.uk, the top job board for academic positions in higher education. View details and apply now.

We explore the foundations and applications of Hirshfeld partitioning, a fundamental technique used in the analysis of atoms in molecules, and the related Hirshfeld surface used to study molecules in ...

A PhD stipend or integrated PhD stipend in computational materials chemistry is available. Development of new sustainable energy materials, including materia...

occ can be run using uv tool (will install occpy into a temporary virtual environment)

In this work, we describe the development of a new algorithm for the computation of Coulomb-type matrices using the well-known resolution of the identity (RI) or density fitting (DF) approximation. The method is linear-scaling with respect to system size and computationally highly efficient. For small molecules, it performs almost as well as the Split-RI-J algorithm (which might be the most efficient RI-J implementation to date), while outperforming it for larger systems with about 300 or more atoms. The method achieves linear scaling through multipole approximations and a hierarchical treatment of multipoles. However, unlike in the fast multipole method (FMM), the algorithm does not use a hierarchical boxing algorithm. Rather, close-lying objects like auxiliary basis shells and basis set shell pairs are grouped together in spheres that enclose the set of objects completely, which includes a new definition of the shell-pair extent that defines a real-space radius outside of which a given shell pair can be safely assumed to be negligible. We refer to these spheres as “bubbles” and therefore refer to the algorithm as the “Bubblepole” (BUPO) algorithm, with the acronym being RI-BUPO-J. The bubbles are constructed in a way to contain a nearly constant number of objects such that a very even workload arises. The hierarchical bubble structure adapts itself to the molecular topology and geometry. For any target object (shell pair or auxiliary shell), one might envision that the bubbles “carve” out what might be referred to as a “far-field surface”. Using the default settings determined in this work, we demonstrate that the algorithm reaches submicro-Eh and even nano-Eh accuracy in the total Coulomb energy for systems as large as 700 atoms and 7000 basis functions. The largest calculations performed (the crambin protein solvated by 500 explicit water molecules in a triple-ζ basis) featured more than 2000 atoms and more than 33,000 basis functions.