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Mechanical properties of molecular crystals are fundamentally important to their in- dustrial utility as pharmaceuticals or agrochemicals, energetic materials and more. Yet, complete measurements of e...

The structural response of a high-pressure phase of isobutyronitrile up to 6.12 GPa was studied by using high-pressure single-crystal X-ray diffraction, periodic density functional theory (DFT), and C...

PET-MAD is a fast and lightweight universal machine-learning potential, trained on a small but diverse dataset, that delivers near-quantum accuracy in atomistic simulations for both organic and inorga...

Our mission is to transform lives and communities through education and research. Curtin employees form a unique and diverse community committed to innovative research and student learning. Find out a...

Our mission is to transform lives and communities through education and research. Curtin employees form a unique and diverse community committed to innovative research and student learning. Find out a...

Scientists, research institutions, funders, libraries and publishers must all improve software practices.

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...