GPAW: An open Python package for electronic structure calculations

Mixed Conducting Oxide Coating for Lithium Batteries

Thin, uniform, and conformal coatings on the active electrode materials are gaining more importance to mitigate degradation mechanisms in lithium-ion batteries. To avoid polarization of the electrode, mixed conductors are of crucial importance. Atomic layer deposition (ALD) is employed in this work to provide superior uniformity, conformality, and the ability to precisely control the stoichiometry and thickness of the desired coating materials. We provide experimental and computational guidelines for the need of mixed electronic and ionic conducting coating materials, especially in the case where highly uniform and conformal coatings are achieved. We report promising results for ALD-deposited protective films achieved by doping fluorine (F) into a lithium vanadate coating. The F-doped lithium vanadate coating at the optimal doping level exhibits an electrical conductivity of 1.2 × 10-5 S·cm-1. Density functional theory calculations corroborate enhanced mixed electronic and ionic conduction in F-doped lithium vanadate through band structure analysis and climbing-image nudge elastic band (CI-NEB) calculations. It has been demonstrated that the experimentally determined optimal doping concentration aligns well with that predicted by density functional theory calculations. CI-NEB calculations have shown that the activation energy for lithium-ion transport was the lowest for optimally doped lithium vanadate.

Co-designing ab initio electronic structure methods on a RISC-V vector architecture

Ab initio electronic structure applications are among the most widely used in High-Performance Computing (HPC), and the eigenvalue problem is often their main computational bottleneck. This article presents our initial efforts in porting these codes to a RISC-V prototype platform leveraging a wide Vector Processing Unit (VPU). Our software tester is based on a mini-app extracted from the ELPA eigensolver library. The user-space emulator Vehave and a RISC-V vector architecture implemented on an FPGA were tested. Metrics from both systems and different vectorisation strategies were extracted, ranging from the simplest and most portable one (using autovectorisation and assisting this by fusing loops in the code) to the more complex one (using intrinsics). We observed a progressive reduction in the number of vectorised instructions, executed instructions and computing cycles with the different methodologies, which will lead to a substantial speed-up in the calculations. The obtained outcomes are crucial in advancing the porting of computational materials and molecular science codes to (post)-exascale architectures using RISC-V-based technologies fully developed within the EU. Our evaluation also provides valuable feedback for hardware designers, engineers and compiler developers, making this use case pivotal for co-design efforts.

Fragmentation patterns of DNA-stabilized silver nanoclusters under mass spectrometry

DNA-stabilized silver nanoclusters (AgN-DNAs) are emitters with tuneable structures and photophysical properties. While understanding of the sequence-structure-property relationships of AgN-DNAs has advanced significantly, their chemical transformations and degradation pathways are far less understood. To advance understanding of these pathways, we analysed the fragmentation products of 21 different red and NIR AgN-DNAs using negative ion mode electrospray ionization mass spectrometry (ESI-MS). AgN-DNAs were found to lose Ag+ under ESI-MS conditions, and sufficient loss of silver atoms can lead to a transition to a lesser number of effective valence electrons, N0. Of more than 400 mass spectral peaks analysed, only even values of N0 were identified, suggesting that solution-phase AgN-DNAs with odd values of N0 are unlikely to be stable. AgN-DNAs stabilized by three DNA strands were found to fragment significantly more than AgN-DNAs stabilized by two DNA strands. Moreover, the fragmentation behaviour depends strongly on the DNA template sequence, with diverse fragmentation patterns even for AgN-DNAs with similar molecular formulae. Molecular dynamics simulations, with forces calculated from density functional theory, of the fragmentation of (DNA)2(Ag16Cl2)8+ with a known crystal structure show that the 6-electron Ag16Cl2 core fragments into a 4-electron Ag10 and a 2-electron Ag6, preserving electron-pairing rules even at early stages of the fragmentation process, in agreement with experimental observation. These findings provide new insights into the mechanisms by which AgN-DNAs degrade and transform, with relevance for their applications in sensing and biomedical applications.

Excited-State Forces with the Gaussian and Augmented Plane Wave Method for the Tamm-Dancoff Approximation of Time-Dependent Density Functional Theory

Augmented plane wave methods enable an efficient description of atom-centered or localized features of the electronic density, circumventing high energy cutoffs and thus prohibitive computational costs of pure plane wave formulations. To complement existing implementations for ground-state properties and excitation energies, we present the extension of the Gaussian and augmented plane wave method to excited-state nuclear gradients within the Tamm-Dancoff approximation of time-dependent density functional theory and its implementation in the CP2K program package. Benchmarks for a test set of 35 small molecules demonstrate that maximum errors in the nuclear forces for excited states of singlet and triplet spin multiplicity are smaller than 0.1 eV/Å. The method is furthermore applied to the calculation of the zero-phonon line of defective hexagonal boron nitride. This spectral feature is reproduced with an error of 0.6 eV in comparison to GW-Bethe-Salpeter reference computations and 0.4 eV in comparison to experimental measurements. Accuracy assessments and applications thus demonstrate the potential use of the outlined developments for large-scale applications on excited-state properties of extended systems.

Controlling Plasmonic Catalysis via Strong Coupling with Electromagnetic Resonators

Plasmonic excitations decay within femtoseconds, leaving nonthermal (often referred to as "hot") charge carriers behind that can be injected into molecular structures to trigger chemical reactions that are otherwise out of reach─a process known as plasmonic catalysis. In this Letter, we demonstrate that strong coupling between resonator structures and plasmonic nanoparticles can be used to control the spectral overlap between the plasmonic excitation energy and the charge injection energy into nearby molecules. Our atomistic description couples real-time density-functional theory self-consistently to an electromagnetic resonator structure via the radiation-reaction potential. Control over the resonator provides then an additional knob for nonintrusively enhancing plasmonic catalysis, here more than 6-fold, and dynamically reacting to deterioration of the catalyst─a new facet of modern catalysis.

i-PI 3.0: A flexible and efficient framework for advanced atomistic simulations

Atomic-scale simulations have progressed tremendously over the past decade, largely thanks to the availability of machine-learning interatomic potentials. These potentials combine the accuracy of electronic structure calculations with the ability to reach extensive length and time scales. The i-PI package facilitates integrating the latest developments in this field with advanced modeling techniques thanks to a modular software architecture based on inter-process communication through a socket interface. The choice of Python for implementation facilitates rapid prototyping but can add computational overhead. In this new release, we carefully benchmarked and optimized i-PI for several common simulation scenarios, making such overhead negligible when i-PI is used to model systems up to tens of thousands of atoms using widely adopted machine learning interatomic potentials, such as Behler-Parinello, DeePMD, and MACE neural networks. We also present the implementation of several new features, including an efficient algorithm to model bosonic and fermionic exchange, a framework for uncertainty quantification to be used in conjunction with machine-learning potentials, a communication infrastructure that allows for deeper integration with electronic-driven simulations, and an approach to simulate coupled photon-nuclear dynamics in optical or plasmonic cavities.

Developments and applications of the OPTIMADE API for materials discovery, design, and data exchange

The Open Databases Integration for Materials Design (OPTIMADE) application programming interface (API) empowers users with holistic access to a growing federation of databases, enhancing the accessibility and discoverability of materials and chemical data. Since the first release of the OPTIMADE specification (v1.0), the API has undergone significant development, leading to the v1.2 release, and has underpinned multiple scientific studies. In this work, we highlight the latest features of the API format, accompanying software tools, and provide an update on the implementation of OPTIMADE in contributing materials databases. We end by providing several use cases that demonstrate the utility of the OPTIMADE API in materials research that continue to drive its ongoing development.

PyDFT-QMMM: A modular, extensible software framework for DFT-based QM/MM molecular dynamics

PyDFT-QMMM is a Python-based package for performing hybrid quantum mechanics/molecular mechanics (QM/MM) simulations at the density functional level of theory. The program is designed to treat short-range and long-range interactions through user-specified combinations of electrostatic and mechanical embedding procedures within periodic simulation domains, providing necessary interfaces to external quantum chemistry and molecular dynamics software. To enable direct embedding of long-range electrostatics in periodic systems, we have derived and implemented force terms for our previously described QM/MM/PME approach [Pederson and McDaniel, J. Chem. Phys. 156, 174105 (2022)]. Communication with external software packages Psi4 and OpenMM is facilitated through Python application programming interfaces (APIs). The core library contains basic utilities for running QM/MM molecular dynamics simulations, and plug-in entry-points are provided for users to implement custom energy/force calculation and integration routines, within an extensible architecture. The user interacts with PyDFT-QMMM primarily through its Python API, allowing for complex workflow development with Python scripting, for example, interfacing with PLUMED for free energy simulations. We provide benchmarks of forces and energy conservation for the QM/MM/PME and alternative QM/MM electrostatic embedding approaches. We further demonstrate a simple example use case for water solute in a water solvent system, for which radial distribution functions are computed from 100 ps QM/MM simulations; in this example, we highlight how the solvation structure is sensitive to different basis-set choices due to under- or over-polarization of the QM water molecule's electron density.

Improved Dielectric Response of Solids: Combining the Bethe-Salpeter Equation with the Random Phase Approximation

The Bethe-Salpeter equation (BSE) can provide an accurate description of low-energy optical spectra of insulating crystals-even when excitonic effects are important. However, due to high computational costs it is only possible to include a few bands in the BSE Hamiltonian. As a consequence, the dielectric screening given by the real part of the dielectric function can be significantly underestimated by the BSE. Here, we show that universally accurate optical response functions can be obtained by combining a four-point BSE-like equation for the irreducible polarizability with a two-point Dyson equation that includes the higher-lying transitions within the random phase approximation. The new method is referred to as BSE+. It has a computational cost comparable to the BSE but a much faster convergence with respect to the size of the electron-hole basis. We use the method to calculate refractive indices and electron energy loss spectra for a test set of semiconductors and insulators. In all cases the BSE+ yields excellent agreement with experimental data across a wide frequency range and outperforms both the BSE and the random phase approximation.

Orbital-Optimized Versus Time-Dependent Density Functional Calculations of Intramolecular Charge Transfer Excited States

The performance of time-independent, orbital-optimized calculations of excited states is assessed with respect to charge transfer excitations in organic molecules in comparison to the linear-response time-dependent density functional theory (TD-DFT) approach. A direct optimization method to converge on saddle points of the electronic energy surface is used to carry out calculations with the local density approximation (LDA) and the generalized gradient approximation (GGA) functionals PBE and BLYP for a set of 27 excitations in 15 molecules. The time-independent approach is fully variational and provides a relaxed excited state electron density from which the extent of charge transfer is quantified. The TD-DFT calculations are generally found to provide larger charge transfer distances compared to the orbital-optimized calculations, even when including orbital relaxation effects with the Z-vector method. While the error on the excitation energy relative to theoretical best estimates is found to increase with the extent of charge transfer up to ca. -2 eV for TD-DFT, no correlation is observed for the orbital-optimized approach. The orbital-optimized calculations with the LDA and the GGA functionals provide a mean absolute error of ∼0.7 eV, outperforming TD-DFT with both local and global hybrid functionals for excitations with a long-range charge transfer character. Orbital-optimized calculations with the global hybrid functional B3LYP and the range-separated hybrid functional CAM-B3LYP on a selection of states with short- and long-range charge transfer indicate that inclusion of exact exchange has a small effect on the charge transfer distance, while it significantly improves the excitation energy, with the best-performing functional CAM-B3LYP providing an absolute error typically around 0.15 eV.

On transient absorption and dual emission of the atomically precise, DNA-stabilized silver nanocluster Ag16Cl2

DNA-stabilized silver nanoclusters with 10 to 30 silver atoms are interesting biocompatible nanomaterials with intriguing fluorescence properties. However, they are not well understood, since atom-scale high level theoretical calculations have not been possible due to a lack of firm experimental structural information. Here, by using density functional theory (DFT), we study the recently atomically resolved (DNA)2-Ag16Cl2 nanocluster in solvent under the lowest-lying singlet (S1) and triplet (T1) excited states, estimate the relative emission maxima for the allowed (S1 → S0) and dark (T1 → S0) transitions, and evaluate the transient absorption spectra. Our results offer a potential interpretation of the recently reported transient absorption and dual emission of similar DNA-stabilized silver nanoclusters, providing a mechanistic view on their photophysical properties that are attractive for applications in biomedical imaging and biophotonics.