Partial Density of States Representation for Accurate Deep Neural Network Predictions of X-ray Spectra

The performance of a Machine Learning (ML) algorithm for chemistry is highly contingent upon the architect’s choice of input representation. This work introduces the partial density of states (p-DOS) descriptor: a novel, quantum-inspired structural representation which encodes relevant electronic information for machine learning models seeking to simulate X-ray spectroscopy. p-DOS uses a minimal basis set in conjunction with a guess (non-optimised) electronic configuration to extract and then discretise the density of states (DOS) of the absorbing atom to form the input vector. We demonstrate that while the electronically-focused p-DOS performs well in isolation, optimal performance is achieved when supplemented with nuclear structural information imparted via a geometric representation. p-DOS provides a description of the key electronic properties of a system which is not only concise and computationally efficient, but also independent of molecular size or choice of basis set. It can be rapidly generated, facilitating its application with large training sets. Its performance is demonstrated using a wide variety of examples at the sulphur K-edge, including the prediction of ultrafast X-ray spectroscopic signal associated with photoexcited 2(5H)-thiophenone. These results highlight the potential for ML models developed using p-DOS to contribute to the interpretation and prediction of experimental results e.g. in operando measurements of batteries and/or catalysts and femtosecond time-resolved studies, especially those made possible by emergent cutting-edge technologies, especially X-ray free electron lasers.</em

Tracking the ultraviolet-induced photochemistry of thiophenone during and after ultrafast ring opening

Photoinduced isomerization reactions lie at the heart of many chemical processes in nature. The mechanisms of such reactions are determined by a delicate interplay of coupled electronic and nuclear dynamics occurring on the femtosecond scale, followed by the slower redistribution of energy into different vibrational degrees of freedom. Here we apply time-resolved photoelectron spectroscopy with a seeded extreme ultraviolet free-electron laser to trace the ultrafast ring opening of gas-phase thiophenone molecules following ultraviolet photoexcitation. When combined with ab initio electronic structure and molecular dynamics calculations of the excited- and ground-state molecules, the results provide insights into both the electronic and nuclear dynamics of this fundamental class of reactions. The initial ring opening and non-adiabatic coupling to the electronic ground state are shown to be driven by ballistic S–C bond extension and to be complete within 350 fs. Theory and experiment also enable visualization of the rich ground-state dynamics that involve the formation of, and interconversion between, ring-opened isomers and the cyclic structure, as well as fragmentation over much longer timescales

Materials and Molecular Modelling at the Exascale

Progression of computational resources towards exascale computing makes possible simulations of unprecedented accuracy and complexity in the fields of materials and molecular modelling (MMM), allowing high fidelity in silico experiments on complex materials of real technological interest. However, this presents demanding challenges for the software used, especially the exploitation of the huge degree of parallelism available on exascale hardware, and the associated problems of developing effective workflows and data management on such platforms. As part of the UKs ExCALIBUR exascale computing initiative, the UK-led MMM Design and Development Working Group has worked with the broad MMM community to identify a set of high priority application case studies which will drive future exascale software developments. We present an overview of these case studies, categorized by the methodological challenges which will be required to realize them on exascale platforms, and discuss the exascale requirements, software challenges and impact of each application area

Nonadiabatic Kinetics in the Intermediate Coupling Regime: Comparing Molecular Dynamics to an Energy-Grained Master Equation

We propose and test an extension of the energy-grained master equation (EGME) for treating nonadiabatic (NA) hopping between different potential energy surfaces, which enables us to model the competition between stepwise collisional relaxation and kinetic processes which transfer population between different electronic states of the same spin symmetry. By incorporating Zhu–Nakamura theory into the EGME, we are able to treat NA passages beyond the simple Landau–Zener approximation, along with the corresponding treatments of zero-point energy and tunneling probability. To evaluate the performance of this NA-EGME approach, we carried out detailed studies of the UV photodynamics of the volatile organic compound C6-hydroperoxy aldehyde (C6-HPALD) using on-the-fly ab initio molecular dynamics and trajectory surface hopping. For this multichromophore molecule, we show that the EGME is able to capture important aspects of the dynamics, including kinetic timescales, and diabatic trapping. Such an approach provides a promising and efficient strategy for treating the long-time dynamics of photoexcited molecules in regimes which are difficult to capture using atomistic on-the-fly molecular dynamics

TDDFT and quantum-classical dynamics: A universal tool describing the dynamics of matter

Time-dependent density functional theory (TDDFT) is currently the most efficient approach allowing to describe electronic dynamics in complex systems, from isolated molecules to the condensed phase. TDDFT has been employed to investigate an extremely wide range of time-dependent phenomena, as spin dynamics in solids, charge and energy transport in nanoscale devices, and photoinduced exciton transfer in molecular aggregates. It is therefore nearly impossible to give a general account of all developments and applications of TDDFT in material science, as well as in physics and chemistry. A large variety of aspects are covered throughout these volumes. In the present chapter, we will limit our presentation to the description of TDDFT developments and applications in the field of quantum molecular dynamics simulations in combination with trajectory-based approaches for the study of nonadiabatic excited-state phenomena. We will present different quantum-classical strategies used to describe the coupled dynamics of electrons and nuclei underlying nonadiabatic processes. In addition, we will give an account of the most recent applications with the aim of illustrating the nature of the problems that can be addressed with the help of these approaches. The potential, as well as the limitations, of the presented methods is discussed, along with possible avenues for future developments in TDDFT and nonadiabatic dynamics

TDDFT and Quantum-Classical Dynamics: A Universal Tool Describing the Dynamics of Matter

Time-dependent density functional theory (TDDFT) is currently the most efficient approach allowing to describe electronic dynamics in complex systems, from isolated molecules to the condensed phase. TDDFT has been employed to investigate an extremely wide range of time-dependent phenomena, as spin dynamics in solids, charge and energy transport in nanoscale devices, and photoinduced exciton transfer in molecular aggregates. It is therefore nearly impossible to give a general account of all developments and applications of TDDFT in material science, as well as in physics and chemistry. A large variety of aspects are covered throughout these volumes. In the present chapter, we will limit our presentation to the description of TDDFT developments and applications in the field of quantum molecular dynamics simulations in combination with trajectory-based approaches for the study of nonadiabatic excited-state phenomena. We will present different quantum-classical strategies used to describe the coupled dynamics of electrons and nuclei underlying nonadiabatic processes. In addition, we will give an account of the most recent applications with the aim of illustrating the nature of the problems that can be addressed with the help of these approaches. The potential, as well as the limitations, of the presented methods is discussed, along with possible avenues for future developments in TDDFT and nonadiabatic dynamics