Progress in the theory of x-ray spectroscopy: From quantum chemistry to machine learning and ultrafast dynamics

CD Rankine, TJ Penfold - The Journal of Physical Chemistry A, 2021 - ACS Publications
The development of high-brilliance third-and fourth-generation light sources such as
synchrotrons and X-ray free-electron lasers (XFELs), the emergence of laboratory-based X …

Gaining More Insights from Synchrotron-Based X-ray Spectroscopy for Alkali Ion Rechargeable Batteries

S Chen, S Jiao, Q Liang, P Li, J Yin, Q Li… - Analytical …, 2024 - ACS Publications
Alkali ion rechargeable batteries play a significant part in portable electronic devices and
electronic vehicles. The rapid development of renewable energy technology nowadays …

[HTML][HTML] Machine-Learning Strategies for the Accurate and Efficient Analysis of X-ray Spectroscopy

T Penfold, L Watson, C Middleton… - Machine Learning …, 2024 - iopscience.iop.org
Computational spectroscopy has emerged as a critical tool for researchers looking to
achieve both qualitative and quantitative interpretations of experimental spectra. Over the …

Latent representation learning for structural characterization of catalysts

PK Routh, Y Liu, N Marcella, B Kozinsky… - The Journal of …, 2021 - ACS Publications
Supervised machine learning-enabled mapping of the X-ray absorption near edge structure
(XANES) spectra to local structural descriptors offers new methods for understanding the …

Accurate, affordable, and generalizable machine learning simulations of transition metal x-ray absorption spectra using the XANESNET deep neural network

CD Rankine, TJ Penfold - The Journal of Chemical Physics, 2022 - pubs.aip.org
The affordable, accurate, and generalizable prediction of spectroscopic observables plays a
key role in the analysis of increasingly complex experiments. In this article, we develop and …

Materials characterization: Can artificial intelligence be used to address reproducibility challenges?

ML Lau, A Burleigh, J Terry, M Long - Journal of Vacuum Science & …, 2023 - pubs.aip.org
Material characterization techniques are widely used to characterize the physical and
chemical properties of materials at the nanoscale and, thus, play central roles in material …

Towards the automated extraction of structural information from X-ray absorption spectra

T David, NKN Aznan, K Garside, T Penfold - Digital Discovery, 2023 - pubs.rsc.org
X-ray absorption near-edge structure (XANES) spectroscopy is widely used across the
natural sciences to obtain element specific atomic scale insight into the structure of matter …

Beyond structural insight: a deep neural network for the prediction of Pt L 2/3-edge X-ray absorption spectra

L Watson, CD Rankine, TJ Penfold - Physical Chemistry Chemical …, 2022 - pubs.rsc.org
X-ray absorption spectroscopy at the L2/3 edge can be used to obtain detailed information
about the local electronic and geometric structure of transition metal complexes. By virtue of …

Toward the Atomic-Level Analysis of Ground-State Electronic Structures of Solid Materials via Prediction from Core-Loss Spectra: A Computational Study in Si

I Takahara, F Uesugi, K Kimoto, K Shibata… - The Journal of …, 2024 - ACS Publications
Local electronic structure in the ground state is essential for understanding the stability and
properties of materials. Core-loss spectroscopy using electron or X-ray provides insights into …

Local structure study of the Fe ions in mixed-valence iron (II)-iron (III) metal formate frameworks

E Piskorska-Hommel, A Ciupa-Litwa - Polyhedron, 2022 - Elsevier
Abstract X-ray Absorption Spectroscopy (XAS) methods have been used to study the mixed-
valence iron (II)-iron (III) metal–organic frameworks (MOFs) that undergo order–disorder …