
Chemical Physics Reviews
@chemphysrev
CPR is a new journal featuring reviews and original research covering all areas of chemical physics. Published by @AIP_Publishing.
ID: 1194624850377220096
https://pubs.aip.org/aip/cha 13-11-2019 14:35:50
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Atomic clusters are intriguing to researchers. We present details of their structure-property relationships to rationalise the observations and guide future applications. ChemE IIT Jodhpur Learn more 👇 aippub.org/4dsrarS


We review the different approaches to the modelling of the kinetics of exciton decay in materials that emit via thermally activated delayed fluorescence. EZ-C Group @StAndrewsOSC Eli Zysman-Colman St Andrews School of Chemistry Learn more 👇 aippub.org/4gI0Blx

Incorporating quantum nuclear delocalization via the CNEO-QM/MM framework reveals significant differences in hydrogen bond geometries and dynamics compared to conventional QM/MM. Yang Group TCI UW-Madison Learn more 👇 aippub.org/3OqPznY

Modeling the Lithium dendrite formation sites/scenarios in the solid electrolyte interphase – a multi-component structure in Li-ion batteries, using high-throughput DFT-NEB and ML techniques. Utah State Science Learn more 👇 aippub.org/495EDp3

We discuss how 2D electronic spectroscopy can be applied to exciton-polaritons to reveal previously hidden information about the photophysics of energy relaxation in these hybrid photonic materials. Minjung Son BU Chemistry Learn more 👇 aippub.org/4iYjBgU

Focusing on molecular materials, we outline the theoretical background of exchange coupling and review available methods for its characterization in the electronic ground and excited states aippub.org/3WBRsCD Sabine Richert, Universität Freiburg

Exploring the potential of machine learning to predict material properties from chemical composition, with a focus on physics-guided ML for accurate, interpretable predictions in materials science. aippub.org/3En7N7O Mohammed Alghadeer

We review theory of kernel regressions & applications in materials informatics, highlighting relations between different flavors of the method and other ML methods. Kernel designs are also reviewed. Science Tokyo (Institute of Science Tokyo) Learn more 👇 aippub.org/4kroQq0



With the relationships between all the most popular polariton Hamiltonians clearly derived in one place, cavity polariton theory becomes more accessible for both new and established researchers. Huo Group @UofR Learn more 👇 aippub.org/4kDY8L0

Chemical Physics Reviews Editor-in-Chief Phil Castellano is presenting tomorrow at #ACSSpring2025! Learn more 👇 aippub.org/4bYgAd8







