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| http://dx.doi.org/10.1073/pnas.1420577112 | DOI Listing |
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Improved Description of Environment and Vibronic Effects with Electrostatically Embedded ML Potentials.
J Phys Chem Lett
January 2025
Departament de Farmàcia i Tecnologia Farmacèutica, i Fisicoquímica, Facultat de Farmàcia i Ciències de l'Alimentació, Universitat de Barcelona (UB), 08028 Barcelona, Spain.
Incorporation of environment and vibronic effects in simulations of optical spectra and excited state dynamics is commonly done by combining molecular dynamics with excited state calculations, which allows to estimate the spectral density describing the frequency-dependent system-bath coupling strength. The need for efficient sampling, however, usually leads to the adoption of classical force fields despite well-known inaccuracies due to the mismatch with the excited state method. Here, we present a multiscale strategy that overcomes this limitation by combining EMLE simulations based on electrostatically embedded ML potentials with the QM/MMPol polarizable embedding model to compute the excited states and spectral density of 3-methyl-indole, the chromophoric moiety of tryptophan that mediates a variety of important biological functions, in the gas phase, in water solution, and in the human serum albumin protein.
View Article and Find Full Text PDFLiquid-Vapor Phase Equilibrium in Molten Aluminum Chloride (AlCl) Enabled by Machine Learning Interatomic Potentials.
J Phys Chem B
January 2025
Chemical Sciences Division, Oak Ridge National Laboratory, Oak Ridge, Tennessee 37830, United States.
Molten salts are promising candidates in numerous clean energy applications, where knowledge of thermophysical properties and vapor pressure across their operating temperature ranges is critical for safe operations. Due to challenges in evaluating these properties using experimental methods, fast and scalable molecular simulations are essential to complement the experimental data. In this study, we developed machine learning interatomic potentials (MLIP) to study the AlCl molten salt across varied thermodynamic conditions ( = 473-613 K and = 2.
View Article and Find Full Text PDFInvestigation of Metal Tellurides As Cathode Materials for High-Energy Lithium-Tellurium Batteries.
ACS Appl Mater Interfaces
January 2025
Department of Energy Engineering, Hanyang University, Seoul 04763, Republic of Korea.
Lithium-tellurium (Li-Te) batteries are gaining attention as a promising next-generation energy storage system due to their superior electrical conductivity and high volumetric capacity compared to sulfur and selenium. Tellurium's unique properties, such as suitable redox potential, excellent conductivity, high volumetric capacity, and greatest stability, position it as a strong candidate for negative electrode materials. This study explores the potential of metal tellurides, specifically CuTe and FeTe monolayers, as effective tellurium host materials, leveraging their polar interactions with lithium polytellurides.
View Article and Find Full Text PDFUnveiling hidden reaction kinetics of carbon dioxide in supercritical aqueous solutions.
Proc Natl Acad Sci U S A
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Department of Physics, The Hong Kong University of Science and Technology, Hong Kong, China.
Dissolution of CO in water followed by the subsequent hydrolysis reactions is of great importance to the global carbon cycle, and carbon capture and storage. Despite numerous previous studies, the reactions are still not fully understood at the atomistic scale. Here, we combined ab initio molecular dynamics (AIMD) simulations with Markov state models to elucidate the reaction mechanisms and kinetics of CO in supercritical water both in the bulk and nanoconfined states.
View Article and Find Full Text PDFMechanistic Understanding of the pH-Dependent Oxygen Reduction Reaction on the Fe-N-C Surface: Linking Surface Charge to Adsorbed Oxygen-Containing Species.
ACS Appl Mater Interfaces
January 2025
Center of Nanomaterials for Renewable Energy (CNRE), State Key Laboratory of Electrical Insulation and Power Equipment, School of Electrical Engineering, Xi'an Jiaotong University, Xi'an 710049, P. R. China.
The Fe-N-C catalyst, featuring a single-atom Fe-N configuration, is regarded as one of the most promising catalytic materials for the oxygen reduction reaction (ORR). However, the significant activity difference under acidic and alkaline conditions of Fe-N-C remains a long-standing puzzle. In this work, using extensive ab initio molecular dynamics (AIMD) simulations, we revealed that pH conditions influence ORR activity by tuning the surface charge density of the Fe-N-C surface, rather than through the direct involvement of HO or OH ions.
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