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Computing chemical potentials with machine-learning-accelerated simulations to accurately predict thermodynamic properties of molten salts.
Chem Sci
January 2025
Chemical Sciences Division, Oak Ridge National Laboratory Oak Ridge TN 37830 USA
The successful design and deployment of next-generation nuclear technologies heavily rely on thermodynamic data for relevant molten salt systems. However, the lack of accurate force fields and efficient methods has limited the quality of thermodynamic predictions from atomistic simulations. Here we propose an efficient free energy framework for computing chemical potentials, which is the central free energy quantity behind many thermodynamic properties.
View Article and Find Full Text PDFIs the Future of Materials Amorphous? Challenges and Opportunities in Simulations of Amorphous Materials.
ACS Phys Chem Au
January 2025
Department of Chemistry, McGill University, Montréal, Québec H3A 0B8, Canada.
Amorphous solids form an enormous and underutilized class of materials. In order to drive the discovery of new useful amorphous materials further we need to achieve a closer convergence between computational and experimental methods. In this review, we highlight some of the important gaps between computational simulations and experiments, discuss popular state-of-the-art computational techniques such as the Activation Relaxation Technique (ARTn) and Reverse Monte Carlo (RMC), and introduce more recent advances: machine learning interatomic potentials (MLIPs) and generative machine learning for simulations of amorphous matter (e.
View Article and Find Full Text PDFCombining Brillouin Light Scattering Spectroscopy and Machine-Learned Interatomic Potentials to Probe Mechanical Properties of Metal-Organic Frameworks.
J Phys Chem Lett
January 2025
Institute of Bioproducts and Paper Technology, Graz University of Technologyy, Inffeldgasse 23, 8010 Graz, Austria.
The mechanical properties of metal-organic frameworks (MOFs) are of high fundamental and practical relevance. A particularly intriguing technique for determining anisotropic elastic tensors is Brillouin scattering, which so far has rarely been used for highly complex materials like MOFs. In the present contribution, we apply this technique to study a newly synthesized MOF-type material, referred to as GUT2.
View Article and Find Full Text PDFSlowly quenched, high pressure glassy B2O3 at DFT accuracy.
J Chem Phys
January 2025
Chemistry and Physics of Materials Unit, Jawaharlal Nehru Centre for Advanced Scientific Research, Bangalore 560064, India.
Modeling inorganic glasses requires an accurate representation of interatomic interactions, large system sizes to allow for intermediate-range structural order, and slow quenching rates to eliminate kinetically trapped structural motifs. Neither first principles-based nor force field-based molecular dynamics (MD) simulations satisfy these three criteria unequivocally. Herein, we report the development of a machine learning potential (MLP) for a classic glass, B2O3, which meets these goals well.
View Article and Find Full Text PDFHighly Efficient Degradation of Bisphenol A by Peroxymonosulfate Activation Using Bamboo Kraft Lignin Single-Atom Catalyst.
Small
January 2025
Key Lab of Bamboo and Rattan Science & Technology, International Center for Bamboo and Rattan, Beijing, 100102, P. R. China.
A nitrogen-coordinated Fe single-atom catalyst (SA Fe-N/C) is synthesized using a homogeneous ethanol-based dissolution system with bamboo kraft lignin serving as the carbon source. Uniformly dispersed Fe atoms with an interatomic distance of less than 2 Å throughout the SA Fe-N/C structure are revealed through X-ray absorption spectral analysis and HAADF-STEM images, which possessed a high Fe loading of 2.69%.
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