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Machine Learning Quantum Mechanical/Molecular Mechanical Potentials: Evaluating Transferability in Dihydrofolate Reductase-Catalyzed Reactions.
J Chem Theory Comput
January 2025
Department of Chemistry and Biochemistry, University of Texas at Arlington, Arlington, Texas 76019, United States.
Integrating machine learning potentials (MLPs) with quantum mechanical/molecular mechanical (QM/MM) free energy simulations has emerged as a powerful approach for studying enzymatic catalysis. However, its practical application has been hindered by the time-consuming process of generating the necessary training, validation, and test data for MLP models through QM/MM simulations. Furthermore, the entire process needs to be repeated for each specific enzyme system and reaction.
View Article and Find Full Text PDFAdjustment of Molecular Sorption Equilibrium on Catalyst Surface for Boosting Catalysis.
Acc Chem Res
January 2025
Key Lab of Biomass Chemical Engineering of Ministry of Education, College of Chemical and Biological Engineering, Zhejiang University, Hangzhou 310027, China.
ConspectusFor chemical reactions with complex pathways, it is extremely difficult to adjust the catalytic performance. The previous strategies on this issue mainly focused on modifying the fine structures of the catalysts, including optimization of the geometric/electronic structure of the metal nanoparticles (NPs), regulation of the chemical composition/morphology of the supports, and/or adjustment of the metal-support interactions to modulate the reaction kinetics on the catalyst surface. Although significant advances have been achieved, the catalytic performance is still unsatisfactory.
View Article and Find Full Text PDFMagnetofluidic-Assisted Portable Automated Microfluidic Devices for Protein Detection.
Anal Chem
January 2025
State Key Laboratory of Chemo/Biosensing and Chemometrics, College of Chemistry and Chemical Engineering, Key Laboratory for Bio-Nanotechnology and Molecular Engineering of Hunan Province, Hunan University, Changsha 410082, China.
To facilitate on-site detection by nonspecialists, there is a demand for the development of portable "sample-to-answer" devices capable of executing all procedures in an automated or easy-to-operate manner. Here, we developed an automated detection device that integrated a magnetofluidic manipulation system and a signal acquisition system. Both systems were controllable via a smartphone.
View Article and Find Full Text PDFStructural Transformation and Degradation of Cu Oxide Nanocatalysts during Electrochemical CO Reduction.
J Am Chem Soc
January 2025
Liquid Sunlight Alliance, Lawrence Berkeley National Laboratory, 1 Cyclotron Road, Berkeley, California 94720, United States.
The electrochemical CO reduction reaction (CORR) holds enormous potential as a carbon-neutral route to the sustainable production of fuels and platform chemicals. The durability for long-term operation is currently inadequate for commercialization, however, and the underlying deactivation process remains elusive. A fundamental understanding of the degradation mechanism of electrocatalysts, which can dictate the overall device performance, is needed.
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