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20250166741. Machine Learning (ml) (Central South University)

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MACHINE LEARNING (ML)-ACCELERATED FIRST-PRINCIPLES PREDICTION METHOD FOR HYDRATION STRUCTURE OF ACID RADICAL ANION

Abstract: a machine learning (ml)-accelerated first-principles prediction method for a hydration structure of an acid radical anion is provided. the prediction method includes the following steps: s1: constructing and optimizing an anion hydration structure m_mho; s2: perturbing the optimized anion hydration structure to generate a training dataset; s3: conducting a ml force field training on the training dataset to establish ml models; s4: conducting a molecular dynamics simulation on the ml models, and identifying atomic structures with a force deviation within a preset range as candidate configurations; s5: merging a validated candidate configuration into a training set for a subsequent iteration to further refine and train the ml model until the model converges, thereby generating an accurate deep potential (dp) model; and s6: conducting a ml-accelerated deep potential molecular dynamics simulation on the dp model to ultimately acquire the hydration structure of the acid radical anion.

Inventor(s): Chenyang ZHANG, Mingjun HAN, Dong FAN, Wei SUN, Jie LI, Yong PEI, Guixiang ZENG, Shangyong LIN, Hongliang ZHANG, Rong WANG

CPC Classification: G16C20/70 (Machine learning, data mining or chemometrics)

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