Robotics & Machine Learning Daily News2024,Issue(Jul.23) :48-49.

Sorbonne Universite Reports Findings in Machine Learning (Accelerating QM/MM sim ulations of electrochemical interfaces through machine learning of electronic ch arge densities)

Robotics & Machine Learning Daily News2024,Issue(Jul.23) :48-49.

Sorbonne Universite Reports Findings in Machine Learning (Accelerating QM/MM sim ulations of electrochemical interfaces through machine learning of electronic ch arge densities)

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Abstract

By a News Reporter-Staff News Editor at Robotics & Machine Learning DailyNews Daily News - New research on Machine Learning is th e subject of a report. According to newsreporting originating from Paris, Franc e, by NewsRx correspondents, research stated, “A crucial aspect inthe simulatio n of electrochemical interfaces consists in treating the distribution of electro nic charge ofelectrode materials that are put in contact with an electrolyte so lution. Recently, it has been shown howa machine-learning method that specifica lly targets the electronic charge density, also known as SALTED,can be used to predict the long-range response of metal electrodes in model electrochemical cel ls.”

Key words

Paris/France/Europe/Chemicals/Cyborg s/Electrochemicals/Emerging Technologies/Machine Learning

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出版年

2024
Robotics & Machine Learning Daily News

Robotics & Machine Learning Daily News

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