首页|Findings from Southwest Petroleum University Update Knowledge of Machine Learnin g (A Prediction Model for Co2/co Adsorption Performance On Binary Alloys Based O n Machine Learning)
Findings from Southwest Petroleum University Update Knowledge of Machine Learnin g (A Prediction Model for Co2/co Adsorption Performance On Binary Alloys Based O n Machine Learning)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – A new study on Machine Learning is now available. According to news reporting out of Chengdu, People’s Republic of Chi na, by NewsRx editors, research stated, “Despite the rapid development of comput ational methods, including density functional theory (DFT), predicting the perfo rmance of a catalytic material merely based on its atomic arrangements remains c hallenging. Although quantum mechanics-based methods can model ‘real’ materials with dopants, grain boundaries, and interfaces with acceptable accuracy, the hig h demand for computational resources no longer meets the needs of modern scienti fic research.”
ChengduPeople’s Republic of ChinaAsi aAlloysCyborgsEmerging TechnologiesMachine LearningSouthwest Petroleum University
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