Data from Department of Environmental Sciences and Engineering Provide New Insig hts into Machine Learning (Single-atom Catalysts Property Prediction Via Supervi sed and Self-supervised Pre-training Models)

来自环境科学与工程系的数据为机器学习提供了新的内部高温超导（通过监督和自我监督的预培训模型进行单原子催化剂性能预测）

Robotics & Machine Learning Daily News2024，Issue(Jun.10) ：102-102.

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Data from Department of Environmental Sciences and Engineering Provide New Insig hts into Machine Learning (Single-atom Catalysts Property Prediction Via Supervi sed and Self-supervised Pre-training Models)

来自环境科学与工程系的数据为机器学习提供了新的内部高温超导（通过监督和自我监督的预培训模型进行单原子催化剂性能预测）

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摘要

由一名新闻记者-机器人与机器学习的工作人员新闻编辑每日新闻-研究人员详细介绍了机器学习的新数据。根据NewsRx记者在中华人民共和国江苏的新闻报道，研究称：“机器学习凭借其在识别材料属性方面的强大预测能力，已经成为追求新材料发现和设计的不可或缺的工具。它对先进催化剂设计的特殊影响正在开启各种科学学科的突破。”

Abstract

By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News-Researchers detail new data in Machine Learning. According to news reporting from Jiangsu, People’s Republic of China, by NewsRx journalists, research stated, “Machine learning, by virtue of its pow erful predictive capabilities in discerning material properties, has emerged as an indispensable tool in the pursuit of new material discovery and design. Its s pecific impact on advanced catalyst design is unlocking breakthroughs across var ious scientific disciplines.”

Key words

Jiangsu/People’s Republic of China/Asia/Cyborgs/Emerging Technologies/Machine Learning/Department of Environmental Sciences and Engineering

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出版年

2024

Robotics & Machine Learning Daily News

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