摘要
一位新闻记者-机器人与机器学习的工作人员新闻编辑每日新闻-机器学习的研究结果在一份新的报告中讨论。根据NewsRx编辑在艾奥瓦艾姆斯的新闻报道，research称：“我们采用深度机器学习(ML)结合第一性原理计算，探索能量有利的三元金属硼氢化物。使用la-b-h作为原型系统，通过第一性原理的计算，证明了迭代训练的ML模型可以有效地筛选数十万个假设结构，并准确地选择一小部分有希望的结构和组成进行进一步研究。本研究的资助者包括山东省自然科学基金、美国能源部(DOE)、美国能源部(DOE)、山东省自然科学基金。
Abstract
By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News-Research findings on Machine Learning are discussed in a new report. According to news reporting out of Ames, Iowa, by NewsRx editors, research stated, "We employ deep machine learning (ML) combined with first-principles calculations to explore energetically favorable ternary m etal borohydrides. Using La-B-H as a prototype system, we demonstrate that itera tively trained ML models can efficiently screen hundreds of thousands of hypothe tical structures and accurately select a small fraction of promising structures and compositions for further studies by first-principles calculations." Funders for this research include Natural Science Foundation of Shandong Provinc e, United States Department of Energy (DOE), United States Department of Energy (DOE), Natural Science Foundation of Shandong Province.
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