近年来，我国在AI领域取得了举世瞩目的成就，而这一次，中科院物理所等机构再次成为了焦点。据报道，中科院物理所等发布AI模型MatChat，用于预测无机材料合成路径。该模型的研发，将极大地促进材料科学领域的发展。
据悉，MatChat模型是由中国科学院物理研究所/北京凝聚态物理国家研究中心SF10组和中国科学院计算机网络信息中心共同合作完成的。合作团队将数万个化学合成路径数据投喂给大语言模型LLAMA2-7b，从而获得了MatChat模型。这一模型可以用于预测无机材料的合成路径，为我国材料科学领域的研究提供了有力的支持。
事实上，AI技术在材料科学领域的研究中已经取得了显著的成果。而这一次，MatChat模型的发布，无疑将极大地推动该领域的技术革新。值得注意的是，MatChat模型的研发过程中，涉及了多个学科领域，包括计算机科学、语言学等，这也体现了学科交叉与融合的重要性。
英文标题：AI model predicts synthetic paths for inorganic materials, significant breakthrough by China’s National Academy of Sciences
关键词：AI model, inorganic materials, synthetic paths, National Academy of Sciences
新闻内容：
Recently, a significant breakthrough has been made in the field of artificial intelligence (AI) in China, where the National Academy of Sciences (CAS) has released an AI model called MatChat for predicting the synthesis paths of inorganic materials. This development is likely to drive significant advancements in the field of materials science and technology in China.
据了解，MatChat model, developed by the Institute of Physics, Chinese Academy of Sciences and Beijing National Collaborative Center for Advanced Technology in Condensed Matter Physics, uses a large language model LLAMA2-7b, which has been trained on tens of thousands of chemical synthesis path data, to predict the synthesis paths of inorganic materials. This innovative model can be used to guide research in the development of new inorganic materials, providing powerful support for the study of materials science in China.
In fact, AI technology has already made significant strides in the field of materials science and technology, and this time, the release of MatChat model is likely to further push the boundaries of research in this area. Notably, the development of MatChat model involves multiple disciplines, including computer science, linguistics, and more, demonstrating the importance of interdisciplinary collaboration and integration.
【来源】https://news.cnstock.com/news,bwkx-202311-5145649.htm
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