计算材料科学是材料、计算机、物理、化学等多学科的交叉领域,主要研究材料多尺度构效关系的建立及新材料设计。主要面向材料科学及相关专业的学生,是材料研发的三大支柱(实验/理论/计算)之一。通过数值计算和人工智能技术,进行多尺度模拟,帮助理解材料机理、设计新材料。它连接理论和实验,既能验证理论模型,又能预测实验结果,指导实际应用。随着大数据和机器学习的发展,计算材料科学从传统模拟转向数据驱动的智能设计,改变了传统“试错法”研发模式,加速了新材料的开发。对高校和科研机构来说,加强计算材料科学的教学和研究,有助于培养跨学科、创新能力强的高水平科研人才,推动材料科学的进步和产业升级。
相关资料Learning Materials
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Universal Maximum Strength of Solid Metals and Alloys
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Ultimate Strength of Metals
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Identifying facile material descriptors for Charpy impact toughness in low-alloy steel via machine learning
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Physical mechanism interpretation of polycrystalline metals’ yield strength via a data-driven method: A novel Hall–Petch relationship
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Correlating dislocation mobility with local lattice distortion in refractory multi-principal element alloys
Multi-principal element alloys (MPEAs) e···
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