论文标题
材料工程中的人工智能：对AI在材料工程中应用的审查
Artificial Intelligence in Material Engineering: A review on applications of AI in Material Engineering
论文作者
论文摘要
随着AI技术的发展，人工智能（AI）在材料科学和工程（MSE）中的作用变得越来越重要。高性能计算的开发使得具有重要参数的深度学习模型成为可能，从而在财产预测中提供了克服传统计算方法的限制，例如密度功能理论（DFT）。基于机器学习（ML）的方法比基于DFT的方法更快，更准确。此外，生成的对抗网络（GAN）促进了无机材料的化学成分，而无需使用晶体结构信息。这些发展对材料工程（ME）和研究产生了重大影响。审查了我本文中AI的一些最新发展。首先，讨论了在我关键领域中的AI发展，例如在材料处理，结构和材料特性的研究中以及在各个方面的材料性能进行测量。然后，讨论了AI及其在MSE中的重要方法，例如图神经网络，生成模型，学习的转移等。还讨论了使用AI来分析现有分析工具的结果。最后，讨论了AI的优势，缺点和未来。
The role of artificial intelligence (AI) in material science and engineering (MSE) is becoming increasingly important as AI technology advances. The development of high-performance computing has made it possible to test deep learning (DL) models with significant parameters, providing an opportunity to overcome the limitation of traditional computational methods, such as density functional theory (DFT), in property prediction. Machine learning (ML)-based methods are faster and more accurate than DFT-based methods. Furthermore, the generative adversarial networks (GANs) have facilitated the generation of chemical compositions of inorganic materials without using crystal structure information. These developments have significantly impacted material engineering (ME) and research. Some of the latest developments in AI in ME herein are reviewed. First, the development of AI in the critical areas of ME, such as in material processing, the study of structure and material property, and measuring the performance of materials in various aspects, is discussed. Then, the significant methods of AI and their uses in MSE, such as graph neural network, generative models, transfer of learning, etc. are discussed. The use of AI to analyze the results from existing analytical instruments is also discussed. Finally, AI's advantages, disadvantages, and future in ME are discussed.
