The paper discusses the advancements and applications of neural networks, specifically ChatGPT, in various fields, including chemistry education and research. It examines the benefits of AI and ChatGPT, such as their ...The paper discusses the advancements and applications of neural networks, specifically ChatGPT, in various fields, including chemistry education and research. It examines the benefits of AI and ChatGPT, such as their ability to process and analyze large amounts of data, create personalized training systems, and offer problem-solving recommendations. The paper delves into practical applications, showcasing how ChatGPT can be utilised to augment chemistry learning. It provides examples of using ChatGPT for creating tests, generating multiple-choice questions, and studying chemistry in general. Concerns are voiced about the ethical and societal impact of AI development. In conclusion, it explores the exciting potential of AI to tackle challenges that may exceed human capabilities alone, paving the way for further exploration and collaboration between humans and intelligent machines.展开更多
在应变速率为0.1、0.01、0.001s^(-1)和变形温度400、450、500℃条件下采用热模拟试验机对Al-11.5Si-1.6Mg-3.5Cu合金进行了等温热压缩试验,并采用动态材料模型(Dynamic Material Modeling, DMM)绘制材料的热加工图,预测了所设计的钎料...在应变速率为0.1、0.01、0.001s^(-1)和变形温度400、450、500℃条件下采用热模拟试验机对Al-11.5Si-1.6Mg-3.5Cu合金进行了等温热压缩试验,并采用动态材料模型(Dynamic Material Modeling, DMM)绘制材料的热加工图,预测了所设计的钎料合金Al-11.5Si-1.6Mg-3.5Cu与芯材铝合金AA3003的变形机制,从而得到钎料合金和芯材合金共同适合的加工窗口,避免复合轧制过程中出现材料开裂、变形不匹配等问题,缩短试验时间。试验结果表明,当变形温度在400~500℃,应变速率范围为0.001s^(-1)~0.1s^(-1),Al-11.5Si-1.6Mg-3.5Cu合金与芯材合金AA3003在高温变形时不会出现失稳现象,并且在较高的温度和较低的应变速率下比较适合材料的成形加工。展开更多
Laser powder bed fusion(LPBF)is an advanced manufacturing technology;however,inappropriate LPBF process parameters may cause printing defects in materials.In the present work,the LPBF process of Ti-6.5Al-3.5Mo-1.5Zr-0...Laser powder bed fusion(LPBF)is an advanced manufacturing technology;however,inappropriate LPBF process parameters may cause printing defects in materials.In the present work,the LPBF process of Ti-6.5Al-3.5Mo-1.5Zr-0.3Si alloy was investigated by a two-step optimization approach.Subsequently,heat transfer and liquid flow behaviors during LPBF were simulated by a well-tested phenomenological model,and the defect formation mechanisms in the as-fabricated alloy were discussed.The optimized process parameters for LPBF were detected as laser power changed from 195 W to 210 W,with scanning speed of 1250 mm/s.The LPBF process was divided into a laser irradiation stage,a spreading flow stage,and a solidification stage.The morphologies and defects of deposited tracks were affected by liquid flow behavior caused by rapid cooling rates.The findings of this research can provide valuable support for printing defect-free metal components.展开更多
文摘The paper discusses the advancements and applications of neural networks, specifically ChatGPT, in various fields, including chemistry education and research. It examines the benefits of AI and ChatGPT, such as their ability to process and analyze large amounts of data, create personalized training systems, and offer problem-solving recommendations. The paper delves into practical applications, showcasing how ChatGPT can be utilised to augment chemistry learning. It provides examples of using ChatGPT for creating tests, generating multiple-choice questions, and studying chemistry in general. Concerns are voiced about the ethical and societal impact of AI development. In conclusion, it explores the exciting potential of AI to tackle challenges that may exceed human capabilities alone, paving the way for further exploration and collaboration between humans and intelligent machines.
文摘在应变速率为0.1、0.01、0.001s^(-1)和变形温度400、450、500℃条件下采用热模拟试验机对Al-11.5Si-1.6Mg-3.5Cu合金进行了等温热压缩试验,并采用动态材料模型(Dynamic Material Modeling, DMM)绘制材料的热加工图,预测了所设计的钎料合金Al-11.5Si-1.6Mg-3.5Cu与芯材铝合金AA3003的变形机制,从而得到钎料合金和芯材合金共同适合的加工窗口,避免复合轧制过程中出现材料开裂、变形不匹配等问题,缩短试验时间。试验结果表明,当变形温度在400~500℃,应变速率范围为0.001s^(-1)~0.1s^(-1),Al-11.5Si-1.6Mg-3.5Cu合金与芯材合金AA3003在高温变形时不会出现失稳现象,并且在较高的温度和较低的应变速率下比较适合材料的成形加工。
基金Supported by Development of a Verification Platform for Product Design,Process and Information Exchange Standards in Additive Manufacturing (Grant No.2019-00899-1-1)Ministry of Science and Technology of the People’s Republic of China (Grant No.2017YFB1103000)+1 种基金National Natural Science Foundation of China (Grant No.51375242)Natural Science Foundation of Jiangsu Province (Grant No.BK20180483)。
文摘Laser powder bed fusion(LPBF)is an advanced manufacturing technology;however,inappropriate LPBF process parameters may cause printing defects in materials.In the present work,the LPBF process of Ti-6.5Al-3.5Mo-1.5Zr-0.3Si alloy was investigated by a two-step optimization approach.Subsequently,heat transfer and liquid flow behaviors during LPBF were simulated by a well-tested phenomenological model,and the defect formation mechanisms in the as-fabricated alloy were discussed.The optimized process parameters for LPBF were detected as laser power changed from 195 W to 210 W,with scanning speed of 1250 mm/s.The LPBF process was divided into a laser irradiation stage,a spreading flow stage,and a solidification stage.The morphologies and defects of deposited tracks were affected by liquid flow behavior caused by rapid cooling rates.The findings of this research can provide valuable support for printing defect-free metal components.