多尺度晶体材料的原位表征技术与计算模拟研究进展
陈昆峰1(
), 胡乾宇1, 刘锋2, 薛冬峰2()
), 胡乾宇1, 刘锋2, 薛冬峰2()
Multi-scale Crystallization Materials: Advances in in-situ Characterization Techniques and Computational Simulations
CHEN Kunfeng1(), HU Qianyu1, LIU Feng2, XUE Dongfeng2()
), HU Qianyu1, LIU Feng2, XUE Dongfeng2()
图7. 基于人工智能预测生长炉内状态, 平均预测时间可达到0.0003 s[
Fig. 7. Based on artificial intelligence, the average prediction time of the growth furnace state reaching 0.0003 s[
