个人信息Personal Information
学历：博士研究生毕业
学位：工学博士学位
性别：男
学科：力学. 航空宇航科学与技术. 材料科学与工程. 机械工程. 冶金工程. 先进制造. 航空工程. 材料工程. 冶金工程. 机械工程. 固体力学
多尺度力学，宏微观力学，梯度结构材料，界面力学，固体本构关系，应变梯度理论，晶体塑性有限元，离散位错动力学，分子动力学，高熵合金，大数据与机器学习，材料基因，极端力学，高性能材料，材料的增强与增韧
报考该导师研究生的方式
欢迎你报考张旭老师的研究生，报考有以下方式：
1、参加西南交通大学暑期夏令营活动，提交导师意向时，选择张旭老师，你的所有申请信息将发送给张旭老师，老师看到后将和你取得联系，点击此处参加夏令营活动
2、如果你能获得所在学校的推免生资格，欢迎通过推免方式申请张旭老师研究生，可以通过系统的推免生预报名系统提交申请，并选择意向导师为张旭老师，老师看到信息后将和你取得联系，点击此处推免生预报名
3、参加全国硕士研究生统一招生考试报考张旭老师招收的专业和方向，进入复试后提交导师意向时选择张旭老师。
4、如果你有兴趣攻读张旭老师博士研究生，可以通过申请考核或者统一招考等方式报考该导师博士研究生。
一、期刊论文
在Journal of the Mechanics and Physics of Solids（3篇）、International Journal of Plasticity（22篇）、Acta Materialia（4篇）、International Journal of Mechanical Sciences（9篇）、Materials Science and Engineering A（7篇）、《力学学报（中英文版）》（11篇）、《中国科学（中英文版）》（3篇）等专业期刊以及Advanced Science、Nature Communications等综合性期刊上发表论文160余篇，其中SCI论文129余篇，其中ESI 高引论文 3 篇。
论文Google Scholar引用3800余次，SCI引用3000余次，H-index 30 (来自Web of Science)，3篇论文入选ESI高被引，1篇论文被Acta Mechnica Sinica选为封面推介，1篇论文被Journal of Material Research 期刊选为Feature论文，1篇论文被Computational Materials Science选为"Editor's Choice"。
研究方向一：先进金属材料力学行为（高熵合金、梯度结构材料等）
核心内容：针对高熵合金、梯度纳米结构材料、层状异构材料等先进金属材料，通过实验、多尺度模拟与理论分析相结合，研究其独特的强化-塑性协同机制、变形与断裂机理。
代表性论文：
Shuang, S., Hu, Y., Li, X., Yuan, F., Kang, G., Gao, H., and Zhang, X., Tuning chemical short-order for simultaneous strength and toughness enhancement in NiCoCr medium-entropy alloys. International Journal of Plasticity, 2024.
Zhang, X., Gui, Y., Lai, M., Lu, X., Gu, J., Wang, F., Yang, T., Wang, Z., and Song, M., Enhanced strength-ductility synergy of medium-entropy alloys via multiple level gradient structures. International Journal of Plasticity, 2023.
Zhao, J., Kan, Q., Zhou, L., Kang, G., Fan, H., and Zhang, X., Deformation mechanisms based constitutive modelling and strength-ductility mapping of gradient nano-grained materials. Materials Science and Engineering: A, 2019.
Lu, X., Gui, Y., Fu, Z., Ao, N., Wu, S., and Zhang, X., Mechanical behavior and microstructure-property correlation of a metastable interstitial high entropy alloy with hierarchical gradient structures. Materials Characterization, 2023.
Fan, L., Xiong, Y., Zeng, Y., Ni, R., Zhang, Y., Ren, L., Dieringa, H., Huang, Y., Quan, G., and Zhang, X., The strength-ductility synergy of magnesium matrix nanocomposite achieved by a dual-heterostructure. Journal of Materials Science & Technology, 2025.
研究方向二：晶体塑性本构建模与计算（CPFEM）
核心内容：开发晶体塑性本构模型，并利用晶体塑性有限元法（CPFEM）模拟多晶材料的宏观力学响应，揭示微观组织（织构、晶粒形态等）与宏观性能的关系。
代表性论文：
Xiong, Y., Zhao, J., Shi, L., Lai, R., Guo, S., Lei, L., Wu, S., Kang, G., and Zhang, X., Microstructure-sensitive fracture in additive manufactured Ni-based superalloys: A coupled crystal plasticity and phase-field modeling. Engineering Fracture Mechanics, 2025.
Lu, X., Zhang, X., Shi, M., Roters, F., Kang, G., and Raabe, D., Dislocation mechanism based size-dependent crystal plasticity modeling and simulation of gradient nano-grained copper. International Journal of Plasticity, 2019.
Lu, X., Zhao, J., Wang, Z., Gan, B., Zhao, J., Kang, G., and Zhang, X., Crystal plasticity finite element analysis of gradient nanostructured TWIP steel. International Journal of Plasticity, 2020.
Song, S., Kan, Q., Liu, Y., Bao, C., Lu, X., and Zhang, X., Tensile and creep behavior of 316L austenite stainless steel at elevated temperatures: experiment and crystal plasticity modeling. Acta Mechanica Sinica, 2024.
熊宇凯, 赵建锋, 饶威, 黄志勇, 康国政, 张旭. 含冷却孔镍基合金次级取向效应的应变梯度晶体塑性有限元研究. 力学学报, 2023.
研究方向三：离散位错动力学（DDD）
核心内容：运用离散位错动力学（DDD）方法，从位错机制层面揭示材料的塑性变形起源、位错-界面交互作用及尺寸效应。
代表性论文：
Lu, S., Kan, Q., Zaiser, M., Li, Z., Kang, G., and Zhang, X., Size-dependent yield stress in ultrafine-grained polycrystals: A multiscale discrete dislocation dynamics study. International Journal of Plasticity, 2022.
Zhang, X., Xiong, J., Fan, H., and Zaiser, M., Microplasticity and yielding in crystals with heterogeneous dislocation distribution. Modelling and Simulation in Materials Science and Engineering, 2019.
Wei, D., Zaiser, M., Feng, Z., Kang, G., Fan, H., and Zhang, X., Effects of twin boundary orientation on plasticity of bicrystalline copper micropillars: A discrete dislocation dynamics simulation study. Acta Materialia, 2019.
Shuang, S., Liang, Y., Zhang, X., Yuan, F., Kang, G., and Zhang, X., Impact of local chemical ordering on deformation mechanisms in single-crystalline CuNiCoFe high-entropy alloys: a molecular dynamics study. Modelling and Simulation in Materials Science and Engineering, 2023.
Du, X., Shuang, S., Zhao, J., Fu, Z., Kan, Q., and Zhang, X., Extra strengthening and Bauschinger effect in gradient high-entropy alloy: A molecular dynamics study. International Journal of Mechanical Sciences, 2024.
研究方向四：机器学习在材料力学中的应用
核心内容：将机器学习（如神经网络、生成对抗网络、遗传算法等）应用于材料本构参数识别、性能预测、微观结构-性能关联和疲劳寿命评估，实现数据驱动的材料研究与设计。
代表性论文：
Zhu, D., Zhao, J., Hu, Y., Kan, Q., Kang, G., and Zhang, X., Predicting tensile behavior from nanoindentation using gradient plasticity model with neural network and genetic algorithm. Mechanics of Materials, 2025.
Lu, S., Zhang, X., Hu, Y., Chu, J., Kan, Q., and Kang, G., Machine Learning-Based Constitutive Parameter Identification for Crystal Plasticity Models. Mechanics of Materials, 2025.
Jiang, L., Hu, Y., Li, H., Shao, X., Zhang, X., Kan, Q., and Kang, G., A cGAN-based fatigue life prediction of 316 austenitic stainless steel in high-temperature and high-pressure water environments. International Journal of Fatigue, 2025.
Li, X., Zhang, X., Feng, W., and Wang, Q., Machine learning-based prediction of fracture toughness and path in the presence of micro-defects. Engineering Fracture Mechanics, 2022.
周瑞, 熊宇凯, 储节磊, 阚前华, 康国政, 张旭. 基于机器学习和遗传算法的非局部晶体塑性模型参数识别. 力学学报, 2024.