通过激光热梯度处理加速固态薄膜金属去合金化三维纳米结构材料设计的发现
Accelerating Discovery of Solid-State Thin-Film Metal Dealloying for 3D Nanoarchitecture Materials Design through Laser Thermal Gradient Treatment
AI总结：
本研究利用激光热梯度处理薄膜样品，结合同步辐射高通量表征，快速识别关键热处理参数，加速固态薄膜金属去合金化三维纳米结构的发现与机器学习预测验证。
摘要：
薄膜固态金属去合金化（thin-film SSMD）是一种有前景的制造具有可控形貌和效率的纳米结构的方法，相较于传统块体材料加工方法，在集成到实际应用方面具有优势。尽管机器学习（ML）已促进了去合金化系统的设计，但用于纳米结构形成的关键热处理参数的选择在很大程度上仍然未知，且依赖于实验试错。为克服这一挑战，需要一种能够在探测薄膜样品局部纳米结构的同时，对热处理参数进行高通量表征的工作流程。在本工作中，展示了一种基于激光的热处理方法，用于在Nb-Al/Sc和Nb-Al/Cu的单薄膜样品上产生温度梯度。这一连续的热空间使得能够观察去合金化转变及所关注的纳米结构。通过同步辐射X射线多模态和高通量表征，可以快速捕获关键转变和纳米结构，并随后使用电子显微镜进行验证。在该框架内，驱动化学反应和形貌演化的关键温度被清晰地识别出来。虽然氧化过程可能在薄膜处理过程中对纳米结构形成有所贡献，但去合金化前沿的去合金化过程仅涉及去合金化元素之间的相互作用，这突显了所选系统的可用性和可行性。该方法能够高效探索去合金化过程并验证机器学习预测，从而加速具有目标纳米结构的薄膜SSMD系统的发现。
英文摘要：
Thin-film solid-state metal dealloying (thin-film SSMD) is a promising method for fabricating nanostructures with controlled morphology and efficiency, offering advantages over conventional bulk materials processing methods for integration into practical applications. Although machine learning (ML) has facilitated the design of dealloying systems, the selection of key thermal treatment parameters for nanostructure formation remains largely unknown and dependent on experimental trial and error. To overcome this challenge, a workflow enabling high-throughput characterization of thermal treatment parameters while probing local nanostructures of thin-film samples is needed. In this work, a laser-based thermal treatment is demonstrated to create temperature gradients on single thin-film samples of Nb-Al/Sc and Nb-Al/Cu. This continuous thermal space enables observation of dealloying transitions and the resulting nanostructures of interest. Through synchrotron X-ray multimodal and high-throughput characterization, critical transitions and nanostructures can be rapidly captured and subsequently verified using electron microscopy. The key temperatures driving chemical reactions and morphological evolutions are clearly identified within this framework. While the oxidation process may contribute to nanostructure formation during thin-film treatment, the dealloying process at the dealloying front involves interactions solely between the dealloying elements, highlighting the availability and viability of the selected systems. This approach enables efficient exploration of the dealloying process and validation of ML predictions, thereby accelerating the discovery of thin-film SSMD systems with targeted nanostructures.
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