Collaborative Research: DMREF: Machine Learning Algorithm Prediction and Synthesis of Next Generation Superhard Functional Materials

该项目的目标是发现具有实现未来技术所需特性的新材料。许多材料具有出色的性能，使它们在某些应用中是理想的，但缺乏其他性能，限制了它们的使用。一个著名的例子是钻石，它是已知最硬的材料，但也是电绝缘体。是否有一种材料可以满足超硬材料的需求，同时又具有金属的高导电性或其他有用的特性？该项目将结合不同领域的专业知识，寻找新的超硬材料，这些材料还具有其他理想的特性，使它们能够满足独特的苛刻技术要求。这些材料的三维和二维形式都将被合成。实验和理论之间的反馈回路将用于表征材料，合理设计具有所需性能的材料，并优化合成方案。学生将在一个跨学科的理论和实验团队中接受培训，他们的专业知识包括化学、物理、材料科学和工程。该项目将结合新开发的晶体结构预测与发现和合成新型超硬材料的实验，包括那些具有附加功能的材料。理论上的努力将开创一种新的晶体结构计算方法，将先验进化算法与机器学习技术相结合。实验工作将采用高压-高温合成方法以及化学气相沉积等技术，从薄膜开始制造亚稳材料。该项目将专注于创造由轻元素硼、碳和氮组成的新材料，可以单独使用，也可以与较重的金属元素结合。新材料将通过多种方法进行表征，包括先进的光谱技术，如目前在同步加速器设施中可用的技术。理论技术将指导合成目标材料的选择和最有前途的前体材料和合成途径。开发的计算工具将在开源许可下提供，从而为网络基础设施做出贡献。学生的理论和实验培训将通过暑期研究经验和本科课程开发，包括针对代表性不足群体的课程开发，推进STEM项目。该奖项反映了美国国家科学基金会的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。

NON-TECHNICAL SUMMARYThe goal of this project is to discover new materials that possess the properties needed to enable the technologies of the future. Many materials have outstanding properties that make them desirable for some applications but are deficient in other properties that limit their use. A well-known example is diamond, which is the hardest known material but is also an electrical insulator. Is there a material yet to be discovered that could satisfy the need for a superhard material that also has the high electrical conductivity of a metal or other useful properties? This project will combine diverse areas of expertise to search for new superhard materials that also possess other desirable properties that enable them to fulfill uniquely demanding technological requirements. Both three-dimensional and two-dimensional forms of these materials will be synthesized. A feedback loop between experiment and theory will be used to characterize the materials, rationally design those with desired properties, and optimize the synthesis protocols. Students will be trained in an interdisciplinary collaborative team of theoreticians and experimentalists whose expertise includes chemistry, physics, and materials science and engineering.TECHNICAL SUMMARYThis project will combine newly developed crystal structure prediction with experiments for the discovery and synthesis of novel superhard materials, including those with additional functionality. The theoretical effort will pioneer a novel method for crystal structure calculations that merges a priori evolutionary algorithms with machine learning techniques. The experimental effort will employ high pressure-temperature synthesis methods along with techniques such as chemical vapor deposition to create metastable materials starting with thin films. The project will focus on the creation of new materials consisting of the light elements boron, carbon, and nitrogen, either alone or combined with heavier metallic elements. The new materials will be characterized by a variety of methods, including advanced spectroscopic techniques such as those now available at synchrotron facilities. The theoretical techniques will guide the choice of target materials for synthesis and the most promising precursor materials and synthesis pathways. The developed computational tools will be made available under open source licenses, thereby contributing towards cyberinfrastructure. Student training in theory and experiment will advance STEM initiatives through summer research experiences and undergraduate course development, including those targeting underrepresented groups.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.