CAREER: Developing Quantum Algorithms for High-Entropy Alloy Discovery

职业：开发用于高熵合金发现的量子算法

• 批准号: 2239216
• 负责人: Houlong Zhuang
• 金额: $ 53.74万
• 依托单位: Arizona State University
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-01-01 至 2027-12-31
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2239216&HistoricalAwards=false
• 关键词: CAREER; Developing; Quantum; Algorithms; Entropy

NONTECHNICAL SUMMARYThis CAREER award supports theoretical and computational research that adopts quantum computers in the noisy intermediate-scale quantum era to discover novel alloys known as high-entropy alloys (HEAs), which refer to alloys consisting of multiple elements with the same or nearly the same concentration. A typical HEA adopts a single-phase solid solution structure, where atoms of the constituent elements are located at random sites of a fixed crystal lattice. HEAs made of certain combinations of elements possess unique properties, such as balanced ductility and strength, that are absent in the conventional alloys, where the content of one element dominates the overall concentration. Discovering HEAs is a complex combinatorial problem, where an optimal selection of elements and their corresponding molar ratios significantly affect the resulting materials' properties. This project tackles this problem to search for the "Materials Genome" of HEAs via developing quantum algorithms and implementing them on near-term quantum computers.This award also supports the PI’s educational and outreach activities that aim to prepare for upcoming revolutions in artificial intelligence and quantum computing. The PI will (i) train quantum workforce by providing an integrated training platform through existing Quantum Collaborative at Arizona State University (ASU) for practitioners and a diversified student body through education and research opportunities, course and thesis projects, and summer internships, (ii) train graduate students and mentor underrepresented high school students based upon the existing outreach programs such as the "Science and Engineering Experience" program at ASU, (iii) organize symposia in the annual meetings of main research societies such as the American Physical Society, (iv) organize a special journal issue to collect contributions reporting the frontier of HEA research, and (v) participate in various activities organized by the U.S.-Africa Initiative in Electronic Structure to enhance collaborations between African and U.S. physicists.TECHNICAL SUMMARYThis CAREER award supports theoretical and computational research with an aim to elucidate the underlying physics and mechanisms associated with the materials discovery of high entropy alloys (HEAs). The PI will (i) develop quantum encoding algorithms to convert classical HEA data to quantum data, which will facilitate subsequent quantum search, learning, and exploring and help understand the effects of constituent elements and concentrations of HEAs on the entropy-stabilized phases, (ii) develop quantum search algorithms that use the encoded quantum states as inputs to achieve reduced time complexity in searching a HEA database comparing with classical search, (iii) perform quantum machine learning computations to determine the phase selection of HEAs and achieve a prediction accuracy level that is comparable to classical machine learning models, and (iv) develop quantum walk algorithms to explore the high-dimensional compositional space to achieve rapid explorations of structure-property relationships to discover new HEAs. This award also supports the PI’s educational and outreach activities that aim to prepare for upcoming revolutions in artificial intelligence and quantum computing. The PI will (i) train quantum workforce by providing an integrated training platform through existing Quantum Collaborative at Arizona State University (ASU) for practitioners and a diversified student body through education and research opportunities, course and thesis projects, and summer internships, (ii) train graduate students and mentor underrepresented high school students based upon the existing outreach programs such as the "Science and Engineering Experience" program at ASU, (iii) organize symposia in the annual meetings of main research societies such as the American Physical Society, (iv) organize a special journal issue to collect contributions reporting the frontier of HEA research, and (v) participate in various activities organized by the U.S.-Africa Initiative in Electronic Structure to enhance collaborations between African and U.S. physicists.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.

非技术摘要该职业奖支持理论和计算研究，在嘈杂的中尺度量子时代采用量子计算机来发现被称为高熵合金（HEA）的新型合金，高熵合金是指由具有相同或几乎相同的多种元素组成的合金典型的HEA采用单相固溶体结构，其中组成元素的原子位于固定晶格的随机位置，由某些元素组合制成，具有独特的特性。平衡的延展性和强度等特性是传统合金所不具备的，传统合金中一种元素的含量在总体浓度中占主导地位。发现 HEA 是一个复杂的组合问题，元素的最佳选择及其相应的摩尔比会显着影响合金的性能。该项目解决了这个问题，通过开发量子算法并在近期量子计算机上实现它们来寻找 HEA 的“材料基因组”。该奖项还支持 PI 旨在做好准备的教育和外展活动。针对即将到来的人工智能和量子计算革命，PI 将 (i) 通过亚利桑那州立大学 (ASU) 现有的量子协作平台，通过教育和研究机会、课程为从业者和多元化学生群体提供综合培训平台，来培训量子劳动力。和论文项目以及暑期实习，（ii）根据现有的外展计划（例如亚利桑那州立大学的“科学与工程经验”计划）培训研究生和指导代表性不足的高中生，（iii）在主要的年会上组织研讨会研究协会，如美国物理学会，(iv) 组织特刊，收集报告 HEA 研究前沿的贡献，以及 (v) 参加美国-非洲电子结构倡议组织的各种活动，以加强非洲之间的合作技术摘要该职业奖支持理论和计算研究，旨在阐明与高熵合金 (HEA) 材料发现相关的基础物理和机制。将（i）开发量子编码算法，将经典HEA数据转换为量子数据，这将有助于后续的量子搜索、学习和探索，并帮助理解HEA的组成元素和浓度对熵稳定相的影响，（ii）开发量子搜索算法，使用编码的量子态作为输入，以实现与经典搜索相比降低搜索 HEA 数据库的时间复杂度，(iii) 执行量子机器学习计算以确定 HEA 的相位选择并实现预测精度水平与经典机器学习相当(iv) 开发量子行走算法来探索高维组合空间，以实现结构-性质关系的快速探索，从而发现新的 HEA。该奖项还支持 PI 的教育和外展活动，旨在为即将到来的革命做好准备。 PI 将 (i) 通过亚利桑那州立大学 (ASU) 现有的量子合作组织通过教育和研究机会、课程和论文项目为从业者和多元化学生群体提供综合培训平台来培训量子劳动力，和暑期实习，(ii) 根据现有的外展计划（例如亚利桑那州立大学的“科学与工程经验”计划）培训研究生和指导代表性不足的高中生，(iii) 在主要研究学会的年会上组织研讨会，例如(iv) 组织特刊，收集报道 HEA 研究前沿的投稿，以及 (v) 参加美国-非洲电子结构倡议组织的各种活动，以加强非洲和美国之间的合作。该奖项反映了 NSF 的法定使命，并通过使用基金会的智力价值和更广泛的影响审查标准进行评估，被认为值得支持。

项目成果

Chemical short-range order in complex concentrated alloys

复杂浓缩合金中的化学短程有序

• DOI: 10.1557/s43577-023-00575-8
• 发表时间: 2023-07-01
• 期刊: MRS Bulletin
• 影响因子: 5
• 作者: Wei Chen;Lin Li;Qiang Zhu;Houlong Zhuang
• 通讯作者: Houlong Zhuang

Quantum machine-learning phase prediction of high-entropy alloys

高熵合金的量子机器学习相预测

• DOI: 10.1016/j.mattod.2023.02.014
• 发表时间: 2023-03-01
• 期刊: Materials Today
• 影响因子: 24.2
• 作者: P. Brown;H. Zhuang
• 通讯作者: H. Zhuang