A Component-wise Model for Understanding Spin-Charge Interactions in Nanoparticle Solids Using Targeted Synthesis, Magnetometry, and Magnetoresistance

利用靶向合成、磁力测定和磁阻来理解纳米颗粒固体中自旋电荷相互作用的组件模型

• 批准号: 2322706
• 负责人: Jeffrey Rinehart
• 金额: $ 63.17万
• 依托单位: University of California-San Diego
• 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: 2023-08-15 至 2026-07-31
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2322706&HistoricalAwards=false
• 关键词: Component; wise; Model; Understanding; Spin

PART 1: NON-TECHNICAL SUMMARYAt the heart of much of modern technology and materials science lies the challenge of understanding and controlling the interaction between an electron’s charge and its spin. This project, which is supported by the Solid State and Materials Chemistry program in NSF’s Division of Materials Research, targets that challenge by focusing on a phenomenon known as magnetoresistance (MR). For a magnetoresistant material, a magnetic field can be used to change the material’s electrical resistance. Unlike traditional MR devices that employ intricate layered structures as the active MR material, this project embraces a unique, simpler, and highly adaptable approach, namely leveraging advances in low-cost, high-purity magnetic nanoparticle synthesis and assemble them into MR-active hybrid composites. This method promises to be more fault-tolerant and tunable, enabling researchers to develop, test, and refine theories of MR and spin transport at an unprecedented pace. Furthermore, this project enhances the impact of its research through a commitment to transparency and accessibility in data management. In an era where data fuels discovery, the team will focus on data analysis and software development embedded in FAIR principles, building a culture of “open-source” research that is genuinely Findable, Accessible, Interoperable, and Reusable to the public funders who make the research possible.PART 2: TECHNICAL SUMMARYThe research, which is supported by the Solid State and Materials Chemistry program in NSF’s Division of Materials Research, explores a nanoscale bottom-up approach to one of the most technologically important methods of electronic spin-charge interaction: magnetoresistance (MR). Instead of the traditional layered MR materials, the research team of Professor Jeffrey Rinehart at UC San Diego focuses on granular MR materials composed of nanoparticles synthesized with specific composition and magnetic phase requirements. By leveraging advancements in colloidal nanochemistry, unparalleled control over the magnetic structure of individual particles is obtained and thoroughly characterized, thereby allowing rigorous correlation with the MR behavior of composite material structures. This is the first time that researchers establish quantitative structure-function relationships between well-defined parameters: interparticle interaction strength, single-particle magnetic anisotropy, and particle volume. Elucidating these key factors influencing the MR behavior of the system allows mapping out the full landscape of MR response as multidimensional response function, providing a far more comprehensive characterization than has previously been attempted. Starting from the simple but important ferrite-based systems, research expands to high-performing magnetic materials with an ultimate goal of creating MR systems with adjustable field sensitivity and pseudo-spin valve behavior for a variety of sensing applications. The research includes an extensive data organization and modeling component with an emphasis on alignment with FAIR data principles and making data widely available for study.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.

理解和控制电子的电荷和自旋之间的相互作用是许多现代技术和材料科学的核心挑战。该项目由美国国家科学基金会材料研究部的固态和材料化学项目支持，通过关注一种被称为磁电阻（MR）的现象来应对这一挑战。对于抗磁材料，磁场可以用来改变材料的电阻。与采用复杂的分层结构作为活性磁共振材料的传统磁共振设备不同，该项目采用了一种独特、更简单、适应性强的方法，即利用低成本、高纯度磁性纳米颗粒合成技术的进步，将它们组装成磁共振活性混合复合材料。这种方法有望具有更强的容错性和可调性，使研究人员能够以前所未有的速度开发、测试和完善磁共振和自旋输运理论。此外，该项目通过致力于数据管理的透明度和可访问性来增强其研究的影响。在一个数据推动发现的时代，团队将专注于嵌入FAIR原则的数据分析和软件开发，建立一种“开源”研究的文化，这种文化对使研究成为可能的公共资助者来说是真正可查找、可访问、可互操作和可重用的。该研究由美国国家科学基金会材料研究部的固态和材料化学项目支持，探索了一种纳米级自下而上的方法来研究电子自旋-电荷相互作用的最重要技术方法之一：磁电阻（MR）。与传统的层状磁共振材料不同，加州大学圣地亚哥分校Jeffrey Rinehart教授的研究团队专注于由具有特定成分和磁相要求的纳米颗粒组成的颗粒状磁共振材料。通过利用胶体纳米化学的进步，获得了对单个颗粒磁结构的无与伦比的控制，并对其进行了彻底的表征，从而允许与复合材料结构的磁流变行为进行严格的关联。这是研究人员首次在定义明确的参数（粒子间相互作用强度、单粒子磁各向异性和粒子体积）之间建立定量的结构-函数关系。阐明这些影响系统核磁共振行为的关键因素，可以将核磁共振反应作为多维反应函数绘制出来，提供比以前尝试的更全面的表征。从简单但重要的基于铁氧体的系统开始，研究扩展到高性能磁性材料，最终目标是创建具有可调场灵敏度和伪自旋阀行为的MR系统，用于各种传感应用。该研究包括广泛的数据组织和建模组件，重点是与FAIR数据原则保持一致，并使数据广泛用于研究。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。