DMREF: Collaborative Research: Design and synthesis of novel materials for spin caloritronic devices

非技术描述：将现代技术推向前所未有水平的微电子学受到电荷载流子运动产生的强烈焦耳加热的严重阻碍。一种新的方法是在使用最少载流子的设备中利用纯自旋电流，从而在金属中产生最小的热量，而在无载流子的磁绝缘体中几乎不产生热量。自旋塞贝克效应（SSE）允许人们从磁性绝缘体的温度梯度中产生纯自旋电流。几年前才在实验中发现的SSE导致了一个新兴的新领域——自旋热电子学（spin caloritronics）的出现，该领域为将废热转化为电能以及电子设备的热管理提供了新的策略。本项目将通过密切的理论/实验互动，重点关注SSE效应的基本理解，并将探索新的铁磁和反铁磁绝缘体，以推进自旋热电子现象和器件。技术描述：提议的项目将结合理论，表征和材料合成的努力，以更好地理解自旋热电子现象和设备。这项工作将建立在三个关键和相互关联的因素上。这些课程包括对自旋热电子现象的物理和相关问题的理论理解，对各种磁性和反铁磁性绝缘体单晶的自旋热电子特性的测量，以及利用性能优越的材料制造自旋热电子薄膜器件。通过对拓扑绝缘体（自旋轨道耦合是一个关键因素）和声子-磁振子相互作用理论的深入研究，Fiete将发展一种微观理论来理解与自旋热电子现象相关的物理。他还将开发用于筛选和设计用于制造自旋热电子器件的新材料的计算工具。模拟工作将涵盖产生自旋电流的材料和高效转换自旋电流为电势的金属材料，以及界面设计。该项目将充分利用周教授在种植各种块状单晶方面的丰富经验和专业知识，包括铁磁性稀土铁石榴石、双钙钛矿、尖晶石、具有单轴、易平面、铋离子和焦绿石等特殊磁性的反铁磁性层状材料。在自旋热电子器件的计算筛选和设计中优先考虑地球富元素。在材料合成中最具挑战性的问题，特别是与地球丰富的元素，可以克服高压合成。本实验室所开发的自旋电子器件的工艺、制造和测量技术将用于研究由这些新材料制成的自旋热电子器件的性能。将实验结果与计算模型进行比较，为进一步完善模型提供新的输入。一个迭代反馈回路将在合作项目之间形成。

Non-technical Description: Microelectronics, which has propelled modern technologies to unprecedented levels, has been severely hampered by the intense Joule heating generated by the motion of electrical charge carriers. A new approach exploits pure spin currents in devices that use a minimum of electrical charge carriers, thus generating minimal heat in metals and virtually no heat in magnetic insulators, which are charge-carrier free. The spin Seebeck effect (SSE) allows one to generate a pure spin current from a temperature gradient in a magnetic insulator. The SSE, experimentally discovered only a few years ago, has lead to a burgeoning new field known as spin caloritronics, which offers new strategies for the conversion of waste heat to electricity as well as thermal management in electronic devices. This project, through close theory/experiment interactions, will focus on the fundamental understanding of the SSE effect and will explore new ferromagnetic and antiferromagnetic insulators for advancing spin caloritronic phenomena and devices. Technical Description: The proposed project will combine theory, characterization, and materials synthesis efforts to better understand spin caloritronic phenomena and devices. The effort will be built on three key and interlocking elements. These include a theoretical understanding of the physics and issues associated with the spin caloritronic phenomena, measurement of spin caloritonic properties of a broad variety of single crystals of magnetic and antiferromagnetic insulators, and the fabrication of spin caloritronic thin films devices exploiting materials with superior properties. By extending the fruitful research on topological insulators where the spin-orbit coupling is a critical factor and the theory of phonon-magnon interaction, Fiete will develop a microscopic theory for understanding physics associated with spin caloritronic phenomena. He will also develop computational tools for screening and designing new materials for fabrication of spin caloritronic devices. The simulation work will cover the materials for generating spin current and metallic materials to convert spin current into electric potential with a high efficiency as well as the interface design. The project will capitalize on the extensive experience and expertise of Zhou in growing a broad range of bulk single crystals including ferrimagnetic rare earth iron garnets, double perovskites, spinels, antiferromagnetic layered materials with peculiar magnetic properties like uniaxial, easy-plane, biskyrmion, and pyrochlores. Earth abundant elements are prioritized in the computational screening and design for the spin caloritronic devices. The most challenging problems in the material synthesis, especially with Earth abundant elements, could be overcome by high-pressure synthesis. The procedures, the fabrication, and measurement techniques for spintronic devices developed in Chien's laboratory will be used to study the performance of spin caloritronic devices made from these new materials. The experimental results will be compared with the computational model and provide new inputs to further refine the model. An iterative feedback loop will be formed among the co-PIs.