Decoding Spatial Complexity in Strongly Correlated Electronic Systems

解码强相关电子系统中的空间复杂性

• 批准号: 1508236
• 负责人: Erica Carlson
• 金额: $ 31.5万
• 依托单位: Purdue University
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2015
• 资助国家: 美国
• 起止时间: 2015-08-01 至 2018-07-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1508236&HistoricalAwards=false
• 关键词: Decoding; Spatial; Complexity; Strongly; Correlated

NON-TECHNICAL SUMMARYThis award supports theoretical and computational research, and education on materials with strong interactions among electrons which lead to strong correlations in the motions of electrons in the material. Inside conventional materials like metals and semiconductors, the electrons are evenly spread out, like tomato soup filling a container. But the electrons inside these strongly correlated materials act more like an exotic gumbo: nanoscale images show that the electrons clump into complicated shapes at the surface. These patterns and their formation may be a key to understanding the unusual electronic properties characteristic of strongly correlated materials and to the eventual mastery of these materials leading to technological applications. Most theoretical and experimental tools are designed for understanding and detecting homogeneous electronic states, and it is necessary to envision and explore new frameworks for understanding why patterns form in the distribution of electrons in strongly correlated materials. Combining theoretical tools from fractal mathematics and the statistical mechanics of disordered materials, the PI aims to develop new concepts and methods for interpreting and understanding the nanoscale electronic textures of these materials. The nanoscale is about two hundred thousand times smaller than the diameter of a human hair. The PI aims to develop geometric cluster analysis techniques that she introduced into the field, in order to better understand and eventually control these materials so that they can be successfully applied in the marketplace. The PI will continue to develop the mentoring program she began for graduate women in the physics program at her home institution. The PI will also continue to visit K-12 public schools to discuss her research. This outreach combines interactive hands-on superconductivity and magnetism demonstrations with education about current condensed matter research. In addition, the proposed work will also advance the training of one graduate student.TECHNICAL SUMMARYThis award supports theoretical and computational research, and education on strongly correlated electron materials with an aim to advance understanding of patterns formed by inhomogeneous distribution of electrons. There is growing experimental evidence that many strongly correlated electronic systems such as nickelates, cuprates, and manganites exhibit nanoscale variations in local electronic properties. Describing the electronic behavior of these materials involves multiple degrees of freedom, including orbital, spin, charge, and lattice degrees of freedom. The interplay with disorder adds another dimension: not only can disorder destroy phase transitions, leaving mere crossovers in the wake; it can fundamentally alter ground states, often forbidding long range order. Especially in systems where different physical tendencies to order compete, disorder can provide nucleation points for competing ground states, leading to spatial pattern formation and complexity. The interplay of many degrees of freedom, strong correlations, and disorder can lead to a hierarchy of length scales and to pattern formation at the nanoscale. There is a need to design and develop new ways of understanding, detecting, and characterizing electronic pattern formation in strongly correlated electronic materials, especially in the presence of severe disorder effects. Resulting theoretical guidance will enable more direct contact between theory and experiment for a number of materials, and provide a path forward for understanding "disputed" regions of phase diagrams of strongly correlated materials. The PI aims to further develop the geometric cluster analysis techniques that she pioneered in the field of strongly correlated electronic systems, in order to maximize the information that can be extracted from experiments using these methods, and to facilitate the broad application of these techniques to various materials and image probes. In order to do this, the PI will develop theory of geometric criticality in random Ising models through numerical simulations. The resulting work is expected to connect to several experimental techniques and to yield new modes of data taking and analysis, and new methods enabling the detection and characterization of novel phases of matter.The PI will continue to develop the mentoring program she began for graduate women in the physics program at her home institution. The PI will also continue to visit K-12 public schools to discuss her research. This outreach combines interactive hands-on superconductivity and magnetism demonstrations with education about current condensed matter research. In addition, the proposed work will also advance the training of one graduate student.

非技术摘要该奖项支持理论和计算研究，以及电子间强相互作用材料的教育，这些相互作用导致材料中电子运动的强相关性。在金属和半导体等传统材料内部，电子均匀分布，就像装满容器的番茄汤一样。 但这些强相关材料内部的电子行为更像是一种奇异的浓汤：纳米级图像显示电子在表面聚集成复杂的形状。 这些图案及其形成可能是理解强相关材料的不寻常电子特性特征以及最终掌握这些材料导致技术应用的关键。 大多数理论和实验工具都是为了理解和检测均匀电子态而设计的，有必要设想和探索新的框架来理解强相关材料中电子分布模式的形成原因。 PI 结合分形数学和无序材料统计力学的理论工具，旨在开发新的概念和方法来解释和理解这些材料的纳米级电子纹理。 纳米尺度大约比人类头发直径小二十万倍。 PI 的目标是开发她引入该领域的几何聚类分析技术，以便更好地理解并最终控制这些材料，以便它们能够成功应用于市场。 PI 将继续开发她为所在机构物理项目女研究生启动的指导计划。 PI 还将继续访问 K-12 公立学校讨论她的研究。 该活动将互动式超导和磁性实践演示与当前凝聚态物质研究的教育结合起来。 此外，拟议的工作还将促进一名研究生的培训。技术摘要该奖项支持理论和计算研究以及强相关电子材料的教育，旨在增进对电子不均匀分布形成的图案的理解。越来越多的实验证据表明，许多强相关的电子系统，如镍酸盐、铜酸盐和锰酸盐，在局部电子特性方面表现出纳米级的变化。描述这些材料的电子行为涉及多个自由度，包括轨道、自旋、电荷和晶格自由度。与无序的相互作用增加了另一个维度：无序不仅会破坏相变，只留下交叉；而且还会破坏相变。它可以从根本上改变基态，通常会禁止长程有序。特别是在不同物理倾向相互竞争的系统中，无序可以为竞争基态提供成核点，从而导致空间图案的形成和复杂性。许多自由度、强相关性和无序性的相互作用可以导致长度尺度的层次结构和纳米尺度的图案形成。需要设计和开发新的方法来理解、检测和表征强相关电子材料中的电子图案形成，特别是在存在严重无序效应的情况下。由此产生的理论指导将使许多材料的理论和实验之间更加直接的联系，并为理解强相关材料相图的“有争议”区域提供一条前进的道路。 PI的目标是进一步发展她在强相关电子系统领域开创的几何聚类分析技术，以便最大限度地利用这些方法从实验中提取信息，并促进这些技术广泛应用于各种领域。材料和图像探针。 为此，PI 将通过数值模拟开发随机伊辛模型中的几何临界理论。 由此产生的工作预计将与多种实验技术相结合，并产生新的数据采集和分析模式，以及能够检测和表征物质新相的新方法。PI将继续开发她为研究生女性启动的指导计划在她所在机构的物理项目中。 PI 还将继续访问 K-12 公立学校讨论她的研究。 该活动将互动式超导和磁性实践演示与当前凝聚态物质研究的教育结合起来。 此外，拟议的工作还将促进一名研究生的培训。

项目成果

Period multiplication cascade at the order-by-disorder transition in uniaxial random field XY magnets

单轴随机场 XY 磁体中有序无序转变的周期倍增级联

• DOI: 10.1038/s41467-020-18270-6
• 发表时间: 2020-12
• 期刊: Nature Communications
• 影响因子: 16.6
• 作者: Basak, S.;Dahmen, K. A.;Carlson, E. W.
• 通讯作者: Carlson, E. W.

Classifying surface probe images in strongly correlated electronic systems via machine learning

通过机器学习对强相关电子系统中的表面探针图像进行分类

• DOI: 10.1103/physrevmaterials.3.033805
• 发表时间: 2019-03
• 期刊: Physical Review Materials
• 影响因子: 3.4
• 作者: Burzawa, L.;Liu, S.;Carlson, E. W.
• 通讯作者: Carlson, E. W.

Connecting Complex Electronic Pattern Formation to Critical Exponents

将复杂的电子模式形成与关键指数联系起来

• DOI: 10.3390/condmat6040039
• 发表时间: 2021-12
• 期刊: Condensed Matter
• 影响因子: 1.7
• 作者: Liu, Shuo;Carlson, Erica W.;Dahmen, Karin A.
• 通讯作者: Dahmen, Karin A.