Collaborative Research: Study of Anisotropic Dust Interactions in the PK-4 Experiment

合作研究：PK-4 实验中各向异性尘埃相互作用的研究

• 批准号: 2308743
• 负责人: Lorin Matthews
• 金额: $ 45.31万
• 依托单位: Baylor 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: 2023-06-01 至 2026-05-31
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2308743&HistoricalAwards=false
• 关键词: Collaborative; Research; Study; Anisotropic; Dust

This award supports a collaborative effort between Auburn University and Baylor University to study behavior of a complex plasma under microgravity in the PlasmaKristall-4 (PK-4) experiment on the International Space Station. Complex plasmas, also known as dusty plasmas, are collections of micron-sized dust particles immersed in a plasma, or ionized gas. The dust grains typically become charged by collecting electrons and ions on their surface. When dusty plasmas are placed in external electric fields, anisotropic interactions between dust grains and ion flows can lead to the formation of filamentary dust structures. Anisotropic interactions, which depend on the relative orientation of interacting particles, are known to arise in some of the most interesting complex systems, including proteins and smart materials. A fundamental open question in the study of these systems is how anisotropic interactions lead to structure formation. This project addresses this question using a combined analytical, numerical, and experimental approach to investigate how anisotropic interactions lead to structure formation in dusty plasma experiments on the International Space Station (ISS).This project will use data from several PK-4 campaigns to investigate the form and origins of the anisotropic dust-dust interaction potential that leads to the formation of filamentary dusty plasma structures. Data collected from PK-4 experiments will be used to quantify structural anisotropy as a function of plasma conditions using statistical analysis and data-driven methods. Molecular dynamics (MD) simulations of dust and ions will be used to calculate the dust–ion wakefield potential. A machine learning (ML) model will be applied to experimental data to identify the most likely form of the interaction forces as a function of plasma parameters. Interaction forces and potentials learned with the ion-dust MD simulation and the ML model will be applied in MD simulations of larger dust clouds to validate against the experimental data. Experiments in the PK-4 BU device, a ground-based replica of the PK-4 ISS with additional diagnostic capabilities, will be used to determine the relationship between plasma conditions and the onset of plasma ionizations waves. Finally, an analytic model will be employed to determine the spectrum of energy states of the Hamiltonian representing the anisotropic interaction potential. This method will be used to determine the relationship between PK-4 filamentary dusty plasma and other filamentary structures, such as electrorheological materials and liquid crystals.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.

该奖项支持奥本大学和贝勒大学之间的合作，以研究国际空间站上PlasmaKristall-4（PK-4）实验中微重力下复杂等离子体的行为。 复杂等离子体，也称为尘埃等离子体，是浸没在等离子体或电离气体中的微米级尘埃颗粒的集合。尘埃颗粒通常通过在其表面收集电子和离子而带电。 当尘埃等离子体被置于外电场中时，尘埃颗粒与离子流之间的各向异性相互作用可以导致尘埃结构的形成。 各向异性的相互作用，这取决于相互作用粒子的相对取向，已知出现在一些最有趣的复杂系统，包括蛋白质和智能材料。 在这些系统的研究中，一个基本的开放问题是各向异性的相互作用如何导致结构的形成。本项目将利用国际空间站（ISS）上多个PK-4活动的数据，研究各向异性尘埃-尘埃相互作用势的形式和起源，并结合分析、数值和实验方法，研究各向异性尘埃相互作用势如何导致尘埃等离子体结构的形成。从PK-4实验中收集的数据将用于使用统计分析和数据驱动方法量化作为血浆条件函数的结构各向异性。尘埃和离子的分子动力学（MD）模拟将被用来计算尘埃-离子韦克菲尔德势。机器学习（ML）模型将应用于实验数据，以确定最可能的形式的相互作用力作为等离子体参数的函数。通过离子尘埃MD模拟和ML模型学习的相互作用力和势将应用于较大尘埃云的MD模拟，以验证实验数据。PK-4 BU装置是PK-4国际空间站的地面复制品，具有额外的诊断能力，将用于确定等离子体条件与等离子体电离波开始之间的关系。最后，将采用一个分析模型来确定代表各向异性相互作用势的哈密顿量的能态谱。该方法将用于确定PK-4导电尘埃等离子体与其他导电结构之间的关系，如电流变材料和液晶。该奖项反映了NSF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。