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努力，以研究国际空间站的Plasmakristall-4（PK-4）实验中微重力下的复杂血浆的行为。复杂的等离子体，也称为尘土飞扬的等离子体，是浸入等离子体或离子气体的微米大小尘埃集合的集合。粉尘晶粒通常通过在其表面上收集电子和离子来充电。当将尘土飞扬的平原放置在外部电场中时，粉尘粒和离子流之间的各向异性相互作用会导致丝状灰尘结构的形成。依赖于相互作用粒子的相对方向的各向异性相互作用是在一些最有趣的复杂系统中出现的，包括蛋白质和智能材料。这些系统的研究中的一个基本开放问题是各向异性相互作用如何导致结构形成。该项目使用一种组合的分析，数值和实验方法来研究这个问题，以研究在国际空间站（ISS）上进行尘土高血浆实验中的结构形成。该项目将使用几个PK-4广告系列的数据来研究各向异性粉尘互动的形式和起源，从而导致了粉尘的粉尘粉的形式。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来量化结构各向异性作为等离子体条件的函数。粉尘和离子的分子动力学（MD）模拟将用于计算粉尘 - 离子Wakefield电位。机器学习（ML）模型将应用于实验数据，以确定相互作用力的最可能形式，这是血浆参数的函数。使用离子粉Dust MD模拟学习的相互作用力和电位将应用于较大的尘埃云的MD模拟中，以验证实验数据。 PK-4 BU设备的实验是具有其他诊断能力的PK-4 IS的基于地面的复制品，将用于确定血浆条件与血浆电离波的发作之间的关系。最后，将进行一个分析模型，以确定代表各向异性相互作用潜力的大麻的能量态。该方法将用于确定PK-4丝状灰尘等离子体与其他丝状结构（例如电学材料和液晶）之间的关系。该奖项反映了NSF的法定任务，并被认为是通过基金会的智力优点和更广泛影响的评估标准通过评估来评估的。