CAREER: Prediction and understanding of thermal transport across successive interfaces
职业:预测和理解连续界面上的热传输
基本信息
- 批准号:2337749
- 负责人:
- 金额:$ 56.62万
- 依托单位:
- 依托单位国家:美国
- 项目类别:Continuing Grant
- 财政年份:2024
- 资助国家:美国
- 起止时间:2024-02-01 至 2029-01-31
- 项目状态:未结题
- 来源:
- 关键词:
项目摘要
Many cutting-edge applications require heat flow management across successive layers of materials. For example, in the power electronics and radiofrequency electronics used in radars, 5G stations, satellite communications, adapters, inverters, and chargers, the extensive heat generated in the modules needs to be dissipated rapidly through multiple layers of semiconductors in the transistors. In the thermal barrier coatings, hypersonic aircraft thermal protection, and thermoelectrics, the extensive heat needs to be blocked by several layers of different materials. However, heat transport through successive layers and interfaces has not been well understood, impeding the rational design of next-generation chips, electronics, engines, hypersonic vehicles, and other applications. Therefore, the principal aim of this project is to provide an accurate prediction and a deep understanding of thermal transport across successive layers and interfaces of different materials. The project will also encompass significant educational activities, including hands-on science kits and lectures for K-12 students in various local communities, online videos for kids, research internship opportunities for high school students, and a free online graduate course.The goal of this project is to establish a comprehensive understanding of phonon thermal transport across two or more successive solid interfaces, build a formalism and a simulation framework for successive interfacial thermal transport, accurately predict the thermal transport across several technologically important wide-bandgap semiconductor heterostructures, and enhance modern science and engineering education from kindergarten to graduate levels using diverse methods. The project will (1) establish high-accuracy machine learning interatomic potential-based molecular dynamics simulations for successive interfacial thermal transport predictions; (2) develop new Landauer’s formalisms capable of double and multiple interfacial thermal transport; (3) develop a new phonon Boltzmann transport framework for successive interfacial thermal transport; and (4) reveal how the interfacial thermal conductance, thermal conductivity, mode-resolved phonon transmission, reflection, temperature, and heat flux are affected by (i) the presence of and distance from a second interface, (ii) the roughness of the interfaces, (iii) the materials comprising the interfaces, (iv) the phonon excitations in the external heat source, (v) the conditions far from the interface such as the impurities inside the film and the roughness of edges, and (vi) the presence of more interfaces. The results will be integrated into educational programs to enhance learning from kindergarten to graduate levels.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.
许多尖端的应用需要在连续的材料层之间进行热流管理。例如,在雷达、5G站、卫星通信、适配器、逆变器和充电器中使用的电力电子设备和射频电子设备中,模块中产生的大量热量需要通过晶体管中的多层半导体迅速消散。在热障涂层、高超声速飞机热防护和热电材料中,需要用几层不同的材料来阻挡大量的热量。然而,通过连续层和界面的热传输尚未得到很好的理解,这阻碍了下一代芯片、电子产品、发动机、高超音速飞行器和其他应用的合理设计。因此,该项目的主要目的是提供准确的预测和对不同材料的连续层和界面的热传输的深入理解。该项目还将包括重要的教育活动,包括为各个地方社区的K-12学生提供动手科学工具包和讲座,为儿童提供在线视频,为高中生提供研究实习机会,以及免费的在线研究生课程。本项目的目标是全面了解声子在两个或多个连续固体界面上的热输运,建立连续界面热输运的形式化和模拟框架,准确预测几种技术上重要的宽带隙半导体异质结构的热输运,并利用多种方法加强从幼儿园到研究生的现代科学和工程教育。该项目将(1)建立高精度的基于机器学习原子间势能的分子动力学模拟,用于连续界面热输运预测;(2)建立了双界面和多界面热输运的新朗道尔形式;(3)建立了连续界面热输运的声子玻尔兹曼输运框架;(4)揭示界面的热导率、热导率、模式分辨声子传输、反射、温度和热流是如何受到以下因素的影响的:(i)第二界面的存在和距离,(ii)界面的粗糙度,(iii)组成界面的材料,(iv)外部热源中的声子激发,(v)远离界面的条件,如薄膜内部的杂质和边缘的粗糙度,(vi)更多界面的存在。研究结果将被整合到教育项目中,以提高从幼儿园到研究生的学习水平。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。
项目成果
期刊论文数量(0)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
数据更新时间:{{ journalArticles.updateTime }}
{{
item.title }}
{{ item.translation_title }}
- DOI:
{{ item.doi }} - 发表时间:
{{ item.publish_year }} - 期刊:
- 影响因子:{{ item.factor }}
- 作者:
{{ item.authors }} - 通讯作者:
{{ item.author }}
数据更新时间:{{ journalArticles.updateTime }}
{{ item.title }}
- 作者:
{{ item.author }}
数据更新时间:{{ monograph.updateTime }}
{{ item.title }}
- 作者:
{{ item.author }}
数据更新时间:{{ sciAawards.updateTime }}
{{ item.title }}
- 作者:
{{ item.author }}
数据更新时间:{{ conferencePapers.updateTime }}
{{ item.title }}
- 作者:
{{ item.author }}
数据更新时间:{{ patent.updateTime }}
Tianli Feng其他文献
Stakeholder Influences and Organization Responses:A Case Study of Corporation Social Responsibility Suspension
利益相关者影响与组织反应:企业社会责任暂缓案例研究
- DOI:
- 发表时间:
2015 - 期刊:
- 影响因子:2.9
- 作者:
Yuhuan Liu;Tianli Feng;Suichuan Li - 通讯作者:
Suichuan Li
Sub-3 nm Intermetallic ordered Pt3In Clusters for Oxygen Reduction Reaction
用于氧还原反应的亚 3 nm 金属间化合物有序 Pt3In 团簇
- DOI:
10.1002/advs.201901279 - 发表时间:
2020 - 期刊:
- 影响因子:15.1
- 作者:
Qi Wang;Zhi Liang Zhao;Zhe Zhang;Tianli Feng;Ruyi Zhong;Hu Xu;Sokrates T. Pantelides;Meng Gu - 通讯作者:
Meng Gu
Realizing high thermoelectric performance in eco-friendly Bi<sub>2</sub>S<sub>3</sub> with nanopores and Cl-doping through shape-controlled nano precursors
- DOI:
10.1016/j.nanoen.2022.107478 - 发表时间:
2022-09-01 - 期刊:
- 影响因子:
- 作者:
Kangpeng Jin;Janak Tiwari;Tianli Feng;Yue Lou;Biao Xu - 通讯作者:
Biao Xu
Impacts of point defects on shallow doping in cubic boron arsenide: A first principles study
- DOI:
10.1016/j.commatsci.2024.113483 - 发表时间:
2025-01-31 - 期刊:
- 影响因子:
- 作者:
Shuxiang Zhou;Zilong Hua;Kaustubh K. Bawane;Hao Zhou;Tianli Feng - 通讯作者:
Tianli Feng
Large-Scale, Solution-Synthesized Nanostructured Composites for Thermoelectric Applications
用于热电应用的大规模溶液合成纳米结构复合材料
- DOI:
10.1002/adma.201801904 - 发表时间:
2018 - 期刊:
- 影响因子:29.4
- 作者:
Biao Xu;Tianli Feng;Zhe Li;Wei Zheng;Yue Wu - 通讯作者:
Yue Wu
Tianli Feng的其他文献
{{
item.title }}
{{ item.translation_title }}
- DOI:
{{ item.doi }} - 发表时间:
{{ item.publish_year }} - 期刊:
- 影响因子:{{ item.factor }}
- 作者:
{{ item.authors }} - 通讯作者:
{{ item.author }}
{{ truncateString('Tianli Feng', 18)}}的其他基金
Prediction of Thermal Transport in Nonmetallic Materials at Ultra-high Temperatures
超高温下非金属材料的热传输预测
- 批准号:
2212830 - 财政年份:2022
- 资助金额:
$ 56.62万 - 项目类别:
Standard Grant
相似海外基金
Understanding the Role of Mesoscale Atmosphere-Ocean Interactions in Seasonal-to-Decadal Climate Prediction
了解中尺度大气-海洋相互作用在季节到十年气候预测中的作用
- 批准号:
2231237 - 财政年份:2023
- 资助金额:
$ 56.62万 - 项目类别:
Continuing Grant
Understanding and Reducing Racial Bias in Cardiovascular Risk Prediction Using Novel AI Methods
使用新型人工智能方法理解和减少心血管风险预测中的种族偏见
- 批准号:
MR/Y000803/1 - 财政年份:2023
- 资助金额:
$ 56.62万 - 项目类别:
Fellowship
Collaborative Research: NSF-CSIRO: HCC: Small: Understanding Bias in AI Models for the Prediction of Infectious Disease Spread
合作研究:NSF-CSIRO:HCC:小型:了解预测传染病传播的 AI 模型中的偏差
- 批准号:
2302969 - 财政年份:2023
- 资助金额:
$ 56.62万 - 项目类别:
Standard Grant
Collaborative Research: NSF-CSIRO: HCC: Small: Understanding Bias in AI Models for the Prediction of Infectious Disease Spread
合作研究:NSF-CSIRO:HCC:小型:了解预测传染病传播的 AI 模型中的偏差
- 批准号:
2302968 - 财政年份:2023
- 资助金额:
$ 56.62万 - 项目类别:
Standard Grant
Integrative deep learning algorithms for understanding protein sequence-structure-function relationships: representation, prediction, and discovery
用于理解蛋白质序列-结构-功能关系的集成深度学习算法:表示、预测和发现
- 批准号:
10712082 - 财政年份:2023
- 资助金额:
$ 56.62万 - 项目类别:
Collaborative Research: NSF-CSIRO: HCC: Small: Understanding Bias in AI Models for the Prediction of Infectious Disease Spread
合作研究:NSF-CSIRO:HCC:小型:了解预测传染病传播的 AI 模型中的偏差
- 批准号:
2302970 - 财政年份:2023
- 资助金额:
$ 56.62万 - 项目类别:
Standard Grant
Her2 status of breast cancer in diverse populations: improving genetic prediction and understanding molecular correlates
不同人群中乳腺癌的 Her2 状况:改善遗传预测并了解分子相关性
- 批准号:
10660883 - 财政年份:2023
- 资助金额:
$ 56.62万 - 项目类别:
Collaborative Research: ANSWERS: The Satellite Surface Charging Observatory for Prediction, Understanding, Learning, and Industry
合作研究:答案:用于预测、理解、学习和工业的卫星表面充电观测站
- 批准号:
2149783 - 财政年份:2022
- 资助金额:
$ 56.62万 - 项目类别:
Continuing Grant
Collaborative Research: HCC: MEDIUM: Understanding the Present and Designing the Future of Risk Prediction IT in Fire Departments
合作研究:HCC:中:了解消防部门风险预测 IT 的现状并设计未来
- 批准号:
2211360 - 财政年份:2022
- 资助金额:
$ 56.62万 - 项目类别:
Standard Grant
Uncovering causal protein markers to improve prostate cancer etiology understanding and risk prediction in Africans and Europeans
发现因果蛋白标记物以提高非洲人和欧洲人对前列腺癌病因的了解和风险预测
- 批准号:
10446594 - 财政年份:2022
- 资助金额:
$ 56.62万 - 项目类别:














{{item.name}}会员




