Collaborative Research: Amplifying the Efficiency of Tungsten Disulfide (WS2) Thermoelectric Devices
Collaborative Research: Amplifying the Efficiency of Tungsten Disulfide (WS2) Thermoelectric Devices
批准号:
1901864
负责人:
Feng Xiong
金额:
$27.0万
依托单位:
依托单位国家:
美国
项目类别:
Standard Grant
财政年份:
2019
资助国家:
美国
项目状态:
已结题
起止时间:
2019-06-01 至 2023-05-31
中文摘要
非技术:美国每年有多达一半的能源生产作为废热损失掉。将废热转化为电能可以大大提高能源效率,并大幅减少温室气体排放。热电(TE)设备将温差转化为电能,有可能彻底改变国家的能源组合。理想的热电材料只导电,不导热。金属两者都导电,而绝缘体两者都不导电。这个项目通过使用一种新的策略来掺杂二硫化钨,一种二维(2D)半导体,挑战了这种二分法。我们将提高其热电系数,以最大限度地提高输出电压;提高电导率,以尽量减少损耗;降低导热系数,以保持较大的温差。所提出的研究将导致废热回收的有效装置。这项工作还将实现用于热管理的高性能2D晶体管、低功耗存储器件和纳米级开关。该团队将与当地社区紧密合作,鼓励不同背景的学生参与工程事业,并培养对纳米技术的兴趣。拓展工作将包括实验室演示、暑期实习和职业研讨会。技术:该项目的目标是通过电化学插层对二维二硫化钨(WS2)器件的电学、热学和热电性能进行改造,提高其平面内热电效率。WS2由于其大的原子质量(低导热系数)、小的带隙(高导电性)和高塞贝克系数,最近成为一种有前途的TE候选者。然而,优化所有材料特性以最大限度地提高其TE效率并掺杂这种2D材料以创建TE器件所需的p型和n型对仍然具有挑战性。在这项工作中,我们将:(1)通过阴离子和阳离子插层在二维材料中实现p型和n型掺杂;(2)通过掺杂优化WS2的面内功率因数;(3)通过插入物的声子散射降低WS2的面内导热系数。从根本上说,这个项目将研究二维材料中的电、离子和热输运。实际上,这项工作将为热电装置的广泛应用铺平道路,以清除来自电子和人体等来源的热量。这项工作还将开发一种用于二维材料的掺杂方法,解决二维电子器件中的关键问题,如低驱动电流和不良接触电阻。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。
英文摘要
Nontechnical:As much as half of US energy production each year is lost as waste heat. Converting waste heat into electricity could improve energy efficiency dramatically and sharply reduce greenhouse gas emissions. Thermoelectric (TE) devices convert temperature differences into electrical power and have the potential to revolutionize the nation's energy portfolio. An ideal thermoelectric material conducts electricity, but not heat. Metals conduct both, whereas insulators conduct neither. This project challenges this dichotomy by using a novel strategy to dope tungsten disulfide, a two-dimensional (2D) semiconductor. We will enhance its thermoelectric coefficient to maximize the output voltage, increase the electrical conductivity to minimize losses, and lower the thermal conductivity to maintain a large temperature difference. The proposed research will lead to efficient devices for waste heat recovery. This work will also enable high-performance 2D transistors, low-power memory devices, and nanoscale switches for thermal management. The team will work closely with local communities to encourage participation by students from all backgrounds in engineering careers and foster interest in nanotechnology. Outreach efforts will include lab demonstrations, summer internships, and career workshops.Technical:The goal of this project is to improve the in-plane thermoelectric efficiency of two-dimensional tungsten disulfide (WS2) devices through engineering their electrical, thermal, and thermoelectric properties via electrochemical intercalation. WS2 has recently emerged as a promising TE candidate due to its large atomic mass (low thermal conductivity), small bandgap (high electrical conductivity), and high Seebeck coefficient. However, it remains challenging to optimize all of the material properties to maximize its TE efficiency and to dope this 2D material to create the p- and n-type pairs needed for TE devices. In this work, we will: (1) achieve p- and n-type doping in 2D materials via anion and cation intercalations; (2) optimize the in-plane power factor of WS2 through doping; (3) reduce the in-plane thermal conductivity of WS2 via phonon scattering by intercalants. Fundamentally, this project will study electrical, ionic, and thermal transport in 2D materials. Practically, this work will pave the way for the wide use of thermoelectric devices to scavenge heat from sources such as electronics and the human body. This work will also develop a doping method for 2D materials, addressing critical issues in 2D electronics such as low drive current and poor contact resistance.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.
期刊论文(4)
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CAREER: Scalable Ionic Gated 2D Synapse (IG-2DS) with Programmable Spatio-Temporal Dynamics for Spiking Neural Networks
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批准号:1943683
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项目类别:Continuing Grant
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资助金额:$50.0万
-
财政年份:2020
-
负责人:Feng Xiong
-
依托单位:
Collaborative Research: Two-dimensional Synaptic Array for Advanced Hardware Acceleration of Deep Neural Networks
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批准号:1955453
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项目类别:Standard Grant
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资助金额:$30.0万
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财政年份:2020
-
负责人:Feng Xiong
-
依托单位:
FET: Small: Neuromorphic Spiking Neural Networks with Dynamic Graphene Synapses for Event-based Computation
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批准号:1909797
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项目类别:Standard Grant
-
资助金额:$50.0万
-
财政年份:2019
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负责人:Feng Xiong
-
依托单位:
国内基金
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