课题基金 / 基金详情

PFI-TT: Rechargeable Battery Cell Testing with magnetic resonance imaging (MRI).

PFI-TT: Rechargeable Battery Cell Testing with magnetic resonance imaging (MRI).
PFI-TT:使用磁共振成像 (MRI) 进行可充电电池测试。
批准号:
1827585
负责人:
Alexej Jerschow
金额:
$20.0万
依托单位:
依托单位国家:
美国
项目类别:
Standard Grant
财政年份:
2018
资助国家:
美国
项目状态:
已结题
起止时间:
2018-08-15 至 2020-01-31

项目摘要

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中文摘要
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英文摘要
The broader impact/commercial potential of this PFI project are the development are to advance battery technology through an unprecedented type of diagnostic. Batteries are at the heart of energy saving, energy efficiency, and energy resilience initiatives, and thus directly contribute to health and wellness, competitiveness, and national defense of the US. The participants (postdocs, graduate students) working on this project will be trained in both science and entrepreneurship, which will provide them with a unique preparation for their next career steps. The new tool, based on magnetic resonance imaging (MRI), will provide fast and nondestructive means of classifying, assessing, and validating battery cells, and thus provide manufacturers and users a means of determining changes in the inside workings of cells throughout the battery life. This new possibility will help save costs, improve safety of battery usage (e.g. in cell phones, cars, and airplanes), and leverage battery technology for next-generation applications. The proposed project will develop a proof-of-concept methodology for a new diagnostic for batteries in a scalable version of the instrumentation and implementation. Safety and capacity are the two most important characteristics of advanced batteries, but battery testing is currently limited to techniques that do not provide sufficient detail to properly assess the correct operation of a device. The technique developed herein is based on magnetic resonance imaging (MRI), is fast, completely non-invasive and can be performed on batteries while they are being charged or discharged. This proposal aims to clear technological hurdles towards implementing the methodology on a small footprint low-field and low-cost MRI instrumentation, which is an important step towards commercialization. Furthermore, the technique will be optimized for speed, tuned with regard to repeatability and reproducibility and will be adjusted to provide specific battery fingerprints, which can be used to classify cells. As a result, a proof-of-concept implementation of the technology will be developed, and the work may result in industrial partnerships, intellectual property development, and technology spinout.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.
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