SBIR Phase I: Multi-Step Sequential Processing of Gas Ions for Identifying Volatile Organic Compounds in Recirculated Air of Energy Efficient Buildings
SBIR Phase I: Multi-Step Sequential Processing of Gas Ions for Identifying Volatile Organic Compounds in Recirculated Air of Energy Efficient Buildings
批准号:
2035894
负责人:
Peter Fowler
金额:
$25.54万
依托单位:
依托单位国家:
美国
项目类别:
Standard Grant
财政年份:
2021
资助国家:
美国
项目状态:
已结题
起止时间:
2021-03-15 至 2023-02-28
中文摘要
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英文摘要
The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase I project is to improve human health, energy savings, and improved environment. Increased urbanization worldwide and demand for high quality, comfortable ambient air environments is expected to drive an existing market for improved heating, ventilation, and air conditioning (HVAC) systems estimated at $12 billion nationally and $190 billion worldwide by 2026. Respiratory disease and human illness are attributed to unregulated amounts of these constituents in indoor air. This project will inform users about the concentrations and identities of volatile organic compounds (VOCs) in recirculated indoor air from energy-efficient HVAC systems. This will inform clinical analyses of disease, industrial process monitoring, screening of food purity and authenticity, and commercial aviation security. This SBIR Phase I project will leverage discoveries in the chemistry of ion fragmentation in strong electric fields in air at ambient pressure and the association of these fragments with molecular identity. Additional merit is derived from algorithms for identification of ion spectra, dependences of fragmentation on electric field strength, and processes to handle ions both in the initial step of ion selection and the final stage of fragment ion analysis. This will be a novel exploration of strong electric field fragmentation of gas ions at ambient pressure. Research objectives include tasks to establish broad understanding of mechanisms of ion fragmentation of volatile organic compounds as gas ions at ambient pressure and establishing autonomous molecular identification using spectral profiles from mobility analysis. The research is organized into three phases including the development of efficient, advanced control of ion fragmentation, the discovery of chemical rules governing ion fragmentation, and the integration of artificial intelligence with chemical instrumentation developed in this project. The key technical result anticipated in this project is a chemical analyzer for autonomous monitoring of the quality of recirculated indoor air in green heating, ventilation, and air conditioning systems in green buildings.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(1)
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会议论文
Neural network classification of mobility spectra for volatile organic compounds using tandem differential mobility spectrometry with field induced fragmentation
使用串联微分迁移谱法和场诱导碎裂对挥发性有机化合物的迁移谱进行神经网络分类
DOI:
10.1016/j.aca.2023.341047
发表时间:
2023
期刊:
Analytica Chimica Acta
影响因子:
6.2
作者:
[Fowler, P.E., Bernat, T., Pilgrim, J.Z., Eiceman, G.A.]
通讯作者:
Eiceman, G.A.
国内基金
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