STTR Phase I: Algorithmic Mid-Infrared Spectroscope Utilizing Narrow-Band, Epsilon-Near-Zero Thermal Emitters

STTR 第一阶段：利用窄带、Epsilon 近零热发射器的算法中红外光谱仪

• 批准号: 2014798
• 负责人: Edward Sachet
• 金额: $ 22.5万
• 依托单位: THIRD FLOOR MATERIALS, INC.
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2020
• 资助国家: 美国
• 起止时间: 2020-06-01 至 2021-05-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2014798&HistoricalAwards=false
• 关键词: STTR; Phase; Algorithmic; Mid; Infrared

The broader/commercial impact of this Small Business Innovation Research (SBIR) Phase I project will advance the development of a new method to conduct infrared spectroscopy, an important tool in the life sciences, materials development and pharmaceutical industries. Chemical producers will spend an estimated $140 million on analytical instrumentation in 2020. The instrument concept is based on human vision, which can deduce roughly 10 million colors from the signals extracted from just three types of light-sensitive cones that have overlapping sensitivity to measure color combinations. The proposed solution uses the same architecture, replacing multiple instruments with a single device. This SBIR Phase I project will advance the translation of an algorithmic spectroscopy tool. Utilizing newly available thermal emitter technology with tunable center emission frequency across the infrared (2-10 microns wavelength), the program will demonstrate that spectroscopic information can be recovered algorithmically from a series of non-dispersive absorption measurements. The technology uses the human vision system as a model and pairs multiple emitters with overlapping emission spectra with low-cost, non-dispersive infrared detectors, such as thermopiles. The proposed solution will develop an algorithmic spectroscopy solution at a frequency range of 3800-2100 cm-1 by demonstrating sensitivity to the characteristic CO2 absorption bands and algorithmically reconstructing the CO2 spectrum. Successful completion of the proposed effort will establish the benchmarks for a new infrared spectroscopy technology that operates without costly dispersive elements or moving parts.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.

这一小型企业创新研究(SBIR)第一阶段项目的广泛/商业影响将推动红外光谱新方法的开发，红外光谱是生命科学、材料开发和制药行业的重要工具。2020年，化学品生产商将在分析仪器上花费约1.4亿美元。该仪器的概念是基于人类视觉的，仅从三种感光锥体提取的信号就可以推断出大约1000万种颜色，这三种光敏锥体具有重叠的灵敏度来测量颜色组合。建议的解决方案使用相同的架构，将多台仪器替换为一台设备。这个SBIR第一阶段项目将推进算法光谱学工具的翻译。利用最新可用的热发射器技术，在整个红外线(2-10微米波长)上具有可调的中心发射频率，该计划将证明可以通过算法从一系列非色散吸收测量中恢复光谱信息。该技术以人类视觉系统为模型，将发射光谱重叠的多个发射器与低成本、非分散的红外探测器(如热电堆)配对。建议的解决方案将通过展示对特征二氧化碳吸收波段的敏感性并通过算法重建二氧化碳光谱，在3800-2100厘米-1的频率范围内开发出算法光谱学解决方案。拟议工作的成功完成将为一种新的红外光谱技术建立基准，该技术在没有昂贵的色散元素或移动部件的情况下运行。该奖项反映了NSF的法定使命，并通过使用基金会的智力优势和更广泛的影响审查标准进行评估，被认为值得支持。