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.

这项小型企业创新研究（SBIR）I阶段项目的更广泛/商业影响将推动开发一种新方法来进行红外光谱，这是生命科学，材料开发和制药行业中的重要工具。化学生产商将在2020年在分析仪器上花费约1.4亿美元。仪器概念基于人类视觉，该概念可以从仅从三种类型的光敏感锥中提取的信号中推断出大约1000万颜色，这些信号具有重叠的灵敏度以测量颜色组合。提出的解决方案使用相同的体系结构，用单个设备代替多个仪器。这个SBIR I期项目将推进算法光谱工具的翻译。该程序利用新的热发射器技术具有可调的中心发射频率（2-10微米波长），该程序将证明可以从一系列非分散性吸收测量值中恢复光谱信息。该技术将人类视觉系统用作模型，并将多个发射器与重叠的发射光谱配对，并与低成本，非分散性红外探测器（例如热电器）配对。提出的解决方案将通过证明对特征CO2吸收带的敏感性，并通过算法对CO2光谱重建算法，在3800-2100 cm-1的频率范围内开发算法光谱溶液。成功完成拟议的努力将为新的红外光谱技术建立基准，该基准在没有昂贵的分散元素或移动零件的情况下运作。该奖项反映了NSF的法定任务，并被认为是值得通过基金会的知识分子优点和更广泛的审查标准通过评估来进行评估的。