Science and Technology Corporation, 111 C Bata Boulevard, Belcamp, Maryland 21017, United States.
U.S. Army CCDC Chemical Biological Center, Aberdeen Proving Ground, Aberdeen, Maryland 21010, United States.
ACS Sens. 2020 Apr 24;5(4):1102-1109. doi: 10.1021/acssensors.0c00042. Epub 2020 Apr 7.
We report the successful use of colorimetric arrays to identify chemical warfare agents (CWAs). Methods were developed to interpret and analyze a 73-indicator array with an entirely automated workflow. Using a cross-validated first-nearest-neighbor algorithm for assessing detection and identification performances on 632 exposures, at 30 min postexposure we report, on average, 78% correct chemical identification, 86% correct class-level identification, and 96% correct red light/green light (agent versus non-agent) detection. Of 174 total independent agent test exposures, 164 were correctly identified from a 30 min exposure in the red light/green light context, yielding a 94% correct identification of CWAs. Of 149 independent non-agent exposures, 139 were correctly identified at 30 min in the red light/green light context, yielding a 7% false alarm rate. We find that this is a promising approach for the development of a miniaturized, field-portable analytical equipment suitable for soldiers and first responders.
我们报告了使用比色阵列来识别化学战剂(CWA)的成功案例。我们开发了方法来解释和分析具有完全自动化工作流程的 73 个指标阵列。使用交叉验证的最近邻算法对 632 次暴露进行检测和识别性能评估,在暴露后 30 分钟,我们报告平均有 78%的化学物质得到正确识别,86%的类别级别得到正确识别,96%的红光/绿光(剂与非剂)检测得到正确识别。在 174 次总独立剂测试暴露中,在红光/绿光背景下,从 30 分钟暴露中正确识别出 164 次,CWA 的正确识别率为 94%。在 149 次独立的非剂暴露中,在红光/绿光背景下,有 139 次在 30 分钟内得到正确识别,错误报警率为 7%。我们发现,这是开发适合士兵和第一响应者的小型化、便携式现场分析设备的一种很有前途的方法。