RT&L FOCUS AREA(S): Warfighting Requirements (GWR) TECHNOLOGY AREA(S): Chemical/Biological Defense OBJECTIVE: Develop capabilities for contact-free, imaging of aerosol particles from environmental matrices with simultaneous assessment and discrimination of particle morphology. The developed instrumentation must be capable of processing chemical and biological aerosols via point detection at the location of the instrument in real time. The instrumentation should be deployable on an unmanned platform such as unmanned aerial vehicles (UAVs) or unmanned ground vehicle (UGVs). DESCRIPTION: The detection and characterization of airborne aerosol particles is paramount to rapidly sense chemical and biological threats. This is especially true for urban and/or battlespace settings where the aerosol composition can include inorganic, organic, and biological particles with complex morphologies across orders of magnitude in size (1-100 microns (mm)) [1]. Because aerosols contain a large majority of innocuous particles, the detection of possible threat materials is limited by their small concentration within a complex ambient matrix containing materials of non-interest as well as interfering compounds. Moreover, aerosol properties can evolve in time through chemical aging processes (environmental degradation) and mechanical forces. While sensor technology has improved over the last 20 years, threat detection still remains a challenge in operational environments at mission-speed due to the complex and dynamic nature of the surrounding environmental media. An essential aspect of useful methods to investigate such aerosols is to do so in a contact-free manner, which has motivated legacy methods such as elastic light scattering. However, the wide diversity of irregularly shaped aerosol particles presents significant challenges for existing methods often because the measured data cannot be mapped onto particle properties without strong assumptions about a particle's size, shape, and source. These limitations underscore the need for technologies with the ability to directly provide particle images, allowing individual particle morphology and orientation to achieve increased detection and characterization confidence. Current capabilities for this purpose that do not involve particle collection or trapping are highly limited. New methods have been developed to image free-flowing aerosol particles on the single and multi-particle level via optical light scattering and holographic imaging [2-4]. Recent efforts have also introduced machine-learning techniques capable of differentiating particle morphology [4]. Leveraging these and similar recent developments in determining morphological properties has the potential to generate a capability that could augment the Department of Defense's current and/or future aerosol particle detection systems by providing a layered approach to distinguish background particles from potential threat agents. But to do so will require the development of sensing instrumentation capable of rapidly imaging particles and characterizing their material composition both autonomously and rapidly. The imaging capability should overlap with the inhalable particle-size range and rely on methods that are contactless and free from conventional assumptions such as particle levitation or flow-through technologies. Analysis of the image data should, at a minimum, enable classification of the particles based upon both size and morphology with the intent that it could queue subsequent non-imaging particle diagnostics. Particle material composition should consist of, at a minimum, the ability to differentiate between absorbing and non-absorbing components present, and be able to discriminate biological from non-biological particles or components within particles. PHASE I: Phase I entails the design of a concept for a rapid, contact-free comprehensive system for aerosol particles. The study should lead to a proof-of-concept or demonstration that outlines an unmanned aerial or ground vehicle-based system consisting of all the elements of a contact-free method to image inhalable-sized aerosol particles. The Phase I project should focus on the discrimination of at least one biological and one non-biological species in the 1-100 mm (micron) size-fraction (i.e., with improved detection performance over current methods). The accompanying architecture required to integrate machine learning techniques for particle differentiation should also be considered. The Phase I project should also define a clear path forward for designing a prototype with low size, weight, and power (SWaP) to enable deployment on unmanned vehicles. Chemical and biological threats of all classes are of interest for sensing and identification. Examples include biological spores, such as anthrax or simulants thereof (that can be accessed by the small business offeror), and allergens like pollens. The Phase I final report must explain in detail the contact-free detection method selected, software concepts, hardware requirements, and identify potential use cases and limitations. PHASE II: Mature the concept into a pre-production portable instrument prototype integrating the capabilities outlined in the concept developed during Phase I. The key deliverable of Phase II will be the demonstration of the system in a relevant environmental setting where the prototype is capable of sampling upwards of 100 particles per second and classifying chemical and biological simulants to within 90% accuracy. Evaluation of the machine-learning particle-detection algorithms will be extended to multiple threat vectors. The system will be benchmarked against standard techniques of aerosol identification. An initial analysis of the commercial applications of the system will be conducted, focusing on the baseline cost of the system and the market space addressed by the technology development. PHASE III: The small business will pursue commercialization of the technologies developed in Phase II for potential government and commercial applications. Government applications include rapid detection of chemical and biological threat aerosols. PHASE III DUAL USE APPLICATIONS: Contact-free aerosol imaging and identification has the potential to be integrated into ongoing Department of Defense programs including the Nuclear, Biological and Chemical Reconnaissance Vehicle Sensor Suite Upgrade (NBCRV SSU) program and the Joint Biological Tactical Detection System (JBTDS) program. The system could similarly be installed on UAVs and UGVs used by other agencies responsible for chemical and biological threat surveillance such as the Department of Homeland Security (DHS). The successful product can also fulfill air quality environmental applications such as assessing pollutants, dust loading, smoke and pollen for commercial applications and for use by government agencies including the U.S. Environmental Protection Agency (EPA). REFERENCES: 1. P. Kulkarni, P. A. Baron, K. Willeke (eds.) Aerosol Measurement: Principles, Techniques, and Applications, 3rd ed., (Wiley, 2011). 2. M. J. Berg, G. Videen, Digital holographic imaging of aerosol particles in flight, J. Quant. Spectrosc. Radiat. Transfer 112, p. 1776-1783 (2011). 3. O Kemppinen, JC Laning, RD Mersmann, G Videen, MJ Berg, Imaging atmospheric aerosol particles from a UAV with digital holography, Nature Scientific Reports 10 (1) 1-12 (2020). 4. P Piedra, A Kalume, E Zubko, D Mackowski, YL Pan, G Videen, Particle-shape classification using light scattering: An exercise in deep learning, Journal of Quantitative Spectroscopy and Radiative Transfer 231, 140-156 (2019). KEYWORDS: Chemical/Biological Threat Detection, sensors, aerosols, environmental sampling; environmental surveillance
