This communication is the final report for the project Utilizing Highly Scattered Light for Intelligence through Aerosols funded by the Laboratory Directed Research and Development (LDRD) program at Sandia National Laboratories and lasting six months in 2019. Aerosols like fog reduce visibility and cause down-time that for critical systems or operations are unacceptable. Information is lost due to the random scattering and absorption of light by tiny particles. Computational diffuse optical imaging methods show promise for interpreting the light transmitted through fog, enabling sensing and imaging to improve situational awareness at depths 10 times greater than current methods. Developing this capability first requires verification and validation of diffusion models of light propagation in fog. For this reason, analytical models were developed and compared to experimental data captured at the Sandia National Laboratory Fog Chamber facility. A methodology was developed to incorporate the propagation of scattered light through the imaging optics to a pixel array. The diffusion approximation to the radiative transfer equation was found to predict light propagation in fog under the appropriate conditions.
Exposure to chemicals in everyday life is now more prevalent than ever. Air and water pollution can be delivery mechanisms for toxins, carcinogens, and other chemicals of interest (COI). A compact, multiplexed, chemical sensor with high responsivity and selectivity is desperately needed. We demonstrate the integration of unique Zr-based metal organic frameworks (MOFs) with a plasmonic transducer to demonstrate a nanoscale optical sensor that is both highly sensitive and selective to the presence of COI. MOFs are a product of coordination chemistry where a central ion is surrounded by a group of ligands resulting in a thin-film with nano-to micro-porosity, ultra-high surface area, and precise structural tunability. These properties make MOFs an ideal candidate for gaseous chemical sensing, however, transduction of a signal which probes changes in MOF films has been difficult. Plasmonic sensors have performed well in many sensing environments, but have had limited success detecting gaseous chemical analytes at low levels. This is due, in part, to the volume of molecules required to interact with the functionalized surface and produce a detectable shift in plasmonic resonance frequency. The fusion of a highly porous thin-film layer with an efficient plasmonic transduction platform is investigated and summarized. We will discuss the integration and characterization of the MOF/plasmonic sensor and summarize our results which show, upon exposure to COI, small changes in optical characteristics of the MOF layer are effectively transduced by observing shifts in plasmonic resonance.