N95 respirators became scarce to the general public in mid-to-late March of 2020 due to the SARS-CoV-2 epidemic. By mid-April of 2020, most states in the United States were requiring face coverings to be worn while in public enclosed places and in busy outdoor areas where groups of people were in close proximity. Many resorted to cloth masks, homemade masks, procedure masks obtained through online purchases, and other ad-hoc means. Thus, there was and still is a need to determine the aerosol filtration efficacy of commonly available materials that can be used for homemade mask construction. This study focused on non- woven polymeric fabrics that are readily available for homemade mask construction. The conclusion of this study is that non-woven materials that carry a high electric charge or those that can easily acquire charge had the highest aerosol filtration efficiency per unit of pressure drop. Future work should examine a wider variety of these materials and determine the maximum pressure drop that a nominal homemade mask can withstand before a significant portion of airflow is diverted around the mask. More broadly, a better understanding of the charge state on non-woven materials and impact of that charge state on filtration efficiency is needed.
A novel derivative of a previously-published polymeric material has been synthesized and developed into an easily-sprayable coating. Surface characterization of coatings confirm correct elemental presence, and viral assays reveal quantitative elimination of MS2 bacteriophage and Phi6 bacteriophage, surrogates used for SARS-CoV-2, in as little as 5 minutes upon contact. Furthermore, an N95 mask was dip-coated in the polymer solution and analyzed through microscopy and filtration efficacy testing. Though coating was successful, electrostatic interactions between mask layers and polymer reduced filtration efficacy significantly. As such, we expect the current results of this work to be applicable on non-respiratory PPE and on solid substrates of commonly-touched surfaces for rapid self-decontamination.
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.
The evaluation of optical system performance in fog conditions typically requires field testing. This can be challenging due to the unpredictable nature of fog generation and the temporal and spatial nonuniformity of the phenomenon itself. We describe the Sandia National Laboratories fog chamber, a new test facility that enables the repeatable generation of fog within a 55m×3m×3m (L×W×H) environment, and demonstrate the fog chamber through a series of optical tests. These tests are performed to evaluate system image quality, determine meteorological optical range (MOR), and measure the number of particles in the atmosphere. Relationships between typical optical quality metrics, MOR values, and total number of fog particles are described using the data obtained from the fog chamber and repeated over a series of three tests.
Degraded visual environments are a serious concern for modern sensing and surveillance systems. Fog is of interest due to the frequency of its formation along our coastlines disrupting border security and surveillance. Fog presents hurdles in intelligence and reconnaissance by preventing data collection with optical systems for extended periods. We will present recent results from our work in operating optical systems in our controlled fog experimental chamber. This facility is a 180-foot-long, 10-foot-wide, and 10-foot-Tall structure that has over 60 spray nozzles to achieve uniform aerosol coverage with various particle size, distributions, and densities. We will discuss the physical formation of fog in nature and how our generated fog compares. In addition, we will discuss fog distributions and characterization techniques. We will investigate the biases of different methods and discuss the different techniques that are appropriate for realistic environments. Finally, we will compare the data obtained from our characterization studies against accepted models (e.g., MODTRAN) and validate the usage of this unique capability as a controlled experimental realization of natural fog formations. By proving the capability, we will enable the testing and validation of future fog penetrating optical systems and providing a platform for performing optical propagation experimentation in a known, stable, and controlled environment.