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Persistent Antiseptic Peroxide from Silica

Award Information
Agency: Department of Defense
Branch: Air Force
Contract: FA8649-21-P-0327
Agency Tracking Number: FX203-CSO1-0520
Amount: $49,906.90
Phase: Phase I
Program: SBIR
Solicitation Topic Code: AF203-CSO1
Solicitation Number: X20.3
Solicitation Year: 2020
Award Year: 2021
Award Start Date (Proposal Award Date): 2021-02-05
Award End Date (Contract End Date): 2021-05-08
Small Business Information
171 E Krepps Rd
Xenia, OH 45385-9778
United States
DUNS: 117561566
HUBZone Owned: No
Woman Owned: No
Socially and Economically Disadvantaged: No
Principal Investigator
 Steven Quillin
 (513) 377-9101
Business Contact
 Kenneth Edge
Phone: (937) 623-4304
Research Institution

The potential for exposure to microbes, toxins, and pollutants in the environment presents an ongoing challenge to Airmen during routine operations and training.  One of the major lessons learned from the novel coronavirus Covid-19 pandemic is that our deployed warfighters are vulnerable to diseases and infection when stationed in theater away from the protections afforded by the U.S. doctors, hospitals, and accessibility to medicines.  To combat this ongoing vulnerability, to reduce potential exposure, and to provide persistent protection to these threats, an on-demand antiseptic hydrogen peroxide system for uniforms, fabrics, cloths, or surfaces is proposed.  A silica-coating technology that wicks water from the surrounding environment to produce hydrogen peroxide is proposed.  This technology would be low-cost, utilize green chemistry principles, and would provide a warfighter-safe protective barrier to unknown environmental exposure. The active persistent antiseptic technology will protect the individual wearer and the warfighter unit by limiting the possibility of unintentional transmission and contact exposure.  In this Phase I effort, an initial experimental design and demonstration will facilitate parameterizing the molecular dynamics and modeling and simulation inputs for Phase II technology optimization and manufacturing using an iterative modeling-experimental design.  

* Information listed above is at the time of submission. *

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