Automated Functional Nanomaterial Platform for Developing Sensors

Medical simulators emulate aspects of battlefield casualties and serve as effective aids to train soldiers and civilians for Tactical and Routine Combat Casualty Care. There is a need for more comprehensive and lifelike clinical simulated training than current sensors permit. Human-like simulator mannequins also require ease of use, a small footprint, little if any wiring, easy portability, and to have a human feel and reaction. Therefore, new smart sensors, with additional capabilities, increased sensitivity, wireless real-time collection, and tracking for feedback of training progression are highly needed. Major challenges in developing smart sensors include but are not limited to fitting sensors into the mannequin size and shape, providing a human-like feel, and having new capabilities and high sensitivity. Medical mannequins and those in forward arenas should not be cumbersome, with extensive electrical connectivity to external devices, or piping for gas flow. However, current industrial processes of developing these new sensors are labor-intensive and time-consuming. Nanobiofab is developing small wireless sensors with low energy consumption based on its disruptive high-throughput platform that can greatly shorten the discovery timeframe to a few months. Nanobiofab will forward its high throughput AI-powered Inkjet Assisted Nano Printing and Screening (IA-Nano) technology to rapidly discover and develop nano-sensors for Synthetic Tissue, Organ, Nerve, and Skin (STONeS). Nanobiofab can rapidly print large numbers of materials (~10,000 formulations/day) for sensors and screen them in parallel. It has achieved a small and low-energy consumption sensor array in Phase I. During Phase II, Nanobiofab will transit the prototype demonstration to the IA-Nano to discover novel gas sensors and pressure sensors for simulation training, and test feasible methods of incorporation into simulators. The IA-Nano platform will be enhanced to allow 1) automatic operation of material discovery, including synthesis, screening, and recording of experimental procedures; 2) increasing testing samples from 9 to 100 in parallel per chamber, and applying multiple test chambers and 3) development of a Combinatorial Nanomaterial Database for gas/pressure sensors. Nanobiofab will work cooperatively with the Simulation Training and Education for Patient Safety (STEPS) at West Virginia University to integrate our discovered gas and pressure sensors into patient training mannequins and validate the efficacy of the discovered sensors for tangible applications. Nanobiofab will provide/present the DOD with 1) AI-powered high-throughput automated IA-Nano platform, 2) gas sensor array prototype (2-6 gas sensors in single sensor chip); 3) high-density pressure sensor array prototype (2-4 pressure sensing materials) as Phase II deliverables, and be available to provide technical support, should sensor testing on-site at DOD be possible.