Impossible Sensing LLC — Department of Energy SBIR Phase I: 32a
Impossible Sensing LLC — SBIR Phase I award from Department of Energy.
- Amount
- $249,586
- Agency
- Department of Energy
- Program / Phase
- SBIR · Phase I
- Topic
- 32a
- NAICS
- —
- Place of performance
- MO
- Period
- 2021-02-22 → 2021-11-21
Description
Monitoring and improving the health and quality of soil is a major concern in the agriculture and biofuel industries and the most useful indicator of soil health organic matter content. Thus, measurement of soil organic matter is critical to increasing crop yields while mitigating the environmental impacts of food and biofuel feedstock production. Current methods require growers to rely on costly and time-consuming sampling and laboratory analyses to assess organic matter and overall soil health. We will develop a durable, lightweight bioimager for quantitative and qualitative analysis of organic matter. This technology will perform real-time, non-destructive, and easily interpretable assessments of soil organic matter in the field. Our innovation can also be configured for attachment to most standard microscopes for complimentary micron-scale imaging. In Phase I we will demonstrate the performance of our organic matter bioimager concept, determine requirements for a commercial imager, and design and optimized an engineering model suitable for Phase II incorporation with robotics systems and on-site field testing. These Phase I efforts are supported by two Ag-Tech and Bio-Tech companies who participate in our R/R&D and business development. Cost-effective and fieldable imagers such as these will [1] provide real-time onsite assessment of soil organic matter quality and quantity; [2] capture spatiotemporal variation and flux within soils in relation to plant roots, soil layers, or other features; [3] provide on-board analysis that generates easily interpretable data and imagery. We estimate cumulative sales net revenues of $115m during the first 10 years of commercialization. The key metrics of our financial model were derived by testing our hypotheses with our customers and partners.