ZYMOSENSE INC. — Department of Commerce SBIR Phase I: NIST Patent
ZYMOSENSE INC. — SBIR Phase I award from Department of Commerce.
Phase I SBIR feasibility signal
- Phase I awards fund proof-of-concept work. For capture teams, they mark early interest from Department of Commerce in a technical approach.
- Watch for Phase II follow-ons from the same firm/topic family — that conversion path is where budgets and transition pressure rise.
- Obligated amount $100,000. Cross-check similar awards in the same agency and technology tags for going-rate context.
- Topic code NIST Patent links this award to a solicitation family — search the same topic stem for incumbents and recompete timing.
- Amount
- $100,000
- Agency
- Department of Commerce · National Institute of Standards and Technology
- Program / Phase
- SBIR · Phase I
- Topic
- NIST Patent
- Solicitation
- 2021-NIST-SBIR-01
- NAICS
- —
- Place of performance
- IA
- Period
- 2021-08-01 → 2022-03-31
Description
Aqueous two phase (ATP) systems have been developed and patented by NIST for separation of chiral pure single walled carbon nanotubes (SWCNT). These methods have been successfully deployed at bench-scale in many laboratories around the world but have yet to be demonstrated in an automated, scalable manufacturing method. It is the intent of this Phase I project to license this IP from NIST and complete proof of concept of an automated ATP system that includes 1) modularity of surfactant and polymer screening, 2) temperature swing control, and 3) surfactant or wrapping removal. We will determine if ATP separation improves SWCNT sensor fluorescence and batch to batch variability. Upon success of Phase I, the Phase II project would use this automated ATP system to probe the design space of single chirality purification to develop most efficient protocols for a library of SWCNT types (starting with 6,5 and 7,5 for efficient sensor applications). At Zymosense Inc. we build SWCNT based probes for measuring the activity of enzymes in complex solutions. This automation platform will allow us to improve signal to noise, standardize batch to batch variability, and enable single well multiplexing.