SBIR/STTR Research Award

SBIR Phase I: Passive Cooling Materials for Transparent Applications in Refrigerated Trucking and Solar

Award identifier 9231ebac5486163f561334768437d1e0e8deef5e4912367075a732cb3d5dfa15Awarding agency National Science Foundation

Award amount

$225,000

Program and phase

SBIR · Phase I

Award year

2019

Explore This Research Award in CaptureIQ

Research the technology, evaluate the recipient and agency, identify related opportunities, and explore potential follow-on work with CaptureIQ.

Award details

Awarding agency
National Science Foundation
Branch
Not reported
Recipient company
HEAT INVERSE, LLC
Proposal award date
2019-07-01
Contract end date
2020-06-30
UEI
NLEVJKWQZHB5
Solicitation number
Not reported
Topic code
MI

Research abstract

The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase I project is to overcome the barrier to transparent passive radiative cooling materials that are applicable to commercial environments. The project develops a transparent passive cooling thin-film applicable to situations that lose efficiency when heated, and where both mechanical and thermal stress are involved, for example, over advertisements on refrigerated trucks, or on the front face of solar panels. It will provide the simultaneous qualities of transparency in visible wavelengths, durability to withstand the elements, flexibility for ease of application, high cooling power to address customers' pain points, and manufacturability in a roll to roll format to minimize costs. The technology has the potential to provide a 25-80% increase in fuel efficiency via application of the thin-film to the outside of refrigerated truck trailers. The benefits to customers include: fuel cost savings, reduced emissions, allowing regulatory requirements to be met, decreased maintenance and replacement costs compared to refrigeration units and in-truck insulation in truck, as well as temperature maintenance in maximum heat. This Small Business Innovation Research (SBIR) Phase I project seeks to develop a thin-film product that could revolutionize cooling technologies across a number of industries. The demand for temperature-sensitive goods is expected to continue to grow significantly. To address the need for refrigeration with reduced fuel costs and emissions, the project is developing selective photonic emitters in thermal wavelength windows such that instead of heat being effectively enclosed in an insulating thermos (the atmosphere), they are exposed to a vast cold sink of space. The result is a revolutionary method of entirely passive heat management. This approach will be optimized in a thin-film photonics material that provides significant cooling to refrigerated truck trailers, saving refrigeration fuel costs. Phase I research objectives will establish proof of feasibility and include producing and testing promising material combinations at wafer-scale, testing to ensure that the material's qualities transfer to a commercially relevant size, and performing a small-scale test with potential customers. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

Technology keywords

Not reported

Other awards by this recipient

Verified by the same UEI. These are other public SBIR/STTR award pages, not a merged company record.

Research funding history

2 SBIR/STTR records share this UEI (2019–2022). Reported award amounts total $1,225,000. Reported amounts are not federal obligations.

Phases: Phase II, Phase I

Agencies: National Science Foundation

Agency intelligence

National Science Foundation

Back to SBIR/STTR Research Awards

Don't take our word for it. Ask AI about RFPCapture.

See what leading AI assistants have to say about RFPCapture and CaptureIQ.

Gemini opens without a prefilled question. The question is copied to your clipboard when the button works. You can also copy it here:

What is RFPCapture.com and its CaptureIQ platform from Smart Logic AI? How does it help federal contractors discover opportunities, evaluate bid/no-bid decisions, research government contracts, and prepare proposals? How does it compare with other federal capture platforms? Use independent sources where available.