SBIR/STTR Research Award

Software for the Predictive Synthesis of Nanoparticles in Plasmas

Award identifier f446113143e63368544bb7ea37a28d68da17a3b273773cb010d852cc54b9b708Awarding agency Department of Energy

Award amount

$1,009,726

Program and phase

SBIR · Phase II

Award year

2017

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
Department of Energy
Branch
Not reported
Recipient company
TECH-X CORPORATION
Proposal award date
2017-07-31
Contract end date
2019-07-30
UEI
VJ7GKNR3MEM3
Solicitation number
DE-FOA-0001646
Topic code
23b

Research abstract

Fundamental understanding of the processes which govern the formation of nanoparticles is required to design industrial-scale automated mass production units. Detailed characterization of the plasma in nanoparticle growth regions enables identification of the parameters influencing the formation of nanoparticles in plasmas. However, since it is very difficult and time-consuming to directly measure the spatial distributions of plasma parameters, numerical simulation is essential to model, understand and predict the growth of nanoparticles in plasmas. A new module will be developed in Tech-X Corporation’s US fluid-plasma simulation software to model plasma sources and nanoparticle growth. Simulation results will be validated against the experiments conducted at The George Washington University (GWU). The simulation software along with the growth models will enable the researchers to conduct feasibility studies of their synthesis process and its sustainability. A new numerical model was implemented in USim software to simulate the arc discharge source using a multi-domain infrastructure. First principles continuum diffusion model was demonstrated in USim to predict the growth of the 2d layered nanoparticles. Experiments were set up, graphene was synthesized, characterized and the plasma discharge parameters were measured. The trends predicted by the simulations showed good agreement with the experiments. A robust and comprehensive simulation package will be developed for the predictive synthesis of nanoparticles. The numerical models implemented during Phase I will be improved for faster and accurate simulation of arc discharge sources and low-pressure synthesis conditions. Validation database will be extended by including semiconducting material synthesis and measuring more plasma parameters including species concentrations. US will be validated against the newly generated benchmarks. The software developed will be essential for designing the synthesis technique as well as the required equipment used in nanomaterial synthesis and plasma device industries including the ion source devices. As a spin-off, the coupled heat transfer capabilities will increase sales in several related areas such as aerothermal heating and material degradation in hypersonic vehicle simulations, internal combustion simulations in the automobile industry, and electronics cooling.

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.

Awards with the same topic code

Verified by an exact topic code match. This is not a text-similarity match.

Research funding history

299 SBIR/STTR records share this UEI (1994–2025). Reported award amounts total $109,779,617. Reported amounts are not federal obligations.

Phases: Phase I, Phase II, Phase II – Direct to Phase II

Agencies: Department of Energy, Department of Defense, National Aeronautics and Space Administration, Department of Education, Department of Commerce

Agency intelligence

Department of Energy

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.