DESC0023917
Project Grant
Overview
Grant Description
Mid-IR UAV-based sensing platform with deep learning to identify and quantify gaseous emission in gas flares.
Awardee
Grant Program (CFDA)
Awarding Agency
Funding Agency
Place of Performance
Austin,
Texas
78757-7598
United States
Geographic Scope
Single Zip Code
Related Opportunity
Omega Optics was awarded
Project Grant DESC0023917
worth $250,000
from the Office of Science in July 2023 with work to be completed primarily in Austin Texas United States.
The grant
has a duration of 1 year and
was awarded through assistance program 81.049 Office of Science Financial Assistance Program.
The Project Grant was awarded through grant opportunity FY 2023 Phase I Release 2.
SBIR Details
Research Type
STTR Phase I
Title
Mid-IR UAV-based sensing platform with deep learning to Identify and Quantify Gaseous Emission in Gas Flares
Abstract
Oil and natural gas contribute 30% of the total methane (CH4) emission in the United States, CH4 is a powerful greenhouse gas that traps 87 times more radiation than carbon dioxide (CO2). Methane is often intentionally released from oil and gas wells through venting or flaring natural gas. Methane emissions occur during all phases of drilling and production, and sometimes after a well has ceased production, improperly plugged wells and incomplete combustion can emit large volumes of methane and other hazardous air pollution. The mitigation of emissions of methane and other gases through the accurate monitoring/measurement of gas flares can play a significant role in setting appropriate and protective limits to protect health and meet U.S. “net-zero” carbon economy goals. In this proposal Omega Optics together with The University of Texas at Austin proposes the development of a portable lab-on-chip Mid-IR spectrometer system and integrates it on a small mobile platform such as unmanned air vehicles (UAVs) and other airborne systems for routine measurement of non-combusted methane (CH4), carbon monoxide (CO), and nitrous oxide (N2O) released to the atmosphere in the gas flare. Moreover, our proposed spectrometer mounted on UAVs will be developed to work in autonomous mode using an adaptive sampling approach to determine the safe location away from the gas flare with the highest emission gradient. In addition, artificial intelligence/machine learning (AI/ML) functions will be facilitated using the butterfly-style photonic-electronic-neural-chip (BPNC) to analyze the sensing dataset collected. Our proposed technical approach for investigating non-combustion gas emission is based on lab-on-chip absorption spectroscopy in the mid-IR regime. Owing to the unique molecular vibration signature and large absorption cross-section of the compounds and gases in the mid-IR wavelengths, spectroscopy in this regime is considered a promising technique in sensing applications. During the phase-I part of the program, our target will be broadly focused on two major objectives. In the first objective, a feasibility demonstration of the on-chip absorption spectrometer on a silicon-on-sapphire (SoS) platform will be performed with targeted detection sensitivity <50 ppb. The second objective will be to implement an adaptive sampling approach for automated UAVs motion planning to accumulate dense data sampling from the gas flare. The integrated outcomes of these two objectives will pave the way to implement a highly efficient in-situ gas detection platform important for numerous applications, especially where human intervention is problematic. As per the global gas sensor market size & share report, in 2020, the global gas sensor market size was estimated at around USD 2.33-billion, and it is expected to reach USD 4.54 billion by 2028 with a compound annual growth rate of 8.7% from 2020 to 2028. As per the future requirement of the gas sensing applications, the proposed sensing platform has distinct benefits over the existing sensing system like high compactness, high sensitivity & specificity, real-time autonomous detection, AI/ML enhanced prediction and analysis capabilities in a cost-effective platform will be beneficial in every sector where chemical and biosensing is required.
Topic Code
C56-27a
Solicitation Number
None
Status
(Complete)
Last Modified 9/12/23
Period of Performance
7/10/23
Start Date
7/9/24
End Date
Funding Split
$250.0K
Federal Obligation
$0.0
Non-Federal Obligation
$250.0K
Total Obligated
Activity Timeline
Additional Detail
Award ID FAIN
DESC0023917
SAI Number
None
Award ID URI
SAI EXEMPT
Awardee Classifications
Small Business
Awarding Office
892430 SC CHICAGO SERVICE CENTER
Funding Office
892401 SCIENCE
Awardee UEI
U11BUN3J3E88
Awardee CAGE
1XA36
Performance District
TX-37
Senators
John Cornyn
Ted Cruz
Ted Cruz
Budget Funding
| Federal Account | Budget Subfunction | Object Class | Total | Percentage |
|---|---|---|---|---|
| Science, Energy Programs, Energy (089-0222) | General science and basic research | Grants, subsidies, and contributions (41.0) | $250,000 | 100% |
Modified: 9/12/23