Available for Licensing: Machine Learning-Enhanced Spectroscopy Technology for High-Resolution Radiation Detection Using Low-Cost Detectors

SOL #: BA-1346Special Notice

Overview

Buyer

Energy
Energy, Department Of
BATTELLE ENERGY ALLIANCE–DOE CNTR
Idaho Falls, ID, 83415, United States

Place of Performance

Idaho Falls, ID

NAICS

Analytical Laboratory Instrument Manufacturing (334516)

PSC

Physical Properties Testing And Inspection (6635)

Set Aside

No set aside specified

Timeline

1
Posted
Oct 30, 2025
2
Last Updated
Mar 4, 2026
3
Action Date
Dec 1, 2025, 7:00 AM

Qualification Details

Fit reasons
  • NAICS alignment with historical contract wins in similar service areas.
  • Scope strongly matches core technical capabilities and delivery model.
Risks
  • Past performance thresholds may require one additional teaming partner.
  • Potential clarification needed on staffing minimums before bid/no-bid.
Next steps

Validate eligibility requirements, assign capture owner, and schedule partner outreach to confirm teaming strategy before submission planning.

Quick Summary

The Department of Energy (DOE), through the Idaho National Laboratory (INL), has issued a Special Notice announcing the availability of a Machine Learning-Enhanced Spectroscopy Technology for licensing and commercialization. This innovative technology enables high-resolution radiation detection using low-cost detectors, significantly reducing system cost, size, and cooling requirements without sacrificing performance. This notice is not a solicitation for funding or services, but an invitation for industry to explore licensing opportunities. Expressions of interest are encouraged by June 1, 2026.

Technology Overview

INL's technology applies a compact convolutional neural network (CNN) to reconstruct high-energy-resolution spectra from low-resolution measurements obtained from inexpensive, room-temperature detectors like sodium iodide (NaI) scintillators. This overcomes the limitations of traditional high-purity germanium (HPGe) detectors, which are costly, fragile, and require cryogenic cooling. The CNN model is compact (1.6M parameters, 6.2 MB), allowing for fast, portable deployment.

Key Advantages

  • Cost Reduction: Enables ≥10× lower system cost and maintenance.
  • Operational Simplicity: Eliminates the need for cryogenic cooling.
  • Improved Deployability: Suitable for remote, field, and mobile environments.
  • Higher Throughput: Supports higher count rates with minimal peak deformation.
  • Cross-Technology Applicability: Adaptable for gamma-ray, x-ray, and neutron detection.

Market Applications

Potential applications include nuclear materials monitoring and safeguards, space-based radiation detection, industrial quality control, medical and environmental radiation monitoring, and homeland security.

Contact & Timeline

  • Opportunity Type: Special Notice (Technology Licensing)
  • Agency: Department of Energy / Idaho National Laboratory
  • Response Date: June 1, 2026
  • Published Date: March 4, 2026
  • Contact: Javier Martinez (javier.martinez@inl.gov)

People

Points of Contact

Javier MartinezPRIMARY

Files

Files

No files attached to this opportunity

Versions

Version 2
Special Notice
Posted: Mar 4, 2026
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Version 1Viewing
Special Notice
Posted: Oct 30, 2025
Available for Licensing: Machine Learning-Enhanced Spectroscopy Technology for High-Resolution Radiation Detection Using Low-Cost Detectors | GovScope