Available for Licensing Machine Learningenhanced Tender

• Country: USA
• Summary: Available for Licensing Machine Learningenhanced Spectroscopy Technology for Highresolution Radiation Detection Using Lowcost Detectors
• UST Ref No: 137178415
• Deadline: 01 Jun 2026
• Financier: Self Financed
• Purchaser Ownership: Government
• Tender Value: Refer Document
• Notice Type: Tender
• Document Ref. No.: BA-1346
• Purchaser's Detail:
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• Description:
• Machine Learning-Enhanced Spectroscopy Technology for High-Resolution Radiation Detection Using Low-Cost Detectors
  Transforms low-energy resolution gamma- and x-ray detector data into high-resolution spectra—reducing cost, size, and cooling requirements without sacrificing performance.
  Technology Summary
  This INL technology enables high-energy-resolution radiation spectroscopy using low-cost, room-temperature detectors such as sodium iodide (NaI) scintillators. Traditionally, researchers and engineers rely on high-purity germanium (HPGe) detectors, lanthanum bromide (LaBr3) or similar for applications requiring fine energy discrimination; however, these systems are expensive, fragile, or require cryogenic cooling.
  The presented approach applies a compact convolutional neural network (CNN) architecture to reconstruct high-energy-resolution spectra from low-resolution measurements. Using four convolution-max pooling layer pairs (128-16 filters) followed by dense layers, the model captures spectral features typically only visible with HPGe detectors. The network contains roughly 1.6 million parameters (6.2 MB total), enabling fast, portable deployment in embedded or field devices.
  The technology offers a new analytical pathway for radiation spectroscopy—maintaining data fidelity while reducing total system cost, weight, and operational complexity.
  Problem Addressed
  High cost and complexity of high-energy-resolution detectors: HPGe systems provide excellent energy resolution (~0.2%) but are 10×-100× more expensive than scintillation-based systems.
  Limited operational flexibility: HPGe detectors require cryogenic cooling and are unsuitable for mobile or high-radiation environments.
  Low detection efficiency and count-rate performance: HPGe detectors have lower detection efficiency per detector volume and cannot handle high count rates without peak deformation or detector dead time, leading to data degradation.
  Restricted deploym...
• Documents:

 Tender Notice