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

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 captur…

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