Scientists at EPFL have developed an AI-based method called PSNMF to improve chemical analysis at the nanoscale. This technique enhances the clarity and accuracy of data obtained from energy-dispersive X-ray spectroscopy, which often suffers from noise and mixed signals when analyzing nanomaterials. By leveraging machine learning and Poisson noise, the method combines high spectral fidelity with detailed spatial resolution, allowing for more precise identification and quantification of chemical elements in complex nanostructures. This advancement could significantly benefit fields like advanced electronics and medical devices.
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