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Conference Spotlight
Nuclear Energy Conference & Expo (NECX)
September 8–11, 2025
Atlanta, GA|Atlanta Marriott Marquis
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The Standards Committee is responsible for the development and maintenance of voluntary consensus standards that address the design, analysis, and operation of components, systems, and facilities related to the application of nuclear science and technology. Find out What’s New, check out the Standards Store, or Get Involved today!
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Latest News
Inkjet droplets of radioactive material enable quick, precise testing at NIST
Researchers at the National Institute of Standards and Technology have developed a technique called cryogenic decay energy spectrometry capable of detecting single radioactive decay events from tiny material samples and simultaneously identifying the atoms involved. In time, the technology could replace characterization tasks that have taken months and could support rapid, accurate radiopharmaceutical development and used nuclear fuel recycling, according to an article published on July 8 by NIST.
Pola Lydia Lagari, Styliani Pantopoulou, Miltos Alamaniotis, Lefteri H. Tsoukalas
Nuclear Technology | Volume 207 | Number 8 | August 2021 | Pages 1270-1279
Technical Paper | doi.org/10.1080/00295450.2020.1816743
Articles are hosted by Taylor and Francis Online.
Since radionuclides have unique characteristic gamma-ray spectra, usually maintained as a set of (energy, counts/energy) ordered pairs, an explicit functional representation would be indisputably useful. In this paper, the Gamma Detector Response and Analysis Software has been used to simulate the gamma-ray spectra as it would be collected by an NaI detector for a set of 70 radionuclides. Gaussian radial basis function (RBF) networks that offer simple, closed-form expressions are then trained to represent each of these spectra. Hence, a library consisting of 70 RBF networks for the corresponding radionuclides has been built. The presence of these library-contained radionuclides in a given gamma-ray spectrum of an unknown source is identified by an algorithm that employs a linear combination of the library spectra to approximate the unknown spectrum. The combination coefficients are then determined by minimizing the squared deviation error function under convexity constraints.