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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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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.
Digby D. Macdonald, Iouri Balachov
Nuclear Technology | Volume 120 | Number 1 | October 1997 | Pages 86-93
Technical Note | Material | doi.org/10.13182/NT97-A35434
Articles are hosted by Taylor and Francis Online.
The viability of an often-employed engineering method of determining bottom drain (lowerplenum) oxygen levels in boiling water reactors is explored, in which bottom drain oxygen is back-calculated from the recirculation system oxygen level and the combined recirculation system/bottom drain value. For a low flow fraction f where 0.16 <f <0.20 is often employed, the back-calculated bottom drain oxygen level can be grossly in error, reflecting the minimal amount of information that is derived from the lower plenum. This finding cautions against using back-calculated lower plenum oxygen levels to specify hydrogen water chemistry conditions for protection of the components in the lower plenum, particularly when f is small. The uncertainty in the bottom drain [O2I has been characterized by using a Monte Carlo error analysis for both systematic and random errors. Modifications to the sampling system that would greatly reduce these errors are identified.