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William Charlton

Professor

University of Texas at Austin

United States

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William Charlton is a Professor at The University of Texas at Austin, USA. His research areas include gamma activation analysis, neutron activation analysis, and the mechanical properties of carbon fibers. He has contributed to recent studies on the measurement of isomeric yield ratios and the use of artificial neural networks in insider threat detection.

Articles (8)

Year:

2025

Year:

2023

Year:

2023

Year:

2023

Year:

2022

Year:

2022

Year:

2022

Year:

2020

Collaborators (1)

Jennifer Niedziela

Senior R&D Staff and Group Leader - Applied Materials Analysis

Oak Ridge National Laboratory

UNITED STATES

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William Charlton

Research Interests

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Articles (8)

Measurement of the isomeric yield ratio for Zr88 thermal neutron absorption

Connecting mechanical properties to hydrogen defects in PAN-based carbon fibers

Prompt gamma activation analysis as a means for quantitative, non-destructive, non-invasive measurement of mercury in steel from oil and gas operations

Use of Compton suppression gamma ray spectrometry to determine <sup>239</sup>Pu

Neutron activation analysis using gamma-gamma coincidence to eliminate spectral interferences

Improved evaluation of safeguards parameters from spent fuel measurements with the Differential Die-Away (DDA) instrument

Results from Invoking Artificial Neural Networks to Measure Insider Threat Detection & Mitigation

A strategic analysis of stationary radiation portal monitors and mobile detection systems in border monitoring

Collaborators (1)

Jennifer Niedziela

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William Charlton

Research Interests

Explore related searches

About

Articles (8)

Measurement of the isomeric yield ratio for Zr88 thermal neutron absorption

Connecting mechanical properties to hydrogen defects in PAN-based carbon fibers

Prompt gamma activation analysis as a means for quantitative, non-destructive, non-invasive measurement of mercury in steel from oil and gas operations

Use of Compton suppression gamma ray spectrometry to determine <sup>239</sup>Pu

Neutron activation analysis using gamma-gamma coincidence to eliminate spectral interferences

Improved evaluation of safeguards parameters from spent fuel measurements with the Differential Die-Away (DDA) instrument

Results from Invoking Artificial Neural Networks to Measure Insider Threat Detection &amp; Mitigation

A strategic analysis of stationary radiation portal monitors and mobile detection systems in border monitoring

Collaborators (1)

Jennifer Niedziela

Make your next move.

Results from Invoking Artificial Neural Networks to Measure Insider Threat Detection & Mitigation