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Search Publications by: David Sheen (Fed)

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Displaying 1 - 22 of 22

Classification and Authentication of Materials using Prompt Gamma Ray Activation Analysis

July 12, 2023
Author(s)
Nathan Mahynski, Jacob Monroe, David Sheen, Rick L. Paul, Heather H. Chen-Mayer, Vincent K. Shen
Prompt gamma ray activation analysis (PGAA) is a non-destructive nuclear measurement technique that quantifies isotopes present in a sample. Here, we use PGAA spectra to train different types of models to elucidate how discriminating these spectra are for

Assessing Arsenic Species in Foods Using Regularized Linear Regression of the Arsenic K-edge X-ray Absorption Near Edge Structure

April 19, 2022
Author(s)
Evan Jahrman, Lee L. Yu, William P. Krekelberg, David Sheen, Thomas C. Allison, John L. Molloy
The toxicity and bioavailability of arsenic is heavily dependent on its speciation. Therefore, robust and accurate methods are needed to determine arsenic speciation profiles for materials related to public health initiatives, such as food safety. Here, X

Principal Component Analysis for Automated Classification of 2D Spectra and Interferograms of Protein Therapeutics: Influence of Noise, Reconstruction Details, and Data Preparation

July 22, 2020
Author(s)
Robert Brinson, Wade Elliott, Luke Arbogast, David Sheen, John Giddens, John Marino, Frank Delaglio
Protein therapeutics must retain their proper three-dimensional fold without forming aggregates for safe and effective use in the clinic. Therefore, the ability to monitor protein higher order structure (HOS) can be valuable throughout the lifecycle of a

Flat-Histogram Extrapolation as a Useful Tool in the Age of Big Data

April 13, 2020
Author(s)
Nathan Mahynski, Harold Hatch, Matthew Witman, David Sheen, Jeffrey R. Errington, Vincent K. Shen
Here we review recent work by the authors to revisit the concept of extrapolating thermodynamic properties of classical systems using statistical mechanical principles. Specifically, we discuss how the combination of these principles with biased sampling

Metabolomics Test Materials for Quality Control: A Study of a Urine Materials Suite

November 7, 2019
Author(s)
Dan Bearden, David A. Sheen, Yamil Simon, Bruce A. Benner Jr., Werickson Fortunato de Carvalho Rocha, Niksa Blonder, Katrice A. Lippa, Richard Beger, Laura Schnackenberg, Jinchun Sun, Khyati Mehta, Amrita Cheema, Haiwei Gu, Ramesh Marupaka, Nagana Gowda, Daniel Raftery
There is a lack of experimental reference materials and standards for metabolomics measurements, such as urine, plasma, and other human fluid samples. Reasons include difficulties with supply, distribution, and dissemination of information about the

interlab: A Python module for analyzing interlaboratory comparison data

March 15, 2019
Author(s)
David A. Sheen
interlab was developed as a software tool to perform consensus analysis on spectral data from interlaboratory studies. It is designed to estimate the spread in the spectral data and to identify possible outliers among both spectral populations and

Classification of petroleum Standard Reference Materials and other fuels by chemometric analysis of gas chromatography-mass spectrometry data

February 23, 2017
Author(s)
Werickson Fortunato de Carvalho Rocha, Michele M. Schantz, David Sheen, Katrice Lippa, Pamela M. Chu
As feedstocks transition from conventional oil to increasing amounts of unconventional petroleum sources and biomass, it will be necessary to determine whether a particular fuel or fuel blend is suitable for use in engines. Certifying a fuel as safe for

Chemical kinetic model uncertainty minimization through laminar flame speed measurements

July 25, 2016
Author(s)
Okjoo Park, Peter S. Veloo, David Sheen, Yujie Tao, Fokion N. Egolfopoulos, Hai Wang
Laminar flame speed measurements were carried for mixture of air with eight C3-4 hydrocarbons (propene, propane, 1,3-butadiene, 1-butene, 2-butene, iso-butene, n-butane, and iso-butane) at the room temperature and ambient pressure. Along with C1-2

A comparison of literature models for the oxidation of normal heptane

February 1, 2014
Author(s)
David A. Sheen, Wing Tsang
The development of detailed chemical kinetic models has proceeded unabated since the pioneering work of Dixon-Lewis and coworkers forty-five years ago. In that time, computational power has increased ten million-fold, and yet, we do not have a consensus on