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Search Publications

NIST Authors in Bold

Displaying 1 - 25 of 2395

Revealing statistically robust strain rate effects on mechanical performance of pristine single fiber aramids

August 10, 2026
Author(s)
Atik Faisal, Alexander Landauer, Walter Adamy, Dumbari Kabari, Kathleen Lamkin-Kennard, Amanda Forster, Amy Engelbrehcht-Wiggans
High-performance synthetic fibers, especially aramid fibers, are widely used for body armor applications for their strength, stiffness, and excellent strength-to-weight ratio. Among those, Kevlar and Twaron (hereafter Aramid A and Aramid B, respectively)

Methods for Estimating Fe Redox in Mesoamerican Jadeite Jade

August 5, 2026
Author(s)
Edward P. Vicenzi, Thomas Lam, Evan Jahrman, Bruce Ravel, Melinda Dyar, Jamie Weaver
Green jadeite has been selectively mined and used by Mesoamerican Indigenous cultures for centuries, with the green hues resulting from interactions among various chromophores, including Cr3+, Fe3+, and Fe2+. This study employed Fe K-edge X-ray absorption

Opioid sensing at point-of-need

July 29, 2026
Author(s)
Thinh Bui, Edward Sisco, Kyle Chapkin, Wenqi Zhu, Junyeob Song, Dhruv Forma, Anthony Kearsley, Henri Lezec
The opioid epidemic, headlined by synthetic fentanyl, is a growing international concern that has especially garnered great attention in the United States at all levels of government. As a federal agency, the National Institute of Technology (NIST) was

Wavelength-Dependent Field Ion Emission in Atom Probe Tomography

July 27, 2026
Author(s)
Ann Debay, Benjamin Caplins, Karen DeRocher, Jacob Garcia, May Martin, Mark McLean, Christopher Mead, Luis Miaja Avila, William Osborn, Xiaochen Ren, Norman Sanford
Laser-pulsed atom probe tomography (APT) is a powerful tool for materials characterization due to its desirable combination of high spatial resolution and analytical sensitivity. In current state-of-the-art commercial APT instruments, near ultraviolet (NUV

Reference Correlation of the Thermal Conductivity of Neon

June 30, 2026
Author(s)
Marc Assael, Sofia Sotiriadou, Monika Thol, Marcia Huber
A new wide-ranging correlation for the thermal conductivity of neon, based on the most recent ab-initio dilute gas theoretical calculations, a simplified crossover critical enhancement contribution, and critically evaluated experimental data, is presented

A Switchable Longitudinal & Shear BLS Microscope for Comprehensive Modulus Imaging of Semiconductor Packaging Materials

June 17, 2026
Author(s)
Andrew Gayle, Sebastian Engmann, Ran Tao, Andrew Korovich, Polette Centellas, Yvonne Gerbig, Christopher Soles, Chris Michaels
Brillouin light scattering (BLS) offers an optical, noncontact, nondestructive method for probing the mechanical properties of next-generation semiconductor packaging materials. In this work, a switchable BLS microscope with both backscattered and off-axis

Photopolymer Additive Manufacturing 2025 Workshop Report: Building a Unified Vision from Research to Regulation

June 10, 2026
Author(s)
Callie Higgins, Jason Killgore, Mike Idacavage, Vince Anewenter, Mickey Fortune, Gary Cohen, Perri Katzman, Jessica Hemond, Spencer Loveless, Michael Gould
The third biannual Photopolymer Additive Manufacturing Alliance Workshop was held on September 15-16, 2025, at the University of Colorado Boulder to continue its mission of advancing photopolymer additive manufacturing (PAM). Building on the 2023 PAMA

Spatial heterogeneity in polymer blends and its impact on dynamics

June 6, 2026
Author(s)
Bret Tantorno, Tuyen Truong, Lori Hoover, Gregory McKenna, Ran Tao, Fan Zhang
The relationship between dynamic and spatial heterogeneity in polymer blends is still not fully understood, yet it plays a crucial role in our understanding of their viscoelastic properties. Here, we report the results of an investigation of the

Determinism analysis in Hybrid-LLM-GNN modeling for materials property prediction

May 26, 2026
Author(s)
Youjia Li, Daniel Wines, Kamal Choudhary, Vishu Gupta, MUHAMMED NUR TALHA KILIC, Sayak Chakrabarty, Wei-keng Liao, Alok Choudhary, Ankit Agrawal
Driven by advances in artificial intelligence and the growing availability of databases, machine learning (ML) now plays a central role in data-driven materials knowledge discovery. In studies that employ ML models, maintaining deterministic workflows is

Atom Probe Tomography

May 13, 2026
Author(s)
Ann Debay, Baptiste Gault, Francois Vurpillot
Atom probe tomography (APT) has been rising in prominence since its inception. APT grew from field-ion microscopy, which was the first technique to allow for directly imaging individual atoms on a surface, as early as the 1950s. Today, APT provides

Digital Volume Correlation Challenge 2.0: A Comprehensive Dataset for Digital Volume Correlation Benchmarking

May 13, 2026
Author(s)
Zixiang Tong, Yujie Zhang, Edward Ando, Bin Chen, Brendan Croom, John Dabiri, Christian Franck, Matthew Fu, Helena Jin, Orion Kafka, Sriram Kunnoth, Thao Nguyen, Jacob Notbohm, Mohak Patel, Mainak Sarkar, Angkur Shaikeea, Jing Zhang, Alexander Landauer, Jin Yang
Background: Digital Volume Correlation (DVC) is a powerful experimental technique for quantifying 3D full-field volumetric displacements and strains. In light of its increase adoption in metrological applications, there is a critical need for benchmark

Overcoming Roadblocks for Implementing AI/ML Methods for Materials Advancement

April 6, 2026
Author(s)
James Warren, Francesca Tavazza, Austin McDannald, Aaron Kusne, Howard Joress, David Hoogerheide, Brian DeCost, Kamal Choudhary, Debra Audus
The development of novel materials with tailored properties is a complex, multi-objective optimization problem that has long been a challenge in materials research. The integration of artificial intelligence (AI) and machine learning (ML) techniques has

Dynamic Embedding Representation for Graph Neural Networks to Enhance Materials Property Prediction with Limited Datasets

March 24, 2026
Author(s)
Vishu Gupta, Kamal Choudhary, Youjia Li, Muhammed Nur Talha Kili, Daniel Wines, Wei-keng Liao, Alok Choudhary, Ankit Agrawal
Graph neural networks (GNNs) have proven effective in understanding and predicting diverse material properties, even when working with limited datasets. An important step in training GNN is to use an appropriate and informative graph embedding that can

Studies Of Water Films and Carbonation Via Neutron Scattering and Infrared Adsorption: In Situ Studies of Mg(OH)2 and Ca(OH)2

March 24, 2026
Author(s)
Hubert King, Ryan Murphy, Avery Baumann, Robert Dalgliesh, Dirk Honecker, Gregory Smith
Small-angle neutron scattering was used to investigate structural evolution during the carbonation of Ca(OH)₂ and Mg(OH)₂ under humidified CO₂, using both H₂O and D₂O vapor. For Ca(OH)₂, carbonation led to a progressive increase in both nano- and meso
Displaying 1 - 25 of 2395
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