U.S. flag

An official website of the United States government

Official websites use .gov
A .gov website belongs to an official government organization in the United States.

Secure .gov websites use HTTPS
A lock ( ) or https:// means you’ve safely connected to the .gov website. Share sensitive information only on official, secure websites.

Search Publications

NIST Authors in Bold

Displaying 5651 - 5675 of 7113

Multi-timescale Frequency-Phase Matching for High-Yield Nonlinear Photonics

November 6, 2025
Author(s)
Mahmoud Jalali Mehrabad, Lida Xu, Gregory Moille, Christopher Flower, Supratik Sarkar, Apurva Padhye, Shao-Chien Ou, Daniel Suarez-Ferero, Mahdi Ghafariasl, Yanne K. Chembo, Kartik Srinivasan, Mohammad Hafezi
… metrology, squeezed-light sources, and nonlinear optical computing …

Bayesian Inference of Anisotropic 2D Small-Angle Scattering from Sparse Measurement

October 15, 2025
Author(s)
Chi-Huan Tung, Yangyang Wang, Jan-Michael Carrillo, Yuya Shinohara, Chun-Yu Chen, Jhih Lin, Lionel Porcar, Ryan Murphy, Guan-Rong Huang, Lijie Ding, Changwoo Do, Wei-Ren Chen
We present a Bayesian inference framework for reconstructing anisotropic two-dimensional small-angle scattering (2D SAS) patterns from sparse, noisy, or partially missing data. The method combines a symmetry-aware angular basis with radial Gaussian process

Best-Practice Reporting for Porous Materials Adsorption Data

October 1, 2025
Author(s)
Daniel Siderius, Louis Vanduyfhuys, Jack Evans, Paul Iacomi, Veronique Van Speybroeck, Volodymyr Bon, Stefan Kaskel
Recent decades have seen an enormous evolution of novel porous materials for catalysis, energy efficient processes, and sustainable technologies to improve life quality. Adsorption characterization is essential to provide descriptors of texture and

Explaining poisoned AI models

June 11, 2025
Author(s)
Peter Bajcsy, Antonio Cardone, Philippe Dessauw, Chenyi Ling, Michael Majurski, Timothy Blattner, Derek Juba, Walid Keyrouz
This work presents a hierarchical approach to explaining poisoned artificial intelligence (AI) models. The motivation comes from using AI models in security and safety-critical applications, for instance, AI models for classifying road traffic signs in

Examining Generalizability of AI Models for Catalysis

June 7, 2025
Author(s)
Kamal Choudhary, Shih Han Wang, Hongliang Xin, Luke Achenie
In this work, we investigate the generalizability of problem-specific machine-learning models for catalysis across different datasets and adsorbates, and examine the potential of unified models as pre-screening tools for density functional theory

Discover STEM Education Resources

March 6, 2024
Author(s)
Cara O'Malley, Elizabeth Benham
The National Institute of Standards & Technology (NIST) invites educators to discover STEM resources on the NIST Educational STEM Resource (NEST-R) registry! Published by NIST scientists, engineers, & staff, NEST-R content is free & publicly available. It

Toward a Standard Data Architecture for Additive Manufacturing

January 16, 2024
Author(s)
Shengyen Li, Shaw C. Feng, Alexander Kuan, Yan Lu
To advance the additive manufacturing (AM) technologies, R&D projects may evaluate new facilities and different processes that need a scalable data architecture to accommodate the progressing knowledge. This work introduces a data pedigree to enable the

Modeling the linear and nonlinear dielectric response of solvents

March 13, 2023
Author(s)
Michael Woodcox, Avik Mahata, Aaron Hagerstrom, Angela Stelson, Chris Muzny, Ravishankar Sundararaman, Kathleen Schwarz
We demonstrate a method to compute the dielectric spectra of fluids in molecular dynamics by directly applying electric fields to the simulation. We obtain spectra from molecular dynamics simulations with low magnitude electric fields (0.01 V/A) in

Characterizing Frequency Stability Measurements having Multiple Data Gaps

February 2, 2022
Author(s)
David A. Howe, Noah Schlossberger
Time series measurements with data gaps (dead times) prevent accurate computations of frequency variances such as the Allan variance (AVAR) and its square-root ADEV. To extract frequency distributions, data must be sequentially ordered and equally spaced

Baseline Control Systems in the Intelligent Building Agents Laboratory

September 22, 2021
Author(s)
Amanda Pertzborn, Daniel Veronica
The goal of the Embedded Intelligence in Buildings program at the National Institute of Standards and Technology (NIST) is to develop and deploy advances in measurement science that will improve building operations to achieve lower operating costs
Displaying 5651 - 5675 of 7113
Was this page helpful?