Data tables for Energy Price Indices and Discount Factors for Life-Cycle Cost Analysis - 2023: Annual Supplement to NIST Handbook 135. Starting in 2022, the data tables for the annual supplement within the text document has been extracted and provided in a supplemental spreadsheet.

The following data files include in-situ thermographic measurement results, scan strategy, and various additional data associated with laser powder bed fusion (LPBF) 3D builds of nickel-based superalloy IN718 test objects for the 2022 Additive Manufacturing Benchmark (AM-Bench) test series. These data are associated with the AMB2022-01 series of modeling challenges described here: https://www.nist.gov/ambench/amb2022-01-benchmark-measurements-and-chal….

Database of MRI quantitative measurements gathered from literature and experimental studies, for tissues and synthetic materials.Additionally, a code base is provided to aid in finding MRI tissue relaxation times for a target field strength, and to provide functionality to solve for tissue mimic composition given target tissue relaxation times.

Round rl-randomized-lavaworld-aug2023-train Train DatasetThis is the training data used to create and evaluate trojan detection software solutions. This data, generated at NIST, consists of Reinforcement Learning agents trained to navigate the Lavaworld Minigrid environment. A known percentage of these trained AI models have been poisoned with a known trigger which induces incorrect behavior. This data will be used to develop software solutions for detecting which trained AI models have been poisoned via embedded triggers.

Mobile manipulators, which are robotic systems integrating an automatic or autonomous mobile base with a manipulator, can potentially enhance automation in many industrial and unstructured environments. Namely, large-scale manufacturing processes, typical in the aerospace, energy, transportation, and conformal additive manufacturing fields, encompass a notable subset of potential future mobile manipulator use-cases.

nlp-question-answering-aug2023-trainThis is the train data used to evaluate trojan detection software solutions. This data, generated at NIST, consists of natural language processing (NLP) AIs trained to perform extractive question answering on English text. A known percentage of these trained AI models have been poisoned with a known trigger which induces incorrect behavior. This data will be used to develop software solutions for detecting which trained AI models have been poisoned via embedded triggers.

A table of known interferences for per- and polyfluoroalkyl substances using mass spectrometry.

Source code for a WebAssembly web application that explores the contents of standardized friction ridge metadata (i.e., "Type 9") within ANSI/NIST-ITL compatible records

Supplemental material to the article "Optical n(p, T_90) measurement suite 1: He, Ar, and N_2" by PF Egan and Y Yang in International Journal of Thermophysics 2023.The archive file contains research data and analysis scripts as follows:* The n(p, T_90) dataset for helium. A Python script analyzes the data to produce the estimate of temperature-dependent compressibility, and reproduces Fig. 2 from the article.* The n(p, T_90) dataset for argon. A Python script analyzes the data to determine T - T_90, and reproduces Fig. 3 from the article.

This code and example files were used to run the self-consistent field theory parameterization in the publication "Predicting the toughness of compatibilized polymer blends" by Robert J. S. Ivancic (OrcID: https://orcid.org/0000-0001-9969-2534, National Institute of Standards and Technology, Material Measurement Laboratory, Division 642, Group 1) and Debra J.