Cycle 2 Advanced Manufacturing

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Cybersecurity Framework Version 2.0 Semiconductor Manufacturing Profile (Initial Public Draft)
Post, August 7, 2026 • (National Institute of Standards and Technology) The NIST Cybersecurity Framework Version 2.0 Semiconductor Manufacturing Profile provides a voluntary, risk-based approach for managing cybersecurity activities and reducing cyber risk to the overall semiconductor manufacturing process. The Profile is a supplement to current cybersecurity standards, regulations, and industry guidelines that are already...

Design and Implementation of Digital Twin Models for Continuous Monitoring and Performance Prediction of Precast Concrete Bridges [supporting dataset]
Post, August 7, 2026 • (University of Illinois at Urbana-Champaign) This project explores the design and implementation of digital twin models for the continuous monitoring and performance prediction of precast concrete (PC) bridges. Leveraging NVIDIA Omniverse, a cutting-edge 3D modeling platform, the research establishes a streamlined methodology for rapidly prototyping digital twin models using engineering...

Dynamic compressive stress-strain curves of aluminum alloy 6061-T6 with rapid heating
Post, August 7, 2026 • (National Institute of Standards and Technology) This dataset contains raw mechanical data (strain, stress and strain rate curvesand initial temperatures) for compression experiments performed on aluminum alloy 6061-T6using the NIST pulse-heated Kolsky Bar at strain rates between 2400 1/s and 2700 1/s and initial temperatures from 23 °C to 527...

Handbook of Advanced Manufactured Material Properties From TCR Structure Builds at ORNL (FY2019)
Post, August 7, 2026 • (Oak Ridge National Laboratory, Argonne National Laboratory) There is growing interest in the use of additive manufacturing techniques for the production and deployment of components for nuclear power applications. Specifically, the Transformational Challenge Reactor (TRC) program seeks to demonstrate the application of advanced manufacturing to rapidly develop and deploy a...

Handbook on the Material Properties of FeCrAl Alloys for Nuclear Power Production Applications (FY18 Version: Revision 1)
Post, August 7, 2026 • (Oak Ridge National Laboratory, Brookhaven National Laboratory) FeCrAl alloys are a class of alloys that have seen increased interest for nuclear power applications including accident tolerant fuel cladding, structural components for fast fission reactors, and as first wall and blanket structures for fusion reactors. FeCrAl alloys are under consideration for...

High Throughput EBSD Characterization of Additive Kovar
Post, August 7, 2026 • (Sandia National Laboratories) For this dataset, 607 unique kovar samples were manufactured using Laser Powder Bed Fusion (LPBF) over 304 unique sets of LPBF process parameters. Electron Backscatter Diffraction (EBSD) data was collected for each sample using one of two methods, called here "Version 1" and "Version 2." For version...

High-Resolution X-ray computed tomography (XCT) image data set of additively manufactured cobalt chrome samples produced with varying laser powder bed fusion processing parameters
Post, August 7, 2026 • (National Institute of Standards and Technology) This data contains X-ray computed tomography (XCT) reconstructed slices of additively manufactured cobalt chrome samples produced with varying laser powder bed fusion (LPBF) processing parameters (scan speed and hatch spacing). A constant laser power of 195 W and a layer thickness of 20 µm...

High-throughput EBSD of Additive Kovar over multiple working distances
Post, August 7, 2026 • (Sandia National Laboratories) This dataset includes EBSD patterns for 60 additively manufactured Kovar sample specimens, printed under 30 sets of process conditions under two orientations with respect to the build plate. EBSD was collected in two directions relative to the sample specimens (build and transverse) over three working distances, for...

Hydroponic Cultivation of Bibb Lettuce in Nitrogen Phosphorus Potassium (NPK)-Limited Conditions
Post, August 7, 2026 • (Georgia Institute of Technology) This comprehensive dataset includes a variety of data types, data volumes, true replications, and pseudo replications of data collected as time-series data during the entire lifecycle for hydroponic lettuce cultivation experiments. This dataset contains large amounts of elemental analysis far beyond anything published previously in part...

In situ Visible Light and Thermal Imaging Data from a Laser Powder Bed Fusion Additive Manufacturing Process Co-Registered to X-ray Computed Tomography and Fatigue Data
Post, August 7, 2026 • (Oak Ridge National Laboratory) This dataset is comprised of in situ sensing data collected during a laser-based powder bed fusion additive manufacturing process, as well as rasterized scan path information, post-build X-ray computed tomography (XCT), and fatigue test results. A total of 64 cylinders, approximately 15 mm in diameter and...

Insider Threat Test Dataset
Post, August 7, 2026 • (Carnegie Mellon University) The Insider Threat Test Dataset is a collection of synthetic insider threat test datasets that provide both background and malicious actor synthetic data. The CERT Division, in partnership with ExactData, LLC, and under sponsorship from DARPA I2O, generated a collection of synthetic insider threat test datasets. These...

Kimberlina 1.2 CCUS Geophysical Models and Synthetic Data Sets
Post, August 7, 2026 • (Lawrence Berkeley National Laboratory, National Energy Technology Laboratory, Los Alamos National Laboratory, Colorado School of Mines) This synthetic multi-scale and multi-physics data set was produced in collaboration with teams at the Lawrence Berkeley National Laboratory, National Energy Technology Laboratory, Los Alamos National Laboratory, and Colorado School of Mines through the...

Laser Additive Manufacturing Process (LAMP) Model Decision Support Tool
Post, August 7, 2026 • (University of Michigan) Laser Additive Manufacturing Process (LAMP) Model Decision Support Tool constructed in excel sheet to predict the environmental impact, cost and lead time associated with various manufacturing processes. A mechanistic model constructed with uncertainty for 5 different manufacturing processes: metal & polymer L-PBF, die casting, injection molding and...

Layer-wise Imaging Dataset from Powder Bed Additive Manufacturing Processes for Machine Learning Applications (Peregrine v2021-03)
Post, August 7, 2026 • (Oak Ridge National Laboratory) This dataset contains layer-wise powder bed images from three different powder bed printing technologies: laser powder bed fusion, electron beam powder bed fusion, and binder jetting. This dataset was collected and annotated using the internally-developed Peregrine software tool and is designed primarily to facilitate research into...

Layer-wise Imaging Dataset from Powder Bed Additive Manufacturing Processes for Machine Learning Applications (Peregrine v2022-10.1)
Post, August 7, 2026 • (Oak Ridge National Laboratory) This release consists of six datasets which together include multi-modal layer-wise powder bed images from two different powder bed printing technologies. These datasets are designed primarily to facilitate the development and testing of new computer vision and machine learning based anomaly and defect detection algorithms. The...

Layer-wise Imaging Dataset from Powder Bed Additive Manufacturing Processes for Machine Learning Applications (Peregrine v2022-10)
Post, August 7, 2026 • (Oak Ridge National Laboratory) This release consists of six datasets which together include multi-modal layer-wise powder bed images from two different powder bed printing technologies. These datasets are designed primarily to facilitate the development and testing of new computer vision and machine learning based anomaly and defect detection algorithms. The...

Machine learning-enhanced near-infrared property prediction for improved polyolefin differentiation
Post, August 7, 2026 • (National Institute of Standards and Technology) This paper employs machine learning to predict key physical properties of polyolefins from NIR spectra, including density, crystallinity, and short chain branching. By integrating rapid NIR measurement with property prediction, we propose a property-based sorting methodology for polyolefins, addressing the current challenges recyclers face...

MatLib 1.2: Nuclear Material Properties Library
Post, August 7, 2026 • (Pacific Northwest National Laboratory, Nuclear Regulatory Commission) The U.S. Nuclear Regulatory Commission (NRC) uses the computer code Fuel Analysis under Steady-state and Transients (FAST) to model steady-state and transient fuel behavior to support regulatory decisions. FAST relies on a material properties library (MatLib) that contains the thermal and mechanical properties...

Metallic Fuel Handbook, Parts 1 and 2
Post, August 7, 2026 • (Idaho National Laboratory) This is revision 3 of the Metallic Fuels Handbook, which is a summary and critical assessment of data involving elements and alloys in the U-Np-Pu-Am-La-Ce-Pr-Nd-Zr system. This Handbook is intended to provide information needed by fuel modelers, project managers, and researchers interested in understanding not only what...

NIST alloy data
Post, August 7, 2026 • (National Institute of Standards and Technology) The NIST Alloy data web application (https://trc.nist.gov/metals_data) provides access to thermophysical property data with a focus on unary, binary, and ternary metal systems. Link to Dataset NIST alloy dataDate last updated: July 29, 2022

NIST Chemistry WebBook
Post, August 7, 2026 • (National Institute of Standards and Technology) This site provides thermochemical, thermophysical, and ion energetics data compiled by NIST under the Standard Reference Data Program. Link to Dataset NIST Chemistry WebBookDate last updated: March, 2025

NIST Inorganic Crystal Structure Database (ICSD)
Post, August 7, 2026 • (National Institute of Standards and Technology) Materials discovery and development necessarily begins with the preparation and identification of product phase(s). Crystalline compounds can be identified by their characteristic diffraction patterns using X-rays, neutrons, and or electrons. An estimated 20,000 X-ray diffractometers and a comparable number of electron microscopes are used...
Results 26–50 of 79