Projects/Programs

Displaying 1 - 25 of 66

Adaptive Closed-Box Interference Susceptibility Testing

Ongoing

The primary project objective is to develop new methods for experimental characterization of dynamic interference impacts on adaptive, closed-box COTS communication links. Specific goals include: Dissemination of low-cost, general-purpose testbed designs for interference testing. Methods to assess

AI-based measurements For Imaging

Ongoing

The problem addressed in this work lies in enabling scientists to apply artificial intelligence (AI) based models to deriving measurements from terabyte-sized images. This problem is important as image-based measurements can become more accurate by introducing supervised AI-based models instead of

Annual Machine Learning for Materials Research Bootcamp

Ongoing

Four days of lectures and hands-on exercises covering a range of data analysis topics from introduction to python and data pre-processing to advanced machine learning analysis techniques. Example topics include: Identifying important features in complex/high dimensional data Visualizing high

Artificial Intelligence for Chemical Manufacturing

Ongoing

The chemical manufacturing design process relies heavily on the recommended values that engineers and researchers usually obtain from handbooks and databases. Those sources often lack easy ways to judge the reliability of information, either in the sense of where the data come from or what the

Augmented Intelligence for Manufacturing Systems (AIMS)

Ongoing

Objective To overcome existing measurement challenges via augmented intelligence, the fusion of integrated metrology, physics-based models, and artificial intelligence, to enable monitoring, diagnostics, and prognostics of manufacturing systems and their processes. Technical Idea One research

Automated Fault Detection and Diagnostics for the Mechanical Services in Commercial Buildings

Ongoing

Objective To put forward a new and practical measurement science whose “instruments” are realized commercially as a marketplace of highly effective, automated fault detection and diagnostic (AFDD) software products and services. These will employ data analytics and artificial intelligence to

Autonomous Synthesis of Metal-Organic Frameworks

Ongoing

Metal-organic frameworks (MOFs) show great promise for a variety of applications, from industrial gas separation, to catalysis, to PFAS absorption. One challenge to the adoption of these technologies is determining and optimizing the synthesis of these materials. There are large computational

Autonomous Systems Assurance

Ongoing

Achieving assured autonomy in any environment requires methods for measuring the input space, to show that the test environment adequately covers real-world conditions that may be encountered. Although some statistical and structural coverage metrics are relevant, they are terribly inadequate for

Biosecurity for Synthetic Nucleic Acid Sequences

Ongoing

Synthetic nucleic acid technologies are fundamental to U.S. biotechnology and biomanufacturing innovation. However, like other transformative technologies, they carry dual-use potential: while they can drive significant progress, they pose risks of unintentional or deliberate misuse to engineer

Broadband Coherent Anti-Stokes Raman Scattering (BCARS) Microscopy

Ongoing

Impact There is a need for label-free chemical microscopy in medicine, biology and materials science. Most of the current methods use chemical labels that often disturb the distribution and nature of chemical components being investigated. The method we are developing enables noninvasive and rapid

CHiMaD Phase Field Community

Ongoing

Please see the community website, https://pages.nist.gov/chimad-phase-field/

Classification of 3.5 GHz Spectrograms

Completed

This project compared various detection algorithms for federal incumbent radar signals in the 3550-3650 MHz band using a set of over 14,000 spectrograms collected by the completed Waveform Measurements of Radars Operating in the 3.5 GHz Band project. The results demonstrated that training deep

Classification Methods for the NIST Biorepository

Ongoing

NIST has been archiving biological and environmental specimens, including marine animal and environmental samples, for over 40 years. Currently, these biospecimens are stored at cryogenic temperatures in the NIST Biorepository located at the Hollings Marine Laboratory in Charleston, SC. Various

Illustration of cyberbrain surrounded by industry icons

Computation Platform for AI/ML

Ongoing

In collaboration with NIST’s Information Technology Laboratory and Office of Information Systems Management, the Office of Data and Informatics is supporting the deployment and development of the long-term operational model for the enki computation platform for NIST staff members who research and

Consistency Analysis and Uncertainty in ‘omic Data

Ongoing

‘Omics is increasingly moving out of the laboratory and towards use in industrial and commercial applications. For instance, in biomanufacturing, there is a need for quality control when developing biotherapeutics, which will almost certainly require a machine-learning classifier to separate

Data Driven Decision Support for Additive Manufacturing

Completed

Objective To develop and deploy the metrics, models, and best practices for using product definition, advanced analytics, and machine learning methods in additive manufacturing design and process planning to reduce lead times and support first-part-correct goals. Technical Idea Future advancements

AI/ML for Data Extraction and Uncertainty Predictions

Ongoing

The Material Measurement Lab at NIST employs artificial intelligence for the prediction and discovery of materials characteristics. Our applications of artificial intelligence (AI) accelerate materials research as well as help the community learn about AI's capabilities and gain confidence in

Deducing Prior Material Deformation from Simple Mechanics

Ongoing

Process-structure-property linkages suggest an opportunity to deduce processing from behavior. Simple imaging experiments provide rich sources of data. Can we deduce prior deformation? Scheme: Thin film plasticity Deform to some reference strain Unload Deform to test strain, image Deduce

Deep Learning for MRI Reconstruction and Analysis

Ongoing

The project is proceeding in three directions. Creating a new MRI reference artifact designed to assess geometric distortion using NIST’s MRI scanner. The artifact will be small enough to fit within the scanner with sufficient clearance to allow for variation in positioning within the scanner.

an infographic showing four proposed standards connecting as four joined puzzle pieces

Development of Standards to Support a Modular and Autonomous Laboratory Ecosystem

Ongoing

Autonomous experimentation (AE), or self-driving laboratories, combines AI and automation while leveraging human intuition and creativity to guide experiment campaigns. AE can reduce the time and resources needed to discover new materials by orders of magnitude and reduce the time-to-market for

Edge AI

Ongoing

This project: Develops edge learning and edge-enabled collaborative learning algorithms. Develops measurement methods for testing the performance and robustness of edge-learned, and more generally collaboratively learned, AI/ML models. Collaborates with other projects (e.g., 5G/6G Core Network

Embodied AI and Data Generation for Robotics

Ongoing

Objective To facilitate the adoption of AI-based robotic approaches in practical manufacturing scenarios by creating test methods that target AI-enabled robotic systems, evaluating the performance of AI-enabled robotic systems, and creating manufacturing-relevant and AI-centric datasets. Technical

Emerging Hardware for Artificial Intelligence

Ongoing

Here is a brief description of our work with links to recent papers from our investigations, broadly classified as experimental and modeling. A brief overview of Josephson junction-based bio-inspired computing can be found in our review article. Experimental We have facilities to develop our devices

Explainable Artificial Intelligence Based Modeling Applied to OMICS Problems

Ongoing

The goal of the project is to produce billions of certified values from multiple measurement methods with well-characterized uncertainty in the “’omics” field (genomics, proteomics, transcriptomics). These values are prepared by a joint effort between human experts and trained AI based models for

GenAI Text to Text (T2T)

Ongoing

Coming soon

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