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NIST’s Material Measurement Laboratory and Communications Technology Laboratory are developing a new spectroscopy for intermolecular interactions. The team is
There is always a degree of uncertainty surrounding measurements of polymeric materials, especially complex mixtures of with varying distributions in chemistry
The goal of this project is to utilize NIST expertise in privacy, cybersecurity, machine learning, wireless technology, ranging, modeling, and hardware and
The development of new platforms for characterization of complex microbial samples are hampered by lack of reproducibility and comparability across different
In the past decade, research data have become widely recognized as a critical national and global resource, and the risks of losing or mismanaging research data
JARVIS-ML is a repository of machine learning (ML) model parameters, descriptors, and ML related input and target data. JARVIS-ML is a part of the NIST-JARVIS
The Chemical Sciences Division (CSD) at NIST is developing an integrated measurement services program for Cannabis (hemp and marijuana) to help ensure the
This project focuses on understanding the potential for nanoscale engineered materials to advance state-of-the-art spectroscopic techniques and foster the
Computational materials design requires a variety of tools to model processing-structure-property relationships across a range of time and length scales. This
Develop a materials innovation infrastructure for the design and discovery of inorganic materials to reduce the time and cost for deploying new materials into
With increasing use of data-driven methodologies, concerns around data discovery, data access, and data interoperability have come to the forefront. Communities
Far-infrared (or terahertz/THz, ca. 25 to 300 micron wavelength) femtosecond pulsed laser and Fourier-transform infrared methods are employed to measure
Condensed matter dynamics can evolve on a subpicosecond timescale, too fast to follow using many characterization techniques. We use femtosecond optical pulses
Discovery of novel materials to facilitate hydrogen gas production has prompted new avenues of research towards developing hydrogen as an alternative to fossil
With the rapid rise of artificial intelligence and its insatiable demand for low-energy, high performance computing, research is accelerating into novel
Using atomistic-level calculations (density functional theory and classical molecular dynamics), this project aims at increasing our knowledge of electronic and
This project provides resources to address some of the challenges to the wider use of classical atomistic simulations (e.g. molecular dynamics and Monte-Carlo)
Conventional techniques for analyzing chemical composition, such as infrared (IR) microscopy often miss critically important nanoscale details. To overcome this
Neuromorphic computing is a radical new approach to information processing for artificial intelligence where, instead of using digital electronics, inspiration
This project aims to develop rigorous measurements and methodology needed for determining optical and electrical properties of advanced materials that might be
We are developing the foundational knowledge and measurement infrastructure that will facilitate the use of solid state systems with emergent quantum properties
One of the most promising new approaches to next generation information processing is spintronics, where information is carried with electronic spin rather than
The human brain does some types of information processing, like speech recognition, image recognition, or video processing, much more efficiently than can be
The working of countless electronic devices involves electric and magnetic effects interacting within nanostructured materials. In the phenomenon known as spin