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Material Measurement Laboratory

MML conducts measurement science across the chemical, biological and material sciences. Activities range from fundamental and applied research to the development and dissemination of certified reference materials and data to industry, academia, and other government agencies to assure the quality of measurement results.

About the Material Measurement Laboratory

The NIST Material Measurement Laboratory (MML) conducts measurement science research to benefit industries based in the chemical, biological, and material sciences, and contributes technical expertise to the development of standards. MML researchers perform fundamental and applied research, evaluate data, and create other programs and tools to assure the quality of measurement results. 

Learn more about MML's work: 
Projects & Programs | News & Updates | Events | Publications | Awards | Press Coverage | Blogs

Our work supports areas of national importance:

Projects & Programs

Advanced Materials Design: Electronic and Functional Applications

Ongoing
Accelerating Materials Discovery using Machine Learning and AI Using machine learning and AI techniques along with high-throughput DFT calculations materials with specific properties are identified to accelerate the the discovery process for a variety of applications. Some of the specific materials

3D Molecular Orientation Imaging

Ongoing
We have developed 3D orientation measurement techniques by analyzing polarization-dependent molecular vibrational signals based on infrared (IR) absorption [1,2] and coherent anti-Stokes Raman scattering (CARS) [3]. The two imaging modalities are complementary to each other: IR imaging broadly

News & Updates

Events

Publications

Experimental Evaluation of AI-Driven Protein Design Risks Using Safe Biological Proxies

Author(s)
Svetlana Ikonomova, Bruce Wittmann, Fernanda Piorino Macruz de Oliveira, David Ross, Samuel Schaffter, Olga Vasilyeva, Elizabeth Strychalski, Eric Horvitz, James Diggans, Sheng Lin-Gibson, Geoffrey Taghon
Advances in machine learning are providing new abilities for engineering biology, promising leaps forward with beneficial applications. At the same time, these

Inter-tool analysis of a NIST dataset for assessing baseline nucleic acid sequence screening

Author(s)
Tyler Laird, Samuel Forry, Kevin Flyangolts, Craig Bartling, Bryan Gemler, Jacob Beal, Tessa Alexanian, Nicole Wheeler, Krista Ternus, Todd Treangen, Gene D. Godbold, Michael Nute, Leonard Foner, Scott Jackson, Jens Berlips
Nucleic acid synthesis is a dual-use technology that can benefit fields such as biology, medicine, and information storage. However, synthetic nucleic acids

Awards

Press Coverage

Setting Standards for Stool

Microbiome studies have yielded hundreds of ideas for ways to detect and influence human health, but the field struggles with reproducibility...

Blog Posts

Contacts

GENERAL INFORMATION: 301-975-8300 (PHONE); [email protected]; 100 BUREAU DRIVE, M/S 8300, GAITHERSBURG, MD 20899-8300

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