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Material Measurement Laboratory / Materials Science and Engineering Division

Polymers Processing Group

Projects/Programs

Displaying 1 - 9 of 9
Diagram of In-Situ AFM During Resist Development

Advanced Metrology to Enable Next Generation EUV Photoresists

Ongoing
EUV (extreme ultraviolet) lithography, the technology that “saved Moore’s Law,” is widely regarded as the future of cutting-edge nanofabrication. It was developed in the United States and U.S. companies in many parts of the EUV ecosystem have established dominance in the field that must be defended
Harnessing EUV capabilities for non-destructive metrology

EUV Scatterometry

Ongoing
To measure and inspect the smallest printed features on an IC chip, researchers and manufacturers use a combination of electron scanning modalities (i.e., transmission electron and scanning electron microscopies) and an optical method, scatterometry. Industrially, the most common modality for

Flexible and Printed Electronics

Ongoing
Approach Developing commercial products based on organic electronics requires materials that deliver predictable and reproducible performance. One advantage of these materials is their compatibility with versatile solution processing methods. However, this advantage can lead to unpredictable
CDSAXS instrument

Metrology for Nanolithography

Ongoing
Small Angle Scattering techniques are employed to measure, with sub-nm precision, pattern shape, dimensions, and orientation for structures created in periodic arrays. Critical-Dimension Small Angle X-ray Scattering (CD-SAXS) utilizes the variable-angle transmission scattering from a small beam size
Materials Extrusion Additive Manufacturing

Polymer Additive Manufacturing and Rheology

Ongoing
We are measuring the fundamental processes and material parameters that are critical to understanding and furthering polymers-based AM. These efforts will aid the AM ecosystem through better online monitoring capabilities and developing strategies for materials optimization. In situ measurements of

Polymer Analytics

Ongoing
This project focuses on a variety of activities to achieve the aforementioned goal of accelerating the discovery of new polymer physics. Polymer databases In collaboration with partners, we build FAIR (findable, accessible, interoperable, reproducible) data resources that enable machine learning

Teaching Liquid State Theory to an Artificial Neural Network (ANN)

Ongoing
Scientific questions: Can an ANN allow us to predict the structure of fluids that are impossible to predict numerically via liquid-state theory? Can we learn something about liquid-state theory itself by the nature of the trained ANN? What features do the hidden layers capture?