Seed – Characterization of Electron Transport and Luminescence of Corroded Metal Alloys
Funding Period: September 1, 2020 – March 31, 2022
Principal Investigators
Jennifer Choy
Assistant Professor, Engineering Physics
Adrien Couet
Assistant Professor, Engineering Physics and Materials Science and Engineering
Students & Postdocs
Ricardo Vidrio
Maryam Zahedian
Hongliang Zhang
Superseed – Validation of Soft Composite Characterization via Microcavitation and Correlation with Macroscopic Mechanical Behavior
Funding Period: September 1, 2020 – August 31, 2021
Principal Investigators
Andrew Boydston
Associate Professor, Chemistry
Padma Gopalan
Professor, Materials Science and Engineering
Co-Investigators
Stephan Rudykh
Assistant Professor, Mechanical Engineering
Ramathasan Thevamaran
Assistant Professor, Engineering Physics
Students & Postdocs
Jizhe Cai
Yuhai Xiang
Materials Systems for Controlling Extra- and Intracellular Assembly and Function
Funding Period: April 1, 2019 – August 31, 2020
Principal Investigator
Wendy Crone
Professor, Engineering Physics
crone@engr.wisc.edu
Co-Investigators
Timothy Kamp
Professor, Medicine/Cell and Regenerative Biology
Wisconsin Institute for Medical Research
Lih-Sheng Turng
Professor, Mechanical Engineering
Students
Alana Stempien, astempien@wisc.edu
Molecularly Doped Topological Photonic Materials
Funding Period: April 1, 2019 – August 31, 2020
Principal Investigator
Randall Goldsmith
Associate Professor, Chemistry
Co-Investigators
Paul Campagnola
Professor, Biomedical Engineering
Zongfu Yu
Associate Professor, Electrical & Computer Engineering
Students & Postdocs
- Samuel Alkmin, alkmin@wisc.edu
- Michael Mattei, mattei2@wisc.edu
- Lei Ying, lying8@wisc.edu
- Ming Zhou, mzhou34@wisc.edu
Synthetic Soft Matter Inspired by Behaviors of Bacterial Communities
Funding Period: April 1, 2019 – August 31, 2020
Principal Investigators
David Lynn
Professor, Chemical and Biological Engineering
Helen Blackwell
Professor, Chemical and Biological Engineering
Co-Investigator
Reid Van Lehn
Assistant Professor, Chemical and Biological Engineering
Students & Postdocs
- Harshit Argawal, hagarwal3@wisc.edu
- Lawrence Chen, lmchen@wisc.edu
- Curran Gahan, cgahan@wisc.edu
- Kayleigh Nyffleler, nyffeler@chem.wisc.edu
- Benjamin Ortiz, bortiz@wisc.edu
- Samarthaben Patel, spatel46@wisc.edu
- Thomas Polaske, polaske@wisc.edu
- Fengrui Wang, fwang82@wisc.edu
- Korbin West, khwest@wisc.edu
- Ke Zhao, kzhao29@wisc.edu
Potential Energy Landscape, Two-Level System and Boson Peak in Silica
Funding Period: April 1, 2019 – August 31, 2020
Principal Investigator
Bu Wang
Asisstant Professor, Civil & Environmental Engineering
bu.wang@wisc.edu
Co-Investigator
Isabel Szlufarska
Professor, Materials Science and Engineering
Students
Zheng Yu, zheng.yu@wisc.edu
Machine Learning Algorithms for High-Throughput Materials Data
Funding Period: April 1, 2019 – August 31, 2020
Principal Investigator
Victor Zavala
Associate Professor, Chemical and Biological Engineering
victor.zavala@wisc.edu
Co-Investigator
Reid Van Lehn
Assistant Professor, Chemical and Biological Engineering
Students
- Shengli Jiang, sjiang87@wisc.edu
- Alexander Smith, adsmith23@wisc.edu
Complex Oxides Nanomembranes: Synthesis, Assembly, and Order-from-Disorder Transitions in Confined Geometries
Funding Period: April 1, 2019 – January 31, 2020
Principal Investigators
Francesca Cavallo
Professor, Electrical and Computer Engineering
fcavallo@unm.edu
Co-Investigator
Christoph Deneke
Professor, Applied Physics, Universidade Estadual de Campinas – UNICAMP
Students
- Divya Jioty Prakash, University of New Mexico, dprakash@unm.edu
- Vijay Saradhi Mangu, University of New Mexico, vjsaradhimangu@unm.edu
Seed Highlights
(2022) Spray-on “SLIPS” and Controlled release “SNIPS”: New Designs for Slippery Antifouling Materials
Coatings that prevent fouling are critical in commercial, industrial, and healthcare contexts. Wisconsin MRSEC researchers have developed new spray-based methods to make nanoporous water-repelling films and spray-on ‘slippery liquid-infused porous surfaces’ (SLIPS). These coatings are antifouling to a range of substances and microorganisms and can be produced using scalable, manufacturing-compatible methods. They also developed new antifouling ‘slippery nanoemulsion-infused porous’ (SNIPS) that use water-in-oil nanoemulsions to slowly release encapsulated cargo.
November 8, 2022
(2022) An Underwater Topological Waveguide at MHz Frequencies
Concepts of topology recently have been brought to bear on materials designed to control sound waves. Sound wavelengths are much longer than light, making acoustic materials easier to synthesize and their behavior easier to measure. Wisconsin MRSEC researchers are using topological acoustic materials to explore topological physics and enable applications in sensing, communication, and energy transport.
November 1, 2022
(2021) Controlling Waves with 3D Printed Materials
Materials with a repetitive pattern the same size as the wavelength of a wave can be used to control the wave, causing it to bend, perfectly reflect or transmit, or even turn around corners. Where different patterns meet, even more exotic behavior occurs, including making highways for light or sound that only travel in one direction or where the waves cannot be dissipated. Synthesizing such materials is a major challenge, which Wisconsin MRSEC researchers have met by adapting a family of 3D printing techniques.
August 9, 2021
(2020) Energy Transfer Inside of a Topological Photonic Materials
The Wisconsin MRSEC has shown that molecules inside in a type of topological photonic material called a Weyl crystal can exchange energy over much larger distances. The intricate twisting structure of the material uses light to connect one molecule to others much farther away. Developing photonic Weyl crystals may contribute to more efficient LEDs and solar cells and improve molecular sensors.
February 22, 2021
(2020) Machine Learning Algorithms
The Wisconsin MRSEC has developed machine learning techniques that enable the design of new toxin sensors using liquid crystal droplets that respond to the presence of different bacterial toxins and at extremely low concentrations by changing shape and appearance. Machine learning enables computers to automatically analyze the droplet responses to measure toxin concentration and type automatically at high accuracy. More generally, these results demonstrate that the machine learning approach can quickly extract valuable information from complex datasets.
June 17, 2020- More Seed posts