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Program Highlights

Monitoring the Solution Persistence of Porous Coordination Cages with Diffusion NMR Spectroscopy and Cryogenic Transmission Electron Microscopy

Here, diffusion of NMR spectroscopy, transmission electron microscopy, and cryogenic transmission electron spectroscopy were used to characterize porous cages in solution. A combination of the methods can be used to discriminate between assembled cages as opposed to decomposed or isomerized materials while dissolved in polar organic solvents, regardless of the metal cations used in their assembly.

Bi2Se3 Growth on (001) GaAs Substrates for Terahertz Integrated Systems

The research focus involves understanding how to integrate van der Waals materials like Bi2Se3 with industrially-relevant semiconductor materials like GaAs(001) using molecular beam epitaxy (MBE) for THz applications, as well as determining the chemical composition and bonding type of the Bi2Se3/GaAs(001) interface using density functional theory (DFT) calculations.

Ultrasensitive detection of various biomarkers including SARS-CoV-2 using deformed graphene channel field effect biosensors

Field-effect transistor (FET)-based biosensors allow label-free detection of biomolecules by measuring their intrinsic charges. We previously reported the extremely low limit of detection on electrical field effect-based sensors using crumpled graphene. Here, we use FETs with a deformed monolayer graphene channel for the detection of various biomarkers.

Packaging and Release of mRNA and of other Macromolecules from Supramolecular Virus-Like Assemblies

We developed one-component, sequence-defined Ionizable Amphiphilic Janus Dendrimers (IAJDs) and their assemblies with mRNA. These Dendrimersome Nanoparticles (DNPs) were investigated for the delivery of mRNA for vaccines and nanotherapeutics.

Relationships between structure, memory, and flow in sheared disordered materials

A disordered material’s structure and macroscopic mechanical response are related in a non-trivial way. By studying a 2D jammed colloidal system under oscillatory shear, our study elucidates this link in the transition from elasticity to plasticity based on microstructural signatures.

First crystal growth and magnetic structure of the high-temperature antiferromagnet Cr2Al

Switching Néel vector orientations in antiferromagnets has been proposed as an ultrafast means of data storage, but the fundamental energy scales of switching cannot be evaluated without oriented measurements on single crystals. These single-crystal methods are vital for understanding if first-principles calculations can predict the energies and dynamics that govern these devices.

Atomic-scale origin of the low grain-boundary resistance in perovskite solid electrolyte Li0.375Sr0.4375Ta0.75Zr0.25O3

The main goal of this research is to reveal the atomic-scale origin of the low grain-boundary (GB) resistance in Li0.375Sr0.4375Ta0.75Zr0.25O3 (LSTZ0.75) perovskite solid electrolyte and to provide insights on overcoming the ubiquitous bottleneck of high GB resistance in other oxide solid electrolytes.

Electrically Fueled Active Materials

The UCI MRSEC team have developed the first electrically-fueled dissipative system that offers rapid kinetics, directionality, and unprecedented spatiotemporal control, closely mimicking systems found in nature.

Student-Industry Seed Projects Teach Essential Skills for Future Success

Preparing students for careers inside and outside academia is a key mission for the Wisconsin MRSEC and its Advanced Materials Industrial Consortium (AMIC). AMIC sponsors student-led seed research projects to help students learn essential skills. AMIC companies suggest project areas, then company engineers work with MRSEC students to develop research proposals that leverage the student’s expertise.

Low temperature properties of glass and its connection to glass stability

Wisconsin MRSEC IRG 1 developed a new theory describing how sound waves couple two level systems together. Experiments using a superconducting qubit measured the coupling of many TLS, one at a time, and showed that they are consistent with the theory. Machine learning applied to simulations identified the atomic arrangements associated with TLS and showed that as the glass grows more stable, the TLS density decreases.