IRG1 has developed a computational framework for understanding how nanoparticles (NPs) assemble at the interface between two immiscible fluids.
IRG1 has developed a computational framework for understanding how nanoparticles (NPs) assemble at the interface between two immiscible fluids.
This is the first demonstration of living ring opening metathesis polymerization (ROMP) from a biological substrate.
The ability to thermally trigger a conformational changeand collapse in a constituent resilin-like protein (RLP) providesthe opportunity to build, and eventually move, a bundlemer nanostructure.
This work demonstrates that the TI vdW material Bi2Se3 can be grown as a single-crystalline single-orientation film on semiconductor substrates with appropriate substrate pre-treatment conditions.
IRG-2 developed a symmetry-based approach that uses only few inputs, to carry out an efficient yet systematic search for topological magnons in magnetic insulators. Robust against disorders and decoherence, they serve as potential platforms for magnon-based spintronic devices.
The Ohio State University and University of California, Santa Barbara MRSECS partnered to host the Conference Across MRSECs and PREMs (CAMPS) in October 2022.
A principal obstacle to widespread applications of self-assembled network morphologies (NETs) of linear block polymers is access to only limited pore diameters and unit cell dimensions (typically <50 nm), originating from their coil configurations and slow self-assembly kinetics at high molar masses.
For the first time, a team comprised of two IRG-1 theorists (Birol and Fernandes) working with experimentalists from other institutions (including the Columbia MRSEC) showed the coexistence of ferroelectricity (i.e., electrostatically switchable macroscopic dipole moment) and superconductivity in a two-dimensional superconductor.
The Partnership for Research and Education in Materials between Navajo Technical University and the MRSEC based at Harvard focuses on developing culturally-informed, sustainable pathways into materials science-related careers and advanced studies for Navajo students.
A team at the Harvard MRSEC led by Bertoldi and Rycroft has developed a framework to design mechanical metamaterials with target nonlinear response. Neural networks were used to accurately learn the relationship between the geometry and nonlinear mechanical response of these metamaterials.