Demonstrated an automated materials multifunctional characterization platform with computer-centered experiments using real-time data fitting and modeling response.
Application of an electrical stimulation training protocol to a phospholipid droplet interface bilayer (DIB) results in persistent synaptic plasticity in the form of long-term potentiation (LTP), an important componen
A novel time-domain quantum electronic dynamics method was developed to evaluate broad-band momentum-resolved cross-sections for electronic excitations of nanomaterials due to inelastic scattering.
The shape-memory effect of two photon polymerization (TPP)-fabricated microfibers in water was revealed and precisely quantified using a novel tensile testing method.
A multimodal scanning probe microscopy (SPM) approach reveals fast ionically mediated electromechanical coupling in the van der Waals ferroelectric CuInP2S6 (CIPS) along wit
Polymeric liquids exhibit complex and fascinating flow behavior. Despite the remarkable theoretical progress brought about by the tube model, understanding the molecular dynamics of long-chain molecules under flow still faces formidable challenges.
Precise control of charge transfer between catalyst nanoparticles and supports presents a unique opportunity to enhance the stability, activity, and selectivity of heterogeneous catalysts.
Additively manufactured (AM) metal alloys by laser powder bed fusion (L-PBF) involve large temperature gradients and rapid cooling that enable microstructural refinement to the nanoscale for achieving high strength.
Machine learning is rapidly becoming an integral part of experimental physical discovery via automated and high-throughput synthesis, and active experiments in scattering and electron/probe microscopy.
Two-terminal memory elements, or memelements, capable of co-locating signal processing and memory via history-dependent reconfigurability at the nanoscale are vital for next-generation computing materials striving to match the brain’s efficiency