activity
19942023
most citedChallenges in materials and devices for Resistive-Switching-based Neuromorphic Computing

256 citations · 2.6k across the 56 of their papers we have counts for

collaborators

56 papers

cond-mat.mtrl-sci2023★ 11 cited

Magnetoresistance anomaly during the electrical triggering of a metal-insulator transition

Pavel Salev, Lorenzo Fratino, Dayne Sasaki +4

Phase separation naturally occurs in a variety of magnetic materials and it often has a major impact on both electric and magnetotransport properties. In resistive switching system…

q-bio.NC2023

Solid State Neuroscience: Spiking Neural Networks as Time Matter

Marcelo J. Rozenberg

We aim at building a bridge between to {\it a priori} disconnected fields: Neuroscience and Material Science. We construct an analogy based on identifying spikes events in time wit…

cond-mat.str-el2023★ 10 cited

Bandwidth Control and Symmetry Breaking in a Mott-Hubbard Correlated Metal

Lishai Shoham, Maria Baskin, Tom Tiwald +10

In Mott materials strong electron correlation yields a spectrum of complex electronic structures. Recent synthesis advancements open realistic opportunities for harnessing Mott phy…

cond-mat.mtrl-sci2023★ 1 cited

Characteristic lengthscales of the electrically-induced insulator-to-metal transition

Theodor Luibrand, Adrien Bercher, Rodolfo Rocco +16

Some correlated materials display an insulator-to-metal transition as the temperature is increased. In most cases this transition can also be induced electrically, resulting in vol…

cond-mat.str-el2022★ 17 cited

Imaging the itinerant-to-localized transmutation of electrons across the metal-to-insulator transition in VO

Maximilian Thees, Min-Han Lee, Rosa Luca Bouwmeester +14

In solids, strong repulsion between electrons can inhibit their movement and result in a "Mott" metal-to-insulator transition (MIT), a fundamental phenomenon whose understanding ha…

cs.ET2022★ 77 cited

Quantum materials for energy-efficient neuromorphic computing

Axel Hoffmann, Shriram Ramanathan, Julie Grollier +16

Neuromorphic computing approaches become increasingly important as we address future needs for efficiently processing massive amounts of data. The unique attributes of quantum mate…