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The search for oxide materials with physical properties similar to the cuprate high Tc superconductors, but based on alternative transition metals such as nickel, has grown and evolved over time. The recent discovery of superconductivity in…
The human brain, with its energy-efficient and massively parallel architecture seamlessly integrates memory and computation. Its topology and functionality serve as the inspiration for the field of neuromorphic computing. Realizing…
The potential of memristive devices is often seeing in implementing neuromorphic architectures for achieving brain-like computation. However, the designing procedures do not allow for extended manipulation of the material, unlike CMOS…
The class of memory circuit elements which comprises memristive, memcapacitive, and meminductive systems, is gaining considerable attention in a broad range of disciplines. This is due to the enormous flexibility these elements provide in…
Rare-earth infinite-layer nickelates represent an emerging class of unconventional superconductors, with materials synthesis largely limited to early lanthanide compounds. Here, we report the synthesis and characterization of phase-pure…
Neuromorphic Computing (NC), which emulates neural activities of the human brain, is considered for low-power implementation of artificial intelligence. Towards realizing NC, fabrication, and investigations of hardware elements such as…
Strongly-correlated transition-metal oxides are widely known for their various exotic phenomena. This is exemplified by rare-earth nickelates such as LaNiO$_{3}$, which possess intimate interconnections between their electronic, spin, and…
Motivated by the high temperature superconductivity observed in the bilayer nickelate La$_3$Ni$_2$O$_7$ and the spectroscopic evidences of strong electron correlations in this compound, we address the role of its multiorbital electron…
The discovery of nickelate superconductors has opened a new arena for studying the behavior of correlated electron liquids that give rise to unconventional superconductivity. While critical information about a material's charge dynamics is…
Superconducting optoelectronic loop neurons are a class of circuits potentially conducive to networks for large-scale artificial cognition. These circuits employ superconducting components including single-photon detectors, Josephson…
Nanoelectronic devices emulating neuro-synaptic functionalities through their intrinsic physics at low operating energies is imperative toward the realization of brain-like neuromorphic computers. In this work, we leverage the non-linear…
Although discovery in hydrogen induced electronic transition within perovskite family of rare-earth nickelate (ReNiO3) opens up a new paradigm in exploring both the new materials functionality and device applications, the existing research…
This paper presents a simulation platform, namely CIMulator, for quantifying the efficacy of various synaptic devices in neuromorphic accelerators for different neural network architectures. Nonvolatile memory devices, such as resistive…
Reduced dimensionality and strong electronic correlations, which are among the most important ingredients for cupratelike high-Tc superconductivity, characterize also the physics of nickelate-based heterostructures. Starting from the…
The metal-insulator transition (MIT) of bulk rare-earth nickelates is accompanied by a simultaneous charge ordering (CO) transition. We have investigated low-frequency resistance fluctuations (noise) across the MIT and magnetic transition…
Electronic circuits are useful tools for studying potential dynamical behaviors of synthetic genetic networks. The circuit models are complementary to numerical simulations of the networks, especially providing a framework for verification…
Mixed-signal neuromorphic systems represent a promising solution for solving extreme-edge computing tasks without relying on external computing resources. Their spiking neural network circuits are optimized for processing sensory data…
Over the past decade Spiking Neural Networks (SNN) have emerged as one of the popular architectures to emulate the brain. In SNN, information is temporally encoded and communication between neurons is accomplished by means of spikes. In…
We demonstrate memory devices based on proton doping and re-distribution in perovskite nickelates (RNiO3, {R=Sm,Nd}) that undergo filling-controlled Mott transition. Switching speeds as high as 30 ns in two-terminal devices patterned by…
Epitaxial strain, layer confinement and inversion symmetry breaking have emerged as powerful new approaches to control the electronic and atomic-scale structural properties in complex metal oxides. Nickelate heterostructures, based on…