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We present results of an ab-initio study of the electronic structure of 140 rare earth compounds. Specifically we predict an electronic phase diagram of the entire range of rare earth monopnictides and monochalcogenides, composed of…
The interplay of multiorbital physics and nonlocal self-energy effects is studied within an effective three-orbital model for the high-pressure normal state of superconducting bilayer nickelate La$_3$Ni$_2$O$_7$. The model is solved within…
Emerging nanodevices such as resistive memories are being considered for hardware realizations of a variety of artificial neural networks (ANNs), including highly promising online variants of the learning approaches known as reservoir…
We present a comparative density-functional theory plus dynamical mean-field theory (DFT+DMFT) study of the two known superconducting members of the rare-earth (R) layered nickelate family: hole-doped RNiO$_{2}$ ($n=\infty$) and…
In this letter, we present an original demonstration of an associative learning neural network inspired by the famous Pavlov's dogs experiment. A single nanoparticle organic memory field effect transistor (NOMFET) is used to implement each…
Infinite-layer nickelate superconductors are typically synthesized as thin films and thus include, besides the more bulk-like inner layers, distinct surface and interface layers in contact with the vacuum and substrate, respectively. Here,…
As a means of dynamically reconfiguring the synaptic weight of a superconducting optoelectronic loop neuron, a superconducting flux storage loop is inductively coupled to the synaptic current bias of the neuron. A standard flux memory cell…
We present a novel methodology to enable control of a neuromorphic circuit in close analogy with the physiological neuromodulation of a single neuron. The methodology is general in that it only relies on a parallel interconnection of…
Infinite layer nickelates have garnered significant attention due to their potential for high-temperature superconductivity. Despite extensive research, the interplay between oxygen stoichiometry and electronic properties in infinite layer…
Biological neural networks do not only include long-term memory and weight multiplication capabilities, as commonly assumed in artificial neural networks, but also more complex functions such as short-term memory, short-term plasticity, and…
We conduct first-principles simulations of La$_3$Ni$_2$O$_7$, a nickelate in which recent experiments have shown signs of high-temperature superconductivity. Within the hydrostatic pressure range where superconductivity is observed, we find…
One of the central questions about the iron pnictides concerns the extent to which their electrons are strongly correlated. Here we address this issue through the phenomenology of the charge transport and dynamics, single-electron…
Oxygen vacancies play a crucial role in the control of the electronic, magnetic, ionic, and transport properties of functional oxide perovskites. Rare earth nickelates (RENiO$_{3-x}$) have emerged over the years as a rich platform to study…
Bio-integrated neuromorphic systems promise for new protocols to record and regulate the signaling of biological systems. Making such artificial neural circuits successful requires minimal circuit complexity and ion-based operating…
Caenorhabditis elegans (C. elegans) illustrated remarkable behavioral plasticities including complex non-associative and associative learning representations. Understanding the principles of such mechanisms presumably leads to constructive…
The fundamental properties of infinite-layer rare-earth nickelates (RNiO2) are carefully revisited and compared with those of CaCuO2 and RNiO3 perovskites. Combining first-principles and finite-temperature second-principles calculations, we…
First-order structural phase transition is a common phenomenon in materials that qualitatively alters their physical properties. Yet, the abrupt first-order nature is usually unexplained by realistic computations, implying an omission of…
Rare-earth ion ensembles doped in single crystals are a promising materials system with widespread applications in optical signal processing, lasing, and quantum information processing. Incorporating rare-earth ions into integrated photonic…
We demonstrate an electrolyte-gated hybrid nanoparticle/organic synapstor (synapse-transistor, termed EGOS) that exhibits short-term plasticity as biological synapses. The response of EGOS makes it suitable to be interfaced with neurons:…
Brain-inspired computing proposes a set of algorithmic principles that hold promise for advancing artificial intelligence. They endow systems with self learning capabilities, efficient energy usage, and high storage capacity. A core concept…