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Non-Boolean computing based on emerging post-CMOS technologies can potentially pave the way for low-power neural computing platforms. However, existing work on such emerging neuromorphic architectures have either focused on solely mimicking…
Bio-inspired neural networks have the potential to advance our understanding of neural computation and improve the state-of-the-art of AI systems. Bio-electrical synapses directly transmit neural signals, by enabling fast current flow…
Recently, superconductivity was discovered in the infinite layer of hole-doped nickelates NdNiO$_{2}$. Contrary to this, superconductivity in LaNiO$_{2}$ is still under debate. This indicates the crucial role played by the $f$ electrons on…
The electronic structure of transition metal oxides featuring correlated electrons can be rationalized within the Zaanen-Sawatzky-Allen framework. Following a brief description of the present paradigms of electronic behavior, we focus on…
Recent advances in neuroscience together with nanoscale electronic device technology have resulted in huge interests in realizing brain-like computing hardwares using emerging nanoscale memory devices as synaptic elements. Although there…
For most metals, increasing temperature (T) or disorder will quicken electron scattering. This hypothesis informs the Drude model of electronic conductivity. However, for so-called bad metals this predicts scattering times so short as to…
Motivated by the recent discovery of superconductivity in the pentalayer nickelate Nd$_6$Ni$_5$O$_{12}$ [Nature Materials 10.1038], we calculate its electronic structure and superconducting critical temperature. We find that electronic…
Understanding how biological neural networks carry out learning using spike-based local plasticity mechanisms can lead to the development of powerful, energy-efficient, and adaptive neuromorphic processing systems. A large number of…
High-transition-temperature ($T_{C}$) superconductivity is recently discovered in Ruddlesden-Popper (RP) nickelate films with extraordinarily strong oxidation. While investigating phase diagrams is essential for uncovering the…
An epitaxial semiconductor-superconductor nanowire is a superconducting system with a complex level structure originating from hybridization: in addition to a dense set of higher-energy states derived predominantly from the metallic…
Computing inspired by the human brain requires a massive parallel architecture of low-power consuming elements of which the internal state can be changed. SrTiO3 is a complex oxide that offers rich electronic properties; here Schottky…
Motivated by the report of superconductivity in bilayer La$_3$Ni$_2$O$_7$ at high pressure, we examine the interacting electrons in this system. First-principles many-body theory is utilized to study the normal-state electronic properties.…
Recently, signatures of superconductivity with critical temperature from 20 to 30 K have been reported in pressured trilayer nickelate La$_4$Ni$_3$O$_{10}$ through a pressure-induced structure transition. Here we explore the evolution of…
The experimental study of neural networks requires simultaneous measurements of a massive number of neurons, while monitoring properties of the connectivity, synaptic strengths and delays. Current technological barriers make such a mission…
Neuromorphic devices represent an attempt to mimic aspects of the brain's architecture and dynamics with the aim of replicating its hallmark functional capabilities in terms of computational power, robust learning and energy efficiency. We…
Recent years have seen an increasing interest in the development of artificial intelligence circuits and systems for edge computing applications. In-memory computing mixed-signal neuromorphic architectures provide promising ultra-low-power…
Molecular circuits capable of autonomous learning could unlock novel applications in fields such as bioengineering and synthetic biology. To this end, existing chemical implementations of neural computing have mainly relied on emulating…
We introduce a methodology to implement the physiological transition {between distinct neuronal spiking modes} in electronic circuits composed of resistors, capacitors and transistors. The result is a simple neuromorphic device organized by…
The strong coupling between an emitter and a cavity is significant for advancing quantum networks. Due to their long optical and spin coherence times, rare-earth ions (REIs) represent a compelling platform for quantum networks. However,…
Skyrmions are nano-sized magnetic whirls attractive for spintronic applications due to their innate stability. They can emulate the characteristic behavior of various spintronic and electronic devices such as spin-torque nano-oscillators,…