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It is now widely accepted that memristive devices are perfect candidates for the emulation of biological synapses in neuromorphic systems. This is mainly because of the fact that like the strength of synapse, memristance of the memristive…
Nanofluidic systems exhibit transport characteristics that have made technological marvels such as desalination, energy harvesting, and highly sensitive biomolecule sensing possible by virtue of their ability to influence small currents due…
The rare-earth nickelates are a rich playground for transport properties, known to host non-Fermi liquid character, resistance saturation and metal-insulator transitions. We report a study of transport in LaNiO3 in the presence of tunable…
We present a design-scheme for ultra-low power neuromorphic hardware using emerging spin-devices. We propose device models for 'neuron', based on lateral spin valves and domain wall magnets that can operate at ultra-low terminal voltage of…
Motivated by recent experimental studies on superconductivity found in nickelate-based materials, we study the temperature dependence of the spin correlation and the superconducting pairing interaction within an effective two-band Hubbard…
Sophisticated machine learning struggles to transition onto battery-operated devices due to the high-power consumption of neural networks. Researchers have turned to neuromorphic engineering, inspired by biological neural networks, for more…
The role of electronic correlations in Condensed Matter is at the heart of various important systems, like magnetic materials, superconductors, topological materials, optical lattices, etc. Electronic correlations are those which change the…
Electron and nuclear spins associated with point defects in insulators are promising systems for solid state quantum technology. While the electron spin usually is used for readout and addressing, nuclear spins are exquisite quantum bits…
The perovskite nickelates RNiO$_3$ (R: rare-earth) have been studied as potential multiferroic compounds. A certain degree of charge disproportionation in the Ni ions has been confirmed by high resolution synchrotron power diffraction:…
Neuromorphic computing and spiking neural networks (SNN) mimic the behavior of biological systems and have drawn interest for their potential to perform cognitive tasks with high energy efficiency. However, some factors such as temporal…
Iron-based superconductors have been found to exhibit an intimate interplay of orbital, spin, and lattice degrees of freedom, dramatically affecting their low-energy electronic properties, including superconductivity. Albeit the precise…
With conventional silicon-based computing approaching its physical and efficiency limits, biocomputing emerges as a promising alternative. This approach utilises biomaterials such as DNA and neurons as an interesting alternative to data…
Driven by the pursuit of high-performance electronic devices, research into novel materials with properties appropriate for cryogenic applications has unveiled the exceptional properties of the rare-earth nitride series of intrinsic…
The recent discovery of bulk superconductivity in trilayer nickelate La$_4$Ni$_3$O$_{10}$ with the critical temperature $T_c$ near $30$K under high pressure is attracting a new wave of research interest, after the breakthrough of bilayer…
Learning and logic are fundamental brain functions that make the individual to adapt to the environment, and such functions are established in human brain by modulating ionic fluxes in synapses. Nanoscale ionic/electronic devices with…
The superconducting infinite-layer (IL) nickelates offer a new platform for investigating the long-standing problem of high-temperature superconductivity. Many models were proposed to understand its superconducting mechanisms based on the…
Nickel-based superconductors provide a long-awaited experimental platform to explore possible cuprate-like superconductivity. Despite similar crystal structure and $d$ electron filling, these systems exhibit several differences. Nickelates…
Neuromorphic architectures offer great promise for achieving computation capacities beyond conventional Von Neumann machines. The essential elements for achieving this vision are highly scalable synaptic mimics that do not undermine…
Single-molecule magnets weakly coupled to two ferromagnetic leads act as memory devices in electronic circuits---their response depends on history, not just on the instantaneous applied voltage. We show that magnetic anisotropy introduces a…
Living systems implement and execute an extraordinary plethora of computational tasks. The inherent degree of large scale coordination emerges as a global property, from the intricate sea of microscopic interactions. The brain, with its…