A5025225622- Advanced Memory and Neural Computing
- Ferroelectric and Negative Capacitance Devices
- Neuroscience and Neural Engineering
- Semiconductor materials and devices
- Neural Networks and Reservoir Computing
- ZnO doping and properties
- Photoreceptor and optogenetics research
- Transition Metal Oxide Nanomaterials
- Copper-based nanomaterials and applications
- Magnetic Properties and Synthesis of Ferrites
- Magnetic properties of thin films
- Magneto-Optical Properties and Applications
Universitat Autònoma de Barcelona
2023-2024
Indian Institute of Science Bangalore
2021-2023
Nanyang Technological University
2022-2023
Neuromorphic computing (NC), which emulates neural activities of the human brain, is considered for low-power implementation artificial intelligence. Toward realizing NC, fabrication, and investigations hardware elements─such as synaptic devices neurons─are crucial. Electrolyte gating has been widely used conductance modulation by massive carrier injections proven to be an effective way emulating biological synapses. Synaptic devices, in form transistors, have studied using various...
Abstract Advanced synaptic devices with simultaneous memory and processor capabilities are envisaged as core elements of neuromorphic computing (NC) for low‐power artificial intelligence. So far, most based on resistive memories, where the device resistance is tuned applied voltage or current. However, use electric current in such causes significant power dissipation due to Joule heating. Higher energy efficiency has been reported materials exhibiting control magnetism (VCM). In particular,...
With the advent of Big Data, traditional digital computing is struggling to cope with intricate tasks related data classification or pattern recognition. To mitigate this limitation, software‐based neural networks are implemented, but they run in conventional computers whose operation principle (with separate memory and data‐processing units) highly inefficient compared human brain. Brain‐inspired in‐memory achieved through a wide variety methods, for example, artificial synapses, spiking...
Neuromorphic computing (NC) is a crucial step toward realizing power-efficient artificial intelligence systems. Hardware implementation of NC expected to overcome the challenges associated with conventional von Neumann computer architecture. Synaptic devices that can emulate rich functionalities biological synapses are emerging. Out several approaches, electrolyte-gated synaptic transistors have attracted enormous scientific interest owing their similar working mechanism. Here, we report...
Tuning the properties of magnetic materials by voltage-driven ion migration (magneto-ionics) gives potential for energy-efficient, non-volatile memory and neuromorphic computing. Here, we report large changes in moment at saturation (mS) coercivity (HC), 34% 78%, respectively, an array CoFe2O4 (CFO) epitaxial nanopillar electrodes (∼50 nm diameter, ∼70 pitch, 90 height) with applied voltage −10 V a liquid electrolyte cell. Furthermore, magneto-ionic response faster than 3 s endurance...
Abstract Artificial synaptic devices capable of synchronized storing and processing information are the critical building blocks neuromorphic computing systems for low-power implementation artificial intelligence. Compared to diverse device structures, emerging electrolyte-gated transistors promising mimicking biological synapses owing their analogous working mode. Despite remarkable progress in transistors, study metallic channel-based remains vastly unexplored. Here, we report a...
Synaptic devices that emulate synchronized memory and processing are considered the core components of neuromorphic computing systems for low-power implementation artificial intelligence. In this regard, electrolyte-gated transistors (EGTs) have gained much scientific attention, having a similar working mechanism as biological synapses. Moreover, compared to traditional solid-state gate dielectric, liquid dielectric has key advantage inducing extremely large modulation carrier density while...
Epitaxial ferrimagnetic thin films of (Co, Ru) Fe2O4 were grown on MgO (001) substrate using pulsed laser deposition technique. Ruthenium substitution in cobalt ferrite has increased the conductivity by orders magnitude, but it a minimal effect magnetic properties. The film high coercivity and perpendicular anisotropy (PMA), where easy axis points to surface. We report electrical transport properties here. temperature variation resistivity showed different conduction mechanisms at...
Magneto-ionics, an emerging approach to manipulate magnetism that relies on voltage-driven ion motion, holds the promise boost energy efficiency in information technologies such as spintronic devices or future non-von Neumann computing architectures. For this purpose, stability, reversibility, endurance, and motion rates need be synergistically optimized. Among various ions, nitrogen has demonstrated superior magneto-ionic performance compared classical species oxygen lithium. Here, we show...
Neuromorphic Computing (NC), which emulates neural activities of the human brain, is considered for low-power implementation artificial intelligence. Towards realizing NC, fabrication, and investigations hardware elements such as synaptic devices neurons are essential. Electrolyte gating has been widely used conductance modulation by massive carrier injections proven to be an effective way emulating biological synapses. Synaptic devices, in form transistors, have studied using a wide variety...