Browsing by Author "Mohili, R."

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    Metallic nanosponges for energy storage and conversion applications
    (Royal Society of Chemistry, 2022) Hemanth, N.R.; Mohili, R.; Patel, M.; Jadhav, A.H.; Lee, K.; Chaudhari, N.K.
    In order to meet the current energy storage demands, the rational design of novel nanostructured materials is crucial for the improvement of electrochemical storage and conversion performance. Nanostructured materials have shown promising results in various energy harvesting systems, owing to their multifunctional properties such as a large active surface area, mechanical strength, catalytic ability, excellent ion diffusion, and electronic conductivity. To date, the library of nanostructured materials consists of diverse compositions ranging from oxides, dichalcogenides, carbides to graphene-based and lithium alloys with various morphologies such as zero-dimensional (0D), 1D, 2D and 3D nanomaterials. In particular, nanosponges have exhibited unusual three-dimensional architecture that provides rich surface defects and excellent structural stability resulting in improved catalytic activity. Additionally, the large conducting surface, electronic conductivity and pronounced crystalline phase stability of nanosponges have been utilized to improve the electrode performance drastically. Moreover, the unique sponge-like metallic porous network not only reduces the overall weight of the device but also decreases the consumption of metal usage. In this context, this review particularly highlights the recent progress in the synthesis and properties of noble metals and other metal-based sulphide, oxide, hydroxide and phosphide nanosponges, and their application in electrochemical storage and conversion devices. © 2022 The Royal Society of Chemistry.
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    MXenes: promising 2D memristor materials for neuromorphic computing components
    (Cell Press, 2022) Patel, M.; Hemanth, N.R.; Gosai, J.; Mohili, R.; Solanki, A.; Roy, M.; Fang, B.; Chaudhari, N.K.
    Brain-inspired parallel computing ‘neuromorphic computing’ is one of the most promising technologies for efficiently handling large amounts of information data, which operates based on a hardware-neural network platform consisting of numerous artificial synapses and neurons. Memristors, as artificial synapses based on various 2D materials for neuromorphic and data storage technologies with low power consumption, high scalability, and high speed, have been developed to address the von Neumann bottleneck and limitations of Moore's law. The 2D MXenes have strong potential application in memristors due to their ultrahigh conductivity, fast charge response, high stacking density, and high hydrophilicity. Here, we discuss how MXenes are emerging as a potential material towards artificial synapses. Recent progress in research on artificial synapses, fabricated particularly using MXenes and their composite materials, is comprehensively discussed with respect to mechanism, synaptic characteristics, power efficiency, and scalability. Finally, we present an outlook of the future development of MXenes for artificial intelligence and challenges in integrating memristors with MXenes are briefly discussed. © 2022 Elsevier Inc.