Research Projects

The rapid growth in information technologies has led to the development of novel data storage and computing devices, which are essential for industry 4.0. Traditional von Neumann computing architecture is inefficient in terms of memory latency, parallel processing, power consumption, and storage capacity. To address these issues, the industry and academia are working on a brain-inspired neuromorphic computing system that mimics the memory, learning, and cognition properties of the human brain. Artificial synaptic devices are a basic building block of neuromorphic computing architecture, and their efficient fabrication can be achieved using resistive switching materials. To reduce e-waste and develop environmentally-specific sustainable electronic systems, electrospinning-derived 1D bionanocomposite nanofiber (NF) materials are proposed. The 1D morphology of electrospun NFs provides excellent charge transport pathways, resulting in excellent switching speed. The project aims to demonstrate the switching voltages of bionanocomposite-based synaptic devices at the biological scale (40 mV to 100 mV) and fabricate bionancomposite-based synaptic devices that show synaptic properties at a biological time scale (μs to ms). The project will also implement artificial or convolution neural networks for pattern/image recognition applications. This project is an important step towards synthesizing technologically important materials and fabricating future-ready devices for next-generation brain-inspired neuromorphic computing applications.