Our lab is dedicated to advancing solar photocatalysis as a sustainable route for environmental remediation and green hydrogen production. This eco-friendly technology leverages sunlight to activate semiconductor materials, enabling the breakdown of pollutants and water splitting without generating secondary waste. To overcome the limitations of traditional photocatalysts—such as poor visible-light response and rapid charge recombination—we design and engineer novel materials with enhanced optical, structural, and electronic properties. Our research spans the development of 2D semiconductors, magnetic nanocomposites, and heterojunction systems optimized for visible light. We focus on strategies like surface functionalization, size control (e.g., quantum dots), and Z-scheme charge transfer to boost photocatalytic efficiency. Magnetic semiconductors are also explored to improve charge separation and enable post-reaction recovery, making our systems more practical for real-world applications.

Neuromorphic computing is an emerging field focused on designing systems that emulate the complex behaviour of biological neural networks. In the age of Artificial Intelligence, neuromorphic computing presents a transformative paradigm for processing vast amounts of data in an energy-efficient, adaptive, and brain-inspired manner. Unlike conventional von Neumann architecture, which separates memory and processing units, neuromorphic systems are based on distributed processing and learning, akin to how biological neurons and synapses communicate and learn. This approach allows for parallel processing and real-time learning capabilities.

In our research, we fabricate synaptic devices using various 2D materials, leveraging their unique electrical and structural properties with changing different parameters to understand the mechanism. Our main goal is to investigate the neuromorphic behaviour of synaptic devices and mimic the synaptic functions of the human brain. By emulating processes such as short-term and long-term plasticity, learning, and memory, we strive to develop artificial synapses that bring us closer to building truly intelligent and adaptive hardware systems.

Triboelectric nanogenerators (TENGs) are innovative devices that convert mechanical energy from everyday sources—such as human motion, vibrations, water flow, and wind—into usable electrical energy. Operating on the principle of the triboelectric effect, which combines electrical friction and induction, TENGs offer a sustainable solution for energy harvesting. Ideal for powering low-energy devices like LEDs, calculators, capacitors, and hand clocks, these generators enable self-powered systems for sensors and smart electronics.