Energy Storage Devices (Supercapacitors and Batteries)
Triboelectric Nanogenerators
2D material-based gas sensors
Nanomaterials Synthesis and Characterizations
Neuromorphic Computing
Energy Storage Devices (Supercapacitor and Batteries)
The supercapacitor and batteries provide constant energy and power to portable electronic devices. SYNERGY Lab aims to develop cost-effective and lightweight nanomaterials for electrodes and cost-effective strategies to fabricate supercapacitors and batteries that can deliver high energy and power density with fast charging time. (Image copyright: Frontiers in Materials)
Triboelectric Nanogenerators (TENGs)
Herein, our research group is to develop new kinds of materials to improve the performance of the TENGs and their use in flexible and wearable electronics applications. TENGs can be used to power small-scale electronic devices and sensors. Additionally, TENGs can be integrated with the Internet of Things (IoT) devices and sensor networks, enabling self-powered and sustainable systems. (Image copyright: Nanoenergy advances)
MEMS Devices and Sensors
This research aims to contribute to the evolution of MEMS devices and sensors, fostering advancements in various applications. The outcomes are expected to have a significant impact on fields such as healthcare, environmental monitoring, and industrial automation by providing more reliable, cost-effective, and energy-efficient sensing solutions. (Image copyright: EV Group)
Nanomaterials Synthesis and Characterization
The expected outcomes of this research are anticipated to significantly impact various industries, including electronics, healthcare, energy, and environmental remediation. By advancing synthesis techniques and characterization methods, this research aims to accelerate the integration of nanomaterials into practical applications, fostering technological advancements and addressing societal challenges.
Neuromorphic Computing with Neurons
The human brain's analogous properties are emulated by utilizing a memristor device in terms of 'learning', 'forgetting' 'potentiation', 'depression', and memory transition in the form of short-term memory (STM) to long-term memory (LTM) and also build the artificial neural network (ANN) with dense memristor crossbar array devices. (Image copyright: Materials Today Physics)