Postdoctor, Sun Yat-sen University, China
Dr. Xiaoci Liang is a postdoctoral researcher at Sun Yat-sen University, specializing in microelectronics and solid-state electronics. After completing his Ph.D., M.E., and B.E. in Microelectronics at the same institution, he has contributed significantly to the study of oxide thin-film transistors and electrolyte-gated transistors. His research is aimed at advancing neuromorphic computing and resistive random-access memory (RRAM) technologies. Dr. Liang’s expertise lies in the development of energy-efficient and high-performance devices for the future of computing and memory systems. His academic achievements include multiple high-impact publications in leading journals like Nature Electronics, The Journal of Physical Chemistry Letters, and Applied Physics Letters, showcasing his innovative work in the field of transistors and memory systems. Dr. Liang continues to push the boundaries of semiconductor research with a focus on sustainability, scalability, and performance optimization.
Profile
Education
Dr. Xiaoci Liang pursued his education at Sun Yat-sen University, where he completed his Bachelor’s degree in Microelectronics (2016), followed by his Master’s in Microelectronics and Solid-State Electronics (2019), and his Ph.D. in the same field (2023). His academic journey has been marked by consistent excellence in the field of microelectronics, culminating in cutting-edge research on oxide thin-film transistors and electrolyte-gated transistors. The focus of his studies has been on integrating advanced materials and device architectures to improve the performance of transistors for next-generation computing and memory technologies. His doctoral research has made a significant impact on the development of neuromorphic computing systems and resistive random-access memory (RRAM), establishing him as a leading researcher in the field. Through his educational path, Dr. Liang has acquired a comprehensive understanding of semiconductor physics and the challenges and opportunities in modern electronics and computing technologies.
Experience
Dr. Xiaoci Liang is currently a postdoctoral researcher at the School of Electronics and Information Technology at Sun Yat-sen University. Since joining the university in 2023, he has focused on developing electrolyte-gated transistors and exploring their potential in neuromorphic computing. His prior research experiences include investigating oxide thin-film transistors and their applications in resistive random-access memory (RRAM). His work on high-performance thin-film transistor technologies has been supported by the Natural Science Foundation of China, and the China National Postdoctoral Program for Innovative Talents. Dr. Liang has published extensively in leading journals such as Nature Electronics, The Journal of Physical Chemistry Letters, and Applied Physics Letters. He has also contributed to high-impact research on energy-efficient devices for neuromorphic systems. His experience has established him as a rising star in the field, with a track record of successful projects and cutting-edge technological advancements.
Research Focus
Dr. Xiaoci Liang’s research primarily revolves around thin-film transistors and electrolyte-gated transistors, with a focus on their application in neuromorphic computing and resistive random-access memory (RRAM). He has explored the underlying physical mechanisms that govern the behavior of high-mobility oxide semiconductors, aiming to enhance their performance for next-generation electronic devices. One of his key research interests is developing low-power, high-speed electrolyte-gated transistors that can emulate biological synapses for neuromorphic computing systems. This research holds the potential to revolutionize artificial intelligence hardware. His projects also focus on improving the scalability and energy efficiency of RRAM devices, which are critical for future memory storage solutions. Through innovative research on material properties and device architecture, Dr. Liang is advancing the integration of these technologies into practical applications. His work is positioning him at the forefront of microelectronics research with a vision for sustainable and high-performance electronics.
Publication Top Notes
- Multimode transistors and neural networks based on ion-dynamic capacitance 🌐🧠 Nature Electronics, 2022
- Evidence for Pseudocapacitance and Faradaic Charge Transfer in High-Mobility Thin-Film Transistors 🧪🔬 The Journal of Physical Chemistry Letters, 2020
- Artificial synaptic transistor with solution-processed InOx channel and AlOx solid electrolyte gate 🧠🔋 Applied Physics Letters, 2020
- Efficient Defect Engineering for Solution Combustion Processed In-Zn-O thin films for high performance transistors ⚡🔧 Semiconductor Science and Technology, 2017
- Extraction method of trap densities for indium zinc oxide thin-film transistors processed by solution method 🔍⚙️ Thin Solid Films, 2018