Dr. Zengguang Cheng, Postdoctoral Research Associate, Department of Materials, University of Oxford, UK.

Zengguang received his Ph.D. in Condensed Matter Physics at National Center for Nanoscience and Technology, Chinese Academy of Sciences in 2015. He studied as a visiting scholar at Harvard University (2013-2014). After finishing his PhD study, he has worked as Postdoctoral Research Associate at University of Oxford (2015-present).

His research is in the area of nanomaterials and on-chip photonics, particularly in 2D materials devices and applications, and phase-change photonic computing. His key achievements include: the demonstration of suspended graphene FET (Nano Lett. 2010), optimization of graphene FET by wet-chemical and thermal treatment (Nano Lett 2011), graphene FET for chemical and biological applications (Nano Lett. 2013), syringe injectable flexible electronics (Nat Nano 2015), the first description of a photonic synapse for neuromorphic computing (Sci. Adv. 2017). His work has been featured widely over the last several years in MIT Technology Review, IEEE Spectrum, Scientific American, C&EN, National Geographic etc.

The search for new neuromorphic computing architectures that mimic the brain’s approach to simultaneous processing and storage of information is intense. Since in real brains neuronal synapses outnumber neurons by many orders of magnitude, the realization of hardware devices mimicking the functionality of a synapse is a first and essential step in such a search. Here we report the development of such a hardware synapse, implemented entirely in the optical domain via a photonic integrated circuit approach. Using purely optical means brings the benefits of ultrafast operation speed, virtually unlimited bandwidth and no electrical interconnect power losses. Our synapse utilizes phase-change materials (PCMs) combined with integrated silicon nitride waveguides. Crucially, we can randomly set the synaptic weight simply by varying the number of optical pulses sent down the waveguide, delivering an incredibly simple yet powerful approach that heralds systems with a continuously-variable synaptic plasticity resembling the true analogue nature of biological synapses.

Keywords:On-chip photonics, Phase-change materials, neuromorphic computing, synapse