Graphene Based Memristors



An innovative new development was featured on the cover of ACS Advanced Electronic Materials. A step forward in the development of graphene-based memristors has been made. Scientists from Queen Mary University of London and Paragaf Limited are researching graphene memristors.  The new work opens the door to scalable production of graphene-based memristors.

Memristers are important devices used in non-volatile memory and artificial neural networks (ANNs). Memristers perform analog computations, mimic the synaptic functions of the brain and even store data without power. Graphene can increase performance in these devices drastically. Until recently, the addition of graphene was difficult to add into electronics in a scalable way. 

Dr. Zhichao Weng is a Research Scientist at the School of Physical and Chemical Sciences at Queen Mary. He reports, "Graphene electrodes bring clear benefits to memristor technology. They offer not only improved endurance but also exciting new applications, such as light sensitive synapses and optically tunable memories."

One important challenge is device degradation. Graphene can help prevent this block to memristor development. Graphene disturbs the chemical pathways that degrade traditional electrodes. It extends the lifetime and reliability of these devices. Graphene memristors transmit 98% of light, therefore it enhances the ability to increase computing applications, particularly in AI and optoelectronics. 

Creating a high quality graphene that is compatible with semi conductor processes is another big challenge. The team at Paragraf has made it possible to grow monolayer graphene directly on target substrates. The scientists used a proprietary process called Metal Organic Chemical Vapor Desposition (MOCVD) process. This technique is already being used in commercial devices. An example of these are graphene-based Hall effect sensors and field-effect transistors (GFETs).

John Tingay is CTO at Paragraf. He reports, "The opportunity for graphene to help in creating next generation computing devices that can combine logic and storage in new ways gives opportunities in solving the energy costs of training large language models in AI. This latest development with Queen Mary University of London to deliver a memrister proof of concept is an important step in extending graphene's use in electronics from magnetic and molecular sensors to proving how it could be used in future logic and memory devices."

Professor Oliver Fenwick is a professor of Electronic Materials at Queen Mary's School of Engineering and Materials Science. He summarizes, "Our research not only establishes proof of concept but also confirms graphene's suitability for enhancing memrister performance over other materials."


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