Researchers from Queen Mary University of London and Paragraf Limited have reported a ‘significant step forward in the development of graphene-based memristors’ for potential use in future computing systems and artificial intelligence (AI).
This innovation, which has been achieved at wafer scale, begins to pave the way toward scalable production of graphene-based memristors, devices crucial for non-volatile memory and artificial neural networks (ANNs). Memristors are recognized as potential game-changers in computing, offering the ability to perform analogue computations, store data without power, and mimic the synaptic functions of the human brain. The integration of graphene can enhance these devices dramatically, but has been notoriously difficult to incorporate into electronics in a scalable way until recently.
Researchers from Queen Mary University of London and Paragraf Limited have reported a ‘significant step forward in the development of graphene-based memristors’ for potential use in future computing systems and artificial intelligence (AI).
This innovation, which has been achieved at wafer scale, begins to pave the way toward scalable production of graphene-based memristors, devices crucial for non-volatile memory and artificial neural networks (ANNs). Memristors are recognized as potential game-changers in computing, offering the ability to perform analogue computations, store data without power, and mimic the synaptic functions of the human brain. The integration of graphene can enhance these devices dramatically, but has been notoriously difficult to incorporate into electronics in a scalable way until recently.
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