138 citations · 342 across the 8 of their papers we have counts for
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cond-mat.mes-hall2023
Graphene-Based Artificial Dendrites for Bio-Inspired Learning in Spiking Neuromorphic Systems
Samuel Liu, Deji Akinwande, Dmitry Kireev +1
Analog neuromorphic computing systems emulate the parallelism and connectivity of the human brain, promising greater expressivity and energy efficiency compared to digital systems.…
cond-mat.mes-hall2022★ 1 cited
Metaplastic and Energy-Efficient Biocompatible Graphene Artificial Synaptic Transistors for Enhanced Accuracy Neuromorphic Computing
Dmitry Kireev, Samuel Liu, Harrison Jin +4
CMOS-based computing systems that employ the von Neumann architecture are relatively limited when it comes to parallel data storage and processing. In contrast, the human brain is…
cond-mat.mes-hall2020★ 30 cited
Origins of leakage currents on electrolyte-gated graphene field-effect transistors
A. Svetlova, D. Kireev, D. Mayer +1
Graphene field-effect transistors are widely used for development of biosensors. However, certain fundamental questions about details of their functioning are not fully understood…