Congratulations
to our colleague MS Student. Pham Phu Quan, for his recent publication entitled
in the journal " Ceramics International", which was a collaboration with
our colleagues in the lab of Dr. Nguyen Thi My Lan at the Faculty of Biology
and Biotechnology of the University of Science, VNU-HCM.
A
new approach is being developed in neuromorphic computing, presenting a
promising method that tightly integrates memory and computing units, known as
in-memory computing. The crucial element in in-memory computing architectures
is a neuromorphic electronic synapse employed to replicate the functionality of
biological synapses. It adapts synaptic weights and stores them as dispersed
memory throughout the neural network. A two-terminal memristor, in which the
device resistance can be gradually adjusted by controlling charge, has been
widely suggested as an artificial synapse for achieving storage and
computational functions. The memristor is comprised of semiconductor layers
positioned between two electrodes, and resistive switching (RS) can occur due
to either electroforming (conductive filaments), charge migrations, or phase
transition. For electronic synapse devices to function effectively in neural
networks, they must be capable of achieving multiple implemented states.
Semiconductor devices lost ground to emerging computational models for tasks
requiring more than two binary states. Historically, CMOS circuits have
simulated ANNs using dozens of transistors, consuming significant chip area and
energy; hence, this approach was not feasible for large-scale integration.
Memristor devices can exhibit gradual set/reset switching behaviour, known as analogue
RS behaviour.
In
this work, by utilizing avocado seed extract instead of hazardous chemicals, we
synthesized ZnO NPs that are non-toxic, environmentally friendly, and
cost-effective for large-scale production. Then, we designed and fabricated a
self-rectifying analogue memristor employing a Cr/ZnO NPs/FTO junction
structure that effectively prevents sneak current. We thoroughly examined and
emulated the memristor's switching characteristics and synaptic behaviour
through statistical analysis.
For more details, please visit:
https://doi.org/10.1016/j.ceramint.2024.05.154
See
the supplementary material for a detailed green synthesis procedure.
Funding
This work was supported by the Vingroup Innovative Fund under grant number VINIF.2023. DA130.
The authors express their sincere thanks to the crew of the Center for INOMAR, VNU-HCM for their continuous support and help in using the XRD and FTIR facilities.
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