NewsNanoparticle-based computing architecture for nanoparticle
neural networks

2nd September 2020by admin0
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Scalable nanoparticle-based computing architectures
have several limitations that can severely compromise the use of
nanoparticles to manipulate and process information through
molecular computing schemes. The von Neumann architecture (VNA)
underlies the operations of multiple arbitrary molecular logic
operations in a single chip without rewiring the device. In a new
report, Sungi Kim and a team of scientists at the Seoul National
University in South Korea developed the nanoparticle-based VNA
(NVNA) on a lipid chip. The nanoparticles on the lipid chip
functioned as the hardware—featuring memories, processors and
output units. The team used DNA strands as the software to provide
molecular instructions to program the logic circuits. The
nanoparticle-based von Neuman architecture (NVNA) allowed a group
of nanoparticles to form a feed-forward neural network known as a
perceptron (a type of artificial neural network). The system can
implement functionally complete Boolean logical operations to
provide a programmable, resettable and scalable computing
architecture and circuit board to form nanoparticle neural networks
and make logical decisions. The work is now published on Science
Advances.

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The New Fusion technology is based on a phenomenon called triplet-triplet annihilation (TTA) which is a process in which two triplet excitons annihilate and produce a higher energy singlet exciton.

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