Dynamical memristors for higher-complexity neuromorphic computing
Research on electronic devices and materials is currently driven by both the slowing down
of transistor scaling and the exponential growth of computing needs, which make present …
of transistor scaling and the exponential growth of computing needs, which make present …
Nanoarchitectonics intelligence with atomic switch and neuromorphic network system
T Tsuchiya, T Nakayama, K Ariga - Applied Physics Express, 2022 - iopscience.iop.org
An emerging concept of" nanoarchitectonics" has been proposed as a way to apply the
progress of nanotechnology to materials science. In the introductory parts, we briefly explain …
progress of nanotechnology to materials science. In the introductory parts, we briefly explain …
In materia reservoir computing with a fully memristive architecture based on self-organizing nanowire networks
Neuromorphic computing aims at the realization of intelligent systems able to process
information similarly to our brain. Brain-inspired computing paradigms have been …
information similarly to our brain. Brain-inspired computing paradigms have been …
2022 roadmap on neuromorphic computing and engineering
DV Christensen, R Dittmann… - Neuromorphic …, 2022 - iopscience.iop.org
Modern computation based on von Neumann architecture is now a mature cutting-edge
science. In the von Neumann architecture, processing and memory units are implemented …
science. In the von Neumann architecture, processing and memory units are implemented …
Nanoarchitectonics: what's coming next after nanotechnology?
K Ariga - Nanoscale Horizons, 2021 - pubs.rsc.org
In science and technology today, the crucial importance of the regulation of nanoscale
objects and structures is well recognized. The production of functional material systems …
objects and structures is well recognized. The production of functional material systems …
Avalanches and edge-of-chaos learning in neuromorphic nanowire networks
The brain's efficient information processing is enabled by the interplay between its neuro-
synaptic elements and complex network structure. This work reports on the neuromorphic …
synaptic elements and complex network structure. This work reports on the neuromorphic …
Neuromorphic learning, working memory, and metaplasticity in nanowire networks
Nanowire networks (NWNs) mimic the brain's neurosynaptic connectivity and emergent
dynamics. Consequently, NWNs may also emulate the synaptic processes that enable …
dynamics. Consequently, NWNs may also emulate the synaptic processes that enable …
Online dynamical learning and sequence memory with neuromorphic nanowire networks
Abstract Nanowire Networks (NWNs) belong to an emerging class of neuromorphic systems
that exploit the unique physical properties of nanostructured materials. In addition to their …
that exploit the unique physical properties of nanostructured materials. In addition to their …
Intermolecular and electrode-molecule bonding in a single dimer junction of naphthalenethiol as revealed by surface-enhanced Raman scattering combined with …
K Homma, S Kaneko, K Tsukagoshi… - Journal of the American …, 2023 - ACS Publications
Electron transport through noncovalent interaction is of fundamental and practical
importance in nanomaterials and nanodevices. Recent single-molecule studies employing …
importance in nanomaterials and nanodevices. Recent single-molecule studies employing …
Physical reservoir computing with emerging electronics
Physical reservoir computing is a form of neuromorphic computing that harvests the dynamic
properties of materials for high-efficiency computing. A wide range of physical systems can …
properties of materials for high-efficiency computing. A wide range of physical systems can …