dc.rights.license | CC-BY-NC-ND | |
dc.contributor | Tim Kamsma, Willem Boon | |
dc.contributor.advisor | Roij, R.H.H.G. van | |
dc.contributor.author | Klop, Martijn | |
dc.date.accessioned | 2024-08-30T23:02:09Z | |
dc.date.available | 2024-08-30T23:02:09Z | |
dc.date.issued | 2024 | |
dc.identifier.uri | https://studenttheses.uu.nl/handle/20.500.12932/47515 | |
dc.description.abstract | Charged micro-scale fluid channels display intriguing and non-linear transport phenomena.
When forced or integrated in an electric circuit, they display spiking and learning behaviour similar
to our neurons and synapses. By adding specific surface chemistry to the walls of these channels, a
coupling between charge accumulation, surface charge and conductivity opens up a new spectrum of
possibilities for neuromorphic engineering. Specifically, intrinsically non-linear charging dynamics
of surface reactions with charged reactants are amplified by the current rectifying behaviour of
inhomogeneous channel types, such as cones, creating a semi-independent internal state parameter
that changes the conductivity. Among other things, these systems can display near non-volatile
memristive properties, frequency dependent plasticity and chemically induced Hebbian learning.
Because of their high-level resemblance with the underlying physics and chemistry of synaptic
transmission, these systems are promising for use in neuromorphic computing, neural implants
and brain-computer interfaces. | |
dc.description.sponsorship | Utrecht University | |
dc.language.iso | EN | |
dc.subject | Using nonlinear transport in microfluidics and surface chemistry to
design fully iontronic memristors with short-term, long-term,
frequency-dependent and Hebbian plasticity | |
dc.title | Synaptic Microchannels | |
dc.type.content | Master Thesis | |
dc.rights.accessrights | Open Access | |
dc.subject.keywords | Memristors, Microchannels, Neuromorphic, Plasticity, Surface Charge, Hebbian | |
dc.subject.courseuu | Theoretical Physics | |
dc.thesis.id | 24717 | |