PhD-Memristor driven by self-propelled particles (Active Matter)
PhD @Loughborough University posted 14 hours agoJob Description
Project details
Memristors are a novel type of electronic component that adjust their resistance based on their electromagnetic history, such as past voltage pulses or current spikes. Non-volatile memristors retain their resistance state even after the voltage is turned off, making them suitable for emulating synaptic behaviour. In contrast, volatile memristors return to a default resistance state once the voltage is removed, enabling the emulation of neurons and their spiking activities.
This project will focus on non-volatile memristors and neuron emulation. A prominent example of an artificial neuron is the diffusive memristor, as described in the Nature article. In such systems, the rearrangement of silver clusters, which diffuse through a silicon oxide (SiO) matrix under an applied voltage, drives the volatile changes in memristor resistance. A neuromorphic circuit comprising this memristor in parallel with a capacitor and in series with a resistor represents a straightforward implementation of an artificial neuron. It converts constant or slowly varying voltage into current spikes, effectively mimicking the spiking behaviour of biological neurons.
We propose to take a significant step forward by replacing passively diffusing silver clusters with active particles. These particles will actively move within the medium, affecting the memristor’s resistance and facilitating artificial neuron spiking. Active particles may include fabricated Janus particles or microorganisms, capable of propelling themselves rather than merely diffusing. This innovation will pave the way for hybrid bio-driven memristor systems, where biological and artificial mechanisms of neurons’ spiking activity coexist.
Such systems could harness not only electrical energy but also chemical or internal energy sources for neuromorphic computations. This approach holds potential for advancing hardware-based spiking neural networks, merging biological and artificial components into a cohesive and efficient computational framework. Such networks have the potential to significantly enhance energy efficiency in AI hardware systems and facilitate direct communication between AI systems and the brain cortex, paving the way for the next generation of brain implants.
94% of Loughborough’s research impact is rated world-leading or internationally excellent. REF 2021
Supervisors
Primary supervisor:Â Sergey Saveliev
Secondary supervisors: Andrew Archer and Marco Mazza
Entry requirements
Our entry requirements are listed using standard UK undergraduate degree classifications i.e. first-class honours, upper second-class honours and lower second-class honours.
Entry requirements for United Kingdom
Physics or mathematics or electrical engineering degree (2.1) or equivalent.
English language requirements
Applicants must meet the minimum English language requirements. Further details are available on the International website.
Applicants must meet the minimum English language requirements. Further details are available on the International website.
Fees and funding
Tuition fees for 2025-26 entry
UK fee
£5,006 Full-time degree per annum
International fee
£28,600 Full-time degree per annum
Fees for the 2025-26 academic year apply to projects starting in October 2025, January 2026, April 2026 and July 2026.
Tuition fees cover the cost of your teaching, assessment and operating University facilities such as the library, IT equipment and other support services. University fees and charges can be paid in advance and there are several methods of payment, including online payments and payment by instalment. Fees are reviewed annually and are likely to increase to take into account inflationary pressures.
How to apply
All applications should be made online. Under programme name, Physics*. Please quote the advertised reference number: PH/SS-SF1/2025in your application.
To avoid delays in processing your application, please ensure that you submit a CV and the minimum supporting documents.
The following selection criteria will be used by academic schools to help them make a decision on your application. Please note that this criteria is used for both funded and self-funded projects.
Please note, applications for this project are considered on an ongoing basis once submitted and the project may be withdrawn prior to the application deadline, if a suitable candidate is chosen for the project.
