Research Group: Center for Condensed Matter Physics Number of Students: 1 Length of Study in Years: 4 years Full-time Project: yes
Funding is provided via the China Scholarship Council.
Emerging technologies, such autonomous transportation and computer vision, rely on processing vast amounts of data. Computers that use separate processing and memory units (a von Neumann architecture), must shuttle this data between CPU and memory. This movement of data is energy inefficient, and bottlenecks computational speed (known as the memory wall). With computing accounting for a growing fraction of global electricity use, researchers are investigating alternative technologies that aim to speed up, and mitigate the environmental impact of, the processing of big data.
Universal memory is one such technology. It combines the speed and low-power operation of static RAM with the non-volatility of flash memory. Resistive RAM (RRAM) has been touted as a universal memory and has a simple architecture: a switchable material placed between two conductive electrodes. The material is switched between a high-resistance state and a low-resistance state by the electric field within the junction and retains its state after being powered off. This hysteretic behaviour gives RRAM the capability for computation-in-memory, circumventing the memory wall. Furthermore, RRAM fabricated into arrays make it is possible to carry out linear-algebra-heavy tasks (such as matrix vector multiplication, MVM) in a highly parallel fashion. Molecules are excellent candidates for use as the switchable material due to their ease of processing and tuneable properties.
The proposed research project is to design and fabricate arrays of self-assembled monolayer molecular junctions in CMOS-compatible devices to (i) gain fundamental scientific insight into electron transport in molecular devices, and (ii) develop crossbar arrays of molecular junctions as a platform to explore RRAM and MVM applications. The candidate will learn skills in device micro- and nanofabrication, electrical measurements, and data analysis. The research could lead to molecule-based hardware for next-generation low power, massively parallel computing.
Applications are invited from outstanding candidates of Chinese nationality holding or expecting to gain a degree in Chemistry, Physics, Materials Science, and Engineering with an interest in computational and materials research. An enquiring and rigorous approach to research, as well as good team-working and communication skills (both presentation and written English) is essential.
Application Method:
To apply for this studentship and for entry on to the Physics programme (Full Time) please follow the instructions detailed on the following webpage:
https://www.qmul.ac.uk/spcs/phdresearch/application-process/#apply
Deadline for application - 31st of January 2024
Supervisor Contact Details:
For informal enquiries about this position, please contact Jan Mol with a full CV.
E-mail: j.mol@qmul.ac.uk
SPCS Academics: Professor Jan Mol