About the project
This project engineers the atomic-scale microstructure of Josephson junctions—optimising grain orientation, stress, and interfaces—for longer-lived, reproducible qubits. Students will combine advanced thin-film growth, microscopy, and cryogenic testing to engineer “perfect” quantum hardware.
Superconducting qubits underpin today’s most advanced quantum computers, yet their performance is limited by materials imperfections at the heart of their nonlinear element — the Josephson junction (JJ). Presently, most transmon qubits use Al/AlOx/Al junctions fabricated by double-angle shadow evaporation. While effective at the nanoscale, this approach faces critical challenges of qubit lifetime, inhomogeneous broadening from fabrication and precise interface control at the nanoscale.
The UK National Quantum Strategy highlights materials and fabrication science as critical to achieving reproducible, manufacturable qubits. There is an urgent need to bring a materials-engineering approach — grain orientation, stress relaxation, micro-texture, interface bonding — to the superconducting JJ stack.
This project aims to systematically engineer and optimise the multilayer materials microstructure of Josephson junctions for superconducting qubits, achieving low lifetime variation, controlled texture, reproducible critical current, and compatibility with scalable manufacturing processes.
Research objectives include:
- Thin Film Nanostructure Control: Study Al, Nb, and NbN thin films: deposition rate, substrate temperature, and post-deposition annealing to tune grain size, orientation, nanoscale texture, and residual stress.
- Barrier and Interface Engineering: Compare native thermal AlOx vs plasma vs Atomic Layer Deposition (ALD) Al₂O₃ and explore epitaxial oxide barriers; characterise interfacial bonding, stoichiometry, and roughness.
- Device-Level Validation: Fabricate test JJ arrays, resonators, and transmons; correlate qubit metrics (T₁, T₂, Ic spread) with measured microstructure and interface chemistry.
- Design Rules and Process Map: Build deposition–microstructure–performance correlations to guide reproducible, scalable JJ fabrication.