Low-loss magnets for EV motors
Engineering magnet composition and electrical behaviour to suppress eddy-current heating without sacrificing bulk magnetic performance.
Materials • Mechanics • Energy
Materials Scientist & Research Associate
Engineering materials for more efficient electric machines — from intrinsically low-loss EV motor magnets to sustainable battery joining and microstructure-informed mechanics.
Current collaboration
LAYRR × University of Sheffield · Henry Royce Institute ICP · Next-generation magnets for reduced eddy-current losses in EV motors.
Read the announcement
Research Associate · University of Sheffield
About Me
Summary
I am a Research Associate at the University of Sheffield working at the intersection of materials design, energy systems and mechanics. My current work includes a £100k Henry Royce Institute Industrial Collaboration Programme with LAYRR to develop next-generation magnets that intrinsically suppress eddy-current losses in high-speed EV motors. The project combines atomic-scale composition design, LAYRR’s physical surface engineering and system-level modelling driven by real-world vehicle drive cycles.
Current project · EV motor efficiency
Engineering the magnet, not just managing the losses
High-speed motors generate circulating eddy currents in fluctuating magnetic fields. This collaboration aims to engineer the electrical behaviour of the magnet itself, reducing heat generation without sacrificing bulk magnetic performance — a potential route to smaller, lighter and more efficient EV motors.
Alongside this work, I design, produce and characterise novel solder alloys through the EPSRC-funded SURFACTANT project, developing flux-free, repairable and recyclable joints for multi-material EV battery assemblies.
Previous projects
- Mechanical Properties of Battery Materials — University of Sheffield, FutureCAT (Oct 2023 – Sep 2025). Mechanically characterised cathode materials using in‑situ nano‑indentation (Alemnis) and micro‑computed tomography to analyse 3D electrode microstructure, defect content and resilience; linked composition, cation‑ordering and electrochemical history to mechanical behaviour for next‑gen battery optimisation.
- LightForm: Crystal Plasticity for Warm Forming — University of Manchester (Nov 2022 – Oct 2023). Extended crystal plasticity in DAMASK, coupling with phase transformation and dynamic precipitation to better describe deformation during warm forming; advanced understanding of light‑alloy formability under industrially relevant conditions.
I hold a joint M.Tech–Ph.D. (IIT Kanpur). My interests span alloy design, advanced characterisation, micromechanics and computational materials, with a focus on sustainable manufacturing and energy applications.
What I work on
Research focus
My work connects processing, microstructure and mechanical response across experimental materials science and computational modelling.
Microstructure → properties
SEM/EBSD, XRD, tomography and mechanical testing to understand phase connectivity, texture and deformation.
Mechanics & data-driven analysis
Crystal plasticity, DAMASK, texture modelling and image-processing workflows for reproducible materials insight.
Experience
Timeline
Research Associate — Advanced Materials for Electrification
University of Sheffield • School of Chemical, Materials & Biological Engineering
Oct 2025 – Present
- Develop next-generation EV motor magnets with LAYRR to suppress eddy-current losses through intrinsic electrical-property design.
- Use system-level modelling and real-world drive-cycle data to establish target material profiles for high-speed motors.
- Design, produce and characterise novel solder alloys; evaluate flux-free joining for multi-material EV cells.
- Investigate wetting on laser‑textured substrates; develop laser‑assisted assembly/disassembly concepts.
- Plan work, coordinate partners, deliver reports, and lead publications.
Research Associate — Mechanical Properties of Battery Materials (FutureCAT)
University of Sheffield
Oct 2023 – Sep 2025
- In‑situ nano‑indentation (Alemnis) on pristine/cycled cathode particles; XCT for 3D microstructure & defects.
- Linked composition, cation ordering and electrochemical history to mechanical behaviour.
Postdoctoral Research Associate — LightForm
University of Manchester
Nov 2022 – Oct 2023
- Extended crystal plasticity models in DAMASK; coupled with phase transformation & dynamic precipitation.
- Improved description of warm‑forming deformation; insights for alloy processing routes.
Selected Publications
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Reading the public ORCID record.
From the research archive
Featured work
A few papers that represent the progression from alloy processing and texture to automated microstructure analysis.
2026 · Liquid-phase sintering
Matrix content, stereology & mechanical behaviour in W–Ni–Fe alloys
How pre-sintering and matrix content influence densification, connectivity, grain growth and tensile response.
View DOI2026 · Image processing
Automated quantification of dihedral angles
A reproducible workflow for measuring grain-junction geometry across large tungsten heavy alloy image datasets.
View DOI2024 · Crystal plasticity
Taylor factor & work hardening in DAMASK
Linking micromechanical Taylor factors with work-hardening parameters through FFT-based simulations.
View DOIHow I work
Capabilities
An end-to-end materials research toolkit spanning alloy processing, advanced characterisation, computational mechanics and reproducible scientific computing.
Processing → structure → properties
Experimental ↔ computational
Energy & structural materials
Materials engineering
Design & processing
Developing compositions and processing routes around performance, manufacturability and sustainability targets.
- Alloy design
- Solder development
- Vacuum melting
- Powder metallurgy
- Liquid-phase sintering
- Wetting & surface interactions
Experimental science
Characterisation & mechanics
Resolving microstructure, texture, defects and phase-level deformation across length scales.
- SEM / EBSD
- X-ray diffraction
- X-ray tomography
- Neutron diffraction
- Nano-indentation
- Mechanical testing
Computational materials
Modelling & quantitative analysis
Connecting grain-scale mechanisms with macroscopic response through physics-based and data-driven workflows.
- Crystal plasticity
- DAMASK / FFT
- Texture modelling
- Dream.3D
- Image processing
- Statistical data analysis
Research infrastructure
Scientific computing & delivery
Building auditable analysis workflows and translating results into publications, reports and partner decisions.
- Python & MATLAB
- Fortran & C++
- Wolfram Mathematica
- Git & GitHub
- Technical writing
- Project coordination
Small tools, useful workflows
Tools
A growing collection of lightweight tools I build for research and everyday technical work.
Writing utility
ChatGPT → Markdown Converter
Clean copied ChatGPT conversations, preserve code, convert math, simplify citations, and download a ready-to-use Markdown file.
Math modesCode-safeNo upload
Get in Touch
Open to collaborations and new research opportunities.