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A novel membrane-free flow battery for renewable energy storage: Prototype Design by Simulation

   School of Computing, Engineering & the Built Environment

About the Project


Please select SCEBE-22SF-NMFFB-Chen from the drop-down list or add this to your proposal writeup.


The greatest challenge for renewable energy utilisation is the severe mismatch between energy demand and energy supply. Energy storage technologies is a promising way to address this challenge. Flow batteries, as a new large-scale energy storage method, have attracted increasing attention. The biggest problem for available flow battery prototypes is their high cost due to the expensive membranes inside them. It is urgent to develop novel membrane-free flow batteries to commercialise the flow battery technology. Accordingly, this PhD project deals with this critical issue for future large-scale energy storage systems. More specifically, the fundamental of heat and mass transfer are expected to be investigated by comprehensive simulation using CFD (computational fluid dynamics). The study is also expected to use machine learning to improve prediction. Based on such exploration, a novel flow battery prototype is expected to be designed and optimised.


In this research study, the candidate is expected to:

-       Conduct a literature review on flow batteries and recognise the challenges and gaps in large-scale energy storage.

-       Numerical simulation, data analysis, and ML/AI for developing an advanced online prediction platform.

-       Develop and validate a novel prototype of a membrane-free flow battery for energy storage, considering flow optimisation.


The candidate is expected to write a detailed proposal, not more than 2000 words, clearly stating how any of the points above can be executed.

The successful candidate has:

• The candidate needs a Master's Degree in relevant Engineering and Science subjects with numerical simulation skills.

• Knowledge of energy storage systems, fluid dynamics, heat & mass transfer and machine learning techniques.

• Strong mathematical, analytical, and programming skills using MATLAB and ANSYS FLUENT.

• Excellent communication skills in spoken and written English and teamwork skills.

• Creativity, positive attitude, and perseverance.

A bench fee of £4000 is required for attendance of relevant conferences and training.

Funding Notes

Applicants are expected to find external funding sources to cover the tuition fees and living expenses. Alumni and International students new to GCU who are self-funding are eligible for fee discounts.
Find out more on our Research Scholarships and Studentships webpage.


For further information, please contact the team as below. Please note that this is treated as an informal query, and not an official application. To be considered officially, you will need to apply via
For further queries, please contact
Director of Studies
Name: Dr. Sheng Chen
GCU Research Online URL:
Dr Sheng Chen is an experienced researcher in energy storage, renewable energy and numerical simulation. He has published more than 100 journal papers with H-index=31 (
2nd Supervisor
Name: Dr. Amit Kumar Jain
GCU Research Online URL:
3rd Supervisor
Name: Dr. Dharminder Singh
GCU Research Online URL:

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