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Machine-Learning Enabled Discovery of Advanced Low-Temperature Proton Conducting Perovskites Oxides

Project description

More resilient materials for hydrogen technologies

Developing efficient hydrogen technologies depends on the ability to find solid electrolytes that can conduct protons effectively at high temperatures (300-400 degrees Celsius), resist degradation from CO2, and steam and minimise electronic leakage. Supported by the Marie Skłodowska-Curie Actions programme, the MEDAL-PCP project aims to identify perovskite oxides that meet these demands. These materials must achieve at least 10 mS cm-1 proton conductivity and remain stable for over 100 hours. To achieve this, researchers will use a physics-informed machine learning model to predict proton movement and electronic conduction. Synthesisable batches will be created using a robotic slurry-to-pellet line and will be screened to test their purity using X-ray diffraction. Finally, the materials will be validated in ceramic fuel cells to ensure reproducible performance.

Objective

Hydrogen technologies need solid electrolytes that conduct protons efficiently at 300-400 degrees Celsius, resist carbon dioxide and steam, and show minimal electronic leakage. This project will discover and validate such perovskite oxides and demonstrate device-level performance. Objectives: (1) identify electrolyte compositions that achieve at least 10 mS cm-1 proton conductivity at 300-400 degrees Celsius, with stability for at least 100 hours in humid carbon dioxide and low electronic leakage; (2) prove performance in button-cell proton-conducting ceramic fuel cells with reproducible area-specific resistance and peak power; (3) release open, reusable datasets, analysis code, and standard operating procedures. Approach: a physics-informed machine learning model estimates mobile-proton population and hydration thermodynamics and maps them to proton conductivity; a parallel branch predicts electronic conduction to cap leakage. Active learning and a planned design-of-experiments schedule propose synthesizable batches. A robotic slurry-to-pellet line produces and gates single-phase materials by X-ray diffraction. Condition-matched measurements include impedance with hydrogen versus deuterium checks, thermogravimetry with van t Hoff fits, oxygen-pressure sweeps for leakage, and stability tests in humid carbon dioxide. Device tests verify ohmic consistency and reproducibility. Relevance: the work advances clean-energy materials while delivering excellent training in data-driven materials discovery, electrochemistry, open science, and research management, aligned with the MSCA Postdoctoral Fellowships work programme.

Fields of science (EuroSciVoc)

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Programme(s)

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Topic(s)

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Funding Scheme

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HORIZON-TMA-MSCA-PF-EF - HORIZON TMA MSCA Postdoctoral Fellowships - European Fellowships

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Call for proposal

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(opens in new window) HORIZON-MSCA-2025-PF

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Coordinator

THE UNIVERSITY OF LIVERPOOL
Net EU contribution

Net EU financial contribution. The sum of money that the participant receives, deducted by the EU contribution to its linked third party. It considers the distribution of the EU financial contribution between direct beneficiaries of the project and other types of participants, like third-party participants.

€ 276 187,92
Address
BROWNLOW HILL 765 FOUNDATION BUILDING
L69 7ZX LIVERPOOL
United Kingdom

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Region
North West (England) Merseyside Liverpool
Activity type
Higher or Secondary Education Establishments
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Total cost

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