Project description
A predictive method for designing better materials for ion capture
Cation-selective sorbents are designed to capture specific positively charged ions from mixtures, enabling water purification and recovery of valuable resources. Supported by the Marie Skłodowska-Curie Actions programme, the CLEANSE project aims to replace traditional trial-and-error material development with a predictive approach. Researchers will use machine-learning models trained on quantum-chemical data to understand why certain microporous frameworks selectively capture potassium from complex ion mixtures. A large database of candidate materials will be screened for capacity, selectivity and ion transport properties. The most promising candidates will be synthesised, structurally characterised and experimentally tested, with results continuously fed back to refine the models, creating an iterative loop that accelerates the rational design of next-generation ion-capture materials.
Objective
CLEANSE replaces the time-consuming, expensive, and error-prone trial-and-error approach for developing cation-selective sorbents with a predictive, iterative computation-to-experiment loop. First, we will resolve why sodium zirconium cyclosilicate (ZS-9) is highly selective for K+ by training equivariant machine-learning interatomic potentials (MLIPs) on ab initio data and running long (biased) molecular-dynamics simulations under realistic aqueous, multi-ion conditions. These models will also predict experimental observables such as solid-state NMR tensor and Born effective charges for effective NMR and IR spectral prediction. Second, we will perform high-throughput screening of broad synthesizable porous silicate databases, ranking candidates by adsorption capacity, competitive selectivity against Na+/NH4+/H3O+, and diffusion barriers to derive design rules for effective/selective K+ capture. The best candidates will be synthesised and evaluated in laboratory assays, then characterised by solid-state NMR, X-ray diffraction, vibrational spectroscopy and electron microscopy. Experimental results will feed back to refine the models and optimise composition and pore architecture. CLEANSE ensures two-way knowledge transfer between my expertise in advanced simulation and the host’s strengths in synthesis and advanced characterisation, and will generate open, reusable datasets, models and workflows. Outcomes enable data-driven design of ion-exchange materials across water treatment, resource recovery, food and medical applications, while advancing fundamental understanding of selective ion capture in porous silicates.
Fields of science (EuroSciVoc)
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques. See: The European Science Vocabulary.
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques. See: The European Science Vocabulary.
- natural sciences computer and information sciences databases
- natural sciences chemical sciences inorganic chemistry alkali metals
- natural sciences physical sciences optics microscopy
- natural sciences computer and information sciences artificial intelligence machine learning
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Keywords
Project’s keywords as indicated by the project coordinator. Not to be confused with the EuroSciVoc taxonomy (Fields of science)
Project’s keywords as indicated by the project coordinator. Not to be confused with the EuroSciVoc taxonomy (Fields of science)
Programme(s)
Multi-annual funding programmes that define the EU’s priorities for research and innovation.
Multi-annual funding programmes that define the EU’s priorities for research and innovation.
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HORIZON.1.2 - Marie Skłodowska-Curie Actions (MSCA)
MAIN PROGRAMME
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Topic(s)
Calls for proposals are divided into topics. A topic defines a specific subject or area for which applicants can submit proposals. The description of a topic comprises its specific scope and the expected impact of the funded project.
Calls for proposals are divided into topics. A topic defines a specific subject or area for which applicants can submit proposals. The description of a topic comprises its specific scope and the expected impact of the funded project.
Funding Scheme
Funding scheme (or “Type of Action”) inside a programme with common features. It specifies: the scope of what is funded; the reimbursement rate; specific evaluation criteria to qualify for funding; and the use of simplified forms of costs like lump sums.
Funding scheme (or “Type of Action”) inside a programme with common features. It specifies: the scope of what is funded; the reimbursement rate; specific evaluation criteria to qualify for funding; and the use of simplified forms of costs like lump sums.
HORIZON-TMA-MSCA-PF-EF - HORIZON TMA MSCA Postdoctoral Fellowships - European Fellowships
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Call for proposal
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Procedure for inviting applicants to submit project proposals, with the aim of receiving EU funding.
(opens in new window) HORIZON-MSCA-2025-PF
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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.
3810-193 Aveiro
Portugal
The total costs incurred by this organisation to participate in the project, including direct and indirect costs. This amount is a subset of the overall project budget.