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Data-driven Design of Molecular Spin Qubits for Quantum Information Science

Objective

DEMO-QIS aims to revolutionise the discovery of molecular spin qubits (MSQs) for quantum information science (QIS). QIS promises technologies ranging from advanced computing to detectors that sense atomic-scale signals in medicine, navigation, and beyond. Realising such breakthroughs requires qubits that are reliable, scalable, and long-lasting. MSQs offer unique advantages: bottom-up design, tunability through chemical modification, compatibility with device integration, and spin-state readout via optically detected magnetic resonance (ODMR). Progress requires two pathways: optimising key figures of merit (FoMs) such as ODMR contrast, photoluminescence (PL) intensity, and coherence time, and exploring new candidates within the vast chemical space. FoMs are interdependent; improving one may compromise another, making trial-and-error ineffective. Intuition-based exploration is inadequate given the vast space. DEMO-QIS will address these challenges by combining density functional theory (DFT) with machine learning (ML). Starting with pentacene derivatives, we first quantify the contrast and PL intensity, generate substitution datasets, and derive design rules. We expand to hydrocarbon databases with supervised ML, enhanced with fine-tuning and few-shot learning, while generative models propose de novo design candidates. The design space will be broadened through radical functionalisation to stabilise high-spin states and by optimising MSQ–host combinations to improve coherence. Finally, we will unify all steps into a transferable pipeline that integrates quantum simulations, predictive modelling, candidate retrieval, and generative design. DEMO-QIS will provide both a workflow for MSQ discovery and candidates for experimental validation. By redefining MSQ research, it will accelerate Europe’s progress in quantum technologies, establish transferable MSQ design methods, and promote interdisciplinary training at the interface of chemistry, physics, and data science.

Fields of science (EuroSciVoc)

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Keywords

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Programme(s)

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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.

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.

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

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Call for proposal

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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Coordinator

THE UNIVERSITY OF BIRMINGHAM
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.

€ 260 347,92
Address
Edgbaston
B15 2TT Birmingham
United Kingdom

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Region
West Midlands (England) West Midlands Birmingham
Activity type
Higher or Secondary Education Establishments
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Total cost

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.

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