Project description
Leveraging 2D materials and deep learning for sustainable energy solutions
The global energy challenge, driven by a steady increase in energy consumption per capita and a slow transition towards renewable energy sources, requires urgent attention. The EU is taking steps towards sustainable energy solutions, including renewable energy sources, energy-efficient technologies, and responsible consumption practices. To contribute to this effort, the AI4SPIN project, funded by the European Research Council, aims to develop ultra-low-power electronics using 2D materials and van der Waal heterostructures with optimised quantum properties. The project will leverage deep neural networks and quantum transport simulations to design a tool that computes spin-orbit torque efficiencies. The tool, based on deep neural networks and a computer-assisted structure optimiser, will pave the way for more sustainable and efficient energy solutions.
Objective
The steady increase in energy consumption per capita and the slow transition toward renewable energy sources is becoming a serious global problem, making energy efficiency paramount for new technologies. Two-dimensional materials offer an encouraging path toward ultra-low-power electronics due to our capability to combine them into Van der Waal heterostructures with tailored quantum properties based on their constituents. The spin-orbit torque (SOT) memories are technological prospects that consume a fraction of conventional memories' power. Still, they offer superior speed and storage capacity and were further improved when using 2D materials as building blocks instead of 3D metallic systems. Recently theoretical efforts demonstrated the existence of thousands of potentially synthesizable 2D materials, opening an exponentially larger pool to mine for optimized heterostructures which brute-force approaches cannot tackle. This project aims at developing artificial intelligence that will propose optimized Van der Waal heterostructures for spin-orbit torques. To this end, we will first construct an automatic material assessment (AUTOMATA) tool based on deep neural networks that will perform numerical modeling and quantum transport simulations autonomously to compute the spin-orbit torque efficiencies. In parallel, we will develop a computer-assisted structure (COMPASS) optimizer that will propose new systems for spin-orbit torques by using an evolutionary strategy. The AUTOMATA tool will rank the candidates generated by the COMPASS optimizer, and we will use those with superior performance to improve the COMPASS optimizer prediction. The successful combination of these tools will accelerate the development of technologies by automatizing the material selection phase through this quantum mechanical optimization process. Although we apply it to spin-orbit torques, it is, with little effort, generalizable to any electrical response functions.
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.1.1 - European Research Council (ERC)
MAIN PROGRAMME
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Topic(s)
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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-ERC - HORIZON ERC Grants
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Call for proposal
Procedure for inviting applicants to submit project proposals, with the aim of receiving EU funding.
Procedure for inviting applicants to submit project proposals, with the aim of receiving EU funding.
(opens in new window) ERC-2022-STG
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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.
08193 BELLATERRA (BARCELONA)
Spain
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.