Project description
China and Europe join forces for CO2-neutral production of polymer building blocks
Olefins are a class of industrially important hydrocarbons, including ethylene, propylene and butylene, that are widely used as chemical feedstocks to produce plastics and as chemical intermediates for polymers and specialty chemicals. Conventionally, they are produced from petroleum refining and natural gas processing. The EU-funded OPTIMAL project will significantly enhance the sustainability of olefin production while strengthening Sino-European ties. The collaboration between the EU and China will harness Big Data and AI to develop technology enabling the capture and use of CO2 to produce olefins in a CO2-neutral production process.
Objective
The proposed project is to develop and maintain long term collaborations between Europe and China towards CO2 neutral Olefin production. We will realize this objective by carrying out joint research in big data and artificial intelligence (AI) for ethylene plants integrated with carbon capture and CO2 utilisation. Specifically this requires a universal set of skills such as pilot scale experimental study, process modelling and analysis, optimisation, catalysis and reaction kinetics that will be strengthened by the individual mobility of researchers between Europe and China. There are 12 partners involved in OPTIMAL with 3 industrial partners. These partners are world leading in their respective research areas. OPTIMAL is planned to start from Aug. 2021 and will continue for 65 months. There will be 28 experienced and 35 early stage researchers participating in OPTIMAL with exchange visits of 262 person months. The funding of €772,800 will be requested from European Commission to support these planned secondments. The European beneficiaries are experts at catalysis, CO2 utilisation, intensified carbon capture, reaction mechanism and kinetics & CFD studies, hybrid modelling, molecular simulation and dynamic optimisation, whilst the Chinese partners are experts at exergy analysis, process control and optimisation, solvent-based carbon capture & data-driven model development, deep reinforced learning based model free control, intelligent predictive control, physics-based reduced order model development, soft exergy sensor development and optimisation under uncertainty. Transfer of knowledge will take place through these exchange visits. We will generate at least 25 Journal publications and 25 Conference papers. 2 Special Issues will be established in leading journals such as Applied Energy. 2 Workshops and 2 Special Sessions in major international conferences will also be organised to disseminate project results.
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 data science big data
- engineering and technology electrical engineering, electronic engineering, information engineering electronic engineering sensors
- natural sciences chemical sciences catalysis
- natural sciences chemical sciences organic chemistry aliphatic compounds
- 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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H2020-EU.1.3. - EXCELLENT SCIENCE - Marie Skłodowska-Curie Actions
MAIN PROGRAMME
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H2020-EU.1.3.3. - Stimulating innovation by means of cross-fertilisation of knowledge
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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.
MSCA-RISE - Marie Skłodowska-Curie Research and Innovation Staff Exchange (RISE)
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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) H2020-MSCA-RISE-2020
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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.
S10 2TN SHEFFIELD
United Kingdom
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.