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The CORENET project has developed a fully automated chemical computing platform that uses networks of chemical reactions to process information, enabling chemical computers to operate continuously and generate large volumes of experimental data.
Using reservoir computing methods, CORENET has demonstrated that reaction networks can perform logic operations and machine-learning tasks, in some cases matching or surpassing conventional electronic models in efficiency. These results represent a first step toward scalable, low-energy computing based on chemistry rather than silicon, providing a novel experimental platform for research in systems chemistry, complexity science, biomedicine, and food technology.
The platform is open for collaboration, allowing other researchers to explore chemical computation, test new reaction networks, and co-develop applications for energy-efficient computing.
Addressing target audiences and expressing needs
- Help in technical expertise
- Use of research Infrastructure
- Collaboration
We are looking to collaborate with researchers, laboratories, and academic groups with expertise in chemical reaction networks, microfluidics, automation and reservoir computing.
- Other Actors who can help us fulfil our market potential
- Research and Technology Organisations
- Academia/ Universities
R&D, Technology and Innovation aspects
CORENET is at TRL 4 – lab validated chemical computing. The automated platform performs logic and machine-learning tasks via chemical reactions. Next steps include scaling, optimizing, and testing in representative environments (TRL 5–6). We seek funding and collaboration with investors, research institutions, and industry partners.
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Value Proposition:
CORENET develops a fully automated chemical computing platform where reaction networks perform logic and machine-learning tasks with low energy consumption. It offers researchers and investors a novel, scalable, sustainable computing paradigm and a platform for collaboration, experimentation, and early-stage technological impact.
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Adress:
MADRID
Community of Madrid
28006
Spain
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