Periodic Reporting for period 1 - CORENET (Complex chemical reaction networks for breakthrough scalable reservoir computing)
Berichtszeitraum: 2022-04-01 bis 2023-03-31
Chemical synthesis has traditionally been a discipline that was part clever application of accumulated knowledge and part “art”. In recent years, a revolution has been gathering pace with the introduction of robotics, microfluidics, integrated analytics, and AI-based integration of data, leading to programmable synthesis of molecules using computer-controlled devices. This paradigm change opens up new opportunities to push chemistry beyond the synthesis of molecules to the synthesis of chemical reaction networks (CRNs), which in living organisms control all essential processes. CORENET aims at construct chemical systems that can perform high-level computation based on chemical reactions. The project will implement reservoir computing based on the compartmentalisation of reaction networks with increasing complexity in microfluidic flow reactors. The main advantage of CRNs for computing is that they are able to generate vast compositional chemical spaces, allowing them to process information and regulate their responses in a ‘metabolic’ way. The project will bring new knowledge bridging system chemistry, microfluidics technology and computational science and may revolutionize patient treatment via in situ synthesis of drug molecules.
The exploration of CRNs has started with the expansion of existing networks (e.g. the formose reaction) and combining chemical expertise and cheminformatics to design networks de novo (e.g. from the reactive prebiotic intermediate glyconitrile). The framework developed using the formose reaction as a model can be transferred to other reaction systems and the glyconitrile CRN reveal that it is very promising to produce a high diversity of chemical structures that can be accurately monitored over time. The consortium has made significant progress towards device fabrication, achieving the preparation of Si-based flow reactors with very high levels of control over stirring speed, temperature and flow rates. As the data-extraction method for the formose CRN has been enhanced, the consortium can now study the response of the CRN to a large range of input combinations, which can all be varied thanks to a script-based programming of the hardware.
CORENET will have a significant impact in various areas of systems chemistry, CRNs and reservoir computing (RC), and it has been progressing in line with the planned outcomes. Looking at the formose CRN, precise data, analysis and important new concepts in reaction pathway self-organization are of high relevance to the prebiotic chemistry community. The framework developed using the formose reaction as a model can be transferred to other CRNs, allowing the rationalisation of complex reaction outcomes and the inspiration of detailed hypotheses for origin of life scenarios that consider the dynamic and out-of-equilibrium properties of the prebiotic environment. With an established reservoir computing capacity of the formose CRN network, we can now demonstrate a range of complex non-linear classifications. The fabrication of integrated Si-based CSTRs has scientific impact as it allows for further integration and robust and reproducible data collection. The fabrication methods include possible patentable inventions with respect to embedding electrodes and heating elements.