Periodic Reporting for period 1 - CompBat (Computer aided desing for next generation flow batteries) Reporting period: 2020-02-01 to 2021-07-31 Summary of the context and overall objectives of the project The electrical energy storage is the key problem to be solved to realize green transition in electricity generation. The transition to low-carbon economy, or hydrogen-based economy, will require extensive storage capacity to balance the fluctuating nature of green energy sources (e.g. wind and solar). Redox flow batteries (RFBs) offer promise for large scale energy storage, but current technology still remains too expensive. Affordable RFBs based on renewable or abundant raw materials are urgently needed. The potential energy storage materials are chemicals that need to fulfil several criteria, including a reasonable high energy density, stability, and production at an affordable cost, but no such chemicals have been discovered yet.To contribute towards solving this problem, CompBat will focus on developing tools for discovery of new prospective candidates for next generation flow batteries, based on machine learning assisted high-throughput screening. Density functional theory calculations will be used to obtain data on solubilities and redox potentials of different molecules, and machine learning methods are used to develop high-throughput screening tools based on the obtained data. The results of the high-throughput screening are validated with experimental results. Target molecules will be bio-inspired organic compounds, as well as derivatives of the redox active specialty chemical already manufactured in bulk quantities.Stability and reversibility of the molecules will also be investigated by DFT calculation, experimental investigations and machine learning methods, for a selected group of interesting molecules.Numerical modelling of flow battery systems will be performed with finite element method, and with more general zero-dimensional models based on mass-transfer coefficients. The models will be verified experimentally, and the modelling will generate a data-set to allow prediction of the flow battery cell performance based on properties of the prospective candidates obtained from high-throughput screening. This data is used then to predict the flow battery system performance from the stack level modelling. Freely available cost estimation tools are then adapted to estimate the system performance also in terms of cost. This approach will allow prediction of the battery performance from molecular structure to cost.Furthermore, the concept of using solid boosters to enhance the battery capacity will be investigated by developing models to simulate the performance of such a systems, and validating the models experimentally with the candidates already reported in the literature. The models will allow evaluating the potential and performance limits of such batteries for stationary energy storage. Work performed from the beginning of the project to the end of the period covered by the report and main results achieved so far CompBat project has:1) Developed tools for identifying suitable redox pairs and electrolyte chemistries for low-cost, high-efficiency and sustainable stationary RFB systems. Specifically, CompBat has develop computational screening and machine learning tools to allow fast evaluation of redox potentials and solvation energies of prospective candidates. We have screened ca. 6000 bioinspired molecules based on vitamin B6 structure. Preliminary experimental evaluation has been performed for three synthesized molecules, that unfortunately turned out to be unstable. (2) Demonstrated numerical modelling over multiple scales, from molecular properties to single cell and stack level. Specifically, CompBat has developed finite element models with <10% deviation, and zero-dimensional models with < 5 % deviation from the experimental values. (3) Developed initial tools for modelling the solid boosters. Specifically, CompBat has started the to develop finite element models.These new results have been exploited to generate new research proposals, and have been disseminated in several scientific meetings and workshops, as well as in Twitter and LikedIn. Progress beyond the state of the art and expected potential impact (including the socio-economic impact and the wider societal implications of the project so far) To go beyond the state-of-the-art, CompBat is developing a comprehensive set of modelling tools to allow evaluating the performance of a prospective molecule in a flow battery, from basic physicochemical parameters to battery and stack performance all the way to the system cost. Furthermore, machine learning is used to find correlation between experimental and computational properties (redox potential and solvation energies) and computed descriptors (electronic and steric). This will allow accelerated computation aided design of new molecules to further improve the performance flow battery performance.One of the challenges of aqueous organic flow batteries is to identify inexpensive candidates for flow battery applications. Cost evaluations can be performed using common evaluation techniques developed for design of chemical plants, but this approach is time consuming and requires detailed knowledge of the synthesis route and the different unit operations etc. CompBat proposes two approaches to address this challenge: focus on bio-inspired molecules and solid boosters. We propose to use safe and inexpensive natural products, such as vitamins and amino acids as building blocks for aqueous flow battery materials operating close to neutral pH. The advantages of natural product-derived materials include: 1) scalable production in tanks by fermentation with reasonable cost, 2) inherent safety and expected biodegradability due to their biological origin and natural roles even in the human body, 3) solubility in water, and 4) high degree of functionalization, minimizing the need for synthetic steps to modify them. This will enable significant cost reduction for sustainable electrochemical energy storage. The solid boosters, on the other hand, can be manufactured from inexpensive and abundant raw materials. As the material is introduced into the flow battery solution tanks as beads composed only of the active material, conductive additive and binder, the extra cost will simply be the cost of the raw materials. The modelling tools developed in for the solid boosted systems will provide critical design parameters that are needed to be taken into account when choosing suitable boosters and organic materials.The project will provide new molecules and structures for energy storage, as well as tools to develop next generation materials. This will generate significant interest in research of both aqueous and non-aqueous RFB systems employing bioinspired molecules. More importantly, the project offers prediction tools to understand in detail which candidate molecules are the most promising for further study as redox mediators. The proposed approach for utilization of bioinspired molecules for renewable energy storage will be highly valuable for the scientific community, generating more research and pushing to improve the energy storage utilizing abundant materials. So far, the field of organic redox flow batteries has been driven by redox flow battery researchers, and especially the design of aqueous systems has received only little attention from the organic chemistry community. This project will help to change this. Furthermore, the synthetic chemistry required to access the RFB materials will have to be low-cost, sustainable, and allow access to end products that are highly water soluble. These requirements will, out of necessity, promote renewal in the field.The project will help in green transition in electricity generation, by accelerating the development of the stationary energy storage systems. CompBat logo
