Periodic Reporting for period 2 - CompBat (Computer aided desing for next generation flow batteries)
Berichtszeitraum: 2021-08-01 bis 2023-05-31
The electrical energy storage is the key problem to be solved to realize green transition in electricity generation. Extensive storage capacity will be required to balance the fluctuating nature of green energy sources. Flow batteries offer promise for large scale energy storage, but technology still remains too expensive. Affordable flow batteries based on renewable or abundant raw materials are urgently needed. The potential energy storage materials 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.
CompBat focused on developing tools for discovery of new prospective candidates for next generation flow batteries, based on machine learning assisted high-throughput screening. Quantum chemical calculations were used to obtain data on redox potentials of different molecules, and machine learning methods were used to develop high-throughput screening tools, followed by experimental validation. A web-based tool allowing prediction of redox potentials of molecules undergoing one electron reduction based on structure was developed. Additionally, machine learning methods for predicting scheme of squares properties (redox potentials, energy of proton coupled electron transfer and protonation) of molecules undergoing proton and electron transfer, such as quinones, were developed. Stability and reversibility of the molecules was investigated by quantum chemical calculation and experimental investigations for a selected group of interesting molecules. This allowed better understanding of why some of the molecules synthesized in CompBat turned out to be unstable. Numerical modelling of flow battery systems was performed with finite element method, and with more general zero-dimensional models based on mass-transfer coefficients. The models were verified experimentally, and the models allowed prediction of the flow battery cell performance based on properties of the prospective candidates. This data was used then to predict the flow battery system performance from the stack level modelling. Cost estimation tools were then adapted to estimate the system performance also in terms of cost.
CompBat focused on developing tools for discovery of new prospective candidates for next generation flow batteries, based on machine learning assisted high-throughput screening. Quantum chemical calculations were used to obtain data on redox potentials of different molecules, and machine learning methods were used to develop high-throughput screening tools, followed by experimental validation. A web-based tool allowing prediction of redox potentials of molecules undergoing one electron reduction based on structure was developed. Additionally, machine learning methods for predicting scheme of squares properties (redox potentials, energy of proton coupled electron transfer and protonation) of molecules undergoing proton and electron transfer, such as quinones, were developed. Stability and reversibility of the molecules was investigated by quantum chemical calculation and experimental investigations for a selected group of interesting molecules. This allowed better understanding of why some of the molecules synthesized in CompBat turned out to be unstable. Numerical modelling of flow battery systems was performed with finite element method, and with more general zero-dimensional models based on mass-transfer coefficients. The models were verified experimentally, and the models allowed prediction of the flow battery cell performance based on properties of the prospective candidates. This data was used then to predict the flow battery system performance from the stack level modelling. Cost estimation tools were then adapted to estimate the system performance also in terms of cost.
CompBat project has:
1) Developed tools for identifying suitable redox pairs and electrolyte chemistries for low-cost, high-efficiency and sustainable stationary flow battery 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, 8000 structurally diverse organic molecules, and ca. 8200 molecules derived via the combination of quinone frameworks and different substituents. Machine learning was employed to screen > 300 000 molecules. Experimental evaluation has been performed for 20 synthesized molecules.
(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.
These new results have been exploited to generate new research projects, and have been disseminated in several scientific publications, meetings and workshops, as well as in Twitter and LikedIn.
1) Developed tools for identifying suitable redox pairs and electrolyte chemistries for low-cost, high-efficiency and sustainable stationary flow battery 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, 8000 structurally diverse organic molecules, and ca. 8200 molecules derived via the combination of quinone frameworks and different substituents. Machine learning was employed to screen > 300 000 molecules. Experimental evaluation has been performed for 20 synthesized molecules.
(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.
These new results have been exploited to generate new research projects, and have been disseminated in several scientific publications, meetings and workshops, as well as in Twitter and LikedIn.
To go beyond the state-of-the-art, CompBat has developed 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 was used to develop a tool to allow prediction of redox potentials of any organic molecule. This tool will be beneficial to all researchers working on flow batteries, and also in other fields where estimation of redox potentials is of crucial interest. The tools developed in CompBat will allow accelerated computation aided design of new molecules to further improve the 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 proposed two approaches to address this challenge: focus on bio-inspired molecules and solid boosters. We proposed 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 could 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 techno-economic modelling has highlighted that sufficient cell performance is required to achieve low cost. Especially cell voltage and solubility of the materials are crucial, as otherwise system costs for power becomes prohibitive even when employing low cost solid boosters.
The project has provided 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 flow battery 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 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 flow battery 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.
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 proposed two approaches to address this challenge: focus on bio-inspired molecules and solid boosters. We proposed 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 could 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 techno-economic modelling has highlighted that sufficient cell performance is required to achieve low cost. Especially cell voltage and solubility of the materials are crucial, as otherwise system costs for power becomes prohibitive even when employing low cost solid boosters.
The project has provided 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 flow battery 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 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 flow battery 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.