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machine learning enhanced Ab Initio Mesoscale electrochemical Simulator

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machine learning enhanced Ab Initio Mesoscale electrochemical Simulator The transition to a sustainable energy future depends on advanced electrochemical technologies such as batteries and fuel cells. However, the development of critical materials and interfaces for these devices is often hindered by a laborious and resource-intensive cycle of experimental trial-and-error. While a paradigm shift towards in silico rational design is underway, a significant gap persists in modeling these electrochemical interfaces at the mesoscale (1-100 nm) with predictive accuracy. Current computational methods are either too slow for this scale, like atomistic simulations, or too inaccurate, like continuum models. The AIMS project will bridge this critical gap by developing a novel computational framework: the machine learning-enhanced Ab Initio Mesoscale electrochemical Simulator (AIMS). This framework

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recordType

award

status

SIGNED

region

EU

value

202125.12

unit

EUR