| Project Detail |
Decoding the molecular mechanisms of organic conductive materials for health and energy applications
Organic materials as biological sensors, electrodes and memristive devices offer promising opportunities in medical diagnosis, treatment, energy storage and neuromorphic computing. These applications rely on organic mixed ionic-electronic conductors that convert ionic currents to electronic signals. However, the molecular mechanisms underpinning their properties remain elusive. Funded under the Marie Sklodowska-Curie Actions programme, the MIXCONDUCTORS project will characterise organic mixed ionic-electronic conductors using machine learning-enhanced multiscale simulations to uncover molecular mechanisms and identify material design guidelines. This approach should improve computational efficiency and help predict device-scale properties. By providing a comprehensive understanding of the properties of such materials, MIXCONDUCTORS should guide the development of advanced materials for health and sustainable energy solutions.
The promise of organic materials as biological sensors, electrodes, and memristive devices creates outstanding opportunities for medical diagnosis and treatment, energy storage, as well as neuromorphic computing. At the core of these applications are organic polymers that efficiently support both ionic and electronic transport and therefore are called organic mixed ionic-electronic conductors. These materials’ enabling feature is their ability to convert ionic currents into electronic signals, and vice versa. However, our understanding of these materials is incomplete and the molecular mechanisms underpinning their properties remain elusive. In MIXCONDUCTORS, I will describe and characterize mixed ionic-electronic conductors using machine learning-enhanced multiscale simulations to unravel molecular mechanisms and identify material design guidelines. I propose to use specific machine learning surrogate models to develop a new multiscale method with dramatically increased computational efficiency, unlocking the possibility of bottom-up simulations able to predict device-scale properties. The proposed multiscale method will be used to characterize in silico the growing library of organic mixed conductors, allowing me to uncover their common and/or unique strengths and discover material design guidelines. Finally, together with experimental collaborators, I will be in the position to unravel the molecular mechanisms underpinning some of mixed conductors’ unique properties, enabling me to formulate application-targeted material design guidelines. In summary, MIXCONDUCTORS will provide detailed and unprecedented understanding of the molecular mechanisms behind the functioning of emerging organic mixed ionic-electronic conductors, thereby informing the rational design of improved materials with ramifications for the development of devices that improve health and well-being and enable a future with clean and affordable energy. |
