A Danish research group works on an automated material discovery and performance optimization platform for perovskiet solar cells. The scientists claim a unique combination of robotics, advanced measuring equipment and machine learning.
Researchers from the University of southern Denmark are working on a new automated material discovery and optimization platform aimed at well-performing perovskite solar cells.
The automated system is intended to accelerate the development of perovskiet devices by manufacturing, modeling, modeling and optimizing the conflicting thin film and cell materials.
It will combine robotics, advanced measuring equipment and technologies for machine learning.
Go further than screening and goal discovery, it will collect and analyze experimental data in real -time to identify performance -reducing patterns, but also to perform device modeling and use methods for machine learning to quantify important material properties, such as mobility and defect densities.
“The aim is to identify the minimum number and types of characterisations that are necessary to fully determine the properties of all layers in a device stack,” said main investigator, Vincent Lecorre, said PV -Magazine. “Once we have determined that, we will use it to develop quantitative structure-character relationships, which links the chemical structure to physical properties.”
According to Lecorre Spinbot equipment from Germany-in-based sciprios, the project, Nealnchronized in reference to the fictional robot in the Hollywood Star Wars series. It is an adjustable research tool with high transit that can be programmed to manipulate objects, load multiple spin coaters, to mix and execute glow open and close to injection lacons, pipette fluids, mix-master solutions.
The Danish project is supported by a DKK 6 million ($ 935,800) Sapere Aude Grant of the Independent Research Fund Denmark.
“This project is a first step in a longer -term plan, whereby the focus will shift to generative AI for material discovery,” specified Lecorre.
Elsewhere, scientists use robotics and automation to accelerate research into emerging thin film solar cells, such as finding the best cargo transport layers or discovering new materials for perovskite solar cells or exposing new material combinations for high -quality organic solar cells.
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