Marina gave a talk " ML prediction of photoluminescence from high-throughput density functional theory ground state properties on the example of Cs2AgxNa1−xBiyIn1−yCl6" at the workshop in Erlangen. Lead-free halide double perovskites have been an emerging material class for various applications in ...
Stefan has successfully completed his PhD examination with distinction. His doctoral thesis, titled 'High-Throughput Experimentation in Organic Photovoltaics: Solubility, Ink-Formulation, and Films,' focuses on the measurement of Hansen parameters, going even beyond to propose ink design strategies...
Recent advancements in organic photovoltaics (OPVs) have propelled small-cell power conversion efficiencies (PCEs) close to 20%. However, transitioning these efficiencies from small cells to large-area modules remains challenging due to lower PCEs at the module level. This study focuses on the upsc...
The longevity and performance of perovskite solar cells (PSCs), essential for their commercial viability, are limited by the stability of their quasi-ohmic contacts, especially under elevated temperatures. Junsheng presents a pioneering approach to this challenge, introducing a polymer-acid-metal b...
Yicheng has developed machine learning model aimed at improving the stability of metal-halide perovskite solar cells. By employing spectral learning techniques, the team has made strides in predicting perovskite stability without the reliance on lengthy aging processes. With promising results achie...
As solar panels silently harness the sun's energy, behind the scenes, Artificial Intelligence is quietly ensuring their longevity and unwavering reliability.
Our "High-throughput characterisation and modelling for PV" team is at the forefront of research aiming to enhance the reliability of sol...
On sunny days, up to 60% of the electricity in Germany is produced by photovoltaics (PV). This is good news to fight climate change, but also entails problems such as the land use by large PV fields or the question of recycling. Addressing these issues requires to devise entirely new materials for ...
Researchers at i-MEET use hybrid (physics aware) artificial intelligence to learn more about photovoltaic materials from faster and simpler experiments. For example, we can obtain performance relevant aspects of microstructure by analysing simple absorption spectra.
In many cases, this helps us...
Jiyun has used fully automated SPINBOT platform for engineering solution-processed Perovskite thin films, addressing the persistent challenge of simultaneously optimizing processing parameters. SPINBOT employs unsupervised processing on hundreds of substrates, showcasing exceptional experimental co...
Larry, Marius, Vincent and Karen have explored multijunction devices and photon up-and-down conversion to enhance efficiency beyond single junction limits. Utilizing Bayesian Optimization in a simulation environment, our team predicts and optimizes the electrical performance of multi-junction archi...
