Fluxim AG 3/30/26 Fluxim AG 3/30/26

Research Paper — AI-driven parameter extraction in perovskite solar cells

Jonas Diekmann, Zitong Yang, Nurlan Tokmoldin, Ziwei Liu, Francisco Peña-Camargo, Zhuofan Xiong, Paria Forozi Sowmeeh, Hongsheng Li, Qiuqiang Kong, Xiaoliang Ju, Felix Lang, Safa Shoaee, Dieter Neher, and Martin Stolterfoht

ACS Energy Letters 0, 0, pp

Fluxim AG 3/30/26 Fluxim AG 3/30/26

Research Paper — Machine learning unlocks impedance analysis for perovskite solar cells

Nabil, M., Grau, I., Grau-Crespo, R., Hamad, S., & Anta, J. A. (2026). Inversion of the impedance response towards physical parameter extraction using interpretable machine learning. Advanced Energy Materials.

Fluxim AG 10/18/25 Fluxim AG 10/18/25

Research Paper:Non-Invasive Composition Identification in Organic Solar Cells via Deep Learning

Chang, Y.-H.; Zhang, Y.-L.; Cheng, C.-H.; Wu, S.-H.; Li, C.-H.; Liao, S.-Y.; Tseng, Z.-C.; Lin, M.-Y.; Huang, C.-Y. (2025), Non-Invasive Composition Identification in Organic Solar Cells via Deep Learning. Nanomaterials, 15, 1112.