Prof. Dr. Christoph Brabec

Institute Materials for Electronics and Energy Technology (i-MEET)

High-efficiency and air-stable P3HT-based polymer solar cells with a new non-fullerene acceptor (2016) Holliday S, Ashraf RS, Wadsworth A, Baran D, Yousaf SA, Nielsen CB, Tan CH, et al. Journal article, Original article Performance of a Module and Defect Detection Algorithm for Aerial Infrared Images as a Function of the Flying Altitude (2016) Dalsaß M, Deitsch S, Luchscheider P, Gallwitz F, Brabec C Conference contribution, Conference Contribution Highly efficient, large area, roll coated flexible and rigid solar modules: Design rules and realization (2016) Lucera L, Machui F, Kubis P, Egelhaaf HJ, Brabec C Conference contribution, Conference Contribution Non-Stationary Outdoor EL-Measurements with a Fast and Highly Sensitive InGaAs Camera (2016) Adams J, Doll B, Buerhop-Lutz C, Pickel T, Teubner J, Camus C, Brabec C Conference contribution, Conference Contribution Failure classification of defective PV Modules based on maximum power point analysis (2016) Fecher F, Pickel T, Buerhop-Lutz C, Camus C, Brabec C Conference contribution, Conference Contribution Non-Uniformity Measurements of a Steady State Solar Simulator Using the Hishikawa-Hashimoto Method and Subsequent Improvement (2016) Doll B, Hoyer U, Hofer M, Pickel T, Buerhop-Lutz C, Camus C, Hauch J, Brabec C Conference contribution, Conference Contribution Time-dependent morphology evolution of solution-processed small molecule solar cells during solvent vapor annealing (2016) Min J, Jiao X, Ata I, Osvet A, Ameri T, Baeuerle P, Ade H, Brabec C Journal article, Original article Coloring Semitransparent Perovskite Solar Cells via Dielectric Mirrors (2016) Ramírez Quiroz CO, Bronnbauer C, Levchuk I, Hou Y, Brabec C, Forberich K Journal article, Original article Automatic Detection and Analysis of Photovoltaic Modules in Aerial Infrared Imagery (2016) Dotenco S, Dalsaß M, Winkler L, Wurzner T, Brabec C, Maier A, Gallwitz F Conference contribution, Conference Contribution Combined Computational Approach Based on Density Functional Theory and Artificial Neural Networks for Predicting the Solubility Parameters of Fullerenes (2016) Perea Ospina JD, Langner S, Salvador MF, Kontos J, Jarvas G, Winkler F, Machui F, et al. Journal article, Original article