All Outputs (2)

Enhanced Lifetime of organic photovoltaic diodes utilizing a ternary blend including an insulating polymer (2016)
Journal Article
AL-Busaidi, Z., Pearson, C., Groves, C., & Petty, M. (2016). Enhanced Lifetime of organic photovoltaic diodes utilizing a ternary blend including an insulating polymer. Solar Energy Materials and Solar Cells, 160, 101-106. https://doi.org/10.1016/j.solmat.2016.10.018

We report on the lifetime of unencapsulated organic photovoltaic diodes (OPVs) based on a ternary blend of poly(3-hexylthiophene) (P3HT), phenyl-C61-butyric acid methyl ester (PCBM) and a soft insulating polymer, poly(methyl methacrylate) (PMMA) as c... Read More about Enhanced Lifetime of organic photovoltaic diodes utilizing a ternary blend including an insulating polymer.

Training a Carbon-Nanotube/Liquid Crystal Data Classifier Using Evolutionary Algorithms (2016)
Presentation / Conference Contribution
Vissol-Gaudin, E., Kotsialos, A., Massey, M., Zeze, D., Pearson, C., Groves, C., & Petty, M. (2016, July). Training a Carbon-Nanotube/Liquid Crystal Data Classifier Using Evolutionary Algorithms. Presented at 15th International Conference on Unconventional Computation and Natural Computation, Manchester, UK

Evolution-in-Materio uses evolutionary algorithms (EA) to exploit the physical properties of unconfigured, physically rich materials, in effect transforming them into information processors. The potential of this technique for machine learning proble... Read More about Training a Carbon-Nanotube/Liquid Crystal Data Classifier Using Evolutionary Algorithms.