%0 Journal Article %1 Lee2019 %A Lee, Min-Husan %D 2019 %I Wiley %J Advanced Energy Materials %K organic %P 1900891 %R 10.1002/aenm.201900891 %T Insights from Machine Learning Techniques for Predicting the Efficiency of Fullerene Derivatives-Based Ternary Organic Solar Cells at Ternary Blend Design %U https://doi.org/10.1002/aenm.201900891

@article{Lee2019, added-at = {2019-08-05T14:47:09.000+0200}, author = {Lee, Min-Husan}, biburl = {https://www.bibsonomy.org/bibtex/26efde55a005988afb4abaa350913e33a/woepps}, doi = {10.1002/aenm.201900891}, interhash = {290e0b7c0d1ca0ef9c5973f04d901614}, intrahash = {6efde55a005988afb4abaa350913e33a}, journal = {Advanced Energy Materials}, keywords = {organic}, month = jun, pages = 1900891, publisher = {Wiley}, timestamp = {2019-08-05T14:47:09.000+0200}, title = {Insights from Machine Learning Techniques for Predicting the Efficiency of Fullerene Derivatives-Based Ternary Organic Solar Cells at Ternary Blend Design}, url = {https://doi.org/10.1002/aenm.201900891}, year = 2019 }