| Title |
Smart tools for optimizing dye loading in efficient DSSCs: hybrid ANN-MOGA strategy |
| Authors |
Hosseinnezhad, Mozhgan ; Mahmoudi Nahavandi, Alireza ; Nasiri, Sohrab |
| DOI |
10.3390/chemengineering10060072 |
| Full Text |
|
| Is Part of |
ChemEngineering.. Basel : MDPI. 2026, vol. 10, iss. 6, art. no. 72, p. 1-15.. ISSN 2305-7084 |
| Keywords [eng] |
durability ; dye-sensitized solar cells ; efficiency ; machine learning simulation ; photosensitizers |
| Abstract [eng] |
The production of sustainable and cost-effective energy remains a global challenge, with photovoltaic technology emerging as a promising solution. Sensitizers play a key role in electron production in dye-sensitized solar cells, which are emerging photovoltaic devices; thus, different chemical structures have been introduced to achieve the best results. Determining the optimal conditions for the coating and application of dye materials to obtain optimal efficiency and performance is of great importance. For this purpose, an organometallic dye was used to extract the optimal coating conditions. Two factors—ambient temperature during photoanode preparation and anti-aggregation agent concentration—were selected as effective parameters, and the optimal conditions for achieving high efficiency and durability were determined using machine learning. Finally, the findings were analyzed from two perspectives: the preparation of laboratory devices using the selected dye and the evaluation of similar dye materials to validate the proposed optimal conditions. |
| Published |
Basel : MDPI |
| Type |
Journal article |
| Language |
English |
| Publication date |
2026 |
| CC license |
|
