Desenvolvimento de modelos para descrição da eficiência de celulas voltaícas sensibilizadas por trifenilaminas

• Ano de defesa: 2022
• Autor(a) principal: Freitas Junior, José Amilton Freire
• Orientador(a): Costa Junior, Nivan Bezerra da
• Tipo de documento: Dissertação
• Tipo de acesso: Acesso aberto
• Idioma: por
• Programa de Pós-Graduação: Pós-Graduação em Química
• Palavras-chave em Português: Química; Relações quantitativas de propriedade estrutura (QSPR); Célula solar; Corantes orgânicos; Células solares sensibilizadas por corante (DSSCs); Descritores moleculares; Modelos estatísticos; Quantitative structure property relationships (QSPR)
• Palavras-chave em Inglês: Solar cell; Organic dyes; Dye sensitized solar cel (DSSCs); Molecular descriptors; Statistical models
• Área do conhecimento CNPq: CIENCIAS EXATAS E DA TERRA::QUIMICA
• Link de acesso: https://ri.ufs.br/jspui/handle/riufs/15660

The consumption of electric energy in the world has grown about 2.2% above the average in recent years, with fossil fuels being one of the main sources, with this simultaneously growing concern about global warming. Among the new ways to produce energy in a cleaner way, the use of solar panels has great prominence, but traditional panels have a high cost, making their mass production impossible. Dye-sensitized solar cells (DSSC) have become a viable alternative and environmental concerns motivate the search for metal-free sensitizers. However, metal-free DSSCs have a moderate efficiency in converting solar energy into electrical energy. Several works sought more efficient sensitizers, modifying the donor, electron acceptor or π bridge. There are enough data in the literature to help understand the relationship between the molecular properties of sensitizers and the energy conversion efficiency of DSSC. In this context, the present work applied statistical methods to relate molecular descriptors with cell quantum yield. Molecular descriptors were calculated using electronic structure methods both in the ground state and in the excited state. Classical methods were also used to obtain classical descriptors. The set of sensitizers was randomly divided into two sets: the training set with 50 dyes and the test set with 25 dyes, where the choice was made randomly for each after performing the hierarchical grouping and using the Stepwise and PLS technique we developed 4 models. The training set was initially used to determine the model and the test set was used to evaluate the models. After choosing the 4 models, they were validated, using another set of 24 different dyes. Since the models were found and validated, the last step is to use the model developed to propose new sensitizers with higher quantum yields in photovoltaic efficiency.