Impact of Nitrogen Configuration on the Electronic Properties of Tailored Triphenilamine Derivatives as Hole Transport Materials for Perovskite Solar Cells: A Computational Chemistry Study
Abstract
Physical properties associated with charge transfer processes of tailored triphenylamine derivative molecules, generated from six nitrogen-containing heterocyclic aromatic cores (nTPAM), were theoretically studied. The conformer-rotamer ensemble sampling tool (CREST) was employed to study the geometric arrangements of n-TPAM monomers and dimers. Essential chemical parameters, such as reorganisation energies, spin densities, and chemical reactivity, were computed utilising the M06, 𝜔B97X, and 𝜔B97X-3c DFT functionals. The 𝜔 parameter of the 𝜔B97X-3c functional was optimised through a non-empirical tuning method. Time-dependent DFT (TD-DFT-M06/6-31G(d,p)) computations yielded insights into the maximum absorption wavelength and transition density matrix of n-TPAM monomers. The electronic coupling between dimers was assessed using M06 and 𝜔B97X. The HOMO energy levels of the n-TPAM derivatives correspond with the perovskite conduction band, situated between YZ22 and SpiroOMeTAD hole transport materials (HTM). n-TPAM molecules demonstrated enhanced electronic coupling for hole transfer, except for C-TPAM (Jeff(h) = 52.3 meV), in contrast to YZ22 (Jeff(h) = 79.5 meV). Nonetheless, n-TPAM exhibited elevated reorganisation energies, varying from 291 to 346 meV, compared to YZ22 (150 meV). Among the analysed derivatives, A-TPAM exhibited the highest chemical hardness and was the only molecule with absorption extending beyond the visible spectrum, as forecasted by TD-DFT. Although A-TPAM exhibited superior electronic properties, its high reorganisation energy may limit its performance as HTM compared to YZ22. Our analysis revealed that the electronic properties relevant to the hole extraction process can be tuned by modifying the nitrogen core configuration. Additionally, the degree of charge delocalisation in cationic compounds significantly influences charge transfer rates; therefore, an optimised DFT functional that effectively represents charge delocalisation is crucial for anticipating accurate trends in physical characteristics.