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首页> 外文期刊>ACS Omega >Do HOMO–LUMO Energy Levels and Band Gaps Provide Sufficient Understanding of Dye-Sensitizer Activity Trends for Water Purification?
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Do HOMO–LUMO Energy Levels and Band Gaps Provide Sufficient Understanding of Dye-Sensitizer Activity Trends for Water Purification?

机译:HOMO-LUMO能量水平和带隙提供足够了解染料敏化剂的净水趋势吗?

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A dye-sensitized solar cell assembly can be used to harvest solar energy, while suitable dye sensitizers can be used to purify water. Here, we characterized the activity trends of four dye sensitizers, namely, PORPC-1, PORPC-2, PORPC-3, and PORPC-4, for water purification applications using density functional theory (DFT) with the Perdew–Burke–Ernzerhof (PBE), B3LYP, and PBE0 functionals, ΔSCF, time-dependent DFT (TD-DFT), and quasiparticle Green’s function (GW ) methods. The energy levels of the highest occupied molecular orbitals (HOMOs) and lowest unoccupied molecular orbitals (LUMOs) were calculated using gas-phase and aqueous-phase methods in order to understand charge-injection abilities and the dye regeneration processes. PBE, B3LYP, PBE0, and TD-DFT methods failed to predict PORPC-4 to be the best sensitizer, while PORPC-2 and PORPC-4 were predicted to be the best sensitizers using ΔSCF coupled with the implicit solvation method, and HOMO–LUMO energies were corrected for the aqueous environment in the GW calculations. However, none of these methods accurately predicted the performance trend of all four dye sensitizers. Consequently, we used the aggregation assembly patterns of the dye molecules in an aqueous environment to further probe the activity trends and found that PORPC-3 and PORPC-4 prefer J -aggregated assembly patterns, whereas PROPC-1 and PORPC-2 prefer to be H -aggregated. Therefore, the performance of these dye molecules can be determined by combining HOMO–LUMO energy levels with aggregate-assembly patterns, with the activity trend predicted to be PORPC-4 > PORPC-2 > PORPC-3 > PORPC-1, which is in good agreement with experimental findings.
机译:染料敏化的太阳能电池组件可用于收获太阳能,而合适的染料敏化剂可用于净化水。在此,我们的特征在于使用密度泛函理论(DFT)与PERDEW-Burke-Ernzerhof( PBE),B3LYP和PBE0功能,ΔSCF,时间依赖DFT(TD-DFT)和Quasiply Green的功能( GW)方法。使用气相和水相方法计算最高占用的分子轨道(HOMOS)和最低未占用的分子轨道(LUMOS)的能量水平,以了解电荷注射能力和染料再生过程。 PBE,B3LYP,PBE0和TD-DFT方法未能将PORPC-4预测为最佳敏感剂,而PORPC-2和PORPC-4预计是使用ΔSCF与隐式溶剂化方法耦合的最佳敏感剂,以及同性恋Lumo Energies在 GW计算中校正了水性环境。然而,这些方法都没有准确地预测所有四种染料敏感剂的性能趋势。因此,我们在含水环境中使用染料分子的聚集组件图案进一步探测活动趋势,并发现Porpc-3和Porpc-4更喜欢j-gregated组装图案,而propc-1和porpc-2喜欢 H-Aggregated。因此,通过将Homo-Lumo能量水平与聚集组件图案组合来确定这些染料分子的性能,预测为Porpc-4> Porpc-2> Porpc-3> Porpc-1的活动趋势与实验结果吻合良好。

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