具有环间隔剂的新型推挽染料(钛醇、铬、铁、镍和锌醇):DSSCs光电优化的DFT研究。

IF 2.1 4区 化学 Q4 BIOCHEMISTRY & MOLECULAR BIOLOGY
Mourad Zouaoui-Rabah, Abdelkader M Elhorri, Madani Hedidi, Hicham Mahdjoub-Araibi, Laib Assia, Mahammed Zenati
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引用次数: 0

摘要

背景:本计算研究深入探讨了染料敏化太阳能电池(DSSCs)双金属Zn/M有机金属D-π-A染料的策略设计,重点研究了过渡金属(Ti, Cr, Fe, Ni)如何调节光电行为和光伏性能。采用密度泛函理论(DFT)和时间相关DFT (TD-DFT)模拟,系统地评价了4种染料(Dye1-Dye4)在真空和四氢呋喃(THF)溶剂化下的光捕获效率(LHE)、电荷转移动力学和稳定性。结果强调了不同金属依赖的权衡:铬基染料(染料2)表现出出色的可见光吸收(λmax = 570 nm),具有高LHE(85%)和振荡器强度(f = 0.830),而镍基染料(染料4)表现出红移吸收(λmax = 609 nm)和延长的激发态寿命(τ = 1.55 ns),有利于电荷分离。钛(染料1)和铁(染料3)变体作为经济替代品出现,提供适度的效率和稳定性。THF溶剂化诱导明显的色移(染料1为+ 138 nm)和热力学上有利的相互作用(ΔGsolv 1),增强光吸收和稳定性。关键指标,如电子注入能量(ΔGinj),开路电压(Voc)和再生能量(ΔGreg)强调需要协调光学性能与电荷管理。该研究提倡染料2和染料4共敏,以协同拓宽光谱响应和提高功率转换效率。这些发现为可持续DSSCs利用地球上丰富的金属铺平了道路,与全球绿色能源创新倡议保持一致。方法:采用高斯16进行计算。利用B3LYP泛函对基态几何进行了DFT优化。过渡金属用LanL2DZ基集,非金属原子用6-31 + + G(d,p)基集。研究的溶剂化模型有CPCM(导体极化连续体)模型和SMD(溶剂化模型密度)模型。利用TD-DFT和CAM-B3LYP函数计算了激发态性质,以评估电子跃迁。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Novel push-pull dyes with cyclic ring spacers (titanol, chromol, ferrol, nickelol, and zinkol): a DFT study for optoelectronic optimization in DSSCs.

Context: This computational investigation delves into the strategic design of bimetallic Zn/M organometallic D-π-A dyes for dye-sensitized solar cells (DSSCs), with a focus on how transition metals (Ti, Cr, Fe, Ni) modulate optoelectronic behavior and photovoltaic performance. Employing density functional theory (DFT) and time-dependent DFT (TD-DFT) simulations, four dyes (Dye1-Dye4) were systematically evaluated for their light-harvesting efficiency (LHE), charge transfer kinetics, and stability under vacuum and tetrahydrofuran (THF) solvation. The results underscore distinct metal-dependent trade-offs: the chromium-based dye (Dye2) demonstrates outstanding visible-light absorption (λmax = 570 nm) with a high LHE (85%) and oscillator strength (f = 0.830), whereas the nickel-based dye (Dye4) exhibits redshifted absorption (λmax = 609 nm) and an extended excited-state lifetime (τ = 1.55 ns), advantageous for charge separation. Titanium (Dye1) and iron (Dye3) variants emerge as economical alternatives, offering moderate efficiency and stability. THF solvation induces pronounced bathochromic shifts (+ 138 nm for Dye1) and thermodynamically favorable interactions (ΔGsolv <  - 61 kcal·mol⁻1), enhancing light absorption and stability. Critical metrics such as electron injection energy (ΔGinj), open-circuit voltage (Voc), and regeneration energy (ΔGreg) emphasize the need to harmonize optical performance with charge management. The study advocates co-sensitization of Dye2 and Dye4 to synergistically broaden spectral response and boost power conversion efficiency. These findings pave the way for sustainable DSSCs leveraging earth-abundant metals, aligning with global initiatives for green energy innovation.

Method: All calculations were performed with Gaussian 16. Ground state geometries were optimized by DFT with the B3LYP functional. The LanL2DZ basis set was used for transition metals, while 6-31 +  + G(d,p) was used for non-metallic atoms. The solvation models studied are the CPCM (Conductor Polarizable Continuum) model and the SMD (Solvation Model Density) model. Excited state properties have been calculated using TD-DFT with the CAM-B3LYP functional to evaluate electronic transitions.

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来源期刊
Journal of Molecular Modeling
Journal of Molecular Modeling 化学-化学综合
CiteScore
3.50
自引率
4.50%
发文量
362
审稿时长
2.9 months
期刊介绍: The Journal of Molecular Modeling focuses on "hardcore" modeling, publishing high-quality research and reports. Founded in 1995 as a purely electronic journal, it has adapted its format to include a full-color print edition, and adjusted its aims and scope fit the fast-changing field of molecular modeling, with a particular focus on three-dimensional modeling. Today, the journal covers all aspects of molecular modeling including life science modeling; materials modeling; new methods; and computational chemistry. Topics include computer-aided molecular design; rational drug design, de novo ligand design, receptor modeling and docking; cheminformatics, data analysis, visualization and mining; computational medicinal chemistry; homology modeling; simulation of peptides, DNA and other biopolymers; quantitative structure-activity relationships (QSAR) and ADME-modeling; modeling of biological reaction mechanisms; and combined experimental and computational studies in which calculations play a major role.
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