scholarly journals Glancing Angle Deposition Effect on Structure and Light-Induced Wettability of RF-Sputtered TiO2 Thin Films

Micromachines ◽  
2018 ◽  
Vol 9 (8) ◽  
pp. 389 ◽  
Author(s):  
Vasiliki Vrakatseli ◽  
Alexandros Kalarakis ◽  
Angelos Kalampounias ◽  
Eleftherios Amanatides ◽  
Dimitrios Mataras
Keyword(s):  
Solar Cells ◽  
Crystalline Phase ◽  
Perovskite Solar Cells ◽  
Dye Sensitized Solar Cells ◽  
Anatase Tio2 ◽  
High Rate ◽  
Tio2 Films ◽  
Working Pressure ◽  
Wetting Properties ◽  
Glancing Angle

Crystalline TiO2 films were prepared on unheated glass substrates by radio frequency (RF) reactive magnetron sputtering at normal angle of incidence (a = 0°) and at glancing angle (a = 87°). The effect of the glancing angle on the structure, microstructure, and wetting properties of the films was investigated. The inclination of the substrate led to phase transformation of the deposited films from rutile to either rutile/anatase or anatase, depending on the working pressure. Extreme shadowing at 87° results in a remarkable increase of the films’ porosity and surface roughness. The mechanism of the glancing-angle-induced crystalline phase formation is thoroughly discussed based on the thermodynamic, kinetic, and geometrical aspects of the nucleation and is related with the microstructural changes. Both crystalline phase and microstructure significantly affect the wetting properties of the TiO2 films. Glancing-angle-deposited anatase TiO2 exhibits a high degree of porosity and roughness, a high rate of UV-induced wettability conversion, and a long-term highly hydrophilic nature in dark. Therefore, anatase TiO2 is potentially a good candidate for applications as dye-sensitized solar cells (DSSC)/perovskite solar cells, microfluidic devices, and self-cleaning surfaces prepared on thermosensitive substrates.

Dye-Sensitized Solar Cells Based on Three-Dimensional Web-Like Structure Anodes

2012 ◽  
Vol 629 ◽  
pp. 332-338 ◽  
Author(s):  
Zhi Hua Tian ◽  
Jian Xi Yao ◽  
Mi Na Guli
Keyword(s):  
Solar Cells ◽  
Conversion Efficiency ◽  
Dye Sensitized Solar Cells ◽  
Three Dimensional ◽  
Precursor Solution ◽  
Photoelectric Conversion Efficiency ◽  
Tio2 Films ◽  
Photoelectric Conversion ◽  
Dye Sensitized ◽  
Sensitized Solar Cells

TiO2 films with three-dimensional web-like structure have been prepared by the photo polymerization-induced phase separation method (PIPS). Scanning electron microscopy and X-ray diffraction were used to characterize the as-prepared TiO2 films. The results showed that the film texture could be tuned by changing the composition of the precursor solution. The TiO2 film with web-like structure exhibited high photocatalytic activity for the degradation of methylene blue (MB) dye. The as-prepared films were used as the photo-anodes in dye-sensitized solar cells (DSCs). The photoelectric conversion efficiency of the DSCs was significantly enhanced by changing the POGTA/TTB in the precursor solution. Because of the increased dye adsorption active sites and efficient electron transport in the TiO2 anode film, a photoelectric conversion efficiency of 3.015% was obtained.

scholarly journals Review of Molecular Modeling and Photoelectronic Applications of Porphyrin-based Materials

2020 ◽  
Author(s):  
M. MogrenAl Mogren ◽  
Noha M.Ahmed ◽  
Ahmed A.Hasanein
Keyword(s):  
Solar Cells ◽  
Energy Gap ◽  
Theoretical Calculations ◽  
Perovskite Solar Cells ◽  
Dye Sensitized Solar Cells ◽  
Electrical Energy ◽  
Dft Methods ◽  
Design Synthesis ◽  
Quantum Dot Solar Cells ◽  
Conversion Performance

In this review, the introduction of solar cells is presented. Old and new generation solar cells are briefly described. Quantum dot solar cells (QDSCs), perovskite solar cells, and dye-sensitized solar cells (DSSCs) are concisely introduced. The sensitization mechanism in DSSCs is discussed in detail concerning the spectral and electron injection properties of different dyes. An analysis of the intramolecular charge transfer process in the excited dye molecule is also provided. The use of porphyrin-based dyes as sensitizers in DSSCs is then reviewed. The design, synthesis, and photovoltaic application of a wide variety of porphyrin-based dyes as well as porphyrin dyads are presented and discussed. Theoretical studies of the spectral and electronic properties of different porphyrin-based dyes using DFT and TD-DFT methods are described. The different possibilities for improving the light-to-electrical energy conversion performance are discussed, such as structural modifications through introducing push-pull moieties, which in turn tunes the HOMO-LUMO energy gap of the sensitizing dye used in the DSSC. Experimental, as well as theoretical calculations of adsorption energies of the sensitizing dyes, are crucial for predicting the relative performance and efficiency of the dyes.

Prediction of Solar Cell Materials via Unsupervised Literature Learning

2021 ◽  
Author(s):  
Lei Zhang ◽  
Mu He
Keyword(s):  
Solar Cells ◽  
Solar Cell ◽  
Language Processing ◽  
Perovskite Solar Cells ◽  
Dye Sensitized Solar Cells ◽  
Cell Types ◽  
Data Driven ◽  
Cell Material ◽  
Textual Data ◽  
Solar Cell Material

Abstract Despite the significant advancement of the data-driven studies for physical science, the textual data that are numerous in the literature are not fully embraced by the physics and materials community. In this manuscript, we successfully employ the natural language processing (NLP) technique to unsupervisedly predict the existence of solar cell types including the dye-sensitized solar cells and the perovskite solar cells based on literatures published prior to their first discovery without human annotation. Enlightened by this, we further identify possible solar cell material candidates via NLP starting with a comprehensive training database of 3.2 million paper abstracts published before 2021. The NLP model effectively predicts the existing solar cell materials, while an uncommon solar cell material namely PtSe2 is suggested as an appropriate candidate for the future solar cells. Its optoelectronic properties are comprehensive investigated via first-principles calculations to reveal the decent stability and optoelectronic performance of the NLP-predicted candidate. This study demonstrates the viability of the textual data for the data-driven materials prediction and highlights the NLP method as a powerful tool to reliably predict the solar cell materials.

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