Development of Solar Cells

The perovskite solar cells (PSC) are believed to have great potential in solar cell industries, since the dramatic power conversion efficiency (PCE) improvement in such short time (i.e., from 3.8% in 2009 to 25% up to date). Organolead halide perovskite materials are commonly used in the PSC, such as CH₃NH₃PbI₃. In order to improve the PCE, many methods have been taken, such as doping ions in perovskite materials, charge transporting layer modification, microstructure modification, and utilizing advanced fabrication techniques. Besides PCE, stability is also an important issue in PSC, because the perovskite can be easily decomposed with moisture, UV light, and overheating, which is a big challenge for the commercialization of PSCs. This chapter summarizes the latest progress of PSCs and provides some useful insights for future study.

In this chapter, we delineate the present state-of-the-art of solution-processed PEDOT:PSS/n-Si heterojunction solar cells in detail. Here, we discuss the emergence, principle of operation, fabrication process, carrier transport properties, and evolution of the efficiency of the PEDOT:PSS/n-Si heterojunction solar cells. We also discuss with the challenges of the solar cells and propose few design guidelines to further improve the efficiency of the solar cells in future. The SCAPS-1D simulation reveals that the use of n⁺ CdS or In₃Se₄ BSF layer which can be deposited by simple solution process enhances the efficiency of the PEDOT:PSS/n-Si heterojunction solar cells to 30.94–35.05% with a higher V_OC of 0.89  V. The short-circuit current of the solar cells can be further increased by the use of proper ARC layer on the top of the PEDOT:PSS/n-Si heterojunction solar cells.

Organic photovoltaic (OPV) cells have attracted considerable attention as renewable energy source with potential for large scale deployment. Among the most efficient OPVs are so-called bulk-heterojunction (BHJ) cells in which the active material consists of an electron donor and electron acceptor material. In this chapter we review how density functional theory (DFT) methods can be employed to characterize interfacial properties, UV-Vis absoprtion spectra, and photoinduced charge separation in BHJ-OPV donor-acceptor complexes based on semiconducting polymers as donor and fullerene derivatives as acceptor. The methods presented here are transferable also to other donor acceptor materials.

A brief history of the development of solar-to-electric devices is discussed for the classically researched solar cell technologies including Si, CIGS, CdTe, GaAs, OPV, DSC, and PSC devices. Relative strengths and weaknesses of these technologies are presented along with the importance of multijunction system research toward higher efficiency solar-to-electric systems. The combining of DSCs with each technology is discussed along with potential directions for designing next generation multijunction systems.

First-principles modeling of charge-neutral excitations with the recognition of charge-transfer and Rydberg states and probing the mechanism of charge-carrier generation from the photoexcited electron–hole pair for the hybrid organic–inorganic photovoltaic materials remain as a cornerstone problem within the framework of time-dependent density functional theory (TDDFT) . The many-body Green’s function Bethe–Salpeter formalism based on a Dyson-like equation for the two-particle correlation function, which accounts for the exchange and attractive screened Coulomb interactions between photoexcited electrons and holes, has emerged as a decent approach to study the photoemission properties including the Frenkel and charge-transfer excitations in an assortment of finite and extended systems of optoelectronic materials. The key ideas of practical implementation of Bethe–Salpeter equation (BSE) involving the computations of single-particle states, quasi-particle energy levels, and the screened Coulomb interaction with the aid of Gaussian atomic basis sets and resolution-of-identity techniques are discussed. The work revisits the computational aspects for the evaluation of electronic, spectroscopic, and photochromic properties of the dye-sensitized solar cell (DSSC) constituents by considering the excitonic effects that renormalize the energy levels and coalesce the single-particle transitions. The most recent advancements in theoretical methods that employ the maximally localized Wannier’s function (MLWF) and curtail the overall scaling of BSE calculations are also addressed, and the viable applications are subsequently illustrated with selected examples. Finally, the review reveals some computational challenges that need to be resolved to expand the applicability of BSE in designing solar cell materials, and to unravel the intricate mechanism of ultrafast excited-state processes.

This chapter discusses the need for energy and a process to address such need with the help of a renewable source of energy—solar energy––when the primary sources such as oil, natural gas, and coal are being depleted while also polluting the atmosphere. It discusses the rise of dye-sensitized solar cells (DSSC) and the invention of organic dyes. Several reports suggest that molecular modeling is an important key to understanding and developing new and efficient organic dyes for DSSC.

The advancement of technology and industrialization demands clean, economic, and reliable energy sources that can be fulfilled by high-volume and power-efficient production of solar cells. To speed up the solar cell development process in a rational way, in the last decade, molecular modeling and machine learning (ML) have shown enough potential to accomplish this task. Especially, quantitative structure–property relationships (QSPRs) modeling has reported designing of promising lead components for diverse solar cell systems with higher power conversion efficiency (%PCE) than the existing ones. Until now, most of the QSPR models have been employed for dye-sensitized solar cells (DSSCs) and polymer solar cells (PSCs) followed by designing acceptor and donor components of these systems. But this chapter also encourages the future application of QSPR for quantum dot solar devices (QDSC’s), perovskite solar cells to improve their efficiency further. The present chapter deals with the role of QSPR modeling in solar cells and discusses how QSPR can be implemented in solar cell designing as well as the virtual screening of materials databases. Additionally, solar cell databases and preparation of webserver for future prediction of %PCE, along with other photophysical parameters, are meticulously discussed to provide an easy start for the beginners. Successful QSPR models for DSSCs and PSCs are also illustrated with detailed modeling information followed by mechanistic introspection.

Dye-sensitized solar cells (DSSCs) represent a promising third-generation photovoltaic technology due to their ease in fabrication, low cost, ability to operate in diffused light, flexibility, and being lightweight. Organic dye-sensitizers are vital components of the DSSCs. Comprehensive theoretical study of the dye’s spectroscopic properties, including excitation energies ground- and excited-state oxidation potential, allows to design and screen organic dye-sensitizers for an efficient DSSC. Density functional theory (DFT) and time-dependent DFT (TDDFT) approaches have been efficiently used to estimate different optoelectronic properties of sensitizers. This chapter outlined the use of the DFT and TDDFT framework to design organic dye-sensitizers for DSSCs to predict different photophysical properties. Prediction of essential factors such as short-circuit current density (\({J}_{SC}\)), open-circuit voltage (\({V}_{OC}\)), along with charge transfer phenomena, will help experimental groups to fabricate DSSCs with higher photoconversion efficiency (PCE). Besides, this chapter includes a basic understanding of the mechanism of DSSCs, based on the energetics of the various constituents of the heterogeneous device.

The present chapter reports a partial least squares (PLS)-regression-based chemometric model for the carbazole class of dyes used in dye-sensitized solar cells (DSSCs) to predict the absorption maxima (λ_max) values. Quantitative prediction of the λ_max values can be an important criterion for molecular design of new dye molecules. We have used only 2D descriptors for the model development purpose as the quantum chemical and electrochemical analyses are time consuming. The developed model was validated extensively using internationally acceptable statistical and validation parameters. A seven-descriptor PLS model with one latent variable (LV) was developed. The statistical results suggested that the model was statistically significant. The majority of the descriptors involved in the model are easily interpretable 2D atom pair descriptors. The model suggests that presence of nitrogen and sulfur atoms at the topological distance of 8, presence of nitrogen and oxygen atoms at the topological distance of 4, higher frequency of oxygen and sulfur atoms at the topological distance of 5, higher frequency of two nitrogen atoms at the topological distance of 5, presence of two oxygen atoms at the topological distance of 4, presence of carbon atoms connected with three aromatic bonds, and presence of two sulfur atoms at the topological distance of 4 in the dye molecules shifted the λ_max value toward the longer wavelength. From the information obtained from the model, it has also been suggested that highly conjugated π-systems shift the λ_max values toward the longer wavelength. Finally, it can be concluded that the identified features from the PLS model for the carbazole derivatives may be employed for the design and development of new carbazole dyes and to predict λ_max values before they are synthesized.