Full space device optimization for solar cells

Numerical simulation based performance enhancement approach for an inorganic BaZrS3/CuO heterojunction solar cell

One of the main components of the worldwide transition to sustainable energy is solar cells, usually referred to as photovoltaics. By converting sunlight into power, they lessen their reliance on fossil fuels and the release of greenhouse gases. Because solar cells are decentralized, distributed energy systems may be developed, which increases the efficiency of the cells. Chalcogenide perovskites have drawn interest due to their potential in solar energy conversion since they provide distinctive optoelectronic characteristics and stability. But high temperatures and lengthy reaction periods make it difficult to synthesise and process them. Therefore, we present the inaugural numerical simulation using SCAPS-1D for emerging inorganic BaZrS3/CuO heterojunction solar cells. This study delves into the behaviour of diverse parameters in photovoltaic devices, encompassing efficiency (η) values, short-circuit current density (Jsc), fill factor (FF), and open-circuit voltage (Voc). Additionally, we thoroughly examine the impact of window and absorber layer thickness, carrier concentration, and bandgap on the fundamental characteristics of solar cells. Our findings showcase the attainment of the highest efficiency (η) values, reaching 27.3% for our modelled devices, accompanied by Jsc values of 40.5 mA/cm2, Voc value of 0.79 V, and FF value of 85.2. The efficiency (η) values are chiefly influenced by the combined effects of Voc, Jsc, and FF values. This optimal efficiency was achieved with CuO thickness, band gap, and carrier concentration set at 5 µm, 1.05 eV, and above 1019 cm-3, respectively. In comparison, the optimal parameters for BaZrS3 include a thickness of 1 µm, a carrier concentration below 1020 cm-3, and a band gap less than 1.6 eV. Therefore, in the near future, the present simulation will simultaneously provide up an entirely novel field for the less defective perovskite solar cell.

SCAPS simulation of novel inorganic ZrS2/CuO heterojunction solar cells

ZrS₂ is transition metal dichalcogenides (TMDCs) which is believed one of the most talented applicants to fabricate photovoltaics. Therefore, we present here for the first-time numerical simulation of novel inorganic ZrS₂/CuO heterojunction solar cells employing SCAPS-1D. The influence of the thickness, carrier concentration, and bandgap for both the window and absorber layers on the solar cell fundamental parameters was explored intensely. Our results reveal that the solar cell devices performance is mainly affected by many parameters such as the depletion width (W_d), built-in voltage (V_bi), collection length of charge carrier, the minority carrier lifetime, photogenerated current, and recombination rate. The η of 23.8% was achieved as the highest value for our simulated devices with the V_oc value of 0.96 V, the J_sc value of 34.2 mA/cm², and the FF value of 72.2%. Such efficiency was obtained when the CuO band gap, thickness, and carrier concentration were 1.35 eV, 5.5 µm, and above 10¹⁸ cm^-3, respectively, and for the ZrS₂ were 1.4 eV, 1 µm, and less than 10²⁰ cm^-3, respectively. Our simulated results indicate that the inorganic ZrS₂/CuO heterojunction solar cells are promising to fabricate low-cost, large-scale, and high-efficiency photovoltaic devices.

Computational modeling to assist in the discovery of supramolecular materials

Computational modeling is increasingly used to assist in the discovery of supramolecular materials. Supramolecular materials are typically primarily built from organic components that are self-assembled through noncovalent bonding and have potential applications, including in selective binding, sorption, molecular separations, catalysis, optoelectronics, sensing, and as molecular machines. In this review, the key areas where computational prediction can assist in the discovery of supramolecular materials, including in structure prediction, property prediction, and the prediction of how to synthesize a hypothetical material are discussed, before exploring the potential impact of artificial intelligence techniques on the field. Throughout, the importance of close integration with experimental materials discovery programs will be highlighted. A series of case studies from the author's work across some different supramolecular material classes will be discussed, before finishing with a discussion of the outlook for the field.

Two-dimensional BiTeI as a novel perovskite additive for printable perovskite solar cells

Hybrid organic-inorganic perovskite solar cells (PSCs) are attractive printable, flexible, and cost-effective optoelectronic devices constituting an alternative technology to conventional Si-based ones. The incorporation of low-dimensional materials, such as two-dimensional (2D) materials, into the PSC structure is a promising route for interfacial and bulk perovskite engineering, paving the way for improved power conversion efficiency (PCE) and long-term stability. In this work, we investigate the incorporation of 2D bismuth telluride iodide (BiTeI) flakes as additives in the perovskite active layer, demonstrating their role in tuning the interfacial energy-level alignment for optimum device performance. By varying the concentration of BiTeI flakes in the perovskite precursor solution between 0.008 mg mL^-1 and 0.1 mg mL^-1, a downward shift in the energy levels of the perovskite results in an optimal alignment of the energy levels of the materials across the cell structure, as supported by device simulations. Thus, the cell fill factor (FF) increases with additive concentration, reaching values greater than 82%, although the suppression of open circuit voltage (V _oc) is reported beyond an additive concentration threshold of 0.03 mg mL^-1. The most performant devices delivered a PCE of 18.3%, with an average PCE showing a +8% increase compared to the reference devices. This work demonstrates the potential of 2D-material-based additives for the engineering of PSCs via energy level optimization at perovskite/charge transporting layer interfaces.

Into the Unknown: How Computation Can Help Explore Uncharted Material Space

Novel functional materials are urgently needed to help combat the major global challenges facing humanity, such as climate change and resource scarcity. Yet, the traditional experimental materials discovery process is slow and the material space at our disposal is too vast to effectively explore using intuition-guided experimentation alone. Most experimental materials discovery programs necessarily focus on exploring the local space of known materials, so we are not fully exploiting the enormous potential material space, where more novel materials with unique properties may exist. Computation, facilitated by improvements in open-source software and databases, as well as computer hardware has the potential to significantly accelerate the rational development of materials, but all too often is only used to postrationalize experimental observations. Thus, the true predictive power of computation, where theory leads experimentation, is not fully utilized. Here, we discuss the challenges to successful implementation of computation-driven materials discovery workflows, and then focus on the progress of the field, with a particular emphasis on the challenges to reaching novel materials.

Research Progress of Plasmonic Nanostructure-Enhanced Photovoltaic Solar Cells

Enhancement of the electromagnetic properties of metallic nanostructures constitute an extensive research field related to plasmonics. The latter term is derived from plasmons, which are quanta corresponding to longitudinal waves that are propagating in matter by the collective motion of electrons. Plasmonics are increasingly finding wide application in sensing, microscopy, optical communications, biophotonics, and light trapping enhancement for solar energy conversion. Although the plasmonics field has relatively a short history of development, it has led to substantial advancement in enhancing the absorption of the solar spectrum and charge carrier separation efficiency. Recently, huge developments have been made in understanding the basic parameters and mechanisms governing the application of plasmonics, including the effects of nanoparticles’ size, arrangement, and geometry and how all these factors impact the dielectric field in the surrounding medium of the plasmons. This review article emphasizes recent developments, fundamentals, and fabrication techniques for plasmonic nanostructures while investigating their thermal effects and detailing light-trapping enhancement mechanisms. The mismatch effect of the front and back light grating for optimum light trapping is also discussed. Different arrangements of plasmonic nanostructures in photovoltaics for efficiency enhancement, plasmonics’ limitations, and modeling performance are also deeply explored.

Multi-dimensional optimization of In0.53Ga0.47As thermophotovoltaic cell using real coded genetic algorithm

The optimization of thermophotovoltaic (TPV) cell efficiency is essential since it leads to a significant increase in the output power. Typically, the optimization of In_0.53Ga_0.47As TPV cell has been limited to single variable such as the emitter thickness, while the effects of the variation in other design variables are assumed to be negligible. The reported efficiencies of In_0.53Ga_0.47As TPV cell mostly remain < 15%. Therefore, this work develops a multi-variable or multi-dimensional optimization of In_0.53Ga_0.47As TPV cell using the real coded genetic algorithm (RCGA) at various radiation temperatures. RCGA was developed using Visual Basic and it was hybridized with Silvaco TCAD for the electrical characteristics simulation. Under radiation temperatures from 800 to 2000 K, the optimized In_0.53Ga_0.47As TPV cell efficiency increases by an average percentage of 11.86% (from 8.5 to 20.35%) as compared to the non-optimized structure. It was found that the incorporation of a thicker base layer with the back-barrier layers enhances the separation of charge carriers and increases the collection of photo-generated carriers near the band-edge, producing an optimum output power of 0.55 W/cm² (cell efficiency of 22.06%, without antireflection coating) at 1400 K radiation spectrum. The results of this work demonstrate the great potential to generate electricity sustainably from industrial waste heat and the multi-dimensional optimization methodology can be adopted to optimize semiconductor devices, such as solar cell, TPV cell and photodetectors.

Assessment of the energy recovery potential of waste Photovoltaic (PV) modules

Global exponential increase in levels of Photovoltaic (PV) module waste is an increasing concern. The purpose of this study is to investigate if there is energy value in the polymers contained within first-generation crystalline silicon (c-Si) PV modules to help contribute positively to recycling rates and the circular economy. One such thermochemical conversion method that appeals to this application is pyrolysis. As c-Si PV modules are made up of glass, metal, semiconductor and polymer layers; pyrolysis has potential not to promote chemical oxidation of any of these layers to help aid delamination and subsequently, recovery. Herein, we analysed both used polymers taken from a deconstructed used PV module and virgin-grade polymers prior to manufacture to determine if any properties or thermal behaviours had changed. The calorific values of the used and virgin-grade Ethylene vinyl acetate (EVA) encapsulant were found to be high, unchanged and comparable to that of biodiesel at 39.51 and 39.87 MJ.Kg⁻¹, respectively. This result signifies that there is energy value within used modules. As such, this study has assessed the pyrolysis behaviour of PV cells and has indicated the energy recovery potential within the used polymers found in c-Si PV modules.

Improved Photoactivity of Pyroxene Silicates by Cation Substitutions

We investigated the possibility of band structure engineering of pyroxene silicates with chemical formula A⁺¹ B⁺³ Si₂ O₆ by proper cation substitution. Typically, band gaps of naturally formed pyroxene silicates such as NaAlSi₂ O₆ are quite high (≈5 eV). Therefore, it is important to find a way to reduce band gaps for these materials below 3 eV to make them usable for optoelectronic applications operating at visible light range of the spectrum. Using first-principles calculations, we found that appropriate substitutions of both A⁺ and B³⁺ cations can reduce the band gaps of these materials to as low as 1.31 eV. We also discuss how the band gap in this class of materials is affected by cation radii, electronegativity of constituent elements, spin-orbit coupling, and structural modifications. In particular, the replacement of Al³⁺ in NaAlSi₂ O₆ by another trivalent cation Tl³⁺ results in the largest band-gap reduction and emergence of intermediate bands. We also found that all considered materials are still thermodynamically stable. This work provides a design approach for new environmentally benign and abundant materials for use in photovoltaics and optoelectronic devices.

Large-Grain Tin-Rich Perovskite Films for Efficient Solar Cells via Metal Alloying Technique

Fast research progress on lead halide perovskite solar cells has been achieved in the past a few years. However, the presence of lead (Pb) in perovskite composition as a toxic element still remains a major issue for large-scale deployment. In this work, a novel and facile technique is presented to fabricate tin (Sn)-rich perovskite film using metal precursors and an alloying technique. Herein, the perovskite films are formed as a result of the reaction between Sn/Pb binary alloy metal precursors and methylammonium iodide (MAI) vapor in a chemical vapor deposition process carried out at 185 °C. It is found that in this approach the Pb/Sn precursors are first converted to (Pb/Sn)I₂ and further reaction with MAI vapor leads to the formation of perovskite films. By using Pb-Sn eutectic alloy, perovskite films with large grain sizes up to 5 µm can be grown directly from liquid phase metal. Consequently, using an alloying technique and this unique growth mechanism, a less-toxic and efficient perovskite solar cell with a power conversion efficiency (PCE) of 14.04% is demonstrated, while pure Sn and Pb perovskite solar cells prepared in this manner yield PCEs of 4.62% and 14.21%, respectively. It is found that this alloying technique can open up a new direction to further explore different alloy systems (binary or ternary alloys) with even lower melting point.