TU Project Work: Simulation of Anti-reflective Coating on Crystalline Silicon Solar Cell using PC1D PDF

Simulation of Anti-reﬂective coating on Crystalline silicon ( C-Si ) solar cell using PC1D A PROJECT WORK SUBMITTED TO THE DEPARTMENT OF PHYSICS CENTRAL CAMPUS OF TECHNOLOGY INSTITUTE OF SCIENCE AND TECHNOLOGY TRIBHUVAN UNIVERSITY NEPAL FOR THE AWARD OF BACHELOR OF SCIENCE (B.Sc.) IN PHYSICS BY BIKASH LIMBU SYMBOL NO: 500080019 T.U. REGISTRATION NO: 5-2-8-159-2019 [02, SEPTEMBER, 2024] RECOMMENDATION This is to recommend that Bikash Limbu, Symbol No. 500080019, T.U. Registration No. 5-2-8-159-2019 has carried out project work entitled "Simulation of Anti-reﬂective coating on Crystalline silicon ( C-Si ) solar cell using PC1D." for the requirement to the project work in Bachelor of Science (B.Sc.) degree in Physics under our supervision Mr. Prem Sagar Dahal in the Department of Physics, Central Campus of Technology, Institute of Science and Technology (IoST), Tribhuvan University (T.U.), Nepal. To our knowledge, this work has not been submitted for any other degree. He has fulﬁlled all the requirements laid down by the Institute of Science and Technology (IoST), Tribhuvan University (T.U.), Nepal for the submission of the project work for the partial fulﬁllment of the Bachelor of Science (B.Sc.) degree. Teach. Asst. Mr. Prem Sagar Dahal Supervisor Department of Physics Central Campus of Technology Dharan, Sunsari Teach. Asst. Mrs. Susmita Paudel Co-supervisor Department of Physics Central Campus of Technology Dharan, Sunsari [02, SEPTEMBER, 2024] i DECLARATION This project work entitled " Simulation of Anti-reﬂective coating on Crystalline sili- con ( C-Si ) solar cell using PC1D. " is being submitted to the Department of Physics, Central Campus of Technology, Institute of Science and Technology (loST), Tribhuvan University (T.U.), Nepal for the partial fulﬁllment of the requirement to the project work in Bachelor of Science (B.Sc.) degree in Physics. This project work is carried out by me under the supervision of Mr. Prem Sagar Dahal and co-supervision Mrs. Susmita Paudel, Department of Physics, Central Campus of Technology, Institute of Science and Technol- ogy (loST), Tribhuvan University (T.U.), Nepal. This work is original and has not been submitted earlier in part or full in this or any other form to any university or institute, here or elsewhere, for the award of any degree......................... Signature Name of student: Bikash Limbu Symbol No: 500080019 T.U. Registration No: 5-2-8-159-2019 [02, SEPTEMBER, 2024] ii LETTER OF FORWARD On the recommendation of Mr. Prem Sagar Dahal, this project work is submitted by Mr. Bikash Limbu, Symbol No. 500080019, T.U. Registration No. 5-2-8-159-2019, entitled " Simulation of Anti-reﬂective coating on Crystalline silicon ( C-Si ) solar cell using PC1D " is forwarded by the Department of Physics, Central Campus of Technol- ogy, for the approval to the Evaluation Committee, Institute of Science and Technology (IoST), Tribhuvan University (T.U.), Nepal. He has fulﬁlled all the requirements laid down by the Institute of Science and Technology (IoST), Tribhuvan University (T.U.), Nepal for the project work. Assoc. Prof. Shreepati Chakrapani Head Department of Physics Central Campus of Technology Tribhuvan University [02, SEPTEMBER, 2024] iii BOARD OF EXAMINATION AND CERTIFICATE OF APPROVAL This project work (PRO-406) entitled " Simulation of Anti-reﬂective coating on Crys- talline silicon ( C-Si ) solar cell using PC1D " by Mr. Bikash Limbu, Symbol No. 500080019 and T.U. Registration No. 5-2-8-159-2019 under the supervision of Mr. Prem Sagar Dahal and co-supervision of Mrs. Susmita Paudel in the Department of Physics, Central Campus of Technology, Institute of Science and Technology (IoST), Tribhuvan University (T.U.), is hereby submitted for the partial fulﬁllment of the Bachelor of Science (B.Sc.) degree in Physics. This report has been accepted and forwarded to the Controller of Examination, Institute of Science and Technology, Tribhuvan University, Nepal for the legal procedure. Teach. Asst. Mr. Prem Sagar Dahal Teach. Asst. Mrs. Susmita Paudel Supervisor Co-Supervisor Department of Physics Department of Physics Central Campus of Technology Central Campus of Technology Tribhuvan University Tribhuvan University Asst. Prof. Dr. Ramesh Kumar Gohivar Internal Examiner External Examiner Internal Examiner Department of Physics Department of Physics M.M.A.M.C Central Campus of Technology Tribhuvan University Tribhuvan University Assoc. Prof. Mr. Shreepati Chakrapani Head of Department Department of Physics Central Campus of Technology Tribhuvan University [02, SEPTEMBER, 2024] iv ACKNOWLEDGEMENT Firstly I would like to express my heartfelt thanks to my project supervisor Mr. Prem Sagar Dahal and co-supervisor Mrs. Susmita Paudel for their inspiration, guidance, coop- eration, and encouragement. I am also deeply grateful to Dr. Parajuli, Assistant Professor at TU for his cooperation on this project. My sincere appreciation goes to the Head of the Department, Asst. Prof. Shreepati Chakrapani, and all the faculty members for their advice and support. Additionally, I would like to acknowledge the staff of the Department of Physics, Central Campus of Technology, Dharan, for their cooperation. I am thankful to the Institute of Science and Technology at Tribhuvan University, Nepal, for providing me the opportunity to undertake this project work. I would also like to express my gratitude to the University of New South Wales for developing the PC1D software, which is simple, fast, and user-friendly. Lastly, I must profound gratitude to my parents for their continuous support and encour- agement throughout my studies, and to all my friends who have assisted me during the writing of this thesis. v ABSTRACT Minimizing photon losses through the deposition of an anti-reﬂective layer can improve the conversion efﬁciency of solar cells. In this study, we investigate how the ARC affects the efﬁciency of solar cells. Speciﬁcally, this paper studies the impact of seven different ARC materials on solar cells using PC1D simulator software. The materials considered are Si3 N4 , TiO2 , SiO2 , ZnO, Polystyrene (PS), Polycarbonate (PC), and MgF2. Firstly, we simulated the without ARC which shows the results of solar cell efﬁciency of ap- proximately 14.14%. A signiﬁcant improvement in efﬁciency was obtained through the use of ARC materials. For all selected ARC materials, the optimal efﬁciency was de- termined at a wavelength of 600 nm. Among the seven ARC materials, Si3 N4 and ZnO, with thicknesses of 74.45 nm and 75.04 nm respectively, demonstrated a notable improve- ment, increasing the solar cell efﬁciency by approximately 4.5%. Using a double-layer combination of MgF2 and ZnO, an efﬁciency of 19.20% was achieved. For efﬁcient mod- eling of solar cells, we used SiO2 as surface passivation on the ARC layer of Si3 N4 , from which we obtained an optimal efﬁciency of 19.02%. In this paper, we analyzed c-Si solar cell efﬁciency at different wavelengths and then chose a suitable wavelength for higher efﬁciency. Keywords: Anti-Reﬂecting Coating (ARC), Crystalline Silicon, Solar cells, PC1D software, Re- fractive index, Surface passivation. vi शोधसार सौयर् ऊजार् एक नवीकरणीय ऊजार् हो । हामीले यस ू तवेदनमा सौयर् सेलबाट उत्पादन हुने उजार्को दक्षतालाई मापन गरे का छौ | यस उजार्को दक्षता बढाउने उपायहरु मध्ये एक ूकाश प रवतर्न वरोधी आवरण हो | हामीले ूकाश प रवंतन र् वरोधी आवरण सामामीहरुको ूयोग ग र सौयर् सेलबाट उत्पादन हुने उजार्लाई बढाउन ूयास गरे का छौ | जसको ूयोगबाट हाॆो प रमाणमा सकारात्मक ूभाव परे को छ | हामीले यस प रक्षणका ला ग सफ्टवेयरको ूयोग गरे का छौ | सुरुमा हामीले सौयर् सेलबाट ूकाश प रवतर्न वरोधी आवरणको ूयोग नग रकन १४.१४% दक्षता हा सल गरे का थयौँ । हामीले ूकाश प रवतर्न वरोधी आवरण साममीहरूको ूयोग गरे र सबैभन्दा बढ Si3 N4 र ZnO बाट १८.६०% दक्षता हा सल गय । हामीले ूकाश प रवतर्न वरोधी आवरण साममीहरूको ूयोग गरे र २-४% सुधार पाएका छौं | vii LIST OF ACRONYMS AND ABBREVIATIONS ACRONYMS ARC Anti-Reﬂecting Coating. vi, 1, 4, 11, 21 c-SI Crystalline Silicon. 22 DLARC Double Layer ARC. 3 Isc Short-circuit Current. 11 nm Nanometre. 10 SLARC Single Layer ARC. 2, 3 Voc Open-circuit Voltage. 11 viii LIST OF TABLES 3.1 Device Parameters................................. 9 3.2 Excitation Proﬁle.................................. 9 4.1 Without ARC.................................... 11 4.2 The simulation outcomes for the silicon cell using an ARC are based on SiO2.. 12 4.3 The simulation outcomes for the silicon cell using an ARC are based on TiO2.. 13 4.4 The simulation outcomes for the silicon cell using an ARC are based on Si3 N4.. 14 4.5 The simulation outcomes for the silicon cell using an ARC are based on MgF2.. 15 4.6 The simulation outcomes for the silicon cell using an ARC are based on Polystyrene (PS)......................................... 16 4.7 The simulation outcomes for the silicon cell using an ARC are based on Polycar- bonate (PC)..................................... 17 4.8 The simulation outcomes for the silicon cell using an ARC are based on ZnO.. 18 4.9 For the Best Parameters and Efﬁciency of ARC Materials............ 20 4.10 Surface Passivation and Double layer ARC.................... 21 ix LIST OF FIGURES 1.1 Scematic diagram of ARC Theory......................... 2 1.2 Scematic diagram of SLARC............................ 2 1.3 Scematic diagram of DLARC............................ 3 3.1 Front-end of PC1D................................. 7 4.1 These ﬁgures show the relationship between the wavelength and efﬁciency for seven ARC materials................................ 19 x CONTENTS Recommendation i Declaration ii Letter of Forward iii Board of Examination and Certiﬁcate of Approval iv Acknowledgement v Abstract vi शोधसार vii List of Acronyms and Abbreviations viii List of Tables ix List of Figures x CHAPTER 1: INTRODUCTION 1 1.1 General Introduction................................. 1 1.1.1 Anti-reﬂecting Thoery............................ 1 1.1.2 single Layer Coating............................. 2 1.1.3 Double Layer Coating as Surface Passivation................ 3 1.2 Rationale....................................... 4 1.3 Objectives....................................... 4 1.3.1 General objectives............................... 4 1.3.2 Speciﬁc objectives.............................. 4 CHAPTER 2 LITERATURE REVIEW 6 CHAPTER 3: MATERIALS AND METHODS 7 3.1 Materials....................................... 7 3.1.1 PC1D Software................................ 7 3.1.2 ARC Materials................................ 8 3.2 Methods........................................ 8 3.2.1 Simulation................................... 8 3.2.2 Simulation without ARC........................... 8 3.2.3 Simulation of c-Si Solar Cell With the Use of ARC............. 9 xi CHAPTER 4: RESULTS AND DISCUSSION 11 4.1 Modeling of c-Si Solar Cell Without the Use of ARC................ 11 4.2 Modeling of c-Si Solar Cell With the Use of ARC.................. 11 4.3 Double Layer as Surface Passivation......................... 20 4.4 Discussion....................................... 21 CHAPTER 5: CONCLUSION AND RECOMMENDATION 22 5.1 Conclusions...................................... 22 5.2 Novelty and National Prosperity aspect of Project work............... 22 5.3 Limitation of the work................................ 23 5.3 Recommendations for further work.......................... 23 References 24 APPENDIX 26 xii CHAPTER 1 1. INTRODUCTION 1.1 General Introduction In our earth, there are many available energy sources, such as fuel, electrical, tidal, geothermal, and solar cell energy. Some of the energy sources affect the environment such as fuel energy, and Coal energy but solar energy is green energy that does not affect our environment. Photovoltaic technology involves converting sunlight directly into electrical energy through the use of solar cells. It emerged as a signiﬁcant renewable energy source in the 1950s and gained momentum in the 1960s for space applications. The 1970s oil crisis highlighted the need for alternative energy, boosting terrestrial photovoltaic development. By the 1980s, silicon solar cells achieved 20% efﬁ- ciency, leading to steady industry growth (Introduction to Photovoltaics, n.d.). Solar energy is the primary source of nearly all the energy available on Earth. Humans and other living organisms rely on the sun for warmth and food, and people also harness solar energy in various ways. For example Fossil fuels, biomass, Wind energy, Photovoltaic (PV), etc. PV is a technique that directly transforms sunlight into electricity through the use of solar cells, which are reliable and pollution-free (PV Education, n.d.). The most common types of photovoltaic modules are mono-crystalline silicon, polycrystalline sil- icon and thin ﬁlm but out of these sources c-Si solar cell occupy the 90% of share market of solar cell market (Andreani, Bozzola, Kowalczewski, Liscidini, & Redorici, 2019). The development of practical solar cells began in the mid-20th century. This period also saw the initial adoption of solar cells for various applications, laying the foundation for their widespread use in the following decades (Chapin, Fuller, & Pearson, 1954). However, commercial c-Si solar cell efﬁciency of production typically ranges between 12% and 19%. This means that only a small portion of the sunlight that strikes these cells is converted into usable electrical energy (Swanson, 2006). For bare silicon, the reﬂectivity is quite high, which means a signiﬁcant portion of light is not absorbed. Speciﬁcally, from the surface of bare silicon surface more than 30% of incident light reﬂected (Education, n.d.). In efforts to minimize surface reﬂectance, silicon (Si) surfaces underwent texturing, resulting in a reduction of surface reﬂectance to approximately 11% (Moona, Kapruwan, & Sharma, 2018). Different methods are employed to reduce reﬂection loss from silicon surfaces. These include surface texturing, light trapping tech- niques, and the application of antireﬂection coatings, among others, all aimed at enhancing the efﬁciency of solar cell performance (Basu et al., 2010; Sharma, Gupta, & Virdi, 2017). Thus, to increase the conversion efﬁciency of solar cells Anti-Reﬂecting Coating (ARC) plays a major role. 1.1.1 Anti-reﬂecting Theory Between the wafer surface and the air, when sunlight hits this boundary, it gets refracted. This causes a reduction in the absorption of sunlight by the solar cell. One approach to address this 1 problem is to apply a thin layer of dielectric materials, known as antireﬂection coatings, to the solar cell. These coatings have speciﬁc thicknesses and refractive indices. The reﬂected wave phase from the ARC surface and the reﬂected wave phase from the semiconductor surface are out of phase, allowing them to cancel each other out. As a result, the reﬂectivity energy becomes zero. This mechanism is illustrated by the following ﬁgure [1.1] (Education, n.d.). Figure 1.1: Scematic diagram of ARC Theory ARC materials are categorized into ﬁve groups: silicon-based, metal-based, polymer-based, composites, and other advanced materials. An effective ARC should cover a broad range of wavelengths, including the ultraviolet region, to meet the requirements for optimal performance (Shanmugam, Pugazhendhi, Elavarasan, Kasiviswanathan, & Das, 2020). 1.1.2 Single Layer Coating The most basic and commonly utilized antireﬂection coating in c-Si solar cells is Single Layer ARC (SLARC). SLARC consists of a dielectric material like Silicon Nitride (SiNx) applied to the surface of a silicon substrate. This coating is designed to achieve nearly zero reﬂectance at a particular wavelength, with its thickness precisely calculated to minimize reﬂection at that speciﬁc wavelength. The basic operating principle of SLARC is illustrated in the ﬁgure 1.2. Figure 1.2: Scematic diagram of SLARC The thickness of the anti-reﬂective coating layer that results in minimal reﬂection can be cal- culated using the following equation For minimum reﬂection, we can deﬁne the ARC thickness 2 using the following equation:(Education, 2024). λ d= 4n Where λ is the wavelength and n denotes the refractive index of the ARC material. 1.1.3 Double Layer Coating as Surface Passivation Single-layer ARCs are limited by their ability to minimize reﬂectance at only one speciﬁc wave- length, determined by the ARC’s design thickness. For a solar cell to be highly efﬁcient, it needs to maintain low reﬂectance across a broad spectrum of wavelengths to maximize the sun’s energy. A solution to this issue is the use of multilayered antireﬂection coatings (Cid, Stem, Brunetti, Beloto, & Ramos, 1998). Using Double Layer ARC (DLARC) can achieve minimal reﬂection across various wavelengths by leveraging the destructive interference of waves. DLARC exhibit more intricate reﬂections that can interact with other reﬂected waves, leading to a reduced overall reﬂectance. The ﬁgure 1.3 illustrates the interaction of various waves within the double-layer ARC. DLARCs Figure 1.3: Scematic diagram of DLARC involve more intricate wave interactions than SLARCs. At each interface of a DLARC, waves are either transmitted or reﬂected, leading to interference with other incoming and outgoing waves. Consequently, designing the materials and thickness for DLARCs is more complex, and the related equations are signiﬁcantly more complicated compared to those for SLARCs (Mandong, 2018). Passivation is a technology designed to prevent electrons and holes from recombining prematurely on the wafer surface or a technique used to enhance material performance and lifespan by mak- ing their surfaces less reactive. This is usually done by creating a thin, protective oxide layer on the materials surface. In solar photovoltaic (PV) technology, To reduce electron recombination, we use passivation, which increases the efﬁciency and performance of solar cells. (Passivation Deﬁnition, n.d.). 3 1.2 Rationale The demand for renewable energy sources globally has led to signiﬁcant advancements in photo- voltaic (PV) technologies. c-Si solar cells have become a dominant technology because of their high efﬁciency and reliability. However, one of the critical challenges in this technology is the less amount of light is absorbed by solar cells due to reﬂection. This problem can be minimized by coating on the solar cell surface, which signiﬁcantly impacts the cells efﬁciency. Additionally, electron-hole recombination on the wafer surface affects efﬁciency too, this can be reduced by applying surface passivation on the surface of the wafer surface. Achieving optimal efﬁciency with ARC, reducing reﬂectance from the wafer surface, and maxi- mizing light absorption remain challenging. This study addresses this gap by simulating various ARC conﬁgurations using the PC1D software to identify the most effective ARC materials that can improve the overall performance of c-Si solar cells. This research is relevant to improve the efﬁciency of solar energy systems. This study may pro- vide the development of more efﬁcient solar panels, which can lead to low cost of production and increased adoption of solar energy. This study will use PC1D simulation software to model and analyze various ARC conﬁgurations and their impact on c-Si solar cell performance. 1.3 Objectives The main objectives of this study are to ﬁnd suitable materials for ARC which reduced the re- ﬂectance with improving efﬁciency on solar cells and to ﬁnd the optimal thickness of these ARC materials. Additionally, the research aims to apply double-layer ARC on the solar cell’s surface and then also use passivation materials to reduce surface recombination. 1.3.1 General Objectives To investigate the effectiveness of anti-reﬂecting coatings in enhancing the efﬁciency of c-Si solar cells. By applying surface passivation to the outer surface of wafers with anti-reﬂecting coatings which also enhances the efﬁciency. 1.3.2 Speciﬁc Objectives To analyze the performance of c-Si solar cells without ARCs. To design and simulate various ARC materials using the PC1D software. To evaluate the impact of different coating thicknesses with corresponding wavelengths on the solar cell performance. To compare the simulated solar cells’ efﬁciency with and without ARCs. To identify the suitable ARC material. 4 To apply double layer and surface passivation to the outer surface of the anti-reﬂecting coated wafers. To measure the performance before and after the apply of double layer and surface passiva- tion on the solar cells. 5 CHAPTER 2 2. LITERATURE REVIEW In the modern era, the development of solar cells plays a crucial role as a source of green energy. New approaches aimed at achieving higher efﬁciency signiﬁcantly contribute to energy develop- ment and sustainability. In their 2018 paper, (Hashmi, Rashid, Mahmood, Hoq, & Rahman, 2018) compares the simu- lation results of solar cells both without and with ARC. They found that SiN achieved maximum efﬁciency at a thickness of 74.257 nm, resulting in a 20.35% efﬁciency at a wavelength of 600 nm. Additionally, ZnO played a signiﬁcant role. The application of ARC led to a notable increase in efﬁciency, and further improvements were observed with the application of surface passivation. Depositing an ARC layer on the wafer surface can minimize photon losses, thereby improv- ing the efﬁciency of solar cells. (Subramanian et al., 2021) studied the reﬂectance properties of ARC materials using the OPAL2 calculator. For single-layer ARC, SiNx and TiO2 were chosen, resulting in short-circuit current densities of 38.4 mA/cm2 and 38.09 mA/cm2 , respectively, with an efﬁciency of 20.7%. Additionally, using SiO2 /SiNx improved the current density by about 0.3 mA/cm2 and efﬁciency by approximately 0.3%. Furthermore, the use of double-layer ARC also showed signiﬁcant improvements in conversion efﬁciency. The competition to improve the efﬁciency of solar cells among global companies supports researchers and leads to advancements in solar cell technology. (Jabbar, 2020) modeled a silicon solar cell with an area of 10 Œ 10 cm2 and thicknesses of 300 ţm for the P layer and 2 ţm for the N layer. Two scenarios were considered: one without ARC and one with ARC. (Jabbar, 2020) used ﬁve polymeric materials in this simulation: polydimethylsiloxane (PDMS), polystyrene (PS), polymethyl methacrylate (PMMA), polyethylene terephthalate (PET), and polycarbonate (PC). Among these materials, polycarbonate achieved the highest efﬁciency of 20.66%, compared to an initial efﬁciency of 15.39% without ARC. Signiﬁcant enhancement was observed at a wavelength of 600 nm for all selected ARC materials. The use of ARC resulted in efﬁciency gains ranging from 3.84% to 5.27%, depending on the material used. These ARC materials also had a positive impact on cost reduction. 6 CHAPTER 3 3. MATERIALS AND METHODS 3.1 Materials This paper focuses on several ARCs materials implemented on c-Si solar cells for improving the efﬁciency and performance of solar cells, which are simulated using the software PC1D. 3.1.1 PC1D Software PC1D is a software tool developed by the University of New South Wales to simulate the solar cell to improve performance. It can model the optical properties and electrical of one-dimensional solar cells and supports a variety of semiconductor materials. Key features include the ability to simulate anti-reﬂective coatings, a user-friendly interface, and tools for data analysis and visualiza- tion. PC1D is widely used in research and development, educational settings, and for optimizing solar cell design parameters to enhance efﬁciency. A c-Si solar cell is simulated using the PC1D simulator software. Figure 3.1 displays the main window of PC1D. Table 3.1 lists the components of PC1D that deﬁne the parameters. Figure 3.1: Front-end of PC1D 7 3.1.2 ARC Materials Anti-reﬂective coating materials are crucial to minimizing reﬂection losses and maximizing light absorption to improve the efﬁciency of solar cells. These coatings are applied to the wafer surface to improve their optical properties. The effectiveness of an ARC depends on its material properties. Here are some materials and their properties. Si3 N4 Tio2 SiO2 ZnO Polystyrene (PS) Polycarbonate (PC) MgF2 3.2 Methods 3.2.1 Simulation To verify the simulation of the c-Si solar cell, we designed a model using the PC1D software based on the parameters given in the tables below. 3.2.2 Simulation without ARC For the simulation c-Si solar cell without ARC we use PC1D simulator, utilizing the optical pa- rameters (TiO2, 2024; Si3N4, 2024; Sio2, 2024; MgF2, 2024; (C8H8), 2024; (C16H14O3), 2024; ZnO, 2024) and the device parameters shown in the table 3.1. 8 Table 3.1: Device Parameters S.N. Name Properties 1. Device Area 100 cm2 (10cm * 10cm) 2. Broadband Reﬂectance 30 % 3. Texturing Angle & Depth 54.9 & 2 ţm 4. Emitter contact 1*10−3 ohm 5. Base contact 4*10−3 ohm 6. Internal conductor 0.05 S 7. Internal optical reﬂectance 90 and 70 8. Thickness 300 u 9. P-type background doping 1*1016 cm−3 10. N-type background doping 1*1018 cm−3 at 2um 11. Bulk recombination Tau = tau =101.1 us 12 Front-back surface recombination S model, Sn = Sp = 1000 cm/s For the excitation proﬁle, Table 3.2: Excitation Proﬁle S.N. Name Properties 1. Excitation mode 100 time steps 2. Temperature 25◦ C 3. Base circuit Sweep from -0.8 to 0.8 4. Constant intensity 0.1 W cm−2 3.2.3 Simulation of c-Si Solar Cell With the Use of ARC In the simulation of the ARC layer, we choose front surface optical coating at simulation. The re- fractive index and thickness were changed on the basis of different properties of ARCs. To design and understand the behavior of the ARC layer, the following equations are crucial:. n̂(λ ) = n(λ ) + iκ (λ ) (3.1) where n(λ ) represents the complex refractive index. This complex refractive index consists of a real part, known as the real refractive index n(λ ), and an imaginary part, called the extinction coefﬁcient (λ ), both of which vary with wavelength. The absorption coefﬁcient κ (λ ) is connected to the extinction coefﬁcient by the following relation. 4π α (λ ) = κ (λ ) (3.2) λ 9 Equation 3.2 clearly shows that the absorption of photons (or radiation) is inﬂuenced by the wavelength, thickness, and properties of the medium. Now the refractive index of ARC is, √ narc = nair × narc (λ0 ) (3.3) And the thickness of ARC is, λ0 d= (3.4) 4n In this context, nair refers to The refractive index for air, and narc refers to the refractive index for ARC at a speciﬁc wavelength (λ0 ). A near examination of Equation 3.3 reveals that the refrac- tive index for ARC is inﬂuenced by both the refractive index of air and the wavelength-dependent refractive index of the particular anti-reﬂection coating. However, the value on the right-hand side of Equation 3.3 was not used in Equation 3.3 or in the simulation. According to references (TiO2, 2024; Si3N4, 2024; Sio2, 2024; MgF2, 2024; (C8H8), 2024; (C16H14O3), 2024; ZnO, 2024), ex- perimentally obtained narc values for various ARCs ranging from 2501100 Nanometre (nm) were directly inputted into Equation 3.4 and then into the simulation. By inputting the wavelength (λ0 ) and the corresponding ARC value, the associated optimum thickness values for each ARC are determined. 10 CHAPTER 4 4. RESULTS AND DISCUSSION 4.1 Modeling of c-Si Solar Cell Without the Use of ARC By using the PC1D simulator, we simulated the c-Si solar cell without an ARC. The results, which include the maximum power output, Open-circuit Voltage (Voc) and Short- circuit Current (Isc), are shown in the given below tables. Table 4.1: Without ARC S.N. Name Properties Efﬁciency 1. Short-circuit Ib -2.798 A 2. Max base power out 1.414 W 14.14% 3. Open-circuit Vb 0.6230 V 4.2 Modeling of c-Si Solar Cell With the Use of ARC Examining the data for various ARC in tables reveals that altering the wavelength and thickness impacts the Voc, Isc, and efﬁciency of the solar cell. Since the refractive index, absorption coefﬁcient, and excitation coefﬁcient depend on the wavelength and are not easily adjustable, optimizing the ﬁlm thickness is crucial for achieving maximum Voc, Isc, and efﬁciency. 11 Table 4.2: The simulation outcomes for the silicon cell using an ARC are based on SiO2 Wavelength Refractive Thickness Voc Isc Pmax FF Efﬁciency Index (Sio2, 2024) 250 1.5074 41.46 0.6236 -2.868 1.45 -0.8107 14.5 300 1.4878 50.41 0.6246 -2.976 1.506 -0.8102 15.06 350 1.4769 59.25 0.6255 -3.088 1.564 -0.8097 15.64 400 1.4701 68.02 0.6264 -3.193 1.618 -0.8090 16.18 450 1.4656 76.76 0.6271 -3.281 1.663 -0.8083 16.63 500 1.4623 85.48 0.6276 -3.347 1.698 -0.8083 16.98 550 1.4599 94.18 0.628 -3.39 1.719 -0.8075 17.19 600 1.4580 102.88 0.6281 -3.409 1.729 -0.8075 17.29 650 1.4565 111.57 0.6281 -3.407 1.729 -0.8080 17.29 700 1.4553 120.25 0.628 -3.389 1.719 -0.8077 17.19 750 1.4542 128.94 0.6277 -3.357 1.703 -0.8082 17.03 800 1.4533 137.62 0.6274 -3.316 1.681 -0.8080 16.81 850 1.4525 146.30 0.627 -3.27 1.658 -0.8087 16.58 900 1.4518 154.98 0.6266 -3.222 1.633 -0.8089 16.33 950 1.4511 163.67 0.6263 -3.175 1.609 -0.8092 16.09 1000 1.4504 172.37 0.6259 -3.131 1.586 -0.8093 15.86 1050 1.4498 181.06 0.6256 -3.092 1.566 -0.8096 15.66 1100 1.4498 189.68 0.6253 -3.058 1.548 -0.8096 15.48 12 Table 4.3: The simulation outcomes for the silicon cell using an ARC are based on TiO2 Wavelength Refractive Thickness Voc Isc Pmax FF Efﬁciency Index (TiO2, 2024) 250 - - - - - - - 300 - - - - - - - 350 - - - - - - - 400 - - - - - - - 450 2.8126 40.00 0.627 -3.269 1.658 -0.8089 16.58 500 2.7114 46.10 0.6278 -3.368 1.708 -0.8077 17.08 550 2.6479 51.93 0.6282 -3.424 1.737 -0.8075 17.37 600 2.6049 57.58 0.6284 -3.448 1.75 -0.8076 17.5 650 2.5742 63.13 0.6284 -3.447 1.749 -0.8074 17.49 700 2.5512 68.60 0.6282 -3.426 1.738 -0.8075 17.38 750 2.5336 74.01 0.628 -3.39 1.72 -0.8079 17.2 800 2.5197 79.37 0.6276 -3.345 1.697 -0.8083 16.97 850 2.5086 84.71 0.6272 -3.296 1.671 -0.8083 16.71 900 2.4995 90.02 0.6269 -3.247 1.646 -0.8086 16.46 950 2.492 95.30 0.6265 -3.203 1.623 -0.8087 16.23 1000 2.4856 100.58 0.6262 -3.167 1.605 -0.8093 16.05 1050 2.4803 105.83 0.626 -3.138 1.59 -0.8094 15.9 1100 2.4757 111.08 0.6258 -3.115 1.578 -0.8094 15.78 13 Table 4.4: The simulation outcomes for the silicon cell using an ARC are based on Si3 N4 WavelengthRefractive Thickness Voc Isc Pmax FF Efﬁciency Index (Si3N4, 2024) 250 2.2819 27.39 0.6241 -2.919 1.477 -0.810 14.77 300 2.1667 34.61 0.6254 -3.076 1.557 -0.8093 15.57 350 2.1076 41.52 0.6268 -3.238 1.641 -0.8085 16.41 400 2.0726 48.25 0.6279 -3.387 1.718 -0.8078 17.18 450 2.05 54.88 0.6288 -3.507 1.78 -0.8071 17.8 500 2.0344 61.44 0.6295 -3.592 1.824 -0.8066 18.24 550 2.0232 67.96 0.6298 -3.643 1.843 -0.8032 18.43 600 2.0149 74.45 0.63 -3.662 1.86 -0.8062 18.6 650 2.0085 80.91 0.6299 -3.655 1.856 -0.8061 18.56 700 2.0035 87.35 0.6297 -3.626 1.841 -0.8062 18.41 750 1.9995 93.77 0.6294 -3.58 1.817 -0.8063 18.17 800 1.9962 100.19 0.629 -3.523 1.788 -0.8068 17.88 850 1.9935 106.60 0.6285 -3.461 1.756 -0.8072 17.56 900 1.9913 112.99 0.628 -3.397 1.723 -0.8076 17.23 950 1.9894 119.38 0.6276 -3.338 1.693 -0.8081 16.93 1000 1.9878 125.77 0.6272 -3.285 1.665 -0.8081 16.65 1050 1.9865 132.14 0.6268 -3.239 1.642 -0.808 16.42 1100 1.9853 138.52 0.6265 -3.2 1.621 -0.8085 16.21 14 Table 4.5: The simulation outcomes for the silicon cell using an ARC are based on MgF2 WavelengthRefractive Thickness Voc Isc Pmax FF Efﬁciency Index (MgF2, 2024) 250 1.4029 44.55 0.6233 -2.834 1.433 -0.8112 14.33 300 1.3931 53.84 0.6242 -2.929 1.482 -0.8106 14.82 350 1.3874 63.07 0.625 -3.027 1.532 -0.8098 15.32 400 1.3839 72.26 0.6258 -3.119 1.58 -0.8095 15.8 450 1.3815 81.43 0.6264 -3.196 1.62 -0.8092 16.2 500 1.3798 90.59 0.6269 -3.255 1.65 -0.8086 16.5 550 1.3785 99.75 0.6272 -3.293 1.67 -0.8086 16.7 600 1.3775 108.89 0.6274 -3.311 1.679 -0.8083 16.79 650 1.3767 118.04 0.6273 -3.31 1.679 -0.8086 16.79 700 1.3761 127.17 0.6272 -3.295 1.671 -0.8086 16.71 750 1.3755 136.31 0.627 -3.267 1.656 -0.8084 16.56 800 1.3751 145.44 0.6267 -3.232 1.638 -0.8087 16.38 850 1.3747 154.58 0.6264 -3.192 1.617 -0.8087 16.17 900 1.3743 163.72 0.6261 -3.149 1.595 -0.8090 15.95 950 1.374 172.85 0.6257 -3.108 1.574 -0.8094 15.74 1000 1.3737 181.99 0.6254 -3.07 1.554 -0.8094 15.54 1050 1.3734 191.13 0.6251 -3.035 1.537 -0.8102 15.37 1100 1.3731 200.28 0.6248 -3.005 1.521 -0.8101 15.21 15 Table 4.6: The simulation outcomes for the silicon cell using an ARC are based on Polystyrene (PS) WavelengthRefractive Thickness Voc Isc Pmax FF Efﬁciency Index ((C8H8), 2024) 250 - - - - - - - 300 - - - - - - - 350 - - - - - - - 400 - - - - - - - 450 1.6136 69.72 0.628 -3.393 1.721 -0.8077 17.21 500 1.6033 77.96 0.6285 -3.466 1.759 -0.8075 17.59 550 1.5959 86.16 0.6289 -3.512 1.782 -0.8068 17.82 600 1.5904 94.32 0.629 -3.531 1.792 -0.8068 17.92 650 1.5862 102.45 0.629 -3.527 1.79 -0.8069 17.9 700 1.5829 110.56 0.6288 -3.504 1.778 -0.8070 17.78 750 1.5803 118.65 0.6285 -3.466 1.759 -0.8075 17.59 800 1.582 126.42 0.6282 -3.42 1.735 -0.8076 17.35 850 1.5764 134.80 0.6278 -3.364 1.706 -0.8078 17.06 900 1.5749 142.87 0.6273 -3.308 1.677 -0.8082 16.77 950 1.5737 150.92 0.6269 -3.254 1.65 -0.8089 16.5 1000 1.5727 158.96 0.6265 -3.205 1.624 -0.8088 16.24 1050 1.5718 167.01 0.6262 -3.161 1.601 -0.8088 16.01 1100 - - - - - - - 16 Table 4.7: The simulation outcomes for the silicon cell using an ARC are based on Poly- carbonate (PC) WavelengthRefractive Thickness Voc Isc Pmax FF Efﬁciency Index ((C16H14O3), 2024) 250 - - - - - - - 300 - - - - - - - 350 - - - - - - - 400 1.6255 62.52 0.6273 -3.307 1.677 -0.8084 16.77 450 1.6078 69.97 0.628 -3.39 1.719 -0.8075 17.19 500 1.597 78.27 0.6285 -3.462 1.757 -0.8075 17.57 550 1.5892 86.52 0.6288 -3.507 1.78 -0.8072 17.8 600 1.5835 94.73 0.629 -3.526 1.79 -0.8071 17.9 650 1.5791 102.91 0.629 -3.522 1.788 -0.8071 17.88 700 1.5756 111.07 0.6288 -3.498 1.775 -0.8070 17.75 750 1.5729 119.21 0.6285 -3.461 1.756 -0.8073 17.56 800 1.5707 127.33 0.6281 -3.413 1.731 -0.8075 17.31 850 1.5688 135.45 0.6277 -3.359 1.704 -0.8082 17.04 900 1.5673 143.56 0.6273 -3.304 1.675 -0.8082 16.75 950 1.566 151.66 0.6269 -3.25 1.647 -0.8084 16.47 1000 1.565 159.74 0.6265 -3.201 1.622 -0.8088 16.22 1050 1.564 167.84 0.6261 -3.157 1.599 -0.8090 15.99 1100 - - - - - - - 17 Table 4.8: The simulation outcomes for the silicon cell using an ARC are based on ZnO WavelengthRefractive Thickness Voc Isc Pmax FF Efﬁciency Index (ZnO, 2024) 250 - - - - - - - 300 - - - - - - - 350 - - - - - - - 400 - - - - - - - 450 2.1054 53.43 0.6288 -3.504 1.778 -0.8070 17.78 500 2.0516 60.93 0.6295 -3.592 1.824 -0.8067 18.24 550 2.0198 68.08 0.6298 -3.643 1.85 -0.8063 18.5 600 1.9989 75.04 0.63 -3.663 1.86 -0.8060 18.6 650 1.9843 81.89 0.6299 -3.656 1.857 -0.8064 18.57 700 1.9736 88.67 0.6297 -3.627 1.842 -0.8065 18.42 750 1.9655 95.40 0.6294 -3.582 1.819 -0.8068 18.19 800 1.9591 102.09 0.629 -3.525 1.789 -0.8069 17.89 850 1.954 108.75 0.6285 -3.463 1.757 -0.8073 17.57 900 1.9498 115.40 0.628 -3.4 1.725 -0.8079 17.25 950 1.9463 122.03 0.6276 -3.34 1.694 -0.8081 16.94 1000 1.9433 128.65 0.6272 -3.286 1.666 -0.8084 16.66 1050 1.9408 135.25 0.6268 -3.24 1.642 -0.8085 16.42 1100 1.9386 141.85 0.6268 -3.24 1.642 -0.8085 16.42 18 (a) SiO2 (b) TiO2 (c) Si3 N4 (d) MgF2 (e) Polystyrene (f) Polycarbonate (g) ZnO Figure 4.1: These ﬁgures show the relationship between the wavelength and efﬁciency for seven ARC materials From the tables above, it is evident that all results peak at a wavelength of 600 nm. Therefore, the corresponding results for this wavelength are presented in the table ?? below. 19 Table 4.9: For the Best Parameters and Efﬁciency of ARC Materials S.N. Name of Refractive Thickness Light Efﬁciency Improvement Materials Index Wavelength 1. Si3 N4 2.0149 74.45 600 18.60 % 4.46 2. TiO2 2.6049 57.58 600 17.50 % 3.36 3. SiO2 1.4580 102.88 600 17.29 % 3.15 4. ZnO 1.9989 75.04 600 18.60 % 4.46 5. Polystyrene 1.5904 94.34 600 17.92 % 3.78 (PS) 6. Polycarbonate1.5835 94.73 600 17.90 % 3.76 (PC) 7. MgF2 1.3775 108.89 600 16.79 % 2.65 In the case of Si3 N4 and ZnO, from the table we see their optimal thickness was found to be different 74.45 and 75.04 nm for this thickness maximum efﬁciency was 18.60 % achieved. At a wavelength of 600 nm, the optimal thicknesses and efﬁciencies for the anti-reﬂective coatings (ARC) of TiO2 , SiO2 , Polystyrene (PS), Polycarbonate (PC), and MgF2 in the solar cell are as follows: thicknesses of 57.58 nm, 102.88 nm, 94.34 nm, 94.73 nm, and 108.89 nm, and efﬁciencies of 17.50%, 17.29%, 17.92%, 17.90%, and 16.79%, respectively. 4.3 Double Layer as Surface Passivation Seven different anti-reﬂective coating (ARC) materials were simulated, as shown in the tables above. We have selected Si3 N4 as the bottom ARC layer for surface passivation, with SiO2 chosen as the top layer. Simulation results using PC1D indicate that the ef- ﬁciency increases to 19.02% when the thicknesses of these materials are 61.44 nm and 85.48 nm, respectively. For the double-layer anti-reﬂective coating, we selected ZnO as the bottom layer with a refractive index of 2.0516 and a thickness of 60.93 nm. The top layer is MgF2 with a refractive index of 1.3785 and a thickness of 99.75 nm. This combination results in an efﬁciency of 19.20%. 20 Table 4.10: Surface Passivation and Double layer ARC S.N.Materials Thickness Refractive Voc Isc Pmax FF Efﬁciency Index 1 SiO2 85.48 1.4623. Si3 N4 61.44 2.0344 0.6305 -3.743 1.902 -0.8059 19.02 2 MgF2 99.75 1.3785. ZnO 60.93 2.0516 0.6308 -3.778 1.92 -0.8057 19.2 4.4 Discussion From Tables 4.1 and 4.9, it is evident that the efﬁciency of solar cells has improved signif- icantly. All of the ARC exhibit strong performance at a 600 nm wavelength. Additionally, Table 4.10 shows that surface passivation and double-layer coatings further enhance efﬁ- ciency. Figure 4.1 illustrates how efﬁciency varies with different wavelengths. Based on the results of this study, it can be concluded that anti-reﬂective coatings play a crucial role in enhancing the performance of solar cells by reducing reﬂection losses. Surface passivation can be used to protect ARCs from external chemical reactions or ox- idation. Since bare silicon has a high reﬂectivity, the most effective way to reduce reﬂection is to use an ARC, which signiﬁcantly reduces the reﬂection from the wafer surface, thereby increasing the conversion efﬁciency of solar cells and improving their potential as an al- ternative energy source. However, the ﬁndings of this study do not address the self-cleaning ability of solar cells, where even small dust particles can impede sunlight from reaching the wafer surface. For a more precise design of solar cells, adjustments can be made to the thickness of the P-type and N-type layers, as well as to the doping levels in the P-type layer. 21 CHAPTER 5 5. CONCLUSION AND RECOMMENDATION 5.1 Conclusions The results we obtained from seven different ARC materials, simulated as single-layer and double-layer on c-Si solar cells using PC1D simulator software. From the literature, it has been noted that there was an enhancement in the efﬁciency of silicon solar cells by the use of ARC. In this simulation, the highest efﬁciencies achieved with a silicon solar cell coated with Si3 N4 , Tio2 , SiO2 , ZnO, Polystyrene (PS), Polycarbonate (PC), and MgF2 are 18.60%, 17.50%, 17.29%, 18.60%, 17.92%, 17.90%, 16.79% respectively. Also, the combination of MgF2 and ZnO as a double layer performs exceptionally well, achieving an efﬁciency of 19.2%. Additionally, a SiO2 surface passivation treatment was applied to the Si3 N4 ARC layer, which gives the efﬁciency of 19.02%. This simulation indicates that a range of wavelength 500-700 nm is appropriate for designing an ARC on a solar cell. The results obtained the optimal efﬁciency for all ARC materials at a wavelength of 600 nm.Si3 N4 and ZnO are the most suitable materials for use as ARC on solar cells. Finally, the use of ARC has improved the efﬁciency of the solar cell. By use of ARC improvement goes to 2-4%. The short circuit current of the solar cell is better after the use of ARC which increases the conductivity of the solar cell surface. The surface-passivated layer combined with the ARC enhances the efﬁciency of the solar cell. Simulating solar cells based on ARC materials positively impacts cost reduction and allows for proper parameter adjustments. Before actual fabrication conducting this simulation is advisable to ensure a superior result. 5.2 Novelty and National Prosperity aspect of Project work This project represents the improvement of efﬁciency and applying different ARC mate- rials on the Crystalline Silicon (c-SI) solar cell and also double layer ARC. This project reviews previous work on the related topic and presents the ﬁndings accordingly. Com- parison of analysis with past work shows similarity in the improvement of efﬁciency of solar cells. This paper also discusses the use of double-layer coatings and surface passi- vation over anti-reﬂective coatings, which function as additional layer. Silicon solar cells dominate the market and offer a longer lifespan than other types of solar cells. However, their efﬁciency is not optimal, so applying anti-reﬂective coatings on the wafer surface of solar cells signiﬁcantly enhances their performance. This paper presents solely software simulation results. While replicating these outcomes in actual fabrication is challenging due to varying parameters, using anti-reﬂective coat- ings is preferable to bare silicon solar cells. From this paper, we learn that all simulated 22 anti-reﬂective coatings perform well at a 600 nm wavelength of light and the correspond- ing thickness in the case of silicon solar cells. Given Nepal’s economic challenges and geographical diversity, producing sufﬁcient elec- tricity domestically is difﬁcult, and installing transmission lines across the country is chal- lenging. Until electricity becomes widely available, solar cells can serve as an alternative energy source this beneﬁts those living in remote areas without access to electricity. Solar cells are compact and can be transported to inaccessible areas by humans. Fabricating solar cells within Nepal could signiﬁcantly boost the economy. Anti-reﬂective coatings are relatively affordable and can be applied using various methods on solar cell. Due to the long lifespan of silicon solar cells, once installed, they can provide continuous energy for an extended period. 5.3 Limitation of the work The primary limitation of our work lies in the speciﬁc parameters we consider and apply. Although PC1D is a powerful software, it may not support complex designs. Additionally, simulations typically do not account for all environmental conditions, such as temperature ﬂuctuations, shading, and dust accumulation, which can impact the performance of solar cells in real-world applications. 5.3 Recommendations for further work In the future, the research could be expanded to include double layers with various anti- reﬂective coating materials, as well as surface passivation techniques. Additionally, fur- ther studies could explore the effects on solar cells by varying doping concentrations, changing wafer area, and adjusting thickness of the p-type and n-type layers. 23 REFERENCES Andreani, L. C., Bozzola, A., Kowalczewski, P., Liscidini, M., & Redorici, L. (2019). Silicon solar cells: toward the efﬁciency limits. Advances in Physics: X, 4(1), 1548305. doi: 10.1080/23746149.2018.1548305 Basu, P., Pujahari, R., Kaur, H., Singh, D., Varandani, D., & Mehta, B. (2010). Im- pact of surface roughness on the electrical parameters of industrial high efﬁciency naohnaocl textured multicrystalline silicon solar cell. Solar Energy, 84(9), 1658- 1665. (C16H14O3), R. I. P. (2024). Refractiveindex.info. Retrieved from https:// refractiveindex.info/?shelf=organic&book=polycarbonate&page= Sultanova (Accessed: August 7, 2024) (C8H8), R. I. P. (2024). Refractiveindex.info. Retrieved from https:// refractiveindex.info/?shelf=organic&book=polystyrene&page= Sultanova (Accessed: August 7, 2024) Chapin, D. M., Fuller, C. S., & Pearson, G. L. (1954). A new silicon pn junction photocell for converting solar radiation into electrical power. Journal of Applied Physics, 25(5), 676-677. doi: 10.1063/1.1721711 Cid, M., Stem, N., Brunetti, C., Beloto, A. F., & Ramos, C. A. S. (1998). Improvements in anti-reﬂection coatings for high-efﬁciency silicon solar cells. Surface and Coatings Technology, 106, 117-120. doi: 10.1016/S0257-8972(98)00499-X Education, P. (n.d.). Anti-reﬂection coatings. https://www.pveducation.org/ pvcdrom/design-of-silicon-cells/anti-reflection-coatings. (Ac- cessed: 2024-08-08) Education, P. (2024). Arc thickness calculator. Retrieved from https://www.pveducation.org/calculators/arc-thickness (Accessed: 2024-08-08) Hashmi, G., Rashid, M. J., Mahmood, Z. H., Hoq, M., & Rahman, M. H. (2018). In- vestigation of the impact of different arc layers using pc1d simulation: application to crystalline silicon solar cells. Journal of Theoretical and Applied Physics, 12, 327–334. Introduction to photovoltaics. (n.d.). Retrieved from https://www.pveducation.org/ pvcdrom/introduction/introduction (Accessed: 2024-08-08) Jabbar, R. I. (2020). Modeling and analysis of different antireﬂection polymer coating on silicon solar cell using pc1d software. Journal of Mechanical Engineering Research and Developments, 43(7), 222-232. Mandong, A.-M. (2018). Design and simulation of single, double, and multi-layer an- tireﬂection coating for crystalline silicon solar cell (Unpublished master’s thesis). Karadeniz Technical University, Trabzon, Turkey. (Supervisor: Dr. Ör. Üyesi Ab- 24 dullah ÜZÜM) MgF2, R. I. (2024). Refractiveindex.info. Retrieved from https://refractiveindex.info/?shelf=main&book=MgF2&page=Li-o (Accessed: August 7, 2024) Moona, G., Kapruwan, P., & Sharma, R. (2018). Silicon wafer surface reﬂectance in- vestigations by using different surface texturing parameters. Proceedings of the National Academy of Sciences, India Section A: Physical Sciences, 88, 617–623. doi: 10.1007/s40010-017-0384-3 Passivation deﬁnition. (n.d.). Retrieved from https://shopsolarkits.com/pages/ passivation-definition. (Accessed: 2024-08-08) PV Education. (n.d.). Solar energy. Retrieved from https://www.pveducation.org/ pvcdrom/introduction/solar-energy (Accessed: 2024-08-08) Shanmugam, N., Pugazhendhi, R., Elavarasan, R. M., Kasiviswanathan, P., & Das, N. (2020). Anti-reﬂective coating materials: A holistic review from pv perspec- tive. Energies, 13(10), 2631. Retrieved from https://www.mdpi.com/journal/ energies doi: 10.3390/en13102631 Sharma, R., Gupta, A., & Virdi, A. (2017). Effect of single and double layer antireﬂection coating to enhance photovoltaic efﬁciency of silicon solar. Journal of Nano- and Electronic Physics, 9(2), 02001. doi: 10.21272/jnep.9(2).02001 Si3N4, R. I. (2024). Refractiveindex.info. Retrieved from https://refractiveindex.info/?shelf=main&book=Si3N4&page=Philipp (Accessed: August 7, 2024) Sio2, R. I. (2024). Refractiveindex.info. Retrieved from https://refractiveindex.info/ (Accessed: August 7, 2024) Subramanian, M., Aldossary, O. M., Alam, M., Ubaidullah, M., Gedi, S., Vaduganathan, L.,... Mekhilef, S. (2021). Optimization of antireﬂection coating design us- ing pc1d simulation for c si solar cell application. Electronics, 10(24). Re- trieved from https://www.mdpi.com/2079-9292/10/24/3132 doi: 10.3390/ electronics10243132 Swanson, R. M. (2006). A vision for crystalline silicon photovoltaics. Progress in Photovoltaics: Research and Applications, 14(5), 443-453. doi: 10.1002/pip.709 TiO2, R. I. (2024). Refractiveindex.info. Retrieved from https://refractiveindex.info/?shelf=main&book=TiO2&page=Devore-o (Accessed: August 7, 2024) ZnO, R. I. (2024). Refractiveindex.info. Retrieved from https://refractiveindex.info/?shelf=main&book=ZnO&page=Bond-o (Accessed: August 7, 2024) 25 APPENDIX 26

TU Project Work: Simulation of Anti-reflective Coating on Crystalline Silicon Solar Cell using PC1D PDF

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