Asadul Islam Shimul*, Avijit Ghosh, Md Ferdous Ahmed, Agnita Sikder Mugdho, Zayadul Hasan, Nasser S. Awwad and Hala A. Ibrahium,
{"title":"利用不同电荷输运材料的机器学习和数值模拟研究Mg3AsBr3钙钛矿太阳能电池的光电特性和提高效率","authors":"Asadul Islam Shimul*, Avijit Ghosh, Md Ferdous Ahmed, Agnita Sikder Mugdho, Zayadul Hasan, Nasser S. Awwad and Hala A. Ibrahium, ","doi":"10.1021/acs.langmuir.5c0182110.1021/acs.langmuir.5c01821","DOIUrl":null,"url":null,"abstract":"<p >This study investigates the optoelectronic characteristics of cubic perovskite Mg<sub>3</sub>AsBr<sub>3</sub> for photovoltaic (PV) applications through first-principles density functional theory (DFT), driven by the increasing interest in perovskites for renewable energy solutions. Mg<sub>3</sub>AsBr<sub>3</sub> is explored as an absorber layer in conjunction with Cu<sub>2</sub>O as the hole transport layer (HTL) and various electron transport layers (ETLs), specifically WS<sub>2</sub>, ZnO, PC<sub>60</sub>BM, and C<sub>60</sub>. SCAPS-1D simulations were employed to optimize parameters including doping concentration, layer thickness, and defect density in the charge transport and absorber layers. The results show significant variations in power conversion efficiency (PCE) depending on the ETL choice. The Al/FTO/WS<sub>2</sub>/Mg<sub>3</sub>AsBr<sub>3</sub>/Cu<sub>2</sub>O/Au configuration exhibited the optimal performance, achieving a <i>V</i><sub>OC</sub> of 1.03 V, an FF of 88.06%, a PCE of 32.55%, and a <i>J</i><sub>SC</sub> of 36.01 mA/cm<sup>2</sup>. Configurations utilizing ZnO, PC<sub>60</sub>BM, and C<sub>60</sub> as ETLs attained PCE of 32.47, 32.21, and 31.63%, respectively. This underscores the significance of choosing the appropriate ETL for optimal perovskite solar cell (PSC) performance. The study assesses aspects including band alignment, defect density, doping concentration, and series-shunt resistances that affect device efficiency and durability. The SCAPS-1D results were validated against wxAMPS simulations, and a machine learning model was created, forecasting essential performance metrics with 84% accuracy. The proposed optimized configurations improve the efficiency and sustainability of PSCs.</p>","PeriodicalId":50,"journal":{"name":"Langmuir","volume":"41 21","pages":"13655–13674 13655–13674"},"PeriodicalIF":3.9000,"publicationDate":"2025-05-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Investigating Optoelectronic Characteristics and Improving the Efficiency of Mg3AsBr3 Perovskite Solar Cells through Machine Learning and Numerical Simulations Utilizing Diverse Charge Transport Materials\",\"authors\":\"Asadul Islam Shimul*, Avijit Ghosh, Md Ferdous Ahmed, Agnita Sikder Mugdho, Zayadul Hasan, Nasser S. Awwad and Hala A. Ibrahium, \",\"doi\":\"10.1021/acs.langmuir.5c0182110.1021/acs.langmuir.5c01821\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p >This study investigates the optoelectronic characteristics of cubic perovskite Mg<sub>3</sub>AsBr<sub>3</sub> for photovoltaic (PV) applications through first-principles density functional theory (DFT), driven by the increasing interest in perovskites for renewable energy solutions. Mg<sub>3</sub>AsBr<sub>3</sub> is explored as an absorber layer in conjunction with Cu<sub>2</sub>O as the hole transport layer (HTL) and various electron transport layers (ETLs), specifically WS<sub>2</sub>, ZnO, PC<sub>60</sub>BM, and C<sub>60</sub>. SCAPS-1D simulations were employed to optimize parameters including doping concentration, layer thickness, and defect density in the charge transport and absorber layers. The results show significant variations in power conversion efficiency (PCE) depending on the ETL choice. The Al/FTO/WS<sub>2</sub>/Mg<sub>3</sub>AsBr<sub>3</sub>/Cu<sub>2</sub>O/Au configuration exhibited the optimal performance, achieving a <i>V</i><sub>OC</sub> of 1.03 V, an FF of 88.06%, a PCE of 32.55%, and a <i>J</i><sub>SC</sub> of 36.01 mA/cm<sup>2</sup>. Configurations utilizing ZnO, PC<sub>60</sub>BM, and C<sub>60</sub> as ETLs attained PCE of 32.47, 32.21, and 31.63%, respectively. This underscores the significance of choosing the appropriate ETL for optimal perovskite solar cell (PSC) performance. The study assesses aspects including band alignment, defect density, doping concentration, and series-shunt resistances that affect device efficiency and durability. The SCAPS-1D results were validated against wxAMPS simulations, and a machine learning model was created, forecasting essential performance metrics with 84% accuracy. 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Investigating Optoelectronic Characteristics and Improving the Efficiency of Mg3AsBr3 Perovskite Solar Cells through Machine Learning and Numerical Simulations Utilizing Diverse Charge Transport Materials
This study investigates the optoelectronic characteristics of cubic perovskite Mg3AsBr3 for photovoltaic (PV) applications through first-principles density functional theory (DFT), driven by the increasing interest in perovskites for renewable energy solutions. Mg3AsBr3 is explored as an absorber layer in conjunction with Cu2O as the hole transport layer (HTL) and various electron transport layers (ETLs), specifically WS2, ZnO, PC60BM, and C60. SCAPS-1D simulations were employed to optimize parameters including doping concentration, layer thickness, and defect density in the charge transport and absorber layers. The results show significant variations in power conversion efficiency (PCE) depending on the ETL choice. The Al/FTO/WS2/Mg3AsBr3/Cu2O/Au configuration exhibited the optimal performance, achieving a VOC of 1.03 V, an FF of 88.06%, a PCE of 32.55%, and a JSC of 36.01 mA/cm2. Configurations utilizing ZnO, PC60BM, and C60 as ETLs attained PCE of 32.47, 32.21, and 31.63%, respectively. This underscores the significance of choosing the appropriate ETL for optimal perovskite solar cell (PSC) performance. The study assesses aspects including band alignment, defect density, doping concentration, and series-shunt resistances that affect device efficiency and durability. The SCAPS-1D results were validated against wxAMPS simulations, and a machine learning model was created, forecasting essential performance metrics with 84% accuracy. The proposed optimized configurations improve the efficiency and sustainability of PSCs.
期刊介绍:
Langmuir is an interdisciplinary journal publishing articles in the following subject categories:
Colloids: surfactants and self-assembly, dispersions, emulsions, foams
Interfaces: adsorption, reactions, films, forces
Biological Interfaces: biocolloids, biomolecular and biomimetic materials
Materials: nano- and mesostructured materials, polymers, gels, liquid crystals
Electrochemistry: interfacial charge transfer, charge transport, electrocatalysis, electrokinetic phenomena, bioelectrochemistry
Devices and Applications: sensors, fluidics, patterning, catalysis, photonic crystals
However, when high-impact, original work is submitted that does not fit within the above categories, decisions to accept or decline such papers will be based on one criteria: What Would Irving Do?
Langmuir ranks #2 in citations out of 136 journals in the category of Physical Chemistry with 113,157 total citations. The journal received an Impact Factor of 4.384*.
This journal is also indexed in the categories of Materials Science (ranked #1) and Multidisciplinary Chemistry (ranked #5).