Investigating Optoelectronic Characteristics and Improving the Efficiency of Mg3AsBr3 Perovskite Solar Cells through Machine Learning and Numerical Simulations Utilizing Diverse Charge Transport Materials DOI

Asadul Islam Shimul,

Avijit Ghosh, Maqsood Ahmed

et al.

Langmuir, Journal Year: 2025, Volume and Issue: unknown

Published: May 20, 2025

This study investigates the optoelectronic characteristics of cubic perovskite Mg3AsBr3 for photovoltaic (PV) applications through first-principles density functional theory (DFT), driven by increasing interest in perovskites renewable energy solutions. is explored as an absorber layer conjunction with Cu2O hole transport (HTL) and various electron layers (ETLs), specifically WS2, ZnO, PC60BM, C60. SCAPS-1D simulations were employed to optimize parameters including doping concentration, thickness, defect charge layers. The results show significant variations power conversion efficiency (PCE) depending on ETL choice. Al/FTO/WS2/Mg3AsBr3/Cu2O/Au configuration exhibited optimal performance, achieving a VOC 1.03 V, FF 88.06%, PCE 32.55%, JSC 36.01 mA/cm2. Configurations utilizing C60 ETLs attained 32.47, 32.21, 31.63%, respectively. underscores significance choosing appropriate solar cell (PSC) performance. assesses aspects band alignment, density, series-shunt resistances that affect device durability. validated against wxAMPS simulations, machine learning model was created, forecasting essential performance metrics 84% accuracy. proposed optimized configurations improve sustainability PSCs.

Language: Английский

Examining the contribution of charge transport layers to boost the performance over 26% in Sr3PCl3 absorber-based bifacial perovskite solar cells DOI Creative Commons

Asadul Islam Shimul,

Avijit Ghosh, Subrata Sarker

et al.

RSC Advances, Journal Year: 2025, Volume and Issue: 15(10), P. 7663 - 7681

Published: Jan. 1, 2025

Strontium phosphorus chloride (Sr 3 PCl ) presents a promising option for photovoltaic (PV) applications due to its distinctive optical, electrical, and structural characteristics.

Language: Английский

Citations

3
Exploring the Influence of Hydrostatic Pressure on the Structural and Optoelectronic Behavior of Cubic A3PCl3 (A = Mg, Ca) Perovskite for Solar Cell Applications DOI

Asadul Islam Shimul,

Md. Mahfuzul Haque, Avijit Ghosh

et al.

Optics Communications, Journal Year: 2025, Volume and Issue: unknown, P. 131807 - 131807

Published: March 1, 2025

Language: Английский

Citations

3
Machine Learning‐Based Optimization and Performance Enhancement of CH3NH3SnBr3 Perovskite Solar Cells with Different Charge Transport Materials Using SCAPS‐1D and wxAMPS DOI Open Access

Asadul Islam Shimul,

Mahfuz Alam Khan,

Abu Rayhan

et al.

Advanced Theory and Simulations, Journal Year: 2025, Volume and Issue: unknown

Published: March 25, 2025

Abstract Recent research focuses on enhancing the sustainability of perovskite solar cells (PSCs) by substituting lead with non‐toxic materials, identifying tin‐based perovskites such as CH 3 NH SnBr a viable alternative. This study examines efficacy absorber layer in conjunction V 2 O 5 hole transport (HTL) and several electron layers (ETLs), including C 60 , IGZO, WS ZnSe. The employs SCAPS‐1D simulations to optimize parameters doping concentration, thickness, defect density, aiming improve photovoltaic efficiency. optimal configuration (FTO/WS /CH /V /Au) attained power conversion efficiency (PCE) 33.54%, surpassing alternative ETL combinations. results simulation are analyzed comparison those wxAMPS simulation. machine learning model is developed predict cell performance, achieving an accuracy 82%. findings underscore significance choosing appropriate enhance PSC sustainability.

Language: Английский

Citations

2
Study of physical properties of novel perovskite FrJCl3 (J = Be, Mg) materials: DFT predictions for photovoltaic applications DOI
Shoukat Hussain, Abhinav Kumar, Soumaya Gouadria

et al.

Journal of Materials Science Materials in Electronics, Journal Year: 2025, Volume and Issue: 36(11)

Published: April 1, 2025

Language: Английский

Citations

1
Investigating the effectiveness of Ca3AsCl3-based Perovskite Solar Cells with optimal hole transport layer selection through numerical optimization and machine learning DOI

Asadul Islam Shimul,

Md Maruf Hossain,

Safia Aktar Dipa

et al.

Optics Communications, Journal Year: 2025, Volume and Issue: unknown, P. 131916 - 131916

Published: April 1, 2025

Language: Английский

Citations

0
Optimizing parameters to enhance photovoltaic performance of Ce1-AZnAO2/ CeMnO2/MAFASnBrI/BaSi2 Solar Cells DOI

Ravi Pushkar,

Amit Prakash, Raushan Kumar

et al.

Optics Communications, Journal Year: 2025, Volume and Issue: unknown, P. 131959 - 131959

Published: May 1, 2025

Language: Английский

Citations

0
Investigating Optoelectronic Characteristics and Improving the Efficiency of Mg3AsBr3 Perovskite Solar Cells through Machine Learning and Numerical Simulations Utilizing Diverse Charge Transport Materials DOI

Asadul Islam Shimul,

Avijit Ghosh, Maqsood Ahmed

et al.

Langmuir, Journal Year: 2025, Volume and Issue: unknown

Published: May 20, 2025

This study investigates the optoelectronic characteristics of cubic perovskite Mg3AsBr3 for photovoltaic (PV) applications through first-principles density functional theory (DFT), driven by increasing interest in perovskites renewable energy solutions. is explored as an absorber layer conjunction with Cu2O hole transport (HTL) and various electron layers (ETLs), specifically WS2, ZnO, PC60BM, C60. SCAPS-1D simulations were employed to optimize parameters including doping concentration, thickness, defect charge layers. The results show significant variations power conversion efficiency (PCE) depending on ETL choice. Al/FTO/WS2/Mg3AsBr3/Cu2O/Au configuration exhibited optimal performance, achieving a VOC 1.03 V, FF 88.06%, PCE 32.55%, JSC 36.01 mA/cm2. Configurations utilizing C60 ETLs attained 32.47, 32.21, 31.63%, respectively. underscores significance choosing appropriate solar cell (PSC) performance. assesses aspects band alignment, density, series-shunt resistances that affect device durability. validated against wxAMPS simulations, machine learning model was created, forecasting essential performance metrics 84% accuracy. proposed optimized configurations improve sustainability PSCs.

Language: Английский

Citations

0