Machine Learning-Assisted Prediction of Ambient-Processed Perovskite Solar Cells’ Performances DOI Creative Commons
Dowon Pyun, Seungtae Lee, Solhee Lee

et al.

Energies, Journal Year: 2024, Volume and Issue: 17(23), P. 5998 - 5998

Published: Nov. 28, 2024

As we move towards the commercialization and upscaling of perovskite solar cells, it is essential to fabricate them in ambient environment rather than conventional glove box environment. The efficiency ambient-processed cells lags behind those fabricated controlled environments, primarily owing external environmental factors such as humidity temperature. In case device fabrication relying solely on a single parameter, temperature or humidity, insufficient for accurately characterizing conditions. Therefore, dew point introduced parameter which accounts both humidity. this study, machine learning model was developed predict based meteorological data, particularly point. A total 238 were fabricated, their photovoltaic parameters points collected from March December 2023. data used train various tree-based models, with random forest achieving highest accuracy. efficiencies January February 2024 predicted MAPE 4.44%. An additional Shapley Additive exPlanations analysis confirmed significance performance cells.

Language: Английский

Key degradation mechanisms of perovskite solar cells and strategies for enhanced stability: issues and prospects DOI Creative Commons
Md. Helal Miah, Md. Bulu Rahman, Mohammad Nur‐E‐Alam

et al.

RSC Advances, Journal Year: 2025, Volume and Issue: 15(1), P. 628 - 654

Published: Jan. 1, 2025

Insights into the factors and mechanisms of degradation, along with potential solutions.

Language: Английский

Citations

1
Chalcogenide perovskites: enticing prospects across a wide range of compositions and optoelectronic properties for stable photodetector devices DOI Creative Commons

Shilpa Mariam Samuel,

Sadasivan Shaji, David Avellaneda Avellaneda

et al.

Nano Express, Journal Year: 2025, Volume and Issue: 6(1), P. 015002 - 015002

Published: Jan. 13, 2025

Abstract Photodetectors are indispensable components of many modern light sensing and imaging devices, converting photon energy into processable electrical signal through absorption, carrier generation extraction using semiconducting thin films with appropriate optoelectronic properties. Recently, metal halide perovskites have demonstrated groundbreaking photodetector performance due to their exceptional properties originating from perovskite structure. However, toxicity stability remain challenges for large-scale applications. Inspired by the structure, intense investigation in search highly stable, non-toxic earth abundant materials superior features has led discovery chalcogenide (CPs). These unconventional semiconductors formula ABX 3 , where A B cations X is a chalcogen, which covers compounds corner sharing structures type II-IV- VI (II = Ba, Sr, Ca, Eu; IV Zr, Hf; S, Se) III 1 -III 2 -VI (III Lanthanides, Y, Sc; Se). The increased coordination ionicity these contribute excellent charge transport exceptionally high optical absorption coefficient (> 10 5 cm −1 ). present review encompasses theoretical analysis that provides electronic band orbital contributions support Furthermore, challenging film deposition, characterizations, application photodetection focusing on BaZrS -which most studied one, ascribed. Additionally, we suggest prospects can bring out true potential photovoltaics.

Language: Английский

Citations

0
Numerical and Experimental Validation of CsPbBr3 Perovskite Solar Cells: Insights on a One-Step Deposition Technique DOI

Soumya Sundar Parui,

K. Vijayan,

Nithin Xavier

et al.

The Journal of Physical Chemistry C, Journal Year: 2025, Volume and Issue: unknown

Published: April 11, 2025

Language: Английский

Citations

0
Exploring the Effect of Nonideal Conditions in Perovskite Solar Cells Performance Using Numerical Simulations DOI
Sutapa Dey,

Mrittika Paul,

Shivam Porwal

et al.

physica status solidi (a), Journal Year: 2025, Volume and Issue: unknown

Published: April 20, 2025

Non‐radiative recombination plays a crucial role in perovskite solar cells, restricting their performance considerably lower than the Shockley‐Queisser limit. Herein, at first, CsPbI 3 ‐based cell configuration is optimized by varying thickness, doping, and defect density of each layer. Then, device investigated under different non‐ideal conditions Auger radiative coefficients employing capacitance simulator‐1D simulation. The observations suggest that notably deteriorates when exceed 10‐24 cm 6 s −1 . Further, variation acceptor concentration significantly impacts J SC , changing 0.6 to 24.2% moderate (10–24 ) high (10–20 recombination, compared low (10–30 effect. In contrast, relatively small variations are observed V OC As result, for an 1016 −3 efficiency abruptly changes from 18.30 17.36% finally 7.77%, respectively, low, moderate, effects. findings offer comprehensive perception consequences on outcomes. this detailed discussion enhancement might also be beneficial addressing issue current mismatch, which remains significant challenge Si/perovskite tandem cells.

Language: Английский

Citations

0
Dual-functional passivation on highly-efficient air-processed FAPbI₃ perovskite solar cells fabricated under high humidity without auxiliary equipment DOI Creative Commons
Bo‐Tau Liu, Huan Su, I−Ru Chen

et al.

Applied Surface Science Advances, Journal Year: 2024, Volume and Issue: 25, P. 100683 - 100683

Published: Dec. 24, 2024

Language: Английский

Citations

1
Design of Ternary metal oxides for Photoelectrochemical Water Splitting using Machine Learning Techniques DOI
Snehangshu Mishra, Prince Kumar, Sutapa Dey

et al.

Journal of environmental chemical engineering, Journal Year: 2024, Volume and Issue: unknown, P. 115260 - 115260

Published: Dec. 1, 2024

Language: Английский

Citations

1
Design of Ternary Metal Oxides for Photoelectrochemical Water Splitting Using Machine Learning Techniques DOI
Snehangshu Mishra, Prince Kumar, Sutapa Dey

et al.

Published: Jan. 1, 2024

Language: Английский

Citations

0
On the Vegard’s law compliance for CsxFA(1-x)PbI3 perovskite thin films DOI Creative Commons
D. Mateus Torres‐Herrera,

Olaf Ramírez-Iturbe,

Rosa Nava-Sánchez

et al.

Physica Scripta, Journal Year: 2024, Volume and Issue: 99(9), P. 095962 - 095962

Published: Aug. 8, 2024

Abstract Perovskite-based solar cells (PSCs) have demonstrated remarkable high power conversion efficiency in recent years. However, the use of mono-organic cations (such as Methylammonium or Formamidinium) limits potential for large-scale development due to degradation under environmental conditions. The incorporation multi-cations has emerged a strategy enhance both performance and stability. cesium (Cs) cation represents solid alternative partial substitution Formamidinium. initial concentration precursors solution is often reported without establishing final present thin films. Herein, Cs into FAPbI 3 structure produce x FA (1-x) PbI perovskite with different values using one-step spin coating process demonstrated. Assessing structural optical properties, it that films behave according Vegard’s law between 0 0.66. In particular, , an 0.33 exhibits cubic lattice parameter 6.28 Å, lower than but higher CsPbI . This showed stability dark phase ambient conditions extended periods. addition, this material bandgap 1.5 eV, making suitable cells.

Language: Английский

Citations

0
Machine Learning-Assisted Prediction of Ambient-Processed Perovskite Solar Cells’ Performances DOI Creative Commons
Dowon Pyun, Seungtae Lee, Solhee Lee

et al.

Energies, Journal Year: 2024, Volume and Issue: 17(23), P. 5998 - 5998

Published: Nov. 28, 2024

As we move towards the commercialization and upscaling of perovskite solar cells, it is essential to fabricate them in ambient environment rather than conventional glove box environment. The efficiency ambient-processed cells lags behind those fabricated controlled environments, primarily owing external environmental factors such as humidity temperature. In case device fabrication relying solely on a single parameter, temperature or humidity, insufficient for accurately characterizing conditions. Therefore, dew point introduced parameter which accounts both humidity. this study, machine learning model was developed predict based meteorological data, particularly point. A total 238 were fabricated, their photovoltaic parameters points collected from March December 2023. data used train various tree-based models, with random forest achieving highest accuracy. efficiencies January February 2024 predicted MAPE 4.44%. An additional Shapley Additive exPlanations analysis confirmed significance performance cells.

Language: Английский

Citations

0