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© 2026 IJSREM – International Journal of Scientific Research in Engineering and Management. This is an open-access journal. Articles are published under the Creative Commons Attribution (CC BY 4.0) License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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Paper ID:10.55041/IJSREM.NEP028

Mathematical Modeling of Perovskite Solar Cells for Efficient Energy Harvesting

Stream/Area:

-

Subject:

-

Paper ID:

10.55041/IJSREM.NEP028

Volume:

10 |

5 |

May 2026

Pages:

1-12

Publication Frequency:

Monthly (12 issues per year)

DOI
Digital Object Identifier
10.55041/ijsrem.NEP028

License:International Journal of Scientific Research in Engineering and Management follows the Creative Commons Attribution 4.0 (CC BY 4.0) License, allowing free use and distribution with proper attribution.

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Authors

DJSK

Dr J Sravan Kumar

Assistant Professor of Mathematics

Government Degree College Gambhiraopet

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Abstract

Perovskite solar cells (PSC) have become a groundbreaking photovoltaic cell because they are considered to possess a high power conversion efficiency (PCE), low fabrication cost and tunable optoelectronic behavior. The mathematical modeling is essential in the processes of learning the dynamics of charge transport, recombination, and effects of ion migration alongside optimization of performance of PSCs. This paper is a complete mathematical model that combines Poisson equation, carrier continuity equations and drift argument equations to model electrical behavior of perovskite solar cases when illuminated. The model also uses the trap-assisted recombination, interfacial charge transfer resistance, and ion migration effects to enhance the accuracy of prediction. The simulation results show the effect of absorber thickness, defect density and mobility, and temperature on the efficiency of a device. The analysis done in terms of optimization shows that the density of controlled defects (= -10 7 cm -1 ), the optimized thickness of the layer (= 500-700 nm), and better carrier mobility are significant factors in optimizing energy harvesting. Nevertheless, applied constraints like long history material unsteadiness and sensitivity to water and magnet influences and expandability complications restrain business applications. Other physical processes that are not considered by the proposed model are the assumption of uniform material characteristics and unreality of complicated grain-boundary dynamics that can influence precision in the real world. To facilitate the adoption of PSC technology by industries, future studies must concentrate on multi-physics coupled modeling (electrical-thermal-mechanical), the use of degradation aware predictive modeling, AI-based integrated optimization structures, and scalable module-scale simulations.

KEYWORDS

Perovskite Solar Cells Mathematical Modeling Drift–Diffusion Model Charge Transport Power Conversion Efficiency Energy Harvesting Optimization Ion Migration Recombination Dynamics.

Cite This Article

Dr J Sravan Kumar, "Mathematical Modeling of Perovskite Solar Cells for Efficient Energy Harvesting," International Journal of Scientific Research in Engineering and Management, vol. 10, no. 5, pp. 1-12, May 2026. https://doi.org/10.55041/ijsrem.NEP028

Full Article/Conclusion

This paper has provided an overarching mathematical model of the processes to be in place in the modeling of perovskite solar cells through the use of coupled Poisson, continuity, and drift, and diffusion equations. The model was able to examine how the photovoltaic performance is affected by the absorber thickness, carrier mobility, density of defects and temperature. Simulation Purposes Mirror simulation models show that a controlled defect density, ideal thickness (approximately 600 nm), and carrier mobility increase energy capture in a vastly greater way, and obtain power conversion efficiencies of high-performance (more than 22% at ideal conditions). Although some promising results are evident, practical constraints owing to material instability, hysteris caused by ion migration, sensitivity to moisture, interfaces degradation and scalability are key setbacks in commercialization. The model also makes a number of assumptions including, but not limited to, a uniformity of the material and steady-state conditions in operation that are not necessarily realistic in the behaviour of a device. Some direction to be taken in future should involve: ·         Electro-thermal modeling Multi-physics. ·         Lifetime prediction models based on degrees of degradation. ·         Optimization of parameters with the help of AI. ·         Grain boundary and interface based modeling. ·         Do large areas back volume simulation and module-level simulation. ·         Combination with parallel building solar cells. The development of mathematical modeling models will hasten the process of transforming the perovskite solar cells development into commercially effective and high-energy yields of renewable energy technology.

References

[1]     N. U. A. Ahmed, P. Lamberti, and V. Tucci, “A science mapping analysis of computational methods and exploration of electrical transport studies in solar cells,” Materials, vol. 19, no. 3, p. 452, Jan. 2026, doi: 10.3390/ma19030452. [2]     S. Raja, V. S. Sujitha, D. Yakkala, M. R. A. Refaai, and O. A. Adebimpe, “Energy-harvesting cementitious materials for sustainable infrastructure: a critical review of piezoelectric, thermoelectric, and photovoltaic mechanisms,” Innovative Infrastructure Solutions, vol. 11, no. 2, Jan. 2026, doi: 10.1007/s41062-025-02445-5. [3]     C. Kuchi, R. M. N. Kalla, Y. A. Kumar, A. G. Al-Sehemi, E. Ravindran, and S. K. Chilaka, “2D layered perovskites: stability, tunability, and their role in next-generation solar energy conversion,” Journal of Materials Science, vol. 61, no. 6, pp. 3577–3615, Jan. 2026, doi: 10.1007/s10853-025-11886-3. [4]     Y. Chen et al., “Recent advances in piezoelectric and triboelectricnanogenerators for ocean current energy harvesting,” Journal of Marine Science and Engineering, vol. 14, no. 3, p. 249, Jan. 2026, doi: 10.3390/jmse14030249. [5]     Nag and D. Chaudhuri, “Advances in nanomaterials for energy and sensing applications: from fundamentals to device,” Discover Electronics, vol. 3, no. 1, Jan. 2026, doi: 10.1007/s44291-026-00165-3. [6]     P. Jiang, K. He, N. Li, L. Xu, and H. Zhan, “A review of the Low-Carbon Transformation Path of Buildings driven by Renewable Energy: Challenges and Optimization of Energy-Efficient Utilization,” Buildings, vol. 16, no. 4, p. 817, Feb. 2026, doi: 10.3390/buildings16040817. [7]     K. J. Chaudhary, M. L. Chaudhary, R. Patel, and R. K. Gupta, “Recent trends in advanced nanomaterials for potential photovoltaic applications,” in Handbook of Energy Materials, 2026, pp. 1177–1202. doi: 10.1007/978-981-95-2947-6_32. [8]     M. Al-Mandhari, O. Cowdall, and A. Ghosh, “Challenges and advancements in direct solar PV to water electrolyser technology for hydrogen production,” Sustainability, vol. 18, no. 4, p. 2089, Feb. 2026, doi: 10.3390/su18042089. [9]     P. Pandey, H.-G. Lim, and D.-W. Kang, “Silver–Tin Sulfide/Selenide semiconductor for Super-Narrow-Bandgapphotovoltaics and Thermoelectric applications: A review,” Energies, vol. 19, no. 4, p. 1029, Feb. 2026, doi: 10.3390/en19041029. [10] H. M. Rizwan, N. Sultan, S. Rafiq, Z. Zubair, and M. R. S. A. Janjua, “Shaping the future of photovoltaics: advances in Non-Fullerene acceptors and tandem organic solar cells,” Brazilian Journal of Physics, vol. 56, no. 2, Jan. 2026, doi: 10.1007/s13538-025-01998-1.

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Publication Date

6/9/2026

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Review Rounds: 2

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