Laser Micro-Texturing and AI-Driven Optimization for Thermal Management of Photovoltaic Systems
DOI:
https://doi.org/10.15421/cims.4.320Keywords:
laser micro-texturing, renewable energy devices, photovoltaic cooling, thermal management, artificial intelligence, optimizationAbstract
Purpose. Photovoltaic (PV) and other renewable systems suffer efficiency and reliability losses from overheating. This review emphasizes the need for scalable, integrated thermal management solutions. Design / Method / Approach. The paper evaluates recent advances in laser-based surface micro-texturing as a promising strategy for thermal regulation. Controlled micro/nano-scale structures enhance heat dissipation, expand surface area, and tune wettability. The study also explores the role of artificial intelligence (AI) in predicting, designing, and optimizing laser-induced textures for simultaneous improvements in thermal, optical, and mechanical durability. Findings. Laser-processed surfaces provide multifunctional benefits such as enhanced convective cooling, anti-reflection, and self-cleaning, but most demonstrations remain confined to laboratory scale. AI methods including neural networks, evolutionary algorithms, and reinforcement learning show strong predictive capability and multi-objective optimization potential, offering pathways for industrial adoption. Theoretical Implications. The review establishes links between surface morphology, thermo-fluid dynamics, and optical behavior, and shows how AI-enabled digital twins can extend these relationships into predictive, generalized models. It also highlights opportunities for modelling coupled thermo-optical effects and advancing data-driven surface engineering. Practical Implications. Integrating laser texturing with AI-driven optimization could embed thermal regulation directly into device structures, reducing reliance on external cooling systems and improving field durability. Originality / Value. Unlike prior reviews, this work unites laser surface engineering and AI optimization into a roadmap for renewable energy devices, highlighting digital twins and techno-economic assessment as enablers for scale-up. Research Limitations / Future Research. Challenges include scalability, durability under harsh environments, limited AI training datasets, and insufficient lifecycle analyses, requiring cross-disciplinary collaboration. Article Type. Review Paper.
Downloads
References
Agostinelli, S., Ciulla, G., Salemi, A., & Borchiellini, R. (2021). Cyber-physical systems improving building energy management: Digital twin and artificial intelligence. Energies, 14(8), 2338. https://doi.org/10.3390/en14082338
Alao, K. T., Shittu, A., Zhang, Y., & Chen, L. (2025). Multi-method cooling strategies for photovoltaic systems: A comprehensive review of passive, active, and AI-optimized hybrid techniques. Multiscale and Multidisciplinary Modeling, Experiments and Design, 8(8), 1–42. https://doi.org/10.1007/s41939-025-00941-w
Alqatamin, A., & Su, J. (2025). Numerical analysis and design of photovoltaic-thermal (PVT) system with novel water-cooling channel structure integrated with perforated V-shape fins. Renewable Energy, 243, 122587. https://doi.org/10.1016/j.renene.2025.122587
Al-Shamkhee, D., Ahmed, S., Kadhim, A., & Ali, H. (2022). Passive cooling techniques for ventilation: An updated review. Renewable Energy and Environmental Sustainability, 7, 23. https://doi.org/10.1051/rees/2022011
Al-Ugla, A. A., Bin Mahfouz, A. A., Said, S. A. M., & Al-Sulaiman, F. A. (2016). Techno-economic analysis of solar-assisted air-conditioning systems for commercial buildings in Saudi Arabia. Renewable and Sustainable Energy Reviews, 54, 1301–1310. https://doi.org/10.1016/j.rser.2015.10.047
Andueza, Á., Zubia, J., Arrue, J., & Illarramendi, M. A. (2021). Enhanced thermal performance of photovoltaic panels based on glass surface texturization. Optical Materials, 121, 111511. https://doi.org/10.1016/j.optmat.2021.111511
Ascencio-Vásquez, J., Köntges, M., Morales, D., & Gutiérrez, J. (2019). Global climate data processing and mapping of degradation mechanisms and degradation rates of PV modules. Energies, 12(24), 4749. https://doi.org/10.3390/en12244749
Asfahan, H. M., Ali, M. A., & Khan, A. (2021). Artificial intelligence for the prediction of the thermal performance of evaporative cooling systems. Energies, 14(13), 3946. https://doi.org/10.3390/en14133946
Astrup, T. F., Møller, J., Fruergaard, T., & Christensen, T. H. (2015). Life cycle assessment of thermal waste-to-energy technologies: Review and recommendations. Waste Management, 37, 104–115. https://doi.org/10.1016/j.wasman.2014.06.011
Aswin, K., Kallath, A., Adithyan, P., & Dayal, A. (2025). Comparison of recent trends in cooling of photovoltaic cells to increase its performance. International Journal of Scientific Development and Research, 10(4), e82-e95. https://doi.org/10.56975/ijsdr.v10i4.302395
Attia, S., Bilir, S., Loonen, R., & Hensen, J. (2022). Comparison of thermal energy saving potential and overheating risk of four adaptive façade technologies in office buildings. Sustainability, 14(10), 6106. https://doi.org/10.3390/su14106106
Auld, G., Mallett, A., Burlica, B., Slater, R., & Cashore, B. (2014). Evaluating the effects of policy innovations: Lessons from a systematic review of policies promoting low-carbon technology. Global Environmental Change, 29, 444–458. https://doi.org/10.1016/j.gloenvcha.2014.03.002
Bennear, L. S., & Stavins, R. N. (2007). Second-best theory and the use of multiple policy instruments. Environmental and Resource Economics, 37(1), 111–129. https://doi.org/10.1007/s10640-007-9110-y
Besheer, A. H., Yousef, M. S., & Huzayyin, A. S. (2016). Review on recent approaches for hybrid PV/T solar technology. International Journal of Energy Research, 40(15), 2038–2053. https://doi.org/10.1002/er.3567
Bezaatpour, J., Heidari, A., Mousavi, S., & Rahimi, M. (2025). Strategic mitigation of temperature-induced efficiency losses in large-scale photovoltaic facades. Energy, 137792. https://doi.org/10.1016/j.energy.2025.137792
Bhat, I. K., & Prakash, R. (2009). LCA of renewable energy for electricity generation systems—A review. Renewable and Sustainable Energy Reviews, 13(5), 1067–1073. https://doi.org/10.1016/j.rser.2008.08.004
Bonse, J., Kirner, S. V., & Krüger, J. (2020). Laser-induced periodic surface structures (LIPSS). In Sugioka, K. (Ed.), Handbook of laser micro- and nano-engineering (pp. 1–59). Springer. https://doi.org/10.1007/978-3-319-69537-2_17-1
Busch, P.-O., Jörgens, H., & Tews, K. (2005). The global diffusion of regulatory instruments: The making of a new international environmental regime. The Annals of the American Academy of Political and Social Science, 598(1), 146–167. https://doi.org/10.1177/0002716204272355
Chen, Z., Liu, W., Wu, Q., & Sun, Y. (2022). Picosecond laser treated aluminium surface for photothermal seawater desalination. Desalination, 528, 115561. https://doi.org/10.1016/j.desal.2022.115561
Chen, Z., Wang, L., Yang, S., & Zhang, L. (2022). A short review on functionalized metallic surfaces by ultrafast laser micromachining. The International Journal of Advanced Manufacturing Technology, 119(11), 6919–6948. https://doi.org/10.1007/s00170-021-08560-8
Coblas, D. G., Silva, F. J. G., Campilho, R. D. S. G., & Pereira, M. T. (2015). Manufacturing textured surfaces: State of art and recent developments. Proceedings of the Institution of Mechanical Engineers, Part J: Journal of Engineering Tribology, 229(1), 3–29. https://doi.org/10.1177/1350650114542242
Conradi, M., Skocaj, D., Jovanovic, Z., & Drevensek, M. (2019). Short-and long-term wettability evolution and corrosion resistance of uncoated and polymer-coated laser-textured steel surface. Coatings, 9(9), 592. https://doi.org/10.3390/coatings9090592
Feng, S. C., Zhang, Y., Guo, J., & Lin, F. (2023). Functional requirements of software tools for laser-based powder bed fusion additive manufacturing for metals. Journal of Computing and Information Science in Engineering, 23(3), 031005. https://doi.org/10.1115/1.4054933
Figgis, B., & Bermudez, V. (2021). PV coating abrasion by cleaning machines in desert environments—Measurement techniques and test conditions. Solar Energy, 225, 252–258. https://doi.org/10.1016/j.solener.2021.07.039
Fillion, R. M., Riahi, A. R., & Edrisy, A. (2014). A review of icing prevention in photovoltaic devices by surface engineering. Renewable and Sustainable Energy Reviews, 32, 797–809. https://doi.org/10.1016/j.rser.2014.01.015
Ghalandari, M., Ahmadi, M. H., Pourkiaei, S. M., & Chen, L. (2020). Applications of nanofluids containing carbon nanotubes in solar energy systems: A review. Journal of Molecular Liquids, 313, 113476. https://doi.org/10.1016/j.molliq.2020.113476
Graham, D., & Woods, N. (2006). Making corporate self-regulation effective in developing countries. World Development, 34(5), 868–883. https://doi.org/10.1016/j.worlddev.2005.04.022
Grillo, F., Wirth, C., Behnam, M., & Fransen, L. (2024). Standardization: Research trends, current debates, and interdisciplinarity. Academy of Management Annals, 18(2), 788–830. https://doi.org/10.5465/annals.2023.0072
Guo, C., Zhang, M., & Hu, J. (2022). Fabrication of hierarchical structures on titanium alloy surfaces by nanosecond laser for wettability modification. Optics & Laser Technology, 148, 107728. https://doi.org/10.1016/j.optlastec.2021.107728
Gupta, N., & Tiwari, G. N. (2016). Review of passive heating/cooling systems of buildings. Energy Science & Engineering, 4(5), 305–333. https://doi.org/10.1002/ese3.129
Hemeida, M. G., Abdelaziz, E. A., Elsayed, A. H., & Salem, M. A. (2022). Renewable energy resources technologies and life cycle assessment. Energies, 15(24), 9417. https://doi.org/10.3390/en15249417
Hu, M., Chen, J., Zhao, J., & Wang, Y. (2016). Experimental study of the effect of inclination angle on the thermal performance of heat pipe photovoltaic/thermal (PV/T) systems with wickless heat pipe and wire-meshed heat pipe. Applied Thermal Engineering, 106, 651–660. https://doi.org/10.1016/j.applthermaleng.2016.06.003
Huang, Y., & Schmid, S. R. (2018). Additive manufacturing for health: State of the art, gaps and needs, and recommendations. Journal of Manufacturing Science and Engineering, 140(9), 094001. https://doi.org/10.1115/1.4040430
Jakhar, S., Paliwal, M. K., & Kumar, M. (2023). Machine learning predictive models for optimal design of photovoltaic/thermal collector with nanofluids based geothermal cooling. Environmental Progress & Sustainable Energy, 42(5), e14131. https://doi.org/10.1002/ep.14131
Jalil, S. A., Ahmed, M., Ali, M., & Khan, S. (2020). Spectral absorption control of femtosecond laser-treated metals and application in solar-thermal devices. Light: Science & Applications, 9(1), 14. https://doi.org/10.1038/s41377-020-0242-y
Ji, M., Chen, R., Zhang, Y., & Wang, J. (2024). Prediction and optimization kerf width in laser beam machining of titanium alloy using genetic algorithm tuned adaptive neuro-fuzzy inference system. The International Journal of Advanced Manufacturing Technology, 132(11), 5873–5893. https://doi.org/10.1007/s00170-024-13681-x
Jo, H. H., Kim, H. J., Park, J., & Lee, S. (2022). Application and evaluation of phase change materials for improving photovoltaic power generation efficiency and roof overheating reduction. Renewable Energy, 195, 1412–1425. https://doi.org/10.1016/j.renene.2022.06.119
Joe, D. J., Lee, J. H., Lee, K., & Kim, S. (2017). Laser-material interactions for flexible applications. Advanced Materials, 29(26), 1606586. https://doi.org/10.1002/adma.201606586
Joo, H.-J., An, Y.-S., Kim, M.-H., & Kong, M. (2023). Long-term performance evaluation of liquid-based photovoltaic thermal (PVT) modules with overheating-prevention technique. Energy Conversion and Management, 296, 117682. https://doi.org/10.1016/j.enconman.2023.117682
Jordan, D. C., Kurtz, S. R., Wohlgemuth, J., & VanSant, K. (2019). PV degradation – Mounting & temperature. In 2019 IEEE 46th Photovoltaic Specialists Conference (PVSC) (pp. 1–6). IEEE. https://doi.org/10.1109/PVSC40753.2019.8980767
Kahoul, N., Houabes, M., & Sadok, M. (2014). Assessing the early degradation of photovoltaic modules performance in the Saharan region. Energy Conversion and Management, 82, 320–326. https://doi.org/10.1016/j.enconman.2014.03.034
Kalinowski, A., Nowak, M., & Wróbel, R. (2023). Laser surface texturing: Characteristics and applications. System Safety: Human-Technical Facility-Environment, 5(1), 240–248. https://doi.org/10.2478/czoto-2023-0026
Kavousi-Fard, A., Ahmadi, M., & Samadi, A. (2024). Digital twin for mitigating solar energy resources challenges: A perspective. Solar Energy, 274, 112561. https://doi.org/10.1016/j.solener.2024.112561
Kempe, M. D., & Wohlgemuth, J. H. (2013). Evaluation of temperature and humidity on PV module component degradation. In 2013 IEEE 39th Photovoltaic Specialists Conference (PVSC) (pp. 1–6). IEEE. https://doi.org/10.1109/PVSC.2013.6744112
Kenfack, A. Z., Ntep, F. A., Fokam, R. B., & Talla, P. K. (2025). Design of a meta-heuristic artificial intelligence (AI) model for an optimal photovoltaic module cooling system. Discover Applied Sciences, 7(4), 269. https://doi.org/10.1007/s42452-025-06696-w
Khan, S. Y., Ali, M., Farooq, R., & Rehman, A. U. (2025). Revolutionizing solar photovoltaic efficiency: A comprehensive review of cutting-edge thermal management methods for advanced and conventional solar photovoltaic. Energy & Environmental Science. https://doi.org/10.1039/d4ee03525a
Kim, J. E., & Tang, T. (2020). Preventing early lock-in with technology-specific policy designs: The Renewable Portfolio Standards and diversity in renewable energy technologies. Renewable and Sustainable Energy Reviews, 123, 109738. https://doi.org/10.1016/j.rser.2020.109738
Lämmle, M. (2019). Thermal management of PVT collectors: Development and modelling of highly efficient glazed, flat plate PVT collectors with low-emissivity coatings and overheating protection (Doctoral dissertation, Fraunhofer-Institut für Solare Energiesysteme ISE, Stuttgart). Fraunhofer Verlag. https://doi.org/10.24406/publica-fhg-282606
Li, S., Zhang, X., Huang, J., & Zhou, T. (2021). A method for accurately assessing field performance degradation of PV modules in different geographical regions. Sustainable Energy Technologies and Assessments, 48, 101638. https://doi.org/10.1016/j.seta.2021.101638
Liang, Z., Wang, C., Li, J., & Zhao, H. (2023). Aluminum-based heterogeneous surface for efficient solar desalination and fog harvesting processed by a picosecond laser. ACS Applied Materials & Interfaces, 15(39), 46195–46204. https://doi.org/10.1021/acsami.3c08121
Liu, Z., Zhao, Y., Chen, H., & Wang, H. (2022). Metal surface wettability modification by nanosecond laser surface texturing: A review. Biosurface and Biotribology, 8(2), 95–120. https://doi.org/10.1049/bsb2.12039
Magalhães, P. M. L. P., Martins, J. F. A., & Joyce, A. L. M. (2016). Comparative analysis of overheating prevention and stagnation handling measures for photovoltaic-thermal (PV-T) systems. Energy Procedia, 91, 346–355. https://doi.org/10.1016/j.egypro.2016.06.282
Mahian, O., Kianifar, A., Kalogirou, S. A., Pop, I., & Wongwises, S. (2013). A review of the applications of nanofluids in solar energy. International Journal of Heat and Mass Transfer, 57(2), 582–594. https://doi.org/10.1016/j.ijheatmasstransfer.2012.10.037
Mallikarjuna, K., Reddy, V., Kumar, M., & Rao, P. (2021). A nanofluids and nanocoatings used for solar energy harvesting and heat transfer applications: A retrospective review analysis. Materials Today: Proceedings, 37, 823–834. https://doi.org/10.1016/j.matpr.2020.05.833
Mani, M., Lyons, K. W., & Gupta, S. K. (2014). Sustainability characterization for additive manufacturing. Journal of Research of the National Institute of Standards and Technology, 119, 419. https://doi.org/10.6028/jres.119.016
Mebarek-Oudina, F., & Chabani, I. (2022). Review on nano-fluids applications and heat transfer enhancement techniques in different enclosures. Journal of Nanofluids, 11(2), 155–168. https://doi.org/10.1166/jon.2022.1834
Napp, T. A., Gambhir, A., Hills, T. P., Florin, N., & Fennell, P. S. (2014). A review of the technologies, economics and policy instruments for decarbonising energy-intensive manufacturing industries. Renewable and Sustainable Energy Reviews, 30, 616–640. https://doi.org/10.1016/j.rser.2013.10.036
Nižetić, S., Grubišić-Čabo, F., Marinić-Kragić, I., & Čoko, D. (2021). A novel and effective passive cooling strategy for photovoltaic panel. Renewable and Sustainable Energy Reviews, 145, 111164. https://doi.org/10.1016/j.rser.2021.111164
Nižetić, S., Papadopoulos, A. M., & Giama, E. (2017). Comprehensive analysis and general economic-environmental evaluation of cooling techniques for photovoltaic panels, Part I: Passive cooling techniques. Energy Conversion and Management, 149, 334–354. https://doi.org/10.1016/j.enconman.2017.07.022
Obilor, A. F., et al. (2022). Micro-texturing of polymer surfaces using lasers: A review. The International Journal of Advanced Manufacturing Technology, 120(1), 103–135. https://doi.org/10.1007/s00170-022-08731-1
Omazic, A., Parikh, H., Deline, C., MacAlpine, S., & Alonso-Álvarez, D. (2019). Relation between degradation of polymeric components in crystalline silicon PV module and climatic conditions: A literature review. Solar Energy Materials and Solar Cells, 192, 123–133. https://doi.org/10.1016/j.solmat.2018.12.027
Pandian, A., Kumar, R., Kumar, S., & Gupta, P. (2016). Fire hazards and overheating caused by shading faults on photovoltaic solar panel. Fire Technology, 52(2), 349–364. https://doi.org/10.1007/s10694-015-0509-7
Perera, A. T. D., Attalage, R. A., Perera, K. K. C. K., & Sonnadara, D. U. J. (2019). Machine learning methods to assist energy system optimization. Applied Energy, 243, 191–205. https://doi.org/10.1016/j.apenergy.2019.03.202
Pfleging, W. (2020). Recent progress in laser texturing of battery materials: A review of tuning electrochemical performances, related material development, and prospects for large-scale manufacturing. International Journal of Extreme Manufacturing, 3(1), 012002. https://doi.org/10.1088/2631-7990/abca84
Qi, L., Zhang, H., Liu, Y., & Huang, W. (2021). Techno-economic assessment of photovoltaic power generation mounted on cooling towers. Energy Conversion and Management, 235, 113907. https://doi.org/10.1016/j.enconman.2021.113907
Rahmani, R., Momeni, M., Javidan, M., & Karimi, N. (2023). Overview of selective laser melting for Industry 5.0: Toward customizable, sustainable, and human-centric technologies. Machines, 11(5), 522. https://doi.org/10.3390/machines11050522
Rico Sierra, D., Edwardson, S. P., & Dearden, G. (2018). Laser surface texturing of titanium with thermal post-processing for improved wettability properties. Procedia CIRP, 74, 362–366. https://doi.org/10.1016/j.procir.2018.08.143
Rubahn, H.-G. (1999). Laser applications in surface science and technology. John Wiley & Sons. https://www.wiley.com/en-us/Laser+Applications+in+Surface+Science+and+Technology-p-9780471984504
Seid Ahmed, Y. (2024). Optimizing femtosecond texturing process parameters through advanced machine learning models in tribological applications. Lubricants, 12(12), 454. https://doi.org/10.3390/lubricants12120454
Shanmugam, N., Babu, M. R., Mohan, S., & Kumar, R. (2020). Anti-reflective coating materials: A holistic review from PV perspective. Energies, 13(10), 2631. https://doi.org/10.3390/en13102631
Sharaf, M., Yousef, M. S., & Huzayyin, A. S. (2022). Review of cooling techniques used to enhance the efficiency of photovoltaic power systems. Environmental Science and Pollution Research, 29(18), 26131–26159. https://doi.org/10.1007/s11356-022-18719-9
Sharma, P., Kumar, R., Singh, A., & Gupta, S. (2022). Recent advances in machine learning research for nanofluid-based heat transfer in renewable energy system. Energy & Fuels, 36(13), 6626–6658. https://doi.org/10.1021/acs.energyfuels.2c01006
Singh, S. C., & Guo, C. (2022). Femtosecond laser‐produced optical absorbers for solar‐thermal energy harvesting. EcoMat, 4(1), e12161. https://doi.org/10.1002/eom2.12161
Sohrabpoor, H., Mianehrow, H., Khodaygan, S., & Eslami, A. (2019). Improving precision in the prediction of laser texturing and surface interference of 316L assessed by neural network and adaptive neuro-fuzzy inference models. The International Journal of Advanced Manufacturing Technology, 104(9), 4571–4580. https://doi.org/10.1007/s00170-019-04291-z
Sugioka, K., & Cheng, Y. (2014). Femtosecond laser three-dimensional micro- and nanofabrication. Applied Physics Reviews, 1(4), 041303. https://doi.org/10.1063/1.4904320
Suwa, T. (2022). Transient heat transfer performance prediction using a machine learning approach for sensible heat storage in parabolic trough solar thermal power generation cycles. Journal of Energy Storage, 56, 105965. https://doi.org/10.1016/j.est.2022.105965
Toyserkani, E., & Rasti, N. (2015). Ultrashort pulsed laser surface texturing. In Laser surface engineering (pp. 441–453). Woodhead Publishing. https://doi.org/10.1016/B978-1-78242-074-3.00018-0
Van de Kaa, G., & Greeven, M. (2017). LED standardization in China and South East Asia: Stakeholders, infrastructure and institutional regimes. Renewable and Sustainable Energy Reviews, 72, 863–870. https://doi.org/10.1016/j.rser.2017.01.101
Vorobyev, A. Y., & Guo, C. (2013). Direct femtosecond laser surface nano/microstructuring and its applications. Laser & Photonics Reviews, 7(3), 385–407. https://doi.org/10.1002/lpor.201200017
Wang, Q., & Wang, H. (2022). Fabrication of textured surface with controllable wettability via laser-thermal hybrid processing. Materials Letters, 315, 131954. https://doi.org/10.1016/j.matlet.2022.131954
Wang, X., Li, Y., Chen, Q., & Zhang, J. (2019). Fabrication of micro/nano-hierarchical structures for droplet manipulation via velocity-controlled picosecond laser surface texturing. Optics and Lasers in Engineering, 122, 319–327. https://doi.org/10.1016/j.optlaseng.2019.06.021
Xu, H., Zhao, Y., Liu, J., & Zhang, W. (2021). Energy conversion performance of a PV/T-PCM system under different thermal regulation strategies. Energy Conversion and Management, 229, 113660. https://doi.org/10.1016/j.enconman.2020.113660
Xu, J., & Gong, J. (2023). Novel sustainable urban management framework based on solar energy and digital twin. Solar Energy, 262, 111861. https://doi.org/10.1016/j.solener.2023.111861
Xu, W., Bai, Y., & Yin, Y. (2018). Surface engineering of nanostructured energy materials. Advanced Materials, 30(48), 1802091. https://doi.org/10.1002/adma.201802091
Ye, J. Y., Tay, A., Hsiao, A., & Hameiri, Z. (2014). Performance degradation of various PV module technologies in tropical Singapore. IEEE Journal of Photovoltaics, 4(5), 1288–1294. https://doi.org/10.1109/JPHOTOV.2014.2338051
Yilbas, B. S., Arif, A. F. M., Ahmed, S. H., & Al-Qahtani, H. (2018). Laser texturing of Inconel 718 alloy surface: Influence of environmental dust in humid air ambient. Optics & Laser Technology, 108, 346–354. https://doi.org/10.1016/j.optlastec.2018.07.017
Yuan, W., Li, H., Zhou, Y., & Liu, Z. (2018). Comparison study of the performance of two kinds of photovoltaic/thermal (PV/T) systems and a PV module at high ambient temperature. Energy, 148, 1153–1161. https://doi.org/10.1016/j.energy.2018.01.121
Zayed, M. E., Aboelmaaref, M. M., & Chazy, M. (2023). Design of solar air conditioning system integrated with photovoltaic panels and thermoelectric coolers: Experimental analysis and machine learning modeling by random vector functional link coupled with white whale optimization. Thermal Science and Engineering Progress, 44, 102051. https://doi.org/10.1016/j.tsep.2023.102051
Zhao, B., Li, C., Wu, X., & Yang, X. (2020). Spectrally selective approaches for passive cooling of solar cells: A review. Applied Energy, 262, 114548. https://doi.org/10.1016/j.apenergy.2020.114548
Downloads
Published
Issue
Section
Categories
License
Copyright (c) 2025 Aswin Karkadakattil (Author)
This work is licensed under a Creative Commons Attribution 4.0 International License.
All articles published in the journal Challenges and Issues of Modern Science are licensed under the Creative Commons Attribution 4.0 International (CC BY) license. This means that you are free to:
- Share, copy, and redistribute the article in any medium or format
- Adapt, remix, transform, and build upon the article
as long as you provide appropriate credit to the original work, include the authors' names, article title, journal name, and indicate that the work is licensed under CC BY. Any use of the material should not imply endorsement by the authors or the journal.
