Linking the Researchers, Developing the Innovations
A file oriented unstructured data collected and transformed into the data warehouse .Two or more records identified separately actually represent same real world entity, detection and prevention to improve data quality. The proposed technique introduces smart tokens of most representative attributes by sorting those tokens identical records are bring into close neighborhood, record duplicates are identified and removed from the data. Clean consistent and non duplicated data loaded into warehouse. The technique is a mile stone for cleaning data as with the explosive amount of data recording it is the need of time that more corrected data to be provided to the data mangers for effective decisions making.
© The authors retain all copyrights
This article is open access and distributed under the Creative Commons Attribution 4.0 International License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Authors disclose no conflict of interest or having no competing interest.
Vol. 12, Issue 09, PP. 175-182, September 2025
In medical image segmentation, the identification, characterization, and visualization of a tumor’s dimension and region are considered to be very crucial, tedious, and time-consuming tasks. In spite of intensive research, segmentation is still one of the most challenging problems in the medical field due to the variety of image content. In this paper, we propose a new hybrid method for detecting and segmenting tumors in T2-weighted magnetic resonance imaging (MRI) brain scans. The approach begins with an efficient thresholding technique, followed by conventional morphological filtering, and then applies the binary K-means clustering algorithm. Experimental results and performance metrics demonstrate that the proposed method effectively identifies and segments tumors in MRI brain scans with significant accuracy.
© The authors retain all copyrights
This article is open access and distributed under the Creative Commons Attribution 4.0 International License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Authors disclose no conflict of interest or having no competing interest.
Vol. 12, Issue 08, PP. 170-174, August 2025
Cancer is among the deadliest diseases afflicting humanity. At present, there exists no successful therapy. Breast cancer is among the most common kinds of cancer. In 2020, the National Breast Cancer Foundation projected that approximately 276,000 fresh patients of invasive breast cancer and 48,000 fresh patients of non-invasive breast cancer were diagnosed in the USA. The patients have a 99% survival rate, as 64% of these cases are detected in initial stage of the disease. Artificial intelligence (AI) has been utilized to detect deadly diseases, which has enhanced the patient likelihood of survival by enabling early diagnosis and treatment. This research presented convolutional neural network (CNN) for the diagnosis of breast cancer disease automatically. The analysis has been carried out on a real-time invasive ductal carcinoma (IDC) dataset available at Kaggle. The dataset is preprocessed before being fed to CNN. The images is normalized to achieve a better accuracy. The developed model has an accuracy of 90% that is improved by 3% from the previous research paper. Different performances metrics are graphically represented in result section to analyze the model efficiency.
[1] Y. Qasim, H. Al-Sameai, O. Ali, and A. Hassan, "Convolutional neural networks for automatic detection of colon adenocarcinoma based on histopathological images," in International Conference of Reliable Information and Communication Technology, 2020: Springer, pp. 19-28.
[2] A. S. Sakr, "Automatic Detection of Various Types of Lung Cancer Based on Histopathological Images Using a Lightweight End-to-End CNN Approach," in 2022 20th International Conference on Language Engineering (ESOLEC), 2022, vol. 20: IEEE, pp. 141-146.
[3] N. A. Abujabal and A. B. Nassif, "Meta-heuristic algorithms-based feature selection for breast cancer diagnosis: A systematic review," in 2022 International Conference on Electrical, Computer, Communications and Mechatronics Engineering (ICECCME), 2022: IEEE, pp. 1-6.
[4] X. Zhou et al., "A comprehensive review for breast histopathology image analysis using classical and deep neural networks," IEEE Access, vol. 8, pp. 90931-90956, 2020.
[5] D. H. Sutanto and M. Abd Ghani, "A Benchmark Feature Selection Framework for Non Communicable Disease Prediction Model," Advanced Science Letters, vol. 21, no. 10, pp. 3409-3416, 2015
[6] R. Gautam, P. Kaur, and M. Sharma, "A comprehensive review on nature inspired computing algorithms for the diagnosis of chronic disorders in human beings," Progress in Artificial Intelligence, vol. 8, no. 4, pp. 401-424, 2019
[7] M. Mahmood, B. Al-Khateeb, and W. M. Alwash, "A review on neural networks approach on classifying cancers," IAES International Journal of Artificial Intelligence, vol. 9, no. 2, p. 317, 2020.
[8] N. Fatima, L. Liu, S. Hong, and H. Ahmed, "Prediction of breast cancer, comparative review of machine learning techniques, and their analysis," IEEE Access, vol. 8, pp. 150360-150376, 2020.
[9] R. Kaur, H. GholamHosseini, R. Sinha, and M. Lindén, "Melanoma classification using a novel deep convolutional neural network with dermoscopic images," Sensors, vol. 22, no. 3, p. 1134, 2022.
[10] I. Elansary, A. Ismail, and W. Awad, "Efficient classification model for melanoma based on convolutional neural networks," in Medical Informatics and Bioimaging Using Artificial Intelligence: Challenges, Issues, Innovations and Recent Developments: Springer, 2021, pp. 15-27
© The authors retain all copyrights
This article is open access and distributed under the Creative Commons Attribution 4.0 International License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Authors disclose no conflict of interest or having no competing interest.
Vol. 12, Issue 08, PP. 150-169, August 2025
Pakistan boasts abundant marble reserves, primarily concentrated in provinces like Khyber Pakhtunkhwa and Baluchistan. The extraction of marble blocks in these regions leads to the generation of marble sludge, comprising water and marble powder, which presents significant environmental challenges by contaminating water bodies, infiltrating groundwater, and posing health risks due to airborne particles. Given the pressing climate situation, it is imperative to address these concerns. To mitigate the environmental impact, we propose the application of a geo-polymerization technique. This method leverages marble powder, fly ash, and blast furnace slag to substitute cement in concrete production. Various mixtures were prepared, utilizing different proportions of these components and diverse liquid media. Particularly noteworthy was the use of a Na2SiO3-8M NaOH solution, which yielded concrete samples with significantly higher compressive strength compared to other media. Upon analyzing the results, it has been concluded that replacing 50% of cement with a combination of 25% marble powder and 25% fly ash, using this solution, resulted in an impressive 143% increase in strength compared to standard concrete (M20 grade) and other geo-polymer concretes. This innovative approach not only mitigates the environmental impact of marble sludge but also contributes to a circular economy by producing high-strength geo-polymer concrete suitable for a wide range of applications.
© The authors retain all copyrights
This article is open access and distributed under the Creative Commons Attribution 4.0 International License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Authors disclose no conflict of interest or having no competing interest.
Vol. 12, Issue 08, PP. 132-150, August 2025
OEE offers an effective framework to monitor and enhance equipment performance. This metric integrates three key components: availability, performance, and quality, which together provide a detailed insight into the operational effectiveness of machinery. The method used in this study is arithmetic calculation of overall equipment efficiency (Availability, Performance and Quality).The results of a thorough data-driven approach offer paper sack makers practical suggestions to boost output, cut waste, and improve long-term equipment dependability, all of which contribute to more sustainable. The current OEE of Thal Packaging calculated was 58%.The downtime for the January 2023 was 6108 minutes. The vital few causes of Thal Packaging downtime was equipment failure, Tube shortage, Paper shortage, Power shutdown and Machine Idleness.
Friederich, Jonas & Lazarova-Molnar, Sanja. (2024). Reliability assessment of manufacturing systems: A comprehensive overview, challenges and opportunities. Journal of Manufacturing Systems. 72. 38-58. 10.1016/j.jmsy.2023.11.001.
https://www.ibm.com/think/topics/mtbf
https://www.ibm.com/think/topics/mttr
Kapuyanyika, M., & Suthar, K. (2018). To improve the overal equipment effectiveness of wheel surface machining plant of railway using total productive maintenance.
M. Braglia, M. Frosolini and F. Zammori. (2008). Overall equipment effectiveness of a manufacturing line (OEEML): an integrated approach to access systems performance. Journal of Manufacturing Technology Management. 20(1), pp. 8-29.
Dahab, A., Backar, S., & Abdulwahed Younes, M. (2023). Overall Equipment Efficiency Improvement through a Lean Approach in SME: A Case Study. International Journal of Engineering Research in Africa, 65, 117–129. https://doi.org/10.4028/p-1zhmxc
Azizi, A. (2015). Evaluation Improvement of Production Productivity Performance using Statistical Process Control, Overall Equipment Efficiency, and Autonomous Maintenance. Procedia Manufacturing, 2, 186–190. https://doi.org/10.1016/j.promfg.2015.07.032
Jauregui Becker, J. M., Borst, J., & Van Der Veen, A. (2015). Improving the overall equipment effectiveness in high-mix-low-volume manufacturing environments. CIRP Annals, 64(1), 419–422. https://doi.org/10.1016/j.cirp.2015.04.126
Mwanza, B. G., & Mbohwa, C. (2015). Design of a Total Productive Maintenance Model for Effective Implementation: Case Study of a Chemical Manufacturing Company. Procedia Manufacturing, 4, 461–470. https://doi.org/10.1016/j.promfg.2015.11.063
De Carlo, F., Tucci, M., & Borgia, O. (2013). Bucket Brigades to Increase Productivity in a Luxury Assembly Line. International Journal of Engineering Business Management, 5, 28. https://doi.org/10.5772/56837
© The authors retain all copyrights
This article is open access and distributed under the Creative Commons Attribution 4.0 International License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Authors disclose no conflict of interest or having no competing interest.
Vol. 12, Issue 08, PP. 126-131, August 2025
Underwater Wireless Sensor Networks (UWSNs) face significant security challenges, particularly Sybil attacks that compromise node authentication and data integrity. This research proposes a hybrid Sybil attack detection model that integrates blockchain technology with anomaly-based detection to ensure secure communication among legitimate nodes. Blockchain provides a tamper-resistant ledger for transaction validation, while the anomaly detection mechanism flags suspicious behavior based on communication patterns. The proposed model was simulated in MATLAB and evaluated against key performance metrics—Packet Delivery Ratio (PDR), Throughput, Energy Consumption, and End-to-End Delay. Results show a notable improvement over baseline and existing models, achieving higher PDR and throughput, and reduced delay and energy usage, validating the model’s effectiveness in enhancing UWSN security.
Taher, Kazi Abu. "A novel authentication mechanism for securing underwater wireless sensors from sybil attack." 2021 5th International Conference on Electrical Engineering and Information Communication Technology (ICEEICT). IEEE, 2021.
[2] Xiao, Xingxing, Haining Huang, and Wei Wang. "Underwater wireless sensor networks: An energy-efficient clustering routing protocol based on data fusion and genetic algorithms." Applied Sciences 11.1 (2020): 312.
[3] Mhemed, Rogaia, et al. "Void avoidance opportunistic routing protocol for underwater wireless sensor networks." Sensors 21.6 (2021): 1942.
[4] Khisa, Shreya, and Sangman Moh. "Survey on recent advancements in energy-efficient routing protocols for underwater wireless sensor networks." IEEE Access 9 (2021): 55045-55062.
[5] Zhao, Danfeng, et al. "Cross-layer-aided opportunistic routing for sparse underwater wireless sensor networks." Sensors 21.9 (2021): 3205.
[6] Du, Xinxin, et al. "Energy-efficient sensory data gathering based on compressed sensing in IoT networks." Journal of Cloud Computing 9 (2020): 1-16.
[7] Yang, Yi, Weishu Zhao, and Xiang Xiao. "The upper temperature limit of life under high hydrostatic pressure in the deep biosphere." Deep Sea Research Part I: Oceanographic Research Papers 176 (2021): 103604.
[8] Yang, Guang, et al. "Challenges and security issues in underwater wireless sensor networks." Procedia Computer Science 147 (2019): 210-216.
[10] Nithiyanandam, N., and Latha Parthiban. "An efficient voting based method to detect sink hole in wireless acoustic sensor networks." International Journal of Speech Technology 23.2 (2020): 343-354.
© The authors retain all copyrights
This article is open access and distributed under the Creative Commons Attribution 4.0 International License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Authors disclose no conflict of interest or having no competing interest.
Vol. 12, Issue 06, PP. 117-125, June 2025
The prevalent energy crisis in Pakistan has affected people and systems in every aspect of the life for the past decade, impacting the economic growth the most of all. The main driver of this slump in economic growth has been the inefficient utilization of the energy resources, further exacerbated by the blunders in decision-making and policy formulation in the uppermost echelons of the country. Energy conservation and efficiency is extensively used to cope with energy crisis that the current world is facing as a powerful tool for addressing the global energy situation. There are different methods of energy efficiency management that can bring positive change i.e. reduce cost at different levels if executed correctly such as increasing energy security or by carrying out different measures to reduce carbon emissions to environment etc. Despite the fact that different energy efficiency management systems are gaining attention in the developed countries, their adoption in underdeveloped countries remains limited, particularly in Pakistan. Pakistan is now experiencing energy crisis, which entails a slew of complicated issues, all of which may be rectified by implementing an energy efficiency management system, if applied to the energy-intensive economy. This research was conducted to explore the different barriers to implementing Energy Management System in different industries across Pakistan. This research is relies on data collected through detailed questionnaire from the industries that participated in an incentive program funded by UNIDO for conducting free energy audits. 20 industries participated in the study. Regression and Pearson correlation analysis are used to study how different parameters create barriers to implementing Energy Management System in industries in Pakistan.
[1] Hye, Q.M.; Riaz, S. Causality between Energy Consumption and Economic Growth: The Case of Pakistan.
Lahore J. Econ. 2008, 13, 45–58.
[2] Ahmed, M.; Azam, M. Causal nexus between energy consumption and economic growth for high, middle and low income countries using frequency domain analysis. Renew. Sustain. Energy Rev. 2016, 60, 653–678.
[3] Siddiqui, R.; Jalil, H.H.; Nasir, M.; Malik, W.S.; Khalid, M. The Cost of Unserved Energy: Evidence from Selected Industrial Cities of Pakistan. Pakistan Dev. Rev. 2008, 47, 227–246.
[4] Ahmed, M.; Riaz, K.; Khan, A.; Bibi, S. Energy consumption–economic growth nexus for Pakistan: Taming the untamed. Renew. Sustain. Energy Rev. 2015, 52, 890–896.
[5] Policy Review and Recommendations on the Promotion of Renewable Energy and Energy Efficiency; Project Report; United Nations Industrial Development Organization: Islamabad, Pakistan, 2016.
[6] Sabir, U.; Ariwa, E.; Taylor, A. Green technology and energy management systems in developing countries: A case study of Pakistan Textile Industry. In Proceedings of the Third International Conference on Innovative Computing Technology (INTECH 2013), London, UK, 29–31 August 2013; pp. 449–451.
[7] Akhtar, M.; Qamar, A.; Farooq, M.; Amjad, M.; Asim, M. Development of an effective energy management system in power plants of Pakistan. Fac. Eng. Technol. 2016, 23, 77–87
[8] Zeb, K.; Ali, S.; Khan, B.; Mehmood, C.; Tareen, N.; Din, W.; Farid, U.; Haider, A. A survey on waste heat recovery: Electric power generation and potential prospects within Pakistan. Renew. Sustain. Energy Rev. 2017, 75, 1142–1155.
[9] IEA. 2014. Capturing the multiple benefits of energy efficiency. Available: http://www.iea.org/publications/freepublications/publication/Captur_the_MultiplB enef_ofEnergyEficiency.pdf [September 29, 2015].
[10] Worrell, E.; Martin, N.; Price, L. Potentials for energy efficiency improvement in the US cement industry. Energy 2000, 25, 1189–1214.
© The authors retain all copyrights
This article is open access and distributed under the Creative Commons Attribution 4.0 International License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Authors disclose no conflict of interest or having no competing interest.
Vol. 12, Issue 05, PP. 105-116, May 2025
This work outlines a specific approach to the isolation of aerodynamic and physical factors towards enhancing flow control in the dynamic stall of rotating wings, a concern in rotor craft, wind turbines and UAVs. Employing a combination of CFD and ML, this research work focuses uniquely on aerodynamics of the aircraft by eliminating the impact of physical parameters like angular velocity, pitch rate, and angle of attack from lift, drag, and pressure distribution. This way, the research offers a finer view of the physical processes involved in vortex shedding, boundary layer development, and stall inception, which are critical to predicting and mitigating stall phenomena. The ML component uses data from CFD simulations to control parameters and provide real-time reaction to the aerodynamic changes. The results of this study show that, if these decoupled parameters are adjusted separately, one can control the stall onset and achieve up to 20% delay in lift hysteresis and control the flow stability across a broad range of operating points. This decoupling concept enables the accurate application of adjustment actions like adaptive pitch control and optimized rotation rates to the corresponding aerodynamic and physical conditions. The proposed approach provides a realistic solution for improving energy efficiency and operational reliability in the RWs subjected to high dynamic loads. This work not only contributes to the knowledge of dynamic stall phenomena in rotating wings but also opens the way to develop more robust and effective flow control strategies in aerospace and renewable energy applications.
[1] G Baldan and A Guardone. A deep neural network reduced order model for unsteady aerodynamics of pitching airfoils. Aerospace Science and Technology, 152:109345, 2024.
[2] G Baldan, F Manara, G Frassoldati, and A Guardone. The effects of turbulence modeling on dynamic stall, 2024. Available at: http://arxiv.org/abs/2404.14172.
[3] G Bangga, T Lutz, and M Arnold. An improved second-order dynamic stall model for wind turbine airfoils. Wind Energy Science, 5(3):1037–1058, 2020.
[4] P Broadley, MRA Nabawy, MK Quinn, and WJ Crowther. Dynamic experimental rigs for investigation of insect wing aerodynamics. Journal of the Royal Society Interface, 19(191):20210909, 2022.
[5] G. A. Flore and B. R. Noack. Flow control in wings and discovery of novel approaches via deep reinforcement learning. Fluids, 7(2), 2022.
[6] MA Garcia Teran, E Olguin-Diaz, A Flores-Abad, and M Nandayapa. Experimental validation of an aerodynamic sectional modeling approach in fixed-wing unmanned aerial vehicles. IEEE Access, 6:74190–74203, 2018.
[7] A Gardner, A Jones, K Mulleners, J Naughton, and M Smith. Review of rotating wing dynamic stall: Experiments and flow control. Progress in Aerospace Sciences, 137:100887, 2023.
[8] AD Gardner and K Richter. Influence of rotation on dynamic stall. Journal of the American Helicopter Society, 58(3), 2013.
[9] S Ho, H Nassef, N Pornsinsirirak, YC Tai, and CM Ho. Unsteady aerodynamics and flow control for flapping wing flyers. Progress in Aerospace Sciences, 39(8):635–681, 2003.
[10] HR Kim, JA Printezis, JD Ahrens, JR Seume, and L Wein. Characterization of dynamic stall on large wind turbines. pages 1–20, 2024. Available from April.
[11] X Li and L-H Feng. Critical indicators of dynamic stall vortex. Journal of Fluid Mechanics, 937:A16, 2022.
[12] Scheuer L. Kopel Y. Basescu M. Polevoy A. Wolfe K. Perrotta, G. and J. Moore. Planning and control for a dynamic morphing-wing uav using a vortex particle model. arXiv preprint, 2023.
[13] V Raghav and N Komerath. Dynamic stall life cycle on a rotating blade in steady forward flight. Journal of the American Helicopter Society, 60(3), 2015.
[14] V Raul and L Leifsson. Multifidelity aerodynamic shape optimization for mitigating dynamic stall using cokriging regression-based infill. Structural and Multidisciplinary Optimization, 66(11):237, 2023.
[15] Y Ruan and M Hajek. Numerical investigation of dynamic stall on a single rotating blade. Aerospace, 8:90, 2021.
[16] G. Sedky, A. Othman, and A. Wissa. Feather-inspired flow control: The flow physics of spatially distributed covert flaps. arXiv preprint arXiv:2311.16966, 2023.
[17] M. Sereez and M. Goman. Evaluation of aerodynamic characteristics in oscillatory coning using cfd methods. arXiv preprint, 2022.
[18] M Smith, A Gardner, R Jain, D Peters, and F Richez. Rotating wing dynamic stall: state of the art and future directions. Vertical Flight Society Annual Forum, 2020.
[19] M. J. Smith and F. Richez. Rotating wing dynamic stall: State of the art and future directions. HAL preprint, 2021.
[20] SMJ et al. Rotating wing dynamic stall: state of the art and future directions, 2021. HAL Id: hal-03106952.
[21] DA Sterpu, D Mariuta, and LT Grigorie. A udf-based approach for the dynamic stall evaluation of airfoils for micro-air vehicles. Biomimetics, 9(6), 2024.
[22] D. Traphan, Melius M. Peinke J. Gülker G. Wester, T. T. B., and R. B. Cal. Dynamic stall of an airfoil under tailored three-dimensional inflow conditions. arXiv preprint arXiv:2003.07840, 2020.
[23] Q Wang and Q Zhao. Numerical study on dynamic-stall characteristics of finite wing and rotor. Applied Sciences, 9(3), 2019.
[24] T Wong. Advanced airfoil. In Special Conference on Aeromechanics, 2010.
[25] G Wu, S Deng, and Q Li. Influence of area distribution along the span direction on flapping wing aerodynamics in hover based on numerical modeling analysis. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 17:6683–6692, 2024
© The authors retain all copyrights
This article is open access and distributed under the Creative Commons Attribution 4.0 International License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Authors disclose no conflict of interest or having no competing interest.
Vol. 12, Issue 05, PP. 91-104, May 2025
A key component of achieving higher efficiency is improving the process of metalizing silicon solar cells. Due to its simplicity and speed, contact realization by screen printing is now the most popular technology in the silicon-based photovoltaic sector. The issue with this type of metallization is that it has a higher contact resistance and a smaller aspect ratio, which restricts the efficiency of solar cells. Silicon solar cell producers are encouraged to develop new metallization techniques that use less silver and do not rely on the pressing process of screen printing due to the rising cost of silver pastes and decreasing silicon wafer thicknesses. Recently, a metallization technique that might address these problems is nickel/copper (Ni/Cu) based metal plating. In this review, we will describe the progress of electroplating techniques, mainly for the deposition of nickel/copper by laser deposition for nickel and the light-induced copper plating process. The metallization of the front-side silicon solar cells using a copper stack system is integral to achieving superior efficiency. The formation of a Ni seed layer by applying laser-assisted deposition has the advantage of using a single step for opening the ARC and the seed layer formation. Cu conducting layer using a light-induced plating (LIP) as the primary stack system, after applying a nickel seed layer to stop copper from diffusing into silicon, we also check tin as a top layer stack to protect it from oxidation. Moreover, we finally addressed the future advanced challenges and the issue of copper diffusion, background plating, and cost reductions.
N. Balaji, M. C. Raval, and S. Saravanan, “Review on Metallization in Crystalline Silicon Solar Cells,” in Solar Cells, IntechOpen, 2020. doi: 10.5772/intechopen.84820.
[2] M. T. Zarmai, N. N. Ekere, C. F. Oduoza, and E. H. Amalu, “A review of interconnection technologies for improved crystalline silicon solar cell photovoltaic module assembly,” Appl Energy, vol. 154, pp. 173–182, Sep. 2015, doi: 10.1016/j.apenergy.2015.04.120.
[3] D. Adachi, J. L. Hernández, and K. Yamamoto, “Impact of carrier recombination on fill factor for large area heterojunction crystalline silicon solar cell with 25.1% efficiency,” Appl Phys Lett, vol. 107, no. 23, Dec. 2015, doi: 10.1063/1.4937224.
[4] J. Cho et al., “Thermal stability improvement of metal oxide-based contacts for silicon heterojunction solar cells,” Solar Energy Materials and Solar Cells, vol. 206, p. 110324, Mar. 2020, doi: 10.1016/j.solmat.2019.110324.
[5] J. Yu et al., “Copper metallization of electrodes for silicon heterojunction solar cells: Process, reliability and challenges,” Solar Energy Materials and Solar Cells, vol. 224, p. 110993, Jun. 2021, doi: 10.1016/j.solmat.2021.110993.
[6] G. S. Seck, E. Hache, C. Bonnet, M. Simoën, and S. Carcanague, “Copper at the crossroads: Assessment of the interactions between low-carbon energy transition and supply limitations,” Resour Conserv Recycl, vol. 163, p. 105072, Dec. 2020, doi: 10.1016/j.resconrec.2020.105072.
[7] A. Rehman and S. Lee, “Review of the Potential of the Ni/Cu Plating Technique for Crystalline Silicon Solar Cells,” Materials, vol. 7, no. 2, pp. 1318–1341, Feb. 2014, doi: 10.3390/ma7021318.
[8] J. Sudagar, J. Lian, and W. Sha, “Electroless nickel, alloy, composite and nano coatings – A critical review,” J Alloys Compd, vol. 571, pp. 183–204, Sep. 2013, doi: 10.1016/j.jallcom.2013.03.107.
[9] A. ur Rahman and S. H. Lee, “Crystalline Silicon Solar Cells with Nickel/Copper Contacts,” in Solar Cells - New Approaches and Reviews, InTech, 2015. doi: 10.5772/59008.
[10] J. Bartsch, V. Radtke, C. Schetter, and S. W. Glunz, “Electrochemical methods to analyse the light-induced plating process,” J Appl Electrochem, vol. 40, no. 4, pp. 757–765, Apr. 2010, doi: 10.1007/s10800-009-0054-5.
© The authors retain all copyrights
This article is open access and distributed under the Creative Commons Attribution 4.0 International License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Authors disclose no conflict of interest or having no competing interest.
Vol. 12, Issue 09, PP. 175-182, September 2025
In medical image segmentation, the identification, characterization, and visualization of a tumor’s dimension and region are considered to be very crucial, tedious, and time-consuming tasks. In spite of intensive research, segmentation is still one of the most challenging problems in the medical field due to the variety of image content. In this paper, we propose a new hybrid method for detecting and segmenting tumors in T2-weighted magnetic resonance imaging (MRI) brain scans. The approach begins with an efficient thresholding technique, followed by conventional morphological filtering, and then applies the binary K-means clustering algorithm. Experimental results and performance metrics demonstrate that the proposed method effectively identifies and segments tumors in MRI brain scans with significant accuracy.
© The authors retain all copyrights
This article is open access and distributed under the Creative Commons Attribution 4.0 International License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Authors disclose no conflict of interest or having no competing interest.
Vol. 12, Issue 08, PP. 170-174, August 2025
Cancer is among the deadliest diseases afflicting humanity. At present, there exists no successful therapy. Breast cancer is among the most common kinds of cancer. In 2020, the National Breast Cancer Foundation projected that approximately 276,000 fresh patients of invasive breast cancer and 48,000 fresh patients of non-invasive breast cancer were diagnosed in the USA. The patients have a 99% survival rate, as 64% of these cases are detected in initial stage of the disease. Artificial intelligence (AI) has been utilized to detect deadly diseases, which has enhanced the patient likelihood of survival by enabling early diagnosis and treatment. This research presented convolutional neural network (CNN) for the diagnosis of breast cancer disease automatically. The analysis has been carried out on a real-time invasive ductal carcinoma (IDC) dataset available at Kaggle. The dataset is preprocessed before being fed to CNN. The images is normalized to achieve a better accuracy. The developed model has an accuracy of 90% that is improved by 3% from the previous research paper. Different performances metrics are graphically represented in result section to analyze the model efficiency.
[1] Y. Qasim, H. Al-Sameai, O. Ali, and A. Hassan, "Convolutional neural networks for automatic detection of colon adenocarcinoma based on histopathological images," in International Conference of Reliable Information and Communication Technology, 2020: Springer, pp. 19-28.
[2] A. S. Sakr, "Automatic Detection of Various Types of Lung Cancer Based on Histopathological Images Using a Lightweight End-to-End CNN Approach," in 2022 20th International Conference on Language Engineering (ESOLEC), 2022, vol. 20: IEEE, pp. 141-146.
[3] N. A. Abujabal and A. B. Nassif, "Meta-heuristic algorithms-based feature selection for breast cancer diagnosis: A systematic review," in 2022 International Conference on Electrical, Computer, Communications and Mechatronics Engineering (ICECCME), 2022: IEEE, pp. 1-6.
[4] X. Zhou et al., "A comprehensive review for breast histopathology image analysis using classical and deep neural networks," IEEE Access, vol. 8, pp. 90931-90956, 2020.
[5] D. H. Sutanto and M. Abd Ghani, "A Benchmark Feature Selection Framework for Non Communicable Disease Prediction Model," Advanced Science Letters, vol. 21, no. 10, pp. 3409-3416, 2015
[6] R. Gautam, P. Kaur, and M. Sharma, "A comprehensive review on nature inspired computing algorithms for the diagnosis of chronic disorders in human beings," Progress in Artificial Intelligence, vol. 8, no. 4, pp. 401-424, 2019
[7] M. Mahmood, B. Al-Khateeb, and W. M. Alwash, "A review on neural networks approach on classifying cancers," IAES International Journal of Artificial Intelligence, vol. 9, no. 2, p. 317, 2020.
[8] N. Fatima, L. Liu, S. Hong, and H. Ahmed, "Prediction of breast cancer, comparative review of machine learning techniques, and their analysis," IEEE Access, vol. 8, pp. 150360-150376, 2020.
[9] R. Kaur, H. GholamHosseini, R. Sinha, and M. Lindén, "Melanoma classification using a novel deep convolutional neural network with dermoscopic images," Sensors, vol. 22, no. 3, p. 1134, 2022.
[10] I. Elansary, A. Ismail, and W. Awad, "Efficient classification model for melanoma based on convolutional neural networks," in Medical Informatics and Bioimaging Using Artificial Intelligence: Challenges, Issues, Innovations and Recent Developments: Springer, 2021, pp. 15-27
© The authors retain all copyrights
This article is open access and distributed under the Creative Commons Attribution 4.0 International License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Authors disclose no conflict of interest or having no competing interest.
Vol. 12, Issue 08, PP. 150-169, August 2025
Pakistan boasts abundant marble reserves, primarily concentrated in provinces like Khyber Pakhtunkhwa and Baluchistan. The extraction of marble blocks in these regions leads to the generation of marble sludge, comprising water and marble powder, which presents significant environmental challenges by contaminating water bodies, infiltrating groundwater, and posing health risks due to airborne particles. Given the pressing climate situation, it is imperative to address these concerns. To mitigate the environmental impact, we propose the application of a geo-polymerization technique. This method leverages marble powder, fly ash, and blast furnace slag to substitute cement in concrete production. Various mixtures were prepared, utilizing different proportions of these components and diverse liquid media. Particularly noteworthy was the use of a Na2SiO3-8M NaOH solution, which yielded concrete samples with significantly higher compressive strength compared to other media. Upon analyzing the results, it has been concluded that replacing 50% of cement with a combination of 25% marble powder and 25% fly ash, using this solution, resulted in an impressive 143% increase in strength compared to standard concrete (M20 grade) and other geo-polymer concretes. This innovative approach not only mitigates the environmental impact of marble sludge but also contributes to a circular economy by producing high-strength geo-polymer concrete suitable for a wide range of applications.
© The authors retain all copyrights
This article is open access and distributed under the Creative Commons Attribution 4.0 International License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Authors disclose no conflict of interest or having no competing interest.
Vol. 12, Issue 08, PP. 132-150, August 2025
OEE offers an effective framework to monitor and enhance equipment performance. This metric integrates three key components: availability, performance, and quality, which together provide a detailed insight into the operational effectiveness of machinery. The method used in this study is arithmetic calculation of overall equipment efficiency (Availability, Performance and Quality).The results of a thorough data-driven approach offer paper sack makers practical suggestions to boost output, cut waste, and improve long-term equipment dependability, all of which contribute to more sustainable. The current OEE of Thal Packaging calculated was 58%.The downtime for the January 2023 was 6108 minutes. The vital few causes of Thal Packaging downtime was equipment failure, Tube shortage, Paper shortage, Power shutdown and Machine Idleness.
Friederich, Jonas & Lazarova-Molnar, Sanja. (2024). Reliability assessment of manufacturing systems: A comprehensive overview, challenges and opportunities. Journal of Manufacturing Systems. 72. 38-58. 10.1016/j.jmsy.2023.11.001.
https://www.ibm.com/think/topics/mtbf
https://www.ibm.com/think/topics/mttr
Kapuyanyika, M., & Suthar, K. (2018). To improve the overal equipment effectiveness of wheel surface machining plant of railway using total productive maintenance.
M. Braglia, M. Frosolini and F. Zammori. (2008). Overall equipment effectiveness of a manufacturing line (OEEML): an integrated approach to access systems performance. Journal of Manufacturing Technology Management. 20(1), pp. 8-29.
Dahab, A., Backar, S., & Abdulwahed Younes, M. (2023). Overall Equipment Efficiency Improvement through a Lean Approach in SME: A Case Study. International Journal of Engineering Research in Africa, 65, 117–129. https://doi.org/10.4028/p-1zhmxc
Azizi, A. (2015). Evaluation Improvement of Production Productivity Performance using Statistical Process Control, Overall Equipment Efficiency, and Autonomous Maintenance. Procedia Manufacturing, 2, 186–190. https://doi.org/10.1016/j.promfg.2015.07.032
Jauregui Becker, J. M., Borst, J., & Van Der Veen, A. (2015). Improving the overall equipment effectiveness in high-mix-low-volume manufacturing environments. CIRP Annals, 64(1), 419–422. https://doi.org/10.1016/j.cirp.2015.04.126
Mwanza, B. G., & Mbohwa, C. (2015). Design of a Total Productive Maintenance Model for Effective Implementation: Case Study of a Chemical Manufacturing Company. Procedia Manufacturing, 4, 461–470. https://doi.org/10.1016/j.promfg.2015.11.063
De Carlo, F., Tucci, M., & Borgia, O. (2013). Bucket Brigades to Increase Productivity in a Luxury Assembly Line. International Journal of Engineering Business Management, 5, 28. https://doi.org/10.5772/56837
© The authors retain all copyrights
This article is open access and distributed under the Creative Commons Attribution 4.0 International License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Authors disclose no conflict of interest or having no competing interest.
Vol. 12, Issue 08, PP. 126-131, August 2025
Underwater Wireless Sensor Networks (UWSNs) face significant security challenges, particularly Sybil attacks that compromise node authentication and data integrity. This research proposes a hybrid Sybil attack detection model that integrates blockchain technology with anomaly-based detection to ensure secure communication among legitimate nodes. Blockchain provides a tamper-resistant ledger for transaction validation, while the anomaly detection mechanism flags suspicious behavior based on communication patterns. The proposed model was simulated in MATLAB and evaluated against key performance metrics—Packet Delivery Ratio (PDR), Throughput, Energy Consumption, and End-to-End Delay. Results show a notable improvement over baseline and existing models, achieving higher PDR and throughput, and reduced delay and energy usage, validating the model’s effectiveness in enhancing UWSN security.
Taher, Kazi Abu. "A novel authentication mechanism for securing underwater wireless sensors from sybil attack." 2021 5th International Conference on Electrical Engineering and Information Communication Technology (ICEEICT). IEEE, 2021.
[2] Xiao, Xingxing, Haining Huang, and Wei Wang. "Underwater wireless sensor networks: An energy-efficient clustering routing protocol based on data fusion and genetic algorithms." Applied Sciences 11.1 (2020): 312.
[3] Mhemed, Rogaia, et al. "Void avoidance opportunistic routing protocol for underwater wireless sensor networks." Sensors 21.6 (2021): 1942.
[4] Khisa, Shreya, and Sangman Moh. "Survey on recent advancements in energy-efficient routing protocols for underwater wireless sensor networks." IEEE Access 9 (2021): 55045-55062.
[5] Zhao, Danfeng, et al. "Cross-layer-aided opportunistic routing for sparse underwater wireless sensor networks." Sensors 21.9 (2021): 3205.
[6] Du, Xinxin, et al. "Energy-efficient sensory data gathering based on compressed sensing in IoT networks." Journal of Cloud Computing 9 (2020): 1-16.
[7] Yang, Yi, Weishu Zhao, and Xiang Xiao. "The upper temperature limit of life under high hydrostatic pressure in the deep biosphere." Deep Sea Research Part I: Oceanographic Research Papers 176 (2021): 103604.
[8] Yang, Guang, et al. "Challenges and security issues in underwater wireless sensor networks." Procedia Computer Science 147 (2019): 210-216.
[10] Nithiyanandam, N., and Latha Parthiban. "An efficient voting based method to detect sink hole in wireless acoustic sensor networks." International Journal of Speech Technology 23.2 (2020): 343-354.
© The authors retain all copyrights
This article is open access and distributed under the Creative Commons Attribution 4.0 International License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Authors disclose no conflict of interest or having no competing interest.
Vol. 12, Issue 06, PP. 117-125, June 2025
The prevalent energy crisis in Pakistan has affected people and systems in every aspect of the life for the past decade, impacting the economic growth the most of all. The main driver of this slump in economic growth has been the inefficient utilization of the energy resources, further exacerbated by the blunders in decision-making and policy formulation in the uppermost echelons of the country. Energy conservation and efficiency is extensively used to cope with energy crisis that the current world is facing as a powerful tool for addressing the global energy situation. There are different methods of energy efficiency management that can bring positive change i.e. reduce cost at different levels if executed correctly such as increasing energy security or by carrying out different measures to reduce carbon emissions to environment etc. Despite the fact that different energy efficiency management systems are gaining attention in the developed countries, their adoption in underdeveloped countries remains limited, particularly in Pakistan. Pakistan is now experiencing energy crisis, which entails a slew of complicated issues, all of which may be rectified by implementing an energy efficiency management system, if applied to the energy-intensive economy. This research was conducted to explore the different barriers to implementing Energy Management System in different industries across Pakistan. This research is relies on data collected through detailed questionnaire from the industries that participated in an incentive program funded by UNIDO for conducting free energy audits. 20 industries participated in the study. Regression and Pearson correlation analysis are used to study how different parameters create barriers to implementing Energy Management System in industries in Pakistan.
[1] Hye, Q.M.; Riaz, S. Causality between Energy Consumption and Economic Growth: The Case of Pakistan.
Lahore J. Econ. 2008, 13, 45–58.
[2] Ahmed, M.; Azam, M. Causal nexus between energy consumption and economic growth for high, middle and low income countries using frequency domain analysis. Renew. Sustain. Energy Rev. 2016, 60, 653–678.
[3] Siddiqui, R.; Jalil, H.H.; Nasir, M.; Malik, W.S.; Khalid, M. The Cost of Unserved Energy: Evidence from Selected Industrial Cities of Pakistan. Pakistan Dev. Rev. 2008, 47, 227–246.
[4] Ahmed, M.; Riaz, K.; Khan, A.; Bibi, S. Energy consumption–economic growth nexus for Pakistan: Taming the untamed. Renew. Sustain. Energy Rev. 2015, 52, 890–896.
[5] Policy Review and Recommendations on the Promotion of Renewable Energy and Energy Efficiency; Project Report; United Nations Industrial Development Organization: Islamabad, Pakistan, 2016.
[6] Sabir, U.; Ariwa, E.; Taylor, A. Green technology and energy management systems in developing countries: A case study of Pakistan Textile Industry. In Proceedings of the Third International Conference on Innovative Computing Technology (INTECH 2013), London, UK, 29–31 August 2013; pp. 449–451.
[7] Akhtar, M.; Qamar, A.; Farooq, M.; Amjad, M.; Asim, M. Development of an effective energy management system in power plants of Pakistan. Fac. Eng. Technol. 2016, 23, 77–87
[8] Zeb, K.; Ali, S.; Khan, B.; Mehmood, C.; Tareen, N.; Din, W.; Farid, U.; Haider, A. A survey on waste heat recovery: Electric power generation and potential prospects within Pakistan. Renew. Sustain. Energy Rev. 2017, 75, 1142–1155.
[9] IEA. 2014. Capturing the multiple benefits of energy efficiency. Available: http://www.iea.org/publications/freepublications/publication/Captur_the_MultiplB enef_ofEnergyEficiency.pdf [September 29, 2015].
[10] Worrell, E.; Martin, N.; Price, L. Potentials for energy efficiency improvement in the US cement industry. Energy 2000, 25, 1189–1214.
© The authors retain all copyrights
This article is open access and distributed under the Creative Commons Attribution 4.0 International License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Authors disclose no conflict of interest or having no competing interest.
Vol. 12, Issue 05, PP. 105-116, May 2025
This work outlines a specific approach to the isolation of aerodynamic and physical factors towards enhancing flow control in the dynamic stall of rotating wings, a concern in rotor craft, wind turbines and UAVs. Employing a combination of CFD and ML, this research work focuses uniquely on aerodynamics of the aircraft by eliminating the impact of physical parameters like angular velocity, pitch rate, and angle of attack from lift, drag, and pressure distribution. This way, the research offers a finer view of the physical processes involved in vortex shedding, boundary layer development, and stall inception, which are critical to predicting and mitigating stall phenomena. The ML component uses data from CFD simulations to control parameters and provide real-time reaction to the aerodynamic changes. The results of this study show that, if these decoupled parameters are adjusted separately, one can control the stall onset and achieve up to 20% delay in lift hysteresis and control the flow stability across a broad range of operating points. This decoupling concept enables the accurate application of adjustment actions like adaptive pitch control and optimized rotation rates to the corresponding aerodynamic and physical conditions. The proposed approach provides a realistic solution for improving energy efficiency and operational reliability in the RWs subjected to high dynamic loads. This work not only contributes to the knowledge of dynamic stall phenomena in rotating wings but also opens the way to develop more robust and effective flow control strategies in aerospace and renewable energy applications.
[1] G Baldan and A Guardone. A deep neural network reduced order model for unsteady aerodynamics of pitching airfoils. Aerospace Science and Technology, 152:109345, 2024.
[2] G Baldan, F Manara, G Frassoldati, and A Guardone. The effects of turbulence modeling on dynamic stall, 2024. Available at: http://arxiv.org/abs/2404.14172.
[3] G Bangga, T Lutz, and M Arnold. An improved second-order dynamic stall model for wind turbine airfoils. Wind Energy Science, 5(3):1037–1058, 2020.
[4] P Broadley, MRA Nabawy, MK Quinn, and WJ Crowther. Dynamic experimental rigs for investigation of insect wing aerodynamics. Journal of the Royal Society Interface, 19(191):20210909, 2022.
[5] G. A. Flore and B. R. Noack. Flow control in wings and discovery of novel approaches via deep reinforcement learning. Fluids, 7(2), 2022.
[6] MA Garcia Teran, E Olguin-Diaz, A Flores-Abad, and M Nandayapa. Experimental validation of an aerodynamic sectional modeling approach in fixed-wing unmanned aerial vehicles. IEEE Access, 6:74190–74203, 2018.
[7] A Gardner, A Jones, K Mulleners, J Naughton, and M Smith. Review of rotating wing dynamic stall: Experiments and flow control. Progress in Aerospace Sciences, 137:100887, 2023.
[8] AD Gardner and K Richter. Influence of rotation on dynamic stall. Journal of the American Helicopter Society, 58(3), 2013.
[9] S Ho, H Nassef, N Pornsinsirirak, YC Tai, and CM Ho. Unsteady aerodynamics and flow control for flapping wing flyers. Progress in Aerospace Sciences, 39(8):635–681, 2003.
[10] HR Kim, JA Printezis, JD Ahrens, JR Seume, and L Wein. Characterization of dynamic stall on large wind turbines. pages 1–20, 2024. Available from April.
[11] X Li and L-H Feng. Critical indicators of dynamic stall vortex. Journal of Fluid Mechanics, 937:A16, 2022.
[12] Scheuer L. Kopel Y. Basescu M. Polevoy A. Wolfe K. Perrotta, G. and J. Moore. Planning and control for a dynamic morphing-wing uav using a vortex particle model. arXiv preprint, 2023.
[13] V Raghav and N Komerath. Dynamic stall life cycle on a rotating blade in steady forward flight. Journal of the American Helicopter Society, 60(3), 2015.
[14] V Raul and L Leifsson. Multifidelity aerodynamic shape optimization for mitigating dynamic stall using cokriging regression-based infill. Structural and Multidisciplinary Optimization, 66(11):237, 2023.
[15] Y Ruan and M Hajek. Numerical investigation of dynamic stall on a single rotating blade. Aerospace, 8:90, 2021.
[16] G. Sedky, A. Othman, and A. Wissa. Feather-inspired flow control: The flow physics of spatially distributed covert flaps. arXiv preprint arXiv:2311.16966, 2023.
[17] M. Sereez and M. Goman. Evaluation of aerodynamic characteristics in oscillatory coning using cfd methods. arXiv preprint, 2022.
[18] M Smith, A Gardner, R Jain, D Peters, and F Richez. Rotating wing dynamic stall: state of the art and future directions. Vertical Flight Society Annual Forum, 2020.
[19] M. J. Smith and F. Richez. Rotating wing dynamic stall: State of the art and future directions. HAL preprint, 2021.
[20] SMJ et al. Rotating wing dynamic stall: state of the art and future directions, 2021. HAL Id: hal-03106952.
[21] DA Sterpu, D Mariuta, and LT Grigorie. A udf-based approach for the dynamic stall evaluation of airfoils for micro-air vehicles. Biomimetics, 9(6), 2024.
[22] D. Traphan, Melius M. Peinke J. Gülker G. Wester, T. T. B., and R. B. Cal. Dynamic stall of an airfoil under tailored three-dimensional inflow conditions. arXiv preprint arXiv:2003.07840, 2020.
[23] Q Wang and Q Zhao. Numerical study on dynamic-stall characteristics of finite wing and rotor. Applied Sciences, 9(3), 2019.
[24] T Wong. Advanced airfoil. In Special Conference on Aeromechanics, 2010.
[25] G Wu, S Deng, and Q Li. Influence of area distribution along the span direction on flapping wing aerodynamics in hover based on numerical modeling analysis. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 17:6683–6692, 2024
© The authors retain all copyrights
This article is open access and distributed under the Creative Commons Attribution 4.0 International License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Authors disclose no conflict of interest or having no competing interest.
Vol. 12, Issue 05, PP. 91-104, May 2025
A key component of achieving higher efficiency is improving the process of metalizing silicon solar cells. Due to its simplicity and speed, contact realization by screen printing is now the most popular technology in the silicon-based photovoltaic sector. The issue with this type of metallization is that it has a higher contact resistance and a smaller aspect ratio, which restricts the efficiency of solar cells. Silicon solar cell producers are encouraged to develop new metallization techniques that use less silver and do not rely on the pressing process of screen printing due to the rising cost of silver pastes and decreasing silicon wafer thicknesses. Recently, a metallization technique that might address these problems is nickel/copper (Ni/Cu) based metal plating. In this review, we will describe the progress of electroplating techniques, mainly for the deposition of nickel/copper by laser deposition for nickel and the light-induced copper plating process. The metallization of the front-side silicon solar cells using a copper stack system is integral to achieving superior efficiency. The formation of a Ni seed layer by applying laser-assisted deposition has the advantage of using a single step for opening the ARC and the seed layer formation. Cu conducting layer using a light-induced plating (LIP) as the primary stack system, after applying a nickel seed layer to stop copper from diffusing into silicon, we also check tin as a top layer stack to protect it from oxidation. Moreover, we finally addressed the future advanced challenges and the issue of copper diffusion, background plating, and cost reductions.
N. Balaji, M. C. Raval, and S. Saravanan, “Review on Metallization in Crystalline Silicon Solar Cells,” in Solar Cells, IntechOpen, 2020. doi: 10.5772/intechopen.84820.
[2] M. T. Zarmai, N. N. Ekere, C. F. Oduoza, and E. H. Amalu, “A review of interconnection technologies for improved crystalline silicon solar cell photovoltaic module assembly,” Appl Energy, vol. 154, pp. 173–182, Sep. 2015, doi: 10.1016/j.apenergy.2015.04.120.
[3] D. Adachi, J. L. Hernández, and K. Yamamoto, “Impact of carrier recombination on fill factor for large area heterojunction crystalline silicon solar cell with 25.1% efficiency,” Appl Phys Lett, vol. 107, no. 23, Dec. 2015, doi: 10.1063/1.4937224.
[4] J. Cho et al., “Thermal stability improvement of metal oxide-based contacts for silicon heterojunction solar cells,” Solar Energy Materials and Solar Cells, vol. 206, p. 110324, Mar. 2020, doi: 10.1016/j.solmat.2019.110324.
[5] J. Yu et al., “Copper metallization of electrodes for silicon heterojunction solar cells: Process, reliability and challenges,” Solar Energy Materials and Solar Cells, vol. 224, p. 110993, Jun. 2021, doi: 10.1016/j.solmat.2021.110993.
[6] G. S. Seck, E. Hache, C. Bonnet, M. Simoën, and S. Carcanague, “Copper at the crossroads: Assessment of the interactions between low-carbon energy transition and supply limitations,” Resour Conserv Recycl, vol. 163, p. 105072, Dec. 2020, doi: 10.1016/j.resconrec.2020.105072.
[7] A. Rehman and S. Lee, “Review of the Potential of the Ni/Cu Plating Technique for Crystalline Silicon Solar Cells,” Materials, vol. 7, no. 2, pp. 1318–1341, Feb. 2014, doi: 10.3390/ma7021318.
[8] J. Sudagar, J. Lian, and W. Sha, “Electroless nickel, alloy, composite and nano coatings – A critical review,” J Alloys Compd, vol. 571, pp. 183–204, Sep. 2013, doi: 10.1016/j.jallcom.2013.03.107.
[9] A. ur Rahman and S. H. Lee, “Crystalline Silicon Solar Cells with Nickel/Copper Contacts,” in Solar Cells - New Approaches and Reviews, InTech, 2015. doi: 10.5772/59008.
[10] J. Bartsch, V. Radtke, C. Schetter, and S. W. Glunz, “Electrochemical methods to analyse the light-induced plating process,” J Appl Electrochem, vol. 40, no. 4, pp. 757–765, Apr. 2010, doi: 10.1007/s10800-009-0054-5.
© The authors retain all copyrights
This article is open access and distributed under the Creative Commons Attribution 4.0 International License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Authors disclose no conflict of interest or having no competing interest.