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Your search keyword '"Arslan, Chaudhry"' showing total 14 results
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14 results on '"Arslan, Chaudhry"'

4. Contributors

Author

Abdel-Raouf, Manar E., primary, Ahmad, Akil, additional, Ahmad, Sajid R., additional, Ali, Nisar, additional, Alshammari, Mohammed B., additional, Anjum, Ph.D, Muzammil, additional, Ansari, Shahid P., additional, Aragaw, Tadele Assefa, additional, Arslan, Chaudhry, additional, Ayalew, Adane Adugna, additional, Ayub, Muhammad, additional, Bilal, Muhammad, additional, Dustgeer, Mohsin R., additional, Gao, Xiaoyan, additional, Gillani, Syed H., additional, Ghotekar, Suresh, additional, Godiya, Chirag Batukbhai, additional, Haque, Md. Morshedul, additional, Hasan, Abdulraheim M.A., additional, Ibrahim, Mohamad Nasir Mohamad, additional, Idris, Mustapha Omenesa, additional, Ismail, Ahmad F., additional, Jaafar, Juhana, additional, Jawaid, Mohammad, additional, Jilani, Asim, additional, Kamaludin, Roziana, additional, Kanwal, Ansa, additional, Khalid, Ph.D, Azeem, additional, Khan, Adnan, additional, Khatoon, Asma, additional, Khurshid, Mohsin, additional, Kian, Lau Kia, additional, Liu, Ph.D, Wei, additional, Malik, Sumeet, additional, Mirza, Muhammad A., additional, Mohammad S, Aleid G., additional, Nasir, Abdul, additional, Ni, Lingli, additional, Niloy, Nahin Mostofa, additional, Othman, Mohd Hafiz Dzarfan, additional, Parvin, Fahmida, additional, Qadeer, Ph.D, Samia, additional, Rahman, Mukhlis A., additional, Rashid, Haroon, additional, Roy, Arpita, additional, Ruotolo, Luis A.M., additional, Saba, Naheed, additional, Sarmad, Muhammad, additional, Setapar, Siti H.M., additional, Shakoor, Muhammad B., additional, Siddique, Affia, additional, Siddique, Jamal A., additional, Tareq, Shafi M., additional, Tariq, Waheed, additional, Tayyab, Nafeesa, additional, Yang, Yong, additional, Yaqoob, Asim Ali, additional, Zakria, Hazirah S., additional, and Zubair, Muhammad, additional

Published
2023
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9. Discrete Element Method (DEM) simulation of three-dimensional forces of full-scale mouldboard plow on paddy soil.

Author

Mari, Irshad Ali, Shaikh, Sher Ali, Chandio, Farman Ali, Arslan, Chaudhry, Ahmad, Fiaz, and Changying Ji

Subjects
DISCRETE element method, SOIL particles, SOILS, CUTTING force
Abstract

Discrete element modelling (DEM) is widely regarded as one of the most effective methods for simulating the soil-to-tool interaction. Discrete element simulations were carried out to evaluate the performance of mouldboard plough in paddy soil. The Hertz-Mindlin bonding contact model was applied to develop the bonding between soil particles. Maximum soil draught force (3.64 N) was obtained at 15 cm depth. The force decreased from 1.98 to 1.10 N as the depth decreased from 10 cm to 5 cm. From the results, the DEM have the potential to predict cutting forces of mouldboard plough in all direction draught, vertical and side (Fx, Fy and Fz. A linear relationship was observed throughout the simulation process between working depths. It is concluded that the EDEM model has the potential to serve as a reliable tool for determining the soil-tool interaction. [ABSTRACT FROM AUTHOR]

Published
2023

13. Synthesis and applications of graphene and graphene-based nanocomposites: Conventional to artificial intelligence approaches

Author

Tariq, Waheed, Ali, Faizan, Arslan, Chaudhry, Nasir, Abdul, Gillani, Syed Hamza, and Rehman, Abdul

Subjects
General Medicine
Abstract

Recent advances in graphene research have enabled the utilization of its nanocomposites for numerous energy-based and environmental applications. Recently, the advancement in graphene-based polymer nanocomposites has received much attention with special emphasis on synthesis and application. Graphene-based nanocomposites show astonishing electrical, mechanical, chemical, and thermal characteristics. Graphene nanocomposites (GNCs) are synthesized using a variety of methods, including covalent and non-covalent methods, a chemical-based deposition approach, hydrothermal growth, electrophoresis deposition, and physical deposition. Chemical methods are the most viable route for producing graphene in small quantities at low temperatures. The technique can also produce graphene films on a variety of substrate materials. The use of artificial intelligence (AI) for the synthesis of AI-created nanoparticles has recently received a lot of attention. These nanocomposite materials have excellent applications in the environmental, energy, and agricultural sectors. Due to high carrier mobility, graphene-based materials enhance the photocatalytic performance of semiconductor materials. Similarly, these materials have high potential for pollutant removal, especially heavy metals, due to their high surface area. This article highlights the synthesis of graphene-based nanocomposites with special reference to harnessing the power of modern AI tools to better understand GNC material properties and the way this knowledge can be used for its better applications in the development of a sustainable future.

Published
2022

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