Authors | Shashikant Raghunathrao Deshmukh1, P. William2, Vaibhav D. Dabhade3, Laxmikant S. Dhamande4, Prasad M. Patare4, Yogeesh N5, R.A. Kapgate6 |
Affiliations |
1Department of Computer Engineering, Sanjivani College Engineering, Kopargaon, MH, India 2Department of Information Technology, Sanjivani College of Engineering, Kopargaon, MH, India 3MET Institute of Engineering, Nashik, India 4Department of Mechanical Engineering, Sanjivani College of Engineering, Kopargaon, MH, India 5Department of Mathematics, Government First Grade College, Tumkur, Karnataka, India 6Department of Mechatronics Engineering, Sanjivani College of Engineering, Kopargaon, MH, India |
Е-mail | shashikant.deshmukh1000@gmail.com |
Issue | Volume 17, Year 2025, Number 4 |
Dates | Received 23 March 2025; revised manuscript received 22 August 2025; published online 29 August 2025 |
Citation | Shashikant Raghunathrao Deshmukh, P. William, et al., J. Nano- Electron. Phys. 17 No 4, 04029 (2025) |
DOI | https://doi.org/10.21272/jnep.17(4).04029 |
PACS Number(s) | 68.65.Pq, 78.67.Sc, 82.45.Mp |
Keywords | Nanocomposite membrane, Two-dimensional (2D) materials, Water filtration, Graphene oxide (GO), Filtration quality. |
Annotation |
Potential water purification and separation technologies include nanocomposite filtration membranes. The complex relationships between numerous components make it difficult to estimate the rejection rate and filtration flux accurately. To address this issue and improve filtration performance in nanocomposite membranes, this research presents a novel Adaptive Golden Jackal Infused Random Forest (AGJ-RF) technique to predict the filtration efficiency in nanocomposite membranes. Polyvinylidene fluoride (PVDF) is the traditional membrane used for water treatment along with the two-dimensional (2D) materials, such as MXenes and graphene oxide (GO). The characterization technique known as permeability testing is employed for maintaining the effective filtration quality. A statistical technique known as analysis of variance (ANOVA) is employed to determine the variance. This analysis utilizes the SPSS software for the performance. The proposed method's efficiency in water filtration is conducted through Python platform. It evaluates the filtration flex and rejection rate by comparing the GO, Mxenes, and traditional membranes. The proposed AGJ-RF technique was performed in various matrices like RMSE (2.1), MAE (1.5) and R2 (0.88). The experimental finding shows that the proposed technique performed more significantly in the field of predicting filtration efficiency in nanocomposite membranes using 2D material. |
List of References |