Search Results

Now showing 1 - 4 of 4

Some of the metrics are blocked by your
consent settings
Advanced inorganic membranes for water purification: FeZr-MOF/GO composites with optimized adsorption performance
(Elsevier BV, 2025-12)
Meng-en Liu
;
Ling Liu
;
Hasan Sh. Majdi
;
Ibrahim Albaijan
;
Meldi Suhatril
This study introduces FeZr-MOF/Graphene Oxide (GO) composite membranes as an innovative application of inorganic membrane technology for advanced separation and purification. These membranes were engineered to efficiently remove industrial dyes such as Congo red and methylene blue from aqueous solutions by leveraging the high surface area, chemical stability, and selective adsorption capabilities of FeZr-Metal-Organic Framework (FeZr-MOF). Based on laboratory evaluations, the composite membranes exhibited strong adsorption performance, achieving 87.5 mg/g capacities for Congo red and 80.2 mg/g for methylene blue. Integrating GO into the membrane matrix enhanced hydrophilicity, water permeability, and anti-fouling behavior, as evidenced by over 90 % permeability recovery after multiple cleaning cycles. This research reflects the latest advancements in inorganic membrane technology and bridge material innovation with industrial water purification needs. Machine Learning (ML), implemented via the Random Forest (RF) algorithm, was used to predict the impact of key operational parameters—pH, dye concentration, and contact time—on removal performance, and the model's predictions aligned closely with experimental trends. These findings, supported by experimental data and predictive modeling, highlight the potential of FeZr-MOF/GO membranes as a scalable and robust material for sustainable water purification applications.
Some of the metrics are blocked by your
consent settings
Delamination, frequency, and bending analysis of GPLRC curved panel with initial crack via machine learning and three-dimensional layerwise theory
(Elsevier BV, 2025-12)
Xinrong Cao
;
Xiaohong Yang
;
Linyuan Fan
;
HABIBI, MOSTAFA
;
Ibrahim Albaijan
In the present study, the thermal stability of graphene-reinforced composite laminates (GPL-RC) with diverse functional gradients and width delamination layers is examined. In this regard, various models of laminated GPL-RC are considered with different geometrical and material parameters. Utilizing the physics-informed neural networks (PINN), we calculate the energy release rate (ERR) at the cleavage boundary, aiming to gauge cleavage growth potential. This study also delves effects of various graphene reinforcement distributions and delamination configurations on the vibrational attributes of delaminated GPL-RC sheets, with an emphasis on pre/post heat bending modalities. Solutions are grounded in the third-order shear strain theory (TSDT), integrating von Karman geometric nonlinearity. Using the principle of minimal potential energy, the nonlinear equilibrium equations are tackled using PINN. Theoretical insights obtained are verified via a comparison to other published studies. Notably, parametric experiments indicate that the ERR in the FGX configuration in which most reinforcement material located adjacent to the upper and lower surfaces of the plate, is double that of the FGA, in which most reinforcement material adjacent to the lower surface of the plate. Moreover, while the FGX sheet's fundamental frequency surpasses other graphene configurations at the primary temperature, its natural frequency in the post-buckling modality is notably the least compared to the entire sample set.
Some of the metrics are blocked by your
consent settings
Use of metamaterials in graphene origami configuration for an electromagnetoelastic sandwich composite beam
(2025-02-25)
Ruoxin Lin
;
Linyuan Fan
;
Lixi Liu
;
HABIBI, MOSTAFA
;
Ibrahim Albaijan
A parametric study on the impact of graphene origami content on the deformation and strain results of a double curved shell is presented. The formulation is extended using the shear deformability property of the kinematic model and the constitutive relations are extended using the overall material properties for the nanofolded composite structures in the thermal environment. The analytical-based method is developed using the energy-based framework for derivation of the governing equations of a nanocomposite double curved shell. The analytical results are extracted using the trigonometric functions in order to satisfy the required boundary conditions.
Some of the metrics are blocked by your
consent settings
An inspection of the metal-foam beam considering torsional dynamic responses
(Elsevier BV, 2024-11)
Jiaman Li
;
Zhixin Wu
;
Mostafa Habibi
;
Ibrahim Albaijan
Metal foam is a multifunctional material with a lower specific weight, high stiffness and compressive strength, and high energy absorption. These remarkable properties make metal foams a promising candidate for conventional materials in different industrial fields. Despite numerous researches on mechanical behavior either static or dynamic of structures made of metal foams, torsional vibration analysis of metal foam structures is still uninvestigated. In this investigation, the influence of various imperfection distribution patterns on the torsional dynamic response of metal foam beams is examined within the framework of Timoshenko-Gere's theory. Two common materials i.e. SUS304 and Aluminum foams are considered the constructive materials of structure. Moreover, three imperfection distribution patterns are taken into account. The virtual work's principle has been employed to derive the torsional governing equation of metal foam beams. Then, the derived governing equation has been solved via an analytical method. The accuracy of the employed methodology has been compared with the findings of former research in the literature. Finally, the influences of different notable parameters on the variation of natural torsional frequency have been examined and demonstrated in a group of tables and diagrams.

CRIS

Browse

Filters

Settings

Sort By

Results per page

Search Results