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9 articles for “rheological response”
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Material-Level Degradation of Magnetorheological Fluids Under Long-Term Cyclic Shear
Abstract: The long-term functional stability of magnetorheological fluids (MRF) remains a key limitation for their reliable use in adaptive systems and continuously operated magnetorheological devices. In this study, the intrinsic evolution of rheological properties in a commercial MRF (MRC-C1L) is systematically examined under prolonged cyclic loading, with the aim of isolating material-level degradation mechanisms independent of device-related effects. The fluid was subjected to 120,000 low-strain oscillatory shear cycles under a constant …
Published in Journal of Polymer & Composites · Vol. 14, Issue 2, 2026 · pp. 101–112 Read article
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Hybrid Quantum–Machine Learning Framework for Nonlinear Rheological Modeling of Polymer and Composite Materials
Abstract: In polymer and composite materials, a major challenge lies in predicting their nonlinear rheological response, owing to complex multiscale interactions that are not captured by traditional constitutive laws or conventional machine learning approaches. In this study, a hybrid Quantum Machine Learning (QML) model comprising Quantum Support Vector Machine (QSVM) and Quantum Neural Network (QNN) architectures is proposed for viscosity prediction without requiring any specific rheological equation. To train and test …
Published in Journal of Polymer & Composites · Vol. 14, Issue 5, 2026 Read article
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Application of Smart Material Technology: A Review
Abstract: These days, smart materials are employed in every aspect of technology and human life. Much work is being done to explore their potential in different engineering applications that could benefit the average person. Shape memory alloys, piezoelectric materials, magneto rheological materials (MR), and electro rheological materials (ER) are just a few examples of the many diverse kinds of smart materials. The electric supply can be adjusted to change the viscosity …
Published in Trends in Mechanical Engineering & Technology · Vol. 14, Issue 1, 2024 · pp. 34–39 Read article
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A Comprehensive Study of ZnxFe2-xO3 Nanoparticles: Assessing Magnetic Properties for Medical Imaging (MI)
Abstract: Diluted magnetic ZnxFe2-xO3 nanoparticles are special semiconducting nanoparticles which are recognized for their magnetic properties. A theoretical examination of Zn-doped αFe2O3 nanostructures reveals a range of structural and property variations, offering insights into their potential applications and behavior at the nanoscale. In this regard, Heisenberg’s model and Weiss molecular filed theory is used to describe the magnetic properties of ZnxFe2-xO3 nanoparticles. These theorems inevitably enable to investigate the relationship between …
Published in Nano Trends – A Journal of Nano Technology & Its Applications · Vol. 26, Issue 2, 2024 · pp. 18–25 Read article
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Temperature-Dependent Viscoelastic Response of Magnetorheological Grease with Varying Particle Shapes
Abstract: This study examines the effect of temperatures on the magnetic and rheological properties of magnetorheological greases (MRGs) comprised of different particle shapes, under oscillatory shear mode test. Two samples were prepared with 70 wt.% flake-shaped electrolytic iron particles (EIP) and spherical carbonyl iron particles (CIP) which dispersed in 30 wt.% lithium-based grease, separately. Respective to magnetic properties test, the vibrating sample magnetometry (VSM) revealed that MRG-EIP exhibited 11.4% higher magnetic …
Published in Journal of Polymer & Composites · Vol. 13, Issue 6, 2025 · pp. 139–147 Read article
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Magnetorheological Composite Dampers for Railway Wagon Suspension: Modelling Validation and Performance Analysis
Abstract: Railway wagons encounter continuous vibrations due to track irregularities, resulting in reduced ride comfort and higher dynamic loads. Conventional suspension systems based on springs, hydraulic dampers, or air suspensions provide only limited vibration mitigation. This work investigates the application of magnetorheological (MR) fluid-based dampers, where a polymeric carrier oil (silicone oil) reinforced with carbonyl iron particles serves as a smart composite suspension medium. The MR fluid is synthesized and characterized …
Published in Journal of Polymer & Composites · Vol. 14, Issue 2, 2026 · pp. 43–63 Read article
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Structure–Property Relationships in Poly (N isopropylacrylamide) Hydrogels: Toward Thermoresponsive Polymer Composites
Abstract: Poly(N-isopropylacrylamide) (PNIPAAm) hydrogels can shift from solid to gel and back again at body temperature. Due to their lack structural integrity, thermal stability, and mechanical strength, they are difficult to use. This study mixed PNIPAAm with biocompatible fillers like chitosan and silicon nanoparticles to create hydrogels with superior structure-property correlations. Free radical polymerization with ammonium persulfate/TEMED initiator and N,N′-methylenebisacrylamide crosslinker produced the composites. Scanning electron microscopy showed a denser, interconnected …
Published in Journal of Polymer & Composites · Vol. 14, Issue 1, 2026 · pp. 884–895 Read article
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Influence of Carbonyl Iron Particle Loading on the Dimensional and Rheological Properties of 4D-Printed TPU-Based Magnetorheological Elastomers
Abstract: The advancement of 4D printing technologies has created new opportunities for fabricating smart materials with tunable properties, including magnetorheological elastomers (MREs). This study investigates the fabrication and characterization of thermoplastic polyurethane (TPU)-based MREs with varying carbonyl iron particle (CIP) loadings (10–50 wt.%) using the fused filament fabrication (FFF) method. MRE filaments were produced through a solvent-assisted mixing and extrusion process, ensuring consistent diameters within 1.75 ± 0.10 mm. Test specimens …
Published in Journal of Polymer & Composites · Vol. 13, Issue 6, 2025 · pp. 127–138 Read article
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Study of an Improved Quantum Particle Swarm Optimization-Based Framework for Neural Network Optimization in Modelling of Polymer Data
Abstract: The accurate forecasting of polymer viscosity at various physicochemical conditions has been quite critical due to the nonlinear interactions and interrelations between the variables. This paper suggests a better hybrid modelling framework, which involves the use of Artificial Neural Networks (ANN) and more advanced versions of Quantum Particle Swarm Optimization (QPSO) to better predict polymer viscosity. The input parameters taken are, namely, log (shear rate), polymer concentration, NaCl concentration, Ca …
Published in Journal of Polymer & Composites · Vol. 14, Issue 4, 2026 Read article