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251 articles for “Predictive Material Modeling”
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Computational Study of Sombor Index on Generalized Abid–Waheed Graphs for Polymer Modeling
Abstract: This study investigates the topological properties of generalized Abid Waheed graphs. Development of theoretical models in chemistry, reducing computational complexity while analysing large molecules or networks Abid Waheed graphs play a significant role. Motivated by these findings, the research was extended to encompass generalized Abid Waheed graphs, characterized by r cycles of order s. A notable similarity between Abid Waheed graphs and Jahangir graphs was observed. The potential applications of …
Published in Journal of Polymer & Composites · Vol. 13, Issue 5, 2025 · pp. 267–274 Read article
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AI-Accelerated Development of Gradient Polymer Nanocomposite Thin Films
Abstract: Gradient polymer nanocomposite thin films are an active field of materials research due to the fact that it enables scientists to de-facto regulate the optical, electrical, and mechanical properties of a film by merely altering its composition on a layer-by-layer basis. This type of control opens the gate to the improved flexible electronics, long lasting protective coats, and the new smart gadgets. The problem is, though, that it is a …
Published in Journal of Polymer & Composites · Vol. 14, Issue 2, 2026 · pp. 456–469 Read article
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Optimization of Surface Roughness in Cylindrical Traverse Cut Grinding of Glass Fibre Reinforced Epoxy Composite
Abstract: Glass fibre reinforced plastic materials are increasingly used in many engineering applications. Making these materials with high level of dimensional accuracy and fine finish has increased enormously. Present work is planned to investigate the effects of grinding parameters infeed, longitudinal feed and work speed on surface roughness in traverse cut cylindrical grinding of glass fibre reinforced epoxy composite. Box-Behnken experimental design has been used to conduct the experimental runs. Analysis …
Published in Journal of Production Research & Management · Vol. 10, Issue 3, 2020 · pp. 27–33 Read article
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IoT and Autonomous RC Boats for Water Quality Assessment: Trends, Challenges, and Future Prospects
Abstract: Nowadays the application of Internet of things (IoT) increasing in many applications like drone, remote control vehicles, electrical vehicle, etc. In this paper we proposed a way to check quality of water present in vast water bodies by Remote Controlled (RC) Boat. This RC environmental monitor boat collects water quality data and sends it online via the Internet of Things. So that we maintain the water by clean from received …
Published in Journal of Microelectronics and Solid State Devices · Vol. 12, Issue 1, 2025 · pp. 13–21 Read article
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Improving Photocatalytic and Antibacterial Properties of Zein/Polyvinyl Alcohol Polymer Composite Film by Dispersing TiO2 Nano Particles
Abstract: Zein/polyvinyl alcohol/nano-TiO2 composite film was effectively blended using a solution casting method. Mechanical, photocatalytic, and antibacterial properties of the composite film were evaluated. The breaking elongation of the composite film increased up to the maximum loading of 0.4% of nano-TiO2. The humidity and moisture content relationship was estimated with standard modified models of Halsey, Oswin, Chung Pfost, and Henderson. It was found that the Halsey model was the most suitable …
Published in Journal of Polymer & Composites · Vol. 8, Issue 2, 2020 · pp. 110–127 Read article
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Multi-Scale Analysis of Polymer Based Energy Storage Systems for High Performance Battery Applications
Abstract: The energy storage systems based on polymers are becoming promising materials for the next generation of high performance batteries because of their excellent mechanical flexibility, improved safety, and favorable electrochemical properties. Even with computational tools in Python, polymer-based energy storage systems remain plagued by poor ionic conductivity, complicated electrochemical reactions and potential thermal runaway. Therefore, a multi-scale model is proposed to improve battery performance, thermal stability, reliability, and large-scale deployment …
Published in Journal of Polymer & Composites · Vol. 14, Issue 3, 2026 · pp. 1035–1048 Read article
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Automated Microstructure Classification with Class-Specific Segmentation for Titanium Based Composite Materials
Abstract: In engineering, characterisation of microstructure is required to determine and forecast behaviour of titanium alloys. Our proposal in this work has been a deep-learning-based framework in the automatic classification and segmentation of Titanium Based Composite Material. The framework then uses EfficientNetB0 backbone, where we have chosen the backbone to scale the performance of classification and the computational efficiency with the assistance of the transfer learning and the compound scaling. In …
Published in Journal of Polymer & Composites · Vol. 14, Issue 3, 2026 · pp. 424–433 Read article
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Predicting Dielectric Constants of Polymers Using Molecular Structural Descriptors and Explainable Machine Learning: A Data-Driven Approach
Abstract: Accurate prediction of dielectric constants in polymeric materials is fundamental to the rational design of advanced electronic components, energy storage capacitors, flexible substrates, and high-frequency communication circuits. Conventional approaches to identifying suitable polymer dielectrics rely on extensive experimental synthesis and characterisation, which are both time-consuming and resource-intensive. In this work, an explainable machine learning framework is developed to predict the dielectric constant of polymers directly from molecular structural descriptors derived …
Published in Journal of Polymer & Composites · Vol. 14, Issue 3, 2026 · pp. 297–304 Read article
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The Effect of Welding Parameters and Tool Geometry on Mechanical Properties of RZ5-10 wt% TiC FSW Joint
Abstract: Friction Stir Welding (FSW) of metal matrix composite (MMC) provides the grain refinement and reinforcement redistribution of the composite used for wide application in aerospace and structural. This wide application needs development of best-suited joining process for MMC which is complicated to unite by the traditional welding process. The paper observed the consequence of the welding parameters and tools’ geometry on the mechanical properties of the friction stir butt welded …
Published in Journal of Polymer & Composites · Vol. 14, Issue 4, 2026 · pp. 81–94 Read article
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AI-Driven Topology Optimization of Woven Fiber-Reinforced Composite Chassis Structures for Electric Vehicles Under Crash Loading
Abstract: The structural design of an electric vehicle (EV) chassis represents a unique engineering challenge to achieve minimal weight while meeting occupants' safety requirements during high-energy crash conditions without compromise to the battery housing's integrity or the geometrical constraints of the electric powertrain package. In this paper, a single framework is proposed to integrate physics-based artificial intelligence (AI) surrogate models using PINNs, CNN-accelerated topology optimization, and FEA to design woven fiber-reinforced …
Published in Journal of Polymer & Composites · Vol. 14, Issue 2, 2026 · pp. 72–89 Read article
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Review On BIM-Based (Revit+Robot Software) Comparative Wind Load Analysis of High-Rise RCC Buildings in Zone-III, IV and V
Abstract: Wind load is one of the most critical factors influencing the design and serviceability of high-rise reinforced concrete (RCC) buildings. As building height increases, wind-induced effects such as storey drift, lateral displacement, and structural stiffness become dominant design considerations. Numerous studies have been conducted using conventional and advanced techniques such as Finite Element Method (FEM), Computational Fluid Dynamics (CFD), and Building Information Modelling (BIM). However, limited research focuses on comparative …
Published in Journal of Structural Engineering and Management · Vol. 13, Issue 2, 2026 · pp. 27–41 Read article
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Versatile CNC Machine for Tabletop Use Enhanced with Machine Learning Integration
Abstract: In the realm of tabletop multipurpose CNC machines, the integration of machine learning represents a groundbreaking advancement potentially revolutionary in the field of desktop manufacturing. This research explores the seamless incorporation of machine learning algorithms into tabletop CNC machines to enhance their capabilities, performance, and user experience. Through case studies and examples, we demonstrate the profound impact of machine learning integration in key areas of CNC machining, such as accurate …
Published in Journal of Polymer & Composites · Vol. 11, Issue 8, 2023 · pp. 353–361 Read article
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From Differential Equations to Data Science: A Survey on Analytical Methods in Contemporary Problems
Abstract: The integration of differential equations and data science methods represents a dynamic and evolving approach to solving contemporary challenges across a wide range of disciplines, including engineering, physics, biology, economics, and finance. Differential equations have long served as fundamental tools for modeling continuous systems and processes, offering powerful insights into the behavior of natural and man-made phenomena. For example, they describe how heat diffuses through materials, how populations grow in …
Published in Recent Trends in Mathematics · Vol. 2, Issue 2, 2025 · pp. 1–6 Read article
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Thermo-hydraulic Performance of Multi-Pass Double-Pipe Heat Exchangers: Integrating Polymer Composite Tube Wall Materials via CFD Parametric Study and Experimental Validation
Abstract: Metallic materials such as steel and copper have traditionally dominated heat exchanger manufacturing because of their excellent thermal conductivity, mechanical strength, and long-established industrial reliability. However, their high weight, susceptibility to corrosion in aggressive operating environments, and inability to provide tunable thermal properties have motivated interest in alternative materials for next-generation thermal systems. Thermally conductive polymer composites reinforced with graphene nanoplatelets (GNP), boron nitride (BN), and carbon-based fillers offer an …
Published in Journal of Polymer & Composites · Vol. 14, Issue 5, 2026 Read article
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AI-Enabled Optimization of Additively Manufactured Composite Materials for Enhanced Mechanical and Thermal Performance
Abstract: This paper discusses the optimization of multi-objective optimization of enhanced coupling of heat and mechanical properties of 3D printed polymer composite materials by artificial intelligence (AI), as a component of a multi-objective optimization framework. It aims at development of nonlinear printing parameters and material properties relationships to achieve maximum tensile strength and thermal conductivity in polymer composites produced through fused deposition modeling (FDM). Short carbon fiber reinforcement was used to …
Published in Journal of Polymer & Composites · Vol. 14, Issue 2, 2026 · pp. 867–891 Read article
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Artificial Neural Network Based Prediction of Impact Loads and Thickness in CFRP and GFRP Composite Laminates
Abstract: Recent technological advancements, particularly the integration of neural networks, have facilitated a predictive approach to complex engineering problems, especially those involving composite materials with directional properties. The scarcity of literature on predicting impact damage using experimental and ultrasonic flaw detection data motivated this study. Experimental assessment of impact damage on carbon fiber/epoxy (CFRP) and glass fiber/epoxy (GFRP) composites was conducted using low-velocity drop weight impact testing. Damage assessment employed an …
Published in International Journal of Fracture Mechanics and Damage Science · Vol. 2, Issue 1, 2024 · pp. 34–45 Read article
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Impact of Shape, Size and Crystal Structure on Vacancy Related Properties of Gold Nanoparticles
Abstract: It is necessary to consider defects to explain the electron movement, thermal transport and mechanical properties of materials. In the present study, a simple quantitative model for cohesive energy of nanoparticles is extended to determine the size, shape and crystal structure effect on vacancy formation energy, vacancy entropy, and vibrational frequency in free surface Au nanoparticles. Vacancy entropy variation with size has been studied for spherical, regular octahedral, regular hexahedral …
Published in Journal of Polymer & Composites · Vol. 13, Issue 1, 2025 · pp. 223–229 Read article
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Unified Ensemble Techniques for Enhanced DDoS Attack Prevention and Detection
Abstract: Today’s world is entirely reliant on the internet. The internet is a worldwide information source that all users rely on, hence its accessibility is critical. There have been reports in recent years, particularly in the information and technology division of significant organizations worldwide, of data breaches where the terms denial-of-service (DoS) and DDoS are consistently present in the stolen material. Network security is seriously threatened by DoS attacks. They have …
Published in International Journal of Wireless Security and Networks · Vol. 2, Issue 2, 2024 · pp. 20–27 Read article
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Polymer Nanocomposites As Emerging Platforms in Pharmaceutical Nanotechnology
Abstract: Nanotechnology allows the handling of materials in the 1–100 nm range, where distinct physicochemical phenomena, including quantum effects and higher surface-to-volume ratio, enable disruptive uses in pharmaceuticals and biomedicine. Significant challenges in solubility, stability and targeted biodistribution of therapeutics can be overcome by incorporating nanostructured polymers and polymer-based composites into drug delivery systems. PLGA nanoparticle and other nanocarriers, such as PLGA micelles, dendrimers, and hydrogels, have revealed promising effects on …
Published in Journal of Polymer & Composites · Vol. 14, Issue 1, 2026 · pp. 268–278 Read article
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Integrated Computational and Bio-catalytic Transformations: DFT-Guided Mechanistic Insights, Machine Learning, and Nano-biocatalyst Engineering for Sustainable Catalysis
Abstract: Computational catalysis has emerged as a transformative scientific discipline that integrates quantum chemistry, molecular modeling, machine learning, and density functional theory (DFT) to understand catalytic mechanisms and design highly efficient catalytic systems for sustainable industrial applications. The increasing global demand for environmentally responsible chemical manufacturing has accelerated research on advanced catalytic materials including transition metal catalysts, metal–organic frameworks (MOFs), homogeneous catalysts, heterogeneous systems, and bimetallic catalysts involving nickel and iron. …
Published in Journal of Catalyst & Catalysis · Vol. 13, Issue 2, 2026 · pp. 36–44 Read article