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24 articles for “property gradient”
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A Mini Review of Synthesis and Applications of Functionally Graded Materials
Abstract: Material composition or microstructure varies gradually along the thickness over a specific volume in functionally graded material (FGM) that results in spatial change in properties like thermal conductivity, strength, stiffness, electrical, magnetic, and light properties, etc. Application of the concept of FGM leads to a single product that has multiple properties in it as demanded by the operational or functional requirements of the product under service conditions. It also allows …
Published in Journal of Polymer & Composites · Vol. 14, Issue 1, 2026 · pp. 54–65 Read article
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Investigation of the Thermoelectric, Electronic Band Profile, and Structural Properties of Skutterudites Based on Cobalt and Antimony
Abstract: We investigated ThCo4Sb12, an actinium-filled skutterudite, from the ground up for structural, electronic, and thermoelectric properties. A generalized gradient approximation and modified BeckeJohnson potentials were used to calculate the exchange-correlation potential. The compound is shown to have metallic properties in the electronic structure calculations. Actinium series element is used as a void filler in this study. The Seebeck coefficient and electrical conductivity can be calculated using Boltzmann's transport theory. According …
Published in Journal of Structural Engineering and Management · Vol. 11, Issue 2, 2024 · pp. 13–19 Read article
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Comparative Buckling Load Analysis of Thin Functionally Graded Material Plates with Variable Distributions: Power Law vs. Sigmoidal vs. Exponential
Abstract: A comprehensive comparative analysis of buckling load behavior in thin Functionally Graded Material (FGM) plates with variable material distributions is presented in this paper. FGMs, characterized by gradient composition, possess unique mechanical properties suitable for diverse engineering applications. The study focuses on three distinct distribution functions: Power Law, Sigmoidal, and Exponential, each exerting different influences on the material gradient. Finite Element Analysis is utilized in exploring the buckling response for …
Published in Journal of Polymer & Composites · Vol. 12, Issue 3, 2024 · pp. 98–105 Read article
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AI-Driven Prediction of Mechanical and Thermal Properties in Polymer-Based Functionally Graded Composites
Abstract: The proposed architecture of the current paper is an artificial intelligence (AI)-driven model of forecasting mechanical and thermal aspects of polymer-based functionally-graded composites (FGCs). Traditional micromechanical and finite element models, which are practical in homogeneous composites, might not be able to account in nonlinear interaction that is caused by compositional gradient. To overcome the challenge, machine learning (ML) models like artificial neural network (ANN), support vectors regression (SVR), and gradient-boosted …
Published in Journal of Polymer & Composites · Vol. 14, Issue 3, 2026 · pp. 70–89 Read article
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Bio-Inspired FGPCs for Biomedical and Structural Applications
Abstract: Bio-inspired functionally graded polymer composites (FGPCs) represent a new class of smart materials that use gradient material distributions to enhance mechanical and biological properties, mimicking natural systems like bones, shells, and plant stems. FGPCs exhibit smooth gradient distributions across interfaces, which improves biocompatibility and reduces the risk of failure under complex loading and environmental conditions. In this study, bio-inspired FGPCs were designed, fabricated, and validated using a combined experimental and …
Published in Journal of Polymer & Composites · Vol. 14, Issue 2, 2026 · pp. 456–481 Read article
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Explainable Machine Learning for Process Parameter Optimization in Gradient 3D-Printed Polymer Composites
Abstract: The explainable machine learning-based structure may be employed to achieve a favorable process parameter of the graduate 3D-printed polymer composite structures to improve the mechanical and thermal properties without compromising the transparency of the decisions made during the fabrication process. Gradient composite specimens were made by systematically varied process parameters like nozzle temperature, raster orientation, deposition speed, gradient transition rate and fused filament fabrication. A predictive model of tensile strength …
Published in Journal of Polymer & Composites · Vol. 14, Issue 2, 2026 · pp. 847–866 Read article
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AI-Designed Functionally Graded Polymer Composites for Multifunctional Thin Films
Abstract: The design of multifunctional polymer composite thin films requires simultaneous optimization of mechanical, optical, barrier, and thermal properties—objectives often in conflict when using conventional homogeneous materials. This study presents an artificial intelligence-driven framework for designing functionally graded material (FGM) architectures in polymer nanocomposite thin films. We integrated machine learning with physics-based modeling to optimize compositional gradients across film thickness, achieving superior performance compared to homogeneous and discrete multilayer alternatives. A …
Published in Journal of Polymer & Composites · Vol. 14, Issue 2, 2026 · pp. 1026–1041 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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Data-Driven Digital Twin Model for Real-Time Strength Estimation in Polymeric Materials
Abstract: The real-time prediction of mechanical properties in polymeric materials is essential for ensuring quality, consistency, and operational efficiency in modern manufacturing systems. As industrial processes become increasingly complex, traditional trial-and-error approaches to material characterization are no longer sufficient to meet the demands of high-throughput production environments. This study introduces a digital twin-integrated machine learning approach for the real-time estimation of tensile strength in polymeric materials by combining simulation-driven insights with …
Published in Journal of Polymer & Composites · Vol. 14, Issue 3, 2026 · pp. 246–257 Read article
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Density Functional Theory (DFT): Understanding and Quantifying Molecular Structure of 2-D Materials
Abstract: Density Functional Theory (DFT) has emerged as a cornerstone in computational chemistry and materials science, offering a powerful framework for predicting electronic structures and properties of atoms, molecules, and solids. By focusing on electron density rather than wave functions, DFT simplifies the many-body problem through approximations like the local density approximation (LDA) and generalized-gradient approximations (GGAs). The Hohenberg-Kohn theorems establish the theoretical foundation, proving that ground-state properties are uniquely determined …
Published in Journal of Microelectronics and Solid State Devices · Vol. 12, Issue 2, 2025 · pp. 33–40 Read article
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Structural, Electronic and Optical Properties of ZnO Material Using First Principle Calculation
Abstract: Structural, electronic and optical properties have been determined by using first principle calculation for ZnO material. In present study, full potential linearized augmented plane wave method has been selected with generalised gradient approximation executed in WIEN2k. Structure of ZnO material stabilises in the Wurtzite form of hexagonal closed packed crystal with lattice constant a=3.289Å, c= 5.307Å. Density of states and band structure diagram of ZnO material shows semiconductor nature with …
Published in Journal of Polymer & Composites · Vol. 11, Issue 5, 2023 · pp. 27–34 Read article
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Machine Learning Assisted Design and Analysis of Polymer Composite Materials for Sustainable Renewable Energy Systems
Abstract: Accurate prediction and optimization of polymer composite properties is of paramount importance in the design of these lightweight, durable, and sustainable materials within renewable energy technologies. This work will provide a holistic machine learning-assisted framework that unites materials informatics with domain-specific features and state-of-the-art ML methodologies in the prediction of the mechanical properties of polymer composites, such as tensile strength. This includes embedding several ensemble models, including Random Forest and …
Published in Journal of Polymer & Composites · Vol. 14, Issue 3, 2026 · pp. 391–402 Read article
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AI-Driven Optimization of Biopolymer Composite Formulations Using IoT Data Streams
Abstract: Biodegradable polymer composites have emerged as a sustainable alternative to petroleum-based materials in packaging, biomedical, and structural applications. However, traditional formulation techniques for reinforced polymer composites often lack precision and fail to adapt to real-time variations during processing, resulting in suboptimal material performance. This research proposes a real-time AI-IoT-enabled framework to optimize biopolymer composite formulations. The goal is to intelligently tune composite properties such as mechanical strength, moisture resistance, and …
Published in Journal of Polymer & Composites · Vol. 13, Issue 5, 2025 · pp. 85–100 Read article
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Detection of Phished URLs Using Machine Learning
Abstract: Phishing attacks remain a significant cybersecurity challenge, requiring innovative detection strategies. This study investigates the use of machine learning to detect phishing URLs, to improve the accuracy and reliability of detection systems. Utilizing a diverse dataset of legitimate and phishing URLs we extracted the features such as lexical properties, domain-specific details, and HTML content to train various machine learning models. Algorithms including Random Forest, support vector machine (SVM), and gradient …
Published in Journal of Web Engineering & Technology · Vol. 11, Issue 3, 2024 · pp. 1–7 Read article
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Prediction of Mechanical Properties for Advanced Engineering Applications utilizing Polymer Composite Materials by Machine Learning
Abstract: Polymer composites show great promise as engineering materials because of their mechanical performance, resistance to corrosion, lightweight nature, and adaptability in design. Aerospace, automotive, biomedical, maritime, and civil engineers all rely on mechanical property prediction to cut down on trial expenses, expedite product development, and optimize material selection. Speedy design optimization is not possible using traditional numerical and experimental methods due to the high costs associated with material characterisation, computational …
Published in Journal of Polymer & Composites · Vol. 14, Issue 3, 2026 Read article
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Architectured Multiphase Polymeric Carriers with Microstructural Gradients: Synergistic Filler Effects for the Precision Delivery in Tuberous Plant Systems
Abstract: In this paper, 50 papers were reviewed to analyse the design, techniques, and applications of polymer composite systems for delivering agrochemicals against major tuberous plant pathogens, including fungi, bacteria, and nematodes. Primary tuber plant pathogens affecting yield are studied, followed by a study of control strategies. This is followed by a study of the basic properties of polymer composites, including the significance of natural and synthetic polymers. Then, the study …
Published in Journal of Polymer & Composites · Vol. 14, Issue 3, 2026 · pp. 940–949 Read article
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A Review on Materials and Working Process Parameters of Selective Laser Sintering
Abstract: The potential for additive manufacturing technology to replace some of the current conventional manufacturing methods makes it one of the research and development fields that is expanding quickly. With additive manufacturing, three-dimensional physical models are produced layer by layer from computer-aided design (CAD) models. Fully dense metal things may be produced more rapidly and accurately with additive manufacturing. The Selective Laser Sintering (SLS) procedure uses powder bed fusion, in which …
Published in Journal of Polymer & Composites · Vol. 13, Issue 2, 2025 · pp. 522–529 Read article
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AR Coatings in Solar Efficiency: A Study
Abstract: In the global race toward renewable energy dominance, the focus often fixes upon the exotic materials within the photovoltaic cell: silicon type, junction structure, or emergent perovskites. Yet, the most immediate and profound efficiency gains are often secured by a layer so thin it is invisible, a film of optimized material applied directly to the glass interface: the Anti-Reflective (AR) coating. These coatings are not merely an expensive aesthetic choice; …
Published in Journal of Thin Films, Coating Science Technology & Application · Vol. 12, Issue 3, 2025 · pp. 26–35 Read article
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Autonomous Agentic AI for Adaptive Cure Optimization and Defect Prevention in Thermoset Polymer Composite Manufacturing
Abstract: Thermoset polymer composites occupy a central position in modern structural manufacturing, from aircraft fuselages to wind-turbine blades. Despite progress in resin chemistry and fiber architecture, the “cure process” that transforms compliant preforms into load-bearing structures remains difficult to manage. Manufacturers encounter ‘voids’, “interlaminar delaminations”, and “spring-back distortion” when curing complex or thick-section parts. The cause is not ignorance of the relevant physics, but rather that ‘temperature’, ‘chemistry’, ‘rheology’, and ‘mechanics’ …
Published in Journal of Polymer & Composites · Vol. 14, Issue 2, 2026 · pp. 301–320 Read article
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Designing and Analysis of Different Types of Fins in Air Cooled Engine
Abstract: This paper is dedicated to the study of various shapes of extended surfaces, commonly known as fins, which are used on cylinder heads of internal combustion engines. Extended surfaces are used to improve heat dissipation from the object by increasing its effective surface area. Efficient heat dissipation is very important since proper cooling of an engine cylinder head helps to maintain optimal working temperatures, improves engine performance, increases service life, …
Published in Journal of Thermal Engineering and Applications · Vol. 13, Issue 1, 2026 · pp. 33–79 Read article