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90 articles for “Structure–property relationships”
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Machine Learning-Based Quantification of Polymer Structure Property Relationships for Predictive Material Design
Abstract: Polymer structures exhibit complex, hierarchical arrangements that strongly influence macroscopic properties, yet consistent quantification remains challenging due to nonlinear interactions and limited unified modeling strategies. Existing approaches inadequately capture generalized structure–property mappings across diverse polymer systems. This research aims to establish a machine learning-based quantification model for polymer structure–property relationships to support predictive material design. A Polymer Structure Property Dataset of 5,000 polymer samples includes structural descriptors and experimentally measured …
Published in Journal of Polymer & Composites · Vol. 14, Issue 3, 2026 · pp. 737–754 Read article
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Machine Learning Based Optimization of Polymer Structure Property Relationships in Composite Material Systems
Abstract: In modern engineering applications, polymer-based composite materials have garnered a lot of attention because of their lightweight nature, high strength-to-weight ratio, and changing physical features. In order to maximize the relationships between polymer structure and properties in composite materials, this study suggests a strategy based on reinforcement learning (RL). The research utilized the Polymer Composite Properties Dataset, which contains 12,700 records associated with polymer matrices, reinforcement fillers, interfacial bonding characteristics, …
Published in Journal of Polymer & Composites · Vol. 14, Issue 3, 2026 · pp. 242–255 Read article
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Image-Based Quantitative Mapping of Structure Property Relationships in Polymer Composite Materials
Abstract: The performance of polymer composite materials is intrinsically governed by their microstructural architecture, which is shaped by manufacturing conditions and constituent interactions. Despite extensive experimental characterization efforts, establishing transparent and quantitative structure–property relationships from microstructural images remains a challenge. In this study, an explainable image-driven framework is developed to systematically correlate microstructural features with composite property indicators. Microstructure images are processed to identify voids, fibers, and filler phases, from which …
Published in Journal of Polymer & Composites · Vol. 14, Issue 3, 2026 · pp. 188–196 Read article
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Structure-Property-Process Relationships in BNNS-Modified PEEK Nanocomposites for High-Performance Applications
Abstract: This study reports the design and performance evaluation of boron nitride nanosheet (BNNS)-reinforced polyetheretherketone (PEEK) nanocomposites fabricated using melt compounding and high-temperature Fused Filament Fabrication (FFF). PEEK, a high-performance thermoplastic, was reinforced with BNNS at 0.5–5wt.% to enhance mechanical, thermal, and tribological functionalities for advanced engineering use. Composite filaments were extruded and printed using a modified Bambu Lab FFF printer. Mechanical testing revealed a peak tensile strength of 108 MPa …
Published in Journal of Polymer & Composites · Vol. 14, Issue 1, 2026 · pp. 867–888 Read article
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Biopolymer Degradation and Structure–Property Relationships in Ageing: A Polymer Science Perspective
Abstract: Ageing, as viewed from the polymer sciences perspective, is perceived as the gradual modification of the structure-property-function interrelationship of biopolymers such as proteins, polysaccharides, nucleic acids and their molecular aggregates. Such changes include structural organization, mechanical behavior, physicochemical stability and functional effectiveness. Ageing is an inevitable multifactorial polymeric process. Due to the growing aging population globally, more age-associated complications emerge, which are correlated with the molecular degeneration of biopolymeric complexes. …
Published in Journal of Polymer & Composites · Vol. 14, Issue 3, 2026 · pp. 479–489 Read article
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Crystallographic Studies on The Stability of Pharmaceutical Compound
Abstract: Crystallographic studies provide detailed insights into the molecular structure and intermolecular interactions within a crystal lattice, which are key determinants of a compound's stability. By analyzing crystal structures, researchers can identify potential polymorphs, solvates, and hydrates that may impact the physical and chemical stability of the drug. This knowledge helps in optimizing formulation strategies, predicting shelf life, and ensuring consistent drug performance. Advanced techniques like X-ray diffraction and neutron diffraction …
Published in International Journal of Crystalline Materials · Vol. 1, Issue 1, 2024 · pp. 38–42 Read article
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Polypropylene Fibres in Cementitious Composites: A Critical Review of Polymer Structure, Processing, Interfacial Behaviour and Performance
Abstract: Polypropylene (PP) fibres are widely used as secondary reinforcement in cementitious composites, yet their performance is governed as much by polymer structure and interfacial chemistry as by dosage. This review synthesises 50 primary sources (2003-2025, concentrated post-2015) to examine how PP molecular structure, fibre-manufacturing history, morphology, surface properties and environmental ageing govern fibre-matrix interaction and multiscale composite performance. Isotacticity, molecular weight, crystallinity and drawing ratio are shown to set the …
Published in Journal of Polymer & Composites · Vol. 14, Issue 4, 2026 Read article
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Computational Intelligence and Neuro-Fuzzy Modelling of Polymer Composites: A Critical Review of Performance Prediction and Optimization
Abstract: The increased variety in polymer matrices, reinforcements, fillers, and processing parameters has led to the need to better understand the structure-property, process-property relationships in order to accurately predict and optimize the performance of polymer composites. This paper reviews the applications of computational intelligence methods in polymer composites, with special focus on artificial neural networks, adaptive neuro-fuzzy inference systems, machine learning techniques, and hybrid optimization. The literature is analyzed based on …
Published in Journal of Polymer & Composites · Vol. 14, Issue 4, 2026 Read article
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Hybrid Polymer Composites Containing GGBS and Copper Slag: A Review of Mechanical Behavior and Interfacial Mechanisms
Abstract: Over the past few years, there has been a push to seek sustainable solutions through material science in the field of industrial by-products that can be used in polymer composite systems. Two such substances are ground granulated blast furnace slag (GGBS) and copper slag that have demonstrated a promising potential because of their abundance and useful physical and chemical properties.This review is dedicated to the application of GGBS and copper …
Published in Journal of Polymer & Composites · Vol. 14, Issue 3, 2026 · pp. 43–50 Read article
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A Study on The Impact of Artificial Intelligence in Pharmaceuticals
Abstract: The main goal of artificial intelligence (AI) is to create intelligent modeling, which facilitates knowledge imagination, problem-solving, and decision-making. AI is becoming more and more significant in several pharmacy domains, including polypharmacology, hospital pharmacy, drug discovery, and drug delivery formulation development. Various types of artificial neural networks (ANNs), including deep neural networks (DNNs) and recurrent neural networks (RNNs), are utilized in the development of drug delivery formulations and in drug …
Published in Research & Reviews: A Journal of Drug Design & Discovery · Vol. 12, Issue 1, 2025 · pp. 24–32 Read article
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Polymer Composite Phase Change Materials: Materials Design, Processing, Characterization, and Structure–Property Relationships—A Comprehensive Review
Abstract: Polymer composite phase change materials (PCPCMs) have been recognized as an innovative category of multifunctional polymeric materials, which could be tuned by appropriate materials design, composite formation, and interface modification. With the incorporation of phase change materials in polymer matrix systems and functional fillers, PCPCMs show improved mechanical properties, physicochemical stability, and functionality in contrast to traditional phase change materials. With recent advances in polymer science, nanocomposites, and processing techniques, …
Published in Journal of Polymer & Composites · Vol. 14, Issue 5, 2026 Read article
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Ligand Efficiency in Relation to 3D Physicochemical Characters of Novel HIV-1 Vif Antagonist: An Approach in The Optimization of HIV Drugs
Abstract: AbstractLigand efficiency is a design framework commonly used in drug discovery. Thirty-six (36) newly discovered 1,2,3-triazole analogues as potent new inhibitors of HIV-1 Vif were subjected to quantitative structure-property relationship (QSPR) modeling to predict their ligand efficiencies (LE) in an attempt to improve/optimize it by using some numerical data of HIV-1 Vif inhibitors based on their physical and chemical properties (descriptors). Various 3D physicochemical properties or descriptors were calculated from …
Published in Research & Reviews: A Journal of Drug Formulation, Development and Production · Vol. 9, Issue 3, 2022 · pp. 50–59 Read article
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Advances in Nanocellulose-Enhanced Polymers and Composites: Structure, Performance, and Applications
Abstract: The most common biopolymer is cellulose, which can be converted into nanocellulose (NC) the sustainable nanomaterial possessing the outstanding characteristic of biodegradability, renewability, low density, high aspect ratio, and excellent mechanical performance. Such distinctive features make NC a promising filler in polymer and composite systems. Recent developments in the preparation of nanocellulose using various natural and artificial sources have facilitated scalable production processes that have less energy requirements and are …
Published in Journal of Polymer & Composites · Vol. 14, Issue 1, 2026 · pp. 1610–1623 Read article
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Physics-Informed Machine Learning and Multiscale Modeling for Structure–Property Quantification of Polymer Composites
Abstract: The growing need for light-weight, high strength, and sustainable polymer composites has led to the development of smart methods that enable accurate structural-property quantification and material design. However, conventional methods have been predominantly data-based, thus ignoring physical constraints as well as multi-scale interactions involving fiber, matrix, interface, and process parameters, leading to lower accuracy and poor robustness and interpretability of the models. In this study, a Cat Swarm Optimization-Tuned Physics-Informed …
Published in Journal of Polymer & Composites · Vol. 14, Issue 4, 2026 Read article
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Computational Modeling of Polymer Semiconductors for Electronic Applications
Abstract: Polymer semiconductors have become important materials in modern electronic applications because they combine semiconducting behavior with mechanical flexibility, low-cost processing, and tunable molecular structure. Their growing use in organic field-effect transistors, organic photovoltaics, organic light-emitting diodes, and flexible sensing devices has increased the need for accurate computational approaches that can predict material properties and device performance before experimental fabrication. This paper reviews the major computational modeling techniques used for polymer …
Published in Journal of Polymer & Composites · Vol. 14, Issue 3, 2026 · pp. 132–146 Read article
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ML-Based Predictive Modeling of Mechanical Properties in 3D-Printed Polymer Composites for IoT Applications
Abstract: This study aims to develop an interpretable and high-accuracy machine learning framework for predicting the mechanical properties of 3D-printed fiber-reinforced polymer composites, with a focus on structure–property correlations relevant to polymer processing and functional performance. Composite specimens based on PLA and ABS matrices were fabricated using FDM with varying weight fractions (5–20 wt%) of carbon and glass fibers. Standardized mechanical testing (ASTM D638, D256, D790) was performed to evaluate tensile …
Published in Journal of Polymer & Composites · Vol. 13, Issue 4, 2025 · pp. 61–78 Read article
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Optimization of Direct Ink Writing Process Parameters for Liquid Silicone Rubber/TiO2 Composite Ink
Abstract: The purpose of this research is to develop and optimize the Liquid Silicone Rubber (LSR)/Titanium Dioxide (TiO₂) composite inks in Direct Ink Writing (DIW)-based 3D printing systems. The primary research objective was to use enhancement of mechanical, rheological, and dielectric characteristics of LSR using TiO₂ reinforcement but still retain extrusion stability and dimensional consistency. TiO₂ content (0, 5, 10, and 15 wt%) and catalyst and glycerol ratios were regulated and …
Published in Journal of Polymer & Composites · Vol. 13, Issue 6, 2025 · pp. 240–259 Read article
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Effect of concentration of Halloysite nanotubes on the Mechanical, Thermal and electrical properties of NBR/PP Elastomer nanocomposites
Abstract: Preparation of nanocomposites from immiscible polymer blends system has been investigated in this work. Natural clay named halloysite nanotubes are incorporated in the immiscible blend system using melt mixing process to prepare halloysite based nanocomposites comprising of PP/NBR blend system. FTIR studies have been carried out to establish the structure properties relationship. Nanocomposites are characterized by SEM for morphological studies. The thermal stability of nanocomposites has been evaluated by TGA …
Published in Journal of Polymer & Composites · Vol. 8, Issue 2, 2020 · pp. 62–67 Read article
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Machine Learning-Based Structure–Property Quantification of Advanced Polymer Composites
Abstract: Advanced polymer composites are widely used in high-performance engineering due to their superior mechanical and multifunctional properties. Accurate structure–property quantification is essential for efficient material design and reducing experimental costs. Existing Machine Learning (ML) approaches often exhibit limited predictive generalization due to inadequate feature discrimination and suboptimal hyperparameter tuning. To address these limitations, the proposed method enhances the ability to capture the complex nonlinear interactions among composite structural descriptors. The …
Published in Journal of Polymer & Composites · Vol. 14, Issue 4, 2026 Read article
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Comparison Analysis of Transformer Boosting and Induced Degeneration Topology Design of LNA for Millimeter Wave Frequency Range Using Polymeric Substrates
Abstract: In this study, a comparison between transformer boosting and source degeneration LNA topologies is conducted using two polymeric substrates—Polyimide (PI) and Liquid Crystal Polymer (LCP)—for millimeter-wave (mmWave) applications. With growing interest in flexible and high-frequency electronics, polymeric materials offer unique advantages such as low dielectric constants, mechanical flexibility, and thermal stability. The analysis explores gain, return loss, and noise figure performance while evaluating the influence of dielectric properties on the …
Published in International Journal of Electrical and Communication Engineering Technology · Vol. 3, Issue 2, 2025 · pp. 1–24 Read article