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19 articles for “Structure–Property Quantification”
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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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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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Introduction to Biological Networks and their Contributions to Systems Biology
Abstract: Biological networks provide a conceptual framework to represent and analyze the intricate interconnections among the numerous components that make up living systems. This review paper elucidates the foundational principles of networks and their diverse applications in systems biology, highlighting their crucial role in understanding the inherent complexity of biological processes. Utilizing graph theory, these networks represent entities like genes, proteins, and metabolites as nodes, with their interactions depicted as edges. …
Published in International Journal of Bioinformatics and Computational Biology · Vol. 2, Issue 1, 2024 · pp. 53–70 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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Automated Blood Cell Counting and Disease Identification Using Image Processing: Implications for Polymer Composite- Based Biomedical Diagnostic Devices
Abstract: Accurate quantification of blood cells is central to clinical decision-making and to the performance of emerging polymer composite–based diagnostic platforms. This work presents a cost-effective, image-processing pipeline for automated counting of red blood cells (including overlapping cells), white blood cells, and platelets from Leishman-stained peripheral blood smears, and articulates its relevance to polymer composite microfluidic and biosensor devices. Implemented in Python with OpenCV, the workflow performs grayscale conversion, median/Gaussian denoising, …
Published in Journal of Polymer & Composites · Vol. 13, Issue 6, 2025 · pp. 262–270 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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Assessment of Fire Resistance of Offshore Structures under Special Environmental Loads: Emphasizing Structural Integrity and Safety Measures for Extreme Conditions
Abstract: Offshore structures are exposed to a myriad of environmental challenges, including high temperatures and fire hazards, necessitating robust fire resistance measures to ensure structural integrity and the safety of personnel and facilities. This study aims to evaluate the fire resistance of offshore structures under special environmental loads, with a focus on the structural integrity and safety measures in place to withstand extreme conditions. The research methodology includes a comprehensive review …
Published in Journal of Offshore Structure and Technology · Vol. 11, Issue 1, 2024 · pp. 1–9 Read article
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Spectral Intuitionistic Fuzzy Hypergraph Operators and Dominance Kernels for Resilient Discrete Network Design
Abstract: A new discrete-mathematical framework is developed for resilient network design on intuitionistic fuzzy hypergraphs, where uncertainty is explicitly represented through membership, non-membership, and hesitation degrees associated with both vertices and hyperedges. These three components are systematically integrated into an effective incidence operator that captures the underlying uncertain relationships within complex hypergraph structures. Based on this operator, both un-normalised and normalized Laplacian matrices are formulated to characterize the spectral properties and …
Published in Recent Trends in Mathematics · Vol. 3, Issue 2, 2026 · pp. 41–48 Read article
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Structure–Property-Guided Polymer–Metal Hybrid Design of a Wall Plastering Spray Assembly
Abstract: Wall plastering spray equipment requires a combination of low mass, dimensional stability, abrasion resistance, chemical compatibility with cementitious mortar, and comfortable operator interaction. The original assembly was primarily developed as a metallic mechanical system; however, a polymer-focused material architecture can reduce non-load-bearing mass while retaining a safe metallic pressure path. This study, therefore, presents a structure–property-guided polymer–metal hybrid design in which the pressure housing and nozzle insert remain metallic, whereas …
Published in Journal of Polymer & Composites · Vol. 14, Issue 5, 2026 · pp. 197–211 Read article
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Integrated DIPlib and OpenCV Framework for Precise Geometric Characterisation of Woven Fibre-Reinforced Polymer Composites
Abstract: The mechanical properties of woven fibre-reinforced polymer (FRP) composites stem entirely from the geometrical regularity inherent in their reinforcement structure. Changes in the size of the unit cell, fibre tow separation, weave angle, and fibre tow spacing will have an immediate effect on the stiffness and shear modulus of the material. In this paper, a combined machine vision system that incorporates both the OpenCV and DIPlib libraries is proposed for …
Published in Journal of Polymer & Composites · Vol. 14, Issue 3, 2026 · pp. 158–171 Read article
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Comparative Analysis of the Structural Integrity and Dimensional Stability of Additively Manufactured Biopolymers vs. Thermoformed PETG: A 1-Year Retrospective Study on Polymer Performance in Orthodontic Applications
Abstract: Objective: This study aimed to evaluate the long-term dimensional accuracy and structural performance of direct 3D-printed biopolymers compared to conventional vacuum-formed Polyethylene Terephthalate Glycol (PETG) composites. The investigation focused on how different polymer processing methods (additive manufacturing vs. thermoforming) influence material thinning and resistance to occlusal stress. Methods: A retrospective analysis was conducted on 60 cases (n = 60) of post-orthodontic maintenance. The sample was divided into two cohorts: Group …
Published in Journal of Polymer & Composites · Vol. 14, Issue 3, 2026 · pp. 140–146 Read article
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Synthesis of Lawsonia Inermis (Henna) Carbon Supported AgO Nanocomposite, Characterizations and Photocatalytic Activity Studies
Abstract: Synthesis of Carbon supported AgO nanocomposite is reported for first time. Henna carbon was successfully synthesized from henna leaf. Bare AgO and C-AgO nanocomposites are effectively made using precipitation method. The synthesised composites structural, morphological, and optical properties are assessed using FT-IR, XRD, FE-SEM, UV-DRS, and PL techniques. FT-IR analysis proved that specific functional groups of synthesized materials. The uniform distribution of the composites is revealed in the FE-SEM. XRD …
Published in Journal of Polymer & Composites · Vol. 13, Issue 1, 2025 · pp. 749–760 Read article
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Experimental Investigations of EDM Parameters on Machining Square Blind Holes in Maraging Steels
Abstract: Square blind holes have certain qualities that make them useful in fields where accuracy and efficiency are crucial, like aerospace, automotive, molding, and general manufacturing industries where structural integration is required in precise assembly. It is challenging to machine square blind holes with traditional machining due to geometrical complexity as precision is required for sharp corners which is difficult to get at the corners due to tool wear. Electrical discharge …
Published in Journal of Polymer & Composites · Vol. 13, Issue 3, 2025 · pp. 390–397 Read article
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Selection of Best Natural Fibre for Retrofitting of Structure by Using AHP
Abstract: Ordinary concrete has certain characteristics such as; it is relatively strong in compression but weak in tension and tends to be brittle. To neutralize this weakness of concrete some natural reinforcement is provided to concrete and subsequent concrete is called fibre reinforced concrete. There are many types of natural fibres which are used in concrete as a reinforced material to increase the properties of concrete such as; Sisal, Coir, Hemp, …
Published in Journal of Structural Engineering and Management · Vol. 2, Issue 2, 2015 · pp. 13–19 Read article
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Tensile and Flexural Strength Quantification of Basalt-Reinforced Epoxy Composites Fabricated via Vacuum-Assisted Resin Transfer Molding at Varied Fiber Volume Fractions Description
Abstract: Fiber-reinforced polymer composites have been identified to possess excellent properties that render them very suitable in the aerospace, automotive, marine and renewable energy sectors. However, for the industrially scalable vacuum-assisted resin transfer molding (VARTM) process, optimization of mechanical properties of basalt epoxy composites must be achieved systematically, which means that the effect of the fiber volume fraction (VF) on the mechanical properties of the composite needs to be quantified for …
Published in Journal of Polymer & Composites · Vol. 14, Issue 4, 2026 · pp. 43–57 Read article
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Comprehensive study of Entanglement Entropy in Quantum Field Theory: Analysis of Conformal Field Theory to Massive Field Extensions and Holographic Entanglement
Abstract: This paper provides an in-depth analysis of entanglement entropy (EE) in quantum field theory (QFT), with a particular focus on its computation using the replica trick and its applications to both conformal and non-conformal systems. Beginning with an introduction to the basics of QFT, the study explains how entanglement entropy quantifies the quantum correlations between subsystems in a pure state, represented by the von Neumann entropy of the reduced density …
Published in Research & Reviews : Journal of Physics · Vol. 13, Issue 3, 2024 · pp. 33–58 Read article
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Synthesis, Characterization of New Imidazolidin-4-One Containing Azo Compound Derived from Acetylacetone as Antibacterial and Antioxidant Agents
Abstract: In the present study, new derivatives of imidazolidine-4-one was prepared. Which involved reactions to diazonium salt of o-methoxy aniline with acetylacetone in the presence of sodium hydroxide, and isolating the azo compound as a brown precipitate. The azo diketone reacts efficiently with aromatic amine derivatives to produce Schiff bases as a light yellow and dark brown precipitates, and from this Schiff bases three derivatives of imidazolidine-4-one was prepared by reacting …
Published in Journal of Modern Chemistry & Chemical Technology · Vol. 17, Issue 1, 2026 · pp. 94–114 Read article
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Tailoring the Compressive Behavior of Tetrachiral Auxetic Structures Through FDM Process-Parameters
Abstract: This research evaluates how fused deposition modeling (FDM) fabrication process parameters affect the compressive behavior of tetrachiral auxetic structures created from Polylactic Acid (PLA). Auxetic materials have several useful properties, including reversible deformation and high-energy absorbing capabilities, which are beneficial to creating ultra-lightweight structural, protective, and shock-resistance designs. Among the available auxetic topologies, the tetrachiral configuration is particularly attractive for engineering use, because its rotation-dominated node–ligament deformation gives a negative …
Published in Journal of Polymer & Composites · Vol. 14, Issue 5, 2026 · pp. 58–70 Read article
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Digital Twin Assisted Intelligent Prediction of Polymer Composite Degradation Under Environmental Exposure
Abstract: Polymer matrix composites (PMCs) deployed in aerospace, marine, automotive, and renewable-energy structures are continuously subjected to coupled environmental stressors — ultraviolet (UV) radiation, moisture ingress, thermal cycling, and mechanical loading — that progressively degrade their mechanical performance. Conventional accelerated ageing tests and empirical lifetime models are time-consuming, destructive, and poorly suited to in-service, asset-specific degradation forecasting. This paper proposes a Digital Twin (DT) assisted intelligent prediction framework that fuses a …
Published in Journal of Polymer & Composites · Vol. 14, Issue 4, 2026 Read article