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58 articles for “structure–property relationship”
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Graph Theoretic Analysis of Cyclodextrin Polymers
Abstract: Topological indicators in chemical graph theory are essential tools in cheminformatics, providing valuable insights into molecular structure and properties to make more accurate predictions about the behavior and efficacy of novel compounds in drug design. The macro molecules are correlated with certain derivatives. The derivatives are growing structures which depends on the cyclic structures. The Cyclodextrin is one of the cyclic structures which depends on the carbon atoms. The polymer …
Published in Journal of Polymer & Composites · Vol. 14, Issue 1, 2026 · pp. 997–1006 Read article
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Heterocyclic Substituted Flavones: Bridging Natural Products and Medicinal Chemistry
Abstract: Heterocyclic substituted flavones represent a unique and promising class of flavonoid derivatives, gaining significant attention in recent years due to their diverse and enhanced biological activities. These compounds are characterized by the incorporation of heterocyclic moieties such as quinoline, pyridine, thiazole, imidazole, oxazole, and pyrazole into the flavone structure, which significantly alters and often enhances their bioactive properties. This structural modification has made heterocyclic flavones particularly appealing as candidates for …
Published in International Journal of Tropical Medicines · Vol. 2, Issue 1, 2025 · pp. 23–30 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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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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Generative Design of Bioactive Orthopedic Composites for Fracture Repair Using an Integrated Conditional GAN–Transformer Framework: A Multi-Objective Approach
Abstract: Orthopedic composite implants for fracture repair must simultaneously satisfy conflicting mechanical and biological demands: high fracture toughness, sufficient compressive stiffness, and bioactive surface chemistry enabling osteoblast adhesion and mineralization. Existing design approaches rely on trial-and-error experimentation, yielding sub-optimal trade-offs between these objectives. This paper presents an integrated conditional Generative Adversarial Network–Transformer (cGAN-T) framework for fully computational, multi-objective generative design of hydroxyapatite (HA)-reinforced polymer composite microstructures targeting Orthopedic fracture repair. A …
Published in Journal of Polymer & Composites · Vol. 14, Issue 4, 2026 · pp. 21–35 Read article
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Investigation and Optimization of Resistance Spot Welding Parameters for Stainless Steel
Abstract: The present work examines the significant impact of resistance spot welding (RSW) process parameters on the properties and efficacy of connections created in sheets of 316L stainless steel. This study examines the intricate relationship between welding parameters, investigating their influence on the microstructure, mechanical characteristics, and overall efficacy of welded connections. By employing a methodical experimental methodology, this study thoroughly investigates the impact of different factors in resistance spot welding …
Published in Journal of Thermal Engineering and Applications · Vol. 12, Issue 3, 2025 · pp. 15–21 Read article
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Polyurethane: Chemistry, Production, Applications, and Future Prospects—An Overview
Abstract: Polyurethane (PU), a class of versatile polymers, has emerged as one of the most significant materials in modern industry owing to its remarkable mechanical strength, elasticity, durability, and resistance to abrasion, chemicals, and environmental degradation. Its wide range of tunable properties has made PU indispensable across multiple sectors, including fashion, automotive, manufacturing, biomedical, coatings, and construction. This review emphasizes the diverse applications of polyurethane and explores how its unique chemistry …
Published in Journal of Thin Films, Coating Science Technology & Application · Vol. 12, Issue 3, 2025 · pp. 17–25 Read article
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Enhancement in Biomedical Polymer Nanocomposites: Biocompatibility and Mechanical Property Predictions using Machine Learning
Abstract: A machine learning (ML)-based framework is developed and validated through experimental analysis and comparative modeling to enhance system dependability and improve prediction performance. The proposed framework includes key stages such as data preprocessing, feature evaluation, model training, and performance benchmarking to determine the most effective prediction technique. Several machine learning models were evaluated, including Ensemble models, Artificial Neural Networks (ANN), Decision Tree (DT), Random Forest (RF), Support Vector Machine (SVM), …
Published in Journal of Polymer & Composites · Vol. 14, Issue 3, 2026 · pp. 275–296 Read article
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Enhancing Surface Roughness of Polylactic Acid (PLA) 3D-Printed Parts Using CO₂ Laser Scanning: An Experimental Study on Parameter Optimization
Abstract: Fused deposition modeling (FDM) of polylactic acid (PLA) often suffers from poor surface finish due to the inherent layer-by-layer deposition process, limiting its use in high-precision applications. This study investigates CO₂ laser scanning as an efficient post-processing technique to reduce the surface roughness (Ra) of PLA parts while maintaining structural integrity. Specimens (100 × 80 × 5 mm) were fabricated with varying infill densities (35%, 70%, and 100%) to assess …
Published in Journal of Polymer & Composites · Vol. 13, Issue 6, 2025 · pp. 503–511 Read article
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House Price Estimation Using Linear Regression: A Machine Learning Perspective
Abstract: House price prediction plays a crucial role in the real estate industry, helping buyers, sellers, and investors make well-informed decisions. Accurate estimation of property values enables stakeholders to assess market trends, plan investments, and minimize financial risks. This study focuses on the application of linear regression, a fundamental and widely used machine learning algorithm, to predict house prices based on multiple influencing factors. These factors include location, property size, number …
Published in Research & Reviews : Journal of Statistics · Vol. 15, Issue 1, 2026 Read article
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Investigation of Bio-Physical Interaction and Electrophoretic Properties of Fe3O4/DNA Nanocomposite and Colloids for Biomedical Application
Abstract: In recent years, research on magnetic nanoparticles has gained significant attention. The core concept behind their physics lies in their interaction with biomolecules such as hemoglobin, DNA, and RNA. This study examines the fundamental forces involved in these interactions, including van der Waals attractions, electrostatic repulsion, thermal effects, and magnetic coupling between nanoparticles and biological molecules. To describe these interactions quantitatively, parameters such as zeta potential, magnetic moment density, and …
Published in Research & Reviews : Journal of Physics · Vol. 14, Issue 3, 2025 · pp. 20–32 Read article
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The Evolution and Impact of Numbers: From Ancient Tallies to Quantum Computing: Review Article on Numbers
Abstract: Numbers are among the most fundamental constructs in human civilization, serving as the backbone of mathematics, science, technology, and virtually every aspect of daily life. They represent not only quantities and measures but also relationships, structures, and patterns that underpin the fabric of human understanding. From the earliest tallies etched on bones by prehistoric humans to the sophisticated numerical systems embedded in today’s artificial intelligence and quantum computing, the evolution …
Published in Research & Reviews: Discrete Mathematical Structures · Vol. 12, Issue 3, 2025 · pp. 15–19 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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Efficient Clustering Techniques for Data Stream Mining
Abstract: Data mining mainly works on a massive database for storing heavy amount of data. It is generally essential for extracting the meaning insights from the massive, continuously growing database. The traditional method often struggles with sheer volume and the dynamic nature of the modern data. Data stream mining allows for the real-time analysis, means insights are generated as the data arrives, and not after the long batch process. This continuous …
Published in Recent Trends in Parallel Computing · Vol. 12, Issue 2, 2025 · pp. 26–32 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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Electroactive Graphene–Polymer Nanocomposites for Self-Sustaining and Multifunctional Flexible Devices
Abstract: Graphene–reinforced polymer–composites were developed and systematically investigated to explore their multifunctionality in flexible electronic applications. The study specifically aims to correlate graphene-induced structure–property–function relationships with electroactive performance and self-sustaining behaviour in flexible devices. The hybridization of electroactive polymers—polyaniline (PANI), poly(3,4-ethylenedioxythiophene): polystyrene sulphonate (PEDOT:PSS), and polyvinylidene fluoride (PVDF)—with graphene nanoplatelets enabled simultaneous enhancement of electroactivity, energy-harvesting, and sensing functionalities. Morphological studies confirmed uniform graphene dispersion at 5 wt.% loading, forming continuous …
Published in Journal of Polymer & Composites · Vol. 13, Issue 6, 2025 · pp. 260–271 Read article
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Role of Ginger (Zingiber officinale Roscoe) in Sustainable Health
Abstract: Attaining sustainable health involves a comprehensive blend of multiple factors, including structural, physiological, metabolic, and psychological aspects, alongside the cultivation of self-awareness and a sense of fulfillment. The World Health Organization (WHO) underscores in its 2030 Agenda for Sustainable Development that lifestyle-related illnesses, especially non-communicable diseases (NCDs), present considerable hurdles to sustainable progress, stressing the importance of mitigating their risk factors. Nutrition is acknowledged as a cornerstone of health preservation, …
Published in Research and Reviews : A Journal of Life Sciences · Vol. 14, Issue 3, 2024 · pp. 72–76 Read article
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Exploring Antimalarial Activity of Chalcone Derivatives through QSAR
Abstract: Background: The core structure of chalcones contains a reactive α,β-unsaturated system within the aromatic rings, which plays a key role in mediating various biological effects. These effects include enzyme inhibition, anticancer activity, anti-inflammatory properties, as well as antibacterial, antifungal, antimalarial, antiprotozoal, and anti-filarial actions.Modifying the structure by introducing substituent groups to the aromatic ring can enhance potency, reduce toxicity, and expand their range of pharmacological actions. Methods: A total of …
Published in International Journal of Bioinformatics and Computational Biology · Vol. 3, Issue 2, 2025 · pp. 1–6 Read article