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70 articles for “structure-property relationship”
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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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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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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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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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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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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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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
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Evaluation of Building Foundations: A Structural Engineering Perspective
Abstract: This study focuses on the comprehensive assessment and design of building foundations, emphasizing the critical relationship between structural loads and soil properties. The depth of the foundation is determined by analyzing the load exerted on the column and the soil's bearing capacity, both of which play a pivotal role in ensuring stability. Similarly, the foundation base size is calculated based on these parameters to ensure it effectively transfers the load …
Published in Journal of Structural Engineering and Management · Vol. 12, Issue 1, 2025 · pp. 6–18 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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Development of Polymersomes as Macromolecular Platforms for Nanomedicine
Abstract: The conventional method of drug delivery is plagued with instability, low targeting and low bioavailability. A solution to these shortcomings is the use of polymersomes, artificial vesicles that are produced through self-assembly of amphiphilic block copolymer, and they are suggested as universal nanoscale carriers. They have stiff, tunable membranes (thickness = 2–50 nm) due to accurate control of polymer chemistry, chain length, and hydrophilic mass fraction (f), which allows predictability …
Published in Journal of Polymer & Composites · Vol. 14, Issue 5, 2026 · pp. 71–89 Read article
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Investigative Study of Relationship of Chemical Characteristics of Group V Elements and Electron Structure
Abstract: Understanding the chemical properties of Group V elements through their electron configurations deepens our comprehension of periodic trends. Transitioning from nitrogen to bismuth, we observe a shift from non-metals to metalloids and then to metals, a change driven by the progression of electron shell and orbital filling. This insight is crucial for forecasting and elucidating the varied chemical behaviors and uses of Group V elements, thereby aiding developments in chemistry …
Published in Journal of Materials & Metallurgical Engineering · Vol. 15, Issue 2, 2025 · pp. 39–45 Read article
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Enhance Thermal and Conductive Properties through Graph Neural Network-Based Machine Learning-Driven Advanced Polymer Material Design
Abstract: Advanced polymer materials are widely used in modern engineering and manufacturing because of their lightweight nature, flexibility, durability, and adaptability to different applications. However, designing polymer materials with enhanced thermal and electrical properties remains a challenging task. The performance of polymers is influenced by a complex combination of molecular structures, filler materials, processing parameters, and nanoscale interactions. Conventional optimization methods often require extensive experimental trials and computational resources, making it …
Published in Journal of Polymer & Composites · Vol. 14, Issue 4, 2026 · pp. 386–407 Read article
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Magnetic Metal–Polymer Composites with Ferromagnetic Particle Networks for EMI Shielding in Flexible Electronics
Abstract: The rapid expansion of flexible and wearable electronic systems has intensified the demand for lightweight, mechanically compliant materials capable of effective electromagnetic interference (EMI) shielding. In this study, magnetic metal–polymer composites with magnetically aligned ferromagnetic particle networks were developed and systematically investigated for EMI shielding in flexible electronics. Thermoplastic polyurethane (TPU) was employed as an elastomeric polymer matrix due to its excellent flexibility, dielectric characteristics, and compatibility with particulate fillers. …
Published in Journal of Polymer & Composites · Vol. 14, Issue 1, 2026 · pp. 25–39 Read article
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Exploration of Partial Order Structures in Menger Spaces Properties Characterizations and Applications
Abstract: Partial order structures play a crucial role in understanding the intricate relationships within mathematical spaces. In this paper, we delve into the realm of Menger spaces and investigate their properties through the lens of partial orders. Menger spaces, a generalization of metric spaces, possess unique characteristics that can be further elucidated by considering partial order structures. Through rigorous analysis, we explore various properties of partial order Menger spaces, including topological …
Published in Research & Reviews: Discrete Mathematical Structures · Vol. 11, Issue 3, 2024 · pp. 17–22 Read article
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Investigating Flexural Behavior in Cyclic Loading of Fly Ash-Based Green Concrete
Abstract: The construction industry is increasingly embracing sustainable materials, and geopolymer concrete (GPC) has emerged as a promising eco-friendly alternative to Ordinary Portland Cement (OPC). Derived from industrial by-products such as fly ash, GPC offers significant environmental advantages by reducing greenhouse gas emissions associated with conventional cement production. This study explores the monotonic and cyclic performance of fly ash-based GPC, with a focus on its mechanical and structural behavior. Key properties, …
Published in Journal of Structural Engineering and Management · Vol. 12, Issue 1, 2025 · pp. 1–5 Read article