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238 articles for “Structure–property modeling”
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Structure-Property Modeling and Engineering Optimization of Biodegradable Starch-Cellulose Biofoams for Sustainable Packaging
Abstract: Since the packaging industry is an engineered product with complex composites that involve a close relationship between composition, processing, and performance, optimization of formulation, cellular morphology, and engineering performance of biodegradable starch-based biofoams presents a considerable challenge. This study proposes a machine-learning-aided structure–property modeling framework to design and optimize starch-based biodegradable biofoams for sustainable packaging applications. A physics-informed synthetic dataset consisting of 10,000 formulations was created based on engineering relationships …
Published in Journal of Polymer & Composites · Vol. 14, Issue 5, 2026 Read article
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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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Advances in Polymer-Modified Concrete using XAI
Abstract: Industry 4.0 technologies are being quickly adopted by the construction sector, opening new avenues for enduring operational and environmental issues. This sector looks at how explainable AI can forecast air and enhance the quality of building materials. XAI, AI, ML, and big data drive a new paradigm in polymeric material development. The effective XAI and ML-assisted design creates innovative, high-performance polymeric materials. It covers building a database and representing structures, …
Published in Journal of Polymer & Composites · Vol. 13, Issue 5, 2025 · pp. 133–144 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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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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Influence of Infill Density on Structural Performance of FDM-Processed PET-G Polymer: Experimental Validation through Quadcopter Flight Testing
Abstract: Polyethylene terephthalate glycol-modified (PET-G) is an amorphous thermoplastic copolymer increasingly adopted in structural applications through fused deposition modeling (FDM). However, the correlation between FDM processing parameters, especially infill density, and mechanical performance of PET-G parts remains inadequately characterized under real-life loading conditions. This study investigates how infill density (10% and 30%, grid pattern) influences the structural integrity of FDM-processed PET-G components, validated experimentally through quadcopter airframe fabrication and flight testing. …
Published in Journal of Polymer & Composites · Vol. 14, Issue 3, 2026 · pp. 644–656 Read article
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Weighted Latent Dirichlet Allocation, an Optimized and Generalized Probabilistic Topic Model
Abstract: In this study, we have introduced a new distribution named as Mixture Weighted Dirichlet Distribution (MWDD) which acts as generalization to other distributions viz. Dirichlet Distribution, Length or Size-Biased Dirichlet, Area Biased and Volume Biased Dirichlet distributions. Aim of this research is to introduce and implement MWDD for Probabilistic Topic Modeling of Corpus of textual data as an optimized as well as generalized probabilistic topic model. Various statistical and structural …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 5, Issue 1, 2018 · pp. 18–31 Read article
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Aerodynamics: Wind Load on Bridge and Construction
Abstract: This article is description about wind load correspondence for bridge constructions. Calculation of high pier has conclusive scheme around transverse direction of wind load for long span girder bridge. Ethic has scoped by code of pursue for design of highway bridge and culvert and load code for design of as build structure. Assessment of expected environmental loads is basic in design of engineering structures that influences chain of load carrying …
Published in Journal of Aerospace Engineering & Technology · Vol. 11, Issue 2, 2021 · pp. 47–54 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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Affect of Finite Element Modelling on Static Behavior of Underwater Shell
Abstract: The objective of the present study is to compare and contrast different numerical models based on their mesh quality and material properties in predicting the response of an underwater shell under an external pressure of 1 MPa. Two different mesh qualities with the same element size are developed for solid geometries without and with slicing the solids at geometric discontinuities to enhance the element quality. From the static response of …
Published in Journal of Polymer & Composites · Vol. 13, Issue 2, 2025 · pp. 154–163 Read article
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An Analysis on Feature Selection Method using Real Coded Genetic Algorithm (RCGA)
Abstract: The work presented in this thesis mainly focuses on the solving protein structure prediction (PSP) problem from machine learning models. The prediction of distance-to-native of protein structure is carried out using regression machine learning models with six physicochemical properties. The objective is to predict the distance to the native like structure in the absence of its true native state and report how far a structure is from its true native. …
Published in Journal of Software Engineering Tools & Technology Trends · Vol. 5, Issue 1, 2018 · pp. 23–30 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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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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Property Estimation of Polymers: A Review
Abstract: AbstractPolymer production processes are facing the problems of optimization of production rate, increasing yield, waste minimization and environmental issues and product quality problems. These issues can be solved by designing efficient polymer manufacturing processes. Accurate properties of polymers are very important in designing efficient processes. Hundreds of property estimation methods are available for property estimation of polymers but the selection of the suitable property model is a challenging task. One …
Published in Journal of Polymer & Composites · Vol. 6, Issue 3, 2018 · pp. 14–24 Read article
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Crystal Engineering Strategies for Tailoring Mechanical Properties of Structural Materials
Abstract: Crystal engineering has emerged as a promising approach for designing materials with tailored mechanical properties, enabling advancements in various fields such as aerospace, automotive, and construction. This review examines the diverse strategies employed in crystal engineering to manipulate the mechanical behavior of structural materials. One key strategy involves controlling the crystal structure at the atomic level through techniques such as alloying, doping, and phase transformations. Alloying introduces foreign atoms into …
Published in International Journal of Crystalline Materials · Vol. 1, Issue 1, 2024 · pp. 01–06 Read article
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Complexities in the Structural Behaviour of Offshore Structural Members subjected to Dynamic Loading
Abstract: Offshore structural members in Maritime Structures are subjected to various kinds of loading starting from Dead Load of structures and Dynamic loads from wind, waves, currents and operational loads during berthing and mooring of ships and vessels. The stability analysis of the structural members also demands an insight into the elastic properties of the founding sea bed level. Due to requirement of transport of large volume of cargoes and related …
Published in Journal of Offshore Structure and Technology · Vol. 9, Issue 2, 2022 · pp. 1–5 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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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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Intelligent Biocomposites for Real-Time Health Monitoring Applications
Abstract: Intelligible biocomposites are emerging as an enhanced material in the sense that they provide the capability to monitor health in real time because they have the inbuilt sensing and adjusting features. In this paper, the concepts of the intelligent biocomposites that have the ability to capture both mechanical and biochemical cues are to be presented as an informatics of designing, fabricating, and modeling. Multiphysics is used to couple mechanical deformation …
Published in Journal of Polymer & Composites · Vol. 14, Issue 4, 2026 Read article
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Impact of Shape, Size and Crystal Structure on Vacancy Related Properties of Gold Nanoparticles
Abstract: It is necessary to consider defects to explain the electron movement, thermal transport and mechanical properties of materials. In the present study, a simple quantitative model for cohesive energy of nanoparticles is extended to determine the size, shape and crystal structure effect on vacancy formation energy, vacancy entropy, and vibrational frequency in free surface Au nanoparticles. Vacancy entropy variation with size has been studied for spherical, regular octahedral, regular hexahedral …
Published in Journal of Polymer & Composites · Vol. 13, Issue 1, 2025 · pp. 223–229 Read article