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194 articles for “Property Prediction”
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Integrative Machine Learning Approaches for Predicting the Rheological Behaviour of Soft Magnetorheological Elastomers
Abstract: Magnetorheological Elastomers (MREs) are advanced composite materials known for their ability to alter mechanical properties under external magnetic fields, making them highly valuable in adaptive damping systems, vibration control, and smart devices. The accurate prediction of rheological behavior in soft MREs remains a significant challenge due to the complex interplay between material composition and magnetic fields. To address this challenge, this study employs a multi-pronged approach that integrates traditional material …
Published in Journal of Polymer & Composites · Vol. 13, Issue 1, 2025 · pp. 1083–1096 Read article
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Structure Property Correlation of Polymer Dielectrics Using Electrical Response Data
Abstract: Polymer dielectrics are foundational to insulation, capacitors, embedded passives, and flexible electronics, where performance is governed by the frequency-dependent electrical response rather than a single dielectric constant. This study presents a spectroscopy-aware structure–property correlation framework that transforms dielectric response data into physically interpretable spectral fingerprints and learns mappings from polymer descriptors to these fingerprints for prediction and interpretation. Broadband spectra are standardized on a log-frequency grid and parameterized using relaxation-informed …
Published in Journal of Polymer & Composites · Vol. 14, Issue 3, 2026 · pp. 315–324 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 3, 2026 Read article
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Detailed review on adsorption refrigeration system for different adsorbent/adsorbate working pair green composite materials – An environmental aspect
Abstract: Adsorption refrigeration is one of the greatest encouraging system for the refrigeration applications due to use of low grade energy. Present study deals with detailed review of adsorption refrigeration system. This article mainly concern with adsorption refrigeration arrangement by the utilization of most appropriate operational pairs namely activated carbon/methanol, silica gel/water and zeolite/water. Detail review carried out to predict thermal analysis and performance of the system. Mechanical properties of the …
Published in Journal of Polymer & Composites · Vol. 12, Issue 4, 2024 · pp. 1–9 Read article
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AI-Driven Innovation in Biomaterials: Predictive Modeling and Design for the Future
Abstract: The integration of artificial intelligence (AI) is revolutionizing the field of biomaterials, paving the way for innovative approaches in their development and production. This paper examines the connection between AI and biomaterials, emphasizing the substantial impact of predictive modeling on the evolution of the field. By examining recent research and cutting-edge uses, the document shows how AI-powered predictive modeling has revolutionized biomaterial design, marking a period of unparalleled precision and …
Published in Trends in Machine design · Vol. 11, Issue 3, 2024 · pp. 25–35 Read article
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Screening Phytocompounds of Tinospora cordifolia to Find Potential Drug Targets for Cystic Fibrosis
Abstract: This study aimed to evaluate the therapeutic potential of phytocompounds derived from Tinospora cordifolia in treating cystic fibrosis (CF), a genetic disorder caused by mutations in the CFTR gene that lead to severe respiratory and digestive complications. Phytocompounds were retrieved from the IMPPAT database and subjected to molecular docking simulations using PyRx to assess their binding affinity to the CFTR protein. The top-scoring compounds – sterol, magnoflorine, tembetarine, kaempferol, and …
Published in International Journal of Genetic Modifications and Recombinations · Vol. 3, Issue 1, 2025 · pp. 16–24 Read article
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AI-Accelerated Development of Gradient Polymer Nanocomposite Thin Films
Abstract: Gradient polymer nanocomposite thin films are an active field of materials research due to the fact that it enables scientists to de-facto regulate the optical, electrical, and mechanical properties of a film by merely altering its composition on a layer-by-layer basis. This type of control opens the gate to the improved flexible electronics, long lasting protective coats, and the new smart gadgets. The problem is, though, that it is a …
Published in Journal of Polymer & Composites · Vol. 14, Issue 2, 2026 · pp. 456–469 Read article
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Using Multitarget Molecular Docking to Examine the Antiviral Potential of Clerodendrum Phlomidis against Measles
Abstract: Objective: Measles, a viral disease caused by a member of the Paramyxoviridae virus family, is highly contagious and characterized by a respiratory illness and a maculopapular rash on the skin. Children are the main victims of the illness. In the context of drug development, this study investigates the efficacy of phytocompounds derived from Clerodendrum phlomidis against the target protein of the measles virus. Methods: The 7SKS protein was retrieved from …
Published in International Journal of Molecular Biotechnological Research · Vol. 1, Issue 2, 2023 · pp. 32–42 Read article
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Computational Screening of Vitex negundo Compounds for Potential Arthritis Therapies in India
Abstract: Objective: Arthritis is a pervasive medical condition that manifests as inflammation and discomfort within the joints. As of September 2021, arthritis has affected an estimated 180 million people in India, making it a substantial public health concern with a considerable impact on individuals' quality of life and healthcare systems. Therefore, using molecular docking, drug-likeness prediction, and ADME analysis, an effort was made to identify natural compounds from Vitex negundo, which …
Published in Research and Reviews : Journal of Computational Biology · Vol. 13, Issue 1, 2024 · pp. 01–18 Read article
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In-silico Approach of Few Selected Phytoconstituents on Newer Cancer Targets
Abstract: Background: Cancer’s high death rates are mainly due to, drug resistance and unmet medical demands. It necessitates novel anticancer medications. AI tools aid in efficient and faster drug discovery by analyzing data, modeling processes and optimizing pipeline stages. Aim: The aim of this present study is to evaluate phytoconstituents against novel and newer cancer targets. Methodology: The ligands Daidzein, Resveratrol and Genistein were targeted against the Glutamate dehydrogenase (PDB ID …
Published in Research and Reviews: A Journal of Pharmaceutical Science · Vol. 15, Issue 3, 2024 · pp. 12–17 Read article
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Explainable Machine Learning for Process Parameter Optimization in Gradient 3D-Printed Polymer Composites
Abstract: The explainable machine learning-based structure may be employed to achieve a favorable process parameter of the graduate 3D-printed polymer composite structures to improve the mechanical and thermal properties without compromising the transparency of the decisions made during the fabrication process. Gradient composite specimens were made by systematically varied process parameters like nozzle temperature, raster orientation, deposition speed, gradient transition rate and fused filament fabrication. A predictive model of tensile strength …
Published in Journal of Polymer & Composites · Vol. 14, Issue 2, 2026 · pp. 847–866 Read article
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Review and Opportunities for Thermal examination approaches Used to Investigate the Thermal Properties of Composite Compounds
Abstract: The use of thermal examination approach to assess the thermal quality of energy materials in “China” is concisely described. They are often used to calculate thermal stability, compatibility, and thermophysical constants, as well as to study thermal breakdown kinetics, causes, and interactions. Furthermore, a few studies focused on creativity or advancement, such as analyzing the mechanisms of topochemical reactions, assessing condensed-phase reaction kinetics by tracking the change in functional groups …
Published in Journal of Polymer & Composites · Vol. 12, Issue 6, 2024 · pp. 96–106 Read article
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Comprehensive Review of the Fundamental and Functional Properties of Crystalline Materials
Abstract: Crystalline materials, characterized by their highly ordered atomic arrangements, serve as the backbone of modern engineering and technology. This review provides a detailed examination of their diverse properties, categorized into mechanical, thermal, electrical, and optical domains. We analyze fundamental mechanical parameters such as the elastic modulus, yield strength, and fracture toughness, alongside functional behaviors like fatigue and creep. The discussion extends to thermal transport and expansion, electrical conductivity and resistivity, …
Published in International Journal of Crystalline Materials · Vol. 3, Issue 1, 2026 · pp. 20–24 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
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Mechanical Performance Assessment of Hybrid FRP Laminates with Carbon Fiber Core Using Experimental and Numerical Approaches
Abstract: The high strength-to-weight ratio, corrosion resistance and design flexibility of Fiber-reinforced polymer (FRP) composites have attracted considerable attention in aerospace, automotive and structural applications. This work presents an experimental and finite element study on the tensile and flexural behavior of epoxy-based hybrid FRP laminates. Five laminate configurations were manufactured, including a unidirectional carbon fiber laminate and four hybrid laminates, Kevlar–Carbon–Kevlar (K/C/K), Glass–Carbon–Glass (G/C/G), Kevlar–Carbon–Glass (K/C/G), and Glass–Carbon–Kevlar (G/C/K). For all …
Published in Journal of Polymer & Composites · Vol. 14, Issue 4, 2026 Read article
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Advanced Computational Models for Predicting Molecular Interactions
Abstract: Understanding molecular interactions is essential for a number of disciplines, including biochemistry, materials science, and medication development. Traditional experimental methods, while accurate, are often time-consuming and expensive. Advanced computational models have emerged as powerful tools to predict molecular interactions efficiently. In order to predict the behavior and interactions of molecules at the atomic and subatomic levels, this paper reviews the most recent developments in computational techniques, such as machine learning …
Published in International Journal of Advance in Molecular Engineering · Vol. 2, Issue 1, 2024 · pp. 8–13 Read article
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Iron Oxide/Chitosan Nanocomposite: Properties and Design for AI Enhanced Immunotherapy and Regenerative Medicine
Abstract: Biopolymers are valuable complex materials. They attract attentions of many scientists, engineers, and medical professionals’ due to their distinguished properties for various applications. In this research, emphasis is given to Fe3O4/Chitosan nanocomposite which has desirable biophysical properties compared to pure Chitosan nanoparticles. Following the green synthesis procedures and characterization methods including thermo gravimetric analysis, AI assisted biomedical application of; Fe3O4/Chitosan nanocomposite is presented. The effect of alkali typically, KOH, in …
Published in International Journal of Cheminformatics · Vol. 3, Issue 2, 2025 · pp. 22–32 Read article
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Regression Analysis of Topological Indices and Physicochemical Properties of Polymer-Based Anticancer Drugs
Abstract: The research analyzed the quantitative correlation between topological indices and the physicochemical properties of selected anticancer compounds using regression analysis. Various topological descriptors—such as the First Zagreb Index, Second Zagreb Index, and Forgotten Index were calculated and regressed against key molecular features, including polar surface area, melting point, and molar refractivity. The regression analysis revealed linear correlations between these topological indices and the properties of anticancer drugs, with particularly strong …
Published in Journal of Polymer & Composites · Vol. 14, Issue 1, 2026 · pp. 255–267 Read article
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In Silico Exploration of Podophyllum Hexandrum-Derived Phytocompounds as Potential Therapeutics Against Small Cell Lung Cancer (SCLC): A Molecular Docking Approach
Abstract: Small Cell Lung Cancer (SCLC) is a fast-growing and aggressive type of lung cancer that spreads quickly strongly associated with smoking. It is characterized by symptoms, such as persistent cough, breathing difficulties, or hoarseness, though it can sometimes be asymptomatic which makes early detection challenging. The tumor suppressor gene TP53 is critical in regulating the cell cycle and preventing uncontrolled cell division. Mutations in TP53 result in the loss of …
Published in International Journal of Molecular Biotechnological Research · Vol. 3, Issue 1, 2025 · pp. 1–11 Read article
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A Review of Recent Advancements in Machine Learning and Deep Learning Approaches for Pet Diseases Prediction
Abstract: This systematic study assesses recent developments in Machine Learning (ML) and Deep Learning (DL) approaches to predict pet diseases. With the increasing role of Artificial Intelligence (AI) in pet healthcare, this study identifies recent research trends, limitations, and future directions. A comprehensive search was done using the Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) guidelines in selecting 20 relevant studies from over 300 articles published between 2020 and …
Published in Research and Reviews : Journal of Veterinary Science and Technology · Vol. 14, Issue 3, 2025 · pp. 1–6 Read article