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134 articles for “property prediction modeling”
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QSAR Modeling of a Novel Series of Methoxylated Chalcones as Antioxidant Agents Against Gram-Positive Bacteria Staphylococcus aureus
Abstract: Background: Chalcones are aromatic ketones belonging to the flavonoid family. They are plant-based compounds and are widely found in nature. For centuries, these bioactive molecules have been utilized in various traditional medicines for the treatment of several ailments. Chalcones have antibacterial, antiviral, antimalarial, antifungal, antioxidant, and antileishmanial properties. They are also used to treat inflammation and cancer. Chalcones act as angiogenesis inhibitors, an important factor in cancer progression and metastasis. …
Published in International Journal of Biochemistry and Biomolecule Research · Vol. 3, Issue 1, 2025 · pp. 28–34 Read article
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A Machine Learning Based Artificial Intelligence Model for Detecting Heart Illness
Abstract: This study centers around the improvement of an artificial intelligence- and computerized reasoning-based heart sickness determination framework. We exhibit how AI can help with foreseeing whether an individual will get cardiovascular infection. In this review, a Python-based application for medical care research is created since it is more reliable and helps track and lay out many kinds of well-being observing applications. We show information handling, which incorporates working with all …
Published in Journal of Computer Technology & Applications · Vol. 15, Issue 1, 2024 · pp. 50–58 Read article
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Influence of SlS Parameters on Strength and Fatigue Durability of Polyamide-12
Abstract: Selective Laser Sintering (SLS), a laser-based polymer powder bed fusion process, has gained prominence in the fabrication of high-performance thermoplastics such as Polyamide-12 (PA12). This paper provides an extensive review of how key SLS process parameters—such as laser power, scan speed, hatch spacing, and energy density—affect the mechanical properties of PA12 components, with a specific focus on tensile strength and fatigue resistance. Studies demonstrate that increasing energy input enhances particle …
Published in Journal of Polymer & Composites · Vol. 14, Issue 2, 2026 · pp. 178–191 Read article
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Mechanical Characterization and Machinability Optimization of Stir-Cast Al6061–SiC Metal Matrix Composites
Abstract: This study presents the fabrication, mechanical characterization, metallurgical analysis, and machinability optimization of Aluminum 6061 reinforced with Silicon Carbide (SiC) metal matrix composites (MMCs) at three weight fractions: 5%, 7.5%, and 10%. Composites were manufactured using the stir casting technique, followed by comprehensive mechanical testing (tensile, hardness, and impact), optical microscopy, and scanning electron microscopy (SEM). Machinability was assessed through turning experiments on a lathe using an L9 Taguchi orthogonal …
Published in Journal of Polymer & Composites · Vol. 14, Issue 3, 2026 Read article
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Viscoelastic Behavior and Wrinkle Formation in Cotton- Polyester Garments: A Data-Driven Approach for Textile Care
Abstract: This study investigates the wrinkle behavior of cotton-polyester blended fabrics by analyzing data from over 1,200 store-handled garments. Integrating concepts from polymer chemistry and computer vision, it aims to establish a smart textile care framework based on fiber-specific wrinkle characteristics. The research identifies how cotton’s hydrophilic and non-elastic structure results in increased wrinkling, while polyester’s thermoplastic and crystalline properties enhance wrinkle resistance. Elastomeric fibers like Lycra contribute to wrinkle recovery …
Published in Journal of Polymer & Composites · Vol. 13, Issue 4, 2025 · pp. 50–60 Read article
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Enhancement of Horizontal Jet Impingement Heat Transfer Analysis on Vertical Flat Plate
Abstract: This research investigates the heat transfer characteristics and heat flux distribution associated with parallel jet impingement on a vertical flat plate. A comprehensive computational fluid dynamics (CFD) analysis is carried out and systematically validated against available experimental data to ensure the accuracy and reliability of the numerical model. The jet length is maintained constant at 12 mm, while the jet-to-plate separation distance is varied at 6, 12, 18, and 24 …
Published in Journal of Experimental & Applied Mechanics · Vol. 17, Issue 1, 2026 · pp. 65–80 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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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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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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AI-Driven Inverse Design of Functionally Graded Bio-Nanocomposites for Sustainable High-Barrier Packaging
Abstract: Multilayer plastic packaging realizes high barrier performance through laminated heterogeneous structures, but the heterogeneous structure has severe end-of-life challenges caused by the interfacial incompatibility of materials and the poor recyclability. This study proposes the inverse design of functionally graded PLA-nanoclay composite films by reinforcement learning as a monolithic alternative to traditional multilayer systems. Twin-screw extrusion is designed as a continuous control Markov decision process, and proximal policy optimization (PPO) is …
Published in Journal of Polymer & Composites · Vol. 14, Issue 2, 2026 · pp. 1547–1564 Read article
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Review On BIM-Based (Revit+Robot Software) Comparative Wind Load Analysis of High-Rise RCC Buildings in Zone-III, IV and V
Abstract: Wind load is one of the most critical factors influencing the design and serviceability of high-rise reinforced concrete (RCC) buildings. As building height increases, wind-induced effects such as storey drift, lateral displacement, and structural stiffness become dominant design considerations. Numerous studies have been conducted using conventional and advanced techniques such as Finite Element Method (FEM), Computational Fluid Dynamics (CFD), and Building Information Modelling (BIM). However, limited research focuses on comparative …
Published in Journal of Structural Engineering and Management · Vol. 13, Issue 2, 2026 Read article
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Artificial Neural Network Modelling to Optimize Micro-Drilling Parameters of ECDM of Developed Novel Zn/(Ag+Fe)-MMC
Abstract: Several engineering fields have increased their use of metal matrix composites (MMCs) in the past few years. Due to the increase in composites, the demand for accurate machining has also become important. Specifically, pertaining to biomaterial applications, accuracy factor with desired surface finish is critical. While the near-net shape manufacturing process has advanced, MMCs frequently require post-mould machining to achieve surface quality, and dimensional tolerances. In the present study, a …
Published in Journal of Polymer & Composites · Vol. 11, Issue 1, 2023 · pp. 01–13 Read article
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AI Application in the Creation of Medications for COPD
Abstract: The crippling lung condition known as chronic obstructive pulmonary disease (COPD) is typified by a continuous restriction of airflow, which results in increased respiratory dysfunction and a reduced quality of life. The rising incidence of COPD worldwide emphasizes the pressing need for innovative pharmaceutical approaches to address the illness. Even though COPD care has advanced significantly, most current medications concentrate on symptom relief rather than disease change. This gap in …
Published in Research & Reviews: A Journal of Drug Design & Discovery · Vol. 12, Issue 2, 2025 · pp. 01–05 Read article
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Multi-Objective Optimization of Polymer-Based Functionally Graded Composites for Lightweight Structures
Abstract: Functionally graded composites (FGCs) improve lightweight structural performance by allowing material properties to change smoothly across a component. Polymer-based FGCs (P-FGCs), in particular, are gaining prominence in aerospace, automotive, and biomedical industries due to their excellent strength-to-weight ratio, tunability, and ease of processing. However, optimizing these materials for lightweight structural applications requires addressing conflicting design objectives, such as maximizing stiffness while minimizing weight or enhancing thermal resistance while maintaining manufacturability. …
Published in Journal of Polymer & Composites · Vol. 14, Issue 2, 2026 · pp. 961–973 Read article
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Artificial Neural Network Based Prediction of Impact Loads and Thickness in CFRP and GFRP Composite Laminates
Abstract: Recent technological advancements, particularly the integration of neural networks, have facilitated a predictive approach to complex engineering problems, especially those involving composite materials with directional properties. The scarcity of literature on predicting impact damage using experimental and ultrasonic flaw detection data motivated this study. Experimental assessment of impact damage on carbon fiber/epoxy (CFRP) and glass fiber/epoxy (GFRP) composites was conducted using low-velocity drop weight impact testing. Damage assessment employed an …
Published in International Journal of Fracture Mechanics and Damage Science · Vol. 2, Issue 1, 2024 · pp. 34–45 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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Process Optimization of Spot Welding for Galvanized Automotive Steel Sheets
Abstract: Resistance Spot Welding (RSW) is a pillar of the modern automotive industry with the usage of lightweight and high-strength products at the highest point of demand. The optimum weld quality of galvanized steel sheets which is a material of choice because of its additional corrosion protective property is however not achieved easily. This study is a well-developed data-based solution to designing the RSW process in the most efficient way, providing …
Published in Journal of Polymer & Composites · Vol. 14, Issue 2, 2026 · pp. 32–42 Read article
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The Effect of Dynamics and Mass Transfer Limitation on the Kinetic Growth Rate of Methane Gas Hydrates
Abstract: Hydrate management aims to prevent impediments to fluid flow in pipes caused by hydrate deposition. To achieve this goal effectively, a comprehensive understanding of the thermodynamics and kinetics of hydrate formation is essential for predicting their equilibrium conditions, quantifying the amount of deposition, and estimating the associated risk. Hydrate growth studies are a relatively new field, and independent laboratory experiments have shown that hydrate growth is controlled by heat transfer, …
Published in Journal of Petroleum Engineering & Technology · Vol. 16, Issue 1, 2026 · pp. 76–84 Read article
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A Review on Enhancement of Building Energy Efficiency Through Insulation
Abstract: This review examines the heat insulation properties of bricks, which are vital for enhancing energy efficiency in buildings. Bricks serve as a fundamental component in construction, and their thermal performance significantly impacts overall energy consumption. Recent advancements in brick manufacturing have led to the development of materials with improved thermal insulation properties. The incorporation of specific additives into brick composition has demonstrated notable improvements in their ability to resist heat …
Published in Journal of Structural Engineering and Management · Vol. 12, Issue 1, 2025 · pp. 19–26 Read article
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Mathematical Modelling of Semiconductor Device Physics: An Analytical Approach
Abstract: Semiconductor device physics forms the foundation of modern electronic and optoelectronic technologies. Mathematical modelling provides a rigorous framework for understanding, predicting, and optimizing the behavior of semiconductor devices by linking physical principles with device-level performance. This work presents an analytical approach to the mathematical modelling of semiconductor devices, emphasizing the derivation and interpretation of governing equations that describe charge transport and electrostatic behavior. The model is based on fundamental physical …
Published in Research & Reviews: Discrete Mathematical Structures · Vol. 13, Issue 1, 2026 · pp. 36–42 Read article