Girish Hariharan¹, Vinyas¹, Gowrishankar Mandya Chennegowda¹, Nitesh Kumar¹, Shiva Kumar¹, Deepak Doreswamy², Subraya Krishna Bhat^1,*

CMC-Computers, Materials & Continua, Vol.86, No.3, 2026, DOI:10.32604/cmc.2025.073772 - 12 January 2026

Abstract This study presents a framework involving statistical modeling and machine learning to accurately predict and optimize the mechanical and damping properties of hybrid granite–epoxy (G–E) composites reinforced with cast iron (CI) filler particles. Hybrid G–E composite with added cast iron (CI) filler particles enhances stiffness, strength, and vibration damping, offering enhanced performance for vibration-sensitive engineering applications. Unlike conventional approaches, this work simultaneously employs Artificial Neural Networks (ANN) for high-accuracy property prediction and Response Surface Methodology (RSM) for in-depth analysis of factor interactions and optimization. A total of 24 experimental test data sets of varying input… More >

Tahir Mahmood^1,*, Muhammad Waseem Ashraf^1,*, Shahzadi Tayyaba², Muhammad Munir³, Babiker M. A. Abdel-Banat³, Hassan Ali Dinar³

CMC-Computers, Materials & Continua, Vol.86, No.3, 2026, DOI:10.32604/cmc.2025.072436 - 12 January 2026

Abstract Artificial intelligence (AI) based models have been used to predict the structural, optical, mechanical, and electrochemical properties of zinc oxide/graphene oxide nanocomposites. Machine learning (ML) models such as Artificial Neural Networks (ANN), Support Vector Regression (SVR), Multilayer Perceptron (MLP), and hybrid, along with fuzzy logic tools, were applied to predict the different properties like wavelength at maximum intensity (444 nm), crystallite size (17.50 nm), and optical bandgap (2.85 eV). While some other properties, such as energy density, power density, and charge transfer resistance, were also predicted with the help of datasets of 1000 (80:20). In… More >

Junwen Huo, Haicheng Liang, Weiye Dong, Xiaoming Du^*

CMC-Computers, Materials & Continua, Vol.86, No.2, pp. 1-20, 2026, DOI:10.32604/cmc.2025.073285 - 09 December 2025

Abstract With the rapid advancement of electromagnetic launch technology, enhancing the structural stability and thermal resistance of armatures has become essential for improving the overall efficiency and reliability of railgun systems. Traditional aluminum alloy armatures often suffer from severe ablation, deformation, and uneven current distribution under high pulsed currents, which limit their performance and service life. To address these challenges, this study employs the Johnson–Cook constitutive model and the finite element method to develop armature models of aluminum matrix composites with varying heterogeneous graphene volume fractions. The temperature, stress, and strain of the armatures during operation… More >

Bindi Saurabh Thakkar¹, Pradeep Kumar Karsh^2,*

CMC-Computers, Materials & Continua, Vol.86, No.2, pp. 1-22, 2026, DOI:10.32604/cmc.2025.072839 - 09 December 2025

Abstract This study investigates the uncertain dynamic characterization of hybrid composite plates by employing advanced machine-assisted finite element methodologies. Hybrid composites, widely used in aerospace, automotive, and structural applications, often face variability in material properties, geometric configurations, and manufacturing processes, leading to uncertainty in their dynamic response. To address this, three surrogate-based machine learning approaches like radial basis function (RBF), multivariate adaptive regression splines (MARS), and polynomial neural networks (PNN) are integrated with a finite element framework to efficiently capture the stochastic behavior of these plates. The research focuses on predicting the first three natural frequencies… More >

Thierry Mugenzi, Cahit Perkgoz^*

CMC-Computers, Materials & Continua, Vol.86, No.1, pp. 1-21, 2026, DOI:10.32604/cmc.2025.070381 - 10 November 2025

Abstract Missing data presents a crucial challenge in data analysis, especially in high-dimensional datasets, where missing data often leads to biased conclusions and degraded model performance. In this study, we present a novel autoencoder-based imputation framework that integrates a composite loss function to enhance robustness and precision. The proposed loss combines (i) a guided, masked mean squared error focusing on missing entries; (ii) a noise-aware regularization term to improve resilience against data corruption; and (iii) a variance penalty to encourage expressive yet stable reconstructions. We evaluate the proposed model across four missingness mechanisms, such as Missing… More >

Ghinwa Al Mimar¹, Natrah Kamaruzaman^1,*, Kamil Talib Alkhateeb²

Frontiers in Heat and Mass Transfer, Vol.23, No.6, pp. 1933-1956, 2025, DOI:10.32604/fhmt.2025.070118 - 31 December 2025

Abstract The pivotal role microchannels play in the thermal management of electronic components has, in recent decades, prompted extensive research into methods for enhancing their heat transfer performance. Among these methods, surface wettability modification was found to be highly effective owing to its significant influence on boiling dynamics and heat transfer mechanisms. In this study, we modified surface wettability using a nanocomposite coating composed of graphene nano plate (GNPs) and multi-walled carbon nanotubes (MWCNT) and then examined how the modification affected the transfer of boiling heat in microchannels. The resultant heat transfer coefficients for hydrophilic and… More >

Zhimin Zhao, Liyun Feng, Dongsheng Song, Ming Zhang^*

Journal of Polymer Materials, Vol.42, No.4, pp. 929-957, 2025, DOI:10.32604/jpm.2025.074529 - 26 December 2025

Abstract Global water pollution is becoming increasingly serious, and compound pollutants such as heavy metals and organic dyes pose multidimensional threats to ecology and human health. Metal-organic skeleton compounds (MOFs) have been proven to be highly efficient in capturing a variety of pollutants by virtue of their large specific surface area, adjustable pore channels, and abundant active sites. However, the easy agglomeration of powders, the difficulty of recycling, and the poor long-term stability have limited their practical applications. Cellulose, as the most abundant renewable polymer in nature, has the characteristics of a three-dimensional network, mechanical flexibility,… More >

Minglei Hu¹, Wei Zhang¹, Bin Hu¹, Haicun Yang², Fuqiang Chu², Zheng Cao^2,*

Journal of Polymer Materials, Vol.42, No.4, pp. 1125-1141, 2025, DOI:10.32604/jpm.2025.073300 - 26 December 2025

Abstract Polypropylene (PP) has low inherent susceptibility to common industrial lasers, which poses a significant challenge for laser-based marking. To improve the laser sensitivity of PP, molybdenum disulfide grafted with polystyrene (MoS₂-g-PS) was synthesized via in-situ free radical polymerization and used as a laser-sensitive filler for PP composites prepared by melt blending. The composites were then marked with a 1064 nm semiconductor laser, producing clear and legible patterns. The marked surfaces were characterized using scanning electron microscopy (SEM), transmission electron microscopy (TEM), colorimetry, Raman spectroscopy, and thermogravimetric analysis (TGA). The results demonstrate that the PP/MoS₂-g-PS composites exhibit significantly More >

Ruiping Wang, Chuang He, Shuo Zhang, Miaojun Xu^*, Zhuo Wang, Xiaoli Li^*, Bin Tao, Suliang Gao, Bin Li^*

Journal of Polymer Materials, Vol.42, No.4, pp. 1035-1049, 2025, DOI:10.32604/jpm.2025.073108 - 26 December 2025

Abstract The fabrication of highly flame-retardant polyamide 6 (PA6) composites is of great significance for expanding their practical applications. Herein, a new flame-retardant system (ADP/FA) was developed by combining aluminum diethylphosphinate (ADP) with excellent flame retardancy and fly ash (FA), an economical and environmentally friendly industrial waste. Due to the synergistic flame-retardant effect of ADP/FA in the condensed phase and gas phase, the PA6 composite containing only 11 wt% of ADP/FA (mass ratio 93:7) obtained vertical burning (UL-94) tests V-0 rating with a limiting oxygen index (LOI) of 30.9%. To obtain the same flame-retardant level of… More > Graphic Abstract

Md Salah Uddin^*

Journal of Polymer Materials, Vol.42, No.4, pp. 1051-1073, 2025, DOI:10.32604/jpm.2025.070688 - 26 December 2025

Abstract Carbon fiber-reinforced composites (CFRCs) have a wide range of applications in the aerospace, automotive, and energy sectors. A higher specific strength-to-weight ratio is desired in high-performance applications. The failure mechanism of CFRCs involves multiscale phenomena, such as failure that can occur at the matrix, fibers, interface, layers, lamina, and laminates. When an impactor hits the CFRCs, the design involves analyzing each of these stages to prevent failure and optimize the properties of CFRCs under various loading conditions. A numerical model was employed to predict the fracture toughness of CFRCs with varying weight fractions and orientations.… More >