Xianrui Lyu, Xiaodan Ren^*

CMES-Computer Modeling in Engineering & Sciences, Vol.146, No.1, 2026, DOI:10.32604/cmes.2025.074388 - 29 January 2026

Abstract Inverse design of advanced materials represents a pivotal challenge in materials science. Leveraging the latent space of Variational Autoencoders (VAEs) for material optimization has emerged as a significant advancement in the field of material inverse design. However, VAEs are inherently prone to generating blurred images, posing challenges for precise inverse design and microstructure manufacturing. While increasing the dimensionality of the VAE latent space can mitigate reconstruction blurriness to some extent, it simultaneously imposes a substantial burden on target optimization due to an excessively high search space. To address these limitations, this study adopts a Variational… More >

Yewon Choi^1,2, Song Hyeon Ju², Jungsoo Nam^2,*, Min Ku Kim^1,3,*

CMES-Computer Modeling in Engineering & Sciences, Vol.146, No.1, 2026, DOI:10.32604/cmes.2025.071817 - 29 January 2026

Abstract The composite material layering process has attracted considerable attention due to its production advantages, including high scalability and compatibility with a wide range of raw materials. However, changes in process conditions can lead to degradation in layer quality and non-uniformity, highlighting the need for real-time monitoring to improve overall quality and efficiency. In this study, an AI-based monitoring system was developed to evaluate layer width and assess quality in real time. Three deep learning models Faster Region-based Convolutional Neural Network (R-CNN), You Only Look Once version 8 (YOLOv8), and Single Shot MultiBox Detector (SSD) were… More >

Jia Yan Lim^1,2, Siti Madiha Muhammad Amir³, Roslan Yahya³, Marta Peña Fernández², Tze Chuen Yap^1,*

CMC-Computers, Materials & Continua, Vol.86, No.2, pp. 1-19, 2026, DOI:10.32604/cmc.2025.070707 - 09 December 2025

Abstract Additive Manufacturing, also known as 3D printing, has transformed conventional manufacturing by building objects layer by layer, with material extrusion or fused deposition modeling standing out as particularly popular. However, due to its manufacturing process and thermal nature, internal voids and pores are formed within the thermoplastic materials being fabricated, potentially leading to a decrease in mechanical properties. This paper discussed the effect of printing parameters on the porosity and the mechanical properties of the 3D printed polylactic acid (PLA) through micro-computed tomography (microCT), computational image analysis, and Charpy impact testing. The results for both… More >

Muhammad Adil¹, Nadeem Javaid^1,*, Imran Ahmed², Abrar Ahmed³, Nabil Alrajeh^4,*

CMC-Computers, Materials & Continua, Vol.86, No.1, pp. 1-20, 2026, DOI:10.32604/cmc.2025.071215 - 10 November 2025

Abstract Heart disease remains a leading cause of mortality worldwide, emphasizing the urgent need for reliable and interpretable predictive models to support early diagnosis and timely intervention. However, existing Deep Learning (DL) approaches often face several limitations, including inefficient feature extraction, class imbalance, suboptimal classification performance, and limited interpretability, which collectively hinder their deployment in clinical settings. To address these challenges, we propose a novel DL framework for heart disease prediction that integrates a comprehensive preprocessing pipeline with an advanced classification architecture. The preprocessing stage involves label encoding and feature scaling. To address the issue of… More >

Kui Wang^*, Qianbing Tan, Yisen Liu

The International Conference on Computational & Experimental Engineering and Sciences, Vol.34, No.1, pp. 1-1, 2025, DOI:10.32604/icces.2025.012404

Abstract To address the increasing demands for lightweight and passive safety in transportation equipment, a series of studies on the crashworthiness design of composite thin-walled structures were conducted. These investigations leveraged the high specific strength/stiffness advantages of carbon fiber-reinforced polyamide composites and the high-formability benefits of fused deposition modeling (FDM) additive manufacturing technology. Compared with traditional composite manufacturing processes, lattice-filled thin-walled structures, integrally fabricated via additive manufacturing, exhibited significant synergistic interactions between their internal lattice and outer walls during compression. This synergy effectively enhanced the energy absorption capacity of the structures and achieved a "1+1>2" synergistic… More >

Du-Yi Wang¹, Shih-Chen Shi^1,*, Dieter Rahmadiawan^1,2

Journal of Polymer Materials, Vol.42, No.4, pp. 1075-1095, 2025, DOI:10.32604/jpm.2025.072263 - 26 December 2025

Abstract Polymethyl methacrylate (PMMA) is widely used in diverse applications such as protective components (e.g., automotive lamp covers and structural casings), optical devices, and biomedical products, owing to its lightweight nature and impact resistance. However, its surface hardness and wear resistance remain insufficient under prolonged exposure to abrasive environments. In this study, a multi-filler strategy with nano-silica (SiO₂), brominated lignin (Br-Lignin), and cellulose nanocrystals (CNCs) was employed to enhance PMMA tribological properties. SiO₂ provided localized reinforcement, Br-Lignin established stable network structures, and CNCs improved compactness, enabling strong synergistic effects. As a result, the composites achieved up to More >

Jinsi Yuan, Haijiang Wang^*, Jiaming Bai^*

The International Conference on Computational & Experimental Engineering and Sciences, Vol.33, No.4, pp. 1-2, 2025, DOI:10.32604/icces.2025.011073

Abstract Solid oxide fuel cells (SOFCs) have attracted considerable attention for their high efficiency, environmental advantages, and versatility in fuel sources. Research has shown that optimizing the structure of SOFCs can lead to significant performance improvements. Additive manufacturing (AM) has emerged as a promising technology for geometrical optimization of SOFCs, owing to its capability to create complex and programmable structures. However, fabricating three-dimensional electrode structures with fine, highly resolved features remains a significant challenge. Herein, a vat photopolymerization (VPP) 3D printing process was developed for fabricating the Nickel Oxide-Yttria Stabilized Zirconia (NiO-YSZ) anode structure of SOFC.… More >

Fida Hussain^1,*, Farooq Khan², Javed Ahmad¹, Heqiang Huo³, Tao Jiang³, Iqrar Rana⁴, Sajida Habib⁵, Muhammad Umer Farooq^1,*

Phyton-International Journal of Experimental Botany, Vol.94, No.10, pp. 3231-3249, 2025, DOI:10.32604/phyton.2025.069654 - 29 October 2025

Abstract The analysis of combining ability and heterosis is very important in enhancing the yield and oil quality of sunflowers under adverse conditions, and it reveals the potential of the parents and the mechanism of gene action. In this study, twenty-one hybrids were developed by crossing seven cytoplasmic male sterile (CMS) lines with three restorer lines and evaluated for agronomic and quality traits. Highly significant general combining ability (GCA) and specific combining ability (SCA) effects were observed, confirming the role of both additive and non-additive gene actions. Among the tested crosses, A-42 × R-86, A-92 ×… More >

Yifei Wang, Zhao Zhang^*

The International Conference on Computational & Experimental Engineering and Sciences, Vol.33, No.3, pp. 1-1, 2025, DOI:10.32604/icces.2025.011121

Abstract Additive manufacturing (AM) reveals high anisotropy in mechanical properties due to the thermal accumulation induced microstructures. How to reveal the internal connection between the microstructures and the mechanical properties in additive manufacturing is a challenge. There are many methods to predict the mechanical properties based on the microstructural evolutions in additive manufacturing [1–3]. Here we summarized the main methods for the prediction of the mechanical properties in additive manufacturing, including crystal plasticity finite element method (CPFEM), dislocation dynamics (DD), and molecular dynamics (MD). We systematically examine these primary approaches for mechanical property predictions in AM,… More >

Xiang Gao, Zhao Zhang^*

The International Conference on Computational & Experimental Engineering and Sciences, Vol.33, No.3, pp. 1-1, 2025, DOI:10.32604/icces.2025.011092

Abstract Microstructures is the key factor determining the properties of the additively manufactured components [1]. It can be highly affected by the temperatures generated during the additive manufacturing process. Phase field method, as established based on Ginzburg-Landau theory is an efficient tool to simulate the microstructural evolutions in additive manufacturing [2]. It can be used to simulate solidification, diffusion, phase transformation and grain growth [3]. Here we compared the new progress on the phase field method in the field of additive manufacturing. Due to the differences between the temperature field and the grain field, how to… More >