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166 pages, 863 KB

Open AccessConference Report

Abstracts of the 4th International Online Conference on Materials

by Ingo Dierking

Mater. Proc. 2025, 26(1), 1; https://doi.org/10.3390/materproc2025026001 - 15 Dec 2025

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(This article belongs to the Proceedings of The 4th International Online Conference on Materials)

6 pages, 933 KB

Open AccessProceeding Paper

Femtosecond Laser Micro- and Nanostructuring of Aluminium Moulds for Durable Superhydrophobic PDMS Surfaces

by Stefania Caragnano, Raffaele De Palo, Felice Alberto Sfregola, Caterina Gaudiuso, Francesco Paolo Mezzapesa, Pietro Patimisco, Antonio Ancona and Annalisa Volpe

Mater. Proc. 2025, 26(1), 2; https://doi.org/10.3390/materproc2025026002 - 22 Dec 2025

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Abstract

Surface functionalisation of polymers is essential for enhancing properties such as wettability and mechanical resistance. This study presents a scalable, coating-free approach to fabricate hydrophobic and superhydrophobic Polydimethylsiloxane (PDMS) surfaces. Aluminium (AA2024) moulds were microstructured using a TruMicro femtosecond laser system to generate grid patterns with controlled hatch distances and depths, as well as laser-induced periodic surface structures (LIPSSs). These features were accurately replicated onto PDMS, as confirmed by scanning electron miscoscopy (SEM) and profilometry. Contact angle measurements showed a marked increase in hydrophobicity, reaching superhydrophobicity for optimised parameters, with surface stability maintained over four months without degradation. Full article

(This article belongs to the Proceedings of The 4th International Online Conference on Materials)

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6 pages, 1519 KB

Open AccessProceeding Paper

A Comparative Assessment of XFEM and FEM for Stress Concentration at Circular Holes near Bi-Material Interfaces

by Huu-Dien Nguyen

Mater. Proc. 2025, 26(1), 3; https://doi.org/10.3390/materproc2025026003 - 5 Jan 2026

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Abstract

Accurately predicting stress concentration factors (SCFs) is essential for assessing the structural integrity of components containing holes or discontinuities, especially in multi-material systems. Traditional Finite Element Method (FEM) models often require substantial mesh refinement near geometric discontinuities, whereas the Extended Finite Element Method (XFEM) allows discontinuities to be represented independently of the mesh through enrichment functions. This study provides a comparative assessment of FEM and XFEM for evaluating SCFs around a circular hole located near a bi-material interface. Both methods are implemented in MATLAB R2019a using the level-set approach to describe the hole. The displacement and stress fields obtained from FEM and XFEM are compared, followed by an evaluation against an established analytical reference solution. The findings show that while both methods reproduce global fields with good agreement, differences arise in the accuracy of SCF prediction. These results highlight the conditions under which XFEM may offer advantages over conventional FEM when modeling discontinuities in heterogeneous materials. Full article

(This article belongs to the Proceedings of The 4th International Online Conference on Materials)

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12 pages, 3719 KB

Open AccessProceeding Paper

Key Predictors of Lightweight Aggregate Concrete Compressive Strength by Machine Learning from Density Parameters and Ultrasonic Pulse Velocity Testing

by Violeta Migallón, Héctor Penadés and José Penadés

Mater. Proc. 2025, 26(1), 4; https://doi.org/10.3390/materproc2025026004 - 6 Jan 2026

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Abstract

Non-destructive evaluation techniques are increasingly recognised as effective alternatives to destructive testing for estimating the compressive strength of lightweight aggregate concrete (LWAC). Among these, ultrasonic pulse velocity (UPV) is a well-established and widely employed method, characterised by its speed, non-invasiveness, and relative simplicity of implementation. In this study, an experimental dataset comprising 640 core segments from 160 cylindrical specimens, provided for analysis, was investigated. Each segment was described by physical and processing variables or features, including lightweight aggregate (LWA) and concrete densities, casting and vibration times, experimental dry density, and P-wave velocity obtained through UPV testing. A segregation index, derived from UPV measurements and defined as the ratio of local to mean P-wave velocity within each specimen, was also considered, following approaches previously suggested in the literature. A range of machine learning techniques was applied to assess the predictive capacity of local P-wave velocity and segregation index. Most ensemble-based methods and support vector regression (SVR) achieved the highest predictive performance when the segregation index was excluded, suggesting that its inclusion did not improve the predictive ability of the models. By contrast, Gaussian process regression (GPR) showed slight improvements when the segregation index was included. The results confirmed that the P-wave velocity measured by UPV testing is a reliable non-destructive predictor of compressive strength in LWAC. At the same time, the added value of the segregation index remained negligible under conditions of low segregation, as reflected by segregation index values above 0.8. These findings highlight the practical potential of integrating UPV-based measurements with data-driven modelling to enhance the reliability of concrete characterisation and quality control. Full article

(This article belongs to the Proceedings of The 4th International Online Conference on Materials)

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