Materials

31 pages, 4719 KiB

Open AccessReview

Exploring the Gas Permeability of Type IV Hydrogen Storage Cylinder Liners: Research and Applications

by Xinshu Li, Qing Wang, Shuang Wu, Dongyang Wu, Chunlei Wu, Da Cui and Jingru Bai

Materials 2025, 18(13), 3127; https://doi.org/10.3390/ma18133127 (registering DOI) - 1 Jul 2025

As hydrogen fuel cell vehicles gain momentum as crucial zero-emission transportation solutions, the urgency to address hydrogen permeability through the polymer liner becomes paramount for ensuring the safety, efficiency, and longevity of Type IV hydrogen storage tanks. This paper synthesizes existing research findings, [...] Read more.

As hydrogen fuel cell vehicles gain momentum as crucial zero-emission transportation solutions, the urgency to address hydrogen permeability through the polymer liner becomes paramount for ensuring the safety, efficiency, and longevity of Type IV hydrogen storage tanks. This paper synthesizes existing research findings, analyzes the influence of different materials and structures on gas permeability, elucidates the dissolution and diffusion mechanisms of hydrogen in plastic liners, and discusses their engineering applications. We focus on measurement methods, influencing factors, and improvement strategies for liner gas permeability. Additionally, we explore the prospects of Type IV hydrogen storage tanks in fields such as automotive, aerospace, and energy storage industries. Through this comprehensive review of liner gas permeability, critical insights are provided to guide the development of efficient and safe hydrogen storage and transportation systems. These insights are vital for advancing the widespread application of hydrogen energy technology and fostering sustainable energy development, significantly contributing to efforts aimed at enhancing the performance and safety of Type IV hydrogen storage tanks. Full article

► Show Figures

Figure 1

16 pages, 1312 KiB

Open AccessArticle

Effect of Zinc, Magnesium, and Manganese Phosphate Coatings on the Corrosion Behaviour of Steel

by Alin-Marian Cazac, Lucian-Ionel Cioca, Petru Lazar, Gheorghe Badarau, Nicanor Cimpoesu, Diana-Petronela Burduhos-Nergis, Pompilica Iagaru, Ramona Cimpoesu, Anca Cazac, Costica Bejinariu and Adriana Milea (Pârvu)

Materials 2025, 18(13), 3126; https://doi.org/10.3390/ma18133126 - 1 Jul 2025

Abstract

This study provides a systematic comparison of three types of phosphate coatings, applied by identical immersion phosphating processes and tested under two different environmental conditions representative of real industrial scenarios. The focus of this study is the investigation of the corrosion behaviour of [...] Read more.

This study provides a systematic comparison of three types of phosphate coatings, applied by identical immersion phosphating processes and tested under two different environmental conditions representative of real industrial scenarios. The focus of this study is the investigation of the corrosion behaviour of zinc, magnesium, and manganese phosphate coatings on reinforcing steel in two different corrosion environments: river water and seawater. The phosphate coatings were obtained via the immersion phosphating technique. Various techniques, including scanning electron microscopy (SEM), energy dispersive X-ray spectroscopy (EDX), potentiodynamic polarization curve (PDP) testing, and electrochemical impedance spectroscopy (EIS), were used to evaluate the morphology and corrosion resistance of the coatings. The overall corrosion protection performance of the coatings followed the order of Zn phosphate > Mn phosphate > Mg phosphate. The results indicate that the samples with the Zn-phosphated coating showing the highest improvement. This coating showed no major morphological changes and achieved significantly reduced corrosion rates—0.258 µm/year in river water and 3.060 µm/year in seawater—compared to the typical corrosion rate of uncoated steel, which is about 45 µm/year. These findings emphasize the effectiveness of Zn phosphate coatings in mitigating corrosion in both river water and marine conditions. Full article

(This article belongs to the Special Issue Characterization of Metallic Materials: Solidification, Deformation, Heat Treatment and Other Related Phenomena—Third Edition)

12 pages, 1461 KiB

Open AccessArticle

Pressure-Induced Structural Stabilities and Superconductivity in Rhodium Borides

by Junyi Du, Weiguo Sun, Xiaofeng Li and Xinfang Su

Materials 2025, 18(13), 3125; https://doi.org/10.3390/ma18133125 - 1 Jul 2025

Abstract

Transition metal borides have garnered significant research interest due to their versatile properties, including superconductivity and exceptional hardness. This study examines the stable crystal structures of Rhodium-Boron (Rh-B) compounds under high pressure using first-principles structural searching. Beyond the previously known Rh₂B, [...] Read more.

Transition metal borides have garnered significant research interest due to their versatile properties, including superconductivity and exceptional hardness. This study examines the stable crystal structures of Rhodium-Boron (Rh-B) compounds under high pressure using first-principles structural searching. Beyond the previously known Rh₂B, RhB₂, and RhB₄ phases, three new boron-rich phases—C2/m-RhB₆, Amm2-RhB₆, and Cmca-RhB₈—are identified, each characterized by three-dimensional covalent bonding networks. Their mechanical and thermodynamic stability is validated through elastic property assessments and phonon dispersion calculations. Surprisingly, these phases exhibit low bulk and shear moduli, ruling them out as candidates for hard materials. The metallic character of these borides is evident from their electronic density of states, which exhibits a sharp peak at the E_F-a signature often associated with superconducting systems. Indeed, our calculations predict T_c values of 8.93 K and 9.36 K for Amm2-RhB₆ and Cmca-RhB₈, respectively, at 100 GPa. Full article

16 pages, 653 KiB

Open AccessCommunication

Equation-Based Modeling of Shape Memory Alloys for Reinforcement of Masonry Structures Against Out-of-Plane Excitation

by Kacper Wasilewski, Artur Zbiciak and Wojciech Terlikowski

Materials 2025, 18(13), 3124; https://doi.org/10.3390/ma18133124 - 1 Jul 2025

Abstract

The incorporation of advanced smart materials, such as shape memory alloys (SMAs), in civil engineering presents significant challenges, particularly in modeling their complex behavior. Traditional numerical SMA models often require material parameters that are difficult to estimate and validate. The objective of this [...] Read more.

The incorporation of advanced smart materials, such as shape memory alloys (SMAs), in civil engineering presents significant challenges, particularly in modeling their complex behavior. Traditional numerical SMA models often require material parameters that are difficult to estimate and validate. The objective of this paper is to introduce an equation-based approach to modeling the superelastic behavior of SMAs based on rheological models. The proposed phenomenological model accurately captures SMA superelasticity under isothermal conditions, with each material parameter directly correlated to data from standard mechanical experiments. Four modifications to the baseline rheological model are proposed, highlighting their impact on superelastic characteristics. The resulting constitutive relationships are expressed as non-linear ordinary differential equations, making them compatible with commercial finite element method (FEM) software through user-defined subroutines. The practical application of this modeling approach is demonstrated through the strengthening of a historical masonry wall subjected to seismic activity. Comparative analysis shows that ties incorporating SMA segments outperform traditional steel ties by reducing the potential damage and enhancing the structural performance. Additionally, the energy dissipation during the SMA phase transformation improves the damping of vibrations, further contributing to the stability of the structure. This study underscores the potential of SMA-based solutions in seismic retrofitting and highlights the advantages of equation-based modeling for practical engineering applications. Full article

(This article belongs to the Special Issue Modelling of Deformation Characteristics of Materials or Structures)

22 pages, 5799 KiB

Open AccessArticle

Use of BOIvy Optimization Algorithm-Based Machine Learning Models in Predicting the Compressive Strength of Bentonite Plastic Concrete

by Shuai Huang, Chuanqi Li, Jian Zhou, Xiancheng Mei and Jiamin Zhang

Materials 2025, 18(13), 3123; https://doi.org/10.3390/ma18133123 - 1 Jul 2025

Abstract

The combination of bentonite and conventional plastic concrete is an effective method for projecting structures and adsorbing heavy metals. Determining the compressive strength (CS) is a crucial step in the design of bentonite plastic concrete (BPC). Traditional experimental analyses are resource-intensive, time-consuming, and [...] Read more.

The combination of bentonite and conventional plastic concrete is an effective method for projecting structures and adsorbing heavy metals. Determining the compressive strength (CS) is a crucial step in the design of bentonite plastic concrete (BPC). Traditional experimental analyses are resource-intensive, time-consuming, and prone to high uncertainties. To address these challenges, several machine learning (ML) models, including support vector regression (SVR), artificial neural network (ANN), and random forest (RF), are generated to forecast the CS of BPC materials. To improve the prediction accuracy, a meta-heuristic optimization, called the Ivy algorithm, is integrated with Bayesian optimization (BOIvy) to optimize the ML models. Several statistical indices, including the coefficient of determination (R²), root mean square error (RMSE), prediction accuracy (U₁), prediction quality (U₂), and variance accounted for (VAF), are adopted to evaluate the predictive performance of all models. Additionally, Shapley additive explanation (SHAP) and sensitivity analysis are conducted to enhance model interpretability. The results indicate that the best model is the BOIvy-ANN model, which achieves the optimal indices during the testing. Moreover, water, curing time, and cement are found to be more influential on the prediction of the CS of BPC than other features. This paper provides a strong example of applying artificial intelligence (AI) techniques to estimate the performance of BPC materials. Full article

(This article belongs to the Section Construction and Building Materials)

20 pages, 5757 KiB

Open AccessArticle

Application of Soft Computing Represented by Regression Machine Learning Model and Artificial Lemming Algorithm in Predictions for Hydrogen Storage in Metal-Organic Frameworks

by Jiamin Zhang, Yanzhe Li, Chuanqi Li, Xiancheng Mei and Jian Zhou

Materials 2025, 18(13), 3122; https://doi.org/10.3390/ma18133122 - 1 Jul 2025

Abstract

Metal-organic frameworks (MOFs) have been extensively studied for hydrogen storage due to their unique properties. This paper aims to develop several regression-based machine learning models to predict the hydrogen storage capacity of MOFs, including artificial neuron network (ANN), support vector regression (SVR), random [...] Read more.

Metal-organic frameworks (MOFs) have been extensively studied for hydrogen storage due to their unique properties. This paper aims to develop several regression-based machine learning models to predict the hydrogen storage capacity of MOFs, including artificial neuron network (ANN), support vector regression (SVR), random forest (RF), extreme learning machine (ELM), kernel extreme learning machine (KELM), and generalized regression neural network (GRNN). An improved population-based metaheuristic optimization algorithm, the artificial lemming algorithm (ALA), is employed to select the hyperparameters of these machine learning models, enhancing their performance. All developed models are trained and tested using experimental data from multiple studies. The performance of the models is evaluated using various statistical metrics, complemented by regression plots, error analysis, and Taylor graphs to further identify the most effective predictive model. The results show that the ALA-RF model obtains the best performance in predicting hydrogen storage, with optimal values of coefficient of determination (R²), root mean square error (RMSE), Willmott’s index (WI), and weighted average percentage error (WAPE) in both training and testing phases (0.9845 and 0.9840, 0.2719 and 0.2828, 0.9961 and 0.9959, and 0.0667 and 0.0714, respectively). Additionally, pressure is identified as the most significant feature for predicting hydrogen storage in MOFs. These findings provide an intelligent solution for the selection of MOFs and optimization of operational conditions in hydrogen storage processes. Full article

(This article belongs to the Special Issue Hydrides for Energy Storage: Materials, Technologies and Applications)

► Show Figures

Figure 1

19 pages, 6386 KiB

Open AccessArticle

Process–Structure Co-Optimization of Glass Fiber-Reinforced Polymer Automotive Front-End Module

by Ziming Chen, Pengcheng Guo, Longjian Tan, Tuo Ye and Luoxing Li

Materials 2025, 18(13), 3121; https://doi.org/10.3390/ma18133121 - 1 Jul 2025

Abstract

For automotive GFRP structural components, beyond structural design, the warpage, residual stress/strain, and fiber orientation inevitably induced during the injection molding process significantly compromise their service performance. These factors also diminish the reliability of performance assessments. Thus, it is imperative to develop a [...] Read more.

For automotive GFRP structural components, beyond structural design, the warpage, residual stress/strain, and fiber orientation inevitably induced during the injection molding process significantly compromise their service performance. These factors also diminish the reliability of performance assessments. Thus, it is imperative to develop a process–structure co-optimization approach for GFRP components. In this paper, the performance of a front-end module is evaluated through topological structure design, injection molding process optimization, and simulation with mapped injection molding history, followed by experimental validation and analysis. Under ±1000 N loading, the initial design shows excessive displacement at the latch mounting points (2.254 mm vs. <2.0 mm limit), which is reduced to 1.609 mm after topology optimization. By employing a sequential valve control system, the controls of the melt line and fiber orientation are is superior to thatose of conventional gating systems. The optimal process parameter combination is determined through orthogonal experiments, reducing the warpage to 1.498 mm with a 41.5% reduction compared to the average warpage of the orthogonal tests. The simulation results incorporating injection molding data mapping (fiber orientation, residual stress–strain) show closer agreement with experimental measurements. When the measured displacement exceeded 0.65 mm, the average relative error

E_{r}

, range

R

, and variance

s^{2}

between the experimental results and mapped simulations were 11.78%, 14%, and 0.002462, respectively, validating the engineering applicability of this method. The methodology and workflow can provide methodological support for the design and performance assessment of GFRP automotive body structures, which enhances structural rigidity, improves control over injection molding process defects, and elevates the reliability of performance evaluation. Full article

(This article belongs to the Special Issue Alloys and Composites: Structural and Functional Applications, Second Edition)

► Show Figures

Figure 1

31 pages, 9815 KiB

Open AccessArticle

Development of Covalently Functionalized Alginate–Pyrrole and Polypyrrole–Alginate Nanocomposites as 3D Printable Electroconductive Bioinks

by Abraham Abbey Paul, Olga Kryukov, Anil Kumar Bandela, Hamody Muadi, Nurit Ashkenasy, Smadar Cohen and Robert S. Marks

Materials 2025, 18(13), 3120; https://doi.org/10.3390/ma18133120 - 1 Jul 2025

Abstract

Electrically conductive hydrogels are gaining attention owing to their applications in biosensing, cellular interfaces, and tissue engineering. However, conventional hydrogels often lack adequate electrical conductivities. Here, we present two novel conductive alginate-based hydrogels designed for extrusion-based 3D bioprinting: (i) covalently synthesized alginate–polypyrrole (alginate–PPy) [...] Read more.

Electrically conductive hydrogels are gaining attention owing to their applications in biosensing, cellular interfaces, and tissue engineering. However, conventional hydrogels often lack adequate electrical conductivities. Here, we present two novel conductive alginate-based hydrogels designed for extrusion-based 3D bioprinting: (i) covalently synthesized alginate–polypyrrole (alginate–PPy) via EDC/NHS-mediated conjugation with 3-aminopropyl pyrrole, and (ii) nanoparticle-reinforced alginate blended with polypyrrole nanoparticles (alginate@PPy-NP). Both systems exhibited shear-thinning behavior, tunable viscoelasticity, and excellent printability. Alginate@PPy-NP demonstrated superior compressive strength and shape fidelity, whereas alginate–PPy showed enhanced elastic moduli (G′/G″), reflecting a more uniform gel network. Electrical conductivity increased with increasing pyrrole content in both formulations. Optimization of the composition and printing conditions enabled the fabrication of fibroblast-laden constructs with high structural integrity. This work highlights the potential of alginate–polypyrrole hydrogels as customizable, conductive bioinks for 3D bioprinting in regenerative medicine. Full article

(This article belongs to the Special Issue Advances in 3D Printing for Biomaterials)

► Show Figures

Figure 1

14 pages, 12761 KiB

Open AccessArticle

CO₂ and UV Laser-Induced Graphene Based on Polymer Transformation: Advanced Characterizations by 2D Raman Mapping Combined with Microscopy Techniques

by Sabina Botti, Francesca Bonfigli, Alessio Bruttomesso, Federico Micciulla, Valentina Nigro, Alessandro Rufoloni and Angelo Vannozzi

Materials 2025, 18(13), 3119; https://doi.org/10.3390/ma18133119 - 1 Jul 2025

Abstract

Since its discovery, laser-induced graphene (LIG) has attracted much interest because this technique, having all the advantages of a laser processing technology, is more convenient and cost-effective than other graphene production methods. This work offers a detailed analysis of LIG structures produced by [...] Read more.

Since its discovery, laser-induced graphene (LIG) has attracted much interest because this technique, having all the advantages of a laser processing technology, is more convenient and cost-effective than other graphene production methods. This work offers a detailed analysis of LIG structures produced by UV and CO₂ laser irradiation from polyimide performed with surface scanning Raman spectroscopy combined with microscopy techniques. Although UV LIG has a less ordered structure than that obtained by CO₂ laser irradiation, our study indicates that UV LIG can be patterned with a resolution higher than that obtained with CO₂ laser irradiation and a much smaller penetration depth into the substrate. Full article

(This article belongs to the Special Issue Carbon Nanomaterials for Multifunctional Applications)

► Show Figures

Figure 1

26 pages, 6855 KiB

Open AccessArticle

Hydrogel Microarray for Bioanalytical Applications: Preliminary Study on Material Properties

by Weronika Kieres, Sonia Kudłacik-Kramarczyk, Joanna Marczyk, Celina Ziejewska, Anna Drabczyk, Robert P. Socha and Marcel Krzan

Materials 2025, 18(13), 3118; https://doi.org/10.3390/ma18133118 - 1 Jul 2025

Abstract

The aim of this study was to develop and characterize UV-crosslinked hydrogel matrices based on polyethylene glycol diacrylate (PEGDA), gum arabic, betaine, and sodium alginate for potential bioanalytical applications. Various physicochemical analyses were performed, including pre-polymerization emulsion stability (Multiscan), FT-IR spectroscopy, swelling behavior [...] Read more.

The aim of this study was to develop and characterize UV-crosslinked hydrogel matrices based on polyethylene glycol diacrylate (PEGDA), gum arabic, betaine, and sodium alginate for potential bioanalytical applications. Various physicochemical analyses were performed, including pre-polymerization emulsion stability (Multiscan), FT-IR spectroscopy, swelling behavior in physiological buffers, pH monitoring, contact angle measurements, and morphological assessment via SEM and optical microscopy. The results demonstrated that both alginate content and UV exposure time significantly influence the structural and functional properties of the hydrogels. The highest swelling ratio (2.32 g/g) was observed for the formulation containing 5% sodium alginate polymerized for 5 min (5SA_5), though this sample showed mechanical fragmentation during incubation. In contrast, the most balanced performance was achieved for the 10SA_15 formulation, which maintained structural integrity and exhibited a swelling ratio of 1.92 g/g after 9 days. The contact angle analysis revealed a surface hydrophilicity range from 50° to 100°, with the lowest angle (50°) recorded for 10SA_5, indicating high surface wettability. These findings confirm the suitability of such hydrogels for biomedical applications, particularly as absorbent, stable platforms for drug delivery or wound healing. Full article

(This article belongs to the Special Issue Functional Hydrogel for Biomedical Applications: Progress, Challenges, and Opportunities)

► Show Figures

Figure 1

16 pages, 3918 KiB

Open AccessArticle

Improvements in Wettability and Tribological Behavior of Zirconia Artificial Teeth Using Surface Micro-Textures

by Yayun Liu, Guangjie Wang, Fanshuo Jia, Xue Jiang, Ning Jiang, Chuanyang Wang and Zhouzhou Lin

Materials 2025, 18(13), 3117; https://doi.org/10.3390/ma18133117 - 1 Jul 2025

Abstract

Zirconia ceramics are promising materials for restoration and are widely used in the field of artificial teeth. However, wear resistance affects the longevity of artificial teeth. In this study, peacock tail feather micro-textures and groove micro-textures are prepared on the surfaces of zirconia [...] Read more.

Zirconia ceramics are promising materials for restoration and are widely used in the field of artificial teeth. However, wear resistance affects the longevity of artificial teeth. In this study, peacock tail feather micro-textures and groove micro-textures are prepared on the surfaces of zirconia ceramics via the laser ablation technique to improve their tribological properties. The effects of micro-textures on the surface wettability and tribological properties of zirconia ceramics are studied. The micro-textures improve the surface wettability and tribological properties of zirconia ceramics. The average coefficient of friction of peacock tail feather micro-textured samples decreases by 53% compared to that of the samples without micro-textures. Different operating conditions affect the friction properties of zirconia ceramics. The samples have the best friction performance when the rotational speed, load, and acid/alkaline environment are 200 r/min, 15 N, and weakly alkaline, respectively. Furthermore, the mechanism by which surface micro-textures reduce frictional wear is as follows: the textured grooves store debris, and the bottom edge of the textured groove acts as a cutting tool to cut debris, preventing debris from scratching the surface. The micro-textures store lubricant and form a liquid film on the ceramic surface to reduce wear. Full article

(This article belongs to the Section Biomaterials)

► Show Figures

Figure 1

4 pages, 160 KiB

Open AccessEditorial

Ceramic Dental Restorations—From Materials Sciences to Applications

by Han Chao Chang and Satoshi Yamaguchi

Materials 2025, 18(13), 3116; https://doi.org/10.3390/ma18133116 - 1 Jul 2025

Abstract

In response to the growing demand from patients for enhanced oral aesthetics, as well as improved chewing and occlusion, coupled with advancements in CAD/CAM technology, a variety of dental ceramic materials have been developed over the past two decades to serve as alternatives [...] Read more.

In response to the growing demand from patients for enhanced oral aesthetics, as well as improved chewing and occlusion, coupled with advancements in CAD/CAM technology, a variety of dental ceramic materials have been developed over the past two decades to serve as alternatives to traditional alloys and pure metals [...] Full article

(This article belongs to the Special Issue Ceramic Dental Restorations: From Materials Sciences to Applications)

25 pages, 26506 KiB

Open AccessArticle

Adhesion Properties Between Rubber Asphalt Mastic and Aggregate: Verification from Surface Free Energy Theory and Molecular Dynamics

by Huajia Yin, Shenyang Cao, Fucheng Guo and Xu Wu

Materials 2025, 18(13), 3115; https://doi.org/10.3390/ma18133115 - 1 Jul 2025

Abstract

The adhesive properties between rubber asphalt mastic and aggregate are crucial to rubber asphalt mixtures’ stability and moisture resistance. This paper employs surface free energy (SFE) theory and molecular dynamics (MD) to examine the bond strength and debonding behavior at the rubber asphalt [...] Read more.

The adhesive properties between rubber asphalt mastic and aggregate are crucial to rubber asphalt mixtures’ stability and moisture resistance. This paper employs surface free energy (SFE) theory and molecular dynamics (MD) to examine the bond strength and debonding behavior at the rubber asphalt mastic–aggregate interface. The results showed that the dispersion fraction of RC1.0 was 7.12 mJ/m² higher than that of RA, and the limestone mineral powder improved the adhesion properties of rubberized asphalt to aggregate and the anti-stripping properties. SiO₂ and CaCO₃ are contributors to the van der Waals and electrostatic forces between rubber asphalt–aggregate, respectively. The high concentration of mineral powder has a bridging effect in rubber asphalt mastic–aggregate. CaCO₃ filler is more pronounced in enhancing the adhesion properties of rubber asphalt–aggregate. CaCO₃ mineral powder mainly improves the anti-debonding ability of rubber asphalt–aggregate by reducing the thickness of water film between rubber asphalt–aggregate. Full article

(This article belongs to the Collection Advanced Civil Engineering Materials: From Synthesis to Application)

► Show Figures

Figure 1

13 pages, 3345 KiB

Open AccessArticle

Grinding Deformation Behavior of a Lamellar γ-TiAl Alloy

by Jiale Qin, Mengxi Xu, Renci Liu, Yingying Shen, Zhiqiang Shan, Zuohai Zhu, Dong Liu, Yuyou Cui and Rui Yang

Materials 2025, 18(13), 3114; https://doi.org/10.3390/ma18133114 - 1 Jul 2025

Abstract

γ-TiAl alloys are susceptible to surface damage during grinding, deteriorating their mechanical properties during service. However, the underlying mechanism of surface microstructure deformation during grinding remains incompletely understood. This work systematically investigated the deformation behavior of surface lamellae in a Ti-45Al-2Nb-2Mn-1B (at.%) alloy [...] Read more.

γ-TiAl alloys are susceptible to surface damage during grinding, deteriorating their mechanical properties during service. However, the underlying mechanism of surface microstructure deformation during grinding remains incompletely understood. This work systematically investigated the deformation behavior of surface lamellae in a Ti-45Al-2Nb-2Mn-1B (at.%) alloy during grinding. The surface lamellae exhibit bending after grinding, with the degree of bending angle φ depending on the orientation of the lamellae. The bending angle φ depends on both the angle between the lamellae interface normal and the grinding direction, and the angle between the lamellae interface normal and the grinding surface normal. The lamellar deformation depth h is primarily governed by the grinding depth. The surface of the sample after grinding can be divided into three distinct layers: a surface fine-equiaxed grain zone, a bending lamella zone, and a near-surface deformation zone. The deformation in the bending lamella zone primarily results from slip bands and stacking faults, whereas the near-surface deformation zone contains extensive dislocation tangles. The results offer fundamental insights into the deformation mechanism of surface lamellar colonies during grinding and provide theoretical guidance for the machining of γ-TiAl alloy components. Full article

(This article belongs to the Special Issue New Advances in High-Temperature Structural Materials)

► Show Figures

Figure 1

23 pages, 6671 KiB

Open AccessArticle

Hierarchical Microstructure–Mechanical Property Correlations in Superior Strength 5 wt% Cr Cold-Work Tool Steel Manufactured by Direct Energy Deposition

by Jung-Hyun Park, Young-Kyun Kim, Jin-Young Kim, Hyo-Yun Jung, Sung-Jin Park and Kee-Ahn Lee

Materials 2025, 18(13), 3113; https://doi.org/10.3390/ma18133113 - 1 Jul 2025

Abstract

The direct energy deposition (DED) metal additive manufacturing process enables rapid deposition and repair, providing an efficient approach to producing durable tool steel components. Here, 5 wt% Cr cold-work tool steel (Caldie) was developed by reducing carbon and chromium to suppress coarse carbide [...] Read more.

The direct energy deposition (DED) metal additive manufacturing process enables rapid deposition and repair, providing an efficient approach to producing durable tool steel components. Here, 5 wt% Cr cold-work tool steel (Caldie) was developed by reducing carbon and chromium to suppress coarse carbide formation and by increasing molybdenum and vanadium to enhance dimensional stability. In this study, Caldie tool steel was fabricated via DED for the first time, and the effects of post-heat treatment on its hierarchical microstructure and mechanical properties were investigated and compared with those of wrought (reference) material. The as-built sample exhibited a mixed microstructure comprising lath martensite, retained austenite, polygonal ferrite, and carbide networks, which transformed into full martensite with fine carbides after heat treatment (DED-HT). The tensile strength of the DED Caldie material increased from 1340 MPa to 1949 MPa after heat treatment, demonstrating superior strength compared to other heat-treated, DED-processed high-carbon tool steels. Compared to DED-HT, the wrought material exhibited finer martensite, a more uniform Bain group distribution, and finer carbides, resulting in higher strength. This study provides insights into the effects of heat treatment on the hierarchical microstructure and mechanical behavior of Caldie tool steel manufactured by DED. Full article

(This article belongs to the Section Manufacturing Processes and Systems)

► Show Figures

Figure 1

18 pages, 3845 KiB

Open AccessArticle

Electrospun Nanofibers of Polyvinylidene Fluoride Enriched with Active Antimicrobial Tannic Acid for the Improvement of the Shelf Life of Cherry Tomatoes

by Rajaram Rajamohan, Ajmal P. Muhammed, Chaitany Jayprakash Raorane, Subramaniyan Ramasundaram, Iruthayapandi Selestin Raja, Sivakumar Allur Subramanian, Seong Cheol Kim, Tae Hwan Oh and Seho Sun

Materials 2025, 18(13), 3112; https://doi.org/10.3390/ma18133112 - 1 Jul 2025

Abstract

Active packaging films have been an essential component in food material research to ensure the safe and efficient preservation of food, fruit, and vegetables. The shelf life of fruits and vegetables may likely be extended by covering them with high-performance nanofiber (NF) films. [...] Read more.

Active packaging films have been an essential component in food material research to ensure the safe and efficient preservation of food, fruit, and vegetables. The shelf life of fruits and vegetables may likely be extended by covering them with high-performance nanofiber (NF) films. The selection of materials for active packaging film has been a critical factor in preventing food materials from environmental contaminants (microbes) and extending the shelf life. This study aims to develop NF-based materials for cherry tomatoes to prevent fungal and bacterial damage. Bioactive NFs were produced through an electrospinning process using tannic acid (TA) within a polyvinylidene fluoride (PVDF) template. These NFs offer a sustainable alternative to synthetic packaging for food preservation. TA was incorporated into the PVDF matrix at varying concentrations (0.4 to 1.2%). Key parameters, including moisture content, thickness, opacity, water-contact angle, and thermal shrinkage, were assessed. The physicochemical results indicate that the TA NFs are suitable for further shelf-life performance evaluations. The antifungal and antibiofilm activity of the NFs was tested, showing that the TA_1.2 in the PVDF matrix was more effective than other concentrations. Shelf-life tests demonstrated that cherry tomatoes covered with TA_1.2 NFs showed no surface changes for up to 4 days. Importantly, the NFs were confirmed to be non-toxic to normal cells, as evidenced by tests on mouse 3T3-L1 fibroblast cells. In summary, we have developed bioactive NFs composed of TA in a PVDF matrix that enhance the shelf life of cherry tomatoes by preventing bacterial and fungal attacks on the fruit surfaces. Full article

(This article belongs to the Special Issue Multi-Scale Bionic Materials: Interfacial Design, Effective Fabrication and Functional Application)

► Show Figures

Figure 1

16 pages, 5893 KiB

Open AccessArticle

AZ31 Magnesium Alloy Roll-Forming Springback Prediction Considering Anisotropic and Asymmetric Properties

by Yu Yan, Hanzhong Xu, Haibo Wang and Jie Bao

Materials 2025, 18(13), 3111; https://doi.org/10.3390/ma18133111 - 1 Jul 2025

Abstract

Plastic forming in magnesium alloy sheet products is becoming a hot topic because of its potential in light-weight structural designs. Due to the special anisotropic and tension–compression asymmetrical properties of magnesium alloys, traditional modeling methods based on the von Mises yield criterion and [...] Read more.

Plastic forming in magnesium alloy sheet products is becoming a hot topic because of its potential in light-weight structural designs. Due to the special anisotropic and tension–compression asymmetrical properties of magnesium alloys, traditional modeling methods based on the von Mises yield criterion and using only uniaxial tensile properties for bending-dominated process simulations are not able to produce accurate predictions. In this study, two kinds of tensile tests (uniaxial and biaxial) and some compressive tests were performed along three material directions to obtain anisotropic and asymmetric properties, based on which the parameters of the Hill48 and Verma yield criteria were obtained. Then, the user subroutine VUMAT was developed, and the roll-forming process for magnesium alloys was simulated with the established anisotropic and asymmetric yield criteria. Finally, a roll-forming experiment on AZ31 magnesium alloy was performed. Compared with the experiments, it was found that roll-forming and springback predictions based on the Verma yield criterion had higher accuracy than those based on the von Mises and Hill48 yield criteria FEM models, which ignore anisotropy and asymmetry. This study provides an important FEM modeling idea that considers not only anisotropy but also asymmetry in the bending-dominated forming processes of magnesium alloys in which tension and compression exist simultaneously. Full article

(This article belongs to the Section Mechanics of Materials)

► Show Figures

Graphical abstract

20 pages, 2831 KiB

Open AccessArticle

Investigation of the Impact of Clinker Grinding Conditions on Energy Consumption and Ball Fineness Parameters Using Statistical and Machine Learning Approaches in a Bond Ball Mill

by Yahya Kaya, Veysel Kobya, Gulveren Tabansiz-Goc, Naz Mardani, Fatih Cavdur and Ali Mardani

Materials 2025, 18(13), 3110; https://doi.org/10.3390/ma18133110 - 1 Jul 2025

Abstract

This study explores the application of machine learning (ML) techniques—gradient boosting (GB), ridge regression (RR), and support vector regression (SVR)—for estimating the consumption of energy (CE) and Blaine fineness (BF) in cement clinker grinding. This study utilizes key clinker grinding parameters, such as [...] Read more.

This study explores the application of machine learning (ML) techniques—gradient boosting (GB), ridge regression (RR), and support vector regression (SVR)—for estimating the consumption of energy (CE) and Blaine fineness (BF) in cement clinker grinding. This study utilizes key clinker grinding parameters, such as maximum ball size, ball filling ratio, clinker mass, rotation speed, and number of revolutions, as input features. Through comprehensive preprocessing, feature selection methods (mutual info regression (MIR), lasso regression (LR), and sequential backward selection (SBS)) were employed to identify the most significant variables for predicting CE and BF. The performance of the models was optimized using a grid search for hyperparameter tuning and validated using k-fold cross-validation (k = 10). The results show that all ML methods effectively estimated the target parameters, with SVR demonstrating superior accuracy in both CE and BF predictions, as evidenced by its higher R² and lower error metrics (MAE, MAPE, and RMSE). This research highlights the potential of ML models in optimizing cement grinding processes, offering a novel approach to parameter estimation that can reduce experimental effort and enhance production efficiency. The findings underscore the advantages of SVR, making it the most reliable method for predicting energy consumption and Blaine fineness in clinker grinding. Full article

► Show Figures

Figure 1

16 pages, 2504 KiB

Open AccessArticle

Thermal Field and High-Temperature Performance of Epoxy Resin System Steel Bridge Deck Pavement

by Rui Mao, Xingyu Gu, Jiwang Jiang, Zhu Zhang and Kaiwen Lei

Materials 2025, 18(13), 3109; https://doi.org/10.3390/ma18133109 - 1 Jul 2025

Abstract

Epoxy Resin System (ERS) steel bridge pavement, which comprises a resin asphalt (RA) base layer and a modified asphalt wearing course, offers cost efficiency and rapid installation. However, the combined effects of traffic loads and environmental conditions pose significant challenges, requiring greater high-temperature [...] Read more.

Epoxy Resin System (ERS) steel bridge pavement, which comprises a resin asphalt (RA) base layer and a modified asphalt wearing course, offers cost efficiency and rapid installation. However, the combined effects of traffic loads and environmental conditions pose significant challenges, requiring greater high-temperature stability than conventional pavements. The thermal sensitivity of resin materials and the use of conventional asphalt mixtures may weaken deformation resistance under elevated temperature conditions. This study investigates the thermal field distribution and high-temperature performance of ERS pavements under extreme conditions and explores temperature reduction strategies. A three-dimensional thermal field model developed using finite element analysis software analyzes interactions between the steel box girder and pavement layers. Based on simulation results, wheel tracking and dynamic creep tests confirm the superior performance of the RA05 mixture, with dynamic stability reaching 23,318 cycles/mm at 70 °C and a 2.1-fold improvement in rutting resistance in Stone Mastic Asphalt (SMA)-13 + RA05 composites. Model-driven optimization identifies that enhancing internal airflow within the steel box girder is possible without compromising its structural integrity. The cooling effect is particularly significant when the internal airflow aligns with ambient wind speeds (open-girder configuration). Surface peak temperatures can be reduced by up to 20 °C and high-temperature durations can be shortened by 3–7 h. Full article

(This article belongs to the Special Issue Advanced Road Materials and Pavement: Design, Characterization, Structural and Mechanical Performance)

► Show Figures

Figure 1

Journal Description

Materials

Latest Articles

Journal Menu

Journal Browser

Highly Accessed Articles

Latest Books

E-Mail Alert

News

Topics

Conferences

Special Issues

Topical Collections

Further Information

Guidelines

MDPI Initiatives

Follow MDPI