Search Results (488)

Addressing the challenges of bulky, low-efficiency sound-insulation materials at low frequencies, this work proposes an acoustic metamaterial based on curve fractal channels. Each unit cell comprises a concentric circular-ring channel recursively iterated: as the fractal order increases, the channel path length grows exponentially, enabling outstanding sound-insulation performance within a deep-subwavelength thickness. Finite-element and transfer-matrix analyses show that increasing the fractal order from one to three raises the number of bandgaps from three to five and expands total stop-band coverage from 17% to over 40% within a deep-subwavelength thickness. Four-microphone impedance-tube measurements on the third-order sample validate a peak transmission loss of 75 dB at 495 Hz, in excellent agreement with simulations. Compared to conventional zigzag and Hilbert-maze designs, this curve fractal architecture delivers enhanced low-frequency broadband insulation, structural lightweighting, and ease of fabrication, making it a promising solution for noise control in machine rooms, ducting systems, and traffic environments. The method proposed in this paper can be applied to noise reduction of transmission parts for ceramic automation production. Full article

Stainless steel is recognized for its excellent durability and anti-corrosion properties, which are essential qualities across various industrial applications. The machining of stainless steel, particularly under a dry environment to attain sustainability, poses several challenges. The poor heat conductivity and high ductility of stainless steel results in poor heat distribution, accelerating tool wear and problematic chip formation. To mitigate these challenges, the implementation of surface texturing has been identified as a beneficial strategy. This study investigates the impact of wave-type texturing patterns, developed on the flank surface of tungsten carbide ceramic tool inserts, on the machinability of AISI 316 stainless steel under dry cutting conditions. In this investigation, chip morphology and surface roughness were used as key indicators of machinability. Analysis of Variance (ANOVA) was conducted for chip thickness, chip thickness ratio, and surface roughness, while Taguchi mono-objective optimization was applied to chip thickness. The ANOVA results showed that linear models accounted for 71.92%, 83.13%, and 82.86% of the variability in chip thickness, chip thickness ratio, and surface roughness, respectively, indicating a strong fit to the experimental data. Microscopic analysis confirmed a substantial reduction in chip thickness, with a minimum observed value of 457.64 µm. The corresponding average surface roughness Ra value 1.645 µm represented the best finish across all experimental runs, highlighting the relationship between thinner chips and enhanced surface quality. In conclusion, wave textures on the cutting tool’s flank face have the potential to facilitate the dry machining of AISI 316 stainless steel to obtain favorable machinability. Full article

Tribological processes in extreme environments pose serious material challenges, requiring coatings that resist both wear and corrosion. This review summarizes recent advances in protective coatings engineered for extreme environments such as high temperatures, chemically aggressive media, and high-pressure and abrasive domains, as well as cryogenic and space applications. A comprehensive overview of promising coating materials is provided, including ceramic-based coatings, metallic and alloy coatings, and polymer and composite systems, as well as nanostructured and multilayered architectures. These materials are deployed using advanced coating technologies such as thermal spraying (plasma spray, high-velocity oxygen fuel (HVOF), and cold spray), chemical and physical vapor deposition (CVD and PVD), electrochemical methods (electrodeposition), additive manufacturing, and in situ coating approaches. Key degradation mechanisms such as adhesive and abrasive wear, oxidation, hot corrosion, stress corrosion cracking, and tribocorrosion are examined with coating performance. The review also explores application-specific needs in aerospace, marine, energy, biomedical, and mining sectors operating in aggressive physiological environments. Emerging trends in the field are highlighted, including self-healing and smart coatings, environmentally friendly coating technologies, functionally graded and nanostructured coatings, and the integration of machine learning in coating design and optimization. Finally, the review addresses broader considerations such as scalability, cost-effectiveness, long-term durability, maintenance requirements, and environmental regulations. This comprehensive analysis aims to synthesize current knowledge while identifying future directions for innovation in protective coatings for extreme environments. Full article

The identification of structural damage types remains a key challenge in electromechanical impedance/admittance (EMI/EMA)-based structural health monitoring realm. This paper proposed a damage classification approach for concrete structures by using integrating discrete wavelet transform (DWT) decomposition of EMA signatures with supervised machine learning. In this approach, the EMA signals of arranged piezoelectric ceramic (PZT) patches were successively measured at initial undamaged and post-damaged states, and the signals were decomposed and processed using the DWT technique to derive indicators including the wavelet energy, the variance, the mean, and the entropy. Then these indicators, incorporated with traditional ones including root mean square deviation (RMSD), baseline-changeable RMSD named RMSDk, correlation coefficient (CC), and mean absolute percentage deviation (MAPD), were processed by a support vector machine (SVM) model, and finally damage type could be automatically classified and identified. To validate the approach, experiments on a full-scale reinforced concrete (RC) slab and application to a practical tunnel segment RC slab structure instrumented with multiple PZT patches were conducted to classify severe transverse cracking and minor crack/impact damages. Experimental and application results cogently demonstrated that the proposed DWT-based approach can precisely classify different types of damage on concrete structures with higher accuracy than traditional ones, highlighting the potential of the DWT-decomposed EMA signatures for damage characterization in concrete infrastructure. Full article

High safety gel polymer electrolyte (GPE) is used in lithium metal solid state batteries, which has the advantages of high energy density, wide temperature range, high safety, and is considered as a subversive new generation battery technology. However, solid-state lithium batteries with multiple layers and large capacity currently have poor cycle life and a large gap between the actual output cycle capacity retention rate and the theoretical level. In this paper, polyvinylidene fluoride-hexafluoropropylene (PVDF-HFP)/polyacrylonitrile (PAN)—lithium perchlorate (LiClO₄)—lithium lanthanum zirconium tantalate (LLZTO) gel polymer electrolytes was prepared by UV curing process using a UV curing machine at a speed of 0.01 m/min for 10 s, with the temperature controlled at 30 °C and wavelength 365 nm. In order to study the performance and failure mechanism of multilayer solid state batteries, single and three layers of solid state batteries with ceramic/polymer composite gel electrolyte were assembled. The results show that the rate and cycle performance of single-layer solid state battery with gel electrolyte are better than those of three-layer solid state battery. As the number of cycles increases, the interface impedance of both single-layer and three-layer electrolyte membrane solid-state batteries shows an increasing trend. Specifically, the three-layer battery impedance increased from 17 Ω to 42 Ω after 100 cycles, while the single-layer battery showed a smaller increase, from 2.2 Ω to 4.8 Ω, indicating better interfacial stability. After 100 cycles, the interface impedance of multi-layer solid-state batteries increases by 9.61 times that of single-layer batteries. After 100 cycles, the corresponding capacity retention rates were 48.9% and 15.6%, respectively. This work provides a new strategy for large capacity solid state batteries with gel electrolyte design. Full article

This research presents the development and management principles of mobile resonant electrical systems designed for high-voltage generation, intended for non-destructive diagnostics of insulation in high-power electrical equipment. The core of the system is a series inductive–capacitive (LC) circuit characterized by a high quality (Q) factor and operating at high frequencies, typically in the range of 40–50 kHz or higher. Practical implementations of the LC circuit with Q-factors exceeding 200 have been achieved using advanced materials and configurations. Specifically, ceramic capacitors with a capacitance of approximately 3.5 nF and Q-factors over 1000, in conjunction with custom-made coils possessing Q-factors above 280, have been employed. These coils are constructed using multi-core, insulated, and twisted copper wires of the Litzendraht type to minimize losses at high frequencies. Voltage amplification within the system is effectively controlled by adjusting the current frequency, thereby maximizing voltage across the load without increasing the system’s size or complexity. This frequency-tuning mechanism enables significant reductions in the weight and dimensional characteristics of the electrical system, facilitating the development of compact, mobile installations. These systems are particularly suitable for on-site testing and diagnostics of high-voltage insulation in power cables, large rotating machines such as turbogenerators, and other critical infrastructure components. Beyond insulation diagnostics, the proposed system architecture offers potential for broader applications, including the charging of capacitive energy storage units used in high-voltage pulse systems. Such applications extend to the synthesis of micro- and nanopowders with tailored properties and the electrohydropulse processing of materials and fluids. Overall, this research demonstrates a versatile, efficient, and portable solution for advanced electrical diagnostics and energy applications in the high-voltage domain. Full article

The intensive use of various sensors in industrial machines has the potential to indicate the real-time health status of critical equipment. This is achieved through the connectivity of their automation systems (PIMS and MES), enabling the optimization of the preventive maintenance interval, a reduction in corrective maintenance and safety-related failures, an increase in productivity and reliability and a reduction in maintenance costs. Through the use of the CRISP-DM data analysis methodology, the fault logs of ceramic plates applied in an iron ore filtration process are coupled with sensor readings of the process variables over the time of operation to create exponential survival models via two techniques: a multiple linear regression model with averaged data and a random forest regression machine learning model with individual instant data. The instantaneous reliability of ceramic plates is then used in the online prediction of the remaining useful life of the components. The model obtained from the instantaneous reading of 12 sensors led to the estimation of the remaining useful life for ceramic plates with up to 5600 h of use, allowing the adoption of a strategy of replacing these components by condition instead of replacing them by a fixed time, leading to increased process reliability and improved stock planning. The linear regression model for reliability prediction had an R² of 78.32%, whereas the random forest regression model had an R² of 63.7%. The final model for predicting the remaining useful life had an R² of 99.6%. Full article

This in vitro study aims to investigate the fracture properties of 3D-printed resin provisional material designed with different connector dimensions for two-unit fixed dental prostheses (FDPs). The master model was digitally designed following Shillingburg’s all-ceramic restoration tooth preparation guidelines and milled from aluminum. Four two-unit FDPs with different connector dimensions were designed: 2 × 3 mm, 3 × 3 mm, 3 × 4 mm, and 4 × 4 mm (width × length) (Groups A, B, C, and D, respectively; n = 10 for each group). These specimens were printed using 3D-printed resin material (Detax FREEPRINT^® temp). Forty specimens were subjected to a three-point test using a universal testing machine until fracture. The failure mode was examined under a stereomicroscope. The Kruskal–Wallis test at α = 0.05 revealed non-significant differences in fracture resistance load but significantly different elastic modulus, yield strength, and compressive strength (p = 0.061, p < 0.001, p < 0.001, and p < 0.001, respectively) among the different groups. The 2 × 3 mm connectors had higher means of modulus, yield strength, and compressive strength compared to the other groups. The study found that the maximum load causing fractures in 3D-printed provisional material connectors was consistent, regardless of connector cross-section variations. The 2 × 3 mm group performed best, while the 4 × 4 mm group performed worst. Full article

Aim: This in vitro study aimed to evaluate the adhesive performance of zirconia and lithium disilicate Maryland cantilever restorations on prepared and non-prepared anterior abutment teeth. While conventional clinical protocols involve abutment tooth preparation, no-preparation (no-prep) restorations have emerged as a viable, minimally invasive alternative. This study compared the adhesion fracture resistance (N) of zirconia restorations on non-prepared enamel surfaces with those on prepared surfaces exposing the dentin. Additionally, the zirconia restorations were compared with lithium disilicate Maryland cantilever restorations, a more common yet costly alternative. Materials and Methods: Forty extracted anterior teeth were allocated into four groups based on preparation type (prepared vs. non-prepared) and material (zirconia vs. lithium disilicate). Each group received cantilevered single-unit FPDs fabricated via CAD/CAM and adhesively cemented using Variolink^® Esthetic DC. Standardized loading was applied using a universal testing machine, and the fracture resistance was recorded. Results: The fracture resistance ranged from 190 to 447 N in the zirconia groups and from 219 to 412 N in the lithium disilicate groups. When comparing all the zirconia versus all the lithium disilicate ceramic restorations, regardless of tooth preparation, no statistically significant difference was found (p = 0.752). However, the non-prepared restorations exhibited significantly higher fracture resistance than their prepared counterparts (p = 0.004 for zirconia; p = 0.012 for lithium disilicate ceramic). All the failures were attributed to tooth fracture, except one zirconia restoration, with no debonding observed. Conclusions: Both zirconia and lithium disilicate Maryland cantilever restorations demonstrated reliable adhesive performance when bonded using appropriate surface conditioning and adhesive protocols. Interestingly, the non-prepared designs exhibited higher fracture resistance than the prepared abutments, highlighting their potential advantage in minimally invasive restorative dentistry. Zirconia Maryland bridges, in particular, represent a cost-effective and mechanically resilient option for anterior single-tooth replacement. Full article

Background and Objectives: Ensuring the optimal shear bond strength (SBS) is essential for the long-term success of prosthodontic restorations. Our in vitro study aimed to evaluate the SBS of three types of ceramics (feldspathic, alumina, and lithium disilicates) using three adhesive cements (Variolink Esthetic LC, Variolink Esthetic DC, and Maxcem Elite). Materials and Methods: Healthy molars were prepared, and ceramic blocks were cemented following universally accepted luting protocols. SBS tests were performed using a custom-made testing machine. A multiple linear regression model assessed the effects of ceramic type, surface treatment, and luting agent on SBS. Results: The regression model explained 61.3% of the variation in SBS values (R² = 0.613); the adjusted R² = 0.605 confirmed the model’s robustness. The global F-test was statistically significant (F = 78.96, p < 0.001). The total-etch technique (+4.47), the use of feldspathic ceramic, and 5% hydrofluoric acid treatment (+3.28) significantly affected SBS. Feldspathic ceramic and lithium disilicate showed superior performance against alumina. Light-cured and self-cured cement showed negative effects. Conclusions: Ceramic material and cement type have combined effects on SBS. Optimal results were obtained with the total-etch technique, feldspathic ceramic, 5% hydrofluoric acid treatment, and dual-cured cement. Full article

Choosing the appropriate cutting tool material is essential for enhancing machining processes because it directly affects product quality, surface finish, dimensional accuracy, tool longevity, and overall efficiency. Different materials are used for cutting tools, i.e., for cutting inserts. Due to their high hardness and high temperature resistance, ceramics cutting inserts allow for increased cutting speeds, resulting in shorter manufacturing times and reduced costs, despite being pricier than traditional cemented carbide and facing certain technical challenges due to their brittleness. Alumina-based ceramics dominate the market, accounting for about two-thirds of usage, followed by silicon nitride and zirconia. This paper provides a comprehensive overview of recent advances in alumina ceramic materials used as cutting inserts, focusing on research conducted in the last five years to optimize static and dynamic mechanical and thermal properties, wear resistance, density, etc. They ways in which the properties are altered through the incorporation of whiskers, nanoparticles, or nanotubes; the modification of the structure; the optimization of sintering parameters; and the application of advanced sintering techniques are demonstrated. The paper also addresses sustainability, environmental impact, and the management of critical raw materials associated with cutting inserts, which pertains to the future development of cutting insert materials. Full article

Electrocaloric materials, which exhibit adiabatic temperature change under an applied electric field, are promising for solid-state cooling technologies. In this study, the electrocaloric response of lead-free Ba_xCa_1−xZr_yTi_1−yO₃ (BCZT) ceramics was modeled to investigate the effects of composition, processing, and measurement conditions on performance. A high-accuracy XGBoost regression model (R² = 0.99, MAE = 0.02 °C) was developed using a dataset of 2188 literature-derived data points to predict and design the electrocaloric response of BCZT ceramics. The feature space incorporated compositional ratios, processing parameters, measurement settings, and atomic-level Magpie descriptors, along with Curie temperature to account for phase-transition behavior. Feature importance analysis revealed that electric field, measurement temperature, and proximity to the Curie point are the most critical factors influencing ΔT_EC. Bayesian optimization was applied to navigate the design space and identify performance maxima under unconstrained and realistic constraints, offering valuable insights into the nonlinear interactions governing electrocaloric performance. Under room temperature and moderate-field conditions (24 °C, 40 kV/cm), the optimized ΔT_EC achieved a value of 1.03 °C for Ba_0.85Ca_0.15Zr_0.40Ti_0.60, to be processed at 1090 °C for 3 h during calcination, 1300 °C for 2 h during sintering. By integrating experimental insight with machine learning and optimization, this study offers a refined, interpretable framework for accelerating the design of high-performance electrocaloric ceramics while reducing the experimental workload. Full article

Objective: This in vitro study aimed to evaluate the influence of cervical margin design—tangential versus chamfer—on the fracture resistance of monolithic crowns fabricated from lithium disilicate and zirconia ceramics. Materials and Methods: Forty extracted human molars were randomly assigned to two preparation types: chamfer and tangential. Each group was restored with CAD/CAM-fabricated crowns made from either zirconia (IPS e.max^® ZirCAD Prime) or lithium disilicate (IPS e.max^® CAD), resulting in four subgroups (n = 10). Standardized adhesive cementation protocols were applied. After 24 h storage in distilled water, the specimens underwent static load-to-failure testing using a ZwickRoell ProLine Z005 universal testing machine. Results: Zirconia crowns with chamfer margins exhibited the highest mean fracture resistance (2658 N), while lithium disilicate crowns with tangential margins showed the lowest (1862 N). Chamfer preparation significantly increased the fracture resistance of lithium disilicate crowns (p < 0.01), whereas margin design had no significant effect on zirconia. All restorations exceeded physiological masticatory forces, confirming their clinical viability. Conclusions: Cervical margin design significantly affected the fracture performance of lithium disilicate crowns but not zirconia. Chamfer preparations are recommended when using lithium disilicate to optimize mechanical strength. These findings underscore the importance of preparation geometry in guiding material selection for CAD/CAM ceramic restorations. Full article

Automation of the structural health monitoring process involves the use of successful methods for detecting defects and determining their critical characteristics. An efficient means of crack detection in composite materials is the ultrasonic method, but its application to determine critical crack parameters, such as depth in construction practice, is difficult or leads to large errors. This article focuses on machine learning methods usage to detect cracks in composite materials like brickwork. Ceramic bricks with various mechanical properties and with pre-grown cracks from 2 to 60 mm are considered. To understand the processes occurring during the ultrasonic pulse transmission, modeling was performed in the ANSYS environment. The brick is considered a porous medium weakened by a crack. Numerical modeling allows for the identification of the main features of the signal response and the determination of the amplitude-time range for different porosity and crack depth values. Using machine learning methods made it possible to solve two related problems. The first, binary classification, i.e., the presence or absence of a crack, is solved with 100% accuracy. The second is determining the crack depth. A neural network was built using an ensemble of decision trees. The accuracy of crack depth prediction is R² = 0.983, and the error in predicted values is within 8%. Full article

This study aimed to comparatively evaluate the effects of various surface treatment protocols on the shear bond strength (SBS) between heat-polymerized polymethyl methacrylate (PMMA) and different CAD/CAM framework materials, including cobalt–chromium (Co–Cr) alloys, ceramic particle-reinforced polyetheretherketone (PEEK), and glass fiber-reinforced composite resin (FRC). A total of 135 disc-shaped specimens were prepared from Co–Cr, PEEK, and FRC materials. Surface treatments specific to each material, including airborne-particle abrasion, sulfuric acid etching, laser irradiation, plasma activation, and primer application, were applied. PMMA cylinders were polymerized onto the treated surfaces, and all specimens were subjected to 30,000 thermal cycles. SBS values were measured using a universal testing machine, and the failure modes were classified. The normality of data distribution was assessed using the Kolmogorov–Smirnov test, and the homogeneity of variances was evaluated using Levene’s test. Group comparisons were performed using the Kruskal–Wallis test, and Dunn’s post hoc test with Bonferroni correction was applied in cases where significant differences were detected (α = 0.05). The highest SBS values (~27–28 MPa) were obtained in the Co–Cr group and in the PEEK groups treated with sulfuric acid and primer. In contrast, the PEEK group with additional laser treatment exhibited a lower SBS value. The untreated PEEK group showed significantly lower SBS (~3.9 MPa) compared to all other groups. The Trinia groups demonstrated intermediate SBS values (16.5–17.4 MPa), which exceeded the clinically acceptable threshold of 10 MPa. SEM observations revealed material- and protocol-specific surface responses; plasma-treated specimens maintained topographic integrity, whereas laser-induced surfaces showed localized degradation, particularly following dual-step protocols. Fracture mode analysis indicated that higher SBS values were associated with cohesive or mixed failures. SEM observations suggested that plasma treatment preserved surface morphology more effectively than laser treatment. This study highlights the importance of selecting material-specific surface treatments to optimize bonding between CAD/CAM frameworks and PMMA. Sulfuric acid and primer provided strong adhesion for PEEK, while the addition of laser or plasma offered no further benefit, making such steps potentially unnecessary. Trinia frameworks also showed acceptable performance with conventional treatments. These findings reinforce that simplified conditioning protocols may be clinically sufficient, and indicate that FRC materials like Trinia should be more fully considered for their broader clinical potential in modern CAD/CAM-based prosthetic planning. Full article