Influence of Sandblasting and Chemical Etching on Titanium 99.2–Dental Porcelain Bond Strength

The metal–ceramic interface requires proper surface preparation of both metal and ceramic substrates. This process is complicated by the differences in chemical bonds and physicochemical properties that characterise the two materials. However, adequate bond strength at the interface and phase composition of the titanium-bioceramics system is essential for the durability of dental implants and improving the substrates’ functional properties. In this paper, the authors present the results of a study determining the effect of mechanical and chemical surface treatment (sandblasting and etching) on the strength and quality of the titanium-low-fusing dental porcelain bond. To evaluate the strength of the metal-ceramic interface, the authors performed mechanical tests (three-point bending) according to EN ISO 9693 standard, microscopic observations (SEM-EDS), and Raman spectroscopy studies. The results showed that depending on the chemical etching medium used, different bond strength values and failure mechanisms of the metal-ceramic system were observed. The analyzed samples met the requirements of EN ISO 9693 for metal-ceramic systems and received strength values above 25 MPa. Higher joint strength was obtained for the samples after sandblasting and chemical etching compared to the samples subjected only to sandblasting.

Electrical Characterization of Thin PEDOT:PSS Films on Alumina and Thiol–Ene Substrates

Transparent polymer layers that heal minor scratches and maintain the optical properties of the devices for a long time are highly desirable in optoelectronics. This paper presents the results of the electrical characterization of thin PEDOT:PSS films on the novel, optically transparent thiol–ene substrates capable of healing scratches under room-temperature conditions. Electrical properties of the PEDOT:PSS films deposited on the conventional alumina ceramic substrates were also tested for comparative purposes. This study demonstrated that the substrate can have a significant effect on the electrical properties of PEDOT:PSS films, and the electrical resistance of the films on thiol–ene substrates is not as stable as on alumina ceramics. However, the changes in electrical resistance of the films on thiol–ene are small enough over a sufficiently wide range of operating temperatures and relative humidities and allow the application of such bilayers in various polymeric optoelectronic devices.

Optimising processing conditions for the functionalisation of photocatalytic glazes by ZnO nanoparticle deposition

ZnO nanospheres were synthesised and then deposited by both single- and double-fire fast processes on as-prepared ceramic substrates. The photocatalytic degradation of resazurin ink was tested under UV light. The single-fired samples did not show any evidence of photocatalytic activity because the nanoparticles melted during sintering at 1210°C. The double-fire ZnO spray-coating method successfully produced glazed materials with an active ZnO surface layer despite the high sintering temperature. The influence of experimental parameters, including the ZnO nanoparticle loading (0.03 to 1 mg/cm2) and firing temperature (650 to 800°C), were also investigated. Samples with a ZnO loading of 1 g/cm2 fired at 650°C showed the best photocatalytic activity. Increasing the temperature to 700 and 800°C led to the coalescence of ZnO nanoparticles, which reduced the photocatalytic activity.

Computer‐aided selective production of low-resistance NiP and NiCuP layers

Purpose This paper aims to present the possibility of computer-aided technology of chemical metallization for the production of electrodes and resistors based on Ni-P and Ni-Cu-P layers. Design/methodology/approach Based on the calculated parameters of the process, test structures were made on an alumina substrate using the selective metallization method. Dependences of the surface resistance on the metallization time were made. These dependencies take into account the comparison of the calculations with the performed experiment. Findings The author created a convenient and easy-to-use tool for calculating basic Ni-P and Ni-Cu-P layer parameters, namely, surface resistance and temperature coefficient of resistance (TCR) of test resistor, based on chemical metallization parameters. The values are calculated for a given level of surface resistance of Ni-P and Ni-Cu-P layer and defined required range of changes of TCR of test resistor. The calculations are possible for surface resistance values in the range of 0.4 Ohm/square ÷ 2.5 Ohm/square. As a result of the experiment, surface resistances were obtained that practically coincide with the calculations made with the use of the program created by the authors. The quality of the structures made is very good. Originality/value To the best of the authors’ knowledge, the paper presents a new, unpublished method of manufacturing electrodes (resistors) on silicon, Al2O3 and low temperature co-fired ceramic substrates based on the authors developed computer program.

Adhesion Phenomenon of Liquid Metals

In this chapter, we study an interfacial phenomenon between liquid metals and ceramic substrates. Therefore, investigation of these phenomena is of great importance not only in technological applications but also in fundamental understanding of physical behavior of the adhesion between two different materials as far as their electrical structures and physiochemical properties are concerned. Moreover, adhesion energy is interpreted thermodynamically by the interfacial interactions and the nature of bonding between liquid metal and ceramic material. The adhesion energy in metal/ceramic systems is determined by using an electro-acoustical model based on the propagation of the acoustic wave in the interface and strongly depends on the electric properties of combination.

Imbalance Modelling for Defect Detection in Ceramic Substrate by Using Convolutional Neural Network

The complexity of defect detection in a ceramic substrate causes interclass and intraclass imbalance problems. Identifying flaws in ceramic substrates has traditionally relied on aberrant material occurrences and characteristic quantities. However, defect substrates in ceramic are typically small and have a wide variety of defect distributions, thereby making defect detection more challenging and difficult. Thus, we propose a method for defect detection based on unsupervised learning and deep learning. First, the proposed method conducts K-means clustering for grouping instances according to their inherent complex characteristics. Second, the distribution of rarely occurring instances is balanced by using augmentation filters. Finally, a convolutional neural network is trained by using the balanced dataset. The effectiveness of the proposed method was validated by comparing the results with those of other methods. Experimental results show that the proposed method outperforms other methods.