Special Issue “Physics and Mechanics of New Materials and Their Applications 2021”

Material science, aimed at designing, fabricating, investigating, and using advanced materials and composites in different fields, is the one of the most rapidly developing directions in science, technologies, and techniques. Novel devices and improved technical solutions employing a broad spectrum of novel materials, at various scales, find numerous applications in modern industry, helping to address the complex issues of great dynamic and oscillating loads, high temperatures, and aggressive media, within the framework of extreme chemical, physical, and mechanical conditions. The particular behaviors of advanced materials are integral to various new research fields.

This Special Issue consists of eight papers, reporting promising results, presented at the 10th Anniversary International Conference on “Physics and Mechanics of New Materials and Their Applications” (PHENMA 2021–2022), which took place in Divnomorsk (Russia), 23–27 May 2022 (http://www.phenma2021.sfedu.ru/).

Cherpakov et al. [1] developed a computational and experimental approach to modeling the oscillations of a new axial-type piezoelectric generator (PEG) with a proof mass and an active base. A pair of cylindrical piezoelements, located along the generator axis, served as an active base. Plate-type piezoelectric elements, constructed in the form of two bimorphs on an elastic PEG base, used the potential energy of PEG bending vibrations. Energy was generated in the cylindrical piezoelectric elements due to the transfer of compressive forces to the piezoelectric element at the PEG base during excitation by structural vibrations. The finite-element results of the modal and harmonic analysis of vibrations are presented. A technique for the experimental analysis of the vibrations is described, with a laboratory test setup. Numerical and experimental results were obtained for the output characteristics of a piezoelectric generator at a low-frequency load. The maximum output power for each cylindrical piezoelectric element was 2138.9 μW, and for plate-type piezoelectric elements, it was 446.9 μW and 423.2 μW at a frequency of 39 Hz and electric load of 10 kΩ. Haldkar et al. [2] designed and studied an axial-type piezoelectric energy generator with different porosities for the piezoelectric ceramics based on 3D finite-element modeling. The porosity of the piezoelectric ceramic was varied from 0% to 80% through its thickness or along the length of the duralumin beam. The axial-type energy harvester consisted of bimorph (d₃₁) and cylindrical (d₃₃) piezoelectric elements. The effects of different porosities, the proof mass located in the duralumin base plate, and various applied accelerations at base harmonic excitation were studied to determine the output voltage and power generation. The maximum output voltage and power obtained were 2.25 V and 5.1 µW, respectively. The measured values of the output current were 2.53 µA and 1.74 µA in the cases of 0% and 80% porosity, respectively. Haldkar et al. [3] investigated a piezoelectric actuated micropump used for the extraction of a blood sample. A pentagonal microneedle, an integral part of the micropump, was used to extract the blood volume. The blood was then delivered to the biosensor, located in the pump chamber, for diagnosis. The purpose of such a low-powered device was to obtain a sufficient blood volume for diagnostic purposes at the biosensor, located within the pump chamber, with a minimum time of actuation, which should ultimately lead to less pain being caused. Finite-element simulations were performed on four quarter piezoelectric bimorph actuators (FQPBs) at 2.5 V. Modal and harmonic analysis were carried out with various load conditions for the FQPBs. The extended microneedle lengths inside the pump chamber showed improved flow characteristics. Tiwari et al. [4] designed a patient-specific temporomandibular joint (TMJ) implant and studied its behavior under different loading conditions compared with a natural intact TMJ. In some cases, TMJ injury results from accidents; to repair the TMJ, temporomandibular joint replacement or TJR surgery is required. In this study, CT-scan data of the skull and mandible region with a broken condylar head were used to investigate the biomechanical behavior of the intact mandible and customized TMJ prostheses in order to design a patient-specific total TMJ implant. The customized TMJ implant was simulated with loading conditions using the finite-element method, and then, the results were compared to those for the intact jaw-mandible for the combinations of two different biocompatible material models. It was shown that the natural TMJ had a higher deformation value compared to the patient-specific TMJ implant due to the lower mechanical strength of bone relative to the Ti-6Al-4V and Co-Cr alloy. It demonstrated that the designed custom TMJ implant was safe for the patient. Bogachev et al. [5] modelled bending vibrations of solid and annular round inhomogeneous prestressed plates within the framework of the Timoshenko hypotheses. New inverse problems of prestress identification in plates were studied based on the acoustic response subjected to a certain probing load. To solve direct problems in calculating oscillations and amplitude-frequency characteristics, a computational Galerkin-method-based scheme was developed. In order to address the inverse problems, a special projection approach based on constructed weak problem statements was used, which made it possible to determine the desired characteristics in the given classes of functions. For both solid and annular plates, the sensitivity of the amplitude-frequency characteristics was estimated. Their values were used as additional data in the inverse problems at the change in the prestress level. Series of computational tests were performed for reconstructing the plate’s prestresses at various levels and distribution patterns (decreasing, increasing, and sign-alternating laws). Yeh et al. [6] highlighted that the flow rate of exhaled gas affected the suspension structure of the MEMS gas sensor and the operating temperature of the gas sensor. Therefore, their study used the Bosch process and the atomic layer deposition process to prepare a room-temperature through-silicon via-structured TiO₂ gas sensor. The experimental results confirmed that the TiO₂ sensing film was a uniform p-type metal oxide semiconductor and covered the through-silicon via (TSV) structure. It was shown that, at room temperature (RT), the response of the sensor increased with an increase in the nitric oxide (NO) gas concentration. The sensor response was 16.5% on average, with an inaccuracy of <±0.5% for five cycles at a 4 ppm NO gas concentration. For the gas at 10 ppm, the response of the sensor to NO was 24.4%, but the sensor produced almost no response to other gases (CO, CO₂, SO₂, and H₂S). Therefore, the developed RT TiO₂ gas sensor with a TSV structure exhibited good stability, reversibility, and selectivity for NO gas. Lin et al. [7] proposed the Robust seasonal-trend decomposition algorithm for long time series (RobustSTL) and temporal convolutional network (TCN) model to forecast hourly power consumption. When using the RobustSTL, instead of the standard seasonal-trend decomposition method utilizing locally estimated scatterplot smoothing (STL), the time series data may be extracted despite containing dynamic patterns, various noise, and burstiness. The trend, seasonality, and remainder components obtained from the decomposition operation were used as input for the TCN model applying deep learning for forecasting. TCN employing dilated causal convolutions and residual blocks to extract the long-term data patterns outperformed recurrent networks in time-series forecasting studies. The study compared the proposed model and counterpart models. The results showed that the proposed model could grasp the rules of historical time-series data related to hourly power consumption, outperforming the counterpart schemes in terms of the mean absolute percentage error (MAPE), mean absolute error (MAE), and root mean square error (RMSE). Moreover, the proposed model obtained the best results for the F1-score values, representing the equilibrium of the precision and recall. Shen et al. [8] compared two candidate fuel oils (FOs) to evaluate a ship’s practical fuel consumption and the CO₂ emissions of a container ship’s 8000 twenty-foot equivalent unit during oceanographic navigation. Two types of FOs were studied: a 3.4% heavy fuel oil with desulfurization (HFOWD) and a 0.5% very-low-sulfur fuel oil (VLSFO). The results showed that the VLSFO increased the fuel consumption 8.4% more than the HFOWD. Moreover, the VLSFO blend of various chemicals further deteriorated and wore out the main engine of the ship. Adopting the VLSFO may lead to more CO₂ emissions. Therefore, when switching to low-sulfur fuels, the maritime industry should improve the related energy efficiency to reduce fuel consumption and CO₂ emissions.

This Special Issue has been closed, but the research in the field of advanced materials, composites, and their applications continues to be of great importance due to the rapid developments in technologies and industry.