Short Processing Time Research Articles

Study on Purification Technology of Silicon Carbide Crystal Growth Powder.

Silicon carbide (SiC) is a wide-bandgap (WBG) semiconductor material, and its preparation process has strict requirements on the purity of raw materials. A self-developed medium-frequency induction heating furnace was used to carry out powder heat treatment and purification experiments on SiC powder to improve the purity of the powder. Samples with 3.5N purity were analyzed using XRD and GDMS characterization methods. It was found that under conditions of high-temperature (2200 °C) and long-time (50 h) processing, the impurity removal effect was quite good, but the powder loss was as high as 53.42%. The powder loss during the low-temperature (less than 2050 °C) and short-time process was less than 1.5%, but the purification effect was not substantial. After a prolonged processing time, the purification effect of low-temperature heat treatment conditions was improved, but the powder loss was also increased to 30%. In contrast, segmented purification processing at a low temperature in the early stage and a high temperature in the later stage achieved a good purification effect. On the premise of maintaining the utilization rate of raw materials, a 5N-purity SiC source was successfully prepared. The test results show that the contents of free Si, free C and free oxygen impurities were reduced to less than 0.01%, and the contents of Al, B, Fe, Mg, Na, Ti and other impurities were less than 1.15 ppm, which is close to the ppb level.

An improved U-Net model for concrete crack detection

Crack detection plays an important role in disease assessment of concrete buildings. However, factors such as complex background, irregular edge, and the real-time and accuracy requirement also make crack detection a challenging task. Aiming at the above challenges, an improved U-Net model for concrete crack detection is proposed, which has strong capability to extract the linear object, improving the performance in crack detection. The model is named Residual Linear Attention U-Net (RLAU-Net). There are three key measures in this paper. First, mirror padding the source image before convolution. Second, the multi-level features are obtained by aggregating the multi-scale features level by level. Third, strip pooling kernels are used to extract global contextual information, reducing information interference from the background. We tested the performance of RLAU-Net on our crack dataset, and the experimental results exhibited that it can improve the quantitative results of mean Intersection Over Union to 81.69%. In addition, F1 score has increased to, 78.21%, the Intersection Over Union of crack increased to 64.47%. We also compared the detect time-consuming of RLAU-Net and that of the original U-Net. Results demonstrate that the proposed model has a short processing time while maintaining a high detection accuracy for crack detection.

Transplantation of fragments from different planaria: A bioelectrical model for head regeneration

Head-tail planaria morphologies are influenced by the electric potential differences across the animal’s primary axis, as evidenced e.g. by voltage-sensitive dyes and functional experiments that create permanent lines of 2-headed but genetically wild-type animals. However, bioelectrical and biochemical models that make predictions on what would happen in the case of spatial chimeras made by tissue transplantation from different planaria (different species and head shapes) are lacking. Here, we use a bioelectrical model to qualitatively describe the effects of tissue transplantation on the shape of the regenerated head. To this end, we assume that the cells may have distinct sets of ion channels and ascribe the system outcome to the axial distributions of average cell potentials over morphologically relevant regions. Our rationale is that the distributions of signaling ions and molecules are spatially coupled with multicellular electric potentials. Thus, long-time downstream transcriptional events should be triggered by short-time bioelectrical processes. We show that relatively small differences between the ion channel characteristics of the cells could eventually give noticeable changes in the electric potential profiles and the expected morphological deviations, which suggests that small but timely bioelectrical actions may have significant morphological effects. Our approach is based on the observed relationships between bioelectrical regionalization and biochemical gradients in body-plan studies. Such models are relevant to regenerative, developmental, and cancer biology in which cells with distinct properties and morphogenetic target states confront each other in the same tissue.

Fast Support Vector Machine for Power Quality Disturbance Classification

The power quality disturbance (PQD) problem involves problems of voltage swell, voltage sag, power interruption, harmonics and complex events involving multiple PQD problems. The PQD problem attracted considerable attention from utilities, especially when renewable energy is getting a higher penetration. The PQD problem could downgrade the service quality, causing problems of malfunctions and instabilities. This paper proposed a simplified SVM technique to identify the PQD problem including the multiple PQD classification. With the simple structure proposed, the methodology could reduce a great deal of training data; requires much less memory space and saves computing time. An IEEE 14-bus power system was used to show the performance. Many tests were conducted, and the method was compared with an artificial neural network (ANN). Simulation results showed the shortened processing time and the effectiveness of the proposed approach.

Novel in-situ constructing approach for vertically aligned AlN skeleton and its thermal conductivity enhancement effect on epoxy

As one of the key components of electronic devices, thermal management materials (TMMs) with high thermal conductivity are essential to ensure their safety and long service life. For polymer-based TMMs, AlN is one of the preferred fillers, but it has some drawbacks such as high cost and easy hydrolysis. Herein, a controllable and continuously oriented three-dimensional AlN skeleton (3D-AlNNS) was in-situ transformed from a low-cost 3D Al-containing skeleton (3D-AlNS) by combining the ice-templating and nitriding reaction sintering. Subsequently, AlN/epoxy composites were obtained by a vacuum infiltration. The composite containing 39.69 vol% AlN had the highest thermal conductivity of 4.29 W m−1·K−1, which was 21.45 times higher than that of pure epoxy. The composite substrates showed excellent heat dissipation performance in practical applications due to their high thermal conductivity. The continuous directional alignment of AlN powders in the 3D skeleton and intersection of AlN whiskers between the skeleton walls produced in-situ contributed to the formation of effective multichannel heat transferring paths and improvement in thermal conductivity. This novel approach has the advantages of low-cost, short processing time, simple operation and repeatability, and provides a new idea for developing heat-conducting polymer composites, which can also be extended to the preparation of similar TMMs.

Recent Developments on Processes for Recovery of Rhodium Metal from Spent Catalysts

Rhodium (Rh) catalyst has played an indispensable role in many important industrial and technological applications due to its unique and valuable properties. Currently, Rh is considered as a strategic or critical metal as the scarce high-quality purity can only be supplemented by refining coarse ores with low content (2–10 ppm) and is far from meeting the fast-growing market demand. Nowadays, exploring new prospects has already become an urgent issue because of the gradual depletion of Rh resources, incidental pressure on environmental protection, and high market prices. Since waste catalyst materials, industrial equipment, and electronic instruments contain Rh with a higher concentration than that of natural minerals, recovering Rh from scrap not only offers an additional source to satisfy market demand but also reduces the risk of ore over-exploitation. Therefore, the recovery of Rh-based catalysts from scrap is of great significance. This review provides an overview of the Rh metal recovery from spent catalysts. The characteristics, advantages and disadvantages of several current recovery processes, including pyrometallurgy, hydrometallurgy, and biosorption technology, are presented and compared. Among them, the hydrometallurgical process is commonly used for Rh recovery from auto catalysts due to its technological simplicity, low cost, and short processing time, but the overall recovery rate is low due to its high remnant Rh within the insoluble residue and the unstable leaching. In contrast, higher Rh recovery and less effluent discharge can be ensured by a pyrometallurgical process which therefore is widely employed in industry to extract precious metals from spent catalysts. However, the related procedure is quite complex, leading to an expensive hardware investment, high energy consumption, long recovery cycles, and inevitable difficulties in controlling contamination in practice. Compared to conventional recovery methods, the biosorption process is considered to be a cost-effective biological route for Rh recovery owing to its intrinsic merits, e.g., low operation costs, small volume, and low amount of chemicals and biological sludge to be treated. Finally, we summarize the challenges and prospect of these three recovery processes in the hope that the community can gain more meaningful and comprehensive insights into Rh recovery.

A novel rapid microwave crystallization of photocatalysts for practical utility in the removal of phenol derivatives

A new concept of the microwave-assisted process was used for the crystallization of titania nanoparticles. The presented microwave crystallization can be indicated as truly environmentally friendly due to its energy efficiency and very short process time. In addition, it allows one to obtain pure materials without surface defects, which was confirmed by the EPR analysis. The physicochemical properties (such as crystallinity, morphology, and textural properties) of the synthesized TiO2 nanomaterials are strongly dependent on the microwave crystallization temperature. In this work, for the first time, the novel and convenient LED photoreactor was compared directly with the classic high-pressure mercury lamp. Photocatalytic studies showed higher activity in the oxidation of phenol and 4-chlorophenol under UV-LED light, compare to high-pressure Hg-lamp. The reason for improving photo-oxidation performance under LED light is indicated that each of the LEDs has the same parameters, so they can be considered as many single sources of UV radiation occurring throughout the entire cross-section of the reactor. This confirms that microwave-assisted crystallization of TiO2-photocatalysts and application of LEDs as light sources can be elements of a novel photocatalytic approach toward environmental protection. The presented results show that the simultaneous approach to the development of photocatalysts and novel light is the right route to further develop photocatalysis to enter this process into truly environmental protection.

Deep learning-based DOA estimation using CRNN for underwater acoustic arrays

In the marine environment, estimating the direction of arrival (DOA) is challenging because of the multipath signals and low signal-to-noise ratio (SNR). In this paper, we propose a convolutional recurrent neural network (CRNN)-based method for underwater DOA estimation using an acoustic array. The proposed CRNN takes the phase component of the short-time Fourier transform of the array signals as the input feature. The convolutional part of the CRNN extracts high-level features, while the recurrent component captures the temporal dependencies of the features. Moreover, we introduce a residual connection to further improve the performance of DOA estimation. We train the CRNN with multipath signals generated by the BELLHOP model and a uniform line array. Experimental results show that the proposed CRNN yields high-accuracy DOA estimation at different SNR levels, significantly outperforming existing methods. The proposed CRNN also exhibits a relatively short processing time for DOA estimation, extending its applicability.

Dry dechlorination of polychlorinated biphenyls in contaminated soil by using nano-sized composite of metallic Ca/CaO and its mechanism

Soil contamination by PCBs is still known as a serious problem across the world, and the development of new technologies or the improvement of existing ones (e.g. higher efficiency, shorter processing time, lower input energy) are more and more important. Moreover, understanding the chemistry of the entire process, from a mechanistic point of view, can accelerate the process of improvement. In these circumstances, we attempted a clarification of the highly efficient degradation of PCBs by nano-sized particle of metallic Ca in CaO (“nCa”) at 250 °C in dry solid state conditions. The reaction involved the hydrodechlorination, simple reduction, reductive coupling and hydroxylation processes. The detoxification efficiency reached over 99%. A tentative pathway and mechanism is proposed for explaining the final reactions products. Finally, the process was applied to real PCBs-contaminated soil, containing various amounts of PCBs, with a total success in completely eliminating the toxic polychlorinated compounds.

Research on Thermal Imaging Usage as a Method for Detecting Bacillus subtilis Bacteria in Mortadella

Meat and meat products are important sources of valuable proteins and other nutrients, but they are also a conducive environment for microorganisms’ growth and can easily corrupt. In order to ensure the safety and quality of these products throughout its entire shelf-life, reliable microbial contamination assessment techniques must be used. Despite their effectiveness, traditional diagnostics methods are expensive and time consuming. Therefore, new timesaving, reliable techniques are searched for. Infrared thermography could be a good alternative method in this area. As a quick technique to detect microorganisms, it can overcome the limitations of traditional microbiological food-quality assessment methods. It has numerous advantages, such as the possibility of taking immediate temperature measurements and short processing times for obtaining a thermal image, non-contact and non-destructive measurements, and, unlike other methods, real-time measurement monitoring. Real-time monitoring is particularly important for modern production systems. The purpose of this research study is to develop a methodology for microbiological quality control of mortadella inoculated with Bacillus subtilis ATCC 6633 bacteria using a thermal imaging camera with an uncooled microbolometric detector. It was found that the thermal imaging measurements used in this research study enabled the distinction of contaminated samples (min. 106 CFU/g) from sterile samples. The tests should only record the temperature of the samples during the first 25 s after previously performing activations at −18 °C ± 1 °C for 60 s. This is where differences between the samples are most pronounced. Estimating the trend line of the sample’s cooling process is advisable.

Facile route for synthesis of strontium hexaborate crystalline powders

AbstractIn this paper, a solid‐state reaction route was developed to synthesize SrB6O10 crystalline powders. Regarding the last preparation methods, a short process time of synthesis was achieved that has not reported before. The prepared sample was characterized using various methods, such as X‐ray diffraction, Raman spectroscopy, field emission scanning electron microscopy, transmission electron microscopy, and diffuse reflection spectroscopy. The obtained results proved that the prepared sample at temperature 840°C with 2.5 h duration consists of SrB6O10 crystalline powders with 4.96 eV bandgap.

Filling Process Optimization through Modifications in Machine Settings

In this paper, a mathematical model is developed for the modified settings of an automatic filling machine to minimize the filling time of orders for different volumes of dairy product and flavors. The linear programming model is solved using the Simplex method to find an optimal solution to the optimization problem. The results of the model are used for sequencing the processing of orders using one-dimensional rules with the aim of obtaining an optimal sequence for the most valued performance measure. The comparative analysis of the one-dimensional rules showed that Shortest Processing Time (SPT) is better than the other rules for minimization of the average time past due. Additionally, the results of the model for the new machine settings, when compared with previous similar studies, yielded encouraging results.

Engineering a monolithic 3D paper-based analytical device (μPAD) by stereolithography 3D printing and sequential digital masks for efficient 3D mixing and dopamine detection

Stereolithography 3D printing and digital masks in sequence are used herein to manufacture 3D µPAD in a monolithic layer of paper within 1 s. Multiple experiments were systematically conducted to further understand the fundamentals and limitation of this manufacturing process, and a novel 3D mixer and a fluorescent chemosensor assay used to determine dopamine concentration at high-alkaline pH conditions were successfully demonstrated. Experiment results showed: (1) the 3D mixer is superior than conventional 2D mixer regarding mixing performance and repeatability, (2) dopamine detection and pH indicator can be realized with fewer operation steps and shorter processing time, (3) a truly 3D µPAD, including multilayer microchannels within a monolithic paper substrate, can be created with fewer reagent loss and higher transportation efficiency, (4) a smallest microchannel, 100 µm wide microchannel, can be successfully created on µPAD. These results clearly proved that this proposed 3D µPAD is not only a novel format of µPAD, but it can also simplify the operation steps for an analytical assay while improving the mixing phenomenon via 3D mixer and using minimum sample volume. • Using SLA 3D printing and multiple digital masks to manufacture monolithic 3D µPAD. • 3D mixer is superior than 2D mixer regarding mixing performance and repeatability. • A truly 3D µPAD can result fewer reagent loss and higher transportation efficiency. • Dopamine detection and pH indicator can be realized with fewer operation steps. • A smallest microchannel, 100 µm wide microchannel, was successfully created.

Design of Fast Patrol Boat for Improving Resistance, Stability, and Seakeeping Performance

Indonesia is the largest archipelagic country and has the potential to become the world’s maritime axis. Two-thirds of Indonesia’s territory is ocean, with a total coastline of 54,716 km. Therefore, Indonesia must have solid systems and tools to overcome the various threats in the maritime sector. One of the technologies that can be developed to protect Indonesia’s naval territory is fast patrol boats. Indonesia requires efficient patrol boats that can optimally monitor the large Indonesian sea area and various potential threats in the maritime sector. Thus, research on the hydrodynamic criteria for the hull design of patrol boats is fundamental. In this study, we aimed to evaluate the design method based on hydrodynamic characteristics to obtain the primary dimensions and shape of the ship’s hull. We designed and analysed 11 ship models in terms of the following criteria: the resistance, stability, and seakeeping performance. The 11 models included five reference models of patrol boats with varying dimensions and block coefficients between 0.42 and 0.53, three ship models with the regression method with the exact dimensions and block coefficients between 0.45 and 0.46, and three ship models with the scale method with the exact measurements and block coefficients between 0.43 and 0.45. According to the analysis results, the regression method had better total hydrodynamic criteria and greater similarity to the reference vessel. With a shorter processing time, the regression method was more efficient than the scaling method and reference ship.

Validation of Viral Inactivation Protocols for Therapeutic Blood Products against Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-COV-2).

Therapeutic blood products including convalescent plasma/serum and immunoglobulins concentrated from convalescent plasma, such as intravenous immunoglobulins or hyperimmune globulins, and monoclonal antibodies are passive immunotherapy options for novel coronavirus disease 2019 (COVID-19). They have been shown to improve the clinical status and biological and radiological parameters in some groups of COVID-19 patients. However, blood products are still potential sources of virus transmission in recipients. The use of pathogen reduction technology (PRT) should increase the safety of the products. The purpose of this study was to determine the impact of solvent/detergents (S/D) procedures on SARS-COV-2 infectivity elimination in the plasma of donors but also on COVID-19 convalescent serum (CCS) capacity to neutralize SARS-COV-2 infectivity. In this investigation, S/D treatment for all experiments was performed at a shortened process time (30 min). We first evaluated the impact of S/D treatments (1% TnBP/1% TritonX-45 and 1% TnBP/1% TritonX-100) on the inactivation of SARS-COV-2 pseudoparticles (SARS-COV-2pp)-spiked human plasma followed by S/D agent removal using a Sep-Pak Plus C18 cartridge. Both treatments were able to completely inactivate SARS-COV-2pp infectivity to an undetectable level. Moreover, the neutralizing activity of CCS against SARS-COV-2pp was preserved after S/D treatments. Our data suggested that viral inactivation methods using such S/D treatments could be useful in the implementation of viral inactivation/elimination processes of therapeutic blood products against SARS-COV-2.

Study on CO2 based thermal plasma torch and its effective utilization for material processing in atmospheric pressure

Reuse of greenhouse gases is one of the promising approaches towards controlling global warming to some extent. As a part of that, an attempt has been made to utilize CO2 gas as one of the primary gases to form a thermal plasma jet for material processing. For that purpose, a unique direct current (DC) non-transferred arc thermal plasma torch was designed and its current-voltage characteristics and electro-thermal efficiency with different discharge currents and gas compositions were studied. The torch is made of rod type cathode and a nozzle type anode, which can produce a stable thermal plasma jet under different gas compositions. CH4 was used as a secondary mixing gas in an Ar-CO2 gas composition to produce a carbon-rich thermal plasma with high electro-thermal efficiency. The maximum electro-thermal efficiency of 73 % were reached while the torch operated at 100 A current with 6 slpm of CH4 flow along with 15 and 20 slpm of Ar and CO2 gas flow, respectively. Torch efficiency decreased to 12 % with increase in discharge current from 100 A to 200 A. Optical emission spectrum of the plasma jet was recorded at the exit of the torch nozzle to understand the emission characteristics of the plasma and estimate temperature and electron density. Temperature of the plasma increased from 13,400 to 17,800 K with respect to the discharge current. Thermodynamical studies were carried out for the given experimental conditions to understand the thermal decomposition of CO2-CH4 gas mixture and select the suitable condition for the material processing. Under the selective conditions, plasma torch was utilized for the spheroidization of tungsten metal powder and carburization of the AISI 316 L stainless-steel coupons in atmospheric pressure without using any shielding gases. Results showed that around 85 % of the metal powders were spheroidized perfectly at 15 kW input power. Plasma carburization results showed that the microhardness of the steel surface reached 605 HV with a short processing time of 3 min which was 4 times higher than the untreated steel surface. This work provides useful insight for the utilization of CO2 as primary plasma forming gas to generate thermal plasma for material processing.

Effects of sequential treatments using radio frequency energy and ultraviolet light on inactivation of Bacillus cereus spores and quality attributes of buckwheat

Buckwheat kernels were susceptible to be contaminated by heat-resistant spores. This study aimed to investigate effects of radio frequency (RF) heating, ultraviolet (UV) light and their combination treatment on the inactivation of B. cereus spores and quality attributes of buckwheat kernels. Results showed that Weibull model well fitted the inactivation curves of B. cereus spores under RF heating or UV light, and both of the two techniques had a tailing phenomenon (n < 1) in the decontamination process. But the inactivation levels of spores significantly increased by the combined treatments of RF and UV, regardless of the treatment sequence. Treatment by individual RF heating at 105 °C for 30 min or UV exposure at 5.00 mW/cm2 for 60 min resulted in >2.0 log CFU/g reduction of B. cereus spores. The similar inactivation effect could be achieved with shorter processing times by combined treatments (RF temperature-holding time + UV intensity-irradiation time: 85–10 + 3.50–10, 90–0 + 2.25–10, and 95–5 + 1.00–10). Besides, the colors, antioxidant compounds and antioxidant activities of buckwheat were not significantly deteriorated after these combined treatments, but the enzymatic activities were reduced, which was beneficial for long-term storage. Therefore, the proposed sequential treatment of RF heating and UV light in this study holds great potential to assure the food safety of grains.

Simultaneous minimisation of mean and variation of waiting times in a two-stage proportionate blocking flow shop

We consider the two-stage proportionate blocking flow shop scheduling problem with the objective of simultaneously minimising the mean and the variation of job waiting times. We show that the problem can be solved in time by evaluating at most two candidate optimal sequences. In some cases, the shortest processing time (SPT) sequence is optimal for any set of processing times. In all other cases, the optimal sequence is either the SPT sequence or a V-shaped sequence. We show that the optimal solution value for the corresponding no-wait flow shop scheduling problem is no worse than the optimal solution value for the blocking flow shop problem. We then analyse the blocking flow shop problem with the option of rejecting jobs from the sequence by paying their job-specific rejection penalties. We show that the problem with the job rejection option can be solved in time by dynamic programming (DP). Finally, we show that our results also apply to the corresponding flow shop scheduling problem with synchronous job transfers.

Tuning Corrosion Properties of the Bio-Inspired AZ-Series Mg Alloys Using Electrochemical Surface Treatment under Varying Experimental Regimes

Plasma electrolytic oxidation (PEO) is a preferable process applied to optimize the corrosion and wear properties of metals and their alloys, particularly magnesium (Mg) alloys used in highly demanded medical and aerospace applications. In this project, AZ series alloys (AZ31, AZ61, AZ91), which are the major commercial magnesium alloys, were coated using the PEO process under varying experimental conditions involving electrolyte with Si based ionic chemical networks together with hydroxyl and fluoride functionalities. Surface analysis was carried out using scanning electron microscopy (SEM). Data were further simulated and analyzed using imageJ software. SEM results showed that, increasing the concentration of Al as in AZ91 and AZ61, dendrites-dominated the microstructure at shorter processing times; a cratered-dendritic matrix was obtained at longer processing time. From the composition analysis, fluoride complex peaks were obtained for the higher Al-content alloy (AZ91), due to the localized intensive discharges made regular by the stable β-phases within the Mg matrix. Corrosion analysis was carried out using potentiodynamic polarization. The compact structure, higher growth rate, and stable chemical phases of MgF2 contributed to the highest hardness values ~1271.2 HV and corrosion potential ~−0.18 V for the AZ91 alloy.

Optimal Power Dispatch of DGs in Radial and Mesh AC Grids: A Hybrid Solution Methodology between the Salps Swarm Algorithm and Successive Approximation Power Flow Method

In this paper, we address the problem of the optimal power dispatch of Distributed Generators (DGs) in Alternating Current (AC) networks, better known as the Optimal Power Flow (OPF) problem. We used, as the objective function, the minimization of power losses (Ploss) associated with energy transport, which are subject to the set of constraints that compose AC networks in an environment of distributed generation. To validate the effectiveness of the proposed methodology in solving the OPF problem in any network topology, we employed one 10-node mesh test system and three radial text systems: 10, 33, and 69 nodes. In each test system, DGs were allowed to inject 20%, 40%, and 60% of the power supplied by the slack generator in the base case. To solve the OPF problem, we used a master–slave methodology that integrates the optimization method Salps Swarm Algorithm (SSA) and the load flow technique based on the Successive Approximation (SA) method. Moreover, for comparison purposes, we employed some of the algorithms reported in the specialized literature to solve the OPF problem (the continuous genetic algorithm, the particle swarm optimization algorithm, the black hole algorithm, the antlion optimization algorithm, and the Multi-Verse Optimizer algorithm), which were selected because of their excellent results in solving such problems. The results obtained by the proposed solution methodology demonstrate its superiority and convergence capacity in terms of minimization of Ploss in both radial and mesh systems. It provided the best reduction in minimum Ploss in short processing times and showed excellent repeatability in each test system and scenario under analysis.