The self-diffusion coefficients of anthraquinone in poly(methyl methacrylate) (PMMA) saturated with carbon dioxide were calculated by molecular dynamics simulations at 328.2 K and pressures of 13.1–20.2 MPa. The TraPPE potential model was adopted for anthraquinone and PMMA, and a single-site model was used for CO₂. Ten initial configurations were prepared under similar calculation conditions using the NTP ensemble to examine the dependence of the diffusion coefficient of anthraquinone on the initial configuration. The diffusion trajectories of anthraquinone were subsequently calculated using the NTV ensemble. The jumping motion of anthraquinone was found to depend on the initial configuration, and was noted to be related to the amount of CO₂ around anthraquinone, based on the analysis of the distribution functions of CO₂ and PMMA around anthraquinone. The diffusion coefficients of anthraquinone were calculated by averaging the mean square displacements obtained using the ten initial configurations. The calculated self-diffusion coefficients of anthraquinone were in good agreement with the experimental data.

The theoretical onset of the Marangoni convection instability occurring in a half-zone liquid bridge of the floating zone (FZ) growth of Si_xGe_1–x has been investigated by numerical simulations. A half-zone model of the liquid bridge between a cold (bottom plane) and a hot (top plane) disk is considered. The highest Si concentration is on the top of the liquid bridge. Therefore, the driving forces for thermal and solutal Marangoni flows are in opposite directions in this configuration. The nonlinear equilibria and periodic orbits are obtained using the Newton–Krylov method, and their stability is analyzed with global linear stability analysis. A flow bifurcation analysis is conducted. The results show that when the solutal Marangoni number, Ma_C, ≤360, the primary flow bifurcation is from 2D axisymmetric to 3D steady flow. When Ma_C>360, the 2D axisymmetric flow becomes weakly periodic 2D axisymmetric, and eventually becomes chaotic. The critical thermal Marangoni number is monotonically increasing as Ma_C increases, and the flow is 2D axisymmetric when the solutal Marangoni forceis dominant. The stability evaluation for various thermal Marangoni number values at Ma_C=893 reveals that the onset of transition is from steady to periodic. However, the reverse transition does not occur at the same Marangoni number value. The simulation results show that the hysteresis behavior of the flow field exhibits an approximately 1% difference between two critical thermal Marangoni numbers. The present study suggests that the control parameters of FZ crystal growth should be smaller than the calculated critical values to avoid any flow-induced disturbances.

Conventional seawater reverse osmosis (SWRO) membranes have been used to treat industrial wastewater with high-salinity and organic contamination. However, SWRO membranes present challenges in the treatment of wastewater containing high concentrations of organics. A new low-fouling, high-pressure reverse osmosis (HPRO) membrane minimizes the adsorption of organic contaminants on the membrane surface, thereby restraining the fouling rate. This study compares HPRO and SWRO membranes by measuring their surface zeta potential and contact angle. The results showed that the HPRO membrane has a neutrally charged surface and a smaller water contact angle than the SWRO membrane. A membrane fouling test was used to measure the adsorption of bovine serum albumin (BSA) on the membrane surface. The test results indicated lower adsorption on the HPRO membrane than on the SWRO membrane surface. Finally, a comparison test between the two membranes was performed at a tannery wastewater plant. The HPRO membrane showed a 10% higher permeate flow and required a 50% lower maintenance cleaning frequency than the SWRO membrane during five months of operation.

In the present work, V₂O₅–WO₃/TiO₂ (VWT) catalysts were loaded onto a cordierite monolith through a novel one-pot method (OP) and a traditional incipient wetness impregnation method (IW). The catalysts were characterized and evaluated for NH₃-SCR before and after hydrothermal aging at 600°C for 36 h. An analysis of catalyst activity showed that the hydrothermal stability of OP was much higher than that of IW. N₂-sorption and X-ray diffraction (XRD) results suggested that there were no significant differences in the textural and structural properties of the two catalysts before and after aging, except for the formation of a small amount of WO₃ crystallites on the surface of aged OP. Separate NH₃-oxidation tests revealed that the NO selectivity of aged OP was significantly lower than that of aged IW, which resulted in a much higher NO_x conversion at high temperatures during NH₃-SCR. X-ray photoelectron spectroscopy (XPS), H₂-temperature programmed reduction (H₂-TPR), and Raman spectroscopy indicated that V and W species were more stable on the surface of OP during aging rather than IW, thus inhibiting the aggregation of surface-active species and leading to a better hydrothermal stability. Furthermore, OP exhibited better adhesion of the washcoat when compared to IW and this VWT catalyst exhibited a good tolerance for SO₂.

In semiconductor manufacturing processes, there are certain quality measurements cannot be easily obtained at a low cost. In such cases, virtual metrology (VM) is typically used to predict the relevant quality variables without increasing the number of physical measurements. Faced with large volumes of raw data, the traditional data-driven VM methods adopt data pre-processing for feature extraction before modeling with a predefined model. However, if the constructed model and the extracted features are not suitable, the identified VM model is generally not reliable. Moreover, almost no VM model has been proposed for multi-stage raw data. To improve the prediction performance of VM models, it is imperative that only suitable features are chosen and used in the modeling, especially for multi-stage raw process data. In this paper, we developed a convolutional neural network (CNN) based on the VM model for multi-stage raw semiconductor data. Owing to the intrinsic nature of CNN, the cascade-connected convolving filters and the regression part are trained together to provide appropriate features for the final prediction. The construction of CNN makes it possible to reasonably extract information at each stage separately when processing multi-stage data. The proposed method is validated using real semiconductor process data and found to be superior to conventional methods with significantly improved accuracy.

The use of microbial electrolysis cells (MECs), which are an extension of microbial fuel cells, is a promising technique for producing H₂ from renewable sources. In this study, we have developed an MEC containing a bicontinuous microemulsion in the cathode chamber, in which methylcyclohexane (MCH) is produced by the electrochemical hydrogenation of toluene. Owing to its relatively high H₂ storage capacity and ease of handling, MCH has attracted considerable attention as an organic chemical hydride, which enables the efficient transportation and storage of H₂. Despite the complicated chemical composition of the cathode solution, the faradaic efficiency of the toluene/MCH conversion in this study reached 49%. The balance between the toluene/MCH conversion and other competing reactions was found to be sensitive to the electrical potential and current density at the cathode. This new method for the direct production of organic chemical hydrides using microorganisms, which does not require the conventional stepwise process comprising H₂ production and hydrogenation of aromatic compounds, is potentially important for establishing a renewable-energy-based society.

The CO₂-assisted polymer compression method is a technique for plasticizing polymers with CO₂ and crimping polymer fibers. Porous materials with different densities and porosities can be produced by varying the number of laminated layers and the compression rate with the same fiber sheets as the raw material. Based on microsphere repulsion tester analysis, it was found that owing to the viscoelastic effect, the restitution coefficient increased with an increase in porosity. In addition, the type-D hardness decreased with an increase in porosity, which can be explained by the typical relationship between the porosity and Young’s modulus of porous materials.

We previously reported that by adding aqueous ammonia to the nitric acid extract of dephosphorization slag, a solid with relatively high concentrations of calcium and phosphorus could be obtained. However, the solid contains considerable amounts of manganese and iron, which hinder its application in production processes. In the present study, the obtained solid was again dissolved in nitric acid, and the resultant filtrate was passed through a cation exchange resin that removed most unwanted cations from the aqueous phosphoric acid solution. The recovery of phosphoric acid was confirmed via phosphorus nuclear magnetic resonance. Furthermore, when calcium nitrate was added to this aqueous solution, calcium hydroxyapatite was obtained, which was converted into calcium phosphate after calcination at 1073 K. Phosphoric acid, calcium hydroxyapatite, and calcium phosphate are raw materials used to produce various industrial products containing phosphorus, and our suggested process significantly improves the technology for recovering phosphorus-containing materials, which are mostly used as fertilizers.