Notes

Speckle depth statistics for chromatic scattering mass media below somewhat polarized illumination.
The γ-Fe2O3/ZIF-7 particles were highly hydrophobic and selectively and rapidly (0.96 at all pollutant concentrations suggested a pseudo-second-order sorption kinetics. The thermal stability and 15 cycles of use and reuse confirmed a robust γ-Fe2O3/ZIF-7 sorbent.The study of copper (Cu) recovery is crucial for the entire recovery process of waste printed circuit boards (WPCBs), and Cu can be leached efficiently via a sulfuric acid-hydrogen peroxide (H2SO4-H2O2) system. To achieve high Cu recovery, it is important to evaluate the parameters of the leaching process and understand the Cu leaching kinetics. Applying statistical and mathematical techniques to the leaching process will further benefit the optimization of the Cu leaching parameters. Moreover, the leaching kinetics of Cu in the H2SO4-H2O2 solution is yet to be fully understood. Hence, in the present work, process parameters, such as temperature, H2SO4 and H2O2 concentrations, solid-liquid ratio, particle size, and stirring speed, were optimized statistically by the response surface methodology (RSM). The results showed that the leaching kinetics conformed to the Avrami model. The maximum Cu leaching efficiency was 99.47%, and it was obtained based on the following optimal conditions 30.98 °C, 2.6 mol/L H2SO4, 1.87 mol/L H2O2, a solid-liquid ratio of 0.05 g/mL, 135 mesh, and 378 rpm. RSM was used for the optimization of the process parameters, and the leaching kinetics in this system was clarified. This study provides an important pathway for the investigation of other metal recoveries from WPCBs.Surfactants such as sodium dodecyl sulfate (SDS) are used to improve the dispersity of carbon nanotubes (CNTs) in aqueous solutions. The surfactant concentration in CNT solutions is a critical factor in the dielectrophoretic (DEP) manipulation of CNTs. A high surfactant concentration causes a rapid increase in the solution conductivity, while a low concentration results in undesirably large CNT bundles within the solution. The increase in the solution conductivity causes drag velocity that obstructs the CNT manipulation process due to the electrothermal forces induced by the electric field. The presence of large CNT bundles is undesirable since they degrade the device performance. In this work, mathematical modeling and experimental work were used to optimize the concentration of the SDS surfactant in multiwalled carbon nanotube (MWCNT) solutions. The solutions were characterized using dynamic light scattering (DLS) and ultraviolet-visible spectroscopy (UV-Vis) analysis. We found that the optimum SDS concentration in MWCNT solutions for the successful DEP manipulation of MWCNTs was between 0.1 and 0.01 wt %. A novel DEP configuration was then used to assemble MWCNTs across transparent electrodes. The configuration was based on ceiling deposition, where the electrodes were on top of a droplet. The newly proposed configuration reduced the drag velocity and prevented the assembly of large MWCNT bundles. MWCNTs were successfully assembled and aligned across interdigitated electrodes (IDEs). The assembly of MWCNTs from aqueous solutions across transparent electrodes has potential use in future transparent electronics and sensor devices.In recent years, a variety of new antibody formats have been developed. One of these formats allows the binding of one type of antibody to two different epitopes. buy Imidazole ketone erastin This can for example be achieved by introduction of the "knob-into-hole" format and a combined CrossMab approach. Due to their complexity, these bispecific antibodies are expected to result in an enhanced variety of different degradation products. Reports on the stability of these molecules are still largely lacking. To address this, a panel of stress conditions, including elevated temperature, pH, oxidizing agents, and forced glycation via glucose incubation, to identify and functionally evaluate critical quality attributes in the complementary-determining and conserved regions of a bispecific antibody was applied in this study. The exertion of various stress conditions combined with an assessment by size exclusion chromatography, ion exchange chromatography, LC-MS/MS peptide mapping, and functional evaluation by cell-based assays was adequate to identify chemical modification sites and assess the stability and integrity, as well as the functionality of a bispecific antibody. Stress conditions induced size variants and post-translational modifications, such as isomerization, deamidation, and oxidation, albeit to a modest extent. Of note, all the observed stress conditions largely maintained functionality. In summary, this study revealed the pronounced stability of IgG1 "knob-into-hole" bispecific CrossMab antibodies compared to already marketed antibody products.The existing research on coal gangue identification based on vibration usually assumes that coal gangue particles are ideal shapes. To understand the vibration response difference in hydraulic support caused by coal and gangue with real shapes, this paper uses a three-dimensional (3D) scanning technology to determine the real shape of coal particles. The process of coal and gangue impacting the tail beam at different angles was simulated in the LS-DYNA software package, and the effects of shape parameters, velocity, and coal strength on the difference in vibration signals caused by the two were analyzed statistically. The conclusions are as follows the vibrational response of the tail beam is concentrated mainly in the area between the ribs. The regularity of the velocity signal caused by gangue is better than the regularity of the velocity signal caused by coal, and the attenuation speed of the acceleration signal of gangue is slower than the attenuation speed of the acceleration signal of coal. The probability distributions of the velocity and acceleration responses were analyzed statistically, and the results show that the results from coal can be well fitted by a logarithmic normal function, and the standard deviations of velocity and acceleration are 0.05591 and 489.8, respectively. The gangue results are fitted by the gamma function and the Weibull function, and the standard deviations are 0.13531 and 737.9, respectively, showing that the fitting function has the potential to be used as the basis for coal gangue identification. The change in coal strength has little effect on the vibration response of the tail beam. With increasingly falling velocity, the vibration signal intensity of the tail beam increases, but the discrimination between coal and gangue weakens; therefore, measures should be taken to reduce the falling velocity of the rock mass. The research results of this paper can provide a reference for further study of coal gangue identification methods based on vibration.The prediction and evaluation of the biodegradability of molecules with computational methods are becoming increasingly important. Among the various methods, quantitative structure-activity relationship (QSAR) models have been demonstrated to predict the ready biodegradation of chemicals but have limited functionality owing to their complex implementation. In this study, we employ the graph convolutional network (GCN) method to overcome these issues. A biodegradability dataset from previous studies was trained to generate prediction models by (i) the QSAR models using the Mordred molecular descriptor calculator and MACCS molecular fingerprint and (ii) the GCN model using molecular graphs. The performance comparison of the methods confirms that the GCN model is more straightforward to implement and more stable; the specificity and sensitivity values are almost identical without specific descriptors or fingerprints. In addition, the performance of the models was further verified by randomly dividing the dataset into 100 different cases of training and test sets and by varying the test set ratio from 20 to 80%. The results of the current study clearly suggest the promise of the GCN model, which can be implemented straightforwardly and can replace conventional QSAR prediction models for various types and properties of molecules.Solid carbon nanoparticles are promising growth seeds to prepare single-walled carbon nanotubes (SWCNTs) at high temperatures, at which the SWCNT crystallinity should be improved significantly but conventional metal catalyst nanoparticles are unstable and suffer from aggregation. The noncatalytic nature of solid carbon nanoparticles, however, makes SWCNT growth inefficient, resulting in a limited growth yield. In this study, we develop a two-step chemical vapor deposition process to efficiently synthesize high-crystallinity SWCNTs at high temperatures from solid carbon nanoparticles obtained from nanodiamond. Based on thermodynamic considerations, the growth conditions are separately adjusted to supply different growth driving forces which are suitable for the formation of the initial cap structures and for the stationary elongation of SWCNTs. This process, called cap formation engineering, improves the nucleation density of the cap structures. We examined the changes in crystallinity, amorphous carbon deposition, diameter, and yield of SWCNTs with respect to the synthesis conditions. By controlling the initial growth conditions, high-quality SWCNTs are grown with improved yield. With the addition of water vapor as the etchant, deposition of amorphous carbon at high temperatures was further prevented. The results provide a pathway for precise growth control of SWCNTs from unconventional solid growth seeds.Dating mafic igneous rocks (silica-undersaturated) is difficult for the lack of suitable minerals such as zircons (ZrSiO4) commonly found in the sialic rocks such as granites. In this regard, baddeleyite (ZrO2) has been long recognized as the most important mineral to serve as a geochronometer for dating silica-undersaturated igneous rocks. However, separating baddeleyite is difficult due to its small grain size, typical tabular morphology, and low abundance in samples. The standard water-based separation technique requires kilogram-sized samples and usually has a very low recovery rate. In this study, a new separation method based on the different solubilities of the minerals within HF + HCl + HNO3 reagents was developed to achieve a high recovery of baddeleyite. With ∼19 g of diabase powder, the new method recovers 150-160 baddeleyite grains of 10-100 μm length and 4-50 μm width, an order of magnitude improvement over the water-based separation method, which typically recovers 11-12 similarly sized baddeleyite grains out of the ∼19 g sample. Subsequent secondary ion mass spectrometry U-Pb analyses demonstrate that the baddeleyite grains recovered by the new separation method keep the U-Pb system closed, indicating no Pb loss during acid treatment. Thus, this new method enables the most efficient baddeleyite recovery from gram-sized rocks and is anticipated to greatly contribute to the geochronological study of silica-unsaturated mafic rocks.Excessive CO2 emissions have resulted in global warming and are a serious threat to the life of people, various strategies have been implemented to cut carbon emissions, and one of them is the use of a gas separation membrane to capture CO2 effectively. In this experiment, the butadiene-bridged polymethylsiloxane (BBPMS)/ethyl cellulose (EC)/ionic liquid (IL) ternary composite membranes were prepared by EC as a substrate, BBPMS, and IL as additives in tetrahydrofuran under high-speed stirring and coated on the membrane. The membrane structure was characterized by a Fourier transform infrared spectrometer and scanning electron microscope, and the membrane properties were tested by a membrane tensile strength tester, thermal weight loss analyzer, and gas permeability meter. The results show that the surface of the ternary composite membrane is dense and flat with a uniform distribution, and the membrane formation, heat resistance, and mechanical properties are good. The permeability coefficient of the ternary composite membrane for CO2 reached 1806.
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