Preparation of Ag3PO4/CoWO4 S-scheme heterojunction and study on sonocatalytic degradation of tetracycline

In this study, 0.6Ag₃PO₄/CoWO₄ composites were synthesized by hydrothermal method. The prepared materials were systematically characterized by techniques of scanning electron microscope (SEM), transmission electron microscope (TEM), X-ray diffractometer (XRD), X-ray photoelectron spectroscopy (XPS), N₂ adsorption/desorption, and UV–vis diffuse reflectance spectrum (DRS). Furthermore, the sonocatalytic degradation performance of 0.6Ag₃PO₄/CoWO₄ composites towards tetracycline (TC) was investigated under ultrasonic radiation. The results showed that, combined with potassium persulfate (K₂S₂O₈), the 0.6Ag₃PO₄/CoWO₄ composites achieved a high sonocatalytic degradation efficiency of 97.89 % within 10 min, which was much better than bare Ag₃PO₄ or CoWO₄. By measuring the electrochemical properties, it was proposed that the degradation mechanism of 0.6Ag₃PO₄/CoWO₄ is the formation of S-scheme heterojunction, which increases the separation efficiency of electron-hole pairs (e^--h⁺) and generates more electrons and holes, thereby enhancing the degradation activity. The scavenger experiments confirmed that hole (h⁺) was the primary active substance in degrading TC, and free radicals (OH) and superoxide anion radical (O₂^–) were auxiliary active substances. The results indicated that 0.6Ag₃PO₄/CoWO₄ nanocomposites could be used as an efficient and reliable sonocatalyst for wastewater treatment.     

Anisotropy Effects and Observational Data on the Constraints of Evolution Dark Energy Models

We investigate cosmological dark energy models where the accelerated expansion of the universe is driven by a field with an anisotropic universe. The constraints on the parameters are obtained by maximum likelihood analysis using observational of 194 Type Ia supernovae(SNIa) and the most recent joint light-curve analysis(JLA) sample. In particular we reconstruct the dark energy equation of state parameter w(z) and the deceleration parameter q(z). We find that the best fit dynamical w(z) obtained from the 194 SNIa dataset does not cross the phantom divide line w(z) =-1 and remains above and close to w(z)≈-0.92 line for the whole redshift range 0 ≤ z ≤ 1.75 showing no evidence for phantom behavior. By applying the anisotropy effect on the ΛCDM model, the joint analysis indicates that ?_(σ0)= 0.0163 ± 0.03,with 194 SNIa, ?_(σ0)=-0.0032 ± 0.032 with 238 the SiFTO sample of JLA and ?_(σ0)= 0.011 ± 0.0117 with 1048 the SALT2 sample of Pantheon at 1σ′confidence interval. The analysis shows that by considering the anisotropy, it leads to more best fit parameters in all models with JLA SNe datasets. Furthermore, we use two statistical tests such as the usual χ_(min)~2/dof and p-test to compare two dark energy models with ΛCDM model. Finally we show that the presence of anisotropy is confirmed in mentioned models via SNIa dataset.     

Improving efficiency for removal of ammoniacal nitrogen from wastewaters using hydrodynamic cavitation

The present study reports significant improvements in the removal of ammoniacal nitrogen from wastewater which is an important problem for many industries such as dyes and pigment, distilleries and fisheries. Pilot plant studies (capacity, 1 m³/h) on synthetic wastewater using 4-amino phenol as model nitrogen containing organic compound and two real industrial effluents of high ammoniacal nitrogen content were carried out using hydrodynamic cavitation. Two reactor geometries were evaluated for increased efficiency in removal-orifice and vortex diode. Effect of initial concentration (100–500 mg/L), effect of pressure drop (0.5–5 bar) and nature of cavitating device (linear and vortex flow for cavitation) were evaluated along with effect of salt content, effect of hydrogen peroxide addition and aeration. Initial concentration was found to have significant impact on the extent of removal: ~ 5 g/m³ removal for initial concentration of 100 mg/L and up to 12 g/m³ removal at high concentration of 500 mg/L. Interestingly, significant improvement of the order of magnitude (up to 8 times) in removal of ammoniacal nitrogen could be obtained by sparging air or oxygen in hydrodynamic cavitation and a very high removal of above 80% could be achieved. The removal of ammoniacal nitrogen by vortex diode was also found to be effective in the industrial wastewaters and results on two different effluent samples of distillery industry indicated up to 75% removal, though with longer time of treatment compared to that of synthetic wastewater. The developed methodology of hydrodynamic cavitation technology with aeration and vortex diode as a cavitating device was found to be highly effective for improving the efficiency of the conventional cavitation methods and hence can be highly useful in industrial wastewater treatment, specifically for the removal of ammoniacal nitrogen.     

An efficient edge based data structure for the compressible Reynolds-averaged Navier–Stokes equations on hybrid unstructured meshes

An efficient edge based data structure has been developed in order to implement an unstructured vertex based finite volume algorithm for the Reynolds-averaged Navier–Stokes equations on hybrid meshes. In the present approach, the data structure is tailored to meet the requirements of the vertex based algorithm by considering data access patterns and cache efficiency. The required data are packed and allocated in a way that they are close to each other in the physical memory. Therefore, the proposed data structure increases cache performance and improves computation time. As a result, the explicit flow solver indicates a significant speed up compared to other open-source solvers in terms of CPU time. A fully implicit version has also been implemented based on the PETSc library in order to improve the robustness of the algorithm. The resulting algebraic equations due to the compressible Navier–Stokes and the one equation Spalart–Allmaras turbulence equations are solved in a monolithic manner using the restricted additive Schwarz preconditioner combined with the FGMRES Krylov subspace algorithm. In order to further improve the computational accuracy, the multiscale metric based anisotropic mesh refinement library PyAMG is used for mesh adaptation. The numerical algorithm is validated for the classical benchmark problems such as the transonic turbulent flow around a supercritical RAE2822 airfoil and DLR-F6 wing-body-nacelle-pylon configuration. The efficiency of the data structure is demonstrated by achieving up to an order of magnitude speed up in CPU times.     

从废水到新能源:光催化燃料电池的优化与应用

随着经济的飞速发展,社会对能源的需求日益扩大,对工业废水的无害化处理也提出了更高的要求。光催化燃料电池 (photocatalytic fuel cell, PFC) 在燃料电池中引入半导体光催化材料作为电极,实现了有机污染物高效降解和同步对外产电的双重功能,在废水无害化与资源化利用方面具有潜在的应用价值。半导体光催化电极是PFC系统高效运行的核心组件,增强其可见光响应和光生载流子分离是提高PFC性能的关键策略。反应器结构设计和运行参数优化也有利于改善PFC性能。本文从PFC基本原理和应用入手,综述了PFC在环境污染物资源化处理中的研究进展,并详细阐述了提高PFC的污染控制性能和产电效率的优化手段,为进一步设计高效稳定的PFC系统并实现其在水污染控制和清洁能源生产中的应用提供理论指导。     

Qualitative and quantitative determination of Atractylodes rhizome using ultra‐performance liquid chromatography coupled with linear ion trap–Orbitrap mass spectrometry with data‐dependent processing

A quick and effective workflow based on ultra‐performance liquid chromatography coupled with electron spray ionization and LTQ‐Orbitrap mass spectrometry (UPLC‐LTQ‐Orbitrap MS) was established for compositional analysis and screening of the characteristic compounds of three species of Atractylodes rhizome for quality evaluation. This technique was employed to determine the seven main components in Atractylodes rhizome samples. Ultimately, 78 constituents were identified; of these, seven characteristic compounds were selected for species discrimination, comprising atractylodin (63), atractylenolide I (43), atractylenolide II (49), atractylenolide III (53), atractylon (69), methyl‐atractylenolide II (54) and (4E,6E,12E)‐tetradecadecatriene‐8,10‐diyne‐1,3‐diacetate (59). The seven main compounds, including six characteristic compounds, were simultaneously determined in 29 batches of Atractylodes rhizome samples. Thus, the method validation showed acceptable results. Quantitative analysis showed significantly different contents of the seven main components among the three species of Atractylodes rhizome, which indicates possible distinctions in the pharmacological effects. This established method can simultaneously provide qualitative and quantitative results for compositional characterization of Atractylodes rhizomes and for quality control.     

Enhancing signal-to-noise ratio and resolution in low-field NMR relaxation measurements using post-acquisition digital filters

The traditional way to enhance signal-to-noise ratio (SNR) of nuclear magnetic resonance (NMR) signals is to increase the number of scans. However, this procedure increases the measuring time that can be prohibitive for some applications. Therefore, we have tested the use of several post-acquisition digital filters to enhance SNR up to one order of magnitude in time domain NMR (TD-NMR) relaxation measurements. The procedures were studied using continuous wave free precession (CWFP-T₁) signals, acquired with very low flip angles that contain six times more noise than the Carr–Purcell–Meiboom–Gill (CPMG) signal of the same sample and experimental time. Linear (LI) and logarithmic (LO) data compression, low-pass infinity impulse response (LP), Savitzky–Golay (SG), and wavelet transform (WA) post-acquisition filters enhanced the SNR of the CWFP-T₁ signals by at least six times. The best filters were LO, SG, and WA that have high enhancement in SNR without significant distortions in the ILT relaxation distribution data. Therefore, it was demonstrated that these post-acquisition digital filters could be a useful way to denoise CWFP-T₁, as well as CPMG noisy signals, and consequently reducing the experimental time. It was also demonstrated that filtered CWFP-T₁ method has the potential to be a rapid and nondestructive method to measure fat content in beef and certainly in other meat samples.