High-Pressure Reverse Osmosis for Industrial Water Recycling: Permeate-Sided Pressure Drop as Performance-Limiting Factor

In the chemical industry large amounts of saline wastewater occur. Its disposal into rivers is a considerable burden to the ecosystem. To strive for a circular economy and enable a viable raw material recycling, energy-efficient concentration processes are requisite. High-pressure reverse osmosis meets this criterion, but its industrial application demands suitable membrane elements that withstand the exceptional operation conditions and provide sufficient performance. Hence, new requirements regarding the design of spiral-wound elements arise. To identify those, specific performance-limiting effects need a better understanding.     

Batch Tests for Optimisation of Solvent Composition and Process Flexibility of the CHALMEX FS-13 Process

ABSTRACT

Studies have been performed with the purpose of determining the optimal solvent composition of a Chalmers grouped actinide extraction (CHALMEX) solvent for the selective co-extraction of transuranic elements in a novel Grouped ActiNide EXtraction (GANEX) process. The solvent is composed of 6,6’-bis(5,5,8,8-tetramethyl-5,6,7,8-tetrahydro-benzo-[1,2,4]-triazin-3-yl)-[2,2’]-bipyridine (CyMe₄-BTBP) and tri-n-butyl phosphate (TBP) in phenyl trifluoromethyl sulfone (FS-13). The performance of the system has been shown to significantly depend on the ratios of the two extracting agents and the diluent to one another. Furthermore, the performance of the determined optimal solvent (10 mM CyMe₄-BTBP in 30% v/v TBP and 70% v/v FS-13) on various simulated PUREX raffinate solutions was tested. It was found that the solvent extracts all transuranic elements with high efficiency and good selectivity with regard to most other elements (fission products/activation products) present in the simulated PUREX raffinate solutions. Moreover, the solvent was found to extract a significant amount of acid. Palladium, silver, and cadmium were co-extracted along with the TRU-radionuclides, which has also been observed in other similar CHALMEX systems. The extraction of plutonium and uranium was preserved for all tested simulated PUREX raffinate solutions compared to experiments using trace amounts.     

基于纸喷雾离子化衍生质谱法快速检测PM2.5中的醌污染物

醌类化合物是PM2.5中的一类有害物质。本研究建立了纸喷雾离子化衍生质谱法快速测定PM2.5中的醌类污染物。通过衍生化反应在醌化合物中引入氨基，提高醌在纸喷雾中的离子化效率。随后对衍生化试剂种类、电压、喷雾溶剂种类等反应条件进行优化。在最优实验条件下，采用内标法定量分析1,4-苯醌、甲基对苯醌、1,4-萘醌和1,4-蒽醌，4种化合物均呈现较好的线性关系，其检出限分别为4.49、20.89、0.13、0.17 ng。利用该方法分析PM2.5实际样品中的萘醌和蒽醌，均获得了较好的定性和定量结果。     

Deconvoluting Energy Transport Mechanisms in Metal Halide Perovskites Using CsPbBr3 Nanowires as a Model System

Understanding energy transport in metal halide perovskites is essential to effectively guide further optimization of materials and device designs. However, difficulties to disentangle charge carrier diffusion, photon recycling, and photon transport have led to contradicting reports and uncertainty regarding which mechanism dominates. In this study, monocrystalline CsPbBr₃ nanowires serve as 1D model systems to help unravel the respective contribution of energy transport processes in metal-halide perovskites. Spatially, temporally, and spectrally resolved photoluminescence (PL) microscopy reveals characteristic signatures of each transport mechanism from which a robust model describing the PL signal accounting for carrier diffusion, photon propagation, and photon recycling is developed. For the investigated CsPbBr₃ nanowires, an ambipolar carrier mobility of μ = 35 cm² V⁻¹ s⁻¹ is determined, and is found that charge carrier diffusion dominates the energy transport process over photon recycling. Moreover, the general applicability of the developed model is demonstrated on different perovskite compounds by applying it to data provided in previous related reports, from which clarity is gained as to why conflicting reports exist. These findings, therefore, serve as a useful tool to assist future studies aimed at characterizing energy transport mechanisms in semiconductor nanowires using PL.     

One-step to prepare high-performance gas diffusion layer (GDL) with three different functional layers for proton exchange membrane fuel cells (PEMFCs)

Gas diffusion layer (GDL) is one of the most important components of fuel cells. In order to improve the fuel cell performance, GDL has developed from single layer to dual layers, and then to multiple layers. However, dual or multi layers in GDL are usually prepared by layer-by-layer methods, which cost too much time, energy, and resources. In this work, we successfully developed a facile one-step method to prepare a GDL with three functional layers by utilizing the different sedimentation rates and filtration rates of short carbon fiber (CF) and carbon nanotube (CNT). The treatment temperature for this GDL is much lower than that of traditional method. The thickness of the GDL can be effectively controlled from as thin as 50 μm to more than 200 μm by simply adjusting the content of CF. The GDL with high flexibility is suitable to develop high performance flexible electronics. The fuel cell with the GDL has the maximum power density 1021 mW cm^?2, which shows 19% improvement comparing to the conventional one. Therefore, this work breaks the traditional concept that GDL for fuel cells only can be prepared by very complex and high-cost procedure.     

Application of artificial neural network method to predict the breakage properties of PGE bearing chromite ore

In the present investigation, systematic grinding experiments were conducted in a laboratory ball mill to determine the breakage properties of low-grade PGE bearing chromite ore. The population balance modeling technique was used to study the breakage parameters such as primary breakage distribution (B_{i, j}) and the specific rates of breakage (S_i). The breakage and selection function values were determined for six feed sizes. The results stated that the breakage follows the first-order grinding kinetics for all the feed sizes. It was observed that the coarser feed sizes exhibit higher selection function values than the finer feed size. Further, an artificial neural network was used to predict breakage characteristics of low-grade PGE bearing chromite ore. The predicted results obtained from the neural network modeling were close to the experimental results with a correlation of determination R² = 0.99 for both product size and selection function.     

Investigation of fabrication of gas diffusion substrate for proton exchange membrane fuel cells

The gas diffusion substrate (GDS) is essential in the proton exchange membrane fuel cells. Its fabrication techniques affect the performance significantly and are worthy of investigation. In this study, a manufacturing process of the GDS is proposed to understand the formation process of GDS and promote its structure and performance more pertinently. Different states during the preparation process, raw carbon paper, pre-curing, curing, carbonation, and graphitization, are characterized and measured. Experimental and numerical methods are employed to determine the relationships between microstructure, transport, and mechanical performance variation with the fabricating processes. The results show that its porosity, average pore size, and effective diffusivity decrease first and increase after curing. These parameters after graphitization are lower than that of the carbon paper (CP). The electrical resistivity increases dramatically while pre-curing and decreases gradually after curing, carbonation, and graphitization, and it is much reduced after graphitization. Moreover, mechanical measurement results show that both the picks of tensile strength and flexural modulus occur after curing. Its tensile strength shows little change after graphitization compared to the initial paper's. In contrast, the flexural modulus is improved significantly.     

An infinite chain, {[Ni(tn)2]3[Fe(CN)4(μ-CN)2]2}n,a new catalyst for electrochemical-driven water splitting and photochemical-driven hydrogen evolution from water under blue light

A new catalyst for both water reduction and oxidation, based on an infinite chain, {[Ni(tn)₂]₃ [Fe(CN)₄ (μ-CN)₂]₂}_n, is formed by the reaction of NiCl₂, 1,3-propanediamine (tn) and K₃ [Fe(CN)₆]. {[Ni(tn)₂]₃ [Fe(CN)₄ (μ-CN)₂]₂}_n can electro-catalyze hydrogen evolution from a neutral aqueous buffer (pH 7.0) with a turnover frequency (TOF) of 1561 mol of hydrogen per mole of catalyst per hour (H₂/mol catalyst/h) at an overpotential (OP) of 837 mV {[Ni(tn)₂]₃ [Fe(CN)₄ (μ-CN)₂]₂}_n also can electro-catalyze O₂ production from water with a TOF of ～45 mol O₂ (mol cat)^?1s^?1 at an OP of 591 mV. Under blue light (λ = 469 nm), together with CdS nanorods (CdS NRs) as a photosensitizer, and ascorbic acid (H₂A) as a sacrificial electron donor, {[Ni(tn)₂]₃ [Fe(CN)₄ (μ-CN)₂]₂}_n can photo-catalyze hydrogen generation from an aqueous buffer (pH 4.0) with a turnover number (TON) of 11,450 mol H₂ per mole of catalyst (mol of H₂ (mol of cat)^?1) during 10 h irradiation. The average of apparent quantum yield (AQY) is as high as 40.96% during 10 h irradiation. Studies indicate that {[Ni(tn)₂]₃ [Fe(CN)₄ (μ-CN)₂]₂}_n exists in two forms: a cyano-bridged chain ({[Ni(tn)₂]₃ [Fe(CN)₄ (μ-CN)₂]₂}_n) in solid, and a salt ([Ni(tn)₂]₃ [Fe(CN)₆]₂) in aqueous media; Catalytic reaction occurs on the nickel center of [Ni(tn)₂]²⁺, and the introduction of [Fe(CN)₆]^3- can improve the catalytic efficiency of [Ni(tn)₂]²⁺ for H₂ or O₂ generation. We hope these findings can afford a new method for the design of catalysts for both water reduction and oxidation.     

Reusable Polyacrylonitrile-Sulfur Extractor of Heavy Metal Ions from Wastewater

Mercury, lead, and cadmium are among the most toxic and carcinogenic heavy metal ions (HMIs), posing serious threats to the sustainability of aquatic ecosystems and public health. There is an urgent need to remove these ions from water by a cheap but green process. Traditional methods have insufficient removal efficiency and reusability. Structurally robust, large surface-area adsorbents functionalized with high-selectivity affinity to HMIs are attractive filter materials. Here, an adsorbent prepared by vulcanization of polyacrylonitrile (PAN), a nitrogen-rich polymer, is reported, giving rise to PAN-S nanoparticles with cyclic π-conjugated backbone and electronic conductivity. PAN-S can be coated on ultra-robust melamine (ML) foam by simple dipping and drying. In agreement with hard/soft acid/base theory, N- and S-containing soft Lewis bases have strong binding to Hg²⁺, Pb²⁺, Cu²⁺, and Cd²⁺, with extraordinary capture efficiency and performance stability. Furthermore, the used filters, when collected and electrochemically biased in a recycling bath, can release the HMIs into the bath and electrodeposit on the counter-electrode as metallic Hg⁰, Pb⁰, Cu⁰, and Cd⁰, and the PAN-S@ML filter can then be reused at least 6 times as new. The electronically conductive PAN-S@ML filter can be fabricated cheaply and holds promise for scale-up applications.     

Modeling unaccounted-for gas among residential natural gas consumers using a comprehensive fuzzy cognitive map

Residential natural gas consumption depends on several factors. Available tools and methods to identify, categorize, and validate effective factors have some limitations, making consumption modeling more complex. Once a comprehensive model of effective consumption factors is developed for residential gas consumers, it can predict consumption. In addition, such a model could be used to verify the accuracy of measuring devices in order to reduce unaccounted for gas (UFG). The key factors affecting residential gas consumption were identified based on previous studies and their mutual effects were analyzed using a fuzzy cognitive mapping (FCM) method. The most significant factors and their effects on natural gas consumption in the residential sector were determined. In this study, for the first time, the expected consumption for each consumer was estimated using a consumption index. Generally, if the estimated consumption is significantly different from the amount recorded by the meter, it could suggest a potential source of UFG. The proposed method was applied to the data collected from the residential gas consumers of a small region in Iran (Dasht-e Arjan region, Fars province), and the results demonstrate the effectiveness of the proposed method.