Processes and mechanisms in remediation of aqueous chromium contamination by sulfidated nano-scale zerovalent iron (S-nZVI): experimental and computational investigations

Sulfidated nano-scale zerovalent iron (S-nZVI) has emerged as an advanced functional nanomaterial for efficiently remediating Cr(VI) contamination in aqueous environments. However, there is an insufficient understanding of its coherent process, removal pathway, and hydrochemical reactive mechanisms, presenting potential challenges for its future environmental applications. To address this gap, this study successfully synthesized S-nZVI through a chemical precipitation method and effectively applied it for the removal of Cr(VI). Additional characterization revealed that the removal of Cr(VI) followed a sequence of rapid chemisorption and intraparticle diffusion processes, concomitant with an increase in pH and a decrease in oxidation-reduction potential. The remediation mechanism encompassed a synergistic reduction of Cr(VI) to Cr(III) and simultaneous immobilization via Cr2FeO4 coprecipitation. The highest Cr(VI) removal capacity of 75 mg/g was attained during dynamic removal experiments in the sand column packed with S-nZVI. Further computational analysis, employing density functional theory calculations based on the experimental data, revealed the involvement of multiple molecular orbitals of Cr(VI) in the removal process. It also elucidated a step-by-step reduction pathway for Cr(VI) characterized by decreasing free energy. These findings provide evidence-based insights into Cr(VI) remediation using S-nZVI and can serve as valuable technical support for future environmental management of heavy metals

An integrated approach using ozone nanobubble and cyclodextrin inclusion complexation to enhance the removal of micropollutants

Ozone (O3) has been widely used for the elimination of recalcitrant micropollutants in aqueous environments, due to its strong oxidation ability. However, the utilization efficiency of O3 is constrained by its low solubility and short half-life during the treatment process. Herein, an integrated approach, using nanobubble technology and micro-environmental chemistry within cyclodextrin inclusion cavities, was studied in order to enhance the reactivity of ozonisation. Compared with traditional macrobubble aeration with O3 in water, nanobubble aeration achieved 1.7 times higher solubility of O3, and increased the mass transfer coefficient 4.7 times. Moreover, the addition of hydroxypropyl-β-cyclodextrin (HPβCD) further increased the stability of O3 through formation of an inclusion complex in its molecule-specific cavity. At a HPβCD:O3 molar ratio of 10:1, the lifespan of O3 reached 18 times longer than in a HPβCD-free O3 solution. Such approach accelerated the removal efficiency of the model micropollutant, 4-chlorophenol by 6.9 times, compared with conventional macrobubble ozonation. Examination of the HPβCD inclusion complex by UV-visible spectroscopy and Nuclear Magnetic Resonance analyses revealed that both O3 and 4-chlorophenol entered the HPβCD cavity, and Benesi-Hildebrand plots indicated a 1:1 stoichiometry of the host and guest compounds. Additionally, molecular docking simulations were conducted in order to confirm the formation of a ternary complex of HPβCD:4-chlorophenol:O3 and to determine the optimal inclusion mode. With these results, our study highlights the viability of the proposed integrated approach to enhance the ozonation of organic micropollutant

Enhanced bioelectroremediation of heavy metal contaminated groundwater through advancing a self-standing cathode

Hexavalent chromium (Cr(VI)) contamination in groundwater poses a substantial global challenge due to its high toxicity and extensive industrial applications. While the bioelectroremediation of Cr(VI) has attracted huge attention for its eco-friendly attributes, its practical application remains constrained by the hydrogeochemical conditions of groundwater (mainly pH), low electron transfer efficiency, limitations in electrocatalyst synthesis and electrode fabrication. In this study, we developed and investigated the use of N, S co-doped carbon nanofibers (CNFs) integrated on a graphite felt (GF) as a self-standing cathode (NS/CNF-GF) for the comprehensive reduction of Cr(VI) from real contaminated groundwater. The binder free cathode, prepared through electro-polymerization, was employed in a dual-chamber microbial fuel cell (MFC) for the treatment of Cr (VI)-laden real groundwater (40 mg/L) with a pH of 7.4. The electrochemical characterization of the prepared cathode revealed a distinct electroactive surface area, more wettability, facilitating enhanced adsorption and rapid electron transfer, resulting in a commendable Cr(VI) reduction rate of 0.83 mg/L/h. The MFC equipped with NS/CNF-GF demonstrated the lowest charge transfer resistance (Rct) and generated the highest power density (155 ± 0.3 mW/m2) compared to control systems. The favorable electrokinetics for modified cathode led to swift substrate consumption in the anode, releasing more electrons and protons, thereby accelerating Cr(VI) reduction to achieve the highest cathodic coulombic efficiency (C.Eca) of80 ± 1.3 %. A similar temporal trend observed between Cr(VI) removal efficiency, COD removal efficiency, and C.Eca, underscores the effective performance of the modified electrode. The reusability of the binder free cathode, exemption from catholyte preparation and the absence of pH regulation requirements highlighted the potential scalability and applicability of our findings on a larger scale

Integration, Launch, and First Results from IDEASSat/INSPIRESat-2 - A 3U CubeSat for Ionospheric Physics and Multi-National Capacity Building

The Ionospheric Dynamics and Attitude Subsystem Satellite (IDEASSat) is a 3U CubeSat carrying a Compact Ionospheric Probe (CIP) to detect ionospheric irregularities that can impact the usability and accuracy of global satellite navigation systems (GNSS), as well as satellite and terrestrial over the horizon communications. The spacecraft was developed by National Central University (NCU) in Taiwan, with additional development and operational support from partners in the International Satellite Program in Science and Education (INSPIRE) consortium. The spacecraft system needed to accommodate these mission objectives required three axis attitude control, dual band communications capable of supporting both tracking, telemetry and command (TT&C) and science data downlink, as well as flight software and ground systems capable of supporting the autonomous operation and short contact times inherent to a low Earth orbit mission developed on a limited university budget with funding agency-imposed constraints. As the first spacecraft developed at NCU, lessons learned during the development, integration, and operation of IDEASSat have proven to be crucial to the objective of developing a sustainable small satellite program. IDEASSat was launched successfully on January 24, 2021 aboard the SpaceX Falcon 9 Transporter 1 flight. and successfully began operations, demonstrating power, thermal, and structural margins, as well as validation of uplink and downlink communications functionality, and autonomous operation. A serious anomaly occurred after 22 days on orbit when communication with the spacecraft were abruptly lost. Communication was re-established after 1.5 months for sufficient time to downlink stored flight data, which allowed the cause of the blackout to be identified to a high level of confidence and precision. In this paper, we will report on experiences and anomalies encountered during the final flight model integration and delivery, commissioning, and operations. The agile support from the international amateur radio community and INSPIRE partners were extremely helpful in this process, especially during the initial commissioning phase following launch. It is hoped that the lessons learned reported here will be helpful for other university teams working to develop spaceflight capacity

An Experimental Method to Determine Rock Joint Stiffness under Constant Normal Load Conditions

Being physical mechanical parameters of joints, normal and shear stiffnesses are indispensable components of the numerical simulation and theoretical analysis of the behavior of joints. The objective of this work is to put forward an experimental method to determine joint stiffness under constant normal load (CNL) conditions. For this purpose, joint closure and direct shear tests under CNL conditions were conducted. Normal stiffness was determined by the ratio of normal stress increment and the corresponding normal displacement; the shear stiffness was calculated by the ratio of shear stress increment to the relative shear displacement. The average and instantaneous shear stiffness were distinguished. Experimental results showed that joint normal and shear stiffness are time and spatially varying parameters during direct shearing. With increasing normal stress, average shear stiffness, maximum instantaneous shear stiffness, and normal stiffness increases. Normal stiffness was about 26–28 times higher than the average shear stiffness under one normal stress level. Average shear stiffness was little influenced by shear velocity. Instantaneous shear stiffness shows the velocity-dependent behavior. Maximum instantaneous shear stiffness decreases rapidly with increasing shear rate. At lower shear velocity, maximum instantaneous shear stiffness is higher than normal stiffness; minimum instantaneous shear stiffness can be negative and the absolute value also decreases with faster shear velocity. These findings provide a reference for selecting the appropriate value of normal and shear stiffness for evaluation of the mechanical response of interface

Physical Clogging Characteristics and Water Quality Variations by Injecting Secondary Effluent into Porous Media: A Laboratory Column Study

Artificial recharge engineering has been widely used to solve the water resource crisis. However, there are still some safety hazards regarding reclaimed water quality. Here, chlorinated secondary effluent (SE) was injected into saturated porous media composed of high–purity quartz sands. The column experiment was conducted and modeled through a developed numerical model to predict the evolution of physical clogging. Some representative inorganic and organic indicators were measured both at different times and in different column sections. The study showed that the relative hydraulic conductivity (K/K0) decreased significantly by approximately 63.5% in 40 h. Especially for the first 3 cm of the column, the clogging was the most serious, with a decrease of approximately 85.8%. The porous media has a certain degree of filtration effect on turbidity, TOC, protein (Pr) and polysaccharide (PS) but has slight removal for other water quality indicators. Pr is the main component of the intercepted TOC, and its content is higher than that of Ps. Moreover, the inorganic and organic parameter variations along the column further verified that the organic floc particles were mainly retained in the first 3 cm. The 3D excitation/emission matrix (3DEEM) fluorescence spectra illustrated that the humic acids and fulvic acids were easy to release and that their injection may be harmful to groundwater quality. The study will lay a theoretical foundation and provide a guiding scheme for optimizing China’s reclaimed water reuse technology, ensuring the safety of reclaimed water quality

Analysis of energy consumption prediction for office buildings based on GA-BP and BP algorithm

To gain building energy consumption information during the design phase, the variance analysis to identify significant factors affecting energy consumption in China cold-region office buildings are carried out in this study. Key factors are selected, and prediction models for energy consumption in cold-region office buildings are established using BP and GA-BP algorithms. Three prediction model evaluation indexes are introduced to evaluate the prediction accuracy of the models. The results show that the maximum RMSE of the BP neural network prediction model is 0.498, and the maximum MAPE is 0.797%. Furthermore, the GA algorithm is used to optimize the BP neural network, resulting in a prediction model with a maximum RMSE of 0.359 and a maximum MAPE of 0.289%. The prediction accuracy of the GA-BP algorithm is better than that of the BP algorithm

Table of K-S test results for each evaluation data.

Table of K-S test results for each evaluation data.</p

D2 dimension residential land market index state spatial pattern.

D2 dimension residential land market index state spatial pattern.</p