Removal of citrate and hypophosphite binary components using Fenton,photo-Fenton and electro-Fenton processes

Both citrate and hypophosphite in aqueous solution were degraded by advanced oxidation processes （Fe^2＋/H2O2, UV/Fe^2＋/H2O2, and electrolysis/Fe^2＋/H2O2） in this study. Comparison of these techniques in oxidation efficiency was undertaken. It was found that Fenton process could not completely degrade citrate in the presence of hypophosphite since it caused a series inhibition. Therefore, UV light （photo-Fenton） or electron current （electro-Fenton） was applied to improve the degradation efficiency of the Fenton process. Results showed that both photo-Fenton and electro-Fenton processes could overcome the inhibition of hypophosphite, especially the electro-Fenton.

Personal Review:Progress and prospect in electro-Fenton process for wastewater treatment

As a novel advanced oxidation process (AOP), electro-Fenton process is powerful for degrading most organic compounds including toxic and non-biodegradable ones, and so has attracted great attention. This paper reviews this process in detail including the mechanism, electrolytic bath, electrode materials, aerations and operation parameters. The application of electro-Fenton method in wastewater treatment is evaluated and summarized. Future work in this field is suggested, and three main directions of new electrode exploitation, development of assisted technologies and mechanistic study should be strengthened.

电芬顿法(Electro-Fenton Process)处理废水

电芬顿法(electro-Fenton)是在Fenton试剂的基础上,在二价铁离子(Fe2+)和过氧化氢(H2O2)作用下,产生强氧化性的羟基自由基(●OH)并由其氧化难降解废水,其中Fe2+和H2O2分别由电化学过程产生。本文概述了电芬顿过程的基本原理,通过介绍国内外电芬顿的发展情况,详细介绍了电芬顿的影响因素,包括pH、阴极电极、催化剂及其他因素等,并展望了其未来的发展方向。

Kinetic degradation of amoxicillin by using the electro-Fenton process in the presence of a graphite rods from used batteries

This study reports the removal of amoxicillin(AMX)in aqueous media using the electroFenton process in the presence of a graphite cathode recovered from used batteries.The impact of the relevant parameters on the electroFenton process,namely the applied current intensity,the temperature,the initial concentration of AMX and the initial concentration of ferrous ions were investigated.The results showed that the optimal values were:I=600 mA,T=25℃,[AMX]_(0)=0.082 mmol·L^( 1) and[Fe^(2+)]=1 mmol·L^(1),leading to 95%degradation and 74%mineralization.The model parameters of AMX mineralization were determined using nonlinear methods,showing that it follows a pseudosecondorder kinetic.The Energy consumption(EC)calculated under the optimal values was found to be 0.79 kWhg 1,which was of the same order of magnitude of those reported in other findings;while it is noteworthy that the electrodes used in our study are of a lower cost.

Simultaneous utilization of electro-generated O_(2)and H_(2)for H_(2)O_(2)production:An upgrade of the Pd-catalytic electro-Fenton process for pollutants degradation

The Electro-Fenton(EF)process is one of the promising advanced oxidation processes(AOPs)for environmental remediation.The H_(2)O_(2) yield of EF process largely determines its performance on organic pollutants degradation.Conventional Pd-catalytic EF process generates H_(2)O_(2) via the combination reaction of anodic O_(2) and cathodic H;.However,the relatively expensive catalyst limits its application.Herein,a hybrid Pd/activated carbon(Pd/AC)-stainless steel mesh(SS)cathode(PACSS)was proposed,which enables more efficie nt H_(2)O_(2)generation.It utilizes AC,the support of Pd catalyst,as part of cathode for H_(2)O_(2) generation via 2-electron anodic O_(2) reduction,and SS serve as a current distributor.Moreover,H_(2)O_(2) could be catalytically decomposed upon AC to generate highly reactive·OH,which avoids the use of Fe;.Compared with conventional Pd catalyst,H_(2)O_(2) concentration obtained by PACSS cathode is248.2%higher,the O_(2)utilization efficiency was also increased from 3.2%to 10.8%.Within 50 min,26.3%,72.5%,and 94.0%H_(2)O_(2) was decomposed by Pd,AC,and Pd/AC.Fluorescence detection results implied that Pd/AC is effective upon H_(2)O_(2) activation for·OH generation.Finally,iron-free EF process enabled by PACSS cathode was examined to be effective for reactive blue 19(RB19)degradation.After continuous running for 10 cycles(500 min),the PACSS cathode was still stable for H_(2)O_(2)generation,H_(2)O_(2)activation,and RB19 degradation,showing its potential application for organic pollutants degradation without increase in the running cost.

Removal of 17β-Estradiol by Electro-Fenton Process

The Electrochemical advanced oxidation method “Electro-Fenton” has been applied to remove 17β-estradiol (17β)- estra-1,3,5(10)-triéne-3,17-diol) in aqueous-acetonitrile mixture. This endocrine disrupting is a steroid hormone, releases from humans, animals and residual pharmaceuticals into the environmental water and usually causes suspected undesirable effects in aquatic organisms. The degradation of this organic compound by Electro-Fenton process was showed using a carbon felt cathode and platinum anode. The evolution of the concentration during treatment was followed up by high performance liquid chromatography (HPLC). The influence of operating conditions on the degradation of 17β-estradiol by Electro-Fenton step, such as initial concentration and catalyst concentration, has been investi- gated and discussed. We showed that the degradation reaction obeyed apparent first-order reaction kinetics, with absolute rate constant determined as 5.12 × 109 M–1 s–1 by competitive kinetics method taking Benzoic Acid as reference compound. The results confirm the efficiency of the Electro-Fenton process to degrade organic pollutant in aqueous-acetonitrile mixture.

基于Arduino与Processing的心率检测计设计研究

随着社会经济的高速发展,人们的物质生活也有了极大的提高,但同时也伴随着各种疾病的到来,身体健康已经成为人们普遍关注的焦点,因此,心率检测仪、血压计、血糖仪等各种家用医疗监测仪器已经逐渐融入日常生活。心脏病是人们难以预防的突发致命疾病之一,本文介绍的是一款基于Arduino【是基于易用硬件和软件的原型开源平台,包由可编程的电路板(简称微控制器),以及集成开发环境(称为Arduino IDE)的现成软件组成】Processing(开源编程语言,包括编辑器、编译器、展示器)的简易心率检测计系统,其功能实用、操作简单,可以测量心率,当超出正常心率范围时及时预警,是一款便携的实时心率测试仪。

A new insight into LPSO phase transformation and mechanical properties uniformity of large-scale Mg-Gd-Y-Zn-Zr alloy prepared by multi-pass friction stir processing

A large-scale fine-grained Mg-Gd-Y-Zn-Zr alloy plate with high strength and ductility was successfully prepared by multi-pass friction stir processing(MFSP)technology in this work.The structure of grains and long period stacking ordered(LPSO)phase were characterized,and the mechanical properties uniformity was investigated.Moreover,a quantitative relationship between the microstructure and tensile yield strength was established.The results showed that the grains in the processed zone(PZ)and interfacial zone(IZ)were refined from 50μm to 3μm and 4μm,respectively,and numerous original LPSO phases were broken.In IZ,some block-shaped 18R LPSO phases were transformed into needle-like 14H LPSO phases due to stacking faults and the short-range diffusion of solute atoms.The severe shear deformation in the form of kinetic energy caused profuse stacking fault to be generated and move rapidly,greatly increasing the transformation rate of LPSO phase.After MFSP,the ultimate tensile strength,yield strength and elongation to failure of the large-scale plate were 367 MPa,305 MPa and 18.0% respectively.Grain refinement and LPSO phase strengthening were the major strengthening mechanisms for the MFSP sample.In particularly,the strength of IZ was comparable to that of PZ because the strength contribution of the 14H LPSO phase offsets the lack of grain refinement strengthening in IZ.This result opposes the widely accepted notion that IZ is a weak region in MFSP-prepared large-scale fine-grained plate.

Recent developments in selective laser processes for wearable devices

Recently,the increasing interest in wearable technology for personal healthcare and smart virtual/augmented reality applications has led to the development of facile fabrication methods.Lasers have long been used to develop original solutions to such challenging technological problems due to their remote,sterile,rapid,and site-selective processing of materials.In this review,recent developments in relevant laser processes are summarized under two separate categories.First,transformative approaches,such as for laser-induced graphene,are introduced.In addition to design optimization and the alteration of a native substrate,the latest advances under a transformative approach now enable more complex material compositions and multilayer device configurations through the simultaneous transformation of heterogeneous precursors,or the sequential addition of functional layers coupled with other electronic elements.In addition,the more conventional laser techniques,such as ablation,sintering,and synthesis,can still be used to enhance the functionality of an entire system through the expansion of applicable materials and the adoption of new mechanisms.Later,various wearable device components developed through the corresponding laser processes are discussed,with an emphasis on chemical/physical sensors and energy devices.In addition,special attention is given to applications that use multiple laser sources or processes,which lay the foundation for the all-laser fabrication of wearable devices.

Effect of bubble morphology and behavior on power consumption in non-Newtonian fluids’aeration process

Due to a prolonged operation time and low mass transfer efficiency, the primary challenge in the aeration process of non-Newtonian fluids is the high energy consumption, which is closely related to the form and rate of impeller, ventilation, rheological properties and bubble morphology in the reactor. In this perspective, through optimal computational fluid dynamics models and experiments, the relationship between power consumption, volumetric mass transfer rate(kLa) and initial bubble size(d0) was constructed to establish an efficient operation mode for the aeration process of non-Newtonian fluids. It was found that reducing the d0could significantly increase the oxygen mass transfer rate, resulting in an obvious decrease in the ventilation volume and impeller speed. When d0was regulated within 2-5 mm,an optimal kLa could be achieved, and 21% of power consumption could be saved, compared to the case of bubbles with a diameter of 10 mm.

Reinforcement Learning in Process Industries:Review and Perspective

This survey paper provides a review and perspective on intermediate and advanced reinforcement learning(RL)techniques in process industries. It offers a holistic approach by covering all levels of the process control hierarchy. The survey paper presents a comprehensive overview of RL algorithms,including fundamental concepts like Markov decision processes and different approaches to RL, such as value-based, policy-based, and actor-critic methods, while also discussing the relationship between classical control and RL. It further reviews the wide-ranging applications of RL in process industries, such as soft sensors, low-level control, high-level control, distributed process control, fault detection and fault tolerant control, optimization,planning, scheduling, and supply chain. The survey paper discusses the limitations and advantages, trends and new applications, and opportunities and future prospects for RL in process industries. Moreover, it highlights the need for a holistic approach in complex systems due to the growing importance of digitalization in the process industries.

Process design and intensification of multicomponent azeotropes special distillation separation via molecular simulation and system optimization

This work provides an overview of distillation processes,including process design for different distillation processes,selection of entrainers for special distillation processes,system integration and intensification of distillation processes,optimization of process parameters for distillation processes and recent research progress in dynamic control strategies.Firstly,the feasibility of using thermodynamic topological theories such as residual curve,phase equilibrium line and distillation boundary line to analyze different separation regions is discussed,and the rationality of distillation process design is discussed by using its feasibility.Secondly,the application of molecular simulation methods such as molecular dynamics simulation and quantum chemical calculation in the screening of entrainer is discussed for the extractive distillation process.The thermal coupling mechanism of different distillation processes is used to explore the process of different process intensifications.Next,a mixed integer nonlinear optimization strategy for the distillation process based on different algorithms is introduced.Finally,the improvement of dynamic control strategies for different distillation processes in recent years is summarized.This work focuses on the application of process intensification and system optimization in the design of distillation process,and analyzes the challenges,prospects,and development trends of distillation technology in the separation of multicomponent azeotropes.

NADARAYA-WATSON ESTIMATORS FOR REFLECTED STOCHASTIC PROCESSES

We study the Nadaraya-Watson estimators for the drift function of two-sided reflected stochastic differential equations.The estimates,based on either the continuously observed process or the discretely observed process,are considered.Under certain conditions,we prove the strong consistency and the asymptotic normality of the two estimators.Our method is also suitable for one-sided reflected stochastic differential equations.Simulation results demonstrate that the performance of our estimator is superior to that of the estimator proposed by Cholaquidis et al.(Stat Sin,2021,31:29-51).Several real data sets of the currency exchange rate are used to illustrate our proposed methodology.

Detection of Oscillations in Process Control Loops From Visual Image Space Using Deep Convolutional Networks

Oscillation detection has been a hot research topic in industries due to the high incidence of oscillation loops and their negative impact on plant profitability.Although numerous automatic detection techniques have been proposed,most of them can only address part of the practical difficulties.An oscillation is heuristically defined as a visually apparent periodic variation.However,manual visual inspection is labor-intensive and prone to missed detection.Convolutional neural networks(CNNs),inspired by animal visual systems,have been raised with powerful feature extraction capabilities.In this work,an exploration of the typical CNN models for visual oscillation detection is performed.Specifically,we tested MobileNet-V1,ShuffleNet-V2,Efficient Net-B0,and GhostNet models,and found that such a visual framework is well-suited for oscillation detection.The feasibility and validity of this framework are verified utilizing extensive numerical and industrial cases.Compared with state-of-theart oscillation detectors,the suggested framework is more straightforward and more robust to noise and mean-nonstationarity.In addition,this framework generalizes well and is capable of handling features that are not present in the training data,such as multiple oscillations and outliers.

Multimodal Data-Driven Reinforcement Learning for Operational Decision-Making in Industrial Processes

Dear Editor, This letter proposes a multimodal data-driven reinforcement learning-based method for operational decision-making in industrial processes. Due to the frequent fluctuations of feedstock properties and operating conditions in the industrial processes, existing data-driven methods cannot effectively adjust the operational variables. In addition, multimodal data such as images, audio.

Operational optimization of copper flotation process based on the weighted Gaussian process regression and index-oriented adaptive differential evolution algorithm

Concentrate copper grade(CCG)is one of the important production indicators of copper flotation processes,and keeping the CCG at the set value is of great significance to the economic benefit of copper flotation industrial processes.This paper addresses the fluctuation problem of CCG through an operational optimization method.Firstly,a density-based affinity propagationalgorithm is proposed so that more ideal working condition categories can be obtained for the complex raw ore properties.Next,a Bayesian network(BN)is applied to explore the relationship between the operational variables and the CCG.Based on the analysis results of BN,a weighted Gaussian process regression model is constructed to predict the CCG that a higher prediction accuracy can be obtained.To ensure the predicted CCG is close to the set value with a smaller magnitude of the operation adjustments and a smaller uncertainty of the prediction results,an index-oriented adaptive differential evolution(IOADE)algorithm is proposed,and the convergence performance of IOADE is superior to the traditional differential evolution and adaptive differential evolution methods.Finally,the effectiveness and feasibility of the proposed methods are verified by the experiments on a copper flotation industrial process.

Dendritic spine degeneration:a primary mechanism in the aging process

Recent reports suggest that aging is not solely a physiological process in living beings;instead, it should be considered a pathological process or disease(Amorim et al., 2022). Consequently, this process involves a wide range of factors, spanning from genetic to environmental factors, and even includes the gut microbiome(GM)(Mayer et al., 2022). All these processes coincide at some point in the inflammatory process, oxidative stress, and apoptosis, at different degrees in various organs and systems that constitute a living organism(Mayer et al., 2022;AguilarHernández et al., 2023).

A review on plasma-based CO_(2) utilization:process considerations in the development of sustainable chemical production

Plasma-based processes,particularly in carbon capture and utilization,hold great potential for addressing environmental challenges and advancing a circular carbon economy.While significant progress has been made in understanding plasma-induced reactions,plasma-catalyst interactions,and reactor development to enhance energy efficiency and conversion,there remains a notable gap in research concerning overall process development.This review emphasizes the critical need for considerations at the process level,including integration and intensification,to facilitate the industrialization of plasma technology for chemical production.Discussions centered on the development of plasma-based processes are made with a primary focus on CO_(2) conversion,offering insights to guide future work for the transition of the technology from laboratory scale to industrial applications.Identification of current research gaps,especially in upscaling and integrating plasma reactors with other process units,is the key to addressing critical issues.The review further delves into relevant research in process evaluation and assessment,providing methodological insights and highlighting key factors for comprehensive economic and sustainability analyses.Additionally,recent advancements in novel plasma systems are reviewed,presenting unique advantages and innovative concepts that could reshape the future of process development.This review provides essential information for navigating the path forward,ensuring a comprehensive understanding of challenges and opportunities in the development of plasma-based CCU process.

Volumetric lattice Boltzmann method for pore-scale mass diffusionadvection process in geopolymer porous structures

Porous materials present significant advantages for absorbing radioactive isotopes in nuclear waste streams.To improve absorption efficiency in nuclear waste treatment,a thorough understanding of the diffusion-advection process within porous structures is essential for material design.In this study,we present advancements in the volumetric lattice Boltzmann method(VLBM)for modeling and simulating pore-scale diffusion-advection of radioactive isotopes within geopolymer porous structures.These structures are created using the phase field method(PFM)to precisely control pore architectures.In our VLBM approach,we introduce a concentration field of an isotope seamlessly coupled with the velocity field and solve it by the time evolution of its particle population function.To address the computational intensity inherent in the coupled lattice Boltzmann equations for velocity and concentration fields,we implement graphics processing unit(GPU)parallelization.Validation of the developed model involves examining the flow and diffusion fields in porous structures.Remarkably,good agreement is observed for both the velocity field from VLBM and multiphysics object-oriented simulation environment(MOOSE),and the concentration field from VLBM and the finite difference method(FDM).Furthermore,we investigate the effects of background flow,species diffusivity,and porosity on the diffusion-advection behavior by varying the background flow velocity,diffusion coefficient,and pore volume fraction,respectively.Notably,all three parameters exert an influence on the diffusion-advection process.Increased background flow and diffusivity markedly accelerate the process due to increased advection intensity and enhanced diffusion capability,respectively.Conversely,increasing the porosity has a less significant effect,causing a slight slowdown of the diffusion-advection process due to the expanded pore volume.This comprehensive parametric study provides valuable insights into the kinetics of isotope uptake in porous structures,facilitating the development of porous materials for nuclear waste treatment applications.

Correlation of Microbiological Stability with Redox Processes in White Wines

In this paper, the authors analyzed the correlation between the microbiological stability of white wines and the content of sulfur dioxide, which influences the main redox processes that take place in the technological stages of the wine. The consecutive, parallel and spontaneous development of several redox processes and their impact on the quality, microbiological and crystalline stability of white wines were examined. The reduction of additive and subtractive technological interventions, of the amounts of adjuvants (sulphurous anhydride) is essential for the production of organic wines.