Efficient fabrication of cellulose polymer networks via alkaline swelling strategy for wood bonding.

Existing issues with bio-based adhesives, such as complex preparation processes, high energy consumption, and production costs, still need to be addressed. In our study, APTES was grafted onto microcrystalline cellulose (MCC) to generate active aminated cellulose, and then reacted with the epoxide group in glycerol triglycidyl ether (GTE) through a swelling strategy under alkaline solvent, forming a network structure via covalent cross-linking. The adhesive exhibits superior bonding performance and water-resistant property in the bonding strength test of poplar plywood, with a dry shear strength of 2.40 MPa, a wet shear strength of 2.16 MPa after soaking in 63 °C hot water, and a wet shear strength of 1.79 MPa after soaking in boiling water. In terms of cost calculation, the theoretical production cost of AC-GTE adhesive is calculated to be 5303.7 RMB per ton, which is comparable to that of phenol-formaldehyde (PF) resin and other petrochemical-based adhesives, and significantly lower than that of isocyanate-based adhesives. These research results can provide a practical example for producing high-efficiency, aldehyde-free, and low-cost bio-based adhesives.

Reconfigurable aJ-Level Ferroelectric Transistor-Based Boolean Logic for Logic-in-Memory.

Logic-in-memory (LIM) architecture holds great potential to break the von Neumann bottleneck. Despite the extensive research on novel devices, challenges persist in developing suitable engineering building blocks for such designs. Herein, we propose a reconfigurable strategy for efficient implementation of Boolean logics based on a hafnium oxide-based ferroelectric field effect transistor (HfO2-based FeFET). The logic results are stored within the device itself (in situ) during the computation process, featuring the key characteristics of LIM. The fast switching speed and low power consumption of a HfO2-based FeFET enable the execution of Boolean logics with an ultralow energy of lower than 8 attojoule (aJ). This represents a significant milestone in achieving aJ-level computing energy consumption. Furthermore, the system demonstrates exceptional reliability with computing endurance exceeding 108 cycles and retention properties exceeding 1000 s. These results highlight the remarkable potential of a FeFET for the realization of high performance beyond the von Neumann LIM computing architectures.

Highly Sensitive, Low-Energy-Consumption Biomimetic Olfactory Synaptic Transistors Based on the Aggregation of the Semiconductor Films.

Artificial olfactory synaptic devices with low energy consumption and low detection limits are important for the further development of neuromorphic computing and intelligent robotics. In this work, an ultralow energy consumption and low detection limit imitation olfactory synaptic device based on organic field-effect transistors (OFETs) was prepared. The aggregation state of poly(diketopyrrolopyrrole-selenophene) (PTDPP) semiconductor films is modulated by adding unfavorable solvents and annealing treatments to obtain excellent charge transfer and gas synaptic properties. The regulated OFET device can execute basic biological synaptic functions, including excitatory postsynaptic currents (EPSCs), paired-pulse facilitation (PPF), and the transition from short-term to long-term plasticity, at an ultralow operating voltage of -0.0005 V. The ultralow energy consumption during the biomimetic simulation is in the range of 8.94-88 fJ per spike. Noteworthily, the gas detection limit of the device is as low as 50 ppb, well below normal human NO2 gas perception limits (100-1000 ppb). Additionally, high-pass filtering, Pavlovian conditioned reflexes, and decoding of "Morse code" were simulated. Finally, a grid-free conformal device with outstanding flexibility and stability was fabricated. In conclusion, the control of semiconductor thin-film aggregation provides effective guidance for preparing low-energy-consumption, highly sensitive olfactory nerve-mimicking devices and promoting the development of wearable electronics.

A Self-Localization Algorithm for Mobile Targets in Indoor Wireless Sensor Networks Using Wake-Up Media Access Control Protocol.

Indoor localization of a mobile target represents a prominent application within wireless sensor network (WSN), showcasing significant values and scientific interest. Interference, obstacles, and energy consumption are critical challenges for indoor applications and battery replacements. A proposed tracking system deals with several factors such as latency, energy consumption, and accuracy presenting an innovative solution for the mobile localization application. In this paper, a novel algorithm introduces a self-localization algorithm for mobile targets using the wake-up media access control (MAC) protocol. The developed tracking application is based on the trilateration technique with received signal strength indication (RSSI) measurements. Simulations are implemented in the objective modular network testbed in C++ (OMNeT++) discrete event simulator using the C++ programming language, and the RSSI values introduced are based on real indoor measurements. In addition, a determination approach for finding the optimal parameters of RSSI is assigned to implement for the simulation parameters. Simulation results show a significant reduction in power consumption and exceptional accuracy, with an average error of 1.91 m in 90% of cases. This method allows the optimization of overall energy consumption, which consumes only 2.69% during the localization of 100 different positions.

Polarized Tunneling Transistor for Ultralow-Energy-Consumption Artificial Synapse toward Neuromorphic Computing.

Neural networks based on low-power artificial synapses can significantly reduce energy consumption, which is of great importance in today's era of artificial intelligence. Two-dimensional (2D) material-based floating-gate transistors (FGTs) have emerged as compelling candidates for simulating artificial synapses owing to their multilevel and nonvolatile data storage capabilities. However, the low erasing/programming speed of FGTs renders them unsuitable for low-energy-consumption artificial synapses, thereby limiting their potential in high-energy-efficient neuromorphic computing. Here, we introduce a FGT-inspired MoS2/Trap/PZT heterostructure-based polarized tunneling transistor (PTT) with a simple fabrication process and significantly enhanced erasing/programming speed. Distinct from the FGT, the PTT lacks a tunnel layer, leading to a marked improvement in its erasing/programming speed. The PTT's highest erasing/programming (operation) speed can reach ∼20 ns, which outperforms the performance of most FGTs based on 2D heterostructures. Furthermore, the PTT has been utilized as an artificial synapse, and its weight-update energy consumption can be as low as 0.0002 femtojoule (fJ), which benefits from the PTT's ultrahigh operation speed. Additionally, PTT-based artificial synapses have been employed in constructing artificial neural network simulations, achieving facial-recognition accuracy (95%). This groundbreaking work makes it possible for fabricating future high-energy-efficient neuromorphic transistors utilizing 2D materials.

Harnessing 2D Ruddlesden-Popper Perovskite with Polar Organic Cation for Ultrasensitive Multibit Nonvolatile Transistor-Type Photomemristors.

Photomemristors have been regarded as one of the most promising candidates for next-generation hardware-based neuromorphic computing due to their potentials of fast data transmission and low power consumption. However, intriguingly, so far, photomemristors seldom display truly nonvolatile memory characteristics with high light sensitivity. Herein, we demonstrate ultrasensitive photomemristors utilizing two-dimensional (2D) Ruddlesden-Popper (RP) perovskites with a highly polar donor-acceptor-type push-pull organic cation, 4-(5-(2-aminoethyl)thiophen-2-yl)benzonitrile+ (EATPCN+), as charge-trapping layers. High linearity and almost zero-decay retention are observed in (EATPCN)2PbI4 devices, which are very distinct from that of the traditional 2D RP perovskite devices consisting of nonpolar organic cations, such as phenethylamine+ (PEA+) and octylamine+ (OA+), and traditional 3D perovskite devices consisting of methylamine+ (MA+). The 2-fold advantages, including desirable spatial crystal arrangement and engineered energetic band alignment, clarify the mechanism of superior performance in (EATPCN)2PbI4 devices. The optimized (EATPCN)2PbI4 photomemristor also shows a memory window of 87.9 V and an on/off ratio of 106 with a retention time of at least 2.4 × 105 s and remains unchanged after >105 writing-reading-erasing-reading endurance cycles. Very low energy consumptions of 1.12 and 6 fJ for both light stimulation and the reading process of each status update are also demonstrated. The extremely low power consumption and high photoresponsivity were simultaneously achieved. The high photosensitivity surpasses that of a state-of-the-art commercial pulse energy meter by several orders of magnitude. With their outstanding linearity and retention, rabbit images have been rebuilt by (EATPCN)2PbI4 photomemristors, which truthfully render the image without fading over time. Finally, by utilizing the powerful ∼8 bits of nonvolatile potentiation and depression levels of (EATPCN)2PbI4 photomemristors, the accuracies of the recognition tasks of CIFAR-10 image classification and MNIST handwritten digit classification have reached 89% and 94.8%, respectively. This study represents the first report of utilizing a functional donor-acceptor type of organic cation in 2D RP perovskites for high-performance photomemristors with characteristics that are not found in current halide perovskites.

Extracellular electron transfer for aerobic denitrification mediated by the bioelectric catalytic system with zero-carbon source.

The slow rate of electron transfer and the large consumption of carbon sources are technical bottlenecks in the biological treatment of wastewater. Here, we first proposed to domesticate aerobic denitrifying bacteria (ADB) from heterotrophic to autotrophic by electricity (0.6 V) under zero organic carbon source conditions, to accelerate electron transfer and shorten hydraulic retention time (HRT) while increasing the biodegradation rate. Then we investigated the extracellular electron transfer (EET) mechanism mediated by this process, and additionally examined the integrated nitrogen removal efficiency of this system with composite pollution. It was demonstrated that compared with the traditional membrane bioreactor (MBR), the BEC displayed higher nitrogen removal efficiency. Especially at C/N = 0, the BEC exhibited a NO3--N removal rate of 95.42 ± 2.71 % for 4 h, which was about 6.5 times higher than that of the MBR. Under the compound pollution condition, the BEC still maintained high NO3--N and tetracycline removal (94.52 ± 2.01 % and 91.50 ± 0.001 %), greatly superior to the MBR (10.64 ± 2.01 % and 12.00 ± 0.019 %). In addition, in-situ electrochemical tests showed that the nitrate in the BEC could be directly converted to N2 by reduction using electrons from the cathode, which was successfully demonstrated as a terminal electron acceptor.

PZT-Enabled MoS2 Floating Gate Transistors: Overcoming Boltzmann Tyranny and Achieving Ultralow Energy Consumption for High-Accuracy Neuromorphic Computing.

Low-power electronic devices play a pivotal role in the burgeoning artificial intelligence era. The study of such devices encompasses low-subthreshold swing (SS) transistors and neuromorphic devices. However, conventional field-effect transistors (FETs) face the inherent limitation of the "Boltzmann tyranny", which restricts SS to 60 mV decade-1 at room temperature. Additionally, FET-based neuromorphic devices lack sufficient conductance states for highly accurate neuromorphic computing due to a narrow memory window. In this study, we propose a pioneering PZT-enabled MoS2 floating gate transistor (PFGT) configuration, demonstrating a low SS of 46 mV decade-1 and a wide memory window of 7.2 V in the dual-sweeping gate voltage range from -7 to 7 V. The wide memory window provides 112 distinct conductance states for PFGT. Moreover, the PFGT-based artificial neural network achieves an outstanding facial-recognition accuracy of 97.3%. This study lays the groundwork for the development of low-SS transistors and highly energy efficient artificial synapses utilizing two-dimensional materials.

A simple and low-energy strategy for the separation of water and acetonitrile.

As acetonitrile is a widely used solvent for the chemical industry, the recovery of acetonitrile from acetonitrile wastewater is significant for both industrial cost reduction and environmental protection. In this article, a simple, low-energy, and low-cost strategy is proposed for the effective separation of acetonitrile from high-concentration acetonitrile wastewater. The approach is based on a sequential combination of two steps: salt-induced phase separation and hydrophobic filtration. The acetonitrile wastewater was first induced to split into two phases by salt, that is, the acetonitrile-rich phase and the water-rich phase, then the above two phases were poured into the hydrophobic filter paper funnel for the separation. It was shown that NaCl is a suitable salting-out reagent, and that hydrophobic filter papers-obtained from modification by butyltrichlorosilane and octyltrichlorosilane were the optimal choice for hydrophobic filtration. The salt-induced phase separation process is able to increase the volume fraction of acetonitrile in the acetonitrile-rich phase up to 92%. The acetonitrile-rich phase can pass through the hydrophobic filter paper, whereas the water-rich phase was intercepted. The hydrophobic filter paper retained strong hydrophobicity and high acetonitrile-separating capacity after 3 months storage, or upon immersion in acetonitrile-water mixtures for 12 h, or applied for 25 consecutive separations.

Regulating the concentration of dissolved oxygen to achieve the directional transformation of reactive oxygen species: A controllable oxidation process for ciprofloxacin degradation by calcined CuCoFe-LDH.

Different reactive oxygen species (ROS) tend to attack specific sites on pollutants, leading to the formation of intermediates with different toxic effects. Therefore, regulating the directional transformation of ROS is a new effective approach for safe degradation of refractory organic compounds in wastewater. However, the regulation mechanism and transformation path of ROS remain unclear. In this work, the dissolved oxygen (DO) content was controlled by aeration to generate different ROS through the activation of O2 on the calcined CuCoFe-LDH (CuCoFe-300). ROS quantitative experiments and electron paramagnetic resonance proved that O2 was mainly activated to superoxide radical (•O2-) and singlet oxygen (1O2) under low DO concentration (0.231 mmol/L) (O2 â†’ â€¢O2- â†’ 1O2). With the increasing of DO concentration (0.606 mmol/L), O2 was inclined to convert into hydroxyl radicals (•OH) (O2 â†’ â€¢O2- â†’ H2O2 â†’ â€¢OH). The density functional theory and function model of active sites utilization and DO concentration built a solid proof for ROS conversion mechanism that increasing the DO concentration promotes the increase of active sites utilization on the CuCoFe-300 system. That is, the •O2- was more prone to convert to •OH, not 1O2 in thermodynamics under high active sites utilization condition. Hence, the ROS generation was controlled by regulating DO concentration, and the nontoxic degradation pathway of ciprofloxacin was well-designed. This work is dedicated to the in-depth exploration of the mechanism between DO concentration and ROS conversion, which provides an extremely flexible, low energy consumption, and environmentally friendly wastewater treatment method in a new perspective.

Lithium-plasmon-based low-powered dynamic color display.

Display and power supply have been two essential and independent cornerstones of modern electronics. Here, we report a lithium-plasmon-based low-powered dynamic color display with intrinsic dual functionality (plasmonic display and energy recycling unit) which is a result of the electric-field-driven transformation of nanostructured lithium metals. Dynamic color displays are enabled by plasmonic transformation through electrodeposition (electrostripping) of lithium metals during the charging (discharging) process, while the consumed energy for coloring can be retrieved in the inverse process respectively. Energy recycling of lithium metals brings energy consumption down to 0.390 mW cm-2 (0.105 mW cm-2) for the active (static) coloration state of a proof-of-concept display/battery device, which approaches nearly-zero-energy-consumption in the near-100%-energy-efficiency limit of commercial lithium batteries. Combining the subwavelength feature of plasmonics with effective energy recycling, the lithium-plasmon-based dynamic display offers a promising route towards next-generation integrated photonic devices, with the intriguing advantages of low energy consumption, a small footprint and high resolution.

Recycling Valuable Metals from Spent Lithium-Ion Batteries Using Carbothermal Shock Method.

Pyrometallurgy technique is usually applied as a pretreatment to enhance the leaching efficiencies in the hydrometallurgy process for recovering valuable metals from spent lithium-ion batteries. However, traditional pyrometallurgy processes are energy and time consuming. Here, we report a carbothermal shock (CTS) method for reducing LiNi0.3 Co0.2 Mn0.5 O2 (NCM325) cathode materials with uniform temperature distribution, high heating and cooling rates, high temperatures, and ultrafast reaction times. Li can be selectively leached through water leaching after CTS process with an efficiency of >90 %. Ni, Co, and Mn are recovered by dilute acid leaching with efficiencies >98 %. The CTS reduction strategy is feasible for various spent cathode materials, including NCM111, NCM523, NCM622, NCM811, LiCoO2 , and LiMn2 O4 . The CTS process, with its low energy consumption and potential scale application, provides an efficient and environmentally friendly way for recovering spent lithium-ion batteries.

Migration electric-field assisted electrocoagulation with sponge biochar capacitive electrode for advanced wastewater phosphorus removal.

Migrating electric field-assisted electrocoagulation (MEAEC) is a three-electrode electrochemical system, including waste flour-derived sponge biochar (SBC) as an adsorption electrode for efficient phosphorus removal from wastewater. The SBC was applied in the MEAEC system as a pseudo capacitance electrode with low energy consumption and reached an excellent effluent level (0.12 mg/L) with a 200-s treatment time in 1 mg/L phosphate synthetic wastewater. The SBC adsorption electrode had a total charge capacitance of 1.14 F/g with abundant micropores. Continuous charging and discharging at a constant voltage over 100 cycles demonstrated the excellent durability of the biochar electrodes. The energy demand of SBC-MEAEC was only 0.0058 kWh/m3 for 90% phosphate removal, which was 65% less than that of the control. The use of SBC in the MEAEC system greatly enhanced phosphate removal at low concentrations. In the SBC-MEAEC system, the electro-desorption synchronous electrocoagulation process demonstrated efficient concentration and release of ions after electro-adsorption. These results indicate that MEAEC with an SBC electrode could achieve a high level of phosphate removal with a much lower energy consumption than in previous studies. The recovered concentrated phosphorus flocs also contained fewer metal impurities than those in previous electrochemical approaches. The proposed desorption synchronous electrocoagulation utilizing waste-derived SBC electrodes provides a cost-effective pathway to treat low phosphorous-containing wastewater.

Bifunctional Ni@NiO catalyst supported on loofah sponge-derived carbon for electrocatalytic air oxidation of biorefractory pollutant in a coupling system.

Oxygen (O2) in the air is a green oxidant, and utilization of air for pollutant removal is highly desired. Herein, we report the preparation and utilization of a novel biomass-based three-dimensional (3D) Ni@NiO/carbon composite for the electro-activation of O2 under room condition. The carbon-coated Ni@NiO nanoparticles are fabricated on a hierarchical 3D porous loofah sponge-derived carbon (LSC) support as the bifunctional catalyst for the activation of O2 via both the electro-oxidation and electro-reduction reactions. An electrocatalytic air oxidation coupling system is constructed with the Ni@NiO/LSC shell-core electrodes for pollutant degradation. A variety of organic pollutants, including pharmaceutics and personal care products (PPCPs), dyes, phenolic compounds, and real waters are mineralized by more than 60% with significantly enhanced biodegradability. Notably, the coupling system obtains high mineralization efficiency of 70.2 ± 1.9% on landfill leachate with significant biodegradability enhancement. The specific energy consumptions of the coupling system are only 6.8 ± 0.7 to 60.2 ± 3.6 kWh kg-TOC-1 in mineralizing different pollutants. The hollow structure of the LSC fibers endows the loaded Ni@NiO with superior intrinsic catalytic activity, which is associated with low reaction resistance and facile electron transfer. The Ni@NiO on LSC presents an electrocatalytic wet air oxidation (ECWAO) catalytic activity higher by 35.8% and cathodic air oxidation (CAO) catalytic activity higher by 22.7% as compared to that loaded on commercial graphite felt.

Research on Smart Tourism Oriented Sensor Network Construction and Information Service Mode.

Smart tourism is the latest achievement of tourism development at home and abroad. It is also an essential part of the smart city. Promoting the application of computer and sensor technology in smart tourism is conducive to improving the efficiency of public tourism services and guiding the innovation of the tourism public service mode. In this paper, we have proposed a new method of using data collected by sensor networks. We have developed and deployed sensors to collect data, which are transmitted to the modular cloud platform, and combined with cluster technology and an Uncertain Support Vector Classifier (A-USVC) location prediction method to assist in emergency events. Considering the attraction of tourists, the system also incorporated human trajectory analysis and intensity of interaction as consideration factors to validate the spatial dynamics of different interests and enhance the tourists' experience. The system explored the innovative road of computer technology to boost the development of smart tourism, which helps to promote the high-quality development of tourism.

Directional Formation of Conductive Filaments for a Reliable Organic-Based Artificial Synapse by Doping Molybdenum Disulfide Quantum Dots into a Polymer Matrix.

The conductive filament (CF) model, as an important means to realize synaptic functions, has received extensive attention and has been the subject of intense research. However, the random and uncontrollable growth of CFs seriously affects the performances of such devices. In this work, we prepared a neural synaptic device based on polyvinyl pyrrolidone-molybdenum disulfide quantum dot (MoS2 QD) nanocomposites. The doping with MoS2 QDs was found to control the growth mode of Ag CFs by providing active centers for the formation of Ag clusters, thus reducing the uncertainty surrounding the growth of Ag CFs. As a result, the device, with a low power consumption of 32.8 pJ/event, could be used to emulate a variety of synaptic functions, including long-term potentiation (LTP), long-term depression (LTD), paired-pulse facilitation, post-tetanic potentiation, short-term memory to long-term memory conversion, and "learning experience" behavior. After having undergone consecutive stimulation with different numbers of pulses, the device stably realized a "multi-level LTP to LTD conversion" function. Moreover, the synaptic characteristics of the device experienced no degradation due to mechanical stress. Finally, the simulation result based on the synaptic characteristics of our devices achieved a high recognition accuracy of 91.77% in learning and inference tests and showed clear digital classification results.

High Gain, Low Noise and Power Transimpedance Amplifier Based on Second Generation Voltage Conveyor in 65 nm CMOS Technology.

A transimpedance amplifier (TIA) based on a voltage conveyor structure designed for high gain, low noise, low distortion, and low power consumption is presented in this work. Following a second-generation voltage conveyor topology, the current and voltage blocks are a regulated cascode amplifier and a down converter buffer, respectively. The proposed voltage buffer is designed for low distortion and low power consumption, whereas the regulated cascode is designed for low noise and high gain. The resulting TIA was fabricated in 65 nm CMOS technology for logic and mixed-mode designs, using low-threshold voltage transistors and a supply voltage of ±1.2 V. It exhibited a 52 dBΩ transimpedance gain and a 1.1 GHz bandwidth, consuming 55.3 mW using a ±1.2 V supply. Our preamplifier stage, based on a regulated cascode, was designed considering detector capacitance, bonding wire, and packaging capacitance. The voltage buffer was designed for low-power consumption and low distortion. The measured input-referred noise of the TIA was 22 pA/√Hz. The obtained total harmonic distortion of the TIA was close to 5%. In addition, the group delay is constant for the considered bandwidth. Comparisons against published results in terms of area (A), power consumption (P), bandwidth (BW), transimpedance gain (G), and noise (N) are were performed. Both figures of merit FoMs-the ratio √ (G × BW) and P × A-and FoM/N values demostrated the advantages of the proposed approach.

Backpropagation with biologically plausible spatiotemporal adjustment for training deep spiking neural networks.

The spiking neural network (SNN) mimics the information-processing operation in the human brain. Directly applying backpropagation to the training of the SNN still has a performance gap compared with traditional deep neural networks. To address the problem, we propose a biologically plausible spatial adjustment that rethinks the relationship between membrane potential and spikes and realizes a reasonable adjustment of gradients to different time steps. It precisely controls the backpropagation of the error along the spatial dimension. Secondly, we propose a biologically plausible temporal adjustment to make the error propagate across the spikes in the temporal dimension, which overcomes the problem of the temporal dependency within a single spike period of traditional spiking neurons. We have verified our algorithm on several datasets, and the experimental results have shown that our algorithm greatly reduces network latency and energy consumption while also improving network performance.

The Optimization of the Transition Zone of the Planar Heterogeneous Interface for High-Performance Seawater Desalination.

Reverse osmosis has become the most prevalent approach to seawater desalination. It is still limited by the permeability-selectivity trade-off of the membranes and the energy consumption in the operation process. Recently, an efficient ionic sieving with high performance was realized by utilizing the bi-unipolar transport behaviour and strong ion depletion of heterogeneous structures in 2D materials. A perfect salt rejection rate of 97.0% and a near-maximum water flux of 1529 L m-2 h-1 bar-1 were obtained. However, the energy consumption of the heterogeneous desalination setup is a very important factor, and it remains largely unexplored. Here, the geometric-dimension-dependent ion transport in planar heterogeneous structures is reported. The two competitive ion migration behaviours during the desalination process, ion-depletion-dominated and electric-field-dominated ion transport, are identified for the first time. More importantly, these two ion-transport behaviours can be regulated. The excellent performance of combined high rejection rate, high water flux and low energy consumption can be obtained under the synergy of voltage, pressure and geometric dimension. With the appropriate optimization, the energy consumption can be reduced by 2 orders of magnitude, which is 50% of the industrial energy consumption. These findings provide beneficial insight for the application and optimized design of low-energy-consumption and portable water desalination devices.

A multifunctional and low-energy electrochemical membrane system for chemical-free regulation of solution pH.

A proper pH environment is essential for a wide variety of industries and applications especially related to water treatment. Current methods for pH adjustment including addition of acid/base and electrochemical processes demonstrate disadvantages associated with environment and energy. Here, we designed a multifunctional electrochemical membrane system (EMS) with one piece of filtration membrane inserted into an electrochemical cell. When electrical field was applied, OH- and H+ ions were produced from reduction and oxidation reactions at cathode and anode, respectively. The membrane posed a resistance for the transport of OH- and H+ ions and prevented their mixing in the cell. The EMS can be also operated in a filtration mode, which could simultaneously regulate permeate and feed pH and accomplish water filtration. In both non-filtration and filtration modes, EMS could achieve effective control of solution pH over a wide range by exerting different voltages without dosing any chemicals. Under the voltage of 1.2 V, the solution pH could reach and be maintained at 10.7 and 3.3 in cathodic and anodic channels, respectively. Furthermore, it was experimentally demonstrated that the EMS only consumed extremely low energy. This, together with membrane filtration in an integrated manner, highlights the huge potential of the EMS for applications in various water industries.