基于softmax的加权Double Q-Learning算法

强化学习作为机器学习的一个分支,用于描述和解决智能体在与环境的交互过程中,通过学习策略以达成回报最大化的问题。Q-Learning作为无模型强化学习的经典方法,存在过估计引起的最大化偏差问题,并且在环境中奖励存在噪声时表现不佳。Double Q-Learning(DQL)的出现解决了过估计问题,但同时造成了低估问题。为解决以上算法的高低估问题,提出了基于softmax的加权Q-Learning算法,并将其与DQL相结合,提出了一种新的基于softmax的加权Double Q-Learning算法(WDQL-Softmax)。该算法基于加权双估计器的构造,对样本期望值进行softmax操作得到权重,使用权重估计动作价值,有效平衡对动作价值的高估和低估问题,使估计值更加接近理论值。实验结果表明,在离散动作空间中,相比于Q-Learning算法、DQL算法和WDQL算法,WDQL-Softmax算法的收敛速度更快且估计值与理论值的误差更小。

Enhancing the stability of Ni Fe-layered double hydroxide nanosheet array for alkaline seawater oxidation by Ce doping

Electrocatalytic hydrogen production from seawater holds enormous promise for clean energy generation.Nevertheless,the direct electrolysis of seawater encounters significant challenges due to poor anodic stability caused by detrimental chlorine chemistry.Herein,we present our recent discovery that the incorporation of Ce into Ni Fe layered double hydroxide nanosheet array on Ni foam(Ce-Ni Fe LDH/NF)emerges as a robust electrocatalyst for seawater oxidation.During the seawater oxidation process,CeO_(2)is generated,effectively repelling Cl^(-)and inhibiting the formation of Cl O-,resulting in a notable enhancement in the oxidation activity and stability of alkaline seawater.The prepared Ce-Ni Fe LDH/NF requires only overpotential of 390 m V to achieve the current density of 1 A cm^(-2),while maintaining long-term stability for 500 h,outperforming the performance of Ni Fe LDH/NF(430 m V,150 h)by a significant margin.This study highlights the effectiveness of a Ce-doping strategy in augmenting the activity and stability of materials based on Ni Fe LDH in seawater electrolysis for oxygen evolution.

Double contrast-enhanced ultrasonography improves diagnostic accuracy of T staging compared with multi-detector computed tomography in gastric cancer patients

BACKGROUND Gastric cancer(GC)is the most common malignant tumor and ranks third for cancer-related deaths among the worldwide.The disease poses a serious public health problem in China,ranking fifth for incidence and third for mortality.Knowledge of the invasive depth of the tumor is vital to treatment decisions.AIM To evaluate the diagnostic performance of double contrast-enhanced ultrasonography(DCEUS)for preoperative T staging in patients with GC by comparing with multi-detector computed tomography(MDCT).METHODS This single prospective study enrolled patients with GC confirmed by preoperative gastroscopy from July 2021 to March 2023.Patients underwent DCEUS,including ultrasonography(US)and intravenous contrast-enhanced ultrasonography(CEUS),and MDCT examinations for the assessment of preoperative T staging.Features of GC were identified on DCEUS and criteria developed to evaluate T staging according to the 8th edition of AJCC cancer staging manual.The diagnostic performance of DCEUS was evaluated by comparing it with that of MDCT and surgical-pathological findings were considered as the gold standard.RESULTS A total of 229 patients with GC(80 T1,33 T2,59 T3 and 57 T4)were included.Overall accuracies were 86.9%for DCEUS and 61.1%for MDCT(P<0.001).DCEUS was superior to MDCT for T1(92.5%vs 70.0%,P<0.001),T2(72.7%vs 51.5%,P=0.041),T3(86.4%vs 45.8%,P<0.001)and T4(87.7%vs 70.2%,P=0.022)staging of GC.CONCLUSION DCEUS improved the diagnostic accuracy of preoperative T staging in patients with GC compared with MDCT,and constitutes a promising imaging modality for preoperative evaluation of GC to aid individualized treatment decision-making.

Correction to:Theoretical analysis of the double-differential cross-sections of neutron,proton,deuteron,3He,and˛for the p+6 Li reaction

Correction to:Nuclear Science and Techniques(2024)35:61 https://doi.org/10.1007/s41365-024-01421-5 In this article,the figures were wrongly numbered.The Fig.7 and 8 should have been Fig.11 and 12.The Fig.9,10,11,and 12 should have been 7,8,9 and 10.The original article has been corrected.

Diagnosis of indirectly driven double shell targets with point-projection hard x-ray radiography

We present an application of short-pulse laser-generated hard x rays for the diagnosis of indirectly driven double shell targets. Coneinserted double shell targets were imploded through an indirect drive approach on the upgraded SG-II laser facility. Then, based on thepoint-projection hard x-ray radiography technique, time-resolved radiography of the double shell targets, including that of their near-peakcompression, were obtained. The backlighter source was created by the interactions of a high-intensity short pulsed laser with a metalmicrowire target. Images of the target near peak compression were obtained with an Au microwire. In addition, radiation hydrodynamicsimulations were performed, and the target evolution obtained agrees well with the experimental results. Using the radiographic images, arealdensities of the targets were evaluated.

Defective Nickel-Iron Layered Double Hydroxide for Enhanced Photocatalytic NO Oxidation with Significant Alleviation of NO2 Production

Photocatalysis offers a sustainable means for the oxidative removal of low concentrations of NOx(NO,NO2,N2O,N2O5,etc.)from the atmosphere.Layered double hydroxides(LDHs)are promising candidate photocatalysts owing to their unique layered and tunable chemical structures and abundant surface hydroxide(OH)moieties,which are hydroxyl radical(OH)precursors.However,the practical applications of LDHs are limited by their poor charge-separation ability and insufficient active sites.Herein,we developed a facile N_(2)H_(4)-driven etching approach to introduce dual Ni^(2+)and OHvacancies(Niv and OHv,respectively)into NiFe-LDH nanosheets(hereafter referred to as NiFe-LDH-et)to facilitate improved charge-carrier separation and active Lewis acidic site(Fe^(3+)and Ni^(2+)exposed at OHv)formation.In contrast to inert pristine LDH,NiFe-LDH-et actively removed NO under visible-light illumination.Specifically,Ni_(76)Fe_(24)-LDH-et etched with 1.50 mmol·L^(-1)N_(2)H_(4)solution removed 32.8%of the NO in continuously flowing air(NO feed concentration:500 parts per billion(ppb))under visible-light illumination,thereby outperforming most reported catalysts.Experimental and theoretical data revealed that the dual vacancies promoted the production of reactive oxygen species(O_(2)·^(-)andOH)and the adsorption of NO on the LDH.In situ spectroscopy demonstrated that NO was preferentially adsorbed at Lewis acidic sites,particularly exposed Fe^(3+)sites,converted into NO+,and subsequently oxidized to NO3without the notable formation of the more toxic intermediate NO2,thereby alleviating risks associated with its production and emission.

Effect of Single- versus Double-Layer Uterine Closure during Caesarean Section on Niche Formation and Menstrual Irregularity

Background: The myometrium at the location of the CS (caesarean section) scars, also known as residual myometrium thickness (RMT), is larger after a double-layer uterine closure procedure than following a single-layer one. It may lessen the formation of a niche that is the myometrium’s disruption at the location of the scar of the uterus. Gynecological manifestations, obstetric problems in a future pregnancy and birth, and maybe subfertility are linked to thin RMT and a niche. Objective: To ascertain if double-layer unlocked closure of the uterus is better than single-layer one in terms of post-menstrual spotting and niche development following a first CS. Patients and Methods: In this randomized clinical study, 287 patients were evaluated for qualifying. Of all eligible individuals, 57 patients were excluded from the study based on the inclusion criteria. Results: The variation in ages, gestational age, body mass index (BMI), and cesarean section indications between the two assigned groups is statistically insignificant. However, postmenstrual spotting was statistically significantly more common in single-layer group compared to in double-group. The current study revealed ultrasound findings suggestive of niche formation was statistically significantly more common in single-layer group compared to in double-layer group. Conclusion: As evident from the current study, it demonstrates the advantages of double-layer unlocked closure of the uterus over single-layer one in terms of post-menstrual spotting and niche development following first-time cs. Thus, we deduced that fewer niches are formed, and fewer menstrual spotting occurs in the presence of double unlocked layers closure. To ascertain the impact of uterus closure method on post-operative niche development and the risk of obstetrics and gynaecological problems, further prospective trials with extended follow-up periods are required.

Internal collision double ionization of molecules driven by co-rotating two-color circularly polarized laser pulses

The double ionization process of molecules driven by co-rotating two-color circularly polarized fields is investigated with a three-dimensional classical ensemble model. Numerical results indicate that a considerable part of the sequential double ionization(DI) events of molecules occur through internal collision double ionization(ICD), and the ICD recollision mechanism is significantly different from that in non-sequential double ionization(NSDI). By analyzing the results of internuclear distances R = 5 a.u. and 2 a.u., these two recollision mechanisms are studied in depth. It is found that the dynamic behaviors of the recollision mechanisms of NSDI and ICD are similar. For NSDI, the motion range of electrons after the ionization is relatively large, and the electrons will return to the core after a period of time. In the ICD process,electrons will rotate around the parent ion before ionization, and the distance of the electron motion is relatively small. After a period of time, the electrons will come back to the core and collide with another electron. Furthermore, the molecular internuclear distance has a significant effect on the electron dynamic behavior of the two ionization mechanisms. This study will help to understand the multi-electron ionization process of complex systems.

Effective multifunctional coatings with polyvinylpyrrolidone-enhanced ZIF-67 and zinc iron layered double hydroxide on microarc oxidation treated AZ31 magnesium alloy

Modulating metal-organic framework’s(MOF)crystallinity and size using a polymer,in conjunction with a high surface area of layered double hydroxide,yields an effective strategy for concurrently enhancing the electrochemical and photocatalytic performance.In this study,we present the development of an optimized nanocomposite,denoted as 0.5PVP/ZIF-67,developed on AZ31 magnesium alloy,serving as an efficient and durable multifunctional coating.This novel strategy aims to enhance the overall performance of the porous coating through the integration of microarc oxidation(MAO),ZnFe LDH backbone,and ZIF-67 formation facilitated by the addition of polyvinylpyrrolidone(PVP),resulting in a three-dimensional,highly efficient,and multifunctional material.The incorporation of 0.5 g of PVP proved to be effective in the size modulation of ZIF-67,which formed a corrosion-resistant top layer,improving the total polarization resistance(R_(p)=8.20×10^(8)).The dual functionality exhibited by this hybrid architecture positions it as a promising candidate for mitigating environmental pollution,degrading 97.93%of Rhodamine B dye in 45 min.Moreover,the sample displayed exceptional degradation efficiency(96.17%)after 5 cycles.This study illuminates the potential of nanocomposites as electrochemically stable and photocatalytically active materials,laying the foundation for the advancements of next-generation multifunctional frameworks.

The microbial community,nutrient supply and crop yields differ along a potassium fertilizer gradient under wheat-maize double-cropping systems

Soil microorganisms play critical roles in ecosystem function.However,the relative impact of the potassium(K)fertilizer gradient on the microbial community in wheat-maize double-cropping systems remains unclear.In this long-term field experiment(2008-2019),we researched bacterial and fungal diversity,composition,and community assemblage in the soil along a K fertilizer gradient in the wheat season(K0,no K fertilizer;K1,45 kg ha^(-1) K_(2)O;K_(2),90 kg ha^(-1)K_(2)O;K3,135 kg ha^(-1)K_(2)O)and in the maize season(K0,no K fertilizer;K_(1),150 kg ha^(-1) K_(2)O;K_(2),300 kg ha^(-1)K_(2)O;K_(3),450 kg ha^(-1)K_(2)O)using bacterial 16S rRNA and fungal internally transcribed spacer(ITS)data.We observed that environmental variables,such as mean annual soil temperature(MAT)and precipitation,available K,ammonium,nitrate,and organic matter,impacted the soil bacterial and fungal communities,and their impacts varied with fertilizer treatments and crop species.Furthermore,the relative abundance of bacteria involved in soil nutrient transformation(phylum Actinobacteria and class Alphaproteobacteria)in the wheat season was significantly increased compared to the maize season,and the optimal K fertilizer dosage(K2 treatment)boosted the relative bacterial abundance of soil nutrient transformation(genus Lactobacillus)and soil denitrification(phylum Proteobacteria)bacteria in the wheat season.The abundance of the soil bacterial community promoting root growth and nutrient absorption(genus Herbaspirillum)in the maize season was improved compared to the wheat season,and the K2 treatment enhanced the bacterial abundance of soil nutrient transformation(genus MND1)and soil nitrogen cycling(genus Nitrospira)genera in the maize season.The results indicated that the bacterial and fungal communities in the double-cropping system exhibited variable sensitivities and assembly mechanisms along a K fertilizer gradient,and microhabitats explained the largest amount of the variation in crop yields,and improved wheat?maize yields by 11.2-22.6 and 9.2-23.8%with K addition,respectively.These modes are shaped contemporaneously by the different meteorological factors and soil nutrient changes in the K fertilizer gradients.

Transformer-Aided Deep Double Dueling Spatial-Temporal Q-Network for Spatial Crowdsourcing Analysis

With the rapid development ofmobile Internet,spatial crowdsourcing has becomemore andmore popular.Spatial crowdsourcing consists of many different types of applications,such as spatial crowd-sensing services.In terms of spatial crowd-sensing,it collects and analyzes traffic sensing data from clients like vehicles and traffic lights to construct intelligent traffic prediction models.Besides collecting sensing data,spatial crowdsourcing also includes spatial delivery services like DiDi and Uber.Appropriate task assignment and worker selection dominate the service quality for spatial crowdsourcing applications.Previous research conducted task assignments via traditional matching approaches or using simple network models.However,advanced mining methods are lacking to explore the relationship between workers,task publishers,and the spatio-temporal attributes in tasks.Therefore,in this paper,we propose a Deep Double Dueling Spatial-temporal Q Network(D3SQN)to adaptively learn the spatialtemporal relationship between task,task publishers,and workers in a dynamic environment to achieve optimal allocation.Specifically,D3SQNis revised through reinforcement learning by adding a spatial-temporal transformer that can estimate the expected state values and action advantages so as to improve the accuracy of task assignments.Extensive experiments are conducted over real data collected fromDiDi and ELM,and the simulation results verify the effectiveness of our proposed models.

Supramolecular polymer-based gel fracturing fluid with a double network applied in ultra-deep hydraulic fracturing

A gel based on polyacrylamide,exhibiting delayed crosslinking characteristics,emerges as the preferred solution for mitigating degradation under conditions of high temperature and extended shear in ultralong wellbores.High viscosity/viscoelasticity of the fracturing fluid was required to maintain excellent proppant suspension properties before gelling.Taking into account both the cost and the potential damage to reservoirs,polymers with lower concentrations and molecular weights are generally preferred.In this work,the supramolecular action was integrated into the polymer,resulting in significant increases in the viscosity and viscoelasticity of the synthesized supramolecular polymer system.The double network gel,which is formed by the combination of the supramolecular polymer system and a small quantity of Zr-crosslinker,effectively resists temperature while minimizing permeability damage to the reservoir.The results indicate that the supramolecular polymer system with a molecular weight of(268—380)×10^(4)g/mol can achieve the same viscosity and viscoelasticity at 0.4 wt%due to the supramolecular interaction between polymers,compared to the 0.6 wt%traditional polymer(hydrolyzed polyacrylamide,molecular weight of 1078×10^(4)g/mol).The supramolecular polymer system possessed excellent proppant suspension properties with a 0.55 cm/min sedimentation rate at 0.4 wt%,whereas the0.6 wt%traditional polymer had a rate of 0.57 cm/min.In comparison to the traditional gel with a Zrcrosslinker concentration of 0.6 wt%and an elastic modulus of 7.77 Pa,the double network gel with a higher elastic modulus(9.00 Pa)could be formed only at 0.1 wt%Zr-crosslinker,which greatly reduced the amount of residue of the fluid after gel-breaking.The viscosity of the double network gel was66 m Pa s after 2 h shearing,whereas the traditional gel only reached 27 m Pa s.

Manipulating the electron dynamics in the non-sequential double ionization process of Ar atoms by an orthogonal two-color laser field

Electron dynamics during non-sequential double ionization(NSDI) is one of the most attractive areas of research in the field of laser–atom or laser–molecule interaction. Based on the classic two-dimensional model, we study the process of NSDI of argon atoms driven by a few-cycle orthogonal two-color laser field composed of 800 nm and 400 nm laser pulses. By changing the relative phase of the two laser pulses, a localized enhancement of NSDI yield is observed at 0.5πand 1.5π, which could be attributed to a rapid and substantial increase in the number of electrons returning to the parent ion within extremely short time intervals at these specific phases. Through the analysis of the electron–electron momentum correlations within different time windows of NSDI events and the angular distributions of emitted electrons in different channels, we observe a more pronounced electron–electron correlation phenomenon in the recollision-induced ionization(RII) channel. This is attributed to the shorter delay time in the RII channel.

An Efficient and Secure Privacy-Preserving Federated Learning Framework Based on Multiplicative Double Privacy Masking

With the increasing awareness of privacy protection and the improvement of relevant laws,federal learning has gradually become a new choice for cross-agency and cross-device machine learning.In order to solve the problems of privacy leakage,high computational overhead and high traffic in some federated learning schemes,this paper proposes amultiplicative double privacymask algorithm which is convenient for homomorphic addition aggregation.The combination of homomorphic encryption and secret sharing ensures that the server cannot compromise user privacy from the private gradient uploaded by the participants.At the same time,the proposed TQRR(Top-Q-Random-R)gradient selection algorithm is used to filter the gradient of encryption and upload efficiently,which reduces the computing overhead of 51.78%and the traffic of 64.87%on the premise of ensuring the accuracy of themodel,whichmakes the framework of privacy protection federated learning lighter to adapt to more miniaturized federated learning terminals.

Probing the electric double layer structure at nitrogen-doped graphite electrodes by constant-potential molecular dynamics simulations

Electric double layer(EDL)is a critical topic in electrochemistry and largely determines the working performance of lithium batteries.However,atomic insights into the EDL structures on heteroatom-modified graphite anodes and EDL evolution with electrode potential are very lacking.Herein,a constant-potential molecular dynamics(CPMD)method is proposed to probe the EDL structure under working conditions,taking N-doped graphite electrodes and carbonate electrolytes as an example.An interface model was developed,incorporating the electrode potential and atom electronegativities.As a result,an insightful atomic scenario for the EDL structure under varied electrode potentials has been established,which unveils the important role of doping sites in regulating both the EDL structures and the following electrochemical reactions at the atomic level.Specifically,the negatively charged N atoms repel the anions and adsorb Li~+at high and low potentials,respectively.Such preferential adsorption suggests that Ndoped graphite can promote Li~+desolvation and regulate the location of Li~+deposition.This CPMD method not only unveils the mysterious function of N-doping from the viewpoint of EDL at the atomic level but also applies to probe the interfacial structure on other complicated electrodes.

Structure Regulation of Electric Double Layer via Hydrogen Bonding Effect to Realize High-Stability Lithium-Metal Batteries

The interfacial chemistry of solid electrolyte interphases(SEI)on lithium(Li)electrode is directly determined by the structural chemistry of the electric double layer(EDL)at the interface.Herein,a strategy for regulating the structural chemistry of EDL via the introduction of intermolecular hydrogen bonds has been proposed(p-hydroxybenzoic acid(pHA)is selected as proof-of-concept).According to the molecular dynamics(MD)simulation and density functional theory(DFT)calculation results,the existence of hydrogen bonds realizes the anion structural rearrangement in the EDL,reduces the lowest unoccupied molecular orbital(LUMO)energy level of anions in the EDL,and the number of free solvent molecules,which promotes the formation of inorganic species-enriched SEI and eventually achieves the dendrite-free Li deposition.Based on this strategy,Li‖Cu cells can stably run over 185 cycles with an accumulated active Li loss of only 2.27 mAh cm^(-2),and the long-term cycle stability of Li‖Li cells is increased to 1200 h.In addition,the full cell pairing with the commercial LiFePO_(4)(LFP)cathodes exhibits stable cycling performance at 1C,with a capacity retention close to 90%after 200 cycles.

An Evidence-Based CoCoSo Framework with Double Hierarchy Linguistic Data for Viable Selection of Hydrogen Storage Methods

Hydrogen is the new age alternative energy source to combat energy demand and climate change.Storage of hydrogen is vital for a nation’s growth.Works of literature provide different methods for storing the produced hydrogen,and the rational selection of a viable method is crucial for promoting sustainability and green practices.Typically,hydrogen storage is associated with diverse sustainable and circular economy(SCE)criteria.As a result,the authors consider the situation a multi-criteria decision-making(MCDM)problem.Studies infer that previous models for hydrogen storage method(HSM)selection(i)do not consider preferences in the natural language form;(ii)weights of experts are not methodically determined;(iii)hesitation of experts during criteria weight assessment is not effectively explored;and(iv)three-stage solution of a suitable selection of HSM is unexplored.Driven by these gaps,in this paper,authors put forward a new integrated framework,which considers double hierarchy linguistic information for rating,criteria importance through inter-criteria correlation(CRITIC)for expert weight calculation,evidence-based Bayesian method for criteria weight estimation,and combined compromise solution(CoCoSo)for ranking HSMs.The applicability of the developed framework is testified by using a case example of HSM selection in India.Sensitivity and comparative analysis reveal the merits and limitations of the developed framework.

Mechanism of Thermally Radiative Prandtl Nanofluids and Double-Diffusive Convection in Tapered Channel on Peristaltic Flow with Viscous Dissipation and Induced Magnetic Field

The application of mathematical modeling to biological fluids is of utmost importance, as it has diverse applicationsin medicine. The peristaltic mechanism plays a crucial role in understanding numerous biological flows. In thispaper, we present a theoretical investigation of the double diffusion convection in the peristaltic transport of aPrandtl nanofluid through an asymmetric tapered channel under the combined action of thermal radiation andan induced magnetic field. The equations for the current flow scenario are developed, incorporating relevantassumptions, and considering the effect of viscous dissipation. The impact of thermal radiation and doublediffusion on public health is of particular interest. For instance, infrared radiation techniques have been used totreat various skin-related diseases and can also be employed as a measure of thermotherapy for some bones toenhance blood circulation, with radiation increasing blood flow by approximately 80%. To solve the governingequations, we employ a numerical method with the aid of symbolic software such as Mathematica and MATLAB.The velocity, magnetic force function, pressure rise, temperature, solute (species) concentration, and nanoparticlevolume fraction profiles are analytically derived and graphically displayed. The results outcomes are compared withthe findings of limiting situations for verification.

Improved Double Deep Q Network Algorithm Based on Average Q-Value Estimation and Reward Redistribution for Robot Path Planning

By integrating deep neural networks with reinforcement learning,the Double Deep Q Network(DDQN)algorithm overcomes the limitations of Q-learning in handling continuous spaces and is widely applied in the path planning of mobile robots.However,the traditional DDQN algorithm suffers from sparse rewards and inefficient utilization of high-quality data.Targeting those problems,an improved DDQN algorithm based on average Q-value estimation and reward redistribution was proposed.First,to enhance the precision of the target Q-value,the average of multiple previously learned Q-values from the target Q network is used to replace the single Q-value from the current target Q network.Next,a reward redistribution mechanism is designed to overcome the sparse reward problem by adjusting the final reward of each action using the round reward from trajectory information.Additionally,a reward-prioritized experience selection method is introduced,which ranks experience samples according to reward values to ensure frequent utilization of high-quality data.Finally,simulation experiments are conducted to verify the effectiveness of the proposed algorithm in fixed-position scenario and random environments.The experimental results show that compared to the traditional DDQN algorithm,the proposed algorithm achieves shorter average running time,higher average return and fewer average steps.The performance of the proposed algorithm is improved by 11.43%in the fixed scenario and 8.33%in random environments.It not only plans economic and safe paths but also significantly improves efficiency and generalization in path planning,making it suitable for widespread application in autonomous navigation and industrial automation.

Recent advances in flat sheet mixed matrix membrane modified by Mg-based layered double hydroxides(LDHs)for salt and organic compound separations

Magnesium(Mg)is a widely used and attractive metal,known for its unique physical and chemical properties,and it has been employed in the manufacture of many practical materials.Layered Double Hydroxides(LDHs),particularly Mg-based LDHs,rank among the most prevalent two-dimensional materials utilized in separation processes,which include adsorption,extraction,and membrane technology.The high popularity of Mg-based LDHs in separation applications can be attributed to their properties,such as excellent hydrophilicity,high surface area,ion exchangeability,and adjustable interlayer space.Currently,polymer membranes play a pivotal role in semi-industrial and industrial separation processes.Consequently,the development of polymer membranes and the mitigation of their limitations have emerged as compelling topics for researchers.Several methods exist to enhance the separation performance and anti-fouling properties of polymer membranes.Among these,incorporating additives into the membrane polymer matrix stands out as a cost-effective,straightforward,readily available,and efficient approach.The use of Mg-based LDHs,either in combination with other materials or as a standalone additive in the polymer membrane matrix,represents a promising strategy to bolster the separation and anti-fouling efficacy of flat sheet mixed matrix polymer membranes.This review highlights Mg-based LDHs as high-potential additives designed to refine flat sheet mixed matrix polymer membranes for applications in wastewater treatment and brackish water desalination.