Application of biochar to soils changes soil physicochemical properties and stimulates the activities of soil microorganisms that influence soil quality and plant performance.Studying the response of soil microbial co...Application of biochar to soils changes soil physicochemical properties and stimulates the activities of soil microorganisms that influence soil quality and plant performance.Studying the response of soil microbial communities to biochar amendments is important for better understanding interactions of biochar with soil,as well as plants.However,the effect of biochar on soil microorganisms has received less attention than its influences on soil physicochemical properties.In this review,the following key questions are discussed:(i)how does biochar affect soil microbial activities,in particular soil carbon(C)mineralization,nutrient cycling,and enzyme activities?(ii)how do microorganisms respond to biochar amendment in contaminated soils?and(iii)what is the role of biochar as a growth promoter for soil microorganisms?Many studies have demonstrated that biochar-soil application enhances the soil microbial biomass with substantial changes in microbial community composition.Biochar amendment changes microbial habitats,directly or indirectly affects microbial metabolic activities,and modifies the soil microbial community in terms of their diversity and abundance.However,chemical properties of biochar,(especially pH and nutrient content),and physical properties such as pore size,pore volume,and specific surface area play significant roles in determining the efficacy of biochar on microbial performance as biochar provides suitable habitats for microorgan-isms.The mode of action of biochar leading to stimulation of microbial activities is complex and is influenced by the nature of biochar as well as soil conditions.展开更多
The Ni-rich Li[Ni0.6Co0.2Mn0.2]O2 surface has been modified with H3PO4. After coating at 80 ℃, the products were heated further at a moderate temperature of 500 ℃ in air, when the added H3PO4 transformed to Li3PO4 a...The Ni-rich Li[Ni0.6Co0.2Mn0.2]O2 surface has been modified with H3PO4. After coating at 80 ℃, the products were heated further at a moderate temperature of 500 ℃ in air, when the added H3PO4 transformed to Li3PO4 after reacting with residual LiOH and Li2CO3 on the surface. A thin and uniform smooth nanolayer （〈 10 nm） was observed on the surface of Li[Ni0.6Co0.2Mn0.2]O2 as confirmed by transmission electron microscopy （TEM）. Time-of-flight secondary ion mass spectroscopic （ToF-SIMS） data exhibit the presence of LIP＋, LiPO-, and Li2PO2＋ fragments, indicating the formation of the Li3PO4 coating layer on the surface of the Li[Ni0.6Co0.2Mn0.2]O2. As a result, the amounts of residual lithium compounds, such as LiOH and Li2CO3, are significantly reduced. As a consequence, the LigPO4-coated Li[Ni0.6Co0.2Mn0.2]O2 exhibits noticeable improvement in capacity retention and rate capability due to the reduction of residual LiOH and Li2CO3. Further investigation of the extensively cycled electrodes by X-ray diffraction （XRD）, TEM, and ToF-SIMS demonstrated that the LiBPO4 coating layers have multi-functions： Absorption of water in the electrolyte that lowers the HF level, HF scavenging, and protection of the active materials from deleterious side reactions with the electrolyte during extensive cycling, enabling high capacity retention over 1,000 cycles.展开更多
The effects of fertilization on activity and composition of soil microbial community depend on nutrient and water availability;however,the combination of these factors on the response of microorganisms was seldom stud...The effects of fertilization on activity and composition of soil microbial community depend on nutrient and water availability;however,the combination of these factors on the response of microorganisms was seldom studied.This study investigated the responses of soil microbial community and enzyme activities to changes in moisture along a gradient of soil fertility formed within a long-term(24 years)field experiment.Soils(0–20 cm)were sampled from the plots under four fertilizer treatments:i)unfertilized control(CK),ii)organic manure(M),iii)nitrogen,phosphorus,and potassium fertilizers(NPK),and iv)NPK plus M(NPK+M).The soils were incubated at three moisture levels:constant submergence,five submerging-draining cycles(S-D cycles),and constant moisture content at 40%water-holding capacity(low moisture).Compared with CK,fertilization increased soil organic carbon(SOC) by 30.1%–36.3%,total N by 27.3%–38.4%,available N by 35.9%–56.4%,available P by 61.4%–440.9%,and total P by 28.6%–102.9%.Soil fertility buffered the negative effects of moisture on enzyme activities and microbial community composition.Enzyme activities decreased in response to submergence and S-D cycles versus low moisture.Compared with low moisture,S-D cycles increased total phospholipid fatty acids(PLFAs)and actinomycete,fungal,and bacterial PLFAs.The increased level of PLFAs in the unfertilized soil after five S-D cycles was greater than that in the fertilized soil.Variations in soil microbial properties responding to moisture separated CK from the long-term fertilization treatments.The coefficients of variation of microbial properties were negatively correlated with SOC,total P,and available N.Soils with higher fertility maintained the original microbial properties more stable in response to changes in moisture compared to low-fertility soil.展开更多
In this study, a novel approach of the landslide numerical risk factor(LNRF) bivariate model was used in ensemble with linear multivariate regression(LMR) and boosted regression tree(BRT) models, coupled with radar re...In this study, a novel approach of the landslide numerical risk factor(LNRF) bivariate model was used in ensemble with linear multivariate regression(LMR) and boosted regression tree(BRT) models, coupled with radar remote sensing data and geographic information system(GIS), for landslide susceptibility mapping(LSM) in the Gorganroud watershed, Iran. Fifteen topographic, hydrological, geological and environmental conditioning factors and a landslide inventory(70%, or 298 landslides) were used in mapping. Phased array-type L-band synthetic aperture radar data were used to extract topographic parameters. Coefficients of tolerance and variance inflation factor were used to determine the coherence among conditioning factors. Data for the landslide inventory map were obtained from various resources, such as Iranian Landslide Working Party(ILWP), Forestry, Rangeland and Watershed Organisation(FRWO), extensive field surveys, interpretation of aerial photos and satellite images, and radar data. Of the total data, 30% were used to validate LSMs, using area under the curve(AUC), frequency ratio(FR) and seed cell area index(SCAI).Normalised difference vegetation index, land use/land cover and slope degree in BRT model elevation, rainfall and distance from stream were found to be important factors and were given the highest weightage in modelling. Validation results using AUC showed that the ensemble LNRF-BRT and LNRFLMR models(AUC = 0.912(91.2%) and 0.907(90.7%), respectively) had high predictive accuracy than the LNRF model alone(AUC = 0.855(85.5%)). The FR and SCAI analyses showed that all models divided the parameter classes with high precision. Overall, our novel approach of combining multivariate and machine learning methods with bivariate models, radar remote sensing data and GIS proved to be a powerful tool for landslide susceptibility mapping.展开更多
In recent years,landslide susceptibility mapping has substantially improved with advances in machine learning.However,there are still challenges remain in landslide mapping due to the availability of limited inventory...In recent years,landslide susceptibility mapping has substantially improved with advances in machine learning.However,there are still challenges remain in landslide mapping due to the availability of limited inventory data.In this paper,a novel method that improves the performance of machine learning techniques is presented.The proposed method creates synthetic inventory data using Generative Adversarial Networks(GANs)for improving the prediction of landslides.In this research,landslide inventory data of 156 landslide locations were identified in Cameron Highlands,Malaysia,taken from previous projects the authors worked on.Elevation,slope,aspect,plan curvature,profile curvature,total curvature,lithology,land use and land cover(LULC),distance to the road,distance to the river,stream power index(SPI),sediment transport index(STI),terrain roughness index(TRI),topographic wetness index(TWI)and vegetation density are geo-environmental factors considered in this study based on suggestions from previous works on Cameron Highlands.To show the capability of GANs in improving landslide prediction models,this study tests the proposed GAN model with benchmark models namely Artificial Neural Network(ANN),Support Vector Machine(SVM),Decision Trees(DT),Random Forest(RF)and Bagging ensemble models with ANN and SVM models.These models were validated using the area under the receiver operating characteristic curve(AUROC).The DT,RF,SVM,ANN and Bagging ensemble could achieve the AUROC values of(0.90,0.94,0.86,0.69 and 0.82)for the training;and the AUROC of(0.76,0.81,0.85,0.72 and 0.75)for the test,subsequently.When using additional samples,the same models achieved the AUROC values of(0.92,0.94,0.88,0.75 and 0.84)for the training and(0.78,0.82,0.82,0.78 and 0.80)for the test,respectively.Using the additional samples improved the test accuracy of all the models except SVM.As a result,in data-scarce environments,this research showed that utilizing GANs to generate supplementary samples is promising because it can improve the predictive展开更多
In the Vehicular Ad-hoc NETworks(VANET),the collection and dissemination of life-threatening traffic event information by vehicles are of utmost importance.However,traditional VANETs face several security issues.We pr...In the Vehicular Ad-hoc NETworks(VANET),the collection and dissemination of life-threatening traffic event information by vehicles are of utmost importance.However,traditional VANETs face several security issues.We propose a new type of blockchain to resolve critical message dissemination issues in the VANET.We create a local blockchain for real-world event message exchange among vehicles within the boundary of a country,which is a new type of blockchain suitable for the VANET.We present a public blockchain that stores the node trustworthiness and message trustworthiness in a distributed ledger that is appropriate for secure message dissemination.展开更多
The rapid advancement of nanotechnology has sparked much interest in applying nanoscale perovskite materials for photodetection applications.These materials are promising candidates for next-generation photodetectors(...The rapid advancement of nanotechnology has sparked much interest in applying nanoscale perovskite materials for photodetection applications.These materials are promising candidates for next-generation photodetectors(PDs)due to their unique optoelectronic properties and flexible synthesis routes.This review explores the approaches used in the development and use of optoelectronic devices made of different nanoscale perovskite architectures,including quantum dots,nanosheets,nanorods,nanowires,and nanocrystals.Through a thorough analysis of recent literature,the review also addresses common issues like the mechanisms underlying the degradation of perovskite PDs and offers perspectives on potential solutions to improve stability and scalability that impede widespread implementation.In addition,it highlights that photodetection encompasses the detection of light fields in dimensions other than light intensity and suggests potential avenues for future research to overcome these obstacles and fully realize the potential of nanoscale perovskite materials in state-of-the-art photodetection systems.This review provides a comprehensive overview of nanoscale perovskite PDs and guides future research efforts towards improved performance and wider applicability,making it a valuable resource for researchers.展开更多
Gully erosion is a disruptive phenomenon which extensively affects the Iranian territory,especially in the Northern provinces.A number of studies have been recently undertaken to study this process and to predict it o...Gully erosion is a disruptive phenomenon which extensively affects the Iranian territory,especially in the Northern provinces.A number of studies have been recently undertaken to study this process and to predict it over space and ultimately,in a broader national effort,to limit its negative effects on local communities.We focused on the Bastam watershed where 9.3%of its surface is currently affected by gullying.Machine learning algorithms are currently under the magnifying glass across the geomorphological community for their high predictive ability.However,unlike the bivariate statistical models,their structure does not provide intuitive and quantifiable measures of environmental preconditioning factors.To cope with such weakness,we interpret preconditioning causes on the basis of a bivariate approach namely,Index of Entropy.And,we performed the susceptibility mapping procedure by testing three extensions of a decision tree model namely,Alternating Decision Tree(ADTree),Naive-Bayes tree(NBTree),and Logistic Model Tree(LMT).We dichotomized the gully information over space into gully presence/absence conditions,which we further explored in their calibration and validation stages.Being the presence/absence information and associated factors identical,the resulting differences are only due to the algorithmic structures of the three models we chose.Such differences are not significant in terms of performances;in fact,the three models produce outstanding predictive AUC measures(ADTree=0.922;NBTree=0.939;LMT=0.944).However,the associated mapping results depict very different patterns where only the LMT is associated with reasonable susceptibility patterns.This is a strong indication of what model combines best performance and mapping for any natural hazard-oriented application.展开更多
The innovation in technologies related to health facilities today is increasingly helping to manage patients with different diseases.The most fatal of these is the issue of heart disease that cannot be detected from a...The innovation in technologies related to health facilities today is increasingly helping to manage patients with different diseases.The most fatal of these is the issue of heart disease that cannot be detected from a naked eye,and attacks as soon as the human exceeds the allowed range of vital signs like pulse rate,body temperature,and blood pressure.The real challenge is to diagnose patients with more diagnostic accuracy and in a timely manner,followed by prescribing appropriate treatments and keeping prescription errors to a minimum.In developing countries,the domain of healthcare is progressing day by day using different Smart healthcare:emerging technologies like cloud computing,fog computing,and mobile computing.Electronic health records(EHRs)are used to manage the huge volume of data using cloud computing.That reduces the storage,processing,and retrieval cost as well as ensuring the availability of data.Machine learning procedures are used to extract hidden patterns and data analytics.In this research,a combination of cloud computing and machine learning algorithm Support vector machine(SVM)is used to predict heart diseases.Simulation results have shown that the proposed intelligent cloud-based heart disease prediction system empowered with a Support vector machine(SVM)-based system model gives 93.33%accuracy,which is better than previously published approaches.展开更多
Breast cancer is the most frequently detected tumor that eventually could result in a significant increase in female mortality globally.According to clinical statistics,one woman out of eight is under the threat of br...Breast cancer is the most frequently detected tumor that eventually could result in a significant increase in female mortality globally.According to clinical statistics,one woman out of eight is under the threat of breast cancer.Lifestyle and inheritance patterns may be a reason behind its spread among women.However,some preventive measures,such as tests and periodic clinical checks can mitigate its risk thereby,improving its survival chances substantially.Early diagnosis and initial stage treatment can help increase the survival rate.For that purpose,pathologists can gather support from nondestructive and efficient computer-aided diagnosis(CAD)systems.This study explores the breast cancer CAD method relying on multimodal medical imaging and decision-based fusion.In multimodal medical imaging fusion,a deep learning approach is applied,obtaining 97.5%accuracy with a 2.5%miss rate for breast cancer prediction.A deep extreme learning machine technique applied on feature-based data provided a 97.41%accuracy.Finally,decisionbased fusion applied to both breast cancer prediction models to diagnose its stages,resulted in an overall accuracy of 97.97%.The proposed system model provides more accurate results compared with other state-of-the-art approaches,rapidly diagnosing breast cancer to decrease its mortality rate.展开更多
In thiswork,the perovskite LaZnO_(3) was synthesized via sol-gel method and applied for photocatalytic treatment of sulfamethizole(SMZ)antibiotics under visible light activation.SMZ was almost completely degraded(99.2...In thiswork,the perovskite LaZnO_(3) was synthesized via sol-gel method and applied for photocatalytic treatment of sulfamethizole(SMZ)antibiotics under visible light activation.SMZ was almost completely degraded(99.2%±0.3%)within 4 hr by photocatalyst LaZnO_(3) at the optimal dosage of 1.1 g/L,with amineralization proportion of 58.7%±0.4%.The efficient performance of LaZnO_(3) can be attributed to itswide-range light absorption and the appropriate energy band edge levels,which facilitate the formation of active agents such as·O_(2)^(−),h^(+),and·OH.The integration of RP-HPLC/Q-TOF-MS and DFT-based computational techniques revealed three degradation pathways of SMZ,which were initiated by the deamination reaction at the aniline ring,the breakdown of the sulfonamidemoieties,and a process known as Smile-type rearrangement and SO2 intrusion.Corresponding toxicity of SMZ and the intermediateswere analyzed by quantitative structure activity relationship(QSAR),indicating the effectiveness of LaZnO_(3)-based photocatalysis in preventing secondary pollution of the intermediates to the ecosystem during the degradation process.The visible-light-activated photocatalyst LaZnO_(3) exhibited efficient performance in the occurrence of inorganic anions and maintained high durability across multiple recycling tests,making it a promising candidate for practical antibiotic treatment.展开更多
A numerical method is presented for the large deflection in elastic analysis of tensegrity structures including both geometric and material nonlinearities.The geometric nonlinearity is considered based on both total L...A numerical method is presented for the large deflection in elastic analysis of tensegrity structures including both geometric and material nonlinearities.The geometric nonlinearity is considered based on both total Lagrangian and updated Lagrangian formulations,while the material nonlinearity is treated through elastoplastic stress-strain relationship.The nonlinear equilibrium equations are solved using an incremental-iterative scheme in conjunction with the modified Newton-Raphson method.A computer program is developed to predict the mechanical responses of tensegrity systems under tensile,compressive and flexural loadings.Numerical results obtained are compared with those reported in the literature to demonstrate the accuracy and efficiency of the proposed program.The flexural behavior of the double layer quadruplex tensegrity grid is sufficiently good for lightweight large-span structural applications.On the other hand,its bending strength capacity is not sensitive to the self-stress level.展开更多
Williams syndrome(WS)is a rare multisystemic disorder caused by recurrent microdeletions on 7q11.23,characterized by intellectual disability,distinctive craniofacial and dental features,and cardiovascular problems.Pre...Williams syndrome(WS)is a rare multisystemic disorder caused by recurrent microdeletions on 7q11.23,characterized by intellectual disability,distinctive craniofacial and dental features,and cardiovascular problems.Previous studies have explored the roles of individual genes within these microdeletions in contributing to WS phenotypes.Here,we report five patients with WS with 1.4 Mb-1.5 Mb microdeletions that include RFC2,as well as one patient with a 167-kb microdeletion involving RFC2 and six patients with intragenic variants within RFC2.To investigate the potential involvement of RFC2 in WS pathogenicity,we generate a rfc2 knockout(KO)zebrafish using CRISPR-Cas9 technology.Additionally,we generate a KO zebrafish of its paralog gene,rfc5,to better understand the functions of these RFC genes in development and disease.Both rfc2 and rfc5 KO zebrafish exhibit similar phenotypes reminiscent of WS,including small head and brain,jaw and dental defects,and vascular problems.RNA-seq analysis reveals that genes associated with neural cell survival and differentiation are specifically affected in rfc2 KO zebrafish.In addition,heterozygous rfc2 KO adult zebrafish demonstrate an anxiety-like behavior with increased social cohesion.These results suggest that RFC2 may contribute to the pathogenicity of WS,as evidenced by the zebrafish model.展开更多
MXene has garnered widespread recognition in the scientific com-munity due to its remarkable properties,including excellent thermal stability,high conductivity,good hydrophilicity and dispersibility,easy processabilit...MXene has garnered widespread recognition in the scientific com-munity due to its remarkable properties,including excellent thermal stability,high conductivity,good hydrophilicity and dispersibility,easy processability,tunable surface properties,and admirable flexibility.MXenes have been categorized into different families based on the number of M and X layers in M_(n+1)X_(n),such as M_(2)X,M_(3)X_(2),M_(4)X_(3),and,recently,M_(5)X_(4).Among these families,M_(2)X and M_(3)X_(2),par-ticularly Ti_(3)C_(2),have been greatly explored while limited studies have been given to M_(5)X_(4)MXene synthesis.Meanwhile,studies on the M_(4)X_(3)MXene family have developed recently,hence,demanding a compilation of evaluated studies.Herein,this review provides a systematic overview of the latest advancements in M_(4)X_(3)MXenes,focusing on their properties and applications in energy storage devices.The objective of this review is to provide guidance to researchers on fostering M_(4)X_(3)MXene-based nanomaterials,not only for energy storage devices but also for broader applications.展开更多
Inspired by erythrocytes that contain oxygen-carrying hemoglobin(Hb)and that exhibit photo-driven activity,we introduce homogenous-sized erythrocyte-like Hb microgel(μGel)systems(5-6μm)that can(i)emit heat,(ii)suppl...Inspired by erythrocytes that contain oxygen-carrying hemoglobin(Hb)and that exhibit photo-driven activity,we introduce homogenous-sized erythrocyte-like Hb microgel(μGel)systems(5-6μm)that can(i)emit heat,(ii)supply oxygen,and(iii)generate reactive oxygen species(ROS;1O2)in response to near-infrared(NIR)laser irradiation.Hb μGels consist of Hb,bovine serum albumin(BSA),chlorin e6(Ce6)and erbium@lutetium upconverting nanoparticles(UCNPs;~35 nm)that effectively convert 808 nm NIR light to 660 nm visible light.These Hb μGels are capable of releasing oxygen to help generate sufficient reactive oxygen species(^(1)O_(2))from UCNPs/Ce6 under severely hypoxic condition upon NIR stimulation for efficient photodynamic activity.Moreover,the Hb μGels emit heat and increase surface temperature due to NIR light absorption by heme(iron protoporphyrin IX)and display photothermal activity.By changing the Hb/UCNP/Ce6 ratio and controlling the amount of NIR laser irradiation,it is possible to formulate bespoke Hb μGels with either photothermal or photodynamic activity or both in the context of combined therapeutic effect.These Hb μGels effectively suppress highly hypoxic 4T1 cell spheroid growth and xenograft mice tumors in vivo.展开更多
This study explores the impact of introducing vacancy in the transition metal layer of rationally designed Na_(0.6)[Ni_(0.3)Ru_(0.3)Mn_(0.4)]O_(2)(NRM)cathode material.The incorporation of Ru,Ni,and vacancy enhances t...This study explores the impact of introducing vacancy in the transition metal layer of rationally designed Na_(0.6)[Ni_(0.3)Ru_(0.3)Mn_(0.4)]O_(2)(NRM)cathode material.The incorporation of Ru,Ni,and vacancy enhances the structural stability during extensive cycling,increases the operation voltage,and induces a capacity increase while also activating oxygen redox,respectively,in Na_(0.7)[Ni_(0.2)V_(Ni0.1)Ru_(0.3)Mn_(0.4)]O_(2)(V-NRM)compound.Various analytical techniques including transmission electron microscopy,X-ray absorption near edge spectroscopy,operando X-ray diffraction,and operando differential electrochemical mass spectrometry are employed to assess changes in the average oxidation states and structural distortions.The results demonstrate that V-NRM exhibits higher capacity than NRM and maintains a moderate capacity retention of 81%after 100 cycles.Furthermore,the formation of additional lone-pair electrons in the O 2p orbital enables V-NRM to utilize more capacity from the oxygen redox validated by density functional calculation,leading to a widened dominance of the OP4 phase without releasing O_(2) gas.These findings offer valuable insights for the design of advanced high-capacity cathode materials with improved performance and sustainability in sodium-ion batteries.展开更多
This study presents a facile and rapid method for synthesizing novel Layered Double Hydroxide(LDH)nanoflakes,exploring their application as a photocatalyst,and investigating the influence of condensed phosphates'g...This study presents a facile and rapid method for synthesizing novel Layered Double Hydroxide(LDH)nanoflakes,exploring their application as a photocatalyst,and investigating the influence of condensed phosphates'geometric linearity on their photocatalytic properties.Herein,the Mg O film,obtained by plasma electrolysis of AZ31 Mg alloys,was modified by growing an LDH film,which was further functionalized using cyclic sodium hexametaphosphate(CP)and linear sodium tripolyphosphate(LP).CP acted as an enhancer for flake spacing within the LDH structure,while LP changed flake dispersion and orientation.Consequently,CP@LDH demonstrated exceptional efficiency in heterogeneous photocatalysis,effectively degrading organic dyes like Methylene blue(MB),Congo red(CR),and Methyl orange(MO).The unique cyclic structure of CP likely enhances surface reactions and improves the catalyst's interaction with dye molecules.Furthermore,the condensed phosphate structure contributes to a higher surface area and reactivity in CP@LDH,leading to its superior photocatalytic performance compared to LP@LDH.Specifically,LP@LDH demonstrated notable degradation efficiencies of 93.02%,92.89%,and 88.81%for MB,MO,and CR respectively,over a 40 min duration.The highest degradation efficiencies were observed in the case of the CP@LDH sample,reporting 99.99%for MB,98.88%for CR,and 99.70%for MO.This underscores the potential of CP@LDH as a highly effective photocatalyst for organic dye degradation,offering promising prospects for environmental remediation and water detoxification applications.展开更多
The Extended Kalman Filter(EKF)has received abundant attention with the growing demands for robotic localization.The EKF algorithm is more realistic in non-linear systems,which has an autonomous white noise in both th...The Extended Kalman Filter(EKF)has received abundant attention with the growing demands for robotic localization.The EKF algorithm is more realistic in non-linear systems,which has an autonomous white noise in both the system and the estimation model.Also,in the field of engineering,most systems are non-linear.Therefore,the EKF attracts more attention than the Kalman Filter(KF).In this paper,we propose an EKF-based localization algorithm by edge computing,and a mobile robot is used to update its location concerning the landmark.This localization algorithm aims to achieve a high level of accuracy and wider coverage.The proposed algorithm is helpful for the research related to the use of EKF localization algorithms.Simulation results demonstrate that,under the situations presented in the paper,the proposed localization algorithm is more accurate compared with the current state-of-the-art localization algorithms.展开更多
As the global electric vehicle market continues to grow,the recycling of Li-ion battery (LIB) becomes more important worldwide and the resynthesis of cathode materials would be the most value-added recycling approach ...As the global electric vehicle market continues to grow,the recycling of Li-ion battery (LIB) becomes more important worldwide and the resynthesis of cathode materials would be the most value-added recycling approach taking into account limited metal resources.Although resynthesized homogenous LiNi_(x)Co_(y)Mn_(z)O_(2)(NCM) from spent LIB leachate shows comparable battery performance to pristine NCM from virgin materials,there is general concern in its cycling performance.Here,we synthesize core–shell(CS) Ni-rich NCM,which consists of Ni-rich NCM as the core and NCM derived from the original or purified leachate of spent LIBs as the shell.Resynthesized CS Ni-rich NCM exhibits improved rate capability resulting from expanded interslab thickness in the NCM structure.CS Ni-rich NCM from purified LIB leachate shows improvement in cycling performance and thermal stability.It specifically delivers a capacity retention of 86.6%at a high temperature after 80 cycles compared to that (75.0%) of pristine CS Ni-rich NCM.These improvements are caused by a relatively high Mg content on the shell and the widespread distribution of Al through the CS structure.CS Ni-rich NCM derived from spent LIB leachate provides a new alternative approach to conventional LIB recycling methods,which would utilize efficiently limited metal resources for the sustainable LIB production.展开更多
Biochar(BC)has gained attention for removal of toxic elements(TEs)from aqueous media;however,pristine biochar often exhibits low adsorption capability.Thus,various modification strategies in BC have been developed to ...Biochar(BC)has gained attention for removal of toxic elements(TEs)from aqueous media;however,pristine biochar often exhibits low adsorption capability.Thus,various modification strategies in BC have been developed to improve its removal capability against TEs.Nanoscale zero-valent iron(nZVI)and iron oxides(FeOx)have been used as sorbents for TE removal.However,these materials are prone to agglomeration and also expensive,which make their usage limited for large-scale applications.The nZVI technical demerits could be resolved by the development of BC-based composite sorbents through the loading of nZVI or FeOx onto BC surface.Nano zero-valent iron modified BC(nZVIBC),FeOx-modified BC(FeOxBC)have attracted attention for their capability in removing pollutants from the aqueous phases.Nonetheless,a potential use of nZVIBC and FeOxBC for TE removal from aqueous environments has not been well-realized or reviewed.As such,this article reviews:(i)the preparation and characterization of nZVIBC and FeOxBC;(ii)the capacity of nZVIBC and FeOxBC for TE retention in line with their physicochemical properties,and(iii)TE removal mechanisms by nZVIBC and FeOxBC.Adopting nZVI and FeOx in BC increases its sporptive capability of TEs due to surface modifications in morphology,functional groups,and elemental composition.The combined effects of BC and nZVI,FeOx or Fe salts on the sorption of TEs are complex because they are very specific to TEs.This review identified significant opportunities for research and technol-ogy advancement of nZVIBC and FeOxBC as novel and effective sorbents for the remediation of TEs contaminated water.展开更多
文摘Application of biochar to soils changes soil physicochemical properties and stimulates the activities of soil microorganisms that influence soil quality and plant performance.Studying the response of soil microbial communities to biochar amendments is important for better understanding interactions of biochar with soil,as well as plants.However,the effect of biochar on soil microorganisms has received less attention than its influences on soil physicochemical properties.In this review,the following key questions are discussed:(i)how does biochar affect soil microbial activities,in particular soil carbon(C)mineralization,nutrient cycling,and enzyme activities?(ii)how do microorganisms respond to biochar amendment in contaminated soils?and(iii)what is the role of biochar as a growth promoter for soil microorganisms?Many studies have demonstrated that biochar-soil application enhances the soil microbial biomass with substantial changes in microbial community composition.Biochar amendment changes microbial habitats,directly or indirectly affects microbial metabolic activities,and modifies the soil microbial community in terms of their diversity and abundance.However,chemical properties of biochar,(especially pH and nutrient content),and physical properties such as pore size,pore volume,and specific surface area play significant roles in determining the efficacy of biochar on microbial performance as biochar provides suitable habitats for microorgan-isms.The mode of action of biochar leading to stimulation of microbial activities is complex and is influenced by the nature of biochar as well as soil conditions.
文摘The Ni-rich Li[Ni0.6Co0.2Mn0.2]O2 surface has been modified with H3PO4. After coating at 80 ℃, the products were heated further at a moderate temperature of 500 ℃ in air, when the added H3PO4 transformed to Li3PO4 after reacting with residual LiOH and Li2CO3 on the surface. A thin and uniform smooth nanolayer （〈 10 nm） was observed on the surface of Li[Ni0.6Co0.2Mn0.2]O2 as confirmed by transmission electron microscopy （TEM）. Time-of-flight secondary ion mass spectroscopic （ToF-SIMS） data exhibit the presence of LIP＋, LiPO-, and Li2PO2＋ fragments, indicating the formation of the Li3PO4 coating layer on the surface of the Li[Ni0.6Co0.2Mn0.2]O2. As a result, the amounts of residual lithium compounds, such as LiOH and Li2CO3, are significantly reduced. As a consequence, the LigPO4-coated Li[Ni0.6Co0.2Mn0.2]O2 exhibits noticeable improvement in capacity retention and rate capability due to the reduction of residual LiOH and Li2CO3. Further investigation of the extensively cycled electrodes by X-ray diffraction （XRD）, TEM, and ToF-SIMS demonstrated that the LiBPO4 coating layers have multi-functions： Absorption of water in the electrolyte that lowers the HF level, HF scavenging, and protection of the active materials from deleterious side reactions with the electrolyte during extensive cycling, enabling high capacity retention over 1,000 cycles.
文摘The effects of fertilization on activity and composition of soil microbial community depend on nutrient and water availability;however,the combination of these factors on the response of microorganisms was seldom studied.This study investigated the responses of soil microbial community and enzyme activities to changes in moisture along a gradient of soil fertility formed within a long-term(24 years)field experiment.Soils(0–20 cm)were sampled from the plots under four fertilizer treatments:i)unfertilized control(CK),ii)organic manure(M),iii)nitrogen,phosphorus,and potassium fertilizers(NPK),and iv)NPK plus M(NPK+M).The soils were incubated at three moisture levels:constant submergence,five submerging-draining cycles(S-D cycles),and constant moisture content at 40%water-holding capacity(low moisture).Compared with CK,fertilization increased soil organic carbon(SOC) by 30.1%–36.3%,total N by 27.3%–38.4%,available N by 35.9%–56.4%,available P by 61.4%–440.9%,and total P by 28.6%–102.9%.Soil fertility buffered the negative effects of moisture on enzyme activities and microbial community composition.Enzyme activities decreased in response to submergence and S-D cycles versus low moisture.Compared with low moisture,S-D cycles increased total phospholipid fatty acids(PLFAs)and actinomycete,fungal,and bacterial PLFAs.The increased level of PLFAs in the unfertilized soil after five S-D cycles was greater than that in the fertilized soil.Variations in soil microbial properties responding to moisture separated CK from the long-term fertilization treatments.The coefficients of variation of microbial properties were negatively correlated with SOC,total P,and available N.Soils with higher fertility maintained the original microbial properties more stable in response to changes in moisture compared to low-fertility soil.
基金supported by the Centre for Advanced Modelling and Geospatial Information Systems(CAMGIS),UTS under grant numbers 321740.2232335,323930,and 321740.2232357
文摘In this study, a novel approach of the landslide numerical risk factor(LNRF) bivariate model was used in ensemble with linear multivariate regression(LMR) and boosted regression tree(BRT) models, coupled with radar remote sensing data and geographic information system(GIS), for landslide susceptibility mapping(LSM) in the Gorganroud watershed, Iran. Fifteen topographic, hydrological, geological and environmental conditioning factors and a landslide inventory(70%, or 298 landslides) were used in mapping. Phased array-type L-band synthetic aperture radar data were used to extract topographic parameters. Coefficients of tolerance and variance inflation factor were used to determine the coherence among conditioning factors. Data for the landslide inventory map were obtained from various resources, such as Iranian Landslide Working Party(ILWP), Forestry, Rangeland and Watershed Organisation(FRWO), extensive field surveys, interpretation of aerial photos and satellite images, and radar data. Of the total data, 30% were used to validate LSMs, using area under the curve(AUC), frequency ratio(FR) and seed cell area index(SCAI).Normalised difference vegetation index, land use/land cover and slope degree in BRT model elevation, rainfall and distance from stream were found to be important factors and were given the highest weightage in modelling. Validation results using AUC showed that the ensemble LNRF-BRT and LNRFLMR models(AUC = 0.912(91.2%) and 0.907(90.7%), respectively) had high predictive accuracy than the LNRF model alone(AUC = 0.855(85.5%)). The FR and SCAI analyses showed that all models divided the parameter classes with high precision. Overall, our novel approach of combining multivariate and machine learning methods with bivariate models, radar remote sensing data and GIS proved to be a powerful tool for landslide susceptibility mapping.
基金This research is funded by the Centre for Advanced Modeling and Geospatial Information Systems(CAMGIS),Faculty of Engineering and Information Technology,the University of Technology Sydney,Australia.
文摘In recent years,landslide susceptibility mapping has substantially improved with advances in machine learning.However,there are still challenges remain in landslide mapping due to the availability of limited inventory data.In this paper,a novel method that improves the performance of machine learning techniques is presented.The proposed method creates synthetic inventory data using Generative Adversarial Networks(GANs)for improving the prediction of landslides.In this research,landslide inventory data of 156 landslide locations were identified in Cameron Highlands,Malaysia,taken from previous projects the authors worked on.Elevation,slope,aspect,plan curvature,profile curvature,total curvature,lithology,land use and land cover(LULC),distance to the road,distance to the river,stream power index(SPI),sediment transport index(STI),terrain roughness index(TRI),topographic wetness index(TWI)and vegetation density are geo-environmental factors considered in this study based on suggestions from previous works on Cameron Highlands.To show the capability of GANs in improving landslide prediction models,this study tests the proposed GAN model with benchmark models namely Artificial Neural Network(ANN),Support Vector Machine(SVM),Decision Trees(DT),Random Forest(RF)and Bagging ensemble models with ANN and SVM models.These models were validated using the area under the receiver operating characteristic curve(AUROC).The DT,RF,SVM,ANN and Bagging ensemble could achieve the AUROC values of(0.90,0.94,0.86,0.69 and 0.82)for the training;and the AUROC of(0.76,0.81,0.85,0.72 and 0.75)for the test,subsequently.When using additional samples,the same models achieved the AUROC values of(0.92,0.94,0.88,0.75 and 0.84)for the training and(0.78,0.82,0.82,0.78 and 0.80)for the test,respectively.Using the additional samples improved the test accuracy of all the models except SVM.As a result,in data-scarce environments,this research showed that utilizing GANs to generate supplementary samples is promising because it can improve the predictive
基金This research was supported in part by Basic Science Research Program through National Research Foundation of Korea(NRF)funded by the Ministry of Education,Science and Technology(2013R1A1A2012006,2015R1D1A1A01058595)This research was supported in part by the MSIP(Ministry of Science and ICT),Korea,under the ITRC(Information Technology Research Center)support program(IITP-2019-2016-0-00313)supervised by the IITP(Institute for Information and Communications Technology Planning&Evaluation)This work was supported in part by the Brain Korea 21 Plus Program(No.22A20130012814)funded by the National Research Foundation of Korea(NRF).
文摘In the Vehicular Ad-hoc NETworks(VANET),the collection and dissemination of life-threatening traffic event information by vehicles are of utmost importance.However,traditional VANETs face several security issues.We propose a new type of blockchain to resolve critical message dissemination issues in the VANET.We create a local blockchain for real-world event message exchange among vehicles within the boundary of a country,which is a new type of blockchain suitable for the VANET.We present a public blockchain that stores the node trustworthiness and message trustworthiness in a distributed ledger that is appropriate for secure message dissemination.
基金supported by the National Research Foundation of Korea(NRF)grant funded by the Korean government(MSIT)(No.RS-2022–00165798)Anhui Natural Science Foundation(No.2308085MF211)The authors extend their appreciation to the Deanship of Research and Graduate Studies at King Khalid University for funding this work through Large Research Project under Grant Number(R.G.P.2/491/45).
文摘The rapid advancement of nanotechnology has sparked much interest in applying nanoscale perovskite materials for photodetection applications.These materials are promising candidates for next-generation photodetectors(PDs)due to their unique optoelectronic properties and flexible synthesis routes.This review explores the approaches used in the development and use of optoelectronic devices made of different nanoscale perovskite architectures,including quantum dots,nanosheets,nanorods,nanowires,and nanocrystals.Through a thorough analysis of recent literature,the review also addresses common issues like the mechanisms underlying the degradation of perovskite PDs and offers perspectives on potential solutions to improve stability and scalability that impede widespread implementation.In addition,it highlights that photodetection encompasses the detection of light fields in dimensions other than light intensity and suggests potential avenues for future research to overcome these obstacles and fully realize the potential of nanoscale perovskite materials in state-of-the-art photodetection systems.This review provides a comprehensive overview of nanoscale perovskite PDs and guides future research efforts towards improved performance and wider applicability,making it a valuable resource for researchers.
文摘Gully erosion is a disruptive phenomenon which extensively affects the Iranian territory,especially in the Northern provinces.A number of studies have been recently undertaken to study this process and to predict it over space and ultimately,in a broader national effort,to limit its negative effects on local communities.We focused on the Bastam watershed where 9.3%of its surface is currently affected by gullying.Machine learning algorithms are currently under the magnifying glass across the geomorphological community for their high predictive ability.However,unlike the bivariate statistical models,their structure does not provide intuitive and quantifiable measures of environmental preconditioning factors.To cope with such weakness,we interpret preconditioning causes on the basis of a bivariate approach namely,Index of Entropy.And,we performed the susceptibility mapping procedure by testing three extensions of a decision tree model namely,Alternating Decision Tree(ADTree),Naive-Bayes tree(NBTree),and Logistic Model Tree(LMT).We dichotomized the gully information over space into gully presence/absence conditions,which we further explored in their calibration and validation stages.Being the presence/absence information and associated factors identical,the resulting differences are only due to the algorithmic structures of the three models we chose.Such differences are not significant in terms of performances;in fact,the three models produce outstanding predictive AUC measures(ADTree=0.922;NBTree=0.939;LMT=0.944).However,the associated mapping results depict very different patterns where only the LMT is associated with reasonable susceptibility patterns.This is a strong indication of what model combines best performance and mapping for any natural hazard-oriented application.
文摘The innovation in technologies related to health facilities today is increasingly helping to manage patients with different diseases.The most fatal of these is the issue of heart disease that cannot be detected from a naked eye,and attacks as soon as the human exceeds the allowed range of vital signs like pulse rate,body temperature,and blood pressure.The real challenge is to diagnose patients with more diagnostic accuracy and in a timely manner,followed by prescribing appropriate treatments and keeping prescription errors to a minimum.In developing countries,the domain of healthcare is progressing day by day using different Smart healthcare:emerging technologies like cloud computing,fog computing,and mobile computing.Electronic health records(EHRs)are used to manage the huge volume of data using cloud computing.That reduces the storage,processing,and retrieval cost as well as ensuring the availability of data.Machine learning procedures are used to extract hidden patterns and data analytics.In this research,a combination of cloud computing and machine learning algorithm Support vector machine(SVM)is used to predict heart diseases.Simulation results have shown that the proposed intelligent cloud-based heart disease prediction system empowered with a Support vector machine(SVM)-based system model gives 93.33%accuracy,which is better than previously published approaches.
基金supported by the KIAS(Research No.CG076601)in part by Sejong University Faculty Research Fund.
文摘Breast cancer is the most frequently detected tumor that eventually could result in a significant increase in female mortality globally.According to clinical statistics,one woman out of eight is under the threat of breast cancer.Lifestyle and inheritance patterns may be a reason behind its spread among women.However,some preventive measures,such as tests and periodic clinical checks can mitigate its risk thereby,improving its survival chances substantially.Early diagnosis and initial stage treatment can help increase the survival rate.For that purpose,pathologists can gather support from nondestructive and efficient computer-aided diagnosis(CAD)systems.This study explores the breast cancer CAD method relying on multimodal medical imaging and decision-based fusion.In multimodal medical imaging fusion,a deep learning approach is applied,obtaining 97.5%accuracy with a 2.5%miss rate for breast cancer prediction.A deep extreme learning machine technique applied on feature-based data provided a 97.41%accuracy.Finally,decisionbased fusion applied to both breast cancer prediction models to diagnose its stages,resulted in an overall accuracy of 97.97%.The proposed system model provides more accurate results compared with other state-of-the-art approaches,rapidly diagnosing breast cancer to decrease its mortality rate.
文摘In thiswork,the perovskite LaZnO_(3) was synthesized via sol-gel method and applied for photocatalytic treatment of sulfamethizole(SMZ)antibiotics under visible light activation.SMZ was almost completely degraded(99.2%±0.3%)within 4 hr by photocatalyst LaZnO_(3) at the optimal dosage of 1.1 g/L,with amineralization proportion of 58.7%±0.4%.The efficient performance of LaZnO_(3) can be attributed to itswide-range light absorption and the appropriate energy band edge levels,which facilitate the formation of active agents such as·O_(2)^(−),h^(+),and·OH.The integration of RP-HPLC/Q-TOF-MS and DFT-based computational techniques revealed three degradation pathways of SMZ,which were initiated by the deamination reaction at the aniline ring,the breakdown of the sulfonamidemoieties,and a process known as Smile-type rearrangement and SO2 intrusion.Corresponding toxicity of SMZ and the intermediateswere analyzed by quantitative structure activity relationship(QSAR),indicating the effectiveness of LaZnO_(3)-based photocatalysis in preventing secondary pollution of the intermediates to the ecosystem during the degradation process.The visible-light-activated photocatalyst LaZnO_(3) exhibited efficient performance in the occurrence of inorganic anions and maintained high durability across multiple recycling tests,making it a promising candidate for practical antibiotic treatment.
基金support of the research reported here by Basic Science Research Program through the National Research Foundation of Korea (NRF)funded by the Ministry of Education, Science and Technology (NRF2010-0019373)
文摘A numerical method is presented for the large deflection in elastic analysis of tensegrity structures including both geometric and material nonlinearities.The geometric nonlinearity is considered based on both total Lagrangian and updated Lagrangian formulations,while the material nonlinearity is treated through elastoplastic stress-strain relationship.The nonlinear equilibrium equations are solved using an incremental-iterative scheme in conjunction with the modified Newton-Raphson method.A computer program is developed to predict the mechanical responses of tensegrity systems under tensile,compressive and flexural loadings.Numerical results obtained are compared with those reported in the literature to demonstrate the accuracy and efficiency of the proposed program.The flexural behavior of the double layer quadruplex tensegrity grid is sufficiently good for lightweight large-span structural applications.On the other hand,its bending strength capacity is not sensitive to the self-stress level.
基金supported by the National Research Foundation of Korea grant funded by the Korean government(MIST)(2020R1A5A8017671,2022R1A2C100677813,and RS-2024-00349650)。
文摘Williams syndrome(WS)is a rare multisystemic disorder caused by recurrent microdeletions on 7q11.23,characterized by intellectual disability,distinctive craniofacial and dental features,and cardiovascular problems.Previous studies have explored the roles of individual genes within these microdeletions in contributing to WS phenotypes.Here,we report five patients with WS with 1.4 Mb-1.5 Mb microdeletions that include RFC2,as well as one patient with a 167-kb microdeletion involving RFC2 and six patients with intragenic variants within RFC2.To investigate the potential involvement of RFC2 in WS pathogenicity,we generate a rfc2 knockout(KO)zebrafish using CRISPR-Cas9 technology.Additionally,we generate a KO zebrafish of its paralog gene,rfc5,to better understand the functions of these RFC genes in development and disease.Both rfc2 and rfc5 KO zebrafish exhibit similar phenotypes reminiscent of WS,including small head and brain,jaw and dental defects,and vascular problems.RNA-seq analysis reveals that genes associated with neural cell survival and differentiation are specifically affected in rfc2 KO zebrafish.In addition,heterozygous rfc2 KO adult zebrafish demonstrate an anxiety-like behavior with increased social cohesion.These results suggest that RFC2 may contribute to the pathogenicity of WS,as evidenced by the zebrafish model.
基金supported by the Hong Kong Research Grants Council(Project Number CityU 11218420)the Deanship of Scientific Research at King Khalid University Saudi Arabia for funding through research groups program under Grant Number R.G.P.2/593/44.
文摘MXene has garnered widespread recognition in the scientific com-munity due to its remarkable properties,including excellent thermal stability,high conductivity,good hydrophilicity and dispersibility,easy processability,tunable surface properties,and admirable flexibility.MXenes have been categorized into different families based on the number of M and X layers in M_(n+1)X_(n),such as M_(2)X,M_(3)X_(2),M_(4)X_(3),and,recently,M_(5)X_(4).Among these families,M_(2)X and M_(3)X_(2),par-ticularly Ti_(3)C_(2),have been greatly explored while limited studies have been given to M_(5)X_(4)MXene synthesis.Meanwhile,studies on the M_(4)X_(3)MXene family have developed recently,hence,demanding a compilation of evaluated studies.Herein,this review provides a systematic overview of the latest advancements in M_(4)X_(3)MXenes,focusing on their properties and applications in energy storage devices.The objective of this review is to provide guidance to researchers on fostering M_(4)X_(3)MXene-based nanomaterials,not only for energy storage devices but also for broader applications.
基金This work was supported by a National Research Foundation of Korea(NRF)grants funded by the Korean government(No.NRF-2019R1A5A2027340)the Bio&Medical Technology Development Program of the National Research Foundation(NRF)funded by the Korean government(MSIT)(No.NRF-2022M3A9G8017220).
文摘Inspired by erythrocytes that contain oxygen-carrying hemoglobin(Hb)and that exhibit photo-driven activity,we introduce homogenous-sized erythrocyte-like Hb microgel(μGel)systems(5-6μm)that can(i)emit heat,(ii)supply oxygen,and(iii)generate reactive oxygen species(ROS;1O2)in response to near-infrared(NIR)laser irradiation.Hb μGels consist of Hb,bovine serum albumin(BSA),chlorin e6(Ce6)and erbium@lutetium upconverting nanoparticles(UCNPs;~35 nm)that effectively convert 808 nm NIR light to 660 nm visible light.These Hb μGels are capable of releasing oxygen to help generate sufficient reactive oxygen species(^(1)O_(2))from UCNPs/Ce6 under severely hypoxic condition upon NIR stimulation for efficient photodynamic activity.Moreover,the Hb μGels emit heat and increase surface temperature due to NIR light absorption by heme(iron protoporphyrin IX)and display photothermal activity.By changing the Hb/UCNP/Ce6 ratio and controlling the amount of NIR laser irradiation,it is possible to formulate bespoke Hb μGels with either photothermal or photodynamic activity or both in the context of combined therapeutic effect.These Hb μGels effectively suppress highly hypoxic 4T1 cell spheroid growth and xenograft mice tumors in vivo.
基金supported by Basic Science Research Program through the National Research Foundation of Korea(NRF)funded by the Ministry of Education,Science and Technology(NRF-2020R1A6A1A03043435,NRF-2023R1A2C2003210,and NRF-2022M3H4A1A04096478)by Technology Innovation Program(Alchemist Project,20012196,Al based supercritical materials discovery)funded by the Ministry of Trade,Industry&Energy,Korea.support from the“Bundesministerium fur Bildung und Forschung”(BMBF)and the computing time granted through JARA-HPC on the supercomputer JURECA at Forschungszentrum Julich.
文摘This study explores the impact of introducing vacancy in the transition metal layer of rationally designed Na_(0.6)[Ni_(0.3)Ru_(0.3)Mn_(0.4)]O_(2)(NRM)cathode material.The incorporation of Ru,Ni,and vacancy enhances the structural stability during extensive cycling,increases the operation voltage,and induces a capacity increase while also activating oxygen redox,respectively,in Na_(0.7)[Ni_(0.2)V_(Ni0.1)Ru_(0.3)Mn_(0.4)]O_(2)(V-NRM)compound.Various analytical techniques including transmission electron microscopy,X-ray absorption near edge spectroscopy,operando X-ray diffraction,and operando differential electrochemical mass spectrometry are employed to assess changes in the average oxidation states and structural distortions.The results demonstrate that V-NRM exhibits higher capacity than NRM and maintains a moderate capacity retention of 81%after 100 cycles.Furthermore,the formation of additional lone-pair electrons in the O 2p orbital enables V-NRM to utilize more capacity from the oxygen redox validated by density functional calculation,leading to a widened dominance of the OP4 phase without releasing O_(2) gas.These findings offer valuable insights for the design of advanced high-capacity cathode materials with improved performance and sustainability in sodium-ion batteries.
基金the National Research Foundation of Korea(NRF)funded by the Korean Government(MSIT)(No.2022R1A2C1006743)。
文摘This study presents a facile and rapid method for synthesizing novel Layered Double Hydroxide(LDH)nanoflakes,exploring their application as a photocatalyst,and investigating the influence of condensed phosphates'geometric linearity on their photocatalytic properties.Herein,the Mg O film,obtained by plasma electrolysis of AZ31 Mg alloys,was modified by growing an LDH film,which was further functionalized using cyclic sodium hexametaphosphate(CP)and linear sodium tripolyphosphate(LP).CP acted as an enhancer for flake spacing within the LDH structure,while LP changed flake dispersion and orientation.Consequently,CP@LDH demonstrated exceptional efficiency in heterogeneous photocatalysis,effectively degrading organic dyes like Methylene blue(MB),Congo red(CR),and Methyl orange(MO).The unique cyclic structure of CP likely enhances surface reactions and improves the catalyst's interaction with dye molecules.Furthermore,the condensed phosphate structure contributes to a higher surface area and reactivity in CP@LDH,leading to its superior photocatalytic performance compared to LP@LDH.Specifically,LP@LDH demonstrated notable degradation efficiencies of 93.02%,92.89%,and 88.81%for MB,MO,and CR respectively,over a 40 min duration.The highest degradation efficiencies were observed in the case of the CP@LDH sample,reporting 99.99%for MB,98.88%for CR,and 99.70%for MO.This underscores the potential of CP@LDH as a highly effective photocatalyst for organic dye degradation,offering promising prospects for environmental remediation and water detoxification applications.
基金The work of J.-H.Lee was supported by the Cross-Ministry Giga KOREA Project grant funded by the Korea Government(MSIT)(No.GK20P0400,Development of Mobile Edge Computing Platform Technology for URLLC Services).
文摘The Extended Kalman Filter(EKF)has received abundant attention with the growing demands for robotic localization.The EKF algorithm is more realistic in non-linear systems,which has an autonomous white noise in both the system and the estimation model.Also,in the field of engineering,most systems are non-linear.Therefore,the EKF attracts more attention than the Kalman Filter(KF).In this paper,we propose an EKF-based localization algorithm by edge computing,and a mobile robot is used to update its location concerning the landmark.This localization algorithm aims to achieve a high level of accuracy and wider coverage.The proposed algorithm is helpful for the research related to the use of EKF localization algorithms.Simulation results demonstrate that,under the situations presented in the paper,the proposed localization algorithm is more accurate compared with the current state-of-the-art localization algorithms.
基金supported by Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Science and ICT (2023R1A2C100571511,RS-2023-00254424)the Ministry of Education(2020R1A6A1A03038540)。
文摘As the global electric vehicle market continues to grow,the recycling of Li-ion battery (LIB) becomes more important worldwide and the resynthesis of cathode materials would be the most value-added recycling approach taking into account limited metal resources.Although resynthesized homogenous LiNi_(x)Co_(y)Mn_(z)O_(2)(NCM) from spent LIB leachate shows comparable battery performance to pristine NCM from virgin materials,there is general concern in its cycling performance.Here,we synthesize core–shell(CS) Ni-rich NCM,which consists of Ni-rich NCM as the core and NCM derived from the original or purified leachate of spent LIBs as the shell.Resynthesized CS Ni-rich NCM exhibits improved rate capability resulting from expanded interslab thickness in the NCM structure.CS Ni-rich NCM from purified LIB leachate shows improvement in cycling performance and thermal stability.It specifically delivers a capacity retention of 86.6%at a high temperature after 80 cycles compared to that (75.0%) of pristine CS Ni-rich NCM.These improvements are caused by a relatively high Mg content on the shell and the widespread distribution of Al through the CS structure.CS Ni-rich NCM derived from spent LIB leachate provides a new alternative approach to conventional LIB recycling methods,which would utilize efficiently limited metal resources for the sustainable LIB production.
文摘Biochar(BC)has gained attention for removal of toxic elements(TEs)from aqueous media;however,pristine biochar often exhibits low adsorption capability.Thus,various modification strategies in BC have been developed to improve its removal capability against TEs.Nanoscale zero-valent iron(nZVI)and iron oxides(FeOx)have been used as sorbents for TE removal.However,these materials are prone to agglomeration and also expensive,which make their usage limited for large-scale applications.The nZVI technical demerits could be resolved by the development of BC-based composite sorbents through the loading of nZVI or FeOx onto BC surface.Nano zero-valent iron modified BC(nZVIBC),FeOx-modified BC(FeOxBC)have attracted attention for their capability in removing pollutants from the aqueous phases.Nonetheless,a potential use of nZVIBC and FeOxBC for TE removal from aqueous environments has not been well-realized or reviewed.As such,this article reviews:(i)the preparation and characterization of nZVIBC and FeOxBC;(ii)the capacity of nZVIBC and FeOxBC for TE retention in line with their physicochemical properties,and(iii)TE removal mechanisms by nZVIBC and FeOxBC.Adopting nZVI and FeOx in BC increases its sporptive capability of TEs due to surface modifications in morphology,functional groups,and elemental composition.The combined effects of BC and nZVI,FeOx or Fe salts on the sorption of TEs are complex because they are very specific to TEs.This review identified significant opportunities for research and technol-ogy advancement of nZVIBC and FeOxBC as novel and effective sorbents for the remediation of TEs contaminated water.
