The traditional EnFCM(Enhanced fuzzy C-means)algorithm only considers the grey-scale features in image segmentation,resulting in less than satisfactory results when the algorithm is used for remote sensing woodland im...The traditional EnFCM(Enhanced fuzzy C-means)algorithm only considers the grey-scale features in image segmentation,resulting in less than satisfactory results when the algorithm is used for remote sensing woodland image segmentation and extraction.An EnFCM remote sensing forest land extraction method based on PCA multi-feature fusion was proposed.Firstly,histogram equalization was applied to improve the image contrast.Secondly,the texture and edge features of the image were extracted,and a multi-feature fused pixel image was generated using the PCA technique.Moreover,the fused feature was used as a feature constraint to measure the difference of pixels instead of a single grey-scale feature.Finally,an improved feature distance metric calculated the similarity between the pixel points and the cluster center to complete the cluster segmentation.The experimental results showed that the error was between 1.5%and 4.0%compared with the forested area counted by experts’hand-drawing,which could obtain a high accuracy segmentation and extraction result.展开更多
Relation extraction plays a crucial role in numerous downstream tasks.Dialogue relation extraction focuses on identifying relations between two arguments within a given dialogue.To tackle the problem of low informatio...Relation extraction plays a crucial role in numerous downstream tasks.Dialogue relation extraction focuses on identifying relations between two arguments within a given dialogue.To tackle the problem of low information density in dialogues,methods based on trigger enhancement have been proposed,yielding positive results.However,trigger enhancement faces challenges,which cause suboptimal model performance.First,the proportion of annotated triggers is low in DialogRE.Second,feature representations of triggers and arguments often contain conflicting information.In this paper,we propose a novel Multi-Feature Filtering and Fusion trigger enhancement approach to overcome these limitations.We first obtain representations of arguments,and triggers that contain rich semantic information through attention and gate methods.Then,we design a feature filtering mechanism that eliminates conflicting features in the encoding of trigger prototype representations and their corresponding argument pairs.Additionally,we utilize large language models to create prompts based on Chain-of-Thought and In-context Learning for automated trigger extraction.Experiments show that our model increases the average F1 score by 1.3%in the dialogue relation extraction task.Ablation and case studies confirm the effectiveness of our model.Furthermore,the feature filtering method effectively integrates with other trigger enhancement models,enhancing overall performance and demonstrating its ability to resolve feature conflicts.展开更多
Caused by the environment clutter,the radar false alarm plots are unavoidable.Suppressing false alarm points has always been a key issue in Radar plots procession.In this paper,a radar false alarm plots elimination me...Caused by the environment clutter,the radar false alarm plots are unavoidable.Suppressing false alarm points has always been a key issue in Radar plots procession.In this paper,a radar false alarm plots elimination method based on multi-feature extraction and classification is proposed to effectively eliminate false alarm plots.Firstly,the density based spatial clustering of applications with noise(DBSCAN)algorithm is used to cluster the radar echo data processed by constant false-alarm rate(CFAR).The multi-features including the scale features,time domain features and transform domain features are extracted.Secondly,a feature evaluation method combining pearson correlation coefficient(PCC)and entropy weight method(EWM)is proposed to evaluate interrelation among features,effective feature combination sets are selected as inputs of the classifier.Finally,False alarm plots classified as clutters are eliminated.The experimental results show that proposed method can eliminate about 90%false alarm plots with less target loss rate.展开更多
This study proposes a multi-scene smoke detection algorithm based on a multi-feature extraction method to address the problems of varying smoke shapes in different scenes,difficulty in locating and detecting transluce...This study proposes a multi-scene smoke detection algorithm based on a multi-feature extraction method to address the problems of varying smoke shapes in different scenes,difficulty in locating and detecting translucent smoke,and variable smoke scales.First,the convolution module of feature extraction in YOLOv5s backbone network is replaced with asymmetric convolution block re-parameterization convolution to improve the detection of different shapes of smoke.Then,coordinate attention mechanism is introduced in the deeper layer of the backbone network to further improve the localization of translucent smoke.Finally,the detection of smoke at different scales is further improved by using the feature pyramid convolution module instead of the standard convolution module of the feature pyramid in the model.The experimental results demonstrate the feasibility and superiority of the proposed model for multi-scene smoke detection.展开更多
In the international shipping industry, digital intelligence transformation has become essential, with both governments and enterprises actively working to integrate diverse datasets. The domain of maritime and shippi...In the international shipping industry, digital intelligence transformation has become essential, with both governments and enterprises actively working to integrate diverse datasets. The domain of maritime and shipping is characterized by a vast array of document types, filled with complex, large-scale, and often chaotic knowledge and relationships. Effectively managing these documents is crucial for developing a Large Language Model (LLM) in the maritime domain, enabling practitioners to access and leverage valuable information. A Knowledge Graph (KG) offers a state-of-the-art solution for enhancing knowledge retrieval, providing more accurate responses and enabling context-aware reasoning. This paper presents a framework for utilizing maritime and shipping documents to construct a knowledge graph using GraphRAG, a hybrid tool combining graph-based retrieval and generation capabilities. The extraction of entities and relationships from these documents and the KG construction process are detailed. Furthermore, the KG is integrated with an LLM to develop a Q&A system, demonstrating that the system significantly improves answer accuracy compared to traditional LLMs. Additionally, the KG construction process is up to 50% faster than conventional LLM-based approaches, underscoring the efficiency of our method. This study provides a promising approach to digital intelligence in shipping, advancing knowledge accessibility and decision-making.展开更多
Solvent extraction is the main method used to separate and purify rare earth elements.In the process of rare earths extraction,emulsification often generated due to the instability of the aqueous and organic phases or...Solvent extraction is the main method used to separate and purify rare earth elements.In the process of rare earths extraction,emulsification often generated due to the instability of the aqueous and organic phases or improper operating conditions.Once emulsification occurs,it would not only lead to low rare earths recovery efficiency,small product quantities,high production costs and the losing of extractant and rare earth resources,but also result in serious environmental pollution.Therefore,it is very important to study the micro-mechanisms of emulsification and establish new methods to prevent emulsification at the source.In this paper,possible factors resulting in emulsification,such as the compositions and properties of the organic and aqueous phases,the operating conditions of the rare earths extraction are reviewed.The micro-mechanisms of emulsification are summarized basing on the microscopic structures in the bulk phase,aggregations of the extractants at the organic-aqueous interface,spectral characterizations and computational simulations.On this basis,new formation mechanisms are proposed for emulsification.Preliminary explorations are employed to verify the correctness of these new viewpoints.Finally,future directions for studies of the emulsification micro-mechanism are proposed.This study provides a theoretical basis for further understanding the micro-mechanisms of interfacial instability resulting in emulsification in the process of rare earths extraction.展开更多
Background:Ampelopsis grossedentata,vine tea,which is the tea alternative beverages in China.In vine tea processing,a large amount of broken tea is produced,which has low commercial value.Methods:This study investigat...Background:Ampelopsis grossedentata,vine tea,which is the tea alternative beverages in China.In vine tea processing,a large amount of broken tea is produced,which has low commercial value.Methods:This study investigates the influence of different extraction methods(room temperature water extraction,boiling water extraction,ultrasonic-assisted room temperature water extraction,and ultrasonic-assisted boiling water extraction,referred to as room temperature water extraction(RE),boiling water extraction(BE),ultrasonic assistance at room temperature water extraction(URE),and ultrasonic assistance in boiling water extraction(UBE))on the yield,dihydromyricetin(DMY)content,free amino acid composition,volatile aroma components,and antioxidant properties of vine tea extracts.Results:A notable influence of extraction temperature on the yield of vine tea extracts(P<0.05),with BE yielding the highest at 43.13±0.26%,higher than that of RE(34.29±0.81%).Ultrasound-assisted extraction significantly increased the DMY content of the extracts(P<0.05),whereas DMY content in the RE extracts was 59.94±1.70%,that of URE reached 66.14±2.78%.Analysis revealed 17 amino acids,with L-serine and aspartic acid being the most abundant in the extracts,nevertheless ultrasound-assisted extraction reduced total free amino acid content.Gas chromatography-mass spectrometry analysis demonstrated an increase in the diversity and quantity of compounds in the vine tea water extracts obtained through ultrasonic-assisted extraction.Specifically,69 and 68 volatile compounds were found in URE and UBE extracts,which were higher than the number found in RE and BE extracts.In vitro,antioxidant activity assessments revealed varying antioxidant capacities among different extraction methods,with RE exhibiting the highest DPPH scavenging rate,URE leading in ABTS•+free radical scavenging,and BE demonstrating superior ferric ion reducing antioxidant activity.Conclusion:The findings suggest that extraction methods significantly influence the chemical composition and antioxidant properties of vine tea extracts.Ultrasonic-assisted extraction proved instrumental in elevating the DMY content in vine tea extracts,thereby enriching its flavor profile while maintaining its antioxidant properties.展开更多
This study aimed to investigate the effect of ultrasound-assisted alkaline extraction(UAE)(at 20 kHz and different powers of 0,200,300,400,500 and 600 W for 10 min)on the yield,structure and emulsifying properties of ...This study aimed to investigate the effect of ultrasound-assisted alkaline extraction(UAE)(at 20 kHz and different powers of 0,200,300,400,500 and 600 W for 10 min)on the yield,structure and emulsifying properties of chickpea protein isolate(CPI).Compared with the non-ultrasound group,ultrasound treatment at 400 W resulted in the largest increase in CPI yield,and both the particle size and turbidity decreased with increasing ultrasound power from 0 to 400 W.The scanning electron microscope results showed a uniform structural distribution of CPI.Moreover,itsα-helix content increased,β-sheet content decreased,and total sulfhydryl group content and endogenous fluorescence intensity rose,illustrating that UAE changed the secondary and tertiary structure of CPI.At 400 W,the solubility of the emulsion increased to 63.18%,and the best emulsifying properties were obtained;the emulsifying activity index(EAI)and emulsifying stability index(ESI)increased by 85.42%and 46.78%,respectively.Furthermore,the emulsion droplets formed were smaller and more uniform.In conclusion,proper UAE power conditions increased the extraction yield and protein content of CPI,and effectively improved its structure and emulsifying characteristics.展开更多
With the rapid expansion of social media,analyzing emotions and their causes in texts has gained significant importance.Emotion-cause pair extraction enables the identification of causal relationships between emotions...With the rapid expansion of social media,analyzing emotions and their causes in texts has gained significant importance.Emotion-cause pair extraction enables the identification of causal relationships between emotions and their triggers within a text,facilitating a deeper understanding of expressed sentiments and their underlying reasons.This comprehension is crucial for making informed strategic decisions in various business and societal contexts.However,recent research approaches employing multi-task learning frameworks for modeling often face challenges such as the inability to simultaneouslymodel extracted features and their interactions,or inconsistencies in label prediction between emotion-cause pair extraction and independent assistant tasks like emotion and cause extraction.To address these issues,this study proposes an emotion-cause pair extraction methodology that incorporates joint feature encoding and task alignment mechanisms.The model consists of two primary components:First,joint feature encoding simultaneously generates features for emotion-cause pairs and clauses,enhancing feature interactions between emotion clauses,cause clauses,and emotion-cause pairs.Second,the task alignment technique is applied to reduce the labeling distance between emotion-cause pair extraction and the two assistant tasks,capturing deep semantic information interactions among tasks.The proposed method is evaluated on a Chinese benchmark corpus using 10-fold cross-validation,assessing key performance metrics such as precision,recall,and F1 score.Experimental results demonstrate that the model achieves an F1 score of 76.05%,surpassing the state-of-the-art by 1.03%.The proposed model exhibits significant improvements in emotion-cause pair extraction(ECPE)and cause extraction(CE)compared to existing methods,validating its effectiveness.This research introduces a novel approach based on joint feature encoding and task alignment mechanisms,contributing to advancements in emotion-cause pair extraction.However,the study’s limitation lies in the data sources,potentially restricting the generalizability of the findings.展开更多
This research optimized the structure of lithium extraction solar ponds to enhance the crystallization rate and yield of Li_(2)CO_(3).Using the response surface methodology in Design-Expert 10.0.3,the authors conducte...This research optimized the structure of lithium extraction solar ponds to enhance the crystallization rate and yield of Li_(2)CO_(3).Using the response surface methodology in Design-Expert 10.0.3,the authors conducted experiments to investigate the influence of four factors related to solar pond structure on the crystallization of Li_(2)CO_(3) and their pairwise interactions.Computational Fluid Dynamics(CFD)simulations of the flow field within the solar pond were performed using COMSOL Multiphysics software to compare temperature distributions before and after optimization.The results indicate that the optimal structure for lithium extraction from the Zabuye Salt Lake solar ponds includes UCZ(Upper Convective Zone)thickness of 53.63 cm,an LCZ(Lower Convective Zone)direct heating temperature of 57.39℃,a CO32−concentration of 32.21 g/L,and an added soda ash concentration of 6.52 g/L.Following this optimized pathway,the Li_(2)CO_(3) precipitation increased by 7.34% compared to the initial solar pond process,with a 33.33% improvement in lithium carbonate crystallization rate.This study demonstrates the feasibility of optimizing lithium extraction solar pond structures,offering a new approach for constructing such ponds in salt lakes.It provides valuable guidance for the efficient extraction of lithium resources from carbonate-type salt lake brines.展开更多
The physical examination of the fruit of soursop fruit (Annona muricata) selected from different parent trees was investigated. Three-stage modified Soxhlet method was used which includes a percolator (boiler and refl...The physical examination of the fruit of soursop fruit (Annona muricata) selected from different parent trees was investigated. Three-stage modified Soxhlet method was used which includes a percolator (boiler and reflux) which circulates the solvent, a thimble (usually made of thick filter paper) which retains the seed to be extracted, and a siphon mechanism, which periodically empties the condensed solvent from the thimble back into the percolator. The extraction of oil from the seed and the percentage yield was examined. The oil samples were characterized for physico-chemical properties. The maximum values of physical parameters found were fruit weight 3.7 ± 7.09, fruit length 12.2 ± 28.3 cm, with 15.2 ± 20.81 cm and 0.12 ± 18.91 g for pulp weight. The percentage oil yield of 48.5% was obtained due to the environmental factors such as the soil type, planting season and optimal temperature of the region of seed cultivation. The result of chemical properties showed maximum acid value 0.46 mg KOH, FFA of 0.33 mg, saponification of 189.4 mg KOH mg and peroxide value of 4.33 mg/g. The oil physical properties as discovered have a melting point of 32˚C, smoke point of 198˚C and flash point of 280˚C. The results obtained in this study further reveal the potential of oil from seed of soursop as a substitute for conventional vegetable oil due to its high flash point which is an indication of its low flammability and can be used as a good source of food, industrially can be used as an anti-microbial agent and for pest control.展开更多
In global navigation satellite system denial environment,cross-view geo-localization based on image retrieval presents an exceedingly critical visual localization solution for Unmanned Aerial Vehicle(UAV)systems.The e...In global navigation satellite system denial environment,cross-view geo-localization based on image retrieval presents an exceedingly critical visual localization solution for Unmanned Aerial Vehicle(UAV)systems.The essence of cross-view geo-localization resides in matching images containing the same geographical targets from disparate platforms,such as UAV-view and satellite-view images.However,images of the same geographical targets may suffer from occlusions and geometric distortions due to variations in the capturing platform,view,and timing.The existing methods predominantly extract features by segmenting feature maps,which overlook the holistic semantic distribution and structural information of objects,resulting in loss of image information.To address these challenges,dilated neighborhood attention Transformer is employed as the feature extraction backbone,and Multi-feature representations based on Multi-scale Hierarchical Contextual Aggregation(MMHCA)is proposed.In the proposed MMHCA method,the multiscale hierarchical contextual aggregation method is utilized to extract contextual information from local to global across various granularity levels,establishing feature associations of contextual information with global and local information in the image.Subsequently,the multi-feature representations method is utilized to obtain rich discriminative feature information,bolstering the robustness of model in scenarios characterized by positional shifts,varying distances,and scale ambiguities.Comprehensive experiments conducted on the extensively utilized University-1652 and SUES-200 benchmarks indicate that the MMHCA method surpasses the existing techniques.showing outstanding results in UAV localization and navigation.展开更多
In recent years,with the rapid development of deep learning technology,relational triplet extraction techniques have also achieved groundbreaking progress.Traditional pipeline models have certain limitations due to er...In recent years,with the rapid development of deep learning technology,relational triplet extraction techniques have also achieved groundbreaking progress.Traditional pipeline models have certain limitations due to error propagation.To overcome the limitations of traditional pipeline models,recent research has focused on jointly modeling the two key subtasks-named entity recognition and relation extraction-within a unified framework.To support future research,this paper provides a comprehensive review of recently published studies in the field of relational triplet extraction.The review examines commonly used public datasets for relational triplet extraction techniques and systematically reviews current mainstream joint extraction methods,including joint decoding methods and parameter sharing methods,with joint decoding methods further divided into table filling,tagging,and sequence-to-sequence approaches.In addition,this paper also conducts small-scale replication experiments on models that have performed well in recent years for each method to verify the reproducibility of the code and to compare the performance of different models under uniform conditions.Each method has its own advantages in terms of model design,task handling,and application scenarios,but also faces challenges such as processing complex sentence structures,cross-sentence relation extraction,and adaptability in low-resource environments.Finally,this paper systematically summarizes each method and discusses the future development prospects of joint extraction of relational triples.展开更多
[Objectives]To investigate the optimal extraction conditions for anthocyanins from defatted Lycium ruthenicum Murray using ultrasonic-assisted solvent extraction.[Methods]Anthocyanins were extracted from wild L.ruthen...[Objectives]To investigate the optimal extraction conditions for anthocyanins from defatted Lycium ruthenicum Murray using ultrasonic-assisted solvent extraction.[Methods]Anthocyanins were extracted from wild L.ruthenicum in Qinghai Province using ultrasonic-assisted ethanol extraction.Through single-factor and orthogonal experiments,the optimal extraction conditions were determined as follows:temperature 50℃,solid-liquid ratio 1:15(g/mL),ethanol concentration 60%(v/v),and ultrasonic extraction time 25 min.Under these conditions,the anthocyanin content of L.ruthenicum was quantified by UV-Vis spectrophotometry at 280 nm.[Results]The extraction yield of anthocyanins from wild Qinghai L.ruthenicum was 17.0 mg/g,which is superior to the yield of 10.0 mg/g obtained by water solvent extraction,representing a 0.7%increase in extraction rate.The anthocyanin content in L.ruthenicum from different regions was determined,revealing that samples from the Chaidamu area in Qinghai had the highest content(17.3 mg/g),while samples from the Gansu area had the lowest(12.0 mg/g).[Conclusions]Ultrasonic-assisted ethanol extraction technology offers advantages including rapid operation,low energy consumption,high extraction yield,simple detection,and safety.展开更多
To improve the ability of diglycolamide extractants for the extraction of Sr(Ⅱ)from high-level waste liquid,N,N,N′,N′-tetracyclohexyldiglycolamide(TCHDGA)was proposed and studied to extract Sr(Ⅱ)from nitrate media...To improve the ability of diglycolamide extractants for the extraction of Sr(Ⅱ)from high-level waste liquid,N,N,N′,N′-tetracyclohexyldiglycolamide(TCHDGA)was proposed and studied to extract Sr(Ⅱ)from nitrate media.TCHDGA was prepared and characterized by 1H nuclear magnetic resonance spectroscopy(NMR),^(13)C NMR,and fourier transform infrared spectroscopy(FT-IR).Various factors affecting extraction were studied systematically.In just 20 s,the extraction rate can reach approximately 98.2%.The extraction capacity of cyclohexyl-substituted extractant TCHDGA is tens of times higher than that with linear or branched chain alkyl.The chemical structure of the complex has been demonstrated to be[Sr3TCHDGA]·(NO_(3))_(2),based on FT-IR,X-ray photoelectron spectroscopy(XPS),and crystal structure analysis.The crystal belongs to the monoclinic system,space group P21,and a strontium ion coordinates with nine oxygen atoms,all of which contribute from TCHDGA.The stripping rate can reach over 99%when using distilled water or 0.50 mol·L^(-1)oxalic acid as stripping agents.展开更多
This study proposes a learner profile framework based on multi-feature fusion,aiming to enhance the precision of personalized learning recommendations by integrating learners’static attributes(e.g.,demographic data a...This study proposes a learner profile framework based on multi-feature fusion,aiming to enhance the precision of personalized learning recommendations by integrating learners’static attributes(e.g.,demographic data and historical academic performance)with dynamic behavioral patterns(e.g.,real-time interactions and evolving interests over time).The research employs Term Frequency-Inverse Document Frequency(TF-IDF)for semantic feature extraction,integrates the Analytic Hierarchy Process(AHP)for feature weighting,and introduces a time decay function inspired by Newton’s law of cooling to dynamically model changes in learners’interests.Empirical results demonstrate that this framework effectively captures the dynamic evolution of learners’behaviors and provides context-aware learning resource recommendations.The study introduces a novel paradigm for learner modeling in educational technology,combining methodological innovation with a scalable technical architecture,thereby laying a foundation for the development of adaptive learning systems.展开更多
A successful extraction process relies heavily on an excellent extractant structure.The theory of extractant structure and extraction performance is still insufficient to guide the design of new extractants,despite ex...A successful extraction process relies heavily on an excellent extractant structure.The theory of extractant structure and extraction performance is still insufficient to guide the design of new extractants,despite extensive research into extractants.However,diglycolamide extractants have demonstrated certain advantages in nuclear fuel reprocessing and rare earth extraction and separation.This paper focuses on the synthesis of 13 structurally serially changed extractants.There is a good connection between the extraction performance and the energy consumption of the carbonyl conformation torsion of the extractant with symmetrical straight-chain alkyl substituents.The extraction capacity of extractant decreases with the increase of alkyl chain length.The methyl substituent extractant shows higher extractability than the other.The steric effect of the alkyl chain with more than two carbons is not significantly different.The relationship between the structure and performance of extractants was systematically studied by the combination of theoretical calculations and experimental data to investigate the effects of symmetric,asymmetric and branched N-substituents on extraction performance.展开更多
This study details a comprehensive approach focusing on the effective separation of light rare earth elements(REEs)via solvent extraction technique.A stock solution containing lanthanum,cerium,neodymium,praseodymium,a...This study details a comprehensive approach focusing on the effective separation of light rare earth elements(REEs)via solvent extraction technique.A stock solution containing lanthanum,cerium,neodymium,praseodymium,and samarium was prepared by dissolving their pure mixed oxide(reclaimed from spent Ni-MH batteries)in a diluted HCl solution.Key extractants,including bis(2,4,4-trimethylpentyl)phosphinic acid(Cyanex 272),Cyanex 572,trialkylphosphine oxide(Cyanex 923),and 2-ethylhexylphosphonic acid mono-2-ethylhexyl ester(PC 88A),along with tributyl phosphate(TBP)as a phase modifier,were utilized to form organic systems.The extraction behavior and separability of these systems at various pH levels as well as their extraction mechanisms were investigated.The results demonstrated a direct relationship between the extraction trend and the experimental pH value,with enhanced selectivity when TBP was added.Notably,Nd and Pr exhibited similar extraction behaviors,with minor deviations from Ce,making their separation difficult to achieve.Sm extraction followed a distinct trend,allowing for its separation from other elements at pH≤2.In contrast,La exhibited a low affinity for coordination with extractants when pH was≤3.5,facilitating the separation of other elements from La,which could then be isolated in the raffinate.Among the studied organic systems,combinations of Cyanex 572 and PC 88A with TBP demonstrated superior performance in element separation.Optimum separation factors were calculated withβ_(Ce/La)=12,βNd/La=87,β_(Pr/La)=127,andβ_(Sm/La)=3191 for the former,andβ_(Sm/Ce)=54,β_(Sm/Nd)=20,andβ_(Sm/Pr)=14 for the latter.These findings provide valuable insights for selecting extraction systems and designing experiments for the effective solvent extraction separation of light REEs from their mixture.展开更多
Simultaneous recovery of Ni and Co from Fe(Ⅲ)and AI is a critical challenge in hydrometallurgical processes.Recognized solvent extraction systems often struggle with selectivity and effective performance in mixed met...Simultaneous recovery of Ni and Co from Fe(Ⅲ)and AI is a critical challenge in hydrometallurgical processes.Recognized solvent extraction systems often struggle with selectivity and effective performance in mixed metal ion environments.Herein,a new synergistic solvent extraction(SSX)system comprised of a novel pyridine analog,N,N-bis(pyridin-2-ylmethyl)dodecan-1-amine(BPMDA),and dinonylnaphthalene sulfonic acid(DNNSA)with tributyl phosphate as phase modifier is introduced.The SSX system demonstrates high extraction performance achieving>90%for Ni and>97%for Co in a singlestage extraction process,with high selectivity.Under optimal conditions,the selectivity sequence is observed as Co^(2+)(>97%)>Ni^(2+)(>90%)>Mn^(2+)(<20%)>Fe^(3+)(<10%)>Mg^(2+)(<5%)>Al^(3+)(<2%)>Ca^(2+)(<1%).Spectroscopic analysis evidences the preferential binding of BPMDA with Ni and Co in the presence of DNNSA,concurrently achieving a significant reduction in the co-extraction of Fe(Ⅲ)and Al.The selective complexation of Ni and Co using the SSX system offers a highly efficient and selective approach for their extraction,with promising potential for applications in recovery-based processes.展开更多
The study introduces eco-friendly leaching agents as alternatives to traditional rare earth element(REE)extraction solvents,addressing environmental concerns associated with ammonium sulfate.Bio-based ionic liquids(IL...The study introduces eco-friendly leaching agents as alternatives to traditional rare earth element(REE)extraction solvents,addressing environmental concerns associated with ammonium sulfate.Bio-based ionic liquids(ILs),known for their non-toxic and biodegradable properties,were screened using the COSMO-RS software.Initially,105 ILs involving 7 cations and 15 anions were computationally screened to find the best ILs for REE extraction.The chosen criteria were based on hydrogen bond formation,affinity screening,hydrophobicity,viscosity,and eco-toxicity test.Based on the COSMO-RS screening,choline oleate,choline decanoate,and choline hexanoate exhibit high solubility for REEs,with a chemical potential of 17.60,17.01,and 18.37 kcal/mol at REE oxidation state+2.Choline glycinate,choline oleate,choline decanoate,choline hexanoate,choline lysinate,and choline leucinate were selected for their strong affinity to extract REE dissociate ions.Experimental results show slightly higher REE extraction from ammonium sulfate(3.17 ppm)compared to choline glycinate(3.15 ppm).For long-term applications,choline glycinate offers a promising eco-friendly and cost-effective alternative to traditional leaching agents,promoting economic feasibility and environmental friendliness.展开更多
基金supported by National Natural Science Foundation of China(No.61761027)Gansu Young Doctor’s Fund for Higher Education Institutions(No.2021QB-053)。
文摘The traditional EnFCM(Enhanced fuzzy C-means)algorithm only considers the grey-scale features in image segmentation,resulting in less than satisfactory results when the algorithm is used for remote sensing woodland image segmentation and extraction.An EnFCM remote sensing forest land extraction method based on PCA multi-feature fusion was proposed.Firstly,histogram equalization was applied to improve the image contrast.Secondly,the texture and edge features of the image were extracted,and a multi-feature fused pixel image was generated using the PCA technique.Moreover,the fused feature was used as a feature constraint to measure the difference of pixels instead of a single grey-scale feature.Finally,an improved feature distance metric calculated the similarity between the pixel points and the cluster center to complete the cluster segmentation.The experimental results showed that the error was between 1.5%and 4.0%compared with the forested area counted by experts’hand-drawing,which could obtain a high accuracy segmentation and extraction result.
基金supported by the National Key Research and Development Program of China(No.2023YFF0905400)the National Natural Science Foundation of China(No.U2341229).
文摘Relation extraction plays a crucial role in numerous downstream tasks.Dialogue relation extraction focuses on identifying relations between two arguments within a given dialogue.To tackle the problem of low information density in dialogues,methods based on trigger enhancement have been proposed,yielding positive results.However,trigger enhancement faces challenges,which cause suboptimal model performance.First,the proportion of annotated triggers is low in DialogRE.Second,feature representations of triggers and arguments often contain conflicting information.In this paper,we propose a novel Multi-Feature Filtering and Fusion trigger enhancement approach to overcome these limitations.We first obtain representations of arguments,and triggers that contain rich semantic information through attention and gate methods.Then,we design a feature filtering mechanism that eliminates conflicting features in the encoding of trigger prototype representations and their corresponding argument pairs.Additionally,we utilize large language models to create prompts based on Chain-of-Thought and In-context Learning for automated trigger extraction.Experiments show that our model increases the average F1 score by 1.3%in the dialogue relation extraction task.Ablation and case studies confirm the effectiveness of our model.Furthermore,the feature filtering method effectively integrates with other trigger enhancement models,enhancing overall performance and demonstrating its ability to resolve feature conflicts.
文摘Caused by the environment clutter,the radar false alarm plots are unavoidable.Suppressing false alarm points has always been a key issue in Radar plots procession.In this paper,a radar false alarm plots elimination method based on multi-feature extraction and classification is proposed to effectively eliminate false alarm plots.Firstly,the density based spatial clustering of applications with noise(DBSCAN)algorithm is used to cluster the radar echo data processed by constant false-alarm rate(CFAR).The multi-features including the scale features,time domain features and transform domain features are extracted.Secondly,a feature evaluation method combining pearson correlation coefficient(PCC)and entropy weight method(EWM)is proposed to evaluate interrelation among features,effective feature combination sets are selected as inputs of the classifier.Finally,False alarm plots classified as clutters are eliminated.The experimental results show that proposed method can eliminate about 90%false alarm plots with less target loss rate.
基金the Natural Science Foundation of Zhejiang Province(Nos.LY20F020015 and LY21F020015)the National Natural Science Foundation of China(Nos.61972121 and 61902099)。
文摘This study proposes a multi-scene smoke detection algorithm based on a multi-feature extraction method to address the problems of varying smoke shapes in different scenes,difficulty in locating and detecting translucent smoke,and variable smoke scales.First,the convolution module of feature extraction in YOLOv5s backbone network is replaced with asymmetric convolution block re-parameterization convolution to improve the detection of different shapes of smoke.Then,coordinate attention mechanism is introduced in the deeper layer of the backbone network to further improve the localization of translucent smoke.Finally,the detection of smoke at different scales is further improved by using the feature pyramid convolution module instead of the standard convolution module of the feature pyramid in the model.The experimental results demonstrate the feasibility and superiority of the proposed model for multi-scene smoke detection.
文摘In the international shipping industry, digital intelligence transformation has become essential, with both governments and enterprises actively working to integrate diverse datasets. The domain of maritime and shipping is characterized by a vast array of document types, filled with complex, large-scale, and often chaotic knowledge and relationships. Effectively managing these documents is crucial for developing a Large Language Model (LLM) in the maritime domain, enabling practitioners to access and leverage valuable information. A Knowledge Graph (KG) offers a state-of-the-art solution for enhancing knowledge retrieval, providing more accurate responses and enabling context-aware reasoning. This paper presents a framework for utilizing maritime and shipping documents to construct a knowledge graph using GraphRAG, a hybrid tool combining graph-based retrieval and generation capabilities. The extraction of entities and relationships from these documents and the KG construction process are detailed. Furthermore, the KG is integrated with an LLM to develop a Q&A system, demonstrating that the system significantly improves answer accuracy compared to traditional LLMs. Additionally, the KG construction process is up to 50% faster than conventional LLM-based approaches, underscoring the efficiency of our method. This study provides a promising approach to digital intelligence in shipping, advancing knowledge accessibility and decision-making.
基金Project supported by the National Natural Science Foundation of China(52074031)the Key Research and Development Program of Shandong Province(ZR2021MB051,ZR2020ME256)the Open Project of Key Laboratory of Green Chemical Engineering Process of Ministry of Education(GCP202117)。
文摘Solvent extraction is the main method used to separate and purify rare earth elements.In the process of rare earths extraction,emulsification often generated due to the instability of the aqueous and organic phases or improper operating conditions.Once emulsification occurs,it would not only lead to low rare earths recovery efficiency,small product quantities,high production costs and the losing of extractant and rare earth resources,but also result in serious environmental pollution.Therefore,it is very important to study the micro-mechanisms of emulsification and establish new methods to prevent emulsification at the source.In this paper,possible factors resulting in emulsification,such as the compositions and properties of the organic and aqueous phases,the operating conditions of the rare earths extraction are reviewed.The micro-mechanisms of emulsification are summarized basing on the microscopic structures in the bulk phase,aggregations of the extractants at the organic-aqueous interface,spectral characterizations and computational simulations.On this basis,new formation mechanisms are proposed for emulsification.Preliminary explorations are employed to verify the correctness of these new viewpoints.Finally,future directions for studies of the emulsification micro-mechanism are proposed.This study provides a theoretical basis for further understanding the micro-mechanisms of interfacial instability resulting in emulsification in the process of rare earths extraction.
基金supported by the Key Research and Development Program of Hunan Province of China(No.2022NK2036)Xiangxi Prefecture Science and Technology Plan Project"School-Local Integration"Special Project(No.2022001)the scientific research project of Hunan Provincial Department of Education(No.22B0520).
文摘Background:Ampelopsis grossedentata,vine tea,which is the tea alternative beverages in China.In vine tea processing,a large amount of broken tea is produced,which has low commercial value.Methods:This study investigates the influence of different extraction methods(room temperature water extraction,boiling water extraction,ultrasonic-assisted room temperature water extraction,and ultrasonic-assisted boiling water extraction,referred to as room temperature water extraction(RE),boiling water extraction(BE),ultrasonic assistance at room temperature water extraction(URE),and ultrasonic assistance in boiling water extraction(UBE))on the yield,dihydromyricetin(DMY)content,free amino acid composition,volatile aroma components,and antioxidant properties of vine tea extracts.Results:A notable influence of extraction temperature on the yield of vine tea extracts(P<0.05),with BE yielding the highest at 43.13±0.26%,higher than that of RE(34.29±0.81%).Ultrasound-assisted extraction significantly increased the DMY content of the extracts(P<0.05),whereas DMY content in the RE extracts was 59.94±1.70%,that of URE reached 66.14±2.78%.Analysis revealed 17 amino acids,with L-serine and aspartic acid being the most abundant in the extracts,nevertheless ultrasound-assisted extraction reduced total free amino acid content.Gas chromatography-mass spectrometry analysis demonstrated an increase in the diversity and quantity of compounds in the vine tea water extracts obtained through ultrasonic-assisted extraction.Specifically,69 and 68 volatile compounds were found in URE and UBE extracts,which were higher than the number found in RE and BE extracts.In vitro,antioxidant activity assessments revealed varying antioxidant capacities among different extraction methods,with RE exhibiting the highest DPPH scavenging rate,URE leading in ABTS•+free radical scavenging,and BE demonstrating superior ferric ion reducing antioxidant activity.Conclusion:The findings suggest that extraction methods significantly influence the chemical composition and antioxidant properties of vine tea extracts.Ultrasonic-assisted extraction proved instrumental in elevating the DMY content in vine tea extracts,thereby enriching its flavor profile while maintaining its antioxidant properties.
文摘This study aimed to investigate the effect of ultrasound-assisted alkaline extraction(UAE)(at 20 kHz and different powers of 0,200,300,400,500 and 600 W for 10 min)on the yield,structure and emulsifying properties of chickpea protein isolate(CPI).Compared with the non-ultrasound group,ultrasound treatment at 400 W resulted in the largest increase in CPI yield,and both the particle size and turbidity decreased with increasing ultrasound power from 0 to 400 W.The scanning electron microscope results showed a uniform structural distribution of CPI.Moreover,itsα-helix content increased,β-sheet content decreased,and total sulfhydryl group content and endogenous fluorescence intensity rose,illustrating that UAE changed the secondary and tertiary structure of CPI.At 400 W,the solubility of the emulsion increased to 63.18%,and the best emulsifying properties were obtained;the emulsifying activity index(EAI)and emulsifying stability index(ESI)increased by 85.42%and 46.78%,respectively.Furthermore,the emulsion droplets formed were smaller and more uniform.In conclusion,proper UAE power conditions increased the extraction yield and protein content of CPI,and effectively improved its structure and emulsifying characteristics.
文摘With the rapid expansion of social media,analyzing emotions and their causes in texts has gained significant importance.Emotion-cause pair extraction enables the identification of causal relationships between emotions and their triggers within a text,facilitating a deeper understanding of expressed sentiments and their underlying reasons.This comprehension is crucial for making informed strategic decisions in various business and societal contexts.However,recent research approaches employing multi-task learning frameworks for modeling often face challenges such as the inability to simultaneouslymodel extracted features and their interactions,or inconsistencies in label prediction between emotion-cause pair extraction and independent assistant tasks like emotion and cause extraction.To address these issues,this study proposes an emotion-cause pair extraction methodology that incorporates joint feature encoding and task alignment mechanisms.The model consists of two primary components:First,joint feature encoding simultaneously generates features for emotion-cause pairs and clauses,enhancing feature interactions between emotion clauses,cause clauses,and emotion-cause pairs.Second,the task alignment technique is applied to reduce the labeling distance between emotion-cause pair extraction and the two assistant tasks,capturing deep semantic information interactions among tasks.The proposed method is evaluated on a Chinese benchmark corpus using 10-fold cross-validation,assessing key performance metrics such as precision,recall,and F1 score.Experimental results demonstrate that the model achieves an F1 score of 76.05%,surpassing the state-of-the-art by 1.03%.The proposed model exhibits significant improvements in emotion-cause pair extraction(ECPE)and cause extraction(CE)compared to existing methods,validating its effectiveness.This research introduces a novel approach based on joint feature encoding and task alignment mechanisms,contributing to advancements in emotion-cause pair extraction.However,the study’s limitation lies in the data sources,potentially restricting the generalizability of the findings.
基金This study was supported by the National Natural Science Foundation of China(U20A20148)the Major Science and Technology Projects of the Xizang(Tibet)Autonomous Region(XZ202201ZD0004G and XZ202201ZD0004G01).
文摘This research optimized the structure of lithium extraction solar ponds to enhance the crystallization rate and yield of Li_(2)CO_(3).Using the response surface methodology in Design-Expert 10.0.3,the authors conducted experiments to investigate the influence of four factors related to solar pond structure on the crystallization of Li_(2)CO_(3) and their pairwise interactions.Computational Fluid Dynamics(CFD)simulations of the flow field within the solar pond were performed using COMSOL Multiphysics software to compare temperature distributions before and after optimization.The results indicate that the optimal structure for lithium extraction from the Zabuye Salt Lake solar ponds includes UCZ(Upper Convective Zone)thickness of 53.63 cm,an LCZ(Lower Convective Zone)direct heating temperature of 57.39℃,a CO32−concentration of 32.21 g/L,and an added soda ash concentration of 6.52 g/L.Following this optimized pathway,the Li_(2)CO_(3) precipitation increased by 7.34% compared to the initial solar pond process,with a 33.33% improvement in lithium carbonate crystallization rate.This study demonstrates the feasibility of optimizing lithium extraction solar pond structures,offering a new approach for constructing such ponds in salt lakes.It provides valuable guidance for the efficient extraction of lithium resources from carbonate-type salt lake brines.
文摘The physical examination of the fruit of soursop fruit (Annona muricata) selected from different parent trees was investigated. Three-stage modified Soxhlet method was used which includes a percolator (boiler and reflux) which circulates the solvent, a thimble (usually made of thick filter paper) which retains the seed to be extracted, and a siphon mechanism, which periodically empties the condensed solvent from the thimble back into the percolator. The extraction of oil from the seed and the percentage yield was examined. The oil samples were characterized for physico-chemical properties. The maximum values of physical parameters found were fruit weight 3.7 ± 7.09, fruit length 12.2 ± 28.3 cm, with 15.2 ± 20.81 cm and 0.12 ± 18.91 g for pulp weight. The percentage oil yield of 48.5% was obtained due to the environmental factors such as the soil type, planting season and optimal temperature of the region of seed cultivation. The result of chemical properties showed maximum acid value 0.46 mg KOH, FFA of 0.33 mg, saponification of 189.4 mg KOH mg and peroxide value of 4.33 mg/g. The oil physical properties as discovered have a melting point of 32˚C, smoke point of 198˚C and flash point of 280˚C. The results obtained in this study further reveal the potential of oil from seed of soursop as a substitute for conventional vegetable oil due to its high flash point which is an indication of its low flammability and can be used as a good source of food, industrially can be used as an anti-microbial agent and for pest control.
基金supported by the National Natural Science Foundation of China(Nos.12072027,62103052,61603346 and 62103379)the Henan Key Laboratory of General Aviation Technology,China(No.ZHKF-230201)+3 种基金the Funding for the Open Research Project of the Rotor Aerodynamics Key Laboratory,China(No.RAL20200101)the Key Research and Development Program of Henan Province,China(Nos.241111222000 and 241111222900)the Key Science and Technology Program of Henan Province,China(No.232102220067)the Scholarship Funding from the China Scholarship Council(No.202206030079).
文摘In global navigation satellite system denial environment,cross-view geo-localization based on image retrieval presents an exceedingly critical visual localization solution for Unmanned Aerial Vehicle(UAV)systems.The essence of cross-view geo-localization resides in matching images containing the same geographical targets from disparate platforms,such as UAV-view and satellite-view images.However,images of the same geographical targets may suffer from occlusions and geometric distortions due to variations in the capturing platform,view,and timing.The existing methods predominantly extract features by segmenting feature maps,which overlook the holistic semantic distribution and structural information of objects,resulting in loss of image information.To address these challenges,dilated neighborhood attention Transformer is employed as the feature extraction backbone,and Multi-feature representations based on Multi-scale Hierarchical Contextual Aggregation(MMHCA)is proposed.In the proposed MMHCA method,the multiscale hierarchical contextual aggregation method is utilized to extract contextual information from local to global across various granularity levels,establishing feature associations of contextual information with global and local information in the image.Subsequently,the multi-feature representations method is utilized to obtain rich discriminative feature information,bolstering the robustness of model in scenarios characterized by positional shifts,varying distances,and scale ambiguities.Comprehensive experiments conducted on the extensively utilized University-1652 and SUES-200 benchmarks indicate that the MMHCA method surpasses the existing techniques.showing outstanding results in UAV localization and navigation.
基金funding from Key Areas Science and Technology Research Plan of Xinjiang Production And Construction Corps Financial Science and Technology Plan Project under Grant Agreement No.2023AB048 for the project:Research and Application Demonstration of Data-driven Elderly Care System.
文摘In recent years,with the rapid development of deep learning technology,relational triplet extraction techniques have also achieved groundbreaking progress.Traditional pipeline models have certain limitations due to error propagation.To overcome the limitations of traditional pipeline models,recent research has focused on jointly modeling the two key subtasks-named entity recognition and relation extraction-within a unified framework.To support future research,this paper provides a comprehensive review of recently published studies in the field of relational triplet extraction.The review examines commonly used public datasets for relational triplet extraction techniques and systematically reviews current mainstream joint extraction methods,including joint decoding methods and parameter sharing methods,with joint decoding methods further divided into table filling,tagging,and sequence-to-sequence approaches.In addition,this paper also conducts small-scale replication experiments on models that have performed well in recent years for each method to verify the reproducibility of the code and to compare the performance of different models under uniform conditions.Each method has its own advantages in terms of model design,task handling,and application scenarios,but also faces challenges such as processing complex sentence structures,cross-sentence relation extraction,and adaptability in low-resource environments.Finally,this paper systematically summarizes each method and discusses the future development prospects of joint extraction of relational triples.
文摘[Objectives]To investigate the optimal extraction conditions for anthocyanins from defatted Lycium ruthenicum Murray using ultrasonic-assisted solvent extraction.[Methods]Anthocyanins were extracted from wild L.ruthenicum in Qinghai Province using ultrasonic-assisted ethanol extraction.Through single-factor and orthogonal experiments,the optimal extraction conditions were determined as follows:temperature 50℃,solid-liquid ratio 1:15(g/mL),ethanol concentration 60%(v/v),and ultrasonic extraction time 25 min.Under these conditions,the anthocyanin content of L.ruthenicum was quantified by UV-Vis spectrophotometry at 280 nm.[Results]The extraction yield of anthocyanins from wild Qinghai L.ruthenicum was 17.0 mg/g,which is superior to the yield of 10.0 mg/g obtained by water solvent extraction,representing a 0.7%increase in extraction rate.The anthocyanin content in L.ruthenicum from different regions was determined,revealing that samples from the Chaidamu area in Qinghai had the highest content(17.3 mg/g),while samples from the Gansu area had the lowest(12.0 mg/g).[Conclusions]Ultrasonic-assisted ethanol extraction technology offers advantages including rapid operation,low energy consumption,high extraction yield,simple detection,and safety.
基金supported by the Natural Science Foundation of Shandong Province(ZR2022QB067).
文摘To improve the ability of diglycolamide extractants for the extraction of Sr(Ⅱ)from high-level waste liquid,N,N,N′,N′-tetracyclohexyldiglycolamide(TCHDGA)was proposed and studied to extract Sr(Ⅱ)from nitrate media.TCHDGA was prepared and characterized by 1H nuclear magnetic resonance spectroscopy(NMR),^(13)C NMR,and fourier transform infrared spectroscopy(FT-IR).Various factors affecting extraction were studied systematically.In just 20 s,the extraction rate can reach approximately 98.2%.The extraction capacity of cyclohexyl-substituted extractant TCHDGA is tens of times higher than that with linear or branched chain alkyl.The chemical structure of the complex has been demonstrated to be[Sr3TCHDGA]·(NO_(3))_(2),based on FT-IR,X-ray photoelectron spectroscopy(XPS),and crystal structure analysis.The crystal belongs to the monoclinic system,space group P21,and a strontium ion coordinates with nine oxygen atoms,all of which contribute from TCHDGA.The stripping rate can reach over 99%when using distilled water or 0.50 mol·L^(-1)oxalic acid as stripping agents.
基金This work is supported by the Ministry of Education of Humanities and Social Science projects in China(No.20YJCZH124)Guangdong Province Education and Teaching Reform Project No.640:Research on the Teaching Practice and Application of Online Peer Assessment Methods in the Context of Artificial Intelligence.
文摘This study proposes a learner profile framework based on multi-feature fusion,aiming to enhance the precision of personalized learning recommendations by integrating learners’static attributes(e.g.,demographic data and historical academic performance)with dynamic behavioral patterns(e.g.,real-time interactions and evolving interests over time).The research employs Term Frequency-Inverse Document Frequency(TF-IDF)for semantic feature extraction,integrates the Analytic Hierarchy Process(AHP)for feature weighting,and introduces a time decay function inspired by Newton’s law of cooling to dynamically model changes in learners’interests.Empirical results demonstrate that this framework effectively captures the dynamic evolution of learners’behaviors and provides context-aware learning resource recommendations.The study introduces a novel paradigm for learner modeling in educational technology,combining methodological innovation with a scalable technical architecture,thereby laying a foundation for the development of adaptive learning systems.
基金supported by the Natural Science Foundation of Shandong Province (ZR2022QB067)。
文摘A successful extraction process relies heavily on an excellent extractant structure.The theory of extractant structure and extraction performance is still insufficient to guide the design of new extractants,despite extensive research into extractants.However,diglycolamide extractants have demonstrated certain advantages in nuclear fuel reprocessing and rare earth extraction and separation.This paper focuses on the synthesis of 13 structurally serially changed extractants.There is a good connection between the extraction performance and the energy consumption of the carbonyl conformation torsion of the extractant with symmetrical straight-chain alkyl substituents.The extraction capacity of extractant decreases with the increase of alkyl chain length.The methyl substituent extractant shows higher extractability than the other.The steric effect of the alkyl chain with more than two carbons is not significantly different.The relationship between the structure and performance of extractants was systematically studied by the combination of theoretical calculations and experimental data to investigate the effects of symmetric,asymmetric and branched N-substituents on extraction performance.
基金support from the Australian Research Council’s Industrial Transformation Research Hub funding scheme(project IH190100009).
文摘This study details a comprehensive approach focusing on the effective separation of light rare earth elements(REEs)via solvent extraction technique.A stock solution containing lanthanum,cerium,neodymium,praseodymium,and samarium was prepared by dissolving their pure mixed oxide(reclaimed from spent Ni-MH batteries)in a diluted HCl solution.Key extractants,including bis(2,4,4-trimethylpentyl)phosphinic acid(Cyanex 272),Cyanex 572,trialkylphosphine oxide(Cyanex 923),and 2-ethylhexylphosphonic acid mono-2-ethylhexyl ester(PC 88A),along with tributyl phosphate(TBP)as a phase modifier,were utilized to form organic systems.The extraction behavior and separability of these systems at various pH levels as well as their extraction mechanisms were investigated.The results demonstrated a direct relationship between the extraction trend and the experimental pH value,with enhanced selectivity when TBP was added.Notably,Nd and Pr exhibited similar extraction behaviors,with minor deviations from Ce,making their separation difficult to achieve.Sm extraction followed a distinct trend,allowing for its separation from other elements at pH≤2.In contrast,La exhibited a low affinity for coordination with extractants when pH was≤3.5,facilitating the separation of other elements from La,which could then be isolated in the raffinate.Among the studied organic systems,combinations of Cyanex 572 and PC 88A with TBP demonstrated superior performance in element separation.Optimum separation factors were calculated withβ_(Ce/La)=12,βNd/La=87,β_(Pr/La)=127,andβ_(Sm/La)=3191 for the former,andβ_(Sm/Ce)=54,β_(Sm/Nd)=20,andβ_(Sm/Pr)=14 for the latter.These findings provide valuable insights for selecting extraction systems and designing experiments for the effective solvent extraction separation of light REEs from their mixture.
基金supported by the National Natural Science Foundation of China(22278407,22001147,21922814,22138012,22178349)CAS Project for Young Scientists in Basic Research(YSBR-038)+2 种基金the Ministry of Science and Technology of China(2021YFC2901500)Excellent Member in Youth Innovation Promotion Association,Chinese Academy of Sciences(Y202014)Shandong Energy Institute(SEI U202306).
文摘Simultaneous recovery of Ni and Co from Fe(Ⅲ)and AI is a critical challenge in hydrometallurgical processes.Recognized solvent extraction systems often struggle with selectivity and effective performance in mixed metal ion environments.Herein,a new synergistic solvent extraction(SSX)system comprised of a novel pyridine analog,N,N-bis(pyridin-2-ylmethyl)dodecan-1-amine(BPMDA),and dinonylnaphthalene sulfonic acid(DNNSA)with tributyl phosphate as phase modifier is introduced.The SSX system demonstrates high extraction performance achieving>90%for Ni and>97%for Co in a singlestage extraction process,with high selectivity.Under optimal conditions,the selectivity sequence is observed as Co^(2+)(>97%)>Ni^(2+)(>90%)>Mn^(2+)(<20%)>Fe^(3+)(<10%)>Mg^(2+)(<5%)>Al^(3+)(<2%)>Ca^(2+)(<1%).Spectroscopic analysis evidences the preferential binding of BPMDA with Ni and Co in the presence of DNNSA,concurrently achieving a significant reduction in the co-extraction of Fe(Ⅲ)and Al.The selective complexation of Ni and Co using the SSX system offers a highly efficient and selective approach for their extraction,with promising potential for applications in recovery-based processes.
基金supported by Petronas Research Sdn Bhd(PRSB)with grant number(015M20-129)Centre of Research in Ionic Liquids(CORIL)Universiti Teknologi PETRONAS for the facilities and support provided。
文摘The study introduces eco-friendly leaching agents as alternatives to traditional rare earth element(REE)extraction solvents,addressing environmental concerns associated with ammonium sulfate.Bio-based ionic liquids(ILs),known for their non-toxic and biodegradable properties,were screened using the COSMO-RS software.Initially,105 ILs involving 7 cations and 15 anions were computationally screened to find the best ILs for REE extraction.The chosen criteria were based on hydrogen bond formation,affinity screening,hydrophobicity,viscosity,and eco-toxicity test.Based on the COSMO-RS screening,choline oleate,choline decanoate,and choline hexanoate exhibit high solubility for REEs,with a chemical potential of 17.60,17.01,and 18.37 kcal/mol at REE oxidation state+2.Choline glycinate,choline oleate,choline decanoate,choline hexanoate,choline lysinate,and choline leucinate were selected for their strong affinity to extract REE dissociate ions.Experimental results show slightly higher REE extraction from ammonium sulfate(3.17 ppm)compared to choline glycinate(3.15 ppm).For long-term applications,choline glycinate offers a promising eco-friendly and cost-effective alternative to traditional leaching agents,promoting economic feasibility and environmental friendliness.
