To reduce the carbon footprint in the transportation sector and improve overall vehicle efficiency,a large number of electric vehicles are being manufactured.This is due to the fact that environmental concerns and the...To reduce the carbon footprint in the transportation sector and improve overall vehicle efficiency,a large number of electric vehicles are being manufactured.This is due to the fact that environmental concerns and the depletion of fossil fuels have become significant global problems.Lithium-ion batteries(LIBs)have been distinguished themselves from alternative energy storage technologies for electric vehicles(EVs) due to superior qualities like high energy and power density,extended cycle life,and low maintenance cost to a competitive price.However,there are still certain challenges to be solved,like EV fast charging,longer lifetime,and reduced weight.For fast charging,the multi-stage constant current(MSCC) charging technique is an emerging solution to improve charging efficiency,reduce temperature rise during charging,increase charging/discharging capacities,shorten charging time,and extend the cycle life.However,there are large variations in the implementation of the number of stages,stage transition criterion,and C-rate selection for each stage.This paper provides a review of these problems by compiling information from the literature.An overview of the impact of different design parameters(number of stages,stage transition,and C-rate) that the MSCC charging techniques have had on the LIB performance and cycle life is described in detail and analyzed.The impact of design parameters on lifetime,charging efficiency,charging and discharging capacity,charging speed,and rising temperature during charging is presented,and this review provides guidelines for designing advanced fast charging strategies and determining future research gaps.展开更多
Rapid evolutions of the Internet of Electric Vehicles(IoEVs)are reshaping and modernizing transport systems,yet challenges remain in energy efficiency,better battery aging,and grid stability.Typical charging methods a...Rapid evolutions of the Internet of Electric Vehicles(IoEVs)are reshaping and modernizing transport systems,yet challenges remain in energy efficiency,better battery aging,and grid stability.Typical charging methods allow for EVs to be charged without thought being given to the condition of the battery or the grid demand,thus increasing energy costs and battery aging.This study proposes a smart charging station with an AI-powered Battery Management System(BMS),developed and simulated in MATLAB/Simulink,to increase optimality in energy flow,battery health,and impractical scheduling within the IoEV environment.The system operates through real-time communication,load scheduling based on priorities,and adaptive charging based on batterymathematically computed State of Charge(SOC),State of Health(SOH),and thermal state,with bidirectional power flow(V2G),thus allowing EVs’participation towards grid stabilization.Simulation results revealed that the proposed model can reduce peak grid load by 37.8%;charging efficiency is enhanced by 92.6%;battery temperature lessened by 4.4℃;SOH extended over 100 cycles by 6.5%,if compared against the conventional technique.By this way,charging time was decreased by 12.4% and energy costs dropped by more than 20%.These results showed that smart charging with intelligent BMS can boost greatly the operational efficiency and sustainability of the IoEV ecosystem.展开更多
Surface polaritons,as surface electromagnetic waves propagating along the surface of a medium,have played a crucial role in enhancing photonic spin Hall effect(PSHE)and developing highly sensitive refractive index(RI)...Surface polaritons,as surface electromagnetic waves propagating along the surface of a medium,have played a crucial role in enhancing photonic spin Hall effect(PSHE)and developing highly sensitive refractive index(RI)sensors.Among them,the traditional surface plasmon polariton(SPP)based on noble metals limits its application beyond the near-infrared(IR)regime due to the large negative permittivity and optical losses.In this contribution,we theoretically proposed a highly sensitive PSHE sensor with the structure of Ge prism-SiC-Si:InAs-sensing medium,by taking advantage of the hybrid surface plasmon phonon polariton(SPPhP)in mid-IR regime.Here,heavily Si-doped InAs(Si:InAs)and SiC excite the SPP and surface phonon polariton(SPhP),and the hybrid SPPhP is realized in this system.More importantly,the designed PSHE sensor based on this SPPhP mechanism achieves the multi-stage RI measurements from 1.00025-1.00225 to 1.70025-1.70225,and the maximal intensity sensitivity and angle sensitivity can be up to 9.4×10^(4)μm/RIU and245°/RIU,respectively.These findings provide a new pathway for the enhancement of PSHE in mid-IR regime,and offer new opportunities to develop highly sensitive RI sensors in multi-scenario applications,such as harmful gas monitoring and biosensing.展开更多
To achieve low-carbon regulation of electric vehicle(EV)charging loads under the“dual carbon”goals,this paper proposes a coordinated scheduling strategy that integrates dynamic carbon factor prediction and multiobje...To achieve low-carbon regulation of electric vehicle(EV)charging loads under the“dual carbon”goals,this paper proposes a coordinated scheduling strategy that integrates dynamic carbon factor prediction and multiobjective optimization.First,a dual-convolution enhanced improved Crossformer prediction model is constructed,which employs parallel 1×1 global and 3×3 local convolutionmodules(Integrated Convolution Block,ICB)formultiscale feature extraction,combinedwith anAdaptive Spectral Block(ASB)to enhance time-series fluctuationmodeling.Based on high-precision predictions,a carbon-electricity cost joint optimization model is further designed to balance economic,environmental,and grid-friendly objectives.The model’s superiority was validated through a case study using real-world data from a renewable-heavy grid.Simulation results show that the proposed multi-objective strategy demonstrated a superior balance compared to baseline and benchmark models,achieving a 15.8%reduction in carbon emissions and a 5.2%reduction in economic costs,while still providing a substantial 22.2%reduction in the peak-valley difference.Its balanced performance significantly outperformed both a single-objective strategy and a state-of-the-art Model Predictive Control(MPC)benchmark,highlighting the advantage of a global optimization approach.This study provides theoretical and technical pathways for dynamic carbon factor-driven EV charging optimization.展开更多
As renewable energy penetration continues to rise,enhancing power system flexibility has become a critical requirement.Photovoltaic–storage–charging stations(PSCSs)are key components for enhancing local regulation c...As renewable energy penetration continues to rise,enhancing power system flexibility has become a critical requirement.Photovoltaic–storage–charging stations(PSCSs)are key components for enhancing local regulation capability and promoting renewable integration.However,evaluating the adjustable capability of such hybrid stations while considering security constraints remains a major challenge.This paper first analyzes the adjustable capabilities of all the resources within such a station based on the power-energy boundary(PEB)model.Then,an optimal formulation is proposed to obtain the adjusted parameters of the aggregate feasible region(AFR)model,which embeds low-dimensional linear models within high-dimensional linear models to improve the accuracy.To solve this formulation,it is transformed using duality theory and an alternating optimization algorithm is designed to obtain the solution.Finally,a multi-station adjustable capability aggregation method considering security constraints is introduced.Simulation results verify that the proposed method effectively reduces infeasible regions and improves smoothness of aggregated boundaries,providing an accurate and practical tool for flexibility evaluation in PSCSs and offering guidance for aggregators and system planners.展开更多
Accurate state of health(SOH)estimation is essential for the safe and reliable operation of lithium-ion batteries.However,existing methods face significant challenges,primarily because they rely on complete charge–di...Accurate state of health(SOH)estimation is essential for the safe and reliable operation of lithium-ion batteries.However,existing methods face significant challenges,primarily because they rely on complete charge–discharge cycles and fixed-form physical constraints,which limit adaptability to different chemistries and real-world conditions.To address these issues,this study proposes an approach that extracts features from segmented state of charge(SOC)intervals and integrates them into an enhanced physics-informed neural network(PINN).Specifically,voltage data within the 25%–75%SOC range during charging are used to derive statistical,time–frequency,and mechanism-based features that capture degradation trends.A hybrid PINN-Lasso-Transformer-BiLSTM architecture is developed,where Lasso regression enables sparse feature selection,and a nonlinear empirical degradation model is embedded as a learnable physical term within a dynamically scaled composite loss.This design adaptively balances data-driven accuracy with physical consistency,thereby enhancing estimation precision,robustness,and generalization.The results show that the proposed method outperforms conventional neural networks across four battery chemistries,achieving root mean square error and mean absolute error below 1%.Notably,features from partial charging segments exhibit higher robustness than those from full cycles.Furthermore,the model maintains strong performance under high temperatures and demonstrates excellent generalization capacity in transfer learning across chemistries,temperatures,and C-rates.This work establishes a scalable and interpretable solution for accurate SOH estimation under diverse practical operating conditions.展开更多
We proposed a strategy to address the issue by synthesizing MnO with half-filled 3 d electron orbitals.That is,MnO nanocubes with an edge length of 61.82 nm were successfully prepared through electros-pinning and one-...We proposed a strategy to address the issue by synthesizing MnO with half-filled 3 d electron orbitals.That is,MnO nanocubes with an edge length of 61.82 nm were successfully prepared through electros-pinning and one-step pyrolysis as the cathode electrode for Li-O_(2)batteries.It is observed that the intermediate LiMnO_(4)rather than Li_(2)O_(2)is formed when LiO_(2)interactes with MnO(111)during the discharge process.It is precisely because of LiMnO_(4)that reduces its charge overpotential to 0.29 V.The novel reaction mechanism dominated by LiMnO_(4)further facilitates the lower charge overpotential,thereby enhancing the energy efficiency of the batteries.展开更多
Due to the centralization of charging stations(CSs),CSs are organized as charging station alliances(CSAs)in the commercial competition.Under this situation,this paper studies the profit-oriented dynamic pricing strate...Due to the centralization of charging stations(CSs),CSs are organized as charging station alliances(CSAs)in the commercial competition.Under this situation,this paper studies the profit-oriented dynamic pricing strategy of CSAs.As the practicability basis,a privacy-protected bidirectional real-time information interaction framework is designed,under which the status of EVs is utilized as the reference for pricing,and the prices of CSs are the reference for charging decisions.Based on this framework,the decision-making models of EVs and CSs are established,in which the uncertainty caused by the information asymmetry between EVs and CSs and the bounded rationality of EV users are integrated.To solve the pricing decision model,the evolutionary game theory is adopted to describe the dynamic pricing game among CSAs,the equilibrium of which gives the optimal pricing strategy.Finally,the case study conducted in an urban area of Shanghai,China,validates the practicability of the framework and the effectiveness of the dynamic pricing strategy.展开更多
In the Jimusaer Sag of the Junggar Basin,crude oils from the upper and lower sweet-spot intervals of the Permian Lucaogou Formation display a pronounced“light-heavy reversal”in oil properties that indicates a fundam...In the Jimusaer Sag of the Junggar Basin,crude oils from the upper and lower sweet-spot intervals of the Permian Lucaogou Formation display a pronounced“light-heavy reversal”in oil properties that indicates a fundamental mismatch between oil composition and host rock maturity.To resolve this anomaly,this study integrates geological,geochemical,and petrophysical datasets and systematically evaluates the combined roles of thermal evolution,organofacies,wettability,abnormal overpressure,and migration-related fractionation on shale oil composition.On this basis,a“staged charging-cumulative charging”model is proposed to explain compositional heterogeneity in lacustrine shale oils.The results demonstrate that crude-oil compositions are jointly controlled by the extent of biomarker depletion,the temporal evolution of hydrocarbon charging,and the openness of the source-reservoir system,rather than by thermal maturity or organofacies alone.The upper sweet-spot interval is interpreted to have functioned as a semi-open system during early stages,in which hydrocarbon generation and expulsion were broadly synchronous,leading to preferential loss of early-generated,biomarker-rich heavy components,whereas progressive shale diagenesis at later stages promoted the retention of highly mature,light hydrocarbons.In contrast,the lower sweet-spot interval represents a relatively closed system,where hydrocarbons generated during multiple stages continuously accumulated and were preserved as mixed charges;overprinting by multi-phase fluids progressively weakened sterane isomerization signals,rendering them unreliable indicators of individual charging events or final thermal maturity.This charging behavior provides a reasonable explanation for anomalously low or distorted biomarker parameters observed in intervals of low or similar maturity.Overall,the proposed charging model reconciles the observed reversal in crude-oil properties and,by shifting the interpretive focus from static maturity assessment to charging dynamics,offers a new theoretical basis for understanding lacustrine shale oil accumulation processes,and guiding sweet-spot selection and exploration-development strategies.展开更多
Under the background of achieving energy efficiency and carbon reduction,the use of Continuous Casting-Direct Hot Charging Rolling(CC-DHCR)technology was explored at the Hot Rolling Plant of Baosteel,China.As temperat...Under the background of achieving energy efficiency and carbon reduction,the use of Continuous Casting-Direct Hot Charging Rolling(CC-DHCR)technology was explored at the Hot Rolling Plant of Baosteel,China.As temperature variation and temperature uniformity directly affect the rolling quality of the billet,numerical simulations of the billet temperature profile changes in the CC-DHCR were conducted at the start of the industrial trial,and the billet temperature distribution and cross-section temperature difference during its transportation and throughout the heating process were analyzed.According to numerical simulation calculations,the average temperature of billet discharged from the heating furnace was 1150℃,which after subsequent controlled cooling met the final rolling temperature requirements of(880±30)℃for this kind of steel.The maximum temperature difference of the billet discharged from the furnace was within 35 K,which meets the billet heating uniformity requirements of the rolling process.The simulation results were compared with experimental results,and the rationality of the simulation was validated.In addition,the industrial trial billet was rolled,and the rolling quality was good during tracking.In this CC-DHCR industrial trial,the fuel consumption was 28.6 kgce/t(kilogram coal equivalent per ton),a reduction of 33.7%compared with the current traditional process,and CO 2 emissions were reduced by 38.09 kg/t.展开更多
Achieving extreme fast charging(XFC,-6 C)capability remains a challenge for Li ion batteries in electric vehicle applications.This work employs time-resolved X-ray diffraction(XRD)to investigate the structural evoluti...Achieving extreme fast charging(XFC,-6 C)capability remains a challenge for Li ion batteries in electric vehicle applications.This work employs time-resolved X-ray diffraction(XRD)to investigate the structural evolution and capacity contributions of a series of LiNi_(x)Co_(y)Mn_(z)O_(2)(x+y+z=1,NCM)cathodes under XFC conditions.All NCM cathodes(NCM-92,NCM-83,and NCM-622)deliver -60%of their capacities with less than 2%unit cell volume expansion during the H1-H2 phase transition,but the subsequent H2-H3 phase transition exhibits significant compositional and rate dependence.The NCM-92 cathode shows a maximum d-spacing shrinkage of-5.3%at 6 C,which is larger than that of NCM-83(-4.1%)and NCM-622(-0.05%).Furthermore,NCM-92 follows a“phase heterogeneity”pathway for its structural evolution above 4.2 V,distinct from the“solid-solution”pathway observed in NCM-83 and NCM-622.This phase heterogeneity is evidenced by the splitting of the(003)diffraction peak and a decrease in intensity during the H2-H3 phase transition,indicating the formation of lithium-rich/depleted domains.These findings establish a direct correlation between cathode composition,structural dynamics,and XFC performance,highlighting a critical trade-off between structural stability and fast-charging capability in nickel-rich layered oxides.展开更多
Zn-based thermal charging devices,utilizing the synergistic effect of ion thermoextraction and thermodiffusion,are able to efficiently convert thermal energy into electrical energy and storage in the devices,making th...Zn-based thermal charging devices,utilizing the synergistic effect of ion thermoextraction and thermodiffusion,are able to efficiently convert thermal energy into electrical energy and storage in the devices,making them a highly promising technology for low-grade heat recovery and utilization.However,the low output power density and energy conversion efficiency resulted by the slow diffusion kinetics of Zn^(2+)hinder their development.Herein,we present a highperformance thermal charging cell design using Zn^(2+)/NH_(4)^(+)hybrid ion electrolyte,which not only maintains the high output voltage of the Zn-based thermoelectric system,but also significantly enhances the output power density due to the fast diffusion kinetics of NH_(4)^(+).Based on this strategy,the thermal charging cell displays a high thermopower of 12.5 mV K^(-1)and an excellent normalized power density of 19.6 mW m^(-2)K^(-2)at a temperature difference of 35 K.The Carnot-relative efficiency is as high as 12.74%.Moreover,it can operate continuously for over 72 h when the temperature difference persists,achieving a balance between thermoelectric conversion and output.This work provides a simple and effective strategy for the design of high-performance thermal charging cells for low-grade heat conversion and utilization.展开更多
To address the performance limitations of conventional LiPF6-carbonate electrolytes under extreme temperatures and high-rate charging,lithium difluoro(oxalato)borate(LiDFOB)is introduced into the LiPF6-carbonate elect...To address the performance limitations of conventional LiPF6-carbonate electrolytes under extreme temperatures and high-rate charging,lithium difluoro(oxalato)borate(LiDFOB)is introduced into the LiPF6-carbonate electrolyte to form a dual-salt system.The optimization mechanism enhancing the fast-charging capability of LiNi_(0.52)Co_(0.2)Mn_(0.28)O_(2)(NCM523)cathode is systematically explored.Molecular dynamics simulations and electrochemical characterization demonstrate the reconstruction of Li+solvation structures,expanding the voltage window and reducting Li^(+)desolvation barriers.In addition,the incorporation of LiDFOB induces the generation of a LiF/Li_(x)BO_(y)F_(z)-enriched cathode-electrolyte interphase,which effectively suppresses the dissolution of transition metals.In situ impedance measurements reveal the accelerated interfacial charge transfer kinetics.As expected,the NCM523 cathode achieves an 82%state-of-charge(SOC)in 12 min at 5 C(25°C)with 87%capacity retention after 100 cycles,and exhibits a 65%higher discharge capacity at 1 C than the baseline at−20°C.The 1 Ah pouch cells based on LiNi_(0.52)Co_(0.2)Mn_(0.28)O_(2)cathodes,graphite anodes,and 0.5 wt%LiDFOB-modified electrolyte demonstrate fast-charging capabilities:charging 97%of the pouch cell capacity within 30 min(2 C)and 80%within 15 min(4 C)at 25°C.This study offers a practical electrolyte design strategy that enhances the fast-charging performance of lithium-ion batteries(LIBs)over a wide temperature range(from−20 to 25°C).展开更多
Objective The natural gas exploration of the Sinian reservoirs in the central Sichuan Basin has made a significant breakthrough in recent years, and has thus attracted much attention among geologists. The Sichuan Bas...Objective The natural gas exploration of the Sinian reservoirs in the central Sichuan Basin has made a significant breakthrough in recent years, and has thus attracted much attention among geologists. The Sichuan Basin is known to have complicated geological settings, which has experienced multiple stages of tectonic evolution, fluid charging and hydrocarbon accumulation. This research aims to determine the geochemical characteristics of each stage of fluids, the features and time interval of fluid activity in different geologic periods, and further to restore the critical period and geological age of the hydrocarbon accumulation.展开更多
Conventional multi-stage constant current charging strategies often use higher multiples of current to charge the battery in pursuit of shorter charging times.However,this leads to an increase in battery temperature,w...Conventional multi-stage constant current charging strategies often use higher multiples of current to charge the battery in pursuit of shorter charging times.However,this leads to an increase in battery temperature,while shortening the charging time.This in turn affects the safety of the charging process.Furthermore,the higher charging currents are not ideal for shortening the charging time in the later stages of charging.To solve the aforementioned problems,in this study,a multi-stage constant current charging strategy is presented.This strategy can shorten the battery charging time by using the increase in battery temperature during the charging process as a constraint,using a genetic algorithm to calculate the charging current value,and investigating the phased approach to charging.Finally,the charging strategy is experimentally validated at different ambient temperatures and different initial SOCs.The experimental results show that the charging strategy proposed in this paper not only reduces the amount of calculations,but also reduces the temperature rise by up to 46.4%and charging time by up to 4.2%under different operating conditions.展开更多
Asphalts distributed widely in the Silurian sandstones of the Tarim Basin include dry asphalt, soft asphalt and heavy oil. These asphaltic sandstones underwent multi-episodic sedimentary and tectonic events, and their...Asphalts distributed widely in the Silurian sandstones of the Tarim Basin include dry asphalt, soft asphalt and heavy oil. These asphaltic sandstones underwent multi-episodic sedimentary and tectonic events, and their occurrence is diverse and complex, being mixed with normal oil usually. So far, very little work has been done on the asphaltic sandstone origin and hydrocarbon charging ages. After detailed study on the Silurian sandstones, the following highlights were obtained from the analytical results: distribution of the mixed asphalt, heavy oil and normal oil in the Silurian sandstones is the result of multi-stage hydrocarbon charging from the Lower Paleozoic marine source rocks; the characters of asphalts formed from oils of different charging ages are of difference; the most important process constraining the asphaltic sandstone origin is thought to be biodegradation.展开更多
This paper introduces a method for modeling the entire aggregated electric vehicle(EV)charging process and analyzing its dispatchable capabilities.The methodology involves developing a model for aggregated EV charging...This paper introduces a method for modeling the entire aggregated electric vehicle(EV)charging process and analyzing its dispatchable capabilities.The methodology involves developing a model for aggregated EV charging at the charging station level,estimating its physical dispatchable capability,determining its economic dispatchable capability under economic incentives,modeling its participation in the grid,and investigating the effects of different scenarios and EV penetration on the aggregated load dispatch and dispatchable capability.The results indicate that using economic dispatchable capability reduces charging prices by 9.7%compared to physical dispatchable capability and 9.3%compared to disorderly charging.Additionally,the peak-to-valley difference is reduced by 64.6%when applying economic dispatchable capability with 20%EV penetration and residential base load,compared to disorderly charging.展开更多
Lithium-ion batteries(LIBs)are an electrochemical energy storage technology that has been widely used for portable electrical devices,electric vehicles,and grid storage,etc.To satisfy the demand for user convenience e...Lithium-ion batteries(LIBs)are an electrochemical energy storage technology that has been widely used for portable electrical devices,electric vehicles,and grid storage,etc.To satisfy the demand for user convenience especially for electric vehicles,the development of a fast-charging technology for LIBs has become a critical focus.In commercial LIBs,the slow kinetics of Li+intercalation into the graphite anode from the electrolyte solution is known as the main restriction for fast-charging.We summarize the recent advances in obtaining fast-charging graphite-based anodes,mainly involving modifications of the electrolyte solution and graphite anode.Specifically,strategies for increasing the ionic conductivity and regulating the Li+solvation/desolvation state in the electrolyte solution,as well as optimizing the fabrication and the intrinsic activity of graphite-based anodes are discussed in detail.This review considers practical ways to obtain fast Li+intercalation kinetics into a graphite anode from the electrolyte as well as analysing progress in the commercialization of fast-charging LIBs.展开更多
In China,electric vehicle(EV)fast-charging power has quadrupled in the past five years,progressing toward 10-minute ultrafast charging.This rapid increase raises concerns about the impact on the power grid including i...In China,electric vehicle(EV)fast-charging power has quadrupled in the past five years,progressing toward 10-minute ultrafast charging.This rapid increase raises concerns about the impact on the power grid including increased peak power demand and the need for substantial upgrades to power infrastruc-ture.Here,we introduce an integrated model to assess fast and ultrafast charging impacts for represen-tative charging stations in China,combining real-world charging patterns and detailed station optimization models.We find that larger stations with 12 or more chargers experience modest peak power increases of less than 30%when fast-charging power is doubled,primarily because shorter charg-ing sessions are less likely to overlap.For more typical stations(e.g.,8-9 chargers and 120 kW·charger^(−1)),upgrading chargers to 350-550 kW while allowing managed dynamic waiting strategies(of∼1 minute)can reduce overall charging times to∼9 minutes.At stations,deploying battery storage and/or expanding transformers can help manage future increases in station loads,yet the primary device cost of the former is∼4 times higher than that of the latter.Our results offer insights for charging infrastructure planning,EV-grid interactions,and associated policymaking.展开更多
The application of machine learning for pyrite discrimination establishes a robust foundation for constructing the ore-forming history of multi-stage deposits;however,published models face challenges related to limite...The application of machine learning for pyrite discrimination establishes a robust foundation for constructing the ore-forming history of multi-stage deposits;however,published models face challenges related to limited,imbalanced datasets and oversampling.In this study,the dataset was expanded to approximately 500 samples for each type,including 508 sedimentary,573 orogenic gold,548 sedimentary exhalative(SEDEX)deposits,and 364 volcanogenic massive sulfides(VMS)pyrites,utilizing random forest(RF)and support vector machine(SVM)methodologies to enhance the reliability of the classifier models.The RF classifier achieved an overall accuracy of 99.8%,and the SVM classifier attained an overall accuracy of 100%.The model was evaluated by a five-fold cross-validation approach with 93.8%accuracy for the RF and 94.9%for the SVM classifier.These results demonstrate the strong feasibility of pyrite classification,supported by a relatively large,balanced dataset and high accuracy rates.The classifier was employed to reveal the genesis of the controversial Keketale Pb-Zn deposit in NW China,which has been inconclusive among SEDEX,VMS,or a SEDEX-VMS transition.Petrographic investigations indicated that the deposit comprises early fine-grained layered pyrite(Py1)and late recrystallized pyrite(Py2).The majority voting classified Py1 as the VMS type,with an accuracy of RF and SVM being 72.2%and 75%,respectively,and confirmed Py2 as an orogenic type with 74.3% and 77.1%accuracy,respectively.The new findings indicated that the Keketale deposit originated from a submarine VMS mineralization system,followed by late orogenic-type overprinting of metamorphism and deformation,which is consistent with the geological and geochemical observations.This study further emphasizes the advantages of Machine learning(ML)methods in accurately and directly discriminating the deposit types and reconstructing the formation history of multi-stage deposits.展开更多
文摘To reduce the carbon footprint in the transportation sector and improve overall vehicle efficiency,a large number of electric vehicles are being manufactured.This is due to the fact that environmental concerns and the depletion of fossil fuels have become significant global problems.Lithium-ion batteries(LIBs)have been distinguished themselves from alternative energy storage technologies for electric vehicles(EVs) due to superior qualities like high energy and power density,extended cycle life,and low maintenance cost to a competitive price.However,there are still certain challenges to be solved,like EV fast charging,longer lifetime,and reduced weight.For fast charging,the multi-stage constant current(MSCC) charging technique is an emerging solution to improve charging efficiency,reduce temperature rise during charging,increase charging/discharging capacities,shorten charging time,and extend the cycle life.However,there are large variations in the implementation of the number of stages,stage transition criterion,and C-rate selection for each stage.This paper provides a review of these problems by compiling information from the literature.An overview of the impact of different design parameters(number of stages,stage transition,and C-rate) that the MSCC charging techniques have had on the LIB performance and cycle life is described in detail and analyzed.The impact of design parameters on lifetime,charging efficiency,charging and discharging capacity,charging speed,and rising temperature during charging is presented,and this review provides guidelines for designing advanced fast charging strategies and determining future research gaps.
文摘Rapid evolutions of the Internet of Electric Vehicles(IoEVs)are reshaping and modernizing transport systems,yet challenges remain in energy efficiency,better battery aging,and grid stability.Typical charging methods allow for EVs to be charged without thought being given to the condition of the battery or the grid demand,thus increasing energy costs and battery aging.This study proposes a smart charging station with an AI-powered Battery Management System(BMS),developed and simulated in MATLAB/Simulink,to increase optimality in energy flow,battery health,and impractical scheduling within the IoEV environment.The system operates through real-time communication,load scheduling based on priorities,and adaptive charging based on batterymathematically computed State of Charge(SOC),State of Health(SOH),and thermal state,with bidirectional power flow(V2G),thus allowing EVs’participation towards grid stabilization.Simulation results revealed that the proposed model can reduce peak grid load by 37.8%;charging efficiency is enhanced by 92.6%;battery temperature lessened by 4.4℃;SOH extended over 100 cycles by 6.5%,if compared against the conventional technique.By this way,charging time was decreased by 12.4% and energy costs dropped by more than 20%.These results showed that smart charging with intelligent BMS can boost greatly the operational efficiency and sustainability of the IoEV ecosystem.
基金Project supported by the National Natural Science Foundation of China(Grant No.12175107)the Qing Lan Project of Jiangsu Province+2 种基金the Hua Li Talents Program of Nanjing University of PostsTelecommunications,Natural Science Foundation of Nanjing Vocational University of Industry Technology(Grant No.YK22-02-08)the Fund from the Research Center of Industrial Perception and Intelligent Manufacturing Equipment Engineering of Jiangsu Province,China(Grant No.ZK21-05-09)。
文摘Surface polaritons,as surface electromagnetic waves propagating along the surface of a medium,have played a crucial role in enhancing photonic spin Hall effect(PSHE)and developing highly sensitive refractive index(RI)sensors.Among them,the traditional surface plasmon polariton(SPP)based on noble metals limits its application beyond the near-infrared(IR)regime due to the large negative permittivity and optical losses.In this contribution,we theoretically proposed a highly sensitive PSHE sensor with the structure of Ge prism-SiC-Si:InAs-sensing medium,by taking advantage of the hybrid surface plasmon phonon polariton(SPPhP)in mid-IR regime.Here,heavily Si-doped InAs(Si:InAs)and SiC excite the SPP and surface phonon polariton(SPhP),and the hybrid SPPhP is realized in this system.More importantly,the designed PSHE sensor based on this SPPhP mechanism achieves the multi-stage RI measurements from 1.00025-1.00225 to 1.70025-1.70225,and the maximal intensity sensitivity and angle sensitivity can be up to 9.4×10^(4)μm/RIU and245°/RIU,respectively.These findings provide a new pathway for the enhancement of PSHE in mid-IR regime,and offer new opportunities to develop highly sensitive RI sensors in multi-scenario applications,such as harmful gas monitoring and biosensing.
基金Supported by State Grid Corporation of China Science and Technology Project:Research on Key Technologies for Intelligent Carbon Metrology in Vehicle-to-Grid Interaction(Project Number:B3018524000Q).
文摘To achieve low-carbon regulation of electric vehicle(EV)charging loads under the“dual carbon”goals,this paper proposes a coordinated scheduling strategy that integrates dynamic carbon factor prediction and multiobjective optimization.First,a dual-convolution enhanced improved Crossformer prediction model is constructed,which employs parallel 1×1 global and 3×3 local convolutionmodules(Integrated Convolution Block,ICB)formultiscale feature extraction,combinedwith anAdaptive Spectral Block(ASB)to enhance time-series fluctuationmodeling.Based on high-precision predictions,a carbon-electricity cost joint optimization model is further designed to balance economic,environmental,and grid-friendly objectives.The model’s superiority was validated through a case study using real-world data from a renewable-heavy grid.Simulation results show that the proposed multi-objective strategy demonstrated a superior balance compared to baseline and benchmark models,achieving a 15.8%reduction in carbon emissions and a 5.2%reduction in economic costs,while still providing a substantial 22.2%reduction in the peak-valley difference.Its balanced performance significantly outperformed both a single-objective strategy and a state-of-the-art Model Predictive Control(MPC)benchmark,highlighting the advantage of a global optimization approach.This study provides theoretical and technical pathways for dynamic carbon factor-driven EV charging optimization.
基金supported by Science and Technology Project of China Southern Power Grid Company(036000KK52222007(GDKJXM20222121)).
文摘As renewable energy penetration continues to rise,enhancing power system flexibility has become a critical requirement.Photovoltaic–storage–charging stations(PSCSs)are key components for enhancing local regulation capability and promoting renewable integration.However,evaluating the adjustable capability of such hybrid stations while considering security constraints remains a major challenge.This paper first analyzes the adjustable capabilities of all the resources within such a station based on the power-energy boundary(PEB)model.Then,an optimal formulation is proposed to obtain the adjusted parameters of the aggregate feasible region(AFR)model,which embeds low-dimensional linear models within high-dimensional linear models to improve the accuracy.To solve this formulation,it is transformed using duality theory and an alternating optimization algorithm is designed to obtain the solution.Finally,a multi-station adjustable capability aggregation method considering security constraints is introduced.Simulation results verify that the proposed method effectively reduces infeasible regions and improves smoothness of aggregated boundaries,providing an accurate and practical tool for flexibility evaluation in PSCSs and offering guidance for aggregators and system planners.
基金supported by the Shanghai Pilot Program for Basic Research(22T01400100-18)the National Natural Science Foundation of China(22278127 and 12447149)+1 种基金the Fundamental Research Funds for the Central Universities(2022ZFJH004)the Postdoctoral Fellowship Program of CPSF(GZB20250159).
文摘Accurate state of health(SOH)estimation is essential for the safe and reliable operation of lithium-ion batteries.However,existing methods face significant challenges,primarily because they rely on complete charge–discharge cycles and fixed-form physical constraints,which limit adaptability to different chemistries and real-world conditions.To address these issues,this study proposes an approach that extracts features from segmented state of charge(SOC)intervals and integrates them into an enhanced physics-informed neural network(PINN).Specifically,voltage data within the 25%–75%SOC range during charging are used to derive statistical,time–frequency,and mechanism-based features that capture degradation trends.A hybrid PINN-Lasso-Transformer-BiLSTM architecture is developed,where Lasso regression enables sparse feature selection,and a nonlinear empirical degradation model is embedded as a learnable physical term within a dynamically scaled composite loss.This design adaptively balances data-driven accuracy with physical consistency,thereby enhancing estimation precision,robustness,and generalization.The results show that the proposed method outperforms conventional neural networks across four battery chemistries,achieving root mean square error and mean absolute error below 1%.Notably,features from partial charging segments exhibit higher robustness than those from full cycles.Furthermore,the model maintains strong performance under high temperatures and demonstrates excellent generalization capacity in transfer learning across chemistries,temperatures,and C-rates.This work establishes a scalable and interpretable solution for accurate SOH estimation under diverse practical operating conditions.
基金Funded by the National Natural Science Foundation of China(No.22075035)the Technology Planning Project of Liaoning Province(No.2020JH2/10700008)the Dalian Science and Technology Innovation Fund Project(No.2022JJ11CG005)。
文摘We proposed a strategy to address the issue by synthesizing MnO with half-filled 3 d electron orbitals.That is,MnO nanocubes with an edge length of 61.82 nm were successfully prepared through electros-pinning and one-step pyrolysis as the cathode electrode for Li-O_(2)batteries.It is observed that the intermediate LiMnO_(4)rather than Li_(2)O_(2)is formed when LiO_(2)interactes with MnO(111)during the discharge process.It is precisely because of LiMnO_(4)that reduces its charge overpotential to 0.29 V.The novel reaction mechanism dominated by LiMnO_(4)further facilitates the lower charge overpotential,thereby enhancing the energy efficiency of the batteries.
基金sponsored in part by the National Natural Science Foundation of China(52167014)in part by the Science and Technology Commission of Shanghai Municipality(23XD1422000,23QB1400500).
文摘Due to the centralization of charging stations(CSs),CSs are organized as charging station alliances(CSAs)in the commercial competition.Under this situation,this paper studies the profit-oriented dynamic pricing strategy of CSAs.As the practicability basis,a privacy-protected bidirectional real-time information interaction framework is designed,under which the status of EVs is utilized as the reference for pricing,and the prices of CSs are the reference for charging decisions.Based on this framework,the decision-making models of EVs and CSs are established,in which the uncertainty caused by the information asymmetry between EVs and CSs and the bounded rationality of EV users are integrated.To solve the pricing decision model,the evolutionary game theory is adopted to describe the dynamic pricing game among CSAs,the equilibrium of which gives the optimal pricing strategy.Finally,the case study conducted in an urban area of Shanghai,China,validates the practicability of the framework and the effectiveness of the dynamic pricing strategy.
基金Supported by the National Natural Science Foundation of China(42173030,42302161,42473034)State Science and Technology Major Project for New Oil and Gas Exploration and Development,Ministry of Science and Technology(2025ZD1400803)。
文摘In the Jimusaer Sag of the Junggar Basin,crude oils from the upper and lower sweet-spot intervals of the Permian Lucaogou Formation display a pronounced“light-heavy reversal”in oil properties that indicates a fundamental mismatch between oil composition and host rock maturity.To resolve this anomaly,this study integrates geological,geochemical,and petrophysical datasets and systematically evaluates the combined roles of thermal evolution,organofacies,wettability,abnormal overpressure,and migration-related fractionation on shale oil composition.On this basis,a“staged charging-cumulative charging”model is proposed to explain compositional heterogeneity in lacustrine shale oils.The results demonstrate that crude-oil compositions are jointly controlled by the extent of biomarker depletion,the temporal evolution of hydrocarbon charging,and the openness of the source-reservoir system,rather than by thermal maturity or organofacies alone.The upper sweet-spot interval is interpreted to have functioned as a semi-open system during early stages,in which hydrocarbon generation and expulsion were broadly synchronous,leading to preferential loss of early-generated,biomarker-rich heavy components,whereas progressive shale diagenesis at later stages promoted the retention of highly mature,light hydrocarbons.In contrast,the lower sweet-spot interval represents a relatively closed system,where hydrocarbons generated during multiple stages continuously accumulated and were preserved as mixed charges;overprinting by multi-phase fluids progressively weakened sterane isomerization signals,rendering them unreliable indicators of individual charging events or final thermal maturity.This charging behavior provides a reasonable explanation for anomalously low or distorted biomarker parameters observed in intervals of low or similar maturity.Overall,the proposed charging model reconciles the observed reversal in crude-oil properties and,by shifting the interpretive focus from static maturity assessment to charging dynamics,offers a new theoretical basis for understanding lacustrine shale oil accumulation processes,and guiding sweet-spot selection and exploration-development strategies.
文摘Under the background of achieving energy efficiency and carbon reduction,the use of Continuous Casting-Direct Hot Charging Rolling(CC-DHCR)technology was explored at the Hot Rolling Plant of Baosteel,China.As temperature variation and temperature uniformity directly affect the rolling quality of the billet,numerical simulations of the billet temperature profile changes in the CC-DHCR were conducted at the start of the industrial trial,and the billet temperature distribution and cross-section temperature difference during its transportation and throughout the heating process were analyzed.According to numerical simulation calculations,the average temperature of billet discharged from the heating furnace was 1150℃,which after subsequent controlled cooling met the final rolling temperature requirements of(880±30)℃for this kind of steel.The maximum temperature difference of the billet discharged from the furnace was within 35 K,which meets the billet heating uniformity requirements of the rolling process.The simulation results were compared with experimental results,and the rationality of the simulation was validated.In addition,the industrial trial billet was rolled,and the rolling quality was good during tracking.In this CC-DHCR industrial trial,the fuel consumption was 28.6 kgce/t(kilogram coal equivalent per ton),a reduction of 33.7%compared with the current traditional process,and CO 2 emissions were reduced by 38.09 kg/t.
基金financially supported by Fujian Science&Technology Innovation Laboratory for Energy Devices of China(21C LAB)。
文摘Achieving extreme fast charging(XFC,-6 C)capability remains a challenge for Li ion batteries in electric vehicle applications.This work employs time-resolved X-ray diffraction(XRD)to investigate the structural evolution and capacity contributions of a series of LiNi_(x)Co_(y)Mn_(z)O_(2)(x+y+z=1,NCM)cathodes under XFC conditions.All NCM cathodes(NCM-92,NCM-83,and NCM-622)deliver -60%of their capacities with less than 2%unit cell volume expansion during the H1-H2 phase transition,but the subsequent H2-H3 phase transition exhibits significant compositional and rate dependence.The NCM-92 cathode shows a maximum d-spacing shrinkage of-5.3%at 6 C,which is larger than that of NCM-83(-4.1%)and NCM-622(-0.05%).Furthermore,NCM-92 follows a“phase heterogeneity”pathway for its structural evolution above 4.2 V,distinct from the“solid-solution”pathway observed in NCM-83 and NCM-622.This phase heterogeneity is evidenced by the splitting of the(003)diffraction peak and a decrease in intensity during the H2-H3 phase transition,indicating the formation of lithium-rich/depleted domains.These findings establish a direct correlation between cathode composition,structural dynamics,and XFC performance,highlighting a critical trade-off between structural stability and fast-charging capability in nickel-rich layered oxides.
基金supported by the Leading Edge Technology of Jiangsu Province(BK20222009-X.Z.,BK20202008-X.Z.)Priority Academic Program Development of Jiangsu Higher Education Institutions(PAPD)National Undergraduate Innovation Training Program of NUAA(202410287179Y).
文摘Zn-based thermal charging devices,utilizing the synergistic effect of ion thermoextraction and thermodiffusion,are able to efficiently convert thermal energy into electrical energy and storage in the devices,making them a highly promising technology for low-grade heat recovery and utilization.However,the low output power density and energy conversion efficiency resulted by the slow diffusion kinetics of Zn^(2+)hinder their development.Herein,we present a highperformance thermal charging cell design using Zn^(2+)/NH_(4)^(+)hybrid ion electrolyte,which not only maintains the high output voltage of the Zn-based thermoelectric system,but also significantly enhances the output power density due to the fast diffusion kinetics of NH_(4)^(+).Based on this strategy,the thermal charging cell displays a high thermopower of 12.5 mV K^(-1)and an excellent normalized power density of 19.6 mW m^(-2)K^(-2)at a temperature difference of 35 K.The Carnot-relative efficiency is as high as 12.74%.Moreover,it can operate continuously for over 72 h when the temperature difference persists,achieving a balance between thermoelectric conversion and output.This work provides a simple and effective strategy for the design of high-performance thermal charging cells for low-grade heat conversion and utilization.
基金financially supported by the National Natural Science Foundation of China (Grant No. 52372191)the National Natural Science Foundation of China (Grant No. 22271106)+2 种基金the National Science Foundation of China (Grant Nos. 52073286 (C.-Z.L.), 22275185 (C.-Z.L.))the Fujian Science&Technology Innovation Laboratory for Optoelectronic Information of China(2021ZZ115 (C.-Z.L.)the XMIREM Autonomously Deployment Project (2023GG01 (C.-Z.L.))
文摘To address the performance limitations of conventional LiPF6-carbonate electrolytes under extreme temperatures and high-rate charging,lithium difluoro(oxalato)borate(LiDFOB)is introduced into the LiPF6-carbonate electrolyte to form a dual-salt system.The optimization mechanism enhancing the fast-charging capability of LiNi_(0.52)Co_(0.2)Mn_(0.28)O_(2)(NCM523)cathode is systematically explored.Molecular dynamics simulations and electrochemical characterization demonstrate the reconstruction of Li+solvation structures,expanding the voltage window and reducting Li^(+)desolvation barriers.In addition,the incorporation of LiDFOB induces the generation of a LiF/Li_(x)BO_(y)F_(z)-enriched cathode-electrolyte interphase,which effectively suppresses the dissolution of transition metals.In situ impedance measurements reveal the accelerated interfacial charge transfer kinetics.As expected,the NCM523 cathode achieves an 82%state-of-charge(SOC)in 12 min at 5 C(25°C)with 87%capacity retention after 100 cycles,and exhibits a 65%higher discharge capacity at 1 C than the baseline at−20°C.The 1 Ah pouch cells based on LiNi_(0.52)Co_(0.2)Mn_(0.28)O_(2)cathodes,graphite anodes,and 0.5 wt%LiDFOB-modified electrolyte demonstrate fast-charging capabilities:charging 97%of the pouch cell capacity within 30 min(2 C)and 80%within 15 min(4 C)at 25°C.This study offers a practical electrolyte design strategy that enhances the fast-charging performance of lithium-ion batteries(LIBs)over a wide temperature range(from−20 to 25°C).
基金supported by the Natural Science Foundation of China(grant No.41372141)
文摘Objective The natural gas exploration of the Sinian reservoirs in the central Sichuan Basin has made a significant breakthrough in recent years, and has thus attracted much attention among geologists. The Sichuan Basin is known to have complicated geological settings, which has experienced multiple stages of tectonic evolution, fluid charging and hydrocarbon accumulation. This research aims to determine the geochemical characteristics of each stage of fluids, the features and time interval of fluid activity in different geologic periods, and further to restore the critical period and geological age of the hydrocarbon accumulation.
基金supported by National Natural Science Foundation of China (Grant No. 51677058)
文摘Conventional multi-stage constant current charging strategies often use higher multiples of current to charge the battery in pursuit of shorter charging times.However,this leads to an increase in battery temperature,while shortening the charging time.This in turn affects the safety of the charging process.Furthermore,the higher charging currents are not ideal for shortening the charging time in the later stages of charging.To solve the aforementioned problems,in this study,a multi-stage constant current charging strategy is presented.This strategy can shorten the battery charging time by using the increase in battery temperature during the charging process as a constraint,using a genetic algorithm to calculate the charging current value,and investigating the phased approach to charging.Finally,the charging strategy is experimentally validated at different ambient temperatures and different initial SOCs.The experimental results show that the charging strategy proposed in this paper not only reduces the amount of calculations,but also reduces the temperature rise by up to 46.4%and charging time by up to 4.2%under different operating conditions.
基金ThispaperwasfinanciallysupportedbyfundsofPetroleum&NaturalGasExplorationintheTarimBasinfromthe"State 9thFive YearPlanPeriod"KeyScientificProject (No .96 111)
文摘Asphalts distributed widely in the Silurian sandstones of the Tarim Basin include dry asphalt, soft asphalt and heavy oil. These asphaltic sandstones underwent multi-episodic sedimentary and tectonic events, and their occurrence is diverse and complex, being mixed with normal oil usually. So far, very little work has been done on the asphaltic sandstone origin and hydrocarbon charging ages. After detailed study on the Silurian sandstones, the following highlights were obtained from the analytical results: distribution of the mixed asphalt, heavy oil and normal oil in the Silurian sandstones is the result of multi-stage hydrocarbon charging from the Lower Paleozoic marine source rocks; the characters of asphalts formed from oils of different charging ages are of difference; the most important process constraining the asphaltic sandstone origin is thought to be biodegradation.
基金State Grid Henan Power Company Science and Technology Project‘Key Technology and Demonstration Application of Multi-Domain Electric Vehicle Aggregated Charging Load Dispatch’(5217L0240003).
文摘This paper introduces a method for modeling the entire aggregated electric vehicle(EV)charging process and analyzing its dispatchable capabilities.The methodology involves developing a model for aggregated EV charging at the charging station level,estimating its physical dispatchable capability,determining its economic dispatchable capability under economic incentives,modeling its participation in the grid,and investigating the effects of different scenarios and EV penetration on the aggregated load dispatch and dispatchable capability.The results indicate that using economic dispatchable capability reduces charging prices by 9.7%compared to physical dispatchable capability and 9.3%compared to disorderly charging.Additionally,the peak-to-valley difference is reduced by 64.6%when applying economic dispatchable capability with 20%EV penetration and residential base load,compared to disorderly charging.
文摘Lithium-ion batteries(LIBs)are an electrochemical energy storage technology that has been widely used for portable electrical devices,electric vehicles,and grid storage,etc.To satisfy the demand for user convenience especially for electric vehicles,the development of a fast-charging technology for LIBs has become a critical focus.In commercial LIBs,the slow kinetics of Li+intercalation into the graphite anode from the electrolyte solution is known as the main restriction for fast-charging.We summarize the recent advances in obtaining fast-charging graphite-based anodes,mainly involving modifications of the electrolyte solution and graphite anode.Specifically,strategies for increasing the ionic conductivity and regulating the Li+solvation/desolvation state in the electrolyte solution,as well as optimizing the fabrication and the intrinsic activity of graphite-based anodes are discussed in detail.This review considers practical ways to obtain fast Li+intercalation kinetics into a graphite anode from the electrolyte as well as analysing progress in the commercialization of fast-charging LIBs.
基金the support of the National Natural Science Foundation of China(72325006,72488101,and 72293601)the Sze Family Foundationthe Climate Imperative Foundation(#2024-001465)
文摘In China,electric vehicle(EV)fast-charging power has quadrupled in the past five years,progressing toward 10-minute ultrafast charging.This rapid increase raises concerns about the impact on the power grid including increased peak power demand and the need for substantial upgrades to power infrastruc-ture.Here,we introduce an integrated model to assess fast and ultrafast charging impacts for represen-tative charging stations in China,combining real-world charging patterns and detailed station optimization models.We find that larger stations with 12 or more chargers experience modest peak power increases of less than 30%when fast-charging power is doubled,primarily because shorter charg-ing sessions are less likely to overlap.For more typical stations(e.g.,8-9 chargers and 120 kW·charger^(−1)),upgrading chargers to 350-550 kW while allowing managed dynamic waiting strategies(of∼1 minute)can reduce overall charging times to∼9 minutes.At stations,deploying battery storage and/or expanding transformers can help manage future increases in station loads,yet the primary device cost of the former is∼4 times higher than that of the latter.Our results offer insights for charging infrastructure planning,EV-grid interactions,and associated policymaking.
基金the National Key Research and Development Program of China(2021YFC2900300)the Natural Science Foundation of Guangdong Province(2024A1515030216)+2 种基金MOST Special Fund from State Key Laboratory of Geological Processes and Mineral Resources,China University of Geosciences(GPMR202437)the Guangdong Province Introduced of Innovative R&D Team(2021ZT09H399)the Third Xinjiang Scientific Expedition Program(2022xjkk1301).
文摘The application of machine learning for pyrite discrimination establishes a robust foundation for constructing the ore-forming history of multi-stage deposits;however,published models face challenges related to limited,imbalanced datasets and oversampling.In this study,the dataset was expanded to approximately 500 samples for each type,including 508 sedimentary,573 orogenic gold,548 sedimentary exhalative(SEDEX)deposits,and 364 volcanogenic massive sulfides(VMS)pyrites,utilizing random forest(RF)and support vector machine(SVM)methodologies to enhance the reliability of the classifier models.The RF classifier achieved an overall accuracy of 99.8%,and the SVM classifier attained an overall accuracy of 100%.The model was evaluated by a five-fold cross-validation approach with 93.8%accuracy for the RF and 94.9%for the SVM classifier.These results demonstrate the strong feasibility of pyrite classification,supported by a relatively large,balanced dataset and high accuracy rates.The classifier was employed to reveal the genesis of the controversial Keketale Pb-Zn deposit in NW China,which has been inconclusive among SEDEX,VMS,or a SEDEX-VMS transition.Petrographic investigations indicated that the deposit comprises early fine-grained layered pyrite(Py1)and late recrystallized pyrite(Py2).The majority voting classified Py1 as the VMS type,with an accuracy of RF and SVM being 72.2%and 75%,respectively,and confirmed Py2 as an orogenic type with 74.3% and 77.1%accuracy,respectively.The new findings indicated that the Keketale deposit originated from a submarine VMS mineralization system,followed by late orogenic-type overprinting of metamorphism and deformation,which is consistent with the geological and geochemical observations.This study further emphasizes the advantages of Machine learning(ML)methods in accurately and directly discriminating the deposit types and reconstructing the formation history of multi-stage deposits.
