Wastewater electrolysis cells(WECs)for decentralized wastewater treatment/reuse coupled with H_(2) production can reduce the carbon footprint associated with transportation of water,waste,and energy carrier.This study...Wastewater electrolysis cells(WECs)for decentralized wastewater treatment/reuse coupled with H_(2) production can reduce the carbon footprint associated with transportation of water,waste,and energy carrier.This study reports Ir-doped NiFe_(2)O_(4)(NFI,~5 at%Ir)spinel layer with TiO_(2) overlayer(NFI/TiO_(2)),as a scalable heterojunction anode for direct electrolysis of wastewater with circumneutral pH in a single-compartment cell.In dilute(0.1 M)NaCl solutions,the NFI/TiO_(2) marks superior activity and selectivity for chlorine evolution reaction,outperforming the benchmark IrO_(2).Robust operation in near-neutral pH was confirmed.Electroanalyses including operando X-ray absorption spectroscopy unveiled crucial roles of TiO_(2) which serves both as the primary site for Cl−chemisorption and a protective layer for NFI as an ohmic contact.Galvanostatic electrolysis of NH4+-laden synthetic wastewater demonstrated that NFI/TiO_(2)not only achieves quasi-stoichiometric NH_(4)^(+)-to-N_(2)conversion,but also enhances H_(2)generation efficiency with minimal competing reactions such as reduction of dissolved oxygen and reactive chlorine.The scaled-up WEC with NFI/TiO_(2)was demonstrated for electrolysis of toilet wastewater.展开更多
Root tips are the main components of absorptive fine roots,but their seasonal dynamics and relationship to environmental factors remain unclear due to the difficulties in methodology.In this study,we explored the temp...Root tips are the main components of absorptive fine roots,but their seasonal dynamics and relationship to environmental factors remain unclear due to the difficulties in methodology.In this study,we explored the temporal patterns of root-tip production and mortality in monoculture plantations of five temperate tree species at a common site in northeastern China,and identified the general environmental controls on such processes.We made monthly in-situ assessments of root tip length(RTL)production and mortality in two hardwood and three coniferous species with a minirhizotron(MR)method during the growing seasons of 2008 and 2009.Air temperature,rainfall,soil temperature and water content at 10 cm depth were determined concurrently.RTL production in all species exhibited consistent peaks in summer(June–August)in two growing seasons.RTL mortality showed substantial interannual and interspecific variability,with peaks in autumn and winter in 2008,but various patterns in 2009.RTL production positively correlated with monthly soil and air temperature across all species,and with monthly rainfall in three coniferous species.However,there was no significant correlation between RTL production and soil water content.By contrast,RTL mortality was weakly related to environmental factors,showing positive correlations with soil temperature in Korean spruce,and with rainfall in Korean pine and Korean spruce.Our findings suggest that the seasonal patterns of RTL production are convergent across the five temperate tree species due to the overlapped distribution of heat and rainfall,which can conduce roots to maximizing the acquisition of nutrient resources in the soil.展开更多
Hydrogen generation and related energy applications heavily rely on the hydrogen evolution reaction(HER),which faces challenges of slow kinetics and high overpotential.Efficient electrocatalysts,particularly single-at...Hydrogen generation and related energy applications heavily rely on the hydrogen evolution reaction(HER),which faces challenges of slow kinetics and high overpotential.Efficient electrocatalysts,particularly single-atom catalysts (SACs) on two-dimensional (2D) materials,are essential.This study presents a few-shot machine learning (ML) assisted high-throughput screening of 2D septuple-atomic-layer Ga_(2)CoS_(4-x)supported SACs to predict HER catalytic activity.Initially,density functional theory (DFT)calculations showed that 2D Ga_(2)CoS4is inactive for HER.However,defective Ga_(2)CoS_(4-x)(x=0–0.25)monolayers exhibit excellent HER activity due to surface sulfur vacancies (SVs),with predicted overpotentials (0–60 mV) comparable to or lower than commercial Pt/C,which typically exhibits an overpotential of around 50 m V in the acidic electrolyte,when the concentration of surface SV is lower than 8.3%.SVs generate spin-polarized states near the Fermi level,making them effective HER sites.We demonstrate ML-accelerated HER overpotential predictions for all transition metal SACs on 2D Ga_(2)CoS_(4-x).Using DFT data from 18 SACs,an ML model with high prediction accuracy and reduced computation time was developed.An intrinsic descriptor linking SAC atomic properties to HER overpotential was identified.This study thus provides a framework for screening SACs on 2D materials,enhancing catalyst design.展开更多
The transition of hydrogen sourcing from carbon-intensive to water-based methodologies is underway,with renewable energy-powered proton exchange membrane water electrolysis(PEMWE)emerging as the preeminent pathway for...The transition of hydrogen sourcing from carbon-intensive to water-based methodologies is underway,with renewable energy-powered proton exchange membrane water electrolysis(PEMWE)emerging as the preeminent pathway for hydrogen production.Despite remarkable advancements in this field,confronting the sluggish electrochemical kinetics and inherent high-energy consumption arising from deteriorated mass transport within PEMWE systems remains a formidable obstacle.This impediment stems primarily from the hindered protons mass transfer and the untimely hydrogen bubbles detachment.To address these challenges,we harness the inherent variability of electrical energy and introduce an innovative pulsed dynamic water electrolysis system.Compared to constant voltage electrolysis(hydrogen production rate:51.6 m L h^(-1),energy consumption:5.37 kWh Nm-^(3)H_(2)),this strategy(hydrogen production rate:66 m L h^(-1),energy consumption:3.83 kWh Nm-^(3)H_(2))increases the hydrogen production rate by approximately 27%and reduces the energy consumption by about 28%.Furthermore,we demonstrate the practicality of this system by integrating it with an off-grid photovoltaic(PV)system designed for outdoor operation,successfully driving a hydrogen production current of up to 500 mA under an average voltage of approximately 2 V.The combined results of in-situ characterization and finite element analysis reveal the performance enhancement mechanism:pulsed dynamic electrolysis(PDE)dramatically accelerates the enrichment of protons at the electrode/solution interface and facilitates the release of bubbles on the electrode surface.As such,PDE-enhanced PEMWE represents a synergistic advancement,concurrently enhancing both the hydrogen generation reaction and associated transport processes.This promising technology not only redefines the landscape of electrolysis-based hydrogen production but also holds immense potential for broadening its application across a diverse spectrum of electrocatalytic endeavors.展开更多
Shale gas, as an environmentally friendly fossil energy resource, has gained significant commercial development and shows immense potential. However, accurately predicting shale gas production faces substantial challe...Shale gas, as an environmentally friendly fossil energy resource, has gained significant commercial development and shows immense potential. However, accurately predicting shale gas production faces substantial challenges due to the complex law of decline, nonlinear and non-stationary features in production data, which greatly repair the robustness of current models in predicting shale gas production time series. To address these challenges and improve accuracy in production forecasting, this paper introduces a novel and innovative approach: a hybrid proxy model that combines the bidirectional long short-term memory(BiLSTM) neural network and random forest(RF) through deep learning. The BiLSTM neural network is adept at capturing long-term dependencies, making it suitable for understanding the intricate relationships between input and output variables in shale gas production.On the other hand, RF serves a dual purpose: reducing model variance and addressing the concept drift problem that arises in non-stationary time series predictions made by BiLSTM. By integrating these two models, the hybrid approach effectively captures the inherent dependencies present in long and nonstationary production time series, thereby reducing model uncertainty. Furthermore, the combination of BiLSTM and RF is optimized using the recently-proposed marine predators algorithm(MPA) to fine-tune hyperparameters and enhance the overall performance of the proxy model. The results demonstrate that the proposed BiLSTM-RF-MPA model achieves higher prediction accuracy and demonstrates stronger generalization capabilities by effectively handling the complex nonlinear and non-stationary characteristics of shale gas production time series. Compared to other models such as LSTM, BiLSTM, and RF, the proposed model exhibits superior fitting and prediction performance, with an average improvement in performance indicators exceeding 20%. This innovative framework provides valuable insights for forecasting the complex production performance of unconventional oil and gas reservoirs, which sheds light on the development of data-driven proxy models in the field of subsurface energy utilization.展开更多
Continuous efforts are underway to reduce carbon emissions worldwide in response to global climate change.Water electrolysis technology,in conjunction with renewable energy,is considered the most feasible hydrogen pro...Continuous efforts are underway to reduce carbon emissions worldwide in response to global climate change.Water electrolysis technology,in conjunction with renewable energy,is considered the most feasible hydrogen production technology based on the viable possibility of large-scale hydrogen production and the zero-carbon-emission nature of the process.However,for hydrogen produced via water electrolysis systems to be utilized in various fields in practice,the unit cost of hydrogen production must be reduced to$1/kg H_(2).To achieve this unit cost,technical targets for water electrolysis have been suggested regarding components in the system.In this paper,the types of water electrolysis systems and the limitations of water electrolysis system components are explained.We suggest guideline with recent trend for achieving this technical target and insights for the potential utilization of water electrolysis technology.展开更多
Herein,ionomer-free amorphous iridium oxide(IrO_(x))thin electrodes are first developed as highly active anodes for proton exchange membrane electrolyzer cells(PEMECs)via low-cost,environmentally friendly,and easily s...Herein,ionomer-free amorphous iridium oxide(IrO_(x))thin electrodes are first developed as highly active anodes for proton exchange membrane electrolyzer cells(PEMECs)via low-cost,environmentally friendly,and easily scalable electrodeposition at room temperature.Combined with a Nafion 117 membrane,the IrO_(x)-integrated electrode with an ultralow loading of 0.075 mg cm^(-2)delivers a high cell efficiency of about 90%,achieving more than 96%catalyst savings and 42-fold higher catalyst utilization compared to commercial catalyst-coated membrane(2 mg cm^(-2)).Additionally,the IrO_(x)electrode demonstrates superior performance,higher catalyst utilization and significantly simplified fabrication with easy scalability compared with the most previously reported anodes.Notably,the remarkable performance could be mainly due to the amorphous phase property,sufficient Ir^(3+)content,and rich surface hydroxide groups in catalysts.Overall,due to the high activity,high cell efficiency,an economical,greatly simplified and easily scalable fabrication process,and ultrahigh material utilization,the IrO_(x)electrode shows great potential to be applied in industry and accelerates the commercialization of PEMECs and renewable energy evolution.展开更多
Data-driven surrogate models that assist with efficient evolutionary algorithms to find the optimal development scheme have been widely used to solve reservoir production optimization problems.However,existing researc...Data-driven surrogate models that assist with efficient evolutionary algorithms to find the optimal development scheme have been widely used to solve reservoir production optimization problems.However,existing research suggests that the effectiveness of a surrogate model can vary depending on the complexity of the design problem.A surrogate model that has demonstrated success in one scenario may not perform as well in others.In the absence of prior knowledge,finding a promising surrogate model that performs well for an unknown reservoir is challenging.Moreover,the optimization process often relies on a single evolutionary algorithm,which can yield varying results across different cases.To address these limitations,this paper introduces a novel approach called the multi-surrogate framework with an adaptive selection mechanism(MSFASM)to tackle production optimization problems.MSFASM consists of two stages.In the first stage,a reduced-dimensional broad learning system(BLS)is used to adaptively select the evolutionary algorithm with the best performance during the current optimization period.In the second stage,the multi-objective algorithm,non-dominated sorting genetic algorithm II(NSGA-II),is used as an optimizer to find a set of Pareto solutions with good performance on multiple surrogate models.A novel optimal point criterion is utilized in this stage to select the Pareto solutions,thereby obtaining the desired development schemes without increasing the computational load of the numerical simulator.The two stages are combined using sequential transfer learning.From the two most important perspectives of an evolutionary algorithm and a surrogate model,the proposed method improves adaptability to optimization problems of various reservoir types.To verify the effectiveness of the proposed method,four 100-dimensional benchmark functions and two reservoir models are tested,and the results are compared with those obtained by six other surrogate-model-based methods.The results demonstrate that our approach can obtain the maximum net present value(NPV)of the target production optimization problems.展开更多
This article outlines the development of separated zone oil production in foreign countries,and details its development in China.According to the development process,production needs,technical characteristics and adap...This article outlines the development of separated zone oil production in foreign countries,and details its development in China.According to the development process,production needs,technical characteristics and adaptability of oilfields in China,the development of separate zone oil production technology is divided into four stages:flowing well zonal oil production,mechanical recovery and water blocking,hydraulically adjustable zonal oil production,and intelligent zonal production.The principles,construction processes,adaptability,advantages and disadvantages of the technology are introduced in detail.Based on the actual production situation of the oilfields in China at present,three development directions of the technology are proposed.First,the real-time monitoring and adjustment level of separated zone oil production needs to be improved by developing downhole sensor technology and two-way communication technology between ground and downhole and enhancing full life cycle service capability and adaptability to horizontal wells.Second,an integrated platform of zonal oil production and management should be built using a digital artificial lifting system.Third,integration of injection and production should be implemented through large-scale application of zonal oil production and zonal water injection to improve matching and adjustment level between the injection and production parameters,thus making the development adjustment from"lag control"to"real-time optimization"and improving the development effect.展开更多
An in-process technology approach is proposed to identify the source of acid mine drainage(AMD)generation and prevent its formation in a porphyry copper waste rock(WR).Adopting actions before stockpiling the WR enable...An in-process technology approach is proposed to identify the source of acid mine drainage(AMD)generation and prevent its formation in a porphyry copper waste rock(WR).Adopting actions before stockpiling the WR enables the establishment of potential contaminants and predicts the more convenient method for AMD prevention.A WR sample was separated into size fractions,and the WR’s net acidgenerating potential was quantified using chemical and mineralogical characterization.The diameter of physical locking of sulfides(DPLS)was determined,and the fractions below the DPLS were desulfurized using flotation.Finally,the WR fractions and tailing from the flotation test were submitted to acid-base accounting and weathering tests to evaluate their acid-generating potential.Results show that the WR’s main sulfide mineral is pyrite,and the DPLS was defined as 850μm.A sulfide recovery of 91%was achieved using a combination of HydroFloat^(®)and Denver cells for a size fraction lower than DPLS.No grinding was conducted.The results show that size fractions greater than DPLS and the desulfurized WR are unlikely to produce AMD.The outcomes show that in-processing technology can be a more proactive approach and an effective tool for avoiding AMD in a porphyry copper WR.展开更多
In order to overcome the defects that the analysis of multi-well typical curves of shale gas reservoirs is rarely applied to engineering,this study proposes a robust production data analysis method based on deconvolut...In order to overcome the defects that the analysis of multi-well typical curves of shale gas reservoirs is rarely applied to engineering,this study proposes a robust production data analysis method based on deconvolution,which is used for multi-well inter-well interference research.In this study,a multi-well conceptual trilinear seepage model for multi-stage fractured horizontal wells was established,and its Laplace solutions under two different outer boundary conditions were obtained.Then,an improved pressure deconvolution algorithm was used to normalize the scattered production data.Furthermore,the typical curve fitting was carried out using the production data and the seepage model solution.Finally,some reservoir parameters and fracturing parameters were interpreted,and the intensity of inter-well interference was compared.The effectiveness of the method was verified by analyzing the production dynamic data of six shale gas wells in Duvernay area.The results showed that the fitting effect of typical curves was greatly improved due to the mutual restriction between deconvolution calculation parameter debugging and seepage model parameter debugging.Besides,by using the morphological characteristics of the log-log typical curves and the time corresponding to the intersection point of the log-log typical curves of two models under different outer boundary conditions,the strength of the interference between wells on the same well platform was well judged.This work can provide a reference for the optimization of well spacing and hydraulic fracturing measures for shale gas wells.展开更多
Direct regeneration method has been widely concerned by researchers in the field of battery recycling because of its advantages of in situ regeneration,short process and less pollutant emission.In this review,we first...Direct regeneration method has been widely concerned by researchers in the field of battery recycling because of its advantages of in situ regeneration,short process and less pollutant emission.In this review,we firstly analyze the primary causes for the failure of three representative battery cathodes(lithium iron phosphate,layered lithium transition metal oxide and lithium cobalt oxide),targeting at illustrating their underlying regeneration mecha-nism and applicability.Efficient stripping of material from the collector to obtain pure cathode material has become a first challenge in recycling,for which we report several pretreatment methods currently available for subsequent regeneration processes.We review and discuss emphatically the research progress of five direct regeneration methods,including solid-state sintering,hydrothermal,eutectic molten salt,electrochemical and chemical lithiation methods.Finally,the application of direct regeneration technology in production practice is introduced,the problems exposed at the early stage of the industrialization of direct regeneration technol-ogy are revealed,and the prospect of future large-scale commercial production is proposed.It is hoped that this review will give readers a comprehensive and basic understanding of direct regeneration methods for used lithium-ion batteries and promote the industrial application of direct regeneration technology.展开更多
To assess whether a development strategy will be profitable enough,production forecasting is a crucial and difficult step in the process.The development history of other reservoirs in the same class tends to be studie...To assess whether a development strategy will be profitable enough,production forecasting is a crucial and difficult step in the process.The development history of other reservoirs in the same class tends to be studied to make predictions accurate.However,the permeability field,well patterns,and development regime must all be similar for two reservoirs to be considered in the same class.This results in very few available experiences from other reservoirs even though there is a lot of historical information on numerous reservoirs because it is difficult to find such similar reservoirs.This paper proposes a learn-to-learn method,which can better utilize a vast amount of historical data from various reservoirs.Intuitively,the proposed method first learns how to learn samples before directly learning rules in samples.Technically,by utilizing gradients from networks with independent parameters and copied structure in each class of reservoirs,the proposed network obtains the optimal shared initial parameters which are regarded as transferable information across different classes.Based on that,the network is able to predict future production indices for the target reservoir by only training with very limited samples collected from reservoirs in the same class.Two cases further demonstrate its superiority in accuracy to other widely-used network methods.展开更多
Hydrogen gas is widely regarded as an ideal green energy carrier and a potential alternative to fossil fuels for coping with the aggravating energy crisis and environmental pollution.Currently,the vast majority of the...Hydrogen gas is widely regarded as an ideal green energy carrier and a potential alternative to fossil fuels for coping with the aggravating energy crisis and environmental pollution.Currently,the vast majority of the world's hydrogen is produced by reforming fossil fuels;however,this hydrogen-making technology is not sustainable or environmentally friendly because ofits high energy consumption and large carbon emissions.Renewables-driven water splitting(2H_(2)0-2H_(2)+0_(2))becomes an extensively studied scheme for sustain-able hydrogen production.Conventional water electrolysis requires an input voltage higher than 1.23 V and forms a gas mixture of H_(2)/O_(2),which results in high electricity consumption,potential safety hazards,and harmful reactive oxygen species.By virtue of the auxiliary redox mediators(RMs)as the robust H^(+)/e^(-)reservoir,decoupled electrolysis splits water at a much lower potential and evolves O_(2)(H_(2)O+RMS_(ox)-O_(2)+H-RMS_(red))and H_(2)(H-RMS_(red)-H_(2)+RMS_(ox))at separate times,rates,and spaces,thus pro-ducing the puretarget hydrogen gas safely.Decoupled electrolysis has accelerated the development ofwater electrolysis technology for H_(2) production.However,itis still lack of a comprehensive and in-depth review in this field based on different types of RMs.This review highlights the basic principles and critical progress of this emerging water electrolysis mode over the past decade.Several representative examples are then dis-played in detail according to the differences in the RMs.The rational choice and design of RMs have also been emphasized.Subsequently,novel applications of decoupled water splitting are briefly discussed,including the manufacture of valuable chemicals,Cl_(2) production,pollutant degradation,and other half-reactions in artificial photosynthesis.Finally,thekey characteristics and disadvantages of each type of mediator are sum-marized in depth.In addition,we present an outlook for future directions in decoupled water splitting.Thus,the flexibility in the design of mediators provides huge space for improving this electrochemical technology.@2024 Science Press and Dalian Institute of Chemical Physics,Chinese Academy of Sciences.Published by ELSEVIER B.V.and Science Press.All rights reserved.展开更多
With the projected global surge in hydrogen demand, driven by increasing applications and the imperative for low-emission hydrogen, the integration of machine learning(ML) across the hydrogen energy value chain is a c...With the projected global surge in hydrogen demand, driven by increasing applications and the imperative for low-emission hydrogen, the integration of machine learning(ML) across the hydrogen energy value chain is a compelling avenue. This review uniquely focuses on harnessing the synergy between ML and computational modeling(CM) or optimization tools, as well as integrating multiple ML techniques with CM, for the synthesis of diverse hydrogen evolution reaction(HER) catalysts and various hydrogen production processes(HPPs). Furthermore, this review addresses a notable gap in the literature by offering insights, analyzing challenges, and identifying research prospects and opportunities for sustainable hydrogen production. While the literature reflects a promising landscape for ML applications in hydrogen energy domains, transitioning AI-based algorithms from controlled environments to real-world applications poses significant challenges. Hence, this comprehensive review delves into the technical,practical, and ethical considerations associated with the application of ML in HER catalyst development and HPP optimization. Overall, this review provides guidance for unlocking the transformative potential of ML in enhancing prediction efficiency and sustainability in the hydrogen production sector.展开更多
Energy supply dominated by fossil energy has been and remains the main cause of carbon dioxide emissions,the major greenhouse gas leading to the current grave climate change challenges.Many technical pathways have bee...Energy supply dominated by fossil energy has been and remains the main cause of carbon dioxide emissions,the major greenhouse gas leading to the current grave climate change challenges.Many technical pathways have been proposed to address the challenges.Carbon capture and utilization(CCU) represents one of the approaches and thermochemical CO_(2) splitting driven by thermal energy is a subset of the CCU,which converts the captured CO_(2) into CO and makes it possible to achieve closed-loop carbon recirculation.Redox-active catalysts are among the most critical components of the thermochemical splitting cycles and perovskites are regarded as the most promising catalysts.Here we review the latest advancements in thermochemical cycles based on perovskites,covering thermodynamic principles,material modifications,reaction kinetics,oxygen pressure control,circular strategies,and demonstrations to provide a comprehensive overview of the topical area.Thermochemical cycles based on such materials require the consideration of trade-off between cost and efficiency,which is related to actual material used,operation mode,oxygen removal,and heat recovery.Lots of efforts have been made towards improving reaction rates,conversion efficiency and cycling stability,materials related research has been lacking-a key aspect affecting the performance across all above aspects.Double perovskites and composite perovskites arise recently as a potentially promising addition to material candidates.For such materials,more effective oxygen removal would be needed to enhance the overall efficiency,for which thermochemical or electrochemical oxygen pumps could contribute to efficient oxygen removal as well as serve as means for inert gas regeneration.The integration of thermochemical CO_(2) splitting process with downstream fuel production and other processes could reduce costs and increase efficiency of the technology.This represents one of the directions for the future research.展开更多
The relativistic mean-field approach was implemented in the Lanzhou quantum molecular dynamics transport model(LQMD.RMF). Using the LQMD.RMF, the properties of collective flow and pion production were investigated sys...The relativistic mean-field approach was implemented in the Lanzhou quantum molecular dynamics transport model(LQMD.RMF). Using the LQMD.RMF, the properties of collective flow and pion production were investigated systematically for nuclear reactions with various isospin asymmetries. The directed and elliptic flows of the LQMD.RMF are able to describe the experimental data of STAR Collaboration. The directed flow difference between free neutrons and protons was associated with the stiffness of the symmetry energy, that is, a softer symmetry energy led to a larger flow difference. For various collision energies, the ratio between the π^(-) and π^(+) yields increased with a decrease in the slope parameter of the symmetry energy. When the collision energy was 270 MeV/nucleon, the single ratio of the pion transverse momentum spectra also increased with decreasing slope parameter of the symmetry energy in both nearly symmetric and neutron-rich systems.However, it is difficult to constrain the stiffness of the symmetry energy with the double ratio because of the lack of threshold energy correction on the pion production.展开更多
The subsea production system is a vital equipment for offshore oil and gas production.The control system is one of the most important parts of it.Collecting and processing the signals of subsea sensors is the only way...The subsea production system is a vital equipment for offshore oil and gas production.The control system is one of the most important parts of it.Collecting and processing the signals of subsea sensors is the only way to judge whether the subsea production control system is normal.However,subsea sensors degrade rapidly due to harsh working environments and long service time.This leads to frequent false alarm incidents.A combinatorial reasoning-based abnormal sensor recognition method for subsea production control system is proposed.A combinatorial algorithm is proposed to group sensors.The long short-term memory network(LSTM)is used to establish a single inference model.A counting-based judging method is proposed to identify abnormal sensors.Field data from an offshore platform in the South China Sea is used to demonstrate the effect of the proposed method.The results show that the proposed method can identify the abnormal sensors effectively.展开更多
Oxygenated carbon materials exhibit outstanding electrocatalytic performance in the production of hydrogen peroxide(H2O2)through a two-electron oxygen reduction reaction.The nature of the active functional group and u...Oxygenated carbon materials exhibit outstanding electrocatalytic performance in the production of hydrogen peroxide(H2O2)through a two-electron oxygen reduction reaction.The nature of the active functional group and underlying reaction mechanism,however,remain unclear.Here,a comprehensive workflow was established to identify the active sites from the numerous possible structures.The common hydroxyl group at the notched edge demonstrates a key role in the two-electron process.The local chemical environment weakens the binding of OOH intermediate to substrate while enhancing interaction with solution,thereby promoting the H_(2)O_(2)production.With increasing pH,the intramolecular hydrogen bond between OOH intermediate and hydroxyl decreases,facilitating OOH desorption.Furthermore,the rise in selectivity with increasing potential stems from the suppression of the four-electron process.The active site was further validated through experiments.Guided by theoretical understanding,optimal performance was achieved with high selectivity(>95%)and current density(2.06 mA/cm^(2))in experiment.展开更多
The global shift towards sustainable food systems has sparked innovations in food sources and production systems,including cell-based meat,plant-based food products,precision fermentation,and 3D food printing.These ad...The global shift towards sustainable food systems has sparked innovations in food sources and production systems,including cell-based meat,plant-based food products,precision fermentation,and 3D food printing.These advancements pose regulatory challenges and opportunities,with China emerging as a critical player in adopting and regulating new food technologies.This review explores the international landscape of new food sources and production systems(NFPS),focusing on China’s role and regulatory approaches compared to global practices.Through this comparative analysis,we aim to contribute to the ongoing dialogue on food safety regulation,offering insights and recommendations for policymakers,industry stakeholders,and researchers engaged in the global food system’s evolution.This comprehensive overview underscores the dynamic nature of regulatory frameworks governing NFPS,highlighting the international efforts to ensure food safety,consumer protection,and the sustainable evolution of the food industry.展开更多
基金supported by the National Research Foundation of Korea(NRF)grants(2022R1A2C4001228,2022M3H4A4097524,2022M3I3A1082499,and 2021M3I3A1084818)the Technology Innovation Program(20026415)of the Ministry of Trade,Industry&Energy(MOTIE,Korea)the supports from Nanopac for fabrication of scaled-up reactor.
文摘Wastewater electrolysis cells(WECs)for decentralized wastewater treatment/reuse coupled with H_(2) production can reduce the carbon footprint associated with transportation of water,waste,and energy carrier.This study reports Ir-doped NiFe_(2)O_(4)(NFI,~5 at%Ir)spinel layer with TiO_(2) overlayer(NFI/TiO_(2)),as a scalable heterojunction anode for direct electrolysis of wastewater with circumneutral pH in a single-compartment cell.In dilute(0.1 M)NaCl solutions,the NFI/TiO_(2) marks superior activity and selectivity for chlorine evolution reaction,outperforming the benchmark IrO_(2).Robust operation in near-neutral pH was confirmed.Electroanalyses including operando X-ray absorption spectroscopy unveiled crucial roles of TiO_(2) which serves both as the primary site for Cl−chemisorption and a protective layer for NFI as an ohmic contact.Galvanostatic electrolysis of NH4+-laden synthetic wastewater demonstrated that NFI/TiO_(2)not only achieves quasi-stoichiometric NH_(4)^(+)-to-N_(2)conversion,but also enhances H_(2)generation efficiency with minimal competing reactions such as reduction of dissolved oxygen and reactive chlorine.The scaled-up WEC with NFI/TiO_(2)was demonstrated for electrolysis of toilet wastewater.
基金supported by the National Natural Science Foundation of China(32071749)。
文摘Root tips are the main components of absorptive fine roots,but their seasonal dynamics and relationship to environmental factors remain unclear due to the difficulties in methodology.In this study,we explored the temporal patterns of root-tip production and mortality in monoculture plantations of five temperate tree species at a common site in northeastern China,and identified the general environmental controls on such processes.We made monthly in-situ assessments of root tip length(RTL)production and mortality in two hardwood and three coniferous species with a minirhizotron(MR)method during the growing seasons of 2008 and 2009.Air temperature,rainfall,soil temperature and water content at 10 cm depth were determined concurrently.RTL production in all species exhibited consistent peaks in summer(June–August)in two growing seasons.RTL mortality showed substantial interannual and interspecific variability,with peaks in autumn and winter in 2008,but various patterns in 2009.RTL production positively correlated with monthly soil and air temperature across all species,and with monthly rainfall in three coniferous species.However,there was no significant correlation between RTL production and soil water content.By contrast,RTL mortality was weakly related to environmental factors,showing positive correlations with soil temperature in Korean spruce,and with rainfall in Korean pine and Korean spruce.Our findings suggest that the seasonal patterns of RTL production are convergent across the five temperate tree species due to the overlapped distribution of heat and rainfall,which can conduce roots to maximizing the acquisition of nutrient resources in the soil.
文摘Hydrogen generation and related energy applications heavily rely on the hydrogen evolution reaction(HER),which faces challenges of slow kinetics and high overpotential.Efficient electrocatalysts,particularly single-atom catalysts (SACs) on two-dimensional (2D) materials,are essential.This study presents a few-shot machine learning (ML) assisted high-throughput screening of 2D septuple-atomic-layer Ga_(2)CoS_(4-x)supported SACs to predict HER catalytic activity.Initially,density functional theory (DFT)calculations showed that 2D Ga_(2)CoS4is inactive for HER.However,defective Ga_(2)CoS_(4-x)(x=0–0.25)monolayers exhibit excellent HER activity due to surface sulfur vacancies (SVs),with predicted overpotentials (0–60 mV) comparable to or lower than commercial Pt/C,which typically exhibits an overpotential of around 50 m V in the acidic electrolyte,when the concentration of surface SV is lower than 8.3%.SVs generate spin-polarized states near the Fermi level,making them effective HER sites.We demonstrate ML-accelerated HER overpotential predictions for all transition metal SACs on 2D Ga_(2)CoS_(4-x).Using DFT data from 18 SACs,an ML model with high prediction accuracy and reduced computation time was developed.An intrinsic descriptor linking SAC atomic properties to HER overpotential was identified.This study thus provides a framework for screening SACs on 2D materials,enhancing catalyst design.
基金National Natural Science Foundation of China(No.52476192,No.52106237)Natural Science Foundation of Heilongjiang Province(No.YQ2022E027)。
文摘The transition of hydrogen sourcing from carbon-intensive to water-based methodologies is underway,with renewable energy-powered proton exchange membrane water electrolysis(PEMWE)emerging as the preeminent pathway for hydrogen production.Despite remarkable advancements in this field,confronting the sluggish electrochemical kinetics and inherent high-energy consumption arising from deteriorated mass transport within PEMWE systems remains a formidable obstacle.This impediment stems primarily from the hindered protons mass transfer and the untimely hydrogen bubbles detachment.To address these challenges,we harness the inherent variability of electrical energy and introduce an innovative pulsed dynamic water electrolysis system.Compared to constant voltage electrolysis(hydrogen production rate:51.6 m L h^(-1),energy consumption:5.37 kWh Nm-^(3)H_(2)),this strategy(hydrogen production rate:66 m L h^(-1),energy consumption:3.83 kWh Nm-^(3)H_(2))increases the hydrogen production rate by approximately 27%and reduces the energy consumption by about 28%.Furthermore,we demonstrate the practicality of this system by integrating it with an off-grid photovoltaic(PV)system designed for outdoor operation,successfully driving a hydrogen production current of up to 500 mA under an average voltage of approximately 2 V.The combined results of in-situ characterization and finite element analysis reveal the performance enhancement mechanism:pulsed dynamic electrolysis(PDE)dramatically accelerates the enrichment of protons at the electrode/solution interface and facilitates the release of bubbles on the electrode surface.As such,PDE-enhanced PEMWE represents a synergistic advancement,concurrently enhancing both the hydrogen generation reaction and associated transport processes.This promising technology not only redefines the landscape of electrolysis-based hydrogen production but also holds immense potential for broadening its application across a diverse spectrum of electrocatalytic endeavors.
基金supported by Sichuan Natural Science Foundation (Grant No. 2023NSFSC0423)CNPC Innovation Found (Grant No. 2022DQ02-0207)+2 种基金Science and Technology Research Program of Chongqing Municipal Education Commission (KJQN202201510)supported by a grant from the Human Resources Development program (No. 20216110100070) of the Korea Institute of Energy Technology Evaluation and Planning (KETEP)funded by the Ministry of Trade, Industry, and Energy of the Korean Government。
文摘Shale gas, as an environmentally friendly fossil energy resource, has gained significant commercial development and shows immense potential. However, accurately predicting shale gas production faces substantial challenges due to the complex law of decline, nonlinear and non-stationary features in production data, which greatly repair the robustness of current models in predicting shale gas production time series. To address these challenges and improve accuracy in production forecasting, this paper introduces a novel and innovative approach: a hybrid proxy model that combines the bidirectional long short-term memory(BiLSTM) neural network and random forest(RF) through deep learning. The BiLSTM neural network is adept at capturing long-term dependencies, making it suitable for understanding the intricate relationships between input and output variables in shale gas production.On the other hand, RF serves a dual purpose: reducing model variance and addressing the concept drift problem that arises in non-stationary time series predictions made by BiLSTM. By integrating these two models, the hybrid approach effectively captures the inherent dependencies present in long and nonstationary production time series, thereby reducing model uncertainty. Furthermore, the combination of BiLSTM and RF is optimized using the recently-proposed marine predators algorithm(MPA) to fine-tune hyperparameters and enhance the overall performance of the proxy model. The results demonstrate that the proposed BiLSTM-RF-MPA model achieves higher prediction accuracy and demonstrates stronger generalization capabilities by effectively handling the complex nonlinear and non-stationary characteristics of shale gas production time series. Compared to other models such as LSTM, BiLSTM, and RF, the proposed model exhibits superior fitting and prediction performance, with an average improvement in performance indicators exceeding 20%. This innovative framework provides valuable insights for forecasting the complex production performance of unconventional oil and gas reservoirs, which sheds light on the development of data-driven proxy models in the field of subsurface energy utilization.
基金supported by the Korea Institute of Energy Technology Evaluation and Planning(KETEP)grant from the Ministry of Trade,Industry&Energy,Republic of Korea(No.20213030040590)the National R&D Program through the National Research Foundation of Korea(NRF)funded by the Ministry of Science and ICT(NRF-2021K1A4A8A01079455)。
文摘Continuous efforts are underway to reduce carbon emissions worldwide in response to global climate change.Water electrolysis technology,in conjunction with renewable energy,is considered the most feasible hydrogen production technology based on the viable possibility of large-scale hydrogen production and the zero-carbon-emission nature of the process.However,for hydrogen produced via water electrolysis systems to be utilized in various fields in practice,the unit cost of hydrogen production must be reduced to$1/kg H_(2).To achieve this unit cost,technical targets for water electrolysis have been suggested regarding components in the system.In this paper,the types of water electrolysis systems and the limitations of water electrolysis system components are explained.We suggest guideline with recent trend for achieving this technical target and insights for the potential utilization of water electrolysis technology.
基金the support from the U.S. Department of Energy's Office of Energy Efficiency and Renewable Energy (EERE) under the Hydrogen and Fuel Cell Technologies Office Awards DE-EE0008426 and DE-EE0008423National Energy Technology Laboratory under Award DEFE0011585.
文摘Herein,ionomer-free amorphous iridium oxide(IrO_(x))thin electrodes are first developed as highly active anodes for proton exchange membrane electrolyzer cells(PEMECs)via low-cost,environmentally friendly,and easily scalable electrodeposition at room temperature.Combined with a Nafion 117 membrane,the IrO_(x)-integrated electrode with an ultralow loading of 0.075 mg cm^(-2)delivers a high cell efficiency of about 90%,achieving more than 96%catalyst savings and 42-fold higher catalyst utilization compared to commercial catalyst-coated membrane(2 mg cm^(-2)).Additionally,the IrO_(x)electrode demonstrates superior performance,higher catalyst utilization and significantly simplified fabrication with easy scalability compared with the most previously reported anodes.Notably,the remarkable performance could be mainly due to the amorphous phase property,sufficient Ir^(3+)content,and rich surface hydroxide groups in catalysts.Overall,due to the high activity,high cell efficiency,an economical,greatly simplified and easily scalable fabrication process,and ultrahigh material utilization,the IrO_(x)electrode shows great potential to be applied in industry and accelerates the commercialization of PEMECs and renewable energy evolution.
基金This work is supported by the National Natural Science Foundation of China under Grant 52274057,52074340 and 51874335the Major Scientific and Technological Projects of CNPC under Grant ZD2019-183-008+2 种基金the Major Scientific and Technological Projects of CNOOC under Grant CCL2022RCPS0397RSNthe Science and Technology Support Plan for Youth Innovation of University in Shandong Province under Grant 2019KJH002111 Project under Grant B08028.
文摘Data-driven surrogate models that assist with efficient evolutionary algorithms to find the optimal development scheme have been widely used to solve reservoir production optimization problems.However,existing research suggests that the effectiveness of a surrogate model can vary depending on the complexity of the design problem.A surrogate model that has demonstrated success in one scenario may not perform as well in others.In the absence of prior knowledge,finding a promising surrogate model that performs well for an unknown reservoir is challenging.Moreover,the optimization process often relies on a single evolutionary algorithm,which can yield varying results across different cases.To address these limitations,this paper introduces a novel approach called the multi-surrogate framework with an adaptive selection mechanism(MSFASM)to tackle production optimization problems.MSFASM consists of two stages.In the first stage,a reduced-dimensional broad learning system(BLS)is used to adaptively select the evolutionary algorithm with the best performance during the current optimization period.In the second stage,the multi-objective algorithm,non-dominated sorting genetic algorithm II(NSGA-II),is used as an optimizer to find a set of Pareto solutions with good performance on multiple surrogate models.A novel optimal point criterion is utilized in this stage to select the Pareto solutions,thereby obtaining the desired development schemes without increasing the computational load of the numerical simulator.The two stages are combined using sequential transfer learning.From the two most important perspectives of an evolutionary algorithm and a surrogate model,the proposed method improves adaptability to optimization problems of various reservoir types.To verify the effectiveness of the proposed method,four 100-dimensional benchmark functions and two reservoir models are tested,and the results are compared with those obtained by six other surrogate-model-based methods.The results demonstrate that our approach can obtain the maximum net present value(NPV)of the target production optimization problems.
基金Supported by the National Key Research and Development Program of China(2018YFE0196000)National Science and Technology Major Project of China(2016ZX05010-006)CNPC Scientific Research and Technical Development Project(2019B-4113)
文摘This article outlines the development of separated zone oil production in foreign countries,and details its development in China.According to the development process,production needs,technical characteristics and adaptability of oilfields in China,the development of separate zone oil production technology is divided into four stages:flowing well zonal oil production,mechanical recovery and water blocking,hydraulically adjustable zonal oil production,and intelligent zonal production.The principles,construction processes,adaptability,advantages and disadvantages of the technology are introduced in detail.Based on the actual production situation of the oilfields in China at present,three development directions of the technology are proposed.First,the real-time monitoring and adjustment level of separated zone oil production needs to be improved by developing downhole sensor technology and two-way communication technology between ground and downhole and enhancing full life cycle service capability and adaptability to horizontal wells.Second,an integrated platform of zonal oil production and management should be built using a digital artificial lifting system.Third,integration of injection and production should be implemented through large-scale application of zonal oil production and zonal water injection to improve matching and adjustment level between the injection and production parameters,thus making the development adjustment from"lag control"to"real-time optimization"and improving the development effect.
基金supported by Agencia Nacional de Investigación y Desarrollo de Chile(ANID)Anillo-Grant ANID/ACT210027,Fondecyt 1211498,and ANID/AFB230001+1 种基金the ANID scholarship Grant 21210801partially performed by Luis Cisternas during the visit to the Universitédu Québec,supported by MINEDUC-UA project,code ANT1999.
文摘An in-process technology approach is proposed to identify the source of acid mine drainage(AMD)generation and prevent its formation in a porphyry copper waste rock(WR).Adopting actions before stockpiling the WR enables the establishment of potential contaminants and predicts the more convenient method for AMD prevention.A WR sample was separated into size fractions,and the WR’s net acidgenerating potential was quantified using chemical and mineralogical characterization.The diameter of physical locking of sulfides(DPLS)was determined,and the fractions below the DPLS were desulfurized using flotation.Finally,the WR fractions and tailing from the flotation test were submitted to acid-base accounting and weathering tests to evaluate their acid-generating potential.Results show that the WR’s main sulfide mineral is pyrite,and the DPLS was defined as 850μm.A sulfide recovery of 91%was achieved using a combination of HydroFloat^(®)and Denver cells for a size fraction lower than DPLS.No grinding was conducted.The results show that size fractions greater than DPLS and the desulfurized WR are unlikely to produce AMD.The outcomes show that in-processing technology can be a more proactive approach and an effective tool for avoiding AMD in a porphyry copper WR.
基金financial support from PetroChina Innovation Foundation。
文摘In order to overcome the defects that the analysis of multi-well typical curves of shale gas reservoirs is rarely applied to engineering,this study proposes a robust production data analysis method based on deconvolution,which is used for multi-well inter-well interference research.In this study,a multi-well conceptual trilinear seepage model for multi-stage fractured horizontal wells was established,and its Laplace solutions under two different outer boundary conditions were obtained.Then,an improved pressure deconvolution algorithm was used to normalize the scattered production data.Furthermore,the typical curve fitting was carried out using the production data and the seepage model solution.Finally,some reservoir parameters and fracturing parameters were interpreted,and the intensity of inter-well interference was compared.The effectiveness of the method was verified by analyzing the production dynamic data of six shale gas wells in Duvernay area.The results showed that the fitting effect of typical curves was greatly improved due to the mutual restriction between deconvolution calculation parameter debugging and seepage model parameter debugging.Besides,by using the morphological characteristics of the log-log typical curves and the time corresponding to the intersection point of the log-log typical curves of two models under different outer boundary conditions,the strength of the interference between wells on the same well platform was well judged.This work can provide a reference for the optimization of well spacing and hydraulic fracturing measures for shale gas wells.
基金supported by the National Key Research and Development Program of China(No.2023YFC3904800)the Key Project of Jiangxi Provincial Research and Development Program(No.20223BBG74006)+5 种基金the Key Project of Ganzhou City Research and Development Program(No.2023PGX17350)“Thousand Talents Program”of Jiangxi Province(No.001043232090)Science&Technology Talents Lifting Project of Hunan Province(No.2022TJ-N16)Natural Science Foundation of Hunan Province(Nos.2024JJ4022 and 2023JJ30277)China Postdoctoral Fellowship Program(No.GZC20233205)the Open-End Fund for National-Local Joint Engineering Research Center of Heavy Metals Pollutants Control and Resource Utilization(ES202480184).
文摘Direct regeneration method has been widely concerned by researchers in the field of battery recycling because of its advantages of in situ regeneration,short process and less pollutant emission.In this review,we firstly analyze the primary causes for the failure of three representative battery cathodes(lithium iron phosphate,layered lithium transition metal oxide and lithium cobalt oxide),targeting at illustrating their underlying regeneration mecha-nism and applicability.Efficient stripping of material from the collector to obtain pure cathode material has become a first challenge in recycling,for which we report several pretreatment methods currently available for subsequent regeneration processes.We review and discuss emphatically the research progress of five direct regeneration methods,including solid-state sintering,hydrothermal,eutectic molten salt,electrochemical and chemical lithiation methods.Finally,the application of direct regeneration technology in production practice is introduced,the problems exposed at the early stage of the industrialization of direct regeneration technol-ogy are revealed,and the prospect of future large-scale commercial production is proposed.It is hoped that this review will give readers a comprehensive and basic understanding of direct regeneration methods for used lithium-ion batteries and promote the industrial application of direct regeneration technology.
基金This work is supported by the National Natural Science Foundation of China under Grant 52274057,52074340 and 51874335the Major Scientific and Technological Projects of CNPC under Grant ZD2019-183-008+2 种基金the Major Scientific and Technological Projects of CNOOC under Grant CCL2022RCPS0397RSNthe Science and Technology Support Plan for Youth Innovation of University in Shandong Province under Grant 2019KJH002111 Project under Grant B08028.
文摘To assess whether a development strategy will be profitable enough,production forecasting is a crucial and difficult step in the process.The development history of other reservoirs in the same class tends to be studied to make predictions accurate.However,the permeability field,well patterns,and development regime must all be similar for two reservoirs to be considered in the same class.This results in very few available experiences from other reservoirs even though there is a lot of historical information on numerous reservoirs because it is difficult to find such similar reservoirs.This paper proposes a learn-to-learn method,which can better utilize a vast amount of historical data from various reservoirs.Intuitively,the proposed method first learns how to learn samples before directly learning rules in samples.Technically,by utilizing gradients from networks with independent parameters and copied structure in each class of reservoirs,the proposed network obtains the optimal shared initial parameters which are regarded as transferable information across different classes.Based on that,the network is able to predict future production indices for the target reservoir by only training with very limited samples collected from reservoirs in the same class.Two cases further demonstrate its superiority in accuracy to other widely-used network methods.
基金the financial support from the National Natural Science Foundation of China(52002146).
文摘Hydrogen gas is widely regarded as an ideal green energy carrier and a potential alternative to fossil fuels for coping with the aggravating energy crisis and environmental pollution.Currently,the vast majority of the world's hydrogen is produced by reforming fossil fuels;however,this hydrogen-making technology is not sustainable or environmentally friendly because ofits high energy consumption and large carbon emissions.Renewables-driven water splitting(2H_(2)0-2H_(2)+0_(2))becomes an extensively studied scheme for sustain-able hydrogen production.Conventional water electrolysis requires an input voltage higher than 1.23 V and forms a gas mixture of H_(2)/O_(2),which results in high electricity consumption,potential safety hazards,and harmful reactive oxygen species.By virtue of the auxiliary redox mediators(RMs)as the robust H^(+)/e^(-)reservoir,decoupled electrolysis splits water at a much lower potential and evolves O_(2)(H_(2)O+RMS_(ox)-O_(2)+H-RMS_(red))and H_(2)(H-RMS_(red)-H_(2)+RMS_(ox))at separate times,rates,and spaces,thus pro-ducing the puretarget hydrogen gas safely.Decoupled electrolysis has accelerated the development ofwater electrolysis technology for H_(2) production.However,itis still lack of a comprehensive and in-depth review in this field based on different types of RMs.This review highlights the basic principles and critical progress of this emerging water electrolysis mode over the past decade.Several representative examples are then dis-played in detail according to the differences in the RMs.The rational choice and design of RMs have also been emphasized.Subsequently,novel applications of decoupled water splitting are briefly discussed,including the manufacture of valuable chemicals,Cl_(2) production,pollutant degradation,and other half-reactions in artificial photosynthesis.Finally,thekey characteristics and disadvantages of each type of mediator are sum-marized in depth.In addition,we present an outlook for future directions in decoupled water splitting.Thus,the flexibility in the design of mediators provides huge space for improving this electrochemical technology.@2024 Science Press and Dalian Institute of Chemical Physics,Chinese Academy of Sciences.Published by ELSEVIER B.V.and Science Press.All rights reserved.
基金express their gratitude to the Higher Institution Centre of Excellence (HICoE) fund under the project code (JPT.S(BPKI)2000/016/018/015JId.4(21)/2022002HICOE)Universiti Tenaga Nasional (UNITEN) for funding the research through the (J510050002–IC–6 BOLDREFRESH2025)Akaun Amanah Industri Bekalan Elektrik (AAIBE) Chair of Renewable Energy grant,and NEC Energy Transition Grant (202203003ETG)。
文摘With the projected global surge in hydrogen demand, driven by increasing applications and the imperative for low-emission hydrogen, the integration of machine learning(ML) across the hydrogen energy value chain is a compelling avenue. This review uniquely focuses on harnessing the synergy between ML and computational modeling(CM) or optimization tools, as well as integrating multiple ML techniques with CM, for the synthesis of diverse hydrogen evolution reaction(HER) catalysts and various hydrogen production processes(HPPs). Furthermore, this review addresses a notable gap in the literature by offering insights, analyzing challenges, and identifying research prospects and opportunities for sustainable hydrogen production. While the literature reflects a promising landscape for ML applications in hydrogen energy domains, transitioning AI-based algorithms from controlled environments to real-world applications poses significant challenges. Hence, this comprehensive review delves into the technical,practical, and ethical considerations associated with the application of ML in HER catalyst development and HPP optimization. Overall, this review provides guidance for unlocking the transformative potential of ML in enhancing prediction efficiency and sustainability in the hydrogen production sector.
文摘Energy supply dominated by fossil energy has been and remains the main cause of carbon dioxide emissions,the major greenhouse gas leading to the current grave climate change challenges.Many technical pathways have been proposed to address the challenges.Carbon capture and utilization(CCU) represents one of the approaches and thermochemical CO_(2) splitting driven by thermal energy is a subset of the CCU,which converts the captured CO_(2) into CO and makes it possible to achieve closed-loop carbon recirculation.Redox-active catalysts are among the most critical components of the thermochemical splitting cycles and perovskites are regarded as the most promising catalysts.Here we review the latest advancements in thermochemical cycles based on perovskites,covering thermodynamic principles,material modifications,reaction kinetics,oxygen pressure control,circular strategies,and demonstrations to provide a comprehensive overview of the topical area.Thermochemical cycles based on such materials require the consideration of trade-off between cost and efficiency,which is related to actual material used,operation mode,oxygen removal,and heat recovery.Lots of efforts have been made towards improving reaction rates,conversion efficiency and cycling stability,materials related research has been lacking-a key aspect affecting the performance across all above aspects.Double perovskites and composite perovskites arise recently as a potentially promising addition to material candidates.For such materials,more effective oxygen removal would be needed to enhance the overall efficiency,for which thermochemical or electrochemical oxygen pumps could contribute to efficient oxygen removal as well as serve as means for inert gas regeneration.The integration of thermochemical CO_(2) splitting process with downstream fuel production and other processes could reduce costs and increase efficiency of the technology.This represents one of the directions for the future research.
基金This study was supported by the National Natural Science Foundation ofChina(Nos.12147106,12175072,and 11722546)the Talent Programof South China University of Technology(No.20210115).
文摘The relativistic mean-field approach was implemented in the Lanzhou quantum molecular dynamics transport model(LQMD.RMF). Using the LQMD.RMF, the properties of collective flow and pion production were investigated systematically for nuclear reactions with various isospin asymmetries. The directed and elliptic flows of the LQMD.RMF are able to describe the experimental data of STAR Collaboration. The directed flow difference between free neutrons and protons was associated with the stiffness of the symmetry energy, that is, a softer symmetry energy led to a larger flow difference. For various collision energies, the ratio between the π^(-) and π^(+) yields increased with a decrease in the slope parameter of the symmetry energy. When the collision energy was 270 MeV/nucleon, the single ratio of the pion transverse momentum spectra also increased with decreasing slope parameter of the symmetry energy in both nearly symmetric and neutron-rich systems.However, it is difficult to constrain the stiffness of the symmetry energy with the double ratio because of the lack of threshold energy correction on the pion production.
基金supported by the National Key Research and Development Program of China (No.2022YFC2806102)the National Natural Science Foundation of China (No.52171287,52325107)+3 种基金High-tech Ship Research Project of Ministry of Industry and Information Technology (No.2023GXB01-05-004-03,No.GXBZH2022-293)the Science Foundation for Distinguished Young Scholars of Shandong Province (No.ZR2022JQ25)the Taishan Scholars Project (No.tsqn201909063)the Fundamental Research Funds for the Central Universities (No.24CX10006A)。
文摘The subsea production system is a vital equipment for offshore oil and gas production.The control system is one of the most important parts of it.Collecting and processing the signals of subsea sensors is the only way to judge whether the subsea production control system is normal.However,subsea sensors degrade rapidly due to harsh working environments and long service time.This leads to frequent false alarm incidents.A combinatorial reasoning-based abnormal sensor recognition method for subsea production control system is proposed.A combinatorial algorithm is proposed to group sensors.The long short-term memory network(LSTM)is used to establish a single inference model.A counting-based judging method is proposed to identify abnormal sensors.Field data from an offshore platform in the South China Sea is used to demonstrate the effect of the proposed method.The results show that the proposed method can identify the abnormal sensors effectively.
基金supported by the National Natural Science Foundation of China(No.52171022,No.22105214)Zhejiang Provincial Natural Science Foundation of China(Grant No.LXR22B030001)+3 种基金Fujian Institute of Innovation and Chinese Academy of Sciences.K.C.Wong Education Foundation(GJTD-2019-13)the National Key Research and Development Program of China(2019YFB2203400)Ningbo Yongjiang Talent Introduction Programme(2021A-036-B)NingBo S&T Innovation 2025 Major Special Programme(No:2020z059)and the“111 Project”(B20030).
文摘Oxygenated carbon materials exhibit outstanding electrocatalytic performance in the production of hydrogen peroxide(H2O2)through a two-electron oxygen reduction reaction.The nature of the active functional group and underlying reaction mechanism,however,remain unclear.Here,a comprehensive workflow was established to identify the active sites from the numerous possible structures.The common hydroxyl group at the notched edge demonstrates a key role in the two-electron process.The local chemical environment weakens the binding of OOH intermediate to substrate while enhancing interaction with solution,thereby promoting the H_(2)O_(2)production.With increasing pH,the intramolecular hydrogen bond between OOH intermediate and hydroxyl decreases,facilitating OOH desorption.Furthermore,the rise in selectivity with increasing potential stems from the suppression of the four-electron process.The active site was further validated through experiments.Guided by theoretical understanding,optimal performance was achieved with high selectivity(>95%)and current density(2.06 mA/cm^(2))in experiment.
基金supported by the National Key Research and Development Program of China(2022YFF1102500)the Special Project of Central Guide to Local Science and Technology Development(Innovation platform construction for food green processing technology and intelligent equipment)(2022BGE247).
文摘The global shift towards sustainable food systems has sparked innovations in food sources and production systems,including cell-based meat,plant-based food products,precision fermentation,and 3D food printing.These advancements pose regulatory challenges and opportunities,with China emerging as a critical player in adopting and regulating new food technologies.This review explores the international landscape of new food sources and production systems(NFPS),focusing on China’s role and regulatory approaches compared to global practices.Through this comparative analysis,we aim to contribute to the ongoing dialogue on food safety regulation,offering insights and recommendations for policymakers,industry stakeholders,and researchers engaged in the global food system’s evolution.This comprehensive overview underscores the dynamic nature of regulatory frameworks governing NFPS,highlighting the international efforts to ensure food safety,consumer protection,and the sustainable evolution of the food industry.
