Vertically oriented carbon structures constructed from low-dimen-sional carbon materials are ideal frameworks for high-performance thermal inter-face materials(TIMs).However,improving the interfacial heat-transfer eff...Vertically oriented carbon structures constructed from low-dimen-sional carbon materials are ideal frameworks for high-performance thermal inter-face materials(TIMs).However,improving the interfacial heat-transfer efficiency of vertically oriented carbon structures is a challenging task.Herein,an orthotropic three-dimensional(3D)hybrid carbon network(VSCG)is fabricated by depositing vertically aligned carbon nanotubes(VACNTs)on the surface of a horizontally oriented graphene film(HOGF).The interfacial interaction between the VACNTs and HOGF is then optimized through an annealing strategy.After regulating the orientation structure of the VACNTs and filling the VSCG with polydimethylsi-loxane(PDMS),VSCG/PDMS composites with excellent 3D thermal conductive properties are obtained.The highest in-plane and through-plane thermal conduc-tivities of the composites are 113.61 and 24.37 W m^(-1)K^(-1),respectively.The high contact area of HOGF and good compressibility of VACNTs imbue the VSCG/PDMS composite with low thermal resistance.In addition,the interfacial heat-transfer efficiency of VSCG/PDMS composite in the TIM performance was improved by 71.3%compared to that of a state-of-the-art thermal pad.This new structural design can potentially realize high-performance TIMs that meet the need for high thermal conductivity and low contact thermal resistance in interfacial heat-transfer processes.展开更多
Nowadays,carbon frameworks derived from natural biomaterials have attracted extensive attention for electromagnetic interference(EMI)shielding due to their renewability and affordability.However,it is critical and cha...Nowadays,carbon frameworks derived from natural biomaterials have attracted extensive attention for electromagnetic interference(EMI)shielding due to their renewability and affordability.However,it is critical and challenging to achieve effective regulation of shielding effectiveness(SE)as well as weaken the strong EM reflection of highly conductive biomass-based carbon materials.Herein,commercial cotton pads with oriented structure were selected as carbonaceous precursor to fabricate aligned carbon networks by pyrolysis,and the EMI SE of the samples with increased temperature of 800-1000℃ can be accurately controlled in the effective range of~21.7-29.1,~27.7-37.1 and~32.7-43.3 d B with high reflection coefficient of>0.8 by changing the cross-angle between the electric-field direction of incident EM waves and the fiber-orientation direction due to the occurrence of opposite internal electric field.Moreover,the further construction of Salisbury absorber-liked double-layer structure could result in an ultralow reflection coefficient of only~0.06 but enhanced SE variation range up to~38.7-49.3 d B during the adjustment of cross-angle,possibly due to the destructive interference of EM waves in the double-layer carbon networks.This work would provide a simple and effective way for constructing high-performance biomass carbon materials with adjustable EMI shielding and ultra-low reflectivity.展开更多
Three-dimensional(3D)carbon networks have been explored as promising capacitive materials thanks to their unique structural features such as large ion-accessible surface area and interconnected porous networks,thus en...Three-dimensional(3D)carbon networks have been explored as promising capacitive materials thanks to their unique structural features such as large ion-accessible surface area and interconnected porous networks,thus enhancing both ions and electrons transport.Here,sustainable bacterial cellulose(BC)is used both precursor and template for facile synthesis of free-standing N,S-codoped 3Dcarbon networks(a-NSC)by the pyrolysis and activation of polyrhodanine coated BC.The synthesized a-NSC shows highly conductive interconnected porous networks(24S·cm^(-1)),large surface area(1 420m^2·g^(-1))with hierarchical meso-microporosity,and high-level heteroatoms codoping(N:3.1%in atom,S:3.2%in atom).Benefitting from these,a-NSC as binder-free electrode exhibits an ultrahigh specific capacitance of 340F·g^(-1)(24μF·cm^(-2))at the current density of 0.5A·g^(-1)in 6MKOH electrolyte,high-rate capability(71%at 20A·g^(-1))and excellent cycle stability.Furthermore,the assembled symmetrical supercapacitor displays a much short time constant of 0.35sin 1MTEABF4/AN electrolyte,obtaining a maximum energy density of 32.1W·h·kg^(-1 )at power density of 637W·kg^(-1).The in situ multi-heteroatoms doping enables biocellulose-derived carbon networks to exploit its full potentials in energy storage applications,which can be extended to other dimensional carbon nanostructures.展开更多
Heteroatom-doped carbon has been demonstrated to be one of the most promising non-noble metal catalysts with high catalytic activity and stability through the modification of the electronic and geometric structures.In...Heteroatom-doped carbon has been demonstrated to be one of the most promising non-noble metal catalysts with high catalytic activity and stability through the modification of the electronic and geometric structures.In this study,we develop a novel solvent method to prepare interconnected N,S co-doped three-dimensional（3D）carbon networks with tunable nanopores derived from an asso-ciated complex based on melamine and sodium dodecylbenzene sulfonate（SDBS）.After the intro-duction of silica templates and calcination,the catalyst exhibits 3D networks with interconnected 50-nm pores and partial graphitization.With the increase of the number of Lewis base sites caused by the N doping and change of the carbon charge and spin densities caused by the S doping,the designed N,S co-doped catalyst exhibits a similar electrochemical activity to that of the commercial 20-wt%Pt/C as an oxygen reduction reaction catalyst.In addition,in an aluminum-air battery,the proposed catalyst even outperforms the commercial 5-wt%Pt/C catalyst.Both interconnected porous structures and synergistic effects of N and S contribute to the superior catalytic perfor-mance.This study paves the way for the synthesis of various other N-doped and co-doped carbon materials as efficient catalysts in electrochemical energy applications.展开更多
Sodium-ion batteries (SIBs) have been attracting considerable attention as a promising candidate for large-scale energy storage because of the abundance and low-cost of sodium resources. However, lack of appropriate a...Sodium-ion batteries (SIBs) have been attracting considerable attention as a promising candidate for large-scale energy storage because of the abundance and low-cost of sodium resources. However, lack of appropriate anode materials impedes further applications. Herein, a novel self-template strategy is designed to synthesize uniform flowerlike N-doped hierarchical porous carbon networks (NHPCN) with high content of N (15.31 at.%) assembled by ultrathin nanosheets via a self-synthesized single precursor and subsequent thermal annealing. Relying on the synergetic coordination of benzimidazole and 2-methylimidazole with metal ions to produce a flowerlike network, a self-formed single precursor can be harvested. Due to the structural and compositional advantages, including the high N doping, the expanded interlayer spacing, the ultrathin two-dimensional nano-sized subunits, and the three-dimensional porous network structure, these unique NHPCN flowers deliver ultrahigh reversible capacities of 453.7 mAh·g^−1 at 0.1 A·g^−1 and 242.5 mAh·g^−1 at 1 A·g^−1 for 2,500 cycles with exceptional rate capability of 5 A·g^−1 with reversible capacities of 201.2 mAh·g^−1. The greatly improved sodium storage performance of NHPCN confirms the importance of reasonable engineering and synthesis of hierarchical carbon with unique structures.展开更多
Black phosphorus has been recognized as a prospective candidate anode material for sodium-ion batteries(SIBs)due to its ultrahigh theoretical capacity of 2596 mA·h/g and high electric conductivity of≈300 S/m.How...Black phosphorus has been recognized as a prospective candidate anode material for sodium-ion batteries(SIBs)due to its ultrahigh theoretical capacity of 2596 mA·h/g and high electric conductivity of≈300 S/m.However,its large volume expansion and contraction during sodiation/desodiation lead to poor cycling stability.In this work,a BP/graphite nanoparticle/nitrogen-doped multiwalled carbon nanotubes(BP/G/CNTs)composite with a dual-carbon conductive network is successfully fabricated as a promising anode material for SIBs through a simple two-step mechanical milling process.The unique structure can mitigate the eff ect of volume changes and provide additional electron conduction pathways during cycles.Furthermore,the formation of P–O–C bonds helps maintain the intimate connection between phosphorus and carbon,thereby improving the cycling and rate performance.As a result,the BP/G/CNTs composite delivers a high initial Coulombic efficiency(89.6%)and a high specific capacity for SIBs(1791.3 mA·h/g after 100 cycles at 519.2 mA/g and 1665.2 mA·h/g after 100 cycles at 1298 mA/g).Based on these results,the integrated strategy of one-and two-dimensional carbon materials can guide other anode materials for SIBs.展开更多
SnO_(2) has been extensively investigated as an anode material for sodium-ion batteries(SIBs)and potassium-ion batteries(PIBs)due to its high Na/K storage capacity,high abundance,and low toxicity.However,the sluggish ...SnO_(2) has been extensively investigated as an anode material for sodium-ion batteries(SIBs)and potassium-ion batteries(PIBs)due to its high Na/K storage capacity,high abundance,and low toxicity.However,the sluggish reaction kinetics,low electronic conductivity,and large volume changes during charge and discharge hinder the practical applications of SnO_(2)-based electrodes for SIBs and PIBs.Engineering rational structures with fast charge/ion transfer and robust stability is important to overcoming these challenges.Herein,S-doped SnO_(2)(S-SnO_(2))quantum dots(QDs)(≈3 nm)encapsulated in an N,S codoped carbon fiber networks(S-SnO_(2)-CFN)are rationally fabricated using a sequential freeze-drying,calcination,and S-doping strategy.Experimental analysis and density functional theory calculations reveal that the integration of S-SnO_(2) QDs with N,S codoped carbon fiber network remarkably decreases the adsorption energies of Na/K atoms in the interlayer of SnO_(2)-CFN,and the S doping can increase the conductivity of SnO_(2),thereby enhancing the ion transfer kinetics.The synergistic interaction between S-SnO_(2) QDs and N,S codoped carbon fiber network results in a composite with fast Na+/K+storage and extraordinary long-term cyclability.Specifically,the S-SnO_(2)-CFN delivers high rate capacities of 141.0 mAh g^(−1) at 20 A g^(−1) in SIBs and 102.8 mAh g^(−1) at 10 A g^(−1) in PIBs.Impressively,it delivers ultra-stable sodium storage up to 10,000 cycles at 5 A g^(−1) and potassium storage up to 5000 cycles at 2 A g^(−1).This study provides insights into constructing metal oxide-based carbon fiber network structures for high-performance electrochemical energy storage and conversion devices.展开更多
Hierarchical porous carbons (HPCs) are obtained via in-situ activation of interpenetrating polymer networks (IPNs) obtained from simultaneous polymerization of resorcinol/formaldehyde (R/F) and polyacrylamide (PAM). T...Hierarchical porous carbons (HPCs) are obtained via in-situ activation of interpenetrating polymer networks (IPNs) obtained from simultaneous polymerization of resorcinol/formaldehyde (R/F) and polyacrylamide (PAM). The hierarchically micro-, meso-and macroporous structure of as-prepared HPCs is attributed to the synergistic pore-forming effect of PAM and KOH, including PAM decomposition, KOH chemical activation, and a foaming process of potassium polyacrylate formed by partial hydrolysis of PAM in KOH aqueous solution. The typical HPC electrode with the highest surface area (2544 m2/g) shows a high specific capacitance of 261 F/g at 1.0 A/g and a superior rate capability of 216 F/g at 20 A/g in alkaline electrolyte. Moreover, the electrode maintains the capacitance retention of 90.8% after 10000 chargingdischarging cycles at 1.0 A/g, exhibiting long cycling life. This study highlights a new avenue towards IPNs-derived carbons with unique pore structure for promising electrochemical applications.展开更多
Soil organic carbon (SOC) is an important and reliable indicator of soil quality. In this study, soil spectra were characterized and analysed to predict the spatial soil organic carbon (SOC) content using multivariate...Soil organic carbon (SOC) is an important and reliable indicator of soil quality. In this study, soil spectra were characterized and analysed to predict the spatial soil organic carbon (SOC) content using multivariate predictive modeling technique-artificial neural network (ANN). EO1-Hyperion (400 - 2500 nm) hyperspectral image, field and laboratory scale data sets (350 - 2500 nm) were generated which consisted of laboratory estimated SOC content of collected soil samples (dependent variable) and their corresponding reflectance data of SOC sensitive spectral bands (predictive variables). For each data set, ANN predictive models were developed and all three datasets (image-scale, field-scale and lab-scale) revealed significant network performances for training, testing and validation indicating a good network generalization for SOC content. ANN based analysis showed high prediction of SOC content at image (R2 = 0.93, and RPD = 3.19), field (R2 = 0.92 and RPD = 3.17), and lab scale (R2 = 0.95 and RPD = 3.16). Validation results of ANN indicated that predictive models performed well (R2 = 0.90) with RMSE 0.070. The result showed that ANN methods had a great potential for estimating and mapping spatial SOC content. The study concluded that ANN model was potential tools in predicting SOC distribution in agricultural field using hyper-spectral remote sensing data at image-scale, field-scale and lab-scale.展开更多
Firstly,neural network based on improved particle swarm optimization (PSO)algorithm is introduced in this paper. Based on the data collected from projects in typical areas,the concrete carbonation depth is assessed wi...Firstly,neural network based on improved particle swarm optimization (PSO)algorithm is introduced in this paper. Based on the data collected from projects in typical areas,the concrete carbonation depth is assessed with consideration of various factors such as unit cement consumption (C),unit water consumption (W),binder material content (B),water binder ratio (W/B ),concrete strength (MPa),rapid carbonization days (D),fly ash consumption of unit volume concrete(FA),fly ash percentage of total cementitious materials (FA%),expansion agent consumption of unit volume concrete(EA),expansion agent percentage of total cementitious materials (FA%).Gaining the data from project-experiment,a model is presented to calculate and forecast carbonation depth using neural network based on improved PSO algorithm. The calculation results indicate that this algorithm accord with the prediction carbonation depth of concrete accuracy requirements and has a better convergence and generalization,worth being popularized.展开更多
Carbon nanotube(CNT)networks enable CNTs to be used as building blocks for synthesizing novel advanced materials,thus taking full advantage of the superior properties of individual CNTs.Multiscale analyses have to be ...Carbon nanotube(CNT)networks enable CNTs to be used as building blocks for synthesizing novel advanced materials,thus taking full advantage of the superior properties of individual CNTs.Multiscale analyses have to be adopted to study the load transfer mechanisms of CNT networks from the atomic scale to the macroscopic scale due to the huge computational cost.Among them,fully resolved structural features include the graphitic honeycomb lattice(atomic),inter-tube stacking(nano)and assembly(meso)of CNTs.On an atomic scale,the elastic properties,ultimate stresses,and failure strains of individual CNTs with distinct chiralities and radii are obtained under various loading conditions by molecular mechanics.The dependence of the cohesive energies on spacing distances,crossing angles,size and edge effects between two CNTs is analyzed through continuum modeling in nanoscale.The mesoscale models,which neglect the atomic structures of individual CNTs but retain geometrical information about the shape of CNTs and their assembly into a network,have been developed to study the multi-level mechanism of material deformation and microstructural evolution in CNT networks under stretching,from elastic elongation,strengthening to damage and failure.This paper summarizes the multiscale theories mentioned above,which should provide insight into the optimal assembling of CNT network materials for elevated mechanical performance.展开更多
Several theoretical models have been developed so far to predict the thermal conductivities of carbon nanotube(CNT)networks.However,these models overestimated the thermal conductivity significantly.In this paper,we cl...Several theoretical models have been developed so far to predict the thermal conductivities of carbon nanotube(CNT)networks.However,these models overestimated the thermal conductivity significantly.In this paper,we claimed that a CNT network can be considered as a contact thermal resistance network.In the contact thermal resistance network,the temperature of an individual CNT is nonuniform and the intrinsic thermal resistance of CNTs can be ignored.Compared with the previous models,the model we proposed agrees well with the experimental results of single-walled CNT networks.展开更多
To determine the effect of dissolution on pore network development in carbonate rocks, dissolution experiments, X-Ray microtomography, and thin section analysis were conducted on argillaceous limestone and grain limes...To determine the effect of dissolution on pore network development in carbonate rocks, dissolution experiments, X-Ray microtomography, and thin section analysis were conducted on argillaceous limestone and grain limestone samples at different temperatures and constant pH, HCl concentration. The relationship between Ca^(2+) concentration and time was revealed through the experiments; pore size distribution before and after dissolution indicate that there is no correlation between the temperature and pore size variation, but pore size variation in grain limestone is more significant, indicating that the variation is mainly controlled by the heterogeneity of the rock itself(initial porosity and permeability) and the abundance of unstable minerals(related to crystal shape, size and mineral type). At different temperatures, the two kinds of carbonate rocks had very small variation in pore throat radius from 0.003 mm to 0.040 mm, which is 1.3 to 3.5 times more, 1.7 on average of the original pore throat radius. Their pore throat length varied from 0.05 mm to 0.35 mm. The minor changes in the pore throat radius, length and connectivity brought big changes to permeability of up to 1 000×10^(-3) μm^2.展开更多
The solubility data of compounds in supercritical fluids and the correlation between the experimental solubility data and predicted solubility data are crucial to the development of supercritical technologies. In the ...The solubility data of compounds in supercritical fluids and the correlation between the experimental solubility data and predicted solubility data are crucial to the development of supercritical technologies. In the present work, the solubility data of silymarin(SM) in both pure supercritical carbon dioxide(SCCO2) and SCCO2 with added cosolvent was measured at temperatures ranging from 308 to 338 K and pressures from 8 to 22 MPa. The experimental data were fit with three semi-empirical density-based models(Chrastil, Bartle and Mendez-Santiago and Teja models) and a back-propagation artificial neural networks(BPANN) model. Interaction parameters for the models were obtained and the percentage of average absolute relative deviation(AARD%) in each calculation was determined. The correlation results were in good agreement with the experimental data. A comparison among the four models revealed that the experimental solubility data were more fit with the BPANN model with AARDs ranging from 1.14% to 2.15% for silymarin in pure SCCO2 and with added cosolvent. The results provide fundamental data for designing the extraction of SM or the preparation of its particle using SCCO2 techniques.展开更多
Climate Pollution due to the Carbon Emission (CO2) from the different fossil fuels is considered as a great and important international challenge to many researchers. In this paper we are providing a solution to forec...Climate Pollution due to the Carbon Emission (CO2) from the different fossil fuels is considered as a great and important international challenge to many researchers. In this paper we are providing a solution to forecast the poison CO2 gas emerged from energy consumption. Four inputs data were considered the global oil, natural gas, coal, and primary energy consumption to build our system. In this paper, we used the Artificial Neural Network (ANN) as successful and powerful tool in handling a time series modeling problem. The proposed ANN model was used to train and test the yearly CO2 Emission. The data were trained from year 1982 to 2000, and tested for the year 2003 to 2010. From the results obtained we can see that ANN performance was Excellent and proved its efficiency as a useful tool in solving the climate pollution problems.展开更多
基金financially supported by the National Natural Science Foundation of China(Grant Nos.52130303,52327802,52303101,52173078,51973158)the China Postdoctoral Science Foundation(2023M732579)+2 种基金Young Elite Scientists Sponsorship Program by CAST(No.2022QNRC001)National Key R&D Program of China(No.2022YFB3805702)Joint Funds of Ministry of Education(8091B032218).
文摘Vertically oriented carbon structures constructed from low-dimen-sional carbon materials are ideal frameworks for high-performance thermal inter-face materials(TIMs).However,improving the interfacial heat-transfer efficiency of vertically oriented carbon structures is a challenging task.Herein,an orthotropic three-dimensional(3D)hybrid carbon network(VSCG)is fabricated by depositing vertically aligned carbon nanotubes(VACNTs)on the surface of a horizontally oriented graphene film(HOGF).The interfacial interaction between the VACNTs and HOGF is then optimized through an annealing strategy.After regulating the orientation structure of the VACNTs and filling the VSCG with polydimethylsi-loxane(PDMS),VSCG/PDMS composites with excellent 3D thermal conductive properties are obtained.The highest in-plane and through-plane thermal conduc-tivities of the composites are 113.61 and 24.37 W m^(-1)K^(-1),respectively.The high contact area of HOGF and good compressibility of VACNTs imbue the VSCG/PDMS composite with low thermal resistance.In addition,the interfacial heat-transfer efficiency of VSCG/PDMS composite in the TIM performance was improved by 71.3%compared to that of a state-of-the-art thermal pad.This new structural design can potentially realize high-performance TIMs that meet the need for high thermal conductivity and low contact thermal resistance in interfacial heat-transfer processes.
基金financial supports from Natural Science Foundation of Ningbo(202003N4026)S&T Innovation 2025 Major Special Programme of Ningbo(2018B10054)National Natural Science Foundation of China(62001065 and 51603218)。
文摘Nowadays,carbon frameworks derived from natural biomaterials have attracted extensive attention for electromagnetic interference(EMI)shielding due to their renewability and affordability.However,it is critical and challenging to achieve effective regulation of shielding effectiveness(SE)as well as weaken the strong EM reflection of highly conductive biomass-based carbon materials.Herein,commercial cotton pads with oriented structure were selected as carbonaceous precursor to fabricate aligned carbon networks by pyrolysis,and the EMI SE of the samples with increased temperature of 800-1000℃ can be accurately controlled in the effective range of~21.7-29.1,~27.7-37.1 and~32.7-43.3 d B with high reflection coefficient of>0.8 by changing the cross-angle between the electric-field direction of incident EM waves and the fiber-orientation direction due to the occurrence of opposite internal electric field.Moreover,the further construction of Salisbury absorber-liked double-layer structure could result in an ultralow reflection coefficient of only~0.06 but enhanced SE variation range up to~38.7-49.3 d B during the adjustment of cross-angle,possibly due to the destructive interference of EM waves in the double-layer carbon networks.This work would provide a simple and effective way for constructing high-performance biomass carbon materials with adjustable EMI shielding and ultra-low reflectivity.
基金supported by the National Basic Research Program of China(973 Program)(No.2014CB239701)the National Natural Science Foundation of China(Nos.51672128,51372116,21773118)+2 种基金the Natural Science Foundation of Jiangsu Province(Nos.BK20150739,BK20151468)the Prospective Joint Research Project of Cooperative Innovation Fund of Jiangsu Province(No.BY2015003-7)the Project Funded by the Priority Academic Program Development of Jiangsu Higher Education Institutions(PAPD)
文摘Three-dimensional(3D)carbon networks have been explored as promising capacitive materials thanks to their unique structural features such as large ion-accessible surface area and interconnected porous networks,thus enhancing both ions and electrons transport.Here,sustainable bacterial cellulose(BC)is used both precursor and template for facile synthesis of free-standing N,S-codoped 3Dcarbon networks(a-NSC)by the pyrolysis and activation of polyrhodanine coated BC.The synthesized a-NSC shows highly conductive interconnected porous networks(24S·cm^(-1)),large surface area(1 420m^2·g^(-1))with hierarchical meso-microporosity,and high-level heteroatoms codoping(N:3.1%in atom,S:3.2%in atom).Benefitting from these,a-NSC as binder-free electrode exhibits an ultrahigh specific capacitance of 340F·g^(-1)(24μF·cm^(-2))at the current density of 0.5A·g^(-1)in 6MKOH electrolyte,high-rate capability(71%at 20A·g^(-1))and excellent cycle stability.Furthermore,the assembled symmetrical supercapacitor displays a much short time constant of 0.35sin 1MTEABF4/AN electrolyte,obtaining a maximum energy density of 32.1W·h·kg^(-1 )at power density of 637W·kg^(-1).The in situ multi-heteroatoms doping enables biocellulose-derived carbon networks to exploit its full potentials in energy storage applications,which can be extended to other dimensional carbon nanostructures.
基金supported by the National Natural Science Foundation of China (51674297)the Natural Science Foundation of Hunan Province (2016JJ2137)the Fundamental Research Funds for the Central Universities of Central South University (2015cx001)~~
文摘Heteroatom-doped carbon has been demonstrated to be one of the most promising non-noble metal catalysts with high catalytic activity and stability through the modification of the electronic and geometric structures.In this study,we develop a novel solvent method to prepare interconnected N,S co-doped three-dimensional（3D）carbon networks with tunable nanopores derived from an asso-ciated complex based on melamine and sodium dodecylbenzene sulfonate（SDBS）.After the intro-duction of silica templates and calcination,the catalyst exhibits 3D networks with interconnected 50-nm pores and partial graphitization.With the increase of the number of Lewis base sites caused by the N doping and change of the carbon charge and spin densities caused by the S doping,the designed N,S co-doped catalyst exhibits a similar electrochemical activity to that of the commercial 20-wt%Pt/C as an oxygen reduction reaction catalyst.In addition,in an aluminum-air battery,the proposed catalyst even outperforms the commercial 5-wt%Pt/C catalyst.Both interconnected porous structures and synergistic effects of N and S contribute to the superior catalytic perfor-mance.This study paves the way for the synthesis of various other N-doped and co-doped carbon materials as efficient catalysts in electrochemical energy applications.
基金The work was financially supported by the National Natural Science of Foundation of China(No.51672114)the Natural Science Foundation of Jiangsu Province(No.BK20181469)the Zhenjiang Key Research and Development Project(Social Development)(No.SSH20190140049).
文摘Sodium-ion batteries (SIBs) have been attracting considerable attention as a promising candidate for large-scale energy storage because of the abundance and low-cost of sodium resources. However, lack of appropriate anode materials impedes further applications. Herein, a novel self-template strategy is designed to synthesize uniform flowerlike N-doped hierarchical porous carbon networks (NHPCN) with high content of N (15.31 at.%) assembled by ultrathin nanosheets via a self-synthesized single precursor and subsequent thermal annealing. Relying on the synergetic coordination of benzimidazole and 2-methylimidazole with metal ions to produce a flowerlike network, a self-formed single precursor can be harvested. Due to the structural and compositional advantages, including the high N doping, the expanded interlayer spacing, the ultrathin two-dimensional nano-sized subunits, and the three-dimensional porous network structure, these unique NHPCN flowers deliver ultrahigh reversible capacities of 453.7 mAh·g^−1 at 0.1 A·g^−1 and 242.5 mAh·g^−1 at 1 A·g^−1 for 2,500 cycles with exceptional rate capability of 5 A·g^−1 with reversible capacities of 201.2 mAh·g^−1. The greatly improved sodium storage performance of NHPCN confirms the importance of reasonable engineering and synthesis of hierarchical carbon with unique structures.
基金financially supported by the National Key Research Program of China(No.2018YFC0808601)。
文摘Black phosphorus has been recognized as a prospective candidate anode material for sodium-ion batteries(SIBs)due to its ultrahigh theoretical capacity of 2596 mA·h/g and high electric conductivity of≈300 S/m.However,its large volume expansion and contraction during sodiation/desodiation lead to poor cycling stability.In this work,a BP/graphite nanoparticle/nitrogen-doped multiwalled carbon nanotubes(BP/G/CNTs)composite with a dual-carbon conductive network is successfully fabricated as a promising anode material for SIBs through a simple two-step mechanical milling process.The unique structure can mitigate the eff ect of volume changes and provide additional electron conduction pathways during cycles.Furthermore,the formation of P–O–C bonds helps maintain the intimate connection between phosphorus and carbon,thereby improving the cycling and rate performance.As a result,the BP/G/CNTs composite delivers a high initial Coulombic efficiency(89.6%)and a high specific capacity for SIBs(1791.3 mA·h/g after 100 cycles at 519.2 mA/g and 1665.2 mA·h/g after 100 cycles at 1298 mA/g).Based on these results,the integrated strategy of one-and two-dimensional carbon materials can guide other anode materials for SIBs.
基金National Natural Science Foundation of China,Grant/Award Number:51971065Innovation Program of Shanghai Municipal Education Commission,Grant/Award Number:2019-01-07-00-07-E00028。
文摘SnO_(2) has been extensively investigated as an anode material for sodium-ion batteries(SIBs)and potassium-ion batteries(PIBs)due to its high Na/K storage capacity,high abundance,and low toxicity.However,the sluggish reaction kinetics,low electronic conductivity,and large volume changes during charge and discharge hinder the practical applications of SnO_(2)-based electrodes for SIBs and PIBs.Engineering rational structures with fast charge/ion transfer and robust stability is important to overcoming these challenges.Herein,S-doped SnO_(2)(S-SnO_(2))quantum dots(QDs)(≈3 nm)encapsulated in an N,S codoped carbon fiber networks(S-SnO_(2)-CFN)are rationally fabricated using a sequential freeze-drying,calcination,and S-doping strategy.Experimental analysis and density functional theory calculations reveal that the integration of S-SnO_(2) QDs with N,S codoped carbon fiber network remarkably decreases the adsorption energies of Na/K atoms in the interlayer of SnO_(2)-CFN,and the S doping can increase the conductivity of SnO_(2),thereby enhancing the ion transfer kinetics.The synergistic interaction between S-SnO_(2) QDs and N,S codoped carbon fiber network results in a composite with fast Na+/K+storage and extraordinary long-term cyclability.Specifically,the S-SnO_(2)-CFN delivers high rate capacities of 141.0 mAh g^(−1) at 20 A g^(−1) in SIBs and 102.8 mAh g^(−1) at 10 A g^(−1) in PIBs.Impressively,it delivers ultra-stable sodium storage up to 10,000 cycles at 5 A g^(−1) and potassium storage up to 5000 cycles at 2 A g^(−1).This study provides insights into constructing metal oxide-based carbon fiber network structures for high-performance electrochemical energy storage and conversion devices.
基金financially supported by the National Natural Science Foundation of China(Nos. 51772216, 21703161 and 21875165)the Science and Technology Commission of Shanghai Municipality, China (No. 14DZ2261100)the Fundamental Research Funds for the Central Universities
文摘Hierarchical porous carbons (HPCs) are obtained via in-situ activation of interpenetrating polymer networks (IPNs) obtained from simultaneous polymerization of resorcinol/formaldehyde (R/F) and polyacrylamide (PAM). The hierarchically micro-, meso-and macroporous structure of as-prepared HPCs is attributed to the synergistic pore-forming effect of PAM and KOH, including PAM decomposition, KOH chemical activation, and a foaming process of potassium polyacrylate formed by partial hydrolysis of PAM in KOH aqueous solution. The typical HPC electrode with the highest surface area (2544 m2/g) shows a high specific capacitance of 261 F/g at 1.0 A/g and a superior rate capability of 216 F/g at 20 A/g in alkaline electrolyte. Moreover, the electrode maintains the capacitance retention of 90.8% after 10000 chargingdischarging cycles at 1.0 A/g, exhibiting long cycling life. This study highlights a new avenue towards IPNs-derived carbons with unique pore structure for promising electrochemical applications.
文摘Soil organic carbon (SOC) is an important and reliable indicator of soil quality. In this study, soil spectra were characterized and analysed to predict the spatial soil organic carbon (SOC) content using multivariate predictive modeling technique-artificial neural network (ANN). EO1-Hyperion (400 - 2500 nm) hyperspectral image, field and laboratory scale data sets (350 - 2500 nm) were generated which consisted of laboratory estimated SOC content of collected soil samples (dependent variable) and their corresponding reflectance data of SOC sensitive spectral bands (predictive variables). For each data set, ANN predictive models were developed and all three datasets (image-scale, field-scale and lab-scale) revealed significant network performances for training, testing and validation indicating a good network generalization for SOC content. ANN based analysis showed high prediction of SOC content at image (R2 = 0.93, and RPD = 3.19), field (R2 = 0.92 and RPD = 3.17), and lab scale (R2 = 0.95 and RPD = 3.16). Validation results of ANN indicated that predictive models performed well (R2 = 0.90) with RMSE 0.070. The result showed that ANN methods had a great potential for estimating and mapping spatial SOC content. The study concluded that ANN model was potential tools in predicting SOC distribution in agricultural field using hyper-spectral remote sensing data at image-scale, field-scale and lab-scale.
文摘Firstly,neural network based on improved particle swarm optimization (PSO)algorithm is introduced in this paper. Based on the data collected from projects in typical areas,the concrete carbonation depth is assessed with consideration of various factors such as unit cement consumption (C),unit water consumption (W),binder material content (B),water binder ratio (W/B ),concrete strength (MPa),rapid carbonization days (D),fly ash consumption of unit volume concrete(FA),fly ash percentage of total cementitious materials (FA%),expansion agent consumption of unit volume concrete(EA),expansion agent percentage of total cementitious materials (FA%).Gaining the data from project-experiment,a model is presented to calculate and forecast carbonation depth using neural network based on improved PSO algorithm. The calculation results indicate that this algorithm accord with the prediction carbonation depth of concrete accuracy requirements and has a better convergence and generalization,worth being popularized.
基金Supported by National Natural Science Foundation of China(Grant Nos.11972171,11572140)Sixth Phase of Jiangsu Province“333 High Level Talent Training Project”Second Level Talents,111 Project(Grant No.B18027)+3 种基金Natural Science Foundation of Jiangsu Province(Grant No.BK20180031)Research Project of State Key Laboratory of Mechanical System and Vibration(Grant No.MSV201909)Fundamental Research Funds for the Central Universities(Grant No.JUSRP22002)Postgraduate Research&Practice Innovation Program of Jiangsu Province(Grant No.KYCX19_1861).
文摘Carbon nanotube(CNT)networks enable CNTs to be used as building blocks for synthesizing novel advanced materials,thus taking full advantage of the superior properties of individual CNTs.Multiscale analyses have to be adopted to study the load transfer mechanisms of CNT networks from the atomic scale to the macroscopic scale due to the huge computational cost.Among them,fully resolved structural features include the graphitic honeycomb lattice(atomic),inter-tube stacking(nano)and assembly(meso)of CNTs.On an atomic scale,the elastic properties,ultimate stresses,and failure strains of individual CNTs with distinct chiralities and radii are obtained under various loading conditions by molecular mechanics.The dependence of the cohesive energies on spacing distances,crossing angles,size and edge effects between two CNTs is analyzed through continuum modeling in nanoscale.The mesoscale models,which neglect the atomic structures of individual CNTs but retain geometrical information about the shape of CNTs and their assembly into a network,have been developed to study the multi-level mechanism of material deformation and microstructural evolution in CNT networks under stretching,from elastic elongation,strengthening to damage and failure.This paper summarizes the multiscale theories mentioned above,which should provide insight into the optimal assembling of CNT network materials for elevated mechanical performance.
基金Project support by the National Natural Science Foundation of China(Grant No.52127811)Department of Science and Technology of Jiangsu Province,China(Grant No.BK20220032)。
文摘Several theoretical models have been developed so far to predict the thermal conductivities of carbon nanotube(CNT)networks.However,these models overestimated the thermal conductivity significantly.In this paper,we claimed that a CNT network can be considered as a contact thermal resistance network.In the contact thermal resistance network,the temperature of an individual CNT is nonuniform and the intrinsic thermal resistance of CNTs can be ignored.Compared with the previous models,the model we proposed agrees well with the experimental results of single-walled CNT networks.
基金sponsored by PETRONAS and YUTP (Yayasan Universiti Teknologi PETRONAS)
文摘To determine the effect of dissolution on pore network development in carbonate rocks, dissolution experiments, X-Ray microtomography, and thin section analysis were conducted on argillaceous limestone and grain limestone samples at different temperatures and constant pH, HCl concentration. The relationship between Ca^(2+) concentration and time was revealed through the experiments; pore size distribution before and after dissolution indicate that there is no correlation between the temperature and pore size variation, but pore size variation in grain limestone is more significant, indicating that the variation is mainly controlled by the heterogeneity of the rock itself(initial porosity and permeability) and the abundance of unstable minerals(related to crystal shape, size and mineral type). At different temperatures, the two kinds of carbonate rocks had very small variation in pore throat radius from 0.003 mm to 0.040 mm, which is 1.3 to 3.5 times more, 1.7 on average of the original pore throat radius. Their pore throat length varied from 0.05 mm to 0.35 mm. The minor changes in the pore throat radius, length and connectivity brought big changes to permeability of up to 1 000×10^(-3) μm^2.
基金supported financially by the Subject Chief Scientist Program (10XD14303900) from Science and Technology Commission of Shanghai Municipalitythe Special Research Fund for the Doctoral Program of Higher Education of China (20123107110005)
文摘The solubility data of compounds in supercritical fluids and the correlation between the experimental solubility data and predicted solubility data are crucial to the development of supercritical technologies. In the present work, the solubility data of silymarin(SM) in both pure supercritical carbon dioxide(SCCO2) and SCCO2 with added cosolvent was measured at temperatures ranging from 308 to 338 K and pressures from 8 to 22 MPa. The experimental data were fit with three semi-empirical density-based models(Chrastil, Bartle and Mendez-Santiago and Teja models) and a back-propagation artificial neural networks(BPANN) model. Interaction parameters for the models were obtained and the percentage of average absolute relative deviation(AARD%) in each calculation was determined. The correlation results were in good agreement with the experimental data. A comparison among the four models revealed that the experimental solubility data were more fit with the BPANN model with AARDs ranging from 1.14% to 2.15% for silymarin in pure SCCO2 and with added cosolvent. The results provide fundamental data for designing the extraction of SM or the preparation of its particle using SCCO2 techniques.
文摘Climate Pollution due to the Carbon Emission (CO2) from the different fossil fuels is considered as a great and important international challenge to many researchers. In this paper we are providing a solution to forecast the poison CO2 gas emerged from energy consumption. Four inputs data were considered the global oil, natural gas, coal, and primary energy consumption to build our system. In this paper, we used the Artificial Neural Network (ANN) as successful and powerful tool in handling a time series modeling problem. The proposed ANN model was used to train and test the yearly CO2 Emission. The data were trained from year 1982 to 2000, and tested for the year 2003 to 2010. From the results obtained we can see that ANN performance was Excellent and proved its efficiency as a useful tool in solving the climate pollution problems.
