This study systematically conducted preparation optimization and performance investigations on Co-modified Ce/TiO_(2) catalysts,with a focus on examining how preparation methods and Co loading regulate the catalyst’s...This study systematically conducted preparation optimization and performance investigations on Co-modified Ce/TiO_(2) catalysts,with a focus on examining how preparation methods and Co loading regulate the catalyst’s low-temperature denitrification activity.After identifying optimal preparation parameters via condition screening,multiple characterization techniques-including BET,XRD,XPS,H_(2)-TPR and in situ DRIFTS-were employed to deeply analyze the catalyst’s physicochemical properties and reaction mechanism.Results demonstrated that compared to the impregnation and co-precipitation methods,the Ce-Co_(0.025)/TiO_(2)-SG catalyst(prepared by the sol-gel method with a Co/Ti mass ratio of 0.025)exhibited significantly superior denitrification activity:NO conversion remained stably above 95%in the 225−350℃ temperature range,and it displayed high N_(2) selectivity.Characterization analysis revealed that abundant surface oxygen vacancies,a high proportion of Ce^(3+) species,and prominent acidic sites collectively contributed to enhancing its low-temperature denitrification performance.This work provides reference value for the development of highly efficient low-temperature denitrification catalysts.展开更多
Nano-scale CuF_(2) with superior electrochemical activity was successfully prepared by a mixed solvent co-precipitation method.The SEM and TEM analyses demonstrated that the methanol concentration had a pronounced eff...Nano-scale CuF_(2) with superior electrochemical activity was successfully prepared by a mixed solvent co-precipitation method.The SEM and TEM analyses demonstrated that the methanol concentration had a pronounced effect on both the particle size and the extent of agglomeration.With the increase in methanol content,the particle size and agglomeration of CuF_(2) decreased first and then increased.When the volume ratio of methanol to deionized water was 1:1,the CuF_(2) particles exhibited the smallest size and the lowest degree of agglomeration.CuF_(2) synthesized with 50%methanol exhibited superior electrochemical performances with a voltage plateau above 3 V and a 1st discharge capacity of 525.8 mAh·g^(-1) at 0.01 C due to the synergistic influence of the particle size and dispersion.The analysis results using electrochemical impedance spectroscopy(EIS)and constant current intermittent titration technique(GITT)affirmed the addition of methanol was beneficial for promoting Li+diffusion and accelerating electrochemical reaction kinetics of CuF_(2).展开更多
Elevation change monitoring of the Antarctic ice sheet has been a key issue in global change research.Satellite altimetry has been proven to be effective in detecting ice sheet variations. With the development of ICES...Elevation change monitoring of the Antarctic ice sheet has been a key issue in global change research.Satellite altimetry has been proven to be effective in detecting ice sheet variations. With the development of ICESat-2, many elevation observations can be used to derive elevation changes. However, the large amount of multitemporal data may include anomalous data points, increasing the uncertainty of the results. In this work, we improved the traditional repeat track method by introducing the Institute of Geodesy and Geophysics Ⅲ(IGGⅢ) method to obtain high-accuracy estimates of elevation change. The improved method was applied to analyze elevation changes along the transect from Zhongshan Station to Dome A in East Antarctica via ICESat-2 satellite altimetry data. The results show that the improved and traditional methods yield consistent numerical and spatial elevation change distributions. The elevation change calculated via the traditional method is 0.033 ± 0.131 m/yr, whereas the elevation change estimated via the IGGⅢ robust estimation method is 0.033 ± 0.109 m/yr from March 2019 to December 2021.In terms of spatial distribution, elevation changes in inland areas remain close to equilibrium, whereas regions with steeper ice sheet margins exhibit positive accumulation trends in elevation changes. The improved method reduces the standard error of the adjustment function from 0.975 to 0.691 m/yr. The improvement is particularly remarkable in the area between 72°S and 77°S. The results demonstrate that the IGGⅢ method effectively reduces errors caused by the inclusion of anomalous data and maintains the high data utilization rate of repeat-orbit methods.展开更多
The two-phase flow in porous media is affected by multiple factors.In the present study,a two-dimensional numerical model of porous media was developed using the actual pore structure of the core sample.The phase fiel...The two-phase flow in porous media is affected by multiple factors.In the present study,a two-dimensional numerical model of porous media was developed using the actual pore structure of the core sample.The phase field method was utilized to simulate the impact of displacement velocity,the water-gas viscosity ratio,and the density ratio on the flow behavior of two-phase fluids in porous media.The effectiveness of displacement was evaluated by analyzing CO_(2)saturation levels.The results indicate that the saturation of CO_(2)in porous media increased as the displacement velocity increased.When the displacement velocity exceeded 0.01 m/s,there was a corresponding increase in CO_(2)saturation.Conversely,when the displacement velocity was below this threshold,the impact on CO_(2)saturation was minimal.An“inflection point,”M3,was present in the viscosity ratio.When the viscosity of CO_(2)is less than 8.937×10^(-5)Pa·s(viscosity ratio below M3),variations in the viscosity of CO_(2)had little impact on its saturation.Conversely,when the viscosity of CO_(2)exceeded 8.937×10^(-5)Pa·s(viscosity ratio greater than M3),saturation increased with an increase in the viscosity ratio.In terms of the density ratio,the saturation of CO_(2)increased monotonically with an increase in the density ratio.Similarly,increasing density ratios resulted in a monotonic increase in CO_(2)saturation,though this trend was less pronounced in numerical simulations.Analysis results of displacement within dead-end pores using pressure and velocity diagrams reveal eddy currents as contributing factors.Finally,the impact of pore throat structure on the formation of dominant channels was examined.展开更多
Objective To improve the accuracy and professionalism of question-answering(QA)model in traditional Chinese medicine(TCM)lung cancer by integrating large language models with structured knowledge graphs using the know...Objective To improve the accuracy and professionalism of question-answering(QA)model in traditional Chinese medicine(TCM)lung cancer by integrating large language models with structured knowledge graphs using the knowledge graph(KG)to text-enhanced retrievalaugmented generation(KG2TRAG)method.Methods The TCM lung cancer model(TCMLCM)was constructed by fine-tuning Chat-GLM2-6B on the specialized datasets Tianchi TCM,HuangDi,and ShenNong-TCM-Dataset,as well as a TCM lung cancer KG.The KG2TRAG method was applied to enhance the knowledge retrieval,which can convert KG triples into natural language text via ChatGPT-aided linearization,leveraging large language models(LLMs)for context-aware reasoning.For a comprehensive comparison,MedicalGPT,HuatuoGPT,and BenTsao were selected as the baseline models.Performance was evaluated using bilingual evaluation understudy(BLEU),recall-oriented understudy for gisting evaluation(ROUGE),accuracy,and the domain-specific TCM-LCEval metrics,with validation from TCM oncology experts assessing answer accuracy,professionalism,and usability.Results The TCMLCM model achieved the optimal performance across all metrics,including a BLEU score of 32.15%,ROUGE-L of 59.08%,and an accuracy rate of 79.68%.Notably,in the TCM-LCEval assessment specific to the field of TCM,its performance was 3%−12%higher than that of the baseline model.Expert evaluations highlighted superior performance in accuracy and professionalism.Conclusion TCMLCM can provide an innovative solution for TCM lung cancer QA,demonstrating the feasibility of integrating structured KGs with LLMs.This work advances intelligent TCM healthcare tools and lays a foundation for future AI-driven applications in traditional medicine.展开更多
To ensure the safe operation of batteries,accurately obtaining key internal state parameters is essential.However,traditional parameter measurement methods either require opening the battery or long-term measurements,...To ensure the safe operation of batteries,accurately obtaining key internal state parameters is essential.However,traditional parameter measurement methods either require opening the battery or long-term measurements,which are impractical.Therefore,the fixed values are commonly used for these parameters in electrochemical models and have significant limitations.To overcome these limitations,this paper proposes a deep neural network(DNN)based data-driven evaluation method to determine model parameters.By coupling an improved one-dimensional isothermal pseudo-twodimensional(P2D)model with DNN,this study identified concentration-dependent parameters through detailed discharge curve analysis.The results show that the data-driven method can effectively obtain the change trend of concentration-dependent parameters through the charge and discharge curve,and the method can be extended to different battery systems in different discharge rates and aging applications.This work is expected to provide new parameter selection insights for data-driven battery prediction and monitoring models.展开更多
基金Supported by the National Key Research and Development Program of China (2023YFB4102903)。
文摘This study systematically conducted preparation optimization and performance investigations on Co-modified Ce/TiO_(2) catalysts,with a focus on examining how preparation methods and Co loading regulate the catalyst’s low-temperature denitrification activity.After identifying optimal preparation parameters via condition screening,multiple characterization techniques-including BET,XRD,XPS,H_(2)-TPR and in situ DRIFTS-were employed to deeply analyze the catalyst’s physicochemical properties and reaction mechanism.Results demonstrated that compared to the impregnation and co-precipitation methods,the Ce-Co_(0.025)/TiO_(2)-SG catalyst(prepared by the sol-gel method with a Co/Ti mass ratio of 0.025)exhibited significantly superior denitrification activity:NO conversion remained stably above 95%in the 225−350℃ temperature range,and it displayed high N_(2) selectivity.Characterization analysis revealed that abundant surface oxygen vacancies,a high proportion of Ce^(3+) species,and prominent acidic sites collectively contributed to enhancing its low-temperature denitrification performance.This work provides reference value for the development of highly efficient low-temperature denitrification catalysts.
文摘Nano-scale CuF_(2) with superior electrochemical activity was successfully prepared by a mixed solvent co-precipitation method.The SEM and TEM analyses demonstrated that the methanol concentration had a pronounced effect on both the particle size and the extent of agglomeration.With the increase in methanol content,the particle size and agglomeration of CuF_(2) decreased first and then increased.When the volume ratio of methanol to deionized water was 1:1,the CuF_(2) particles exhibited the smallest size and the lowest degree of agglomeration.CuF_(2) synthesized with 50%methanol exhibited superior electrochemical performances with a voltage plateau above 3 V and a 1st discharge capacity of 525.8 mAh·g^(-1) at 0.01 C due to the synergistic influence of the particle size and dispersion.The analysis results using electrochemical impedance spectroscopy(EIS)and constant current intermittent titration technique(GITT)affirmed the addition of methanol was beneficial for promoting Li+diffusion and accelerating electrochemical reaction kinetics of CuF_(2).
基金supported by the National Key Research and Development Program of China under grant number 2023YFC2809103the Fundamental Research Funds for the Central Universities under grant numbers 2042022kf1204, 2042022kf1069, 2042023gf0012, 2042022dx0001+1 种基金the Hubei Provincial Natural Science Foundation of China under grant number 2022CFB081the State Key Laboratory of Geodesy and Earth's Dynamics, Innovation Academy for Precision Measurement Science and Technology under grant number SKLGED2023-2-6
文摘Elevation change monitoring of the Antarctic ice sheet has been a key issue in global change research.Satellite altimetry has been proven to be effective in detecting ice sheet variations. With the development of ICESat-2, many elevation observations can be used to derive elevation changes. However, the large amount of multitemporal data may include anomalous data points, increasing the uncertainty of the results. In this work, we improved the traditional repeat track method by introducing the Institute of Geodesy and Geophysics Ⅲ(IGGⅢ) method to obtain high-accuracy estimates of elevation change. The improved method was applied to analyze elevation changes along the transect from Zhongshan Station to Dome A in East Antarctica via ICESat-2 satellite altimetry data. The results show that the improved and traditional methods yield consistent numerical and spatial elevation change distributions. The elevation change calculated via the traditional method is 0.033 ± 0.131 m/yr, whereas the elevation change estimated via the IGGⅢ robust estimation method is 0.033 ± 0.109 m/yr from March 2019 to December 2021.In terms of spatial distribution, elevation changes in inland areas remain close to equilibrium, whereas regions with steeper ice sheet margins exhibit positive accumulation trends in elevation changes. The improved method reduces the standard error of the adjustment function from 0.975 to 0.691 m/yr. The improvement is particularly remarkable in the area between 72°S and 77°S. The results demonstrate that the IGGⅢ method effectively reduces errors caused by the inclusion of anomalous data and maintains the high data utilization rate of repeat-orbit methods.
基金National Science Foundation of China,Grant/Award Number:5227090113Shenzhen Science and Technology Program,Grant/Award Numbers:KCXFZ20230731093901003,KCXFZ20211020163816023The Project of Hetao Shenzhen-Hong Kong Science and Technology Innovation Cooperation Zone,Grant/Award Number:HZQB-KCZYB-2020083。
文摘The two-phase flow in porous media is affected by multiple factors.In the present study,a two-dimensional numerical model of porous media was developed using the actual pore structure of the core sample.The phase field method was utilized to simulate the impact of displacement velocity,the water-gas viscosity ratio,and the density ratio on the flow behavior of two-phase fluids in porous media.The effectiveness of displacement was evaluated by analyzing CO_(2)saturation levels.The results indicate that the saturation of CO_(2)in porous media increased as the displacement velocity increased.When the displacement velocity exceeded 0.01 m/s,there was a corresponding increase in CO_(2)saturation.Conversely,when the displacement velocity was below this threshold,the impact on CO_(2)saturation was minimal.An“inflection point,”M3,was present in the viscosity ratio.When the viscosity of CO_(2)is less than 8.937×10^(-5)Pa·s(viscosity ratio below M3),variations in the viscosity of CO_(2)had little impact on its saturation.Conversely,when the viscosity of CO_(2)exceeded 8.937×10^(-5)Pa·s(viscosity ratio greater than M3),saturation increased with an increase in the viscosity ratio.In terms of the density ratio,the saturation of CO_(2)increased monotonically with an increase in the density ratio.Similarly,increasing density ratios resulted in a monotonic increase in CO_(2)saturation,though this trend was less pronounced in numerical simulations.Analysis results of displacement within dead-end pores using pressure and velocity diagrams reveal eddy currents as contributing factors.Finally,the impact of pore throat structure on the formation of dominant channels was examined.
基金Postgraduate Research&Practice Innovation Program of Jiangsu Province(KYCX24_2145).
文摘Objective To improve the accuracy and professionalism of question-answering(QA)model in traditional Chinese medicine(TCM)lung cancer by integrating large language models with structured knowledge graphs using the knowledge graph(KG)to text-enhanced retrievalaugmented generation(KG2TRAG)method.Methods The TCM lung cancer model(TCMLCM)was constructed by fine-tuning Chat-GLM2-6B on the specialized datasets Tianchi TCM,HuangDi,and ShenNong-TCM-Dataset,as well as a TCM lung cancer KG.The KG2TRAG method was applied to enhance the knowledge retrieval,which can convert KG triples into natural language text via ChatGPT-aided linearization,leveraging large language models(LLMs)for context-aware reasoning.For a comprehensive comparison,MedicalGPT,HuatuoGPT,and BenTsao were selected as the baseline models.Performance was evaluated using bilingual evaluation understudy(BLEU),recall-oriented understudy for gisting evaluation(ROUGE),accuracy,and the domain-specific TCM-LCEval metrics,with validation from TCM oncology experts assessing answer accuracy,professionalism,and usability.Results The TCMLCM model achieved the optimal performance across all metrics,including a BLEU score of 32.15%,ROUGE-L of 59.08%,and an accuracy rate of 79.68%.Notably,in the TCM-LCEval assessment specific to the field of TCM,its performance was 3%−12%higher than that of the baseline model.Expert evaluations highlighted superior performance in accuracy and professionalism.Conclusion TCMLCM can provide an innovative solution for TCM lung cancer QA,demonstrating the feasibility of integrating structured KGs with LLMs.This work advances intelligent TCM healthcare tools and lays a foundation for future AI-driven applications in traditional medicine.
基金supported by National Natural Science Foundation of China(22478239)Science and Technology Commission of Shanghai Municipality(19DZ2271100)National Natural Science Foundation of China(22208208)。
文摘To ensure the safe operation of batteries,accurately obtaining key internal state parameters is essential.However,traditional parameter measurement methods either require opening the battery or long-term measurements,which are impractical.Therefore,the fixed values are commonly used for these parameters in electrochemical models and have significant limitations.To overcome these limitations,this paper proposes a deep neural network(DNN)based data-driven evaluation method to determine model parameters.By coupling an improved one-dimensional isothermal pseudo-twodimensional(P2D)model with DNN,this study identified concentration-dependent parameters through detailed discharge curve analysis.The results show that the data-driven method can effectively obtain the change trend of concentration-dependent parameters through the charge and discharge curve,and the method can be extended to different battery systems in different discharge rates and aging applications.This work is expected to provide new parameter selection insights for data-driven battery prediction and monitoring models.
