Sesquiterpanes are ubiquitous components of crude oils and ancient sediments.Liquid saturated hydrocarbons from simulated pyrolysis experiments on immature organic-rich mudstone collected from the Lower Cretaceous Hes...Sesquiterpanes are ubiquitous components of crude oils and ancient sediments.Liquid saturated hydrocarbons from simulated pyrolysis experiments on immature organic-rich mudstone collected from the Lower Cretaceous Hesigewula Sag were analyzed by gas chromatography-mass spectrometry(GC-MS).C14 bicyclic sesquiterpanes,namely,8β(H)-drimane,8β(H)-homodrimane,and 8 a(H)-homodrimane were detected and identified on basis of their diagnostic fragment ions(m/z123,179,193,and 207),and previously published mass spectra data,and these bicyclic sesquiterpanes presented relatively regular characteristics in their thermal evolution.The ratios 8β(H)-drimane/8β(H)-homodrimane,8β(H)-homodrimane/8 a(H)-homodrimane,and 8β(H)-drimane/8 a(H)-homodrimane all show a clear upward trend with increasing temperature below the temperature turning point.Thus,all these ratios can be used as evolution indexes of source rocks in the immature-lowmaturity stage.However,the last two ratios may be more suitable than the first ratio as valid parameters for measuring the extent of thermal evolution of organic matter in the immature-low-maturity stage because their change amplitude with increasing temperature is more obvious.展开更多
Detailed research on China's CO_(2) emission pathway of the 2030 peak and 2060 carbon neutrality goals is fundamental to promote China's climate change action.Previous studies on emission pathways have been ba...Detailed research on China's CO_(2) emission pathway of the 2030 peak and 2060 carbon neutrality goals is fundamental to promote China's climate change action.Previous studies on emission pathways have been based on long-term emission data or model analyses.However,few studies have achieved synergy and pathway optimization at both the micro and macro levels or focused on China's 2060 carbon neutrality goal,making it difficult to support the systematic management of national and regional emission pathways.In this study,we developed an integrated CO_(2) emission pathway model,the Chinese Academy of Environmental Planning Carbon Pathways 1.2 model,under China's climate change goals.Our pathway coupled the top-down and bottom-up approaches and conducted optimization analysis under social fairness and optimal cost conditions.The results provide a clear CO_(2) emission pathway and offer insights for implementing fine management of CO_(2) emissions at the national,regional,sectoral,and spatial gridded levels.展开更多
The accurate and rapid prediction of materials’physical properties,such as thermal transport and mechanical properties,are of particular importance for potential applications of featuring novel materials.We demonstra...The accurate and rapid prediction of materials’physical properties,such as thermal transport and mechanical properties,are of particular importance for potential applications of featuring novel materials.We demonstrate,using graphene as an example,how machine learning potential,combined with the Boltzmann transport equation and molecular dynamics simulations,can simultaneously provide an accurate prediction of multiple-target physical properties,with an accuracy comparable to that of density functional theory calculation and/or experimental measurements.Benchmarked quantities include the Grüneisen parameter,the thermal expansion coefficient,Young’s modulus,Poisson’s ratio,and thermal conductivity.Moreover,the transferability of commonly used empirical potential in predicting multiple-target physical properties is also examined.Our study suggests that atomic simulation,in conjunction with machine learning potential,represents a promising method of exploring the various physical properties of novel materials.展开更多
Photoluminescence（PL） measurements are carried out to investigate the degradation of GaInP top cell and GaAs middle cell for GaInP/GaAs/Ge triple-junction solar cells irradiated with 1.0, 1.8 and 11.5 MeV electrons ...Photoluminescence（PL） measurements are carried out to investigate the degradation of GaInP top cell and GaAs middle cell for GaInP/GaAs/Ge triple-junction solar cells irradiated with 1.0, 1.8 and 11.5 MeV electrons with fluences ranging up to 3 × 10^15, 1 × 10^15 and 3 × 10^14 cm^-2, respectively. The degradation rates of PL intensity increase with the electron fluence and energy. Furthermore, the damage coefficient of minority carrier diffusion length is estimated by the PL radiative efficiency. The damage coefficient increases with the electron energy. The relation of damage coefficient to electron energy is discussed with the non-ionizing energy loss（NIEL）, which shows a quadratic dependence between damage coefficient and NIEL.展开更多
The pyrolysis parameter S1,which indicates the amount of free hydrocarbons present in shale,is often underestimated due to hydrocarbon loss during sample handling and measurement processes.To remedy this issue,we stro...The pyrolysis parameter S1,which indicates the amount of free hydrocarbons present in shale,is often underestimated due to hydrocarbon loss during sample handling and measurement processes.To remedy this issue,we strongly recommend an immediate three-step hydrocarbon thermal desorption(HTD)approach to be conducted on oil shale at the drilling site.This approach measures S_(g),S_(O),and S_(1)^(*),which refer to gaseous,light,and free hydrocarbons,respectively.The new shale oil content value,calculated from the total of these three parameters,is far more precise and reliable than traditional pyrolysis S1.Moreover,we thoroughly investigated the components and microscopic occurrence features of hydrocarbons thermally desorbed at three temperature stages using gas chromatography(GC)and X-ray microcomputed tomography(CT).For example,we selected Chang 7_(3)mud shale.Our experimental results irrefutably indicate that the ultimate shale oil content of poor resource rocks is significantly impacted by evaporative loss,with this effect being greater when the total organic carbon(TOC)is lower.Additionally,C_(1-5)and C_(1-7)hydrocarbons constitute almost all of S_(g)and S_(O),respectively.S_(g)and S_(O)are predominantly composed of C_(1-3)gaseous hydrocarbons,with a maximum proportion of 42.93%.In contrast,S_(1)^(*)contains a substantial amount of C_(16-31)hydrocarbons.A three-dimensional reconstruction model of an X-ray micro-CT scan shows that while the amount of shale organic matter greatly decreases from the frozen state to 300℃,the pore volume significantly increases,particularly between 90 and 300℃.The increased pore volume is mainly due to macropores and fractures.It is imperative to note that the shale oil triple-division boundaries must be adjusted based on more accurate oil content,although this would not affect the resource zones to which the samples already belong(ineffective,low-efficient,and enriched resources).In conclusion,we strongly advise conducting an immediate well-site analysis or utilizing preservation procedures,such as deep freezing or plastic film wrapping followed by core waxing,to minimize volatile loss.展开更多
This paper aims to evaluate the cost of environmental degradation by adopting the conventional environmental economic methodology in China from 2004 to 2017 and summarize the change in both the causes and costs of Ch...This paper aims to evaluate the cost of environmental degradation by adopting the conventional environmental economic methodology in China from 2004 to 2017 and summarize the change in both the causes and costs of China’s environmental degradation.Results from this study revealed the following:i.The environmental degradation cost in China increased from 511 billion yuan to 1,892 billion yuan from 2004 to 2017,and its share in the GDP decreased from 3.05% to 2.23%;ii.The environmental degradation cost growth rate was lower than the GDP growth rate.The environmental degradation cost growth rate decreased sharply,by dropping from 10% in 2014 to 2% in 2017.The environmental benefits of industrial transformation have emerged;iii.The provinces of Shandong,Hebei,Jiangsu,Henan,and Guangdong had the highest environmental degradation costs.The annual average growth rate of the environmental degradation costs in Jiangsu,Guangdong,and Zhejiang were lower than their growth rate of the GDP respectively;iv.Consideration of environmental degradation cost in decision-making could contribute to the high-quality development of China.展开更多
Based on the Weather Research and Forecasting model and the Models-3 community multi-scale air quality model(WRF-CMAQ),this study analyzes the impacts of meteorological conditions and changes in air pollutant emission...Based on the Weather Research and Forecasting model and the Models-3 community multi-scale air quality model(WRF-CMAQ),this study analyzes the impacts of meteorological conditions and changes in air pollutant emissions on the heavy air pollution episode occurred over North China around the 2020 Spring Festival(January to Februray 2020).Regional reductions in air pollutant emissions required to eliminate the PM2.5 heavy pollution episode are also quantified.Our results found that meteorological conditions for the Beijing-Tianjin-Hebei and surrounding"2+26"cities are the worst during the heavy pollution episode around the 2020 Spring Festival as compared with two other typical heavy pollution episodes that occurred after 2015.However,because of the substantial reductions in air pollutant emissions in the"2+26"cities in recent years,and the32%extra reduction in emissions during January to February 2020 compared with the baseline emission levels of the autumn and winter of 2019 to 2020,the maximum PM2.5 level during this heavy pollution episode around the 2020 Spring Festival was much lower than that in the other two typical episodes.Yet,these emission reductions are still not enough to eliminate regional heavy pollution episodes.Compared with the actual emission levels during January to February 2020,a 20%extra reduction in air pollutant emissions in the"2+26"cities(or a 45%extra reduction compared with baseline emission levels of the autumn and winter of 2019 to 2020)could help to generally eliminate regionwide severe pollution episodes,and avoid heavy pollution episodes that last three or more consecutive days in Beijing;a 40%extra reduction in emissions(or a 60%extra reduction compared with baseline emission levels of the autumn and winter of 2019 to 2020)could help to generally eliminate regionwide and continuous heavy pollution episodes.Our analysis finds that during the clean period after the heavy pollution episode around the 2020 Spring Festival,the regionwide heavy pollution episode would only occur with at least a 10-fold increase in air pollutant emissions.展开更多
Traditional simulation methods have made prominent progress in aiding experiments for understanding thermal transport properties of materials,and in predicting thermal conductivity of novel materials.However,huge chal...Traditional simulation methods have made prominent progress in aiding experiments for understanding thermal transport properties of materials,and in predicting thermal conductivity of novel materials.However,huge challenges are also encountered when exploring complex material systems,such as formidable computational costs.As a rising computational method,machine learning has a lot to offer in this regard,not only in speeding up the searching and optimization process,but also in providing novel perspectives.In this work,we review the state-of-the-art studies on material’s thermal properties based on machine learning technique.First,the basic principles of machine learning method are introduced.We then review applications of machine learning technique in the prediction and optimization of material’s thermal properties,including thermal conductivity and interfacial thermal resistance.Finally,an outlook is provided for the future studies.展开更多
基金supported by the National Natural Science Foundation of China (Grant Nos. 41672117 and 41503034)the Hubei Provincial Natural Science Foundation of China (Project No. 2017CFA027)+1 种基金the Open Subject of Shandong Provincial Key Laboratory of Depositional Mineralization & Sedimentary Mineral (Baojun Liu Geoscience Science Foundation) (DMSM2017084)the Open Subject of the State Key Laboratory of Petroleum Resources and Prospecting (PRP/open-1509)
文摘Sesquiterpanes are ubiquitous components of crude oils and ancient sediments.Liquid saturated hydrocarbons from simulated pyrolysis experiments on immature organic-rich mudstone collected from the Lower Cretaceous Hesigewula Sag were analyzed by gas chromatography-mass spectrometry(GC-MS).C14 bicyclic sesquiterpanes,namely,8β(H)-drimane,8β(H)-homodrimane,and 8 a(H)-homodrimane were detected and identified on basis of their diagnostic fragment ions(m/z123,179,193,and 207),and previously published mass spectra data,and these bicyclic sesquiterpanes presented relatively regular characteristics in their thermal evolution.The ratios 8β(H)-drimane/8β(H)-homodrimane,8β(H)-homodrimane/8 a(H)-homodrimane,and 8β(H)-drimane/8 a(H)-homodrimane all show a clear upward trend with increasing temperature below the temperature turning point.Thus,all these ratios can be used as evolution indexes of source rocks in the immature-lowmaturity stage.However,the last two ratios may be more suitable than the first ratio as valid parameters for measuring the extent of thermal evolution of organic matter in the immature-low-maturity stage because their change amplitude with increasing temperature is more obvious.
基金The research was funded by the project“An Emission Scenario Air Quality Model Based Study on the Evaluation of‘Dual Attainments’of Chinese City”[Grant number.72074154],supported by the National Natural Science Foundation of China.
文摘Detailed research on China's CO_(2) emission pathway of the 2030 peak and 2060 carbon neutrality goals is fundamental to promote China's climate change action.Previous studies on emission pathways have been based on long-term emission data or model analyses.However,few studies have achieved synergy and pathway optimization at both the micro and macro levels or focused on China's 2060 carbon neutrality goal,making it difficult to support the systematic management of national and regional emission pathways.In this study,we developed an integrated CO_(2) emission pathway model,the Chinese Academy of Environmental Planning Carbon Pathways 1.2 model,under China's climate change goals.Our pathway coupled the top-down and bottom-up approaches and conducted optimization analysis under social fairness and optimal cost conditions.The results provide a clear CO_(2) emission pathway and offer insights for implementing fine management of CO_(2) emissions at the national,regional,sectoral,and spatial gridded levels.
基金the National Natural Science Foundation of China(Grant Nos.12075168 and 11890703)the Science and Technology Commission of Shanghai Municipality(Grant Nos.19ZR1478600,18ZR1442000 and 18JC1410900)+1 种基金the Fundamental Research Funds for the Central Universities(Grant No.22120200069)the Open Fund of Hunan Provincial Key Laboratory of Advanced Materials for New Energy Storage and Conversion(Grant No.2018TP1037_201901)。
文摘The accurate and rapid prediction of materials’physical properties,such as thermal transport and mechanical properties,are of particular importance for potential applications of featuring novel materials.We demonstrate,using graphene as an example,how machine learning potential,combined with the Boltzmann transport equation and molecular dynamics simulations,can simultaneously provide an accurate prediction of multiple-target physical properties,with an accuracy comparable to that of density functional theory calculation and/or experimental measurements.Benchmarked quantities include the Grüneisen parameter,the thermal expansion coefficient,Young’s modulus,Poisson’s ratio,and thermal conductivity.Moreover,the transferability of commonly used empirical potential in predicting multiple-target physical properties is also examined.Our study suggests that atomic simulation,in conjunction with machine learning potential,represents a promising method of exploring the various physical properties of novel materials.
基金Supported by the National Natural Science Foundation of China under Grant Nos 11675020,11375028,11075018 and 10675023
文摘Photoluminescence（PL） measurements are carried out to investigate the degradation of GaInP top cell and GaAs middle cell for GaInP/GaAs/Ge triple-junction solar cells irradiated with 1.0, 1.8 and 11.5 MeV electrons with fluences ranging up to 3 × 10^15, 1 × 10^15 and 3 × 10^14 cm^-2, respectively. The degradation rates of PL intensity increase with the electron fluence and energy. Furthermore, the damage coefficient of minority carrier diffusion length is estimated by the PL radiative efficiency. The damage coefficient increases with the electron energy. The relation of damage coefficient to electron energy is discussed with the non-ionizing energy loss（NIEL）, which shows a quadratic dependence between damage coefficient and NIEL.
基金This study is financially supported by the National Natural Science Foundation of China(Grant Number 41972122,42172139 and 42072186)the China Scholarship Council(CSC),the Open Foundation of Cooperative Innovation Center of Uncon-ventional Oil and Gas,Yangtze University(Ministry of Education&Hubei Province)(Grant Number UOGBX 2022-03)Petro-China Innovation Found(No.2020D-5007-0101)。
文摘The pyrolysis parameter S1,which indicates the amount of free hydrocarbons present in shale,is often underestimated due to hydrocarbon loss during sample handling and measurement processes.To remedy this issue,we strongly recommend an immediate three-step hydrocarbon thermal desorption(HTD)approach to be conducted on oil shale at the drilling site.This approach measures S_(g),S_(O),and S_(1)^(*),which refer to gaseous,light,and free hydrocarbons,respectively.The new shale oil content value,calculated from the total of these three parameters,is far more precise and reliable than traditional pyrolysis S1.Moreover,we thoroughly investigated the components and microscopic occurrence features of hydrocarbons thermally desorbed at three temperature stages using gas chromatography(GC)and X-ray microcomputed tomography(CT).For example,we selected Chang 7_(3)mud shale.Our experimental results irrefutably indicate that the ultimate shale oil content of poor resource rocks is significantly impacted by evaporative loss,with this effect being greater when the total organic carbon(TOC)is lower.Additionally,C_(1-5)and C_(1-7)hydrocarbons constitute almost all of S_(g)and S_(O),respectively.S_(g)and S_(O)are predominantly composed of C_(1-3)gaseous hydrocarbons,with a maximum proportion of 42.93%.In contrast,S_(1)^(*)contains a substantial amount of C_(16-31)hydrocarbons.A three-dimensional reconstruction model of an X-ray micro-CT scan shows that while the amount of shale organic matter greatly decreases from the frozen state to 300℃,the pore volume significantly increases,particularly between 90 and 300℃.The increased pore volume is mainly due to macropores and fractures.It is imperative to note that the shale oil triple-division boundaries must be adjusted based on more accurate oil content,although this would not affect the resource zones to which the samples already belong(ineffective,low-efficient,and enriched resources).In conclusion,we strongly advise conducting an immediate well-site analysis or utilizing preservation procedures,such as deep freezing or plastic film wrapping followed by core waxing,to minimize volatile loss.
基金Supported by National Key Research and Development Program of China(No.2016YFC0207605)Ministry of Ecology and Environment Financial Program of China(No.2110105).
文摘This paper aims to evaluate the cost of environmental degradation by adopting the conventional environmental economic methodology in China from 2004 to 2017 and summarize the change in both the causes and costs of China’s environmental degradation.Results from this study revealed the following:i.The environmental degradation cost in China increased from 511 billion yuan to 1,892 billion yuan from 2004 to 2017,and its share in the GDP decreased from 3.05% to 2.23%;ii.The environmental degradation cost growth rate was lower than the GDP growth rate.The environmental degradation cost growth rate decreased sharply,by dropping from 10% in 2014 to 2% in 2017.The environmental benefits of industrial transformation have emerged;iii.The provinces of Shandong,Hebei,Jiangsu,Henan,and Guangdong had the highest environmental degradation costs.The annual average growth rate of the environmental degradation costs in Jiangsu,Guangdong,and Zhejiang were lower than their growth rate of the GDP respectively;iv.Consideration of environmental degradation cost in decision-making could contribute to the high-quality development of China.
基金supported by the National Key Research and Development Program(Grant Nos.2016YFC0207502,2016YFC0208805)the National Research Program for Key Issues in Air Pollution Control(Grant No.DQGG0302)。
文摘Based on the Weather Research and Forecasting model and the Models-3 community multi-scale air quality model(WRF-CMAQ),this study analyzes the impacts of meteorological conditions and changes in air pollutant emissions on the heavy air pollution episode occurred over North China around the 2020 Spring Festival(January to Februray 2020).Regional reductions in air pollutant emissions required to eliminate the PM2.5 heavy pollution episode are also quantified.Our results found that meteorological conditions for the Beijing-Tianjin-Hebei and surrounding"2+26"cities are the worst during the heavy pollution episode around the 2020 Spring Festival as compared with two other typical heavy pollution episodes that occurred after 2015.However,because of the substantial reductions in air pollutant emissions in the"2+26"cities in recent years,and the32%extra reduction in emissions during January to February 2020 compared with the baseline emission levels of the autumn and winter of 2019 to 2020,the maximum PM2.5 level during this heavy pollution episode around the 2020 Spring Festival was much lower than that in the other two typical episodes.Yet,these emission reductions are still not enough to eliminate regional heavy pollution episodes.Compared with the actual emission levels during January to February 2020,a 20%extra reduction in air pollutant emissions in the"2+26"cities(or a 45%extra reduction compared with baseline emission levels of the autumn and winter of 2019 to 2020)could help to generally eliminate regionwide severe pollution episodes,and avoid heavy pollution episodes that last three or more consecutive days in Beijing;a 40%extra reduction in emissions(or a 60%extra reduction compared with baseline emission levels of the autumn and winter of 2019 to 2020)could help to generally eliminate regionwide and continuous heavy pollution episodes.Our analysis finds that during the clean period after the heavy pollution episode around the 2020 Spring Festival,the regionwide heavy pollution episode would only occur with at least a 10-fold increase in air pollutant emissions.
基金the grants from the National Natural Science Foundation of China(Grant Nos.12075168 and 11890703)the National Key Research and Development Program of China(Grant No.2017YFB0406000)+2 种基金Science and Technology Commission of Shanghai Municipality(Grant Nos.19ZR1478600,18JC1410900,and 18ZR1442000)the Fundamental Research Funds for the Central Universities(Grant No.22120200069)Open Fund of Hunan Provincial Key Labora tory of Advanced Materials for New Energy Storage and Conversion(Grant No.2018TP1037_201901).
文摘Traditional simulation methods have made prominent progress in aiding experiments for understanding thermal transport properties of materials,and in predicting thermal conductivity of novel materials.However,huge challenges are also encountered when exploring complex material systems,such as formidable computational costs.As a rising computational method,machine learning has a lot to offer in this regard,not only in speeding up the searching and optimization process,but also in providing novel perspectives.In this work,we review the state-of-the-art studies on material’s thermal properties based on machine learning technique.First,the basic principles of machine learning method are introduced.We then review applications of machine learning technique in the prediction and optimization of material’s thermal properties,including thermal conductivity and interfacial thermal resistance.Finally,an outlook is provided for the future studies.
