Selective hydrogenation of 1,3‐butadiene is an essential process in the upgrading of the crude C4 cut from the petroleum chemical sector.Catalyst design is crucial to achieve a virtually alkadiene‐free product while...Selective hydrogenation of 1,3‐butadiene is an essential process in the upgrading of the crude C4 cut from the petroleum chemical sector.Catalyst design is crucial to achieve a virtually alkadiene‐free product while avoiding over‐hydrogenating valuable olefins.In addition to the great industrial relevance,this demanding selectivity pattern renders 1,3‐butadiene hydrogenation a widely used model reaction to discriminate selective hydrogenation catalysts in academia.Nonetheless,critical reviews on the catalyst development are extremely lacking in literature.In this review,we aim to provide the reader an in‐depth overview of different catalyst families,particularly the precious metal‐based monometallic catalysts(Pd,Pt,and Au),developed in the last half century.The emphasis is placed on the development of new strategies to design high‐performance architectures,the establishment of structure‐performance relationships,and the reaction and deactivation mechanisms.Thrilling directions for future optimization of catalyst formulations and engineering aspect are also provided.展开更多
Threshold pressure gradient has great importance in efficient tight gas field development as well as for research and laboratory experiments.This experimental study is carried out to investigate the threshold pressure...Threshold pressure gradient has great importance in efficient tight gas field development as well as for research and laboratory experiments.This experimental study is carried out to investigate the threshold pressure gradient in detail.Experiments are carried out with and without back pressure so that the effect of pore pressure on threshold pressure gradient may be observed.The trend of increasing or decreasing the threshold pressure gradient is totally opposite in the cases of considering and not considering the pore pressure.The results demonstrate that the pore pressure of tight gas reservoirs has great influence on threshold pressure gradient.The effects of other parameters like permeability and water saturation,in the presence of pore pressure,on threshold pressure gradient are also examined which show that the threshold pressure gradient increases with either a decrease in permeability or an increase in water saturation.Two new correlations of threshold pressure gradient on the basis of pore pressure and permeability,and pore pressure and water saturation,are also introduced.Based on these equations,new models for tight gas production are proposed.The gas slip correction factor is also considered during derivation of this proposed tight gas production models.Inflow performance relationship curves based on these proposed models show that production rates and absolute open flow potential are always be overestimated while ignoring the threshold pressure gradients.展开更多
Identification of the catalyst characteristics correlating with the key performance parameters including selectivity and stability is key to the rational catalyst design. Herein we focused on the identification of pro...Identification of the catalyst characteristics correlating with the key performance parameters including selectivity and stability is key to the rational catalyst design. Herein we focused on the identification of property-performance relationships in the methanol-to-olefin(MTO) process by studying in detail the catalytic behaviour of MFI, MEL and their respective intergrowth zeolites. The detailed material characterization reveals that both the high production of propylene and butylenes and the large Me OH conversion capacity correlate with the enrichment of lattice Al sites in the channels of the pentasil structure as identified by 27 Al MAS NMR and 3-methylpentane cracking results. The lack of correlation between MTO performance and other catalyst characteristics, such as crystal size, presence of external Brønsted acid sites and Al pairing suggests their less pronounced role in defining the propylene selectivity. Our analysis reveals that catalyst deactivation is rather complex and is strongly affected by the enrichment of lattice Al in the intersections, the overall Al-content, and crystal size. The intergrowth of MFI and MEL phases accelerates the catalyst deactivation rate.展开更多
To enhance students＇ all-around development and personal potential is the main purpose that teachers want to obtain in their teachings. The author believes that it can be achieved only in a relaxed and safe class atm...To enhance students＇ all-around development and personal potential is the main purpose that teachers want to obtain in their teachings. The author believes that it can be achieved only in a relaxed and safe class atmosphere. The article introduces the humanistic psychology and illustrates how to apply humanistic psychology to the foreign language class and establish an effective emotional class climate in China.展开更多
The advancement of hydrogen-based energy systems necessitates innovative solutions for safe,efficient hydrogen storage and transportation.Liquid organic hydrogen carriers(LOHCs)emerge as a transformative technology by...The advancement of hydrogen-based energy systems necessitates innovative solutions for safe,efficient hydrogen storage and transportation.Liquid organic hydrogen carriers(LOHCs)emerge as a transformative technology by combining high hydrogen capacity,excellent stability,and seamless integration with existing fuel infrastructure,enabling large-scale,long-distance hydrogen logistics.Despite these merits,challenges in dehydrogenation kinetics and catalyst instability impede practical deployment.Herein,we present a comprehensive mechanistic review of dehydrogenation pathways across diverse LOHC platforms,including cyclohexane,methylcyclohexane,decalin,dodecahydro-N-ethylcarbazole,perhydro-dibenzyltoluene/benzyltoluene,bicyclohexyl,and indole-based LOHCs.Compared with previous reviews,this study integrates geometric and electronic effects across multiple LOHC systems to identify cross-cutting structure-activity principles.Building on this framework,it further reveals reactant-dependent rules for active-site regulation,where the molecular architecture of hydrogen carriers critically determines the required catalyst characteristics.This perspective establishes a unified framework that links molecular descriptors to coordination-specific active sites,thereby advancing precision catalyst design for next-generation LOHC technologies.展开更多
The rational design of organic functional devices relies on understanding structure-propertyperformance relationships through multi-scale characterization.However,traditional characterizations are costly and require m...The rational design of organic functional devices relies on understanding structure-propertyperformance relationships through multi-scale characterization.However,traditional characterizations are costly and require multidisciplinary expertise.Here we present OCNet,a domain-knowledge-enhanced representation learning framework that,for the first time,enables unified virtual characterization from molecules to devices.Pre-trained on over ten million selfgenerated conjugated molecules and dimers,OCNet learns generalizable microscopic representations comparable to expert-crafted features.As a result,it surpasses state-of-the-art models by over 20%in predicting key computed and experimental molecular optoelectronic properties.OCNet further provides the first transferable model for predicting transfer integrals in thin films,enabling accurate mesoscale carrier mobility estimation via multiscale simulations.By integrating tight-binding-level electronic descriptors,OCNet achieves near real-time,accurate prediction of device power conversion efficiency.Together,OCNet offers a unified and scalable foundation for virtual characterization of organic materials across multiple scales,with broad applicability in photovoltaics,displays,and sensing.展开更多
Electrocatalysis plays an essential role in sustainable energy conversion technologies such as fuel cells,water electrolysis,and the carbon dioxide reduction reaction that occurs at solid–liquid interfaces.However,du...Electrocatalysis plays an essential role in sustainable energy conversion technologies such as fuel cells,water electrolysis,and the carbon dioxide reduction reaction that occurs at solid–liquid interfaces.However,due to the complexity of the respective electrochemical interfaces and trace amounts of interfacial species,researchers’knowledge of these reaction mechanisms remains incomplete,limiting our ability to improve electrocatalytic performance.In situ electrochemical surface-enhanced Raman spectroscopy(EC-SERS)has proven to have appealing potential for the study of electrocatalytic reaction mechanisms because it can provide exceptionally sensitive fingerprint vibrational spectroscopic information about interfacial species and their interactions.This review offers insights into electrocatalysis through in situ EC-SERS.We begin with an introduction to the basic principles,substrate engineering,and the implementation of in situ EC-SERS for electrocatalysis,with an emphasis on capturing trace interfacial species and determining the capability of this technique.We then discuss fundamentals,still-debated mechanistic issues,as well as advanced applications of EC-SERS for mechanism studies of the fundamentally and practically important reactions in sustainable energy conversion technologies,to gain insights into electrocatalysis.Finally,we propose directions for the future development of in situ EC-SERS in catalysis.Through this review paper,we aim to attract greater attention to the use of in situ EC-SERS in catalysis studies and introduce versatile methodologies and techniques for catalytic studies that will result in superior performance.展开更多
To enhance the power conversion efficiency(PCE)of organic photovoltaic(OPV)cells,the identification of high-performance polymer/macromolecule materials and understanding their relationship with photovoltaic performanc...To enhance the power conversion efficiency(PCE)of organic photovoltaic(OPV)cells,the identification of high-performance polymer/macromolecule materials and understanding their relationship with photovoltaic performance before synthesis are critical objectives.In this study,we developed five algorithms using a dataset of 1343 experimentally validated OPV NFA acceptor materials.The random forest(RF)algorithm exhibited the best predictive performance for material design and screening.Additionally,we explored a newly developed polymer/macromolecule structure expression,polymer-unit fingerprint(PUFp),which outperformed the molecular access system(MACCS)across diverse machine learning(ML)algorithms.PUFp facilitated the interpretability of structure-property relationships,enabling PCE predictions of conjugated polymers/macromolecules formed by the combination of donor(D)and acceptor(A)units.Our PUFp-ML model efficiently preevaluated and classified numerous acceptor materials,identifying and screening the two most promising NFA candidates.The proposed framework demonstrates the ability to design novel materials based on PUFp-ML-established feature/substructure-property relationships,providing rational design guidelines for developing high-performanceOPV acceptors.These methodologies are transferable to donor materials,thereby supporting accelerated material discovery and offering insights for designing innovative OPV materials.展开更多
基金supported by Zhejiang Normal University (YS304320035, YS304320036)
文摘Selective hydrogenation of 1,3‐butadiene is an essential process in the upgrading of the crude C4 cut from the petroleum chemical sector.Catalyst design is crucial to achieve a virtually alkadiene‐free product while avoiding over‐hydrogenating valuable olefins.In addition to the great industrial relevance,this demanding selectivity pattern renders 1,3‐butadiene hydrogenation a widely used model reaction to discriminate selective hydrogenation catalysts in academia.Nonetheless,critical reviews on the catalyst development are extremely lacking in literature.In this review,we aim to provide the reader an in‐depth overview of different catalyst families,particularly the precious metal‐based monometallic catalysts(Pd,Pt,and Au),developed in the last half century.The emphasis is placed on the development of new strategies to design high‐performance architectures,the establishment of structure‐performance relationships,and the reaction and deactivation mechanisms.Thrilling directions for future optimization of catalyst formulations and engineering aspect are also provided.
基金supported by the National Science Foundation(51674279,51804328)Major National Science and Technology Project(2017ZX05009-001,2017ZX05069,2017ZX05072)+4 种基金Shandong Province Key Research and Development Program(2018GSF116004)Shandong Province Natural Science Foundation(ZR2018BEE008,ZR2018BEE018)Fundamental Research Funds for the Central Universities(18CX02168A)China Postdoctoral Science Foundation(2018M630813)Postdoctoral Applied Research Project Foundation of Qingdao city(BY201802003)。
文摘Threshold pressure gradient has great importance in efficient tight gas field development as well as for research and laboratory experiments.This experimental study is carried out to investigate the threshold pressure gradient in detail.Experiments are carried out with and without back pressure so that the effect of pore pressure on threshold pressure gradient may be observed.The trend of increasing or decreasing the threshold pressure gradient is totally opposite in the cases of considering and not considering the pore pressure.The results demonstrate that the pore pressure of tight gas reservoirs has great influence on threshold pressure gradient.The effects of other parameters like permeability and water saturation,in the presence of pore pressure,on threshold pressure gradient are also examined which show that the threshold pressure gradient increases with either a decrease in permeability or an increase in water saturation.Two new correlations of threshold pressure gradient on the basis of pore pressure and permeability,and pore pressure and water saturation,are also introduced.Based on these equations,new models for tight gas production are proposed.The gas slip correction factor is also considered during derivation of this proposed tight gas production models.Inflow performance relationship curves based on these proposed models show that production rates and absolute open flow potential are always be overestimated while ignoring the threshold pressure gradients.
基金supported by the BASF and the Advanced Research Center Chemical Building Blocks Consortium (ARC CBBC) for Funding under Project (2016.007.TUD)
文摘Identification of the catalyst characteristics correlating with the key performance parameters including selectivity and stability is key to the rational catalyst design. Herein we focused on the identification of property-performance relationships in the methanol-to-olefin(MTO) process by studying in detail the catalytic behaviour of MFI, MEL and their respective intergrowth zeolites. The detailed material characterization reveals that both the high production of propylene and butylenes and the large Me OH conversion capacity correlate with the enrichment of lattice Al sites in the channels of the pentasil structure as identified by 27 Al MAS NMR and 3-methylpentane cracking results. The lack of correlation between MTO performance and other catalyst characteristics, such as crystal size, presence of external Brønsted acid sites and Al pairing suggests their less pronounced role in defining the propylene selectivity. Our analysis reveals that catalyst deactivation is rather complex and is strongly affected by the enrichment of lattice Al in the intersections, the overall Al-content, and crystal size. The intergrowth of MFI and MEL phases accelerates the catalyst deactivation rate.
文摘To enhance students＇ all-around development and personal potential is the main purpose that teachers want to obtain in their teachings. The author believes that it can be achieved only in a relaxed and safe class atmosphere. The article introduces the humanistic psychology and illustrates how to apply humanistic psychology to the foreign language class and establish an effective emotional class climate in China.
基金partially supported by the National Natural Science Foundation of China(No.22208374,22578497,22478419)the Excellent Youth Scientist Award Foundation of Shandong Province(No.ZR2024YQ009)+2 种基金the Distinguished Young Scholars of the National Natural Science Foundation of China(No.22322814)CNPC Innovation Found(2022DQ02-0607)Foundation of Hubei Key Laboratory of Processing and Application of Catalytic Materials(No.202441504)。
文摘The advancement of hydrogen-based energy systems necessitates innovative solutions for safe,efficient hydrogen storage and transportation.Liquid organic hydrogen carriers(LOHCs)emerge as a transformative technology by combining high hydrogen capacity,excellent stability,and seamless integration with existing fuel infrastructure,enabling large-scale,long-distance hydrogen logistics.Despite these merits,challenges in dehydrogenation kinetics and catalyst instability impede practical deployment.Herein,we present a comprehensive mechanistic review of dehydrogenation pathways across diverse LOHC platforms,including cyclohexane,methylcyclohexane,decalin,dodecahydro-N-ethylcarbazole,perhydro-dibenzyltoluene/benzyltoluene,bicyclohexyl,and indole-based LOHCs.Compared with previous reviews,this study integrates geometric and electronic effects across multiple LOHC systems to identify cross-cutting structure-activity principles.Building on this framework,it further reveals reactant-dependent rules for active-site regulation,where the molecular architecture of hydrogen carriers critically determines the required catalyst characteristics.This perspective establishes a unified framework that links molecular descriptors to coordination-specific active sites,thereby advancing precision catalyst design for next-generation LOHC technologies.
基金supported in part by NSFC’s Major Research Project 92270001Z.Z.’s work is supported in part by the Beijing Nova Program(20250484934).
文摘The rational design of organic functional devices relies on understanding structure-propertyperformance relationships through multi-scale characterization.However,traditional characterizations are costly and require multidisciplinary expertise.Here we present OCNet,a domain-knowledge-enhanced representation learning framework that,for the first time,enables unified virtual characterization from molecules to devices.Pre-trained on over ten million selfgenerated conjugated molecules and dimers,OCNet learns generalizable microscopic representations comparable to expert-crafted features.As a result,it surpasses state-of-the-art models by over 20%in predicting key computed and experimental molecular optoelectronic properties.OCNet further provides the first transferable model for predicting transfer integrals in thin films,enabling accurate mesoscale carrier mobility estimation via multiscale simulations.By integrating tight-binding-level electronic descriptors,OCNet achieves near real-time,accurate prediction of device power conversion efficiency.Together,OCNet offers a unified and scalable foundation for virtual characterization of organic materials across multiple scales,with broad applicability in photovoltaics,displays,and sensing.
基金supported by the National Natural Science Foundation of China(22574071,22472074,22272069,T2293692,22074058,22021001,and 21925404)the Natural Science Foundation of Fujian Province,China(2023H01010004 and 2021J01988)the XMIREM autonomously deployment project,China(2023CX10 and 2023GG01).
文摘Electrocatalysis plays an essential role in sustainable energy conversion technologies such as fuel cells,water electrolysis,and the carbon dioxide reduction reaction that occurs at solid–liquid interfaces.However,due to the complexity of the respective electrochemical interfaces and trace amounts of interfacial species,researchers’knowledge of these reaction mechanisms remains incomplete,limiting our ability to improve electrocatalytic performance.In situ electrochemical surface-enhanced Raman spectroscopy(EC-SERS)has proven to have appealing potential for the study of electrocatalytic reaction mechanisms because it can provide exceptionally sensitive fingerprint vibrational spectroscopic information about interfacial species and their interactions.This review offers insights into electrocatalysis through in situ EC-SERS.We begin with an introduction to the basic principles,substrate engineering,and the implementation of in situ EC-SERS for electrocatalysis,with an emphasis on capturing trace interfacial species and determining the capability of this technique.We then discuss fundamentals,still-debated mechanistic issues,as well as advanced applications of EC-SERS for mechanism studies of the fundamentally and practically important reactions in sustainable energy conversion technologies,to gain insights into electrocatalysis.Finally,we propose directions for the future development of in situ EC-SERS in catalysis.Through this review paper,we aim to attract greater attention to the use of in situ EC-SERS in catalysis studies and introduce versatile methodologies and techniques for catalytic studies that will result in superior performance.
基金support was provided by the National Natural Science Foundation of China(92463310,92163212,52473235,52472213,22179062,52125202,and U24A2065)National Key R&D Program of China(2022YFA1203400)+3 种基金High Level of Special Funds(G03050K002)Guangdong Provincial Key Laboratory of Computational Science and Material Design(2019B030301001)the Natural Science Foundation of Jiangsu Province(BK20230035)Computing resources were supported by the Center for Computational Science and Engineering at Southern University of Science and Technology.
文摘To enhance the power conversion efficiency(PCE)of organic photovoltaic(OPV)cells,the identification of high-performance polymer/macromolecule materials and understanding their relationship with photovoltaic performance before synthesis are critical objectives.In this study,we developed five algorithms using a dataset of 1343 experimentally validated OPV NFA acceptor materials.The random forest(RF)algorithm exhibited the best predictive performance for material design and screening.Additionally,we explored a newly developed polymer/macromolecule structure expression,polymer-unit fingerprint(PUFp),which outperformed the molecular access system(MACCS)across diverse machine learning(ML)algorithms.PUFp facilitated the interpretability of structure-property relationships,enabling PCE predictions of conjugated polymers/macromolecules formed by the combination of donor(D)and acceptor(A)units.Our PUFp-ML model efficiently preevaluated and classified numerous acceptor materials,identifying and screening the two most promising NFA candidates.The proposed framework demonstrates the ability to design novel materials based on PUFp-ML-established feature/substructure-property relationships,providing rational design guidelines for developing high-performanceOPV acceptors.These methodologies are transferable to donor materials,thereby supporting accelerated material discovery and offering insights for designing innovative OPV materials.
