Precise control of the local environment and electronic state of the guest is an important method of controlling catalytic activity and reaction pathways.In this paper,guest Pd NPs were introduced into a series of hos...Precise control of the local environment and electronic state of the guest is an important method of controlling catalytic activity and reaction pathways.In this paper,guest Pd NPs were introduced into a series of host UiO-67 MOFs with different functional ligands and metal nodes,the microenvironment and local electronic structure of Pd is modulated by introducing bipyridine groups and changing metal nodes(Ce_(6)O_(6) or Zr_(6)O_(6)).The bipyridine groups not only promoted the dispersion Pd NPs,but also facilitated electron transfer between Pd and UiO-67 MOFs through the formation of Pd-N bridges.Compared with Zr6 clusters,the tunability and orbital hybridisation of the 4f electronic structure in the Ce_(6) clusters modulate the electronic structure of Pd through the construction of the Ce-O-Pd interfaces.The optimal catalyst Pd/UiO-67(Ce)-bpy presented excellent low-temperature activity towards dicyclopentadiene hydrogenation with a conversion of>99% and a selectivity of>99%(50℃,10 bar).The results show that the synergy of Ce-O-Pd and Pd-N promotes the formation of active Pd^(δ+),which not only enhances the adsorption of H_(2) and electron-rich C=C bonds,but also contributes to the reduction of proton migration distance and improves proton utilization efficiency.These results provide valuable insights for investigating the regulatory role of the host MOFs,the nature of host-guest interactions,and their correlation with catalytic performance.展开更多
Electrochemical reduction of water to hydrogen holds great promise for clean energy,while its widespread application relies on the development of efficient catalysts with large surface area,abundant exposed active sit...Electrochemical reduction of water to hydrogen holds great promise for clean energy,while its widespread application relies on the development of efficient catalysts with large surface area,abundant exposed active sites and superior electron conductivity.Herein,we report a facile strategy to configure an electrocatalyst composed of cobalt phosphide and rhodium uniformly anchored on reduced graphene oxide for hydrogen generation.The hybrids effectively integrate the exposed active sites,electron conductivity and synergistic effect of the catalyst.Electrochemical tests exhibit that the catalyst shows superior hydrogen evolution reaction catalytic activity and stability,with a small Tafel slope of 43 m V dec-1.Overpotentials as low as 29 and 72 mV are required to achieve current densities of 2 and 10 mA cm-2in 0.5M H2SO4,respectively.The hybrid constitution with highly active sites on conductive substrate is a new strategy to synthesize extremely efficient electrocatalysts.Especially,the efficient synergistic effect among cobalt phosphide,rhodium and reduced graphene oxide provides a novel approach for configuring electrocatalysts with high electron efficiency.展开更多
Over the past decades, the energy and concomitant environment issues, such as energy shortage, air pollution and global warming, have been becoming increasingly striking world-wide challenges [1,2]. Such a dilemma in ...Over the past decades, the energy and concomitant environment issues, such as energy shortage, air pollution and global warming, have been becoming increasingly striking world-wide challenges [1,2]. Such a dilemma in turn appeals to the development and employment of clean and renewable energy.展开更多
Advanced multifunctional composite phase change materials(PCMs)for integrating energy storage,photothermal conversion and microwave absorption can promote the development of next-generation miniaturized electronic dev...Advanced multifunctional composite phase change materials(PCMs)for integrating energy storage,photothermal conversion and microwave absorption can promote the development of next-generation miniaturized electronic devices.Here,we report paraffin wax(PW)-based multifunctional composite PCMs with a hierarchical network structure assembled by two‐dimensional(2D)nickel-based metal-organic frameworks(Ni-MOFs)decorated carbon nanotubes(CNTs).The PW/CNTs@Ni-MOF composite PCMs yield an excellent photothermal energy conversion efficiency of 93.2%,as well as a good phase change enthalpy of 126.5 J/g and prominent thermal stability.Preferably,the composite PCMs also present great microwave absorption with-25.32 dB minimum reflection loss(RLmin)at 9.85 GHz.The remarkable features of the composite PCMs lie in their hierarchical network architecture and the synergistic enhancement of CNTs and MOFs,giving rise to the increased surface area,accelerated photon capture and transmission,and enhanced dielectric loss caused by polarization effects and multiple reflections,thus further boosting the latent energy storage capacity,photothermal kinetics,and microwave reflection loss.This work provides a facile and scalable approach to regulating the multifunction of composite PCMs.展开更多
Simultaneous achievement of constructing mesopores and eliminating anatase is a long-term pursuit for enhancing the catalytic performance of TS-1.Here,we developed an aromatic compounds-mediated synthesis method to pr...Simultaneous achievement of constructing mesopores and eliminating anatase is a long-term pursuit for enhancing the catalytic performance of TS-1.Here,we developed an aromatic compounds-mediated synthesis method to prepare anatase-free and hierarchical TS-1 for olefin epoxidation.A series of hierarchical TS-1 zeolites were prepared by introducing aromatic compounds containing different functional groups via the crystallization process.The formation of intercrystalline mesopores and insertion of titanium into framework were facilitated at different extent.The synergistic coordination of carboxyl and hydroxyl in aromatic compounds with Ti(OH)4 realizes the uniform distribution of titanium species and eliminates the generation of anatase.Noteworthily,eight machine learning models were trained to reveal the mechanism of additive functional groups and preparation conditions on anatase formation and microstructure optimization.The prediction accuracy of most models can reach more than 80%.Benefiting from the larger mesopore volumes(0.37 cm3⋅g−1)and higher content of framework Ti species,TS-DHBDC-48h samples exhibit a higher catalytic performance than other zeolites,giving 1-hexene conversion of 49.3%and 1,2-epoxyhenane selectivity of 99.9%.The paper provides a facile aromatic compounds-mediated synthesis strategy and promotes the application of machine learning toward the design and optimization of new zeolites.展开更多
Metal-organic frameworks(MOFs),renowned for structural diversity and design flexibility,exhibit potential in catalysis.However,the pursuit of higher catalytic activity through defects often compromises stability,requi...Metal-organic frameworks(MOFs),renowned for structural diversity and design flexibility,exhibit potential in catalysis.However,the pursuit of higher catalytic activity through defects often compromises stability,requiring a delicate balance.Traditional trial-and-error method for optimizing synthesis parameters within the complex chemical space is inefficient.Herein,taking the typical MOF UiO-66(Ce)as an illustrative example,a closed loop workflow is built,which integrates ma-chine learning(ML)-assissted prediction,multi-objective optimization(MOO)and experimental preparation to synergistically optimize the defect content and thermal stability of UiO-66(Ce)for efficient hydrogenation of dicyclopentadiene(DCPD).An automatic data extraction program ensures data accuracy,establishing a high-quality database.ML is employed to explore the intricate synthesis-structure-property correlations,enabling precise delineation of pure-phase subspace and accurate predictions of properties.After two iterations,MOO model identifies optimal protocols for high defect content(>40%)and thermal stability(>300℃).The optimized UiO-66(Ce)exhibits superior catalytic performance in hydroge-nation of DCPD,validating the precision and reliability of our methodology.This ML-assisted approach offers a valuable paradigm for solving the trade-off riddle in materials field.展开更多
文摘Precise control of the local environment and electronic state of the guest is an important method of controlling catalytic activity and reaction pathways.In this paper,guest Pd NPs were introduced into a series of host UiO-67 MOFs with different functional ligands and metal nodes,the microenvironment and local electronic structure of Pd is modulated by introducing bipyridine groups and changing metal nodes(Ce_(6)O_(6) or Zr_(6)O_(6)).The bipyridine groups not only promoted the dispersion Pd NPs,but also facilitated electron transfer between Pd and UiO-67 MOFs through the formation of Pd-N bridges.Compared with Zr6 clusters,the tunability and orbital hybridisation of the 4f electronic structure in the Ce_(6) clusters modulate the electronic structure of Pd through the construction of the Ce-O-Pd interfaces.The optimal catalyst Pd/UiO-67(Ce)-bpy presented excellent low-temperature activity towards dicyclopentadiene hydrogenation with a conversion of>99% and a selectivity of>99%(50℃,10 bar).The results show that the synergy of Ce-O-Pd and Pd-N promotes the formation of active Pd^(δ+),which not only enhances the adsorption of H_(2) and electron-rich C=C bonds,but also contributes to the reduction of proton migration distance and improves proton utilization efficiency.These results provide valuable insights for investigating the regulatory role of the host MOFs,the nature of host-guest interactions,and their correlation with catalytic performance.
基金National Key Research and Development Program of China (No. 2016YFB0701100)the National Natural Science Foundation of China (51802015)+1 种基金the Fundamental Research Funds for the Central Universities (FRF-TP-16-028A1)Program of Young Scholar sponsored by Beijing Organization Department (2017000020124G090) for financial support
文摘Electrochemical reduction of water to hydrogen holds great promise for clean energy,while its widespread application relies on the development of efficient catalysts with large surface area,abundant exposed active sites and superior electron conductivity.Herein,we report a facile strategy to configure an electrocatalyst composed of cobalt phosphide and rhodium uniformly anchored on reduced graphene oxide for hydrogen generation.The hybrids effectively integrate the exposed active sites,electron conductivity and synergistic effect of the catalyst.Electrochemical tests exhibit that the catalyst shows superior hydrogen evolution reaction catalytic activity and stability,with a small Tafel slope of 43 m V dec-1.Overpotentials as low as 29 and 72 mV are required to achieve current densities of 2 and 10 mA cm-2in 0.5M H2SO4,respectively.The hybrid constitution with highly active sites on conductive substrate is a new strategy to synthesize extremely efficient electrocatalysts.Especially,the efficient synergistic effect among cobalt phosphide,rhodium and reduced graphene oxide provides a novel approach for configuring electrocatalysts with high electron efficiency.
基金supported by the National Natural Science Foundation of China(51972024,51702013,51902025)the Fundamental Research Funds for the Central Universities(FRF-BD-20-07A,2019NTST29)+1 种基金the Scientific and Technological Innovation Foundation of Shunde Graduate School,University of Science and Technology Beijing(BK19AE029)funding from China Scholarship Council。
文摘Over the past decades, the energy and concomitant environment issues, such as energy shortage, air pollution and global warming, have been becoming increasingly striking world-wide challenges [1,2]. Such a dilemma in turn appeals to the development and employment of clean and renewable energy.
基金supported by the Beijing Natural Science Foundation(No.2232053)the National Natural Science Foundation of China(No.52002029)+1 种基金Natural Science Foundation of Guangdong Province(No.2022A1515011918)Scientific and Technological Innovation Foundation of Shunde Graduate School,University of Science and Technology Beijing(No.BK20AE003).
文摘Advanced multifunctional composite phase change materials(PCMs)for integrating energy storage,photothermal conversion and microwave absorption can promote the development of next-generation miniaturized electronic devices.Here,we report paraffin wax(PW)-based multifunctional composite PCMs with a hierarchical network structure assembled by two‐dimensional(2D)nickel-based metal-organic frameworks(Ni-MOFs)decorated carbon nanotubes(CNTs).The PW/CNTs@Ni-MOF composite PCMs yield an excellent photothermal energy conversion efficiency of 93.2%,as well as a good phase change enthalpy of 126.5 J/g and prominent thermal stability.Preferably,the composite PCMs also present great microwave absorption with-25.32 dB minimum reflection loss(RLmin)at 9.85 GHz.The remarkable features of the composite PCMs lie in their hierarchical network architecture and the synergistic enhancement of CNTs and MOFs,giving rise to the increased surface area,accelerated photon capture and transmission,and enhanced dielectric loss caused by polarization effects and multiple reflections,thus further boosting the latent energy storage capacity,photothermal kinetics,and microwave reflection loss.This work provides a facile and scalable approach to regulating the multifunction of composite PCMs.
基金National Key Research and Development Program of China,Grant/Award Number:2021YFB3500700SINOPEC Research Institute of Petroleum Processing+3 种基金Natural Science Foundation of Guangdong Province of China,Grant/Award Number:2022A1515011918Scientific and Technological Innovation Foundation of Shunde Graduate SchoolUniversity of Science and Technology Beijing,Grant/Award Number:BK20AE003Fundamental Research Funds for the Central Universities,Grant/Award Number:FRF-IDRY-20-004。
文摘Simultaneous achievement of constructing mesopores and eliminating anatase is a long-term pursuit for enhancing the catalytic performance of TS-1.Here,we developed an aromatic compounds-mediated synthesis method to prepare anatase-free and hierarchical TS-1 for olefin epoxidation.A series of hierarchical TS-1 zeolites were prepared by introducing aromatic compounds containing different functional groups via the crystallization process.The formation of intercrystalline mesopores and insertion of titanium into framework were facilitated at different extent.The synergistic coordination of carboxyl and hydroxyl in aromatic compounds with Ti(OH)4 realizes the uniform distribution of titanium species and eliminates the generation of anatase.Noteworthily,eight machine learning models were trained to reveal the mechanism of additive functional groups and preparation conditions on anatase formation and microstructure optimization.The prediction accuracy of most models can reach more than 80%.Benefiting from the larger mesopore volumes(0.37 cm3⋅g−1)and higher content of framework Ti species,TS-DHBDC-48h samples exhibit a higher catalytic performance than other zeolites,giving 1-hexene conversion of 49.3%and 1,2-epoxyhenane selectivity of 99.9%.The paper provides a facile aromatic compounds-mediated synthesis strategy and promotes the application of machine learning toward the design and optimization of new zeolites.
基金supported by the National Key R&D Program of China(Grant No.2021YFB3500700)Beijing Natural Science Foundation(Grant No.L233011)Guangdong Basic and Applied Basic Research Foundation(Grant No.2022A1515010185).
文摘Metal-organic frameworks(MOFs),renowned for structural diversity and design flexibility,exhibit potential in catalysis.However,the pursuit of higher catalytic activity through defects often compromises stability,requiring a delicate balance.Traditional trial-and-error method for optimizing synthesis parameters within the complex chemical space is inefficient.Herein,taking the typical MOF UiO-66(Ce)as an illustrative example,a closed loop workflow is built,which integrates ma-chine learning(ML)-assissted prediction,multi-objective optimization(MOO)and experimental preparation to synergistically optimize the defect content and thermal stability of UiO-66(Ce)for efficient hydrogenation of dicyclopentadiene(DCPD).An automatic data extraction program ensures data accuracy,establishing a high-quality database.ML is employed to explore the intricate synthesis-structure-property correlations,enabling precise delineation of pure-phase subspace and accurate predictions of properties.After two iterations,MOO model identifies optimal protocols for high defect content(>40%)and thermal stability(>300℃).The optimized UiO-66(Ce)exhibits superior catalytic performance in hydroge-nation of DCPD,validating the precision and reliability of our methodology.This ML-assisted approach offers a valuable paradigm for solving the trade-off riddle in materials field.
