Transition metal cobalt exhibits strong activation capabilities for alkanes,however,the instability of Co sites leads to sintering and coke deposition,resulting in rapid deactivation.Hierarchical zeolites,with their d...Transition metal cobalt exhibits strong activation capabilities for alkanes,however,the instability of Co sites leads to sintering and coke deposition,resulting in rapid deactivation.Hierarchical zeolites,with their diverse pore structures and high surface areas,are used to effectively anchor metals and enhance coke tolerance.Herein,a post-treatment method using an alkaline solution was employed to synthesize meso-microporous zeolite supports,which were subsequently loaded with Co species for propane dehydrogenation catalyst.The results indicate that the application of NaOH,an inorganic base,produces supports with a larger mesopore volume and more abundant hydroxyl nests compared to TPAOH,an organic base.UV-vis,Raman,and XPS analyses reveal that Co in the 0.5Co/SN-1-0.05 catalyst is mainly in the form of tetrahedral Co^(2+),which effectively activates C-H bonds.In contrast,the 0.5Co/S-1 catalyst contains mainly Co_(3)O_(4)species.Co^(2+)supported on hierarchical zeolites shows better propane conversion(58.6%)and propylene selectivity(>96%)compared to pure silica zeolites.Coke characterization indicates that hierarchical zeolites accumulate more coke,but it is mostly in the form of easily removable disordered carbon.The mesopores in the microporous zeolite support help disperse the active Co metal and facilitate coke removal during dehydrogenation,effectively preventing deactivation from sintering and coke coverage.展开更多
Crystalized CeO_(2)structures were typically considered potential photocatalysts due to their great capacity to alter the active sites’size and ability to absorb light.However,the controllable fabrication of well-def...Crystalized CeO_(2)structures were typically considered potential photocatalysts due to their great capacity to alter the active sites’size and ability to absorb light.However,the controllable fabrication of well-defined hierarchical structures of CeO_(2)with high reactive facets is significant and challenging.Herein,a series of CeO_(2)supports including hierarchical flower-like(F-CeO_(2)),ball-like(B-CeO_(2)),cube-like(C-CeO_(2)),and rod-like CeO_(2)(R-CeO_(2))supports were prepared by hydrothermal method(BCeO_(2),R-CeO_(2)and C-CeO_(2))or ice-bath method(F-CeO_(2))respectively.V atoms were selected as the active atoms and loaded on these supports.Their structure-activity relationship in photo-assisted thermal propane dehydrogenation(PTPDH)was investigated systematically.The samples were characterized by Xray diffraction,scanning electron microscopy,transmission electron microscopy,N2 adsorption-desorption isotherms,and Fourier transform infrared spectrum.Results show that R-CeO_(2)support exhibits the biggest surface area thus achieving the best dispersion of VOx species.UV-vis spectrum and photoluminescence spectrum indicate that V/F-CeO_(2)has the best light adsorption property and V/R-CeO_(2)has the best carrier migration capacity.The activity tests demonstrate that the V/R-CeO_(2)has the largest net growth rate and the V/F-CeO_(2)has the biggest relative growth ratio.Furthermore,the non-thermal effect was confirmed by the kinetic method,which lowers the propane reaction orders,selectively promoting the first C-H bond activation.The light radiation TPSR experiment confirmed this point.DFT calculations show a good linear relationship between the energy barrier and the exchanged electron number.It inspires the design of high-reactive facets for boosting the intrinsic activity of the C-H bond in photoassisted thermal chemical processes.展开更多
The C–H bond activation in alkane dehydrogenation reactions is a key step in determining the reaction rate.To understand the impact of entropy,we performed ab initio static and molecular dynamics free energy simulati...The C–H bond activation in alkane dehydrogenation reactions is a key step in determining the reaction rate.To understand the impact of entropy,we performed ab initio static and molecular dynamics free energy simulations of ethane dehydrogenation over Co@BEA zeolite at different temperatures.AIMD simulations showed that a sharp decrease in free energy barrier as temperature increased.Our analysis of the temperature dependence of activation free energies uncovered an unusual entropic effect accompanying the reaction.The unique spatial structures around the Co active site at different temperatures influenced both the extent of charge transfer in the transition state and the arrangement of 3d orbital energy levels.We provided explanations consistent with the principles of thermodynamics and statistical physics.The insights gained at the atomic level have offered a fresh interpretation of the intricate long-range interplay between local chemical reactions and extensive chemical environments.展开更多
Cell-free system has emerged as a powerful platform with a wide range of in vitro applications and recently has contributed to express metabolic pathways for biosynthesis.Here we report in vitro construction of a nati...Cell-free system has emerged as a powerful platform with a wide range of in vitro applications and recently has contributed to express metabolic pathways for biosynthesis.Here we report in vitro construction of a native biosynthetic pathway for L-4-nitrotryptophan(L-4-nitro-Trp)synthesis using an Escherichia coli-based cell-free protein synthesis(CFPS)system.Naturally,a nitric oxide(NO)synthase(TxtD)and a cytochrome P450 enzyme(TxtE)are responsible for synthesizing L-4-nitro-Trp,which serves as one substrate for the biosynthesis of a nonribosomal peptide herbicide thaxtomin A.Recombinant coexpression of TxtD and TxtE in a heterologous host like E.coli for L-4-nitro-Trp production has not been achieved so far due to the poor or insoluble expression of TxtD.Using CFPS,TxtD and TxtE were successfully expressed in vitro,enabling the formation of L-4-nitro-Trp.After optimization,the cell-free system was able to synthesize approximately 360μM L-4-nitro-Trp within 16 h.Overall,this work expands the application scope of CFPS for study and synthesis of nitro-containing compounds,which are important building blocks widely used in pharmaceuticals,agrochemicals,and industrial chemicals.展开更多
High-speed visualization of three-dimensional(3D)processes across a large field of view with cellular resolution is essential for understanding living systems.Light-field microscopy(LFM)has emerged as a powerful tool ...High-speed visualization of three-dimensional(3D)processes across a large field of view with cellular resolution is essential for understanding living systems.Light-field microscopy(LFM)has emerged as a powerful tool for fast volumetric imaging.However,one inherent limitation of LFM is that the achievable lateral resolution degrades rapidly with the increase of the distance from the focal plane,which hinders the applications in observing thick samples.Here,we propose Spherical-Aberration-assisted scanning LFM(SAsLFM),a hardware-modification-free method that modulates the phase-space point-spread-functions(PSFs)to extend the effective high-resolution range along the z-axis by~3 times.By transferring the foci to different depths,we take full advantage of the redundant light-field data to preserve finer details over an extended depth range and reduce artifacts near the original focal plane.Experiments on a USAF-resolution chart and zebrafish vasculatures were conducted to verify the effectiveness of the method.We further investigated the capability of SAsLFM in dynamic samples by imaging large-scale calcium transients in the mouse brain,track-ing freely-moving jellyfish,and recording the development of Drosophila embryos.In addition,combined with deep-learning approaches,we accelerated the three-dimen-sional reconstruction of SAsLFM by three orders of magnitude.Our method is compat-ible with various phase-space imaging techniques without increasing system complex-ity and can facilitate high-speed large-scale volumetric imaging in thick samples.展开更多
Federated learning (FL) is a promising decentralized machine learning approach that enables multiple distributed clients to train a model jointly while keeping their data private. However, in real-world scenarios, the...Federated learning (FL) is a promising decentralized machine learning approach that enables multiple distributed clients to train a model jointly while keeping their data private. However, in real-world scenarios, the supervised training data stored in local clients inevitably suffer from imperfect annotations, resulting in subjective, inconsistent and biased labels. These noisy labels can harm the collaborative aggregation process of FL by inducing inconsistent decision boundaries. Unfortunately, few attempts have been made towards noise-tolerant federated learning, with most of them relying on the strategy of transmitting overhead messages to assist noisy labels detection and correction, which increases the communication burden as well as privacy risks. In this paper, we propose a simple yet effective method for noise-tolerant FL based on the well-established co-training framework. Our method leverages the inherent discrepancy in the learning ability of the local and global models in FL, which can be regarded as two complementary views. By iteratively exchanging samples with their high confident predictions, the two models “teach each other” to suppress the influence of noisy labels. The proposed scheme enjoys the benefit of overhead cost-free and can serve as a robust and efficient baseline for noise-tolerant federated learning. Experimental results demonstrate that our method outperforms existing approaches, highlighting the superiority of our method.展开更多
In the original publication of this article[1],there is a problem with the display of the Fig.3 due to the incompatibility of image format.It needs to be updated with the correct one.The original article[1]was updated.
基金supported by the National Natural Science Foundation of China(Nos.22035009,22178381)the National Key R&D Program of China(Nos.2021YFA1501301,2021YFC2901100)the State Key Laboratory of Heavy Oil Processing(No.2021-03).
文摘Transition metal cobalt exhibits strong activation capabilities for alkanes,however,the instability of Co sites leads to sintering and coke deposition,resulting in rapid deactivation.Hierarchical zeolites,with their diverse pore structures and high surface areas,are used to effectively anchor metals and enhance coke tolerance.Herein,a post-treatment method using an alkaline solution was employed to synthesize meso-microporous zeolite supports,which were subsequently loaded with Co species for propane dehydrogenation catalyst.The results indicate that the application of NaOH,an inorganic base,produces supports with a larger mesopore volume and more abundant hydroxyl nests compared to TPAOH,an organic base.UV-vis,Raman,and XPS analyses reveal that Co in the 0.5Co/SN-1-0.05 catalyst is mainly in the form of tetrahedral Co^(2+),which effectively activates C-H bonds.In contrast,the 0.5Co/S-1 catalyst contains mainly Co_(3)O_(4)species.Co^(2+)supported on hierarchical zeolites shows better propane conversion(58.6%)and propylene selectivity(>96%)compared to pure silica zeolites.Coke characterization indicates that hierarchical zeolites accumulate more coke,but it is mostly in the form of easily removable disordered carbon.The mesopores in the microporous zeolite support help disperse the active Co metal and facilitate coke removal during dehydrogenation,effectively preventing deactivation from sintering and coke coverage.
基金the National Key R&D Program of China(Nos.2021YFA1501301,2021YFC2901100)the National Natural Science Foundation of China(Nos.22178381,22035009).
文摘Crystalized CeO_(2)structures were typically considered potential photocatalysts due to their great capacity to alter the active sites’size and ability to absorb light.However,the controllable fabrication of well-defined hierarchical structures of CeO_(2)with high reactive facets is significant and challenging.Herein,a series of CeO_(2)supports including hierarchical flower-like(F-CeO_(2)),ball-like(B-CeO_(2)),cube-like(C-CeO_(2)),and rod-like CeO_(2)(R-CeO_(2))supports were prepared by hydrothermal method(BCeO_(2),R-CeO_(2)and C-CeO_(2))or ice-bath method(F-CeO_(2))respectively.V atoms were selected as the active atoms and loaded on these supports.Their structure-activity relationship in photo-assisted thermal propane dehydrogenation(PTPDH)was investigated systematically.The samples were characterized by Xray diffraction,scanning electron microscopy,transmission electron microscopy,N2 adsorption-desorption isotherms,and Fourier transform infrared spectrum.Results show that R-CeO_(2)support exhibits the biggest surface area thus achieving the best dispersion of VOx species.UV-vis spectrum and photoluminescence spectrum indicate that V/F-CeO_(2)has the best light adsorption property and V/R-CeO_(2)has the best carrier migration capacity.The activity tests demonstrate that the V/R-CeO_(2)has the largest net growth rate and the V/F-CeO_(2)has the biggest relative growth ratio.Furthermore,the non-thermal effect was confirmed by the kinetic method,which lowers the propane reaction orders,selectively promoting the first C-H bond activation.The light radiation TPSR experiment confirmed this point.DFT calculations show a good linear relationship between the energy barrier and the exchanged electron number.It inspires the design of high-reactive facets for boosting the intrinsic activity of the C-H bond in photoassisted thermal chemical processes.
文摘The C–H bond activation in alkane dehydrogenation reactions is a key step in determining the reaction rate.To understand the impact of entropy,we performed ab initio static and molecular dynamics free energy simulations of ethane dehydrogenation over Co@BEA zeolite at different temperatures.AIMD simulations showed that a sharp decrease in free energy barrier as temperature increased.Our analysis of the temperature dependence of activation free energies uncovered an unusual entropic effect accompanying the reaction.The unique spatial structures around the Co active site at different temperatures influenced both the extent of charge transfer in the transition state and the arrangement of 3d orbital energy levels.We provided explanations consistent with the principles of thermodynamics and statistical physics.The insights gained at the atomic level have offered a fresh interpretation of the intricate long-range interplay between local chemical reactions and extensive chemical environments.
基金This work was supported by the National Natural Science Foundation of China(Nos.31971348 and 32171427)the Natural Science Foundation of Shanghai(No.19ZR1477200)J.L.also acknowledges the starting grant from ShanghaiTech University.
文摘Cell-free system has emerged as a powerful platform with a wide range of in vitro applications and recently has contributed to express metabolic pathways for biosynthesis.Here we report in vitro construction of a native biosynthetic pathway for L-4-nitrotryptophan(L-4-nitro-Trp)synthesis using an Escherichia coli-based cell-free protein synthesis(CFPS)system.Naturally,a nitric oxide(NO)synthase(TxtD)and a cytochrome P450 enzyme(TxtE)are responsible for synthesizing L-4-nitro-Trp,which serves as one substrate for the biosynthesis of a nonribosomal peptide herbicide thaxtomin A.Recombinant coexpression of TxtD and TxtE in a heterologous host like E.coli for L-4-nitro-Trp production has not been achieved so far due to the poor or insoluble expression of TxtD.Using CFPS,TxtD and TxtE were successfully expressed in vitro,enabling the formation of L-4-nitro-Trp.After optimization,the cell-free system was able to synthesize approximately 360μM L-4-nitro-Trp within 16 h.Overall,this work expands the application scope of CFPS for study and synthesis of nitro-containing compounds,which are important building blocks widely used in pharmaceuticals,agrochemicals,and industrial chemicals.
基金supported by the National Natural Science Foundation of China(62088102,62071272,61827804,62131011,62222508).
文摘High-speed visualization of three-dimensional(3D)processes across a large field of view with cellular resolution is essential for understanding living systems.Light-field microscopy(LFM)has emerged as a powerful tool for fast volumetric imaging.However,one inherent limitation of LFM is that the achievable lateral resolution degrades rapidly with the increase of the distance from the focal plane,which hinders the applications in observing thick samples.Here,we propose Spherical-Aberration-assisted scanning LFM(SAsLFM),a hardware-modification-free method that modulates the phase-space point-spread-functions(PSFs)to extend the effective high-resolution range along the z-axis by~3 times.By transferring the foci to different depths,we take full advantage of the redundant light-field data to preserve finer details over an extended depth range and reduce artifacts near the original focal plane.Experiments on a USAF-resolution chart and zebrafish vasculatures were conducted to verify the effectiveness of the method.We further investigated the capability of SAsLFM in dynamic samples by imaging large-scale calcium transients in the mouse brain,track-ing freely-moving jellyfish,and recording the development of Drosophila embryos.In addition,combined with deep-learning approaches,we accelerated the three-dimen-sional reconstruction of SAsLFM by three orders of magnitude.Our method is compat-ible with various phase-space imaging techniques without increasing system complex-ity and can facilitate high-speed large-scale volumetric imaging in thick samples.
基金supported by National Natural Science Foundation of China(Nos.92270116 and 62071155).
文摘Federated learning (FL) is a promising decentralized machine learning approach that enables multiple distributed clients to train a model jointly while keeping their data private. However, in real-world scenarios, the supervised training data stored in local clients inevitably suffer from imperfect annotations, resulting in subjective, inconsistent and biased labels. These noisy labels can harm the collaborative aggregation process of FL by inducing inconsistent decision boundaries. Unfortunately, few attempts have been made towards noise-tolerant federated learning, with most of them relying on the strategy of transmitting overhead messages to assist noisy labels detection and correction, which increases the communication burden as well as privacy risks. In this paper, we propose a simple yet effective method for noise-tolerant FL based on the well-established co-training framework. Our method leverages the inherent discrepancy in the learning ability of the local and global models in FL, which can be regarded as two complementary views. By iteratively exchanging samples with their high confident predictions, the two models “teach each other” to suppress the influence of noisy labels. The proposed scheme enjoys the benefit of overhead cost-free and can serve as a robust and efficient baseline for noise-tolerant federated learning. Experimental results demonstrate that our method outperforms existing approaches, highlighting the superiority of our method.
文摘In the original publication of this article[1],there is a problem with the display of the Fig.3 due to the incompatibility of image format.It needs to be updated with the correct one.The original article[1]was updated.
