Dynamic polymers with both physical interactions and dynamic covalent bonds exhibit superior performance,but achieving such dry polymers in an effi-cient manner remains a challenge.Herein,we report a novel organic sol...Dynamic polymers with both physical interactions and dynamic covalent bonds exhibit superior performance,but achieving such dry polymers in an effi-cient manner remains a challenge.Herein,we report a novel organic solvent quenched polymer synthesis using the natural molecule thioctic acid(TA),which has both a dynamic disulfide bond and carboxylic acid.The effects of the solvent type and concentration along with reaction times on the proposed reaction were thoroughly explored for polymer synthesis.Solid-state proton nuclear magnetic resonance(1 H NMR)and first-principles simulations were carried out to investigate the reaction mechanism.They show that the chlorinated solvent can efficiently stabilize and mediate the depolymerization of poly(TA),which is more kinetically favorable upon lowering the temperature.Attributed to the numerous dynamic covalent disulfide bonds and noncovalent hydrogen bonds,the obtained poly(TA)shows high extensibility,self-healing,and reprocessable properties.It can also be employed as an efficient adhesive even on a Teflon surface and 3D printed using the fused deposition modeling technique.This new polymer synthesis approach of using organic solvents as catalysts along with the unique reaction mechanism provides a new pathway for efficient polymer synthesis,especially for multifunctional dynamic polymers.展开更多
Digital Ocean is a new research domain of Digital Earth.Because of the spatiotemporal,three-dimensional(3D)and intrinsically dynamic nature of ocean data,it is more difficult to make a breakthrough in this domain.The ...Digital Ocean is a new research domain of Digital Earth.Because of the spatiotemporal,three-dimensional(3D)and intrinsically dynamic nature of ocean data,it is more difficult to make a breakthrough in this domain.The construction of the China Digital Ocean Prototype System(CDOPS)pushes Digital Ocean a step forward from its operation as a mere concept to its achievement as a realistic system.In this paper,the technical framework of the CDOPS is discussed,including its data,function,and application layers.Then,two key technologies are studied in detail that will enable the construction of the 3D ocean environment and the visualization of the ocean model output data.Practical demonstrations show that the CDOPS provides a technical reference for the development of Digital Ocean.This paper is based on an ongoing research project of the development of CDOPS that aims at the facilitation,integration,sharing,accessing,visualization,and use of the ocean data and model computing data from the Digital Earth perspective.展开更多
In recent years,the rapid development of Earth observation tech-nology has produced an increasing growth in remote sensing big data,posing serious challenges for effective and efficient proces-sing and analysis.Meanwh...In recent years,the rapid development of Earth observation tech-nology has produced an increasing growth in remote sensing big data,posing serious challenges for effective and efficient proces-sing and analysis.Meanwhile,there has been a massive rise in deeplearningbased algorithms for remote sensing tasks,providing a large opportunity for remote sensing big data.In this article,we initially summarize the features of remote sensing big data.Subsequently,following the pipeline of remote sensing tasks,a detailed and technical review is conducted to discuss how deep learning has been applied to the processing and analysis of remote sensing data,including geometric and radiometric processing,cloud masking,data fusion,object detection and extraction,landuse/cover classification,change detection and multitemporal ana-lysis.Finally,we discussed technical challenges and concluded directions for future research in deep-learning-based applications for remote sensing big data.展开更多
基金research at the Oak Ridge National Laboratory,managed by UT Battelle,LLC,for the U.S.Department of Energy(DOE)under Contract No.DE-AC05-00OR22725sponsored by the Laboratory Directed Research and Development Program at Oak Ridge National Laboratory.P.-F.C.acknowledges financial support by Fundamental Research Funds for the Central Universities(buctrc202222)。
文摘Dynamic polymers with both physical interactions and dynamic covalent bonds exhibit superior performance,but achieving such dry polymers in an effi-cient manner remains a challenge.Herein,we report a novel organic solvent quenched polymer synthesis using the natural molecule thioctic acid(TA),which has both a dynamic disulfide bond and carboxylic acid.The effects of the solvent type and concentration along with reaction times on the proposed reaction were thoroughly explored for polymer synthesis.Solid-state proton nuclear magnetic resonance(1 H NMR)and first-principles simulations were carried out to investigate the reaction mechanism.They show that the chlorinated solvent can efficiently stabilize and mediate the depolymerization of poly(TA),which is more kinetically favorable upon lowering the temperature.Attributed to the numerous dynamic covalent disulfide bonds and noncovalent hydrogen bonds,the obtained poly(TA)shows high extensibility,self-healing,and reprocessable properties.It can also be employed as an efficient adhesive even on a Teflon surface and 3D printed using the fused deposition modeling technique.This new polymer synthesis approach of using organic solvents as catalysts along with the unique reaction mechanism provides a new pathway for efficient polymer synthesis,especially for multifunctional dynamic polymers.
基金The study is funded by the National High Technology Research and Development Program of China(863 Program)(No.2009AA12Z208,No.2009AA12Z225)the 908 Project of the State Oceanic Administration,China(No.908-03-03-02)。
文摘Digital Ocean is a new research domain of Digital Earth.Because of the spatiotemporal,three-dimensional(3D)and intrinsically dynamic nature of ocean data,it is more difficult to make a breakthrough in this domain.The construction of the China Digital Ocean Prototype System(CDOPS)pushes Digital Ocean a step forward from its operation as a mere concept to its achievement as a realistic system.In this paper,the technical framework of the CDOPS is discussed,including its data,function,and application layers.Then,two key technologies are studied in detail that will enable the construction of the 3D ocean environment and the visualization of the ocean model output data.Practical demonstrations show that the CDOPS provides a technical reference for the development of Digital Ocean.This paper is based on an ongoing research project of the development of CDOPS that aims at the facilitation,integration,sharing,accessing,visualization,and use of the ocean data and model computing data from the Digital Earth perspective.
基金supported in part by the National Key Research and Development Program under Grant[2017YFB0504201]the National Natural Science Foundation of China under Grant Nos.[42071316,61473286 and 401201460]+1 种基金Open Fund of State Key Laboratory of Remote Sensing Science under Grant No.[OFSLRSS201919]the Fundamental Research Funds for the Central Universities under Grant No.[B200202008].
文摘In recent years,the rapid development of Earth observation tech-nology has produced an increasing growth in remote sensing big data,posing serious challenges for effective and efficient proces-sing and analysis.Meanwhile,there has been a massive rise in deeplearningbased algorithms for remote sensing tasks,providing a large opportunity for remote sensing big data.In this article,we initially summarize the features of remote sensing big data.Subsequently,following the pipeline of remote sensing tasks,a detailed and technical review is conducted to discuss how deep learning has been applied to the processing and analysis of remote sensing data,including geometric and radiometric processing,cloud masking,data fusion,object detection and extraction,landuse/cover classification,change detection and multitemporal ana-lysis.Finally,we discussed technical challenges and concluded directions for future research in deep-learning-based applications for remote sensing big data.
