Carbon materials are a key component in energy storage and conversion devices and their microstructure plays a crucial role in determining device performance.However,traditional carbon materials are unable to meet the...Carbon materials are a key component in energy storage and conversion devices and their microstructure plays a crucial role in determining device performance.However,traditional carbon materials are unable to meet the requirements for applications in emerging fields such as renewable energy and electric vehicles due to limitations including a disordered structure and uncontrolled defects.With an aim of realizing devisable structures,adjustable functions,and performance breakthroughs,superstructured carbons is proposed and represent a category of carbon-based materials,characterized by precisely-built pores,networks,and interfaces.Superstructured carbons can overcome the limitations of traditional carbon materials and improve the performance of energy storage and conversion devices.We review the structure-activity relationships of superstructured carbons and recent research advances from three aspects including a precisely customized pore structure,a dense carbon network framework,and a multi-component highly coupled interface between the different components.Finally,we provide an outlook on the future development of and practical challenges in energy storage and conversion devices.展开更多
Apriori算法是关联规则挖掘中最经典的算法之一,其核心问题是频繁项集的获取。针对经典Apriori算法存在的需多次遍历事务数据库及需产生候选项集等问题,首先通过转换存储结构、消除候选集产生过程等方法对Apriori算法进行优化;同时,随...Apriori算法是关联规则挖掘中最经典的算法之一,其核心问题是频繁项集的获取。针对经典Apriori算法存在的需多次遍历事务数据库及需产生候选项集等问题,首先通过转换存储结构、消除候选集产生过程等方法对Apriori算法进行优化;同时,随着大数据时代的到来,数据量与日俱增,传统算法面临巨大挑战,将优化的Apriori与Spark相结合,充分利用Spark的内存计算、弹性分布式数据集等优势,提出了IABS(improved Apriori algorithm based on Spark)。通过与已有的同类算法进行比较,IABS的数据可扩展性和节点可扩展性得以验证,并且在多种数据集上平均获得了23.88%的性能提升,尤其随着数据量的增长,性能提升更加明显。展开更多
文摘Carbon materials are a key component in energy storage and conversion devices and their microstructure plays a crucial role in determining device performance.However,traditional carbon materials are unable to meet the requirements for applications in emerging fields such as renewable energy and electric vehicles due to limitations including a disordered structure and uncontrolled defects.With an aim of realizing devisable structures,adjustable functions,and performance breakthroughs,superstructured carbons is proposed and represent a category of carbon-based materials,characterized by precisely-built pores,networks,and interfaces.Superstructured carbons can overcome the limitations of traditional carbon materials and improve the performance of energy storage and conversion devices.We review the structure-activity relationships of superstructured carbons and recent research advances from three aspects including a precisely customized pore structure,a dense carbon network framework,and a multi-component highly coupled interface between the different components.Finally,we provide an outlook on the future development of and practical challenges in energy storage and conversion devices.
文摘Apriori算法是关联规则挖掘中最经典的算法之一,其核心问题是频繁项集的获取。针对经典Apriori算法存在的需多次遍历事务数据库及需产生候选项集等问题,首先通过转换存储结构、消除候选集产生过程等方法对Apriori算法进行优化;同时,随着大数据时代的到来,数据量与日俱增,传统算法面临巨大挑战,将优化的Apriori与Spark相结合,充分利用Spark的内存计算、弹性分布式数据集等优势,提出了IABS(improved Apriori algorithm based on Spark)。通过与已有的同类算法进行比较,IABS的数据可扩展性和节点可扩展性得以验证,并且在多种数据集上平均获得了23.88%的性能提升,尤其随着数据量的增长,性能提升更加明显。
