静电纺纳米纤维基超级电容器无粘合剂电极材料的研究进展

对高性能超级电容器不断增长的需求促进了无粘合剂电极材料的快速发展。静电纺纳米纤维由于具有良好的柔性、大比表面积、高孔隙率、容易制备等优点引起了研究者们的强烈关注。本文综述了静电纺纳米纤维基无粘合剂电极材料在超级电容器领域的研究进展,阐述了不同材料的设计制备过程和提升电化学性能的诸多方法,并指明了静电纺纳米纤维基超级电容器无粘合剂电极材料的发展机遇与挑战,为性能优异的无粘合剂超级电容器电极材料的进一步开发与应用拓宽了思路。     

Corrosion inhibition performance of tannins for mild steel in hydrochloric acid solution

Research on Chemical Intermediates - The corrosion inhibition behavior of commercial hydrolysable tannin (tara tannin), condensed tannin (black wattle tannin) and complex tannin (bayberry tannin)...     

Synthesis and microwave absorbing properties of highly ordered mesoporous crystalline NiFe2O4

Highly ordered mesoporous NiFe(2)O(4) with excellent microwave absorption properties has been synthesized by using mesoporous silica (KIT-6) as a hard template.     

Estimation of leaf chlorophyll content and density in Populus euphratica based on hyperspectral characteristic variables

Abstract

Chlorophylls are the most important pigments for photosynthesis and are related to the phenology and health status of plants. Monitoring the chlorophyll content and density of Populus euphratica leaves via remote sensing technology has great significance for restoring and reconstructing damaged desert ecosystems. In this study, Populus euphratica leaves were collected in the public welfare forest reserve of Awati county, Xinjiang, China. Spectral variables and the chlorophyll content and density of leaves were obtained, simple linear regression and multiple linear regression models were built to predict leaf chlorophyll content and density. The results showed that partial least-squares regression models are the most appropriate for chlorophyll content estimation and its determination coefficient and root mean square error were 0.630?～?0.745 and 0.031?～?0.240, respectively. The standard deviation to root mean square error ratio was greater than 1.8 and the ratio of the standard error of the laboratory to the standard error of prediction was close to 1 for the partial least-squares regression models. These results confirmed that chlorophyll content can be accurately predicted and the proposed partial least-squares regression models were adequate for estimating Populus euphratica chlorophyll content rapidly and nondestructively, representing an alternative to conventional measurement methods. The rapid monitoring of chlorophyll content can reflect the health condition of Populus euphratica in a timely manner and provide technical support for ecological reconstruction in arid areas.