Construction of Soft Base Tongs on Separator to Grasp Polysulfides from Shuttling in Lithium-Sulfur Batteries.

Rechargeable lithium-sulfur batteries, which use sulfur as the cathode material, promise great potentials to be the next-generation high-energy system. However, higher-order lithium polysulfides, Li2 Sx (x = 4, 6, and 8), regardless of in charge or in discharge, always form first, dissolve subsequently in the electrolyte, and shuttle to the cathode and the anode, which is called "shuttle effect." The polysulfides shuttle effect leads to heavy loss of the active-sulfur materials. Literature works mostly "cover or fill" the pores to block polysulfides from shuttling, which also hinder the lithium ion transfer. Here a protocol is invented to grasp polysulfides based on the "soft and hard acid-base" theory. Tertiary amine layer (TAL) polymerized on a polypropylene separator selectively coordinates with the dissolved high-order Li2 Sx in the cathode. Meanwhile, the transportation of lithium cations is not interrupted because of enough pores left for their transportation. After 400 cycles of charge/discharge at 0.5C, the TAL modified separator battery still possesses a capacity of 865 mAh g-1 , which is among the best of the state-of-the-art performances of lithium-sulfur batteries. The flexible "polysulfides tongs" construction method paves a new way for Li-S batteries to reach desired performances with less worry about polysulfides shuttle.

[Studies on the estimation of soil organic matter content based on hyper-spectrum].

Hyperspectral remote sensing technology can be extensively applied in soil nutrient research due to its three special advantages, high spectral resolution, strong waveband continuity as well as a great deal of spectral information. Based on analyzing the soil organic matter content using hyper-spectral remote sensing technology, soil nutrients status and its dynamic changes can be fully understood, thus providing the scientific basis for guidance of the agricultural production and protection of agricultural ecological environment. The present paper studies the relationship between soil spectrum and soil organic fraction based on spectrum curves (ranging from 350 to 2500 nm) of 34 soil samples, which were collected in Yujiang and Taihe County, Jiangxi Province. First, soil reflection spectrum was mathematically manipulated into first derivative reflectance spectra (FDR) and inverse-log spectra (log(1/R)); second, the relationship between soil spectrum and soil organic fraction was investigated by step-wise multiple linear regression (SMLR) and partial least square regression (PLSR) on the ground of characteristic absorption; third, corresponding estimation model was built and examined. The result conveys that spectral data are compressed by carrying out arithmetic average operation by 10 nm for intervals. The first derivative of the reflectivity is an effective spectrum indicator, in the stepwise multiple linear regression analysis of soil organic matter, for the first derivative transformation, the regression models' precision of establishment and verification increased. The model built by PLSR method based on the characteristic absorption bands precedes that of SMLR. In the PLSR model of soil reflection spectrum and the inverse-log spectra, the test samples' average of relative error is 16% and 17% respectively, the correlation coefficient between retrieval value and measured value is 0.84 and 0.91 respectively, for it's faster to estimate the soil organic fraction.

[Analysis of directional characteristics of winter wheat canopy spectra].

The bidirectional reflectance factors vary as the incidence directions and the view angles change. At present the remote sensing is almost at nadir, therefore it is possible to improve the accuracy of remote sensing application by reasonably selecting the looking angle, solar zenith angle, and so on. Based on the multidirectional spectra of winter wheat canopy at several critical growth stages, the paper quantitatively analyzed the sensitivity of narrowband bidirectional reflectance to view planes, view zenith angle, solar zenith angle, growth stage, and band by using anisotropy factor (ANIF) and anisotropy index (ANIX). The change of NDVI with view zenith angle, solar zenith angle and growth stage was also studied. The results show that the anisotropy characteristics of bidirectional reflectance factors at solar principal plane was stronger than that at the other planes, and orthogonal principal plane was the weakest. The ANIX at solar principal plane was the biggest. The reason was that the shadow of canopy changed more dramatically at solar principal plane than at the other planes. The sensitivity of bidirectional reflectance factor at visible bands to zenith angles was stronger than in near infrared regions, the reason for which was that the shadow effect in visible regions was stronger than in near infrared regions. The ANIX in visible regions was bigger than in near infrared regions. The sensitivity of bidirectional reflectance factor to solar zenith angles increased as the view zenith angle increased. The NDVIs at every looking zenith angle all increased with the leaf area index increasing. The NDVIs at forward direction were larger than at backward direction, which resulted from that the shadow effect in visible regions was stronger than in near infrared regions. The solar principal plane implies rich internal structure information on object. In order to reduce the uncertainty from the observing method, the near infrared bands and small solar zenith angle should be chosen. The retrieve of structure parameters ought to select solar principal plane, and avoid hot spot region when inversing biological parameters using NDVI.