Preparation and Performance of Ferric-Rich Bauxite-Tailing-Based Thermal Storage Ceramics.

In recent years, regenerative thermal oxidizer (RTO) has been widely used in the petroleum industry, chemical industry, etc. The massive storage required by solid waste has become a serious problem. Due to their chemical composition, bauxite tailings as raw materials for high-temperature thermal storage ceramics show enormous potential in the fields of research and application. In this study, we propose a method for preparing ferric-rich and high specific storage capacity by adding Fe2O3 powder to bauxite tailings. Based on a 7:3 mass ratio of bauxite tailings to lepidolite, Fe2O3 powder with different mass fractions (7 wt%, 15 wt%, 20 wt%, 30 wt%, and 40 wt%) was added to the ceramic material to improve the physical properties and thermal storage capacity of thermal storage ceramics. The results showed that ferric-rich thermal storage ceramics with optimal performance were obtained by holding them at a sintering temperature of 1000 °C for 2 h. When the Fe2O3 content was 15 wt%, the bulk density of the thermal storage ceramic reached 2.53 g/cm3, the compressive strength was 120.81 MPa, and the specific heat capacity was 1.06 J/(g·K). This study has practical guidance significance in the preparation of high thermal storage ceramics at low temperatures and low costs.

Hierarchical Fibrous Honeycomb Ceramics with High Load Capability and Low Light-Off Temperature for the Next-Generation Auto Emissions Standards.

Novel and stringent automotive exhaust gas emissions standards are urgently needed to counter the problems posed by the worsening global climate and environment. However, the traditional cordierite-based honeycomb ceramics substrates with ultimate pore density have seriously restricted the establishment of new emission standards. Herein, we introduce a novel robust substrate with tailored volume-specific surface area and low heat capacity. This substrate employs the synergy of high-strength ceramic fibers and ultrathin TiO2 nanosheets. The micro-sized fibers provide support to ensure structural strength during the catalytic reaction, while the nanosheets play the dual role of connecting the fibers and providing a high surface area for catalyst immobilization. The new three-dimensional (3D) microarchitecture exhibits a high volume-specific surface area of 3.59×104  cm2 /cm3 , a compressive strength of 2.01 MPa, and remarkable stability after high-speed air erosion at 800 °C. The honeycomb-like structure exhibit low resistance to gas flow. Furthermore, after loading with Pt and Pd nanoparticles, the composite 3D microarchitecture delivered an excellent catalytic performance and prominent structural stability, with a super low light-off temperature of 150 °C. The outstanding mechanical and thermal stability and the high surface area and light-off temperature of the new substrate indicate its potential for use as a highly efficient catalytic carrier to meet the next-generation auto emissions standards.

Review of Research and Application for Vegetation BRDF.

Plant leaves, as a vital organ of the plant photosynthesis, directly reflects the plant growth and nutrition status. Internal physicochemical property model, based on the reflection and transmission of plant leaf, indirectly reflects the information of matter and energy exchange in the process of plant growth information, which can be the premise and foundation of the plant growth process of fine management. The optical properties of plant leaves plays a great significant role in the field of crop nutrition diagnosis and plant morphological structure based on remote sensing, in the field of virtual plant light transmission simulation and computer graphics et al. BRDF (Bidirectional Reflectance Distribution Function) mainly focused on spatial distribution and spectral characteristics of the reflected light on the surface of the object characteristics. It can characterize crop growth parameters accurately and efficiently by acquiring optical properties information of plant leaves, which also has great advantages in the research and application of remote sensing in agriculture. In order to better apply BRDF technology in the agricultural remote sensing, this paper will focus on BRDF measurement and device, model development and classification and its application in the field of plants remote sensing. Eventually, although BRDF technology is still in early exploration stage and is facing many tough challenges, it has a promising future in terms of digital agriculture development.

[Method of Background Elimination for Wheat Leaves Based on the BPLT Model].

In order to precisely acquire leaf reflectance spectra (400-1 000 nm), influence of background on leaf reflectance spectra was studied. Experiment was conducted to discriminate the characteristics of wheat leaves based on 8 background materials and leaf chlorophyll concentration. BPLT (Background Plate) model, based on the Plate model, was promoted and applied to remove the influence of leave background. The BPLT model needed "2-3-1"variables, which were input variables R0 (reflectance of the interaction of leaves and background), σ(reflectance of background alone), intermediate variables R12 (reflectance of interacting interface from air to a compact leaf), R21 (reflectance of interacting interface from a compact leaf to air), τ (the transmissivity of the plate), and ultimate variable R (reflectance of a compact leaf alone). To verify this model, Analysis of Variance (ANOVA) was conducted to compare ten vegetation indices under different background influences. The results indicated that percent of variation in background reflectance associated with spectral vegetation indices was 5% lower after using the BPLT model. Meanwhile, wheat leaf chlorophyll concentration at different levels could be effectively estimated by the means of BPLT model with determined coefficients (DC) greater than 0.9 and residual sum of squares (SSE) less than 1. As with the ANOVA, vegetation indices NIX and MCARI were better than the other 8 ones. The slope of NDI&-MCARI plotted as a function of mean wheat leaf chlorophyll concentration. R2 ranged from 0.847 8 to 0.977 8 with the applied method of BPLT model. The BPLT model is a powerful and accurate method for the acquisition of wheat leaf reflectance information.

[Study of detection of SPAD value in tomato leaves stressed by grey mold based on hyperspectral technique].

Hyperspectral imaging feature of chlorophyll content (SPAD) in tomato leaves stressed by grey mold was studied in the present paper. Hyperspectral imagings of healthy and infected tomato leaves were obtained by hyperspectral imaging system from 380 to 1 030 nm and diffuse spectral response of region of interest (ROI) from hyperspectral imaging was extracted by EN-VI software, then different preprocessing methods were used including smoothing and normalization etc. The partial least squares regress (PLSR) and principal component regress (PCR) models were developed for the prediction of SPAD value in tomato leaves based on normalization preprocessing method, then the back-propagation neural network (BPNN) and least squares-support vector machine (LS-SVM) models were built based on the four variables suggested by PLSR model. Among the four models, LS-SVM model was the best to predict SPAD value and the coefficient of determination (R2) was 0.901 8 with the root mean square error of prediction (RMSEP) of 2.599 2. It was demonstrated that chlorophyll content (SPAD) in healthy and infected tomato leaves can be effectively detected by the hyperspectral imaging technique.