Products of carbothermic reduction of Fe-Cr-O and Fe-Cr-Ni-O systems

The reduction behaviors and characteristics of products of the Fe-Cr-O system （FeCr2O4 and Fe2O3＋Cr2O3） and Fe-Cr-Ni-O system （Fe2O3＋Cr2O3＋NiO） under various conditions were studied. The results show that more Fe-Cr or Fe-Cr-Ni solution and less residual carbon content were obtained at higher temperatures and lower initial molar ratio of C to O （nC：nO）. The degree of reduction was highly dependent on both time and temperature, and the residual carbon content greatly increased with increasing nC：nO at each temperature. The products generated during the carbothermic reduction of the Fe-Cr-O system were examined using X-ray diffraction （XRD）. A scanning electron microscope （SEM） coupled with energy dispersive spectrometer was used to observe the microstructure and the distribution of elements in the various phases of the final reduction products of the Fe-Cr-O and Fe-Cr-Ni-O.

Liquefaction of Rice Straw with Ethylene Carbonate

In this study,rice straw(RS) was liquefied by ethylene carbonate(EC) using H_2SO_4 as a catalyst.The effects of various process conditions on the liquefaction characteristics were investigated by FT-IR and residue content analysis.The results show that cellulose and lignin are degraded during the liquefaction process and large amounts of groups are generated.In addition,it is difficult to effectively liquefy RS by using EC alone as the liquefying agent without other additives.Compared to water addition on liquefaction,the residue content can be significantly reduced up to 30% by adding H_2O_2.It has also been proved that the liquor ratio(RS/EC,w/v) of 1∶5 with H_2O_2 as an additive at 145℃ for liquefaction time of 60 min in the presence of H_2SO_4 can accelerate the liquefaction process and high liquefaction yield can be obtained.

Predicting Soil Moisture Characteristic Curves from Continuous Particle-Size Distribution Data

Soil moisture characteristic curve （SMC） is a fundamental soil property and its direct measurement is tedious and time consuming. Therefore, various indirect methods have been developed to predict SMC from particle-size distribution （PSD）. However, the majority of these methods often yield intermittent SMC data because they involve estimating individual SMC points. The objectives of this study were 1） to develop a procedure to predict continuous SMC from a limited number of experimental PSD data points and 2） to evaluate model predictions through comparisons with measured values. In this study, an approach that allowed predicting SMC from the knowledge of PSD, parameterized by means of the closed-form van Genuchten model （VG）, was used. Through using Mohammadi and Vanclooster （MV） model, the parameters obtained from fitting of VG to PSD data were applied to predict SMC curves. Since the residual water content （Or） could not be obtained through fitting of VG-MV integrated model to PSD data, we also examined and compared four different methods estimating 0r. Results showed that the proposed equation （MV-VG integrated model） provided an excellent fit to all the PSD data and the model could adequately predict SMC as measured in forty-two soils sampled from different regions of Iran. For all soils, the method in which Or Was obtained through parameter optimization procedure provided the best overall predictions of SMC. The two methods estimating Or with Campbell and Shiozawa （CS） model resulted in less accuracy than the optimization procedure. Furthermore, the proposed model underestimated the moisture content in the dry range of SMC when the value of 0r was assumed to equal zero. 0r could be attributed to the incomplete desorption of water coated on soil particles and the accurate estimation of 0r was critical in prediction of SMC, especially for fine-textured soils at high suction heads. It could be concluded that the advantages of our approach were the continuity, robustness, and independency of model performance on soil type, allowing to improve predictions of SMC from PSD at the field and watershed scales.