Silicon Carbide Supported Palladium-Iridium Bimetallic Catalysts for Efficient Selective Hydrogenation of Cinnamaldehyde

Summary of main observation and conclusion Selective hydrogenation of a,B-unsaturated carbonyls into saturated carbonyls is important to obtain remunerative products.However,it is still a challenge to achieve high activity and selec tivity under mild conditions.Herein,Pd,Ir and bimetallic Pd-Ir nanoparticles were uniformly deposited with high dispersity on the surface of SIC by a facile impregnation method,respectively.The as prepared Pd/SIC catalysts eficiently hydrogenate cinnamaldehyde to hydrocinnamaldehyde at room temperature and atmospheric pressure,and the activity of Pd/SiC is observed further enhanced by adding Ir component(conversion of 100%).In addition,the dependence of Pd-lr catalyst activity on Pd/Ir molar ratio con.firms a synergistic effect between Ir and Pd,which originates from the electron transfer between Pd and Ir.

Nondestructive determining the soluble solids content of citrus using near infrared transmittance technology combined with the variable selection algorithm

Nondestructive determination the internal quality of thick-skin fruits has always been a challenge.In order to investigate the prediction ability of full transmittance mode on the soluble solid content(SSC)in thick-skin fruits,the full transmittance spectra of citrus were collected using a visible/near infrared(Vis/NIR)portable spectrograph(550–1100 nm).Three obvious absorption peakswere found at 710,810 and 915 nmin the original spectra curve.Four spectral preprocessing methods including Smoothing,multiplicative scatter correction(MSC),standard normal variate(SNV)and first derivativewere employed to improve the quality of the original spectra.Subsequently,the effective wavelengths of SSC were selected from the original and pretreated spectra with the algorithms of successive projections algorithm(SPA),competitive adaptive reweighted sampling(CARS)and genetic algorithm(GA).Finally,the prediction models of SSC were established based on the full wavelengths and effectivewavelengths.Results showed that SPA performed the best performance on eliminating the useless information variable and optimizing the number of effective variables.The optimal predictionmodel was established based on 10 characteristic variables selected from the spectra pretreated by SNV with the algorithmof SPA,with the correlation coefficient,root mean square error,and residual predictive deviation for prediction set being 0.9165,0.5684°Brix and 2.5120,respectively.Overall,the full transmittance mode was feasible to predict the internal quality of thick-skin fruits,like citrus.Additionally,the combination of spectral preprocessing with a variable selection algorithmwas effective for developing the reliable predictionmodel.The conclusions of this study also provide an alternative method for fast and real-time detection of the internal quality of thick-skin fruits using Vis/NIR spectroscopy.

Biomorphic SiC from lotus root

Biomorphic silicon carbide （bioSiC） with macro-channels and alveolate micropores was prepared by spontaneous infiltration of melted silicon into a carbon template derived from lotus root at 1600cC. The carbon template and purified bioSiC samples were characterized by X-ray diffraction, scanning electron microscopy, camera and mercury intrusion. The results suggest that the bioSiC mainly consists of β-SiC and perfectly replicates the shape and microstructure of the carbon template. The bioSiC has a mean pore diameter of 91.1 μm and a porosity of 50.1%, both similar to those of the carbon template, 92.3 μm and 50.7%, respectively.