Abstract: This study deals with the synthesis of phenylazo-N,N-diphenylpropanediamide which is a kind of excellent pigment. During the preparation, intermediate product, N,N-diphenylpropanediamide is first synthesized through the substitution reaction of malonic acid diethyl ester and substituted aniline. Then, final product, phenylazo-N,N-diphenylpropanediamide can be obtained by coupling reaction of N,N-diphenylpropanediamide and phenyl substituted diazonium salt. The final product has been analyzed by UV, MS and HNMR, respectively, to determine the composition and structure. In addition, the effects of solvents, coupling catalyst and pH on yield rate have also been investigated.
Abstract: In this work, Ziegler-Natta/Metallocene hybrid catalyst (Z-M) was prepared magnifying. The activity and copolymerization behavior of the catalyst were evaluated through 10L model device. Model experiment results confirmed that the catalyst was suitable for Spheripol-II PP pilot device. Subsequently, pilot experiment was carried out on 75 kgPP/h Spheripol-II PP pilot device. SP179 which was prepared by traditional Ziegler-Natta catalyst was used as a reference object. Pilot experiment results showed that: Z-M hybrid catalyst demonstrated good activity and copolymerization properties. The resultant polypropylene in-reactor alloys have better impact strength and flowability than SP179. These alloys showed good stiffness-toughness balance. The impact strength and the flexural modulus of the best alloy was 50 kJ/m2 at 23 °C and 848 MPa, respectively. The other performances were similar to that of SP179. But Z-M hybrid catalyst required lower feed ratio of ethylene than the traditional Ziegler-Natta catalyst for SP179.
Abstract: A laboratory-scale method for treating bulk concentrate for reclaiming lead and silver was developed utilizing new hydrometallurgical technology as an alternative to the traditional pyrometallurgical processing. The condition experiments of every chief segment in the whole flowsheet have been systematically investigated, and then the whole hydrometallurgical processing flowsheet was determined. The main contents are followed as: Bulk concentrate was treated using pressure leaching in autoclave, the optimal leaching conditions were determined. The elemental sulphur was deprived from the pressure leaching residue using flotation-distillation. Carbonate conversion -silicofluoric acid leaching on flotation gangue containing lead sulfate using hydrometallurgy was carried. And Leaching silver using thiourea from the residue was carried after extracting lead. Through the whole hydrometallurgy flowsheet, the reclaiming of lead and silver was actualized.
Abstract: The effectiveness of lead ion and tetrabutylammonium bromide (TBAB) as inhibitors of spongy zinc deposits from flowing zincate solutions has been testified. To assess the efficacy of the two additives, current–time technique using potentiostatic electro-deposition, scanning electron microscopy and cycling test were undertaken. The results show that the spongy growth of zinc can be effectively inhibited by the individual addition of 10-4M Pb(II) or TBAB at the cathodic potential (η=-100mV). But, the dual addition of 10-4M Pb(II) and 5×10-5M TBAB produces more effective suppression on spongy zinc deposits. Obvious synergistic effect of Pb(II) and TBAB on the spongy inhibition of zinc electrode is found in flowing electrolytes. From the charge/discharge cycling tests of the single flow Zn-Ni test cells, it is shown that the rechargeability of deposited Zn anode is highly improved by the mixed introduction of 10-4M Pb(II) and 5×10-5M TBAB.
Abstract: Wear status diagnosis to frictional particle analysis is the better technology for aeroengine failure predict. The monitoring wear conditions for on-line lubricating oil samples of the aeroengine are diagnosed based on spectrography and ferrography, and it is given the results that both of these combinational analytical methods are so relatively reliable that they can diagnose the wear faults and predict wear trend of the aeroengine.
Abstract: The influence of Cu2+, Fe2+ on the Maillard reaction were studied by heating L-ascorbic(ASA) and glycine (Gly) solutions adjusted to pH 5 at 120±2°C for 140 min in an oil bath. The presence of metals affected the intensity of browning and intermediate products, as monitored by absorbance at 420 nm and absorbance at 294 nm, sharply increased with the increase of metal concentrations applied (0.000M, 0.005M, 0.010M, 0.015M, 0.020M). Thereafter, slight increases were observed up to 0.020M. Antioxidative activity of all MRPs derived from ASA-Gly model systems sharply increased at 0.015M (P < 0.05) and slightly changes in activity were found with increasing metal concentrations up to 0.020M. Moreover, radical-scavenging activity correlated well with browning intensity and absorbance at 294 nm.
Abstract: Alkalizer or coagulation and alkalizer technology were adopted to pretreat seawater in the study. Turbidity removal was investigated with different pH, mixing time,and mixing speed. The A was the best by contrasting alkalizer A, B and C. Turbidity removal was 99.4%. The effect of boron removal in the seawater was also studied. The results showed that the pH value has a great impact on the boron removal. The highest boron removal was 89% by alkalizer A under pH 11.The best reaction condition for turbidity removal : pH value 10.8,stirring rate 200r/min,reaction time 10 minutes and dosage of PAM 0.5 mg/L.
Abstract: Cross-linked poly(N-isopropylacrylamide) tethered Hydroxyapatite hybrid materials (HA- PNIPAM) were prepared by the ATRP reaction. The hybrid materials were characterized by FT-IR、TGA、SEM and UV spectra. The TGA results demonstrated that there was 122 g PNIPAM grafted on the surface of per 100g of HA. The UV results showed that the HA-PNIPAM have thermal responsive property around 33°C.
Abstract: This paper presents an information-entropy-based integrated model for predicting the burn-through point (BTP) in lead-zinc sintering process. First, a fuzzy T-S prediction model for BTP was established to deal with the uncertainty of the vertical burning speed. Considering the BTP is also affected by process parameters, a neural network (NN) prediction model for BTP was then built. Finally, an integrated model for predicting the BTP was constructed by combining the above two models using the recursive entropy algorithm. The practical running results demonstrate the validity of the proposed integrated predictive model.