Henan Normal University

About: Henan Normal University is a education organization based out in Xinxiang, China. It is known for research contribution in the topics: Catalysis & Ionic liquid. The organization has 10863 authors who have published 11077 publications receiving 166773 citations.

Volumetric properties of some α-amino acids in aqueous guanidine hydrochloride at 5, 15, 25, and 35°C

Abstract: The infinite-dilution apparent molar volumesV 2φ o for glycine, DL-alanine, DL-α-amino-n-butyric acid, DL-valine, DL-leucine, and L-serine in 6 mol-kg−1 aqueous guanidine hydrochloride were determined at 5, 15, 25, and 35°C from precise density measurements. Using these data, the standard volumes of transfer, Δt V°, from water to 6m> aqueous guanidine hydrochloride solution were calculated. A linear relationship was found between V 2φ o and temperature. Both V 2φ o and Δt V° vary linearly with increasing number of carbon atoms in the alkyl chain of the amino acids. The results show that the apparent molar volumes at infinite dilution for (NH 3 + ,COO-) groups increase with increasing temperature and those for CH2 and the other alkyl chains are almost constant. These results also shows that guanidine hydrochloride has stronger interactions with amino acids than urea. These phenomena are discussed in terms of the cosphere overlap model.

Imbalanced Fault Diagnosis of Rolling Bearing Based on Generative Adversarial Network: A Comparative Study

Abstract: Due to the real working conditions and data acquisition equipment, the collected working data of bearings are actually limited. Meanwhile, as the rolling bearing works in the normal state at most times, it is easy to raise the imbalance problem of fault types which restricts the diagnosis accuracy and stability. To solve these problems, we present an imbalanced fault diagnosis method based on the generative adversarial network (GAN) and provide a comparative study in detail. The key idea is utilizing GAN, a kind of deep learning technique, to generate synthetic samples for minority fault class and then improve the generalization ability of the fault diagnosis model. First, this method applies fast Fourier transform to pre-process the original vibration signal and then obtains the frequency spectrum of fault samples. Second, it uses the spectrum data as the input of GAN to generate the synthetic minority samples following the data distribution of the real samples. Finally, it puts the synthetic samples into the training set and builds a stacked denoising auto encoder model for fault diagnosis. To testify the effectiveness of the proposed method, a series of comparative experiments is carried out on the CWRU bearing dataset. The results show that the proposed method can provide a better solution for imbalanced fault diagnosis on the basis of generating similar fault samples. As a comparative study, the proposed method is compared to several diagnostic methods with traditional time-frequency domain characteristics. Moreover, we also demonstrate that the proposed method outperforms three widely used sample synthesis techniques, such as random oversampling, synthetic minority oversampling technique, and the principal curve-based oversampling method in terms of diagnosis accuracy and numerical stability.

C3N monolayers as promising candidates for NO2 sensors

Abstract: Searching for suitable materials for NO2 sensing has important scientific significance and application value. First-principles calculations have been performed on the adsorption of NO2 and its various interfering gases on the pristine C3N monolayer (p-C3N) and the B-doped C3N monolayer. The studies on the adsorption stability, geometric structure, charge transfer, and electronic structure indicate that the p-C3N is a promising room-temperature NO2 sensor, with high selectivity and sensitivity, and good reversibility. For the B-doped C3N monolayer, the calculated formation energies suggest that B doping into the C3N lattice is thermodynamically highly favorable. Furthermore, B doping by replacing the N atom in the C3N monolayer should can further improve the sensing selectivity and sensitivity of the C3N monolayer toward NO2. However, it is noted that a large adsorption energy for NO2 indicates that the B-doped C3N monolayer may be reversibly operated above the room temperature. The possible reason for the distinct adsorption behaviors of the various molecules is also provided. Our theoretical studies indicate the great potential of the C3N-based two-dimensional semiconductor as good NO2 gas sensors.

Peroxymonosulfate-enhanced visible light photocatalytic degradation of bisphenol A by perylene imide-modified g-C3N4

Abstract: In this study, a metal-free photocatalyst (PI-g-C3N4) was synthesized through an amidation reaction between perylene tetracarboxylic dianhydride (PTCDA) and graphitic carbon nitride (g-C3N4). In order to enhance the photocatalytic degradation efficiency of bisphenol A (BPA) by 5 wt% PI-g-C3N4, peroxymonosulfate (PMS) was introduced into this system. When 5 mM PMS was added, 96% of BPA with an initial concentration of 10 mg/L was degraded within 60 min; the pseudo-first-order degradation kinetics constant of BPA was increased from 0.0057 to 0.0501 min−1. Based on the photoelectrochemical analysis, it was proposed that PI-g-C3N4 achieved a more effective separation of photogenerated electron–hole pairs and displayed higher conductivity than PTCDA and g-C3N4 individually, thus promoting the PMS activation into active radicals by the photogenerated electrons. The BPA degradation was favored at high PMS concentrations under alkaline conditions. The slight inhibition effect of co-existing anions on the degradation of BPA followed the order: H2PO4− > NO3− ≈ HCO3−; Cl− had a remarkable positive effect on the degradation of BPA. The radical quenching tests and electron spin resonance results indicated that O2 −, 1O2, and h+ were the major species for the degradation of BPA. Combined with intermediates analysis, the degradation mechanism and pathway of BPA was proposed. The high stability of the 5 wt% PI-g-C3N4 was finally demonstrated.