Improved Ethanol Production from Xylose by Candida shehatae Induced by Dielectric Barrier Discharge Air Plasma

Xylose fermentation is essential for ethanol production from lignocellulosic biomass. Exposure of the xylose-fermenting yeast Candida shehatae （C. shehatae） CICC1766 to atmospheric pressure dielectric barrier discharge （DBD） air plasma yields a clone （designated as C81015） with stability, which exhibits a higher ethanol fermentation rate from xylose, giving a maximal enhancement in ethanol production of 36.2% compared to the control （untreated）. However, the biomass production of C81015 is lower than that of the control. Analysis of the NADH （nicotinamide adenine dinucleotide）- and NADPH （nicotinamide adenine dinucleotide phosphate）- linked xylose reductases and NAD＋-linked xylitol dehydrogenase indicates that their activities are enhanced by 34.1%, 61.5% and 66.3%, respectively, suggesting that the activities of these three enzymes are responsible for improving ethanol fermentation in C81015 with xylose as a substrate. The results of this study show that DBD air plasma could serve as a novel and effective means of generating microbial strains that can better use xylose for ethanol fermentation.

Surface Modification of Polyethylene (PE) Films Using Dielectric Barrier Discharge Plasma at Atmospheric Pressure

Modification of the surface properties of polyethylene （PE） films is studied using air dielectric barrier discharge at atmospheric pressure. The treated samples are examined by Water contact angle measurements, Fourier transform infrared attenuated total reflection spectroscopy （FTIR-ATR）, X-ray photoelectron spectroscopy （XPS） and scanning electron microscopy （SEM）. With the increase in treating time, the water contact angle changes from 93.2° before treatment to a minimum of 53.3° after a treatment for 50 s. Both ATR and XPS results show some oxidized species are introduced into the sample surface by the plasma treatment and the tendency of the water contact angle with the treating time is the same as that of oxygen concentration on the treated sample surface. SEM result shows the surface roughness of PE samples increases with the treatment time increasing.

Prediction of Equivalent Electrical Parameters of Dielectric Barrier Discharge Load Using a Neural Network

A reliable, efficient and economical power supply for dielectric barrier discharge （DBD） is essential for its industrial applications. However, the equivalent load parameters complicare the design of power supply as they are variable and varied nonlinearly in response to varied voltage and power. In this paper the equivalent electrical parameters of DBD are predicted using a neural network, which is beneficial for the design of power supply and helps to investigate how the electrical parameters influence the equivalent load parameters. The electrical parameters includ- ing voltage and power are determined to be the inputs of the neural network model, as these two parameters greatly influence the discharge type and the equivalent DBD load parameters which are the outputs of the model. The voltage and power are decoupled with pulse density modula- tion （PDM） and hence the impact of the two electrical parameters is discussed individually. The neural network model is trained with the back-propagation （BP） algorithm. The obtained neural network model is evaluated by the relative error, and the prediction has a good agreement with the practical values obtained in experiments.

Experimental and simulated investigation of microdischarge characteristics in a pin-to-pin dielectric barrier discharge(DBD)reactor

Both experimental and simulated studies of microdischarge(MD)are carried out in a dielectric barrier discharge with a pin-to-pin gap of 3.5 mm,ignited by a sinusoidal voltage with a peak voltage of 10 kV and a driving frequency of 5 kHz.Statistical results have shown that the probability of the single current pulse in the positive half-period(HP)reaches 73.6%under these conditions.Experimental results show that great luminous intensity is concentrated on the dielectric surface and the tip of the metal electrode.A 1D plasma fluid model is implemented by coupling the species continuity equations,electron energy density equations,Poisson equation,and Helmholtz equations to analyze the MD dynamics on the microscale.The simulated results are in good qualitative agreement with the experimental results.The simulated results show that the MD dynamics can be divided into three phases:the Townsend phase,the streamer propagation phase,and the discharge decay phase.During the streamer propagation phase,the electric field and electron density increase with the streamer propagation from the anode to the cathode,and their maximal values reach 625.48 Td and 2.31×10^(19)m^(-3),as well as 790.13 Td and 3.58×10^(19)m^(-3)in the positive and negative HP,respectively.Furthermore,a transient glow-like discharge is detected around the anode during the same period of streamer propagation.The formation of transient glow-like discharge is attributed to electrons drifting back to the anode,which is driven by the residual voltage in the air gap.