Syu-Ruei Jhang

Hydrogen production from banyan leaves using an atmospheric-pressure microwave plasma reactor

Growth of the hydrogen market has motivated increased study of hydrogen production. Understanding how biomass is converted to hydrogen gas can help in evaluating opportunities for reducing the environmental impact of petroleum-based fuels. The microwave power used in the reaction is found to be proportional to the rate of production of hydrogen gas, mass of hydrogen gas produced per gram of banyan leaves consumed, and amount of hydrogen gas formed with respect to the H-atom content of banyan leaves decomposed. Increase the microwave power levels results in an increase of H2 and decrease of CO2 concentrations in the gaseous products. This finding may possibly be ascribed to the water-gas shift reaction. These results will help to expand our knowledge concerning banyan leaves and hydrogen yield on the basis of microwave-assisted pyrolysis, which will improve the design of hydrogen production technologies.

Development of novel alternative biodiesel fuels for reducing PM emissions and PM-related genotoxicity

ABSTRACT This paper intend to investigate the effects of biodiesel fuel blends comprising of waste‐cooking oil and butanol‐diesel (B10W10–B10W40) under steady‐state conditions. Both particulate organic carbon (OC) and PM including PM2.5 and PM10 significantly decreased with the increasing percentage of biodiesel fuel blends. The fuel blend of B10W40 also demonstrated the most effective function in reducing the emissions of PM10 and PM2.5 in the volume by 59.4% and 57.7%, respectively. Moreover, the emissions of nitrogen oxides decreased with the blending of B10W10‐B10W40 (13.9–28.5%), while the brake specific fuel consumption was substantially increased (5.69–13.4%). The overall biological toxicity of PM10 generated from the fuel tested in this study was determined according to Single Cell Gel Electrophoresis assay in human alveolar basal epithelial A549 cells and micronucleus assay in CHO‐K1 cells. In addition, the volume of more than 20% waste‐cooking oil (B10W20 and B10W40) significantly reduced diesel‐induced genotoxicity in lung cells and micronucleus formation in CHO‐K1 cells. Collectively, these results indicated that biodiesel fuel blends with the butanol could be a potential alternative fuels for diesel engines because of its substantial property with a significant reduction of the PM‐related genotoxicity and the emissions of PM, particulate OC, and NOX. HighlightsDiesel/biodiesel/butanol blends investigated experimentally.Butanol blends reduced the heating value and increased the fuel consumption.Butanol (10 vol%) are potential alternative fuels for diesel engines.Diesel/biodiesel/butanol blends decrease PM10, PM2.5, and NOX emissions.Diesel/biodiesel/butanol blends decrease mutagenicity and genotoxicity.

Prediction of Proinflammatory Potentials of Engine Exhausts by Integrating Chemical and Biological Features

The increasing prevalence of immune-related diseases has raised concerns about immunotoxicity of engine exhausts. The evaluation of immunotoxicity associated with engine exhausts has relied on expensive and time-consuming experiments. In this study, a computational method named CBM was developed for predicting proinflammatory potentials of engine exhausts using chemical and biological data which are routinely analyzed for toxicity evaluation. The CBM model, based on a principal component regression algorithm, performs well with high correlation coefficient values of 0.972 and 0.849 obtained from training and independent test sets, respectively. In contrast, chemical or biological features alone showed poor correlation with the toxicity. The model indicates the importance of the utilization of both chemical and biological features for developing an effective model. The proposed method could be further developed and applied to predict bioactivities of mixtures.

Using sodium hydroxide with microwave to enhance the saccharification efficiency of water hyacinth to improve the optimal pre-treatment for producing into biomass butanol

Sugar drivened from aquatic plants with high cellulose and hemicellulose content is one of the dynamic development that assists to maintain the advancement in bioproducts. Therefore, this study explored the potentiality of improvement on the saccharification efficiency of sugar from water hyacinth (Eichhornia crassipes) caused by microwave heating system. Pre-treatment is the most essential process for improving the function of lignocellulose as well as to decrease the crystallinity of cellulose so that reduce the cost of production. The structural changes of the fibers after microwave treatment with sodium hydroxide was observed on the residue by using X-ray Diffractometer (XRD), Fourier Transform Infrared Spectrometry (FTIR) and Environmental Scanning Electron Micrograph (ESEM) analysis. The methods of full factorial experimental design were adopted to explore different parameters that influence the conversion rates of fibers into fermentable sugar. According to the result obtained the saccharification efficiency of sugar production were 10.2 ± 0.3%, 20.2 ± 0.2%, 14.7 ± 0.4%, 19.7 ± 0.6%, 15.3 ± 0.4%, 19.5 ± 0.5%, 20.1 ± 0.8%, 42.8 ± 0.1%, 14.2 ± 0.3%, 12.7 ± 0.9%, 18.4 ± 0.5%, 17.4 ± 0.1%, 18.4 ± 0.8%, 29.3 ± 0.6%, 17.2 ± 0.7%, and 52.6 ±0.5%. Henceforth, resulting from the interaction of these three parameters, the better sugar transfer efficiency was obtained under the conditions of high Microwave power (500W), long hydrolysis time (30min) and high Sodium hydroxide concentration (1.5%).

Identification of informative features for predicting proinflammatory potentials of engine exhausts

BackgroundThe immunotoxicity of engine exhausts is of high concern to human health due to the increasing prevalence of immune-related diseases. However, the evaluation of immunotoxicity of engine exhausts is currently based on expensive and time-consuming experiments. It is desirable to develop efficient methods for immunotoxicity assessment.MethodsTo accelerate the development of safe alternative fuels, this study proposed a computational method for identifying informative features for predicting proinflammatory potentials of engine exhausts. A principal component regression (PCR) algorithm was applied to develop prediction models. The informative features were identified by a sequential backward feature elimination (SBFE) algorithm.ResultsA total of 19 informative chemical and biological features were successfully identified by SBFE algorithm. The informative features were utilized to develop a computational method named FS-CBM for predicting proinflammatory potentials of engine exhausts. FS-CBM model achieved a high performance with correlation coefficient values of 0.997 and 0.943 obtained from training and independent test sets, respectively.ConclusionsThe FS-CBM model was developed for predicting proinflammatory potentials of engine exhausts with a large improvement on prediction performance compared with our previous CBM model. The proposed method could be further applied to construct models for bioactivities of mixtures.