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Abstract The research of electric thermal storage (ETS) has attracted a lot of attention recently, which converts off-peak electrical energy into thermal energy and release it later at peak hours. In this study, new electric thermal storage composites are developed by employing paraffin wax as thermal storage media and carbon nanofiber (CNF) as conductive fillers. Electric heating and thermal energy release performances of the CNF/paraffin wax composites are experimentally investigated. Experimental results show that, when the composites are heated to about 70 °C, the developed electrically conductive CNF/paraffin wax composites present a thermal storage capacity of about 280 kJ/kg, which is five times of that of traditional thermal storage medium such as ceramic bricks (54 kJ/kg). The CNF/paraffin wax composites can also effectively store the thermal energy and release the thermal energy in later hours.

Abstract Hydrolysis of lignocellulosic biomass is important for isolation of glucose in a biorefinery. In this research, intermittent ball milling was applied to facilitate and enhance enzymatic hydrolysis of dilute acid-pretreated lignocellulosic biomass, with the highest glucose yield of 66.5% at a low enzyme dose (10 FPU g−1 glucan) over 24h. In comparison, the yield for the typical liquid-state enzymatic hydrolysis was only 38.7% for 24h, although it reached 69.0% after 72h. Glucose yield increased further to 84.7% using the delignified lignocellulosic biomass after a 24 h intermittent ball milling process. The observed glucose yield (24h) is comparable to the desired 80% (72h) milestone yield set by the US DOE but only with a three times shorter processing time despite the differences in experimental conditions. Further, the amount of solvent needed for the intermittent ball milling process was 25-folds reduced, compared with typical hydrolysis. Intermittent ball milling was useful for enhancing the performance of enzymatic hydrolysis with favorable adsorption of enzymes into cellulose. It also exhibited high efficiency in enzymatic hydrolysis of lignocellulosic biomass relative to continuous ball milling. It was suggested that ball milling could help distribute enzymes into cellulose, however, continuous ball milling would simultaneously separate enzymes from cellulose before the completion of hydrolysis. Therefore, intermittent ball milling could facilitate enzymes distribution and leave enough time for them to consume the boned cellulose chains. This technology should be beneficial for development of more effective and environmentally benign approaches to enzymatic hydrolysis to effectively isolate glucose from lignocellulosic biomass.

A Lignin-Mediated Fenton (LMF) mechanism for low temperature generation of formaldehyde from wood is described where low levels of iron (ubiquitous in the environment) participate in oxygen radical generation which then initiates attack on lignin.

Large numbers of plant cell-wall (CW)-related genes have been identified or predicted in several plant genomes such as Arabidopsis thaliana, Oryza sativa (rice), and Zea mays (maize), as results of intensive studies of these organisms in the past 2 decades. However, no such gene list has been identified in switchgrass (Panicum virgatum), a key bioenergy crop. Here, we present a computational study for prediction of CW genes in switchgrass using a two-step procedure: (i) homology mapping of all annotated CW genes in the fore-mentioned species to switchgrass, giving rise to a total of 991 genes, and (ii) candidate prediction of CW genes based on switchgrass genes co-expressed with the 991 genes under a large number of experimental conditions. Specifically, our co-expression analyses using the 991 genes as seeds led to the identification of 104 large clusters of co-expressed genes, each referred to as a co-expression module (CEM), covering 830 of the 991 genes plus 823 additional genes that are strongly co-expressed with some of the 104 CEMs. These 1653 genes represent our prediction of CW genes in switchgrass, 112 of which are homologous to predicted CW genes in Arabidopsis. Functional inference of these genes is conducted to derive the possible functional relations among these predicted CW genes. Overall, these data may offer a highly useful information source for cell-wall biologists of switchgrass as well as plants in general.

Abstract Thermoelectric generator is a device taking advantage of the temperature difference in thermoelectric material to generate electric power, where the higher the temperature difference of the hot-cold ends, the higher the efficiency will be. However, higher temperature or higher heat flux upon the hot end will cause strong thermal stress which will negatively influence the lifecycle of the thermoelectric module. This phenomenon is very common in industrial applications but seldom has research work been reported. In this paper, numerical analysis on the thermodynamics and thermal stress performance of the thermoelectric module has been performed, considering the variation on the thickness of materials; the influence of high heat flux on thermal efficiency, power output, and thermal stress has been examined. It is found that under high heat flux imposing upon the hot end, the thermal stress is so strong that it has a decisive effect on the life expectation of the device. To improve the module’s working condition, different geometrical configurations are tested and the optimum sizes are achieved. Besides, the side effects on the efficiency, power output, and open circuit voltage output of the thermoelectric module are taken into consideration.

Abstract A mathematical model was established to analyze the heat transfer and thermal stress behavior of a segmented thermoelectric generator (STEG). Temperature gradient-induced thermal stress was studied with non-uniform steady heat flux (including Gaussian heat flux and parabolic heat flux), uniform heat flux, and transient heat flux applied to the surface of the hot end, respectively. The results showed that the heat fluxes applied to the hot end lead to uneven temperature distribution on the whole surface of the thermoelectric generator. Thermal stress in the horizontal direction is the major cause of fatigue damage and failures of STEG. When the heat concentration ratio increases, the horizontal temperature uneven distribution will also increase. The thermal stress on the hot end varied significantly reaching the maximum value as high as 16.3 GPa. In addition, the transient heat stress in the system gives rise to periodic stress fluctuations up to 0.6 GPa, which can seriously affect the life cycle of the system.

Abstract Different kinds of catalysts have a great influence on the characteristics and products of the biomass catalytic pyrolysis. Catalysts of Cu/C, Pd/C, Pd Ag and H-Zeolites socony mobil #5 (HZSM-5) were selected and characterized by the X-ray diffraction (XRD) and field-emission scanning electron microscope (FE-SEM). Decomposition behaviors of the larch catalytic pyrolysis were studied by the thermogravimetric analyzer (TG). The total carboxylic acids (TCAs) and total phenolic compounds (TPCs) in bio-oil were determined using the non-aqueous potentiometric titration method. The chemical distribution of bio-oil was investigated by the gas chromatography/mass spectrometry (GC/MS). Results showed that the temperature of the maximum weight loss rate of larch was decreased by adding these four catalysts. The carbon residue rate was increased by using HZSM-5. The content of GC-detected phenols increased from 25.28% to 35.11% (area) by adding Pd/C. However, TCAs in bio-oil were decreased sharply with Pd Ag and Pd/C. HZSM-5 promoted the formation of phenols and enhanced TPCs in bio-oils (26.56 wt%), which increased by approximately 35% compared to that from the non-catalytic pyrolysis process. This phenol-rich bio-oil can be used to replace the traditional phenol for the manufacturing of high-value biomaterials.

Abstract This work emphases the influence of using different heating sources (direct thermal, solar, infrared, microwave heating) on the pyro-oil yield. The effect of the dominating process parameters, namely the heating rate and final temperature, are thoroughly discussed with respect to the heating and reaction mechanism involved. Emphasis is then placed on reviewing the application of microwave (MW) heating in pyrolysis as a relatively new technology with many promising features, particularly the little-known mechanisms of MW heating, new MW heating pattern and pathway using MW absorbents for pyrolysis of waste materials. Machine learning (ML) techniques were then used to statistically analyze the 182 observations in 59 pyrolysis cases obtained from previous pyrolysis practices. The ML linear regression model was developed to predict oil yield by five input variables (feedstock type, feedstock size, heating rate, final temperature, and heating source), which can be used as a guideline for pyrolysis production management. By comparing three heating sources (direct, solar and MW), MW heating is found to be the most efficient method to achieve the highest oil yield. The Decision Tree Analysis demonstrates that the importance order for key variables is as: Log feedstock size > Log heating rate > Heating rate > Temperature > Feedstock size > Heating sources > Feedstock type. Future work should focus on optimizing the heating method and heating rate to achieve optimal yield and quality of pyro-oil. The findings are envisaged to be useful for scaling up the pyrolysis of waste materials for industrial energy applications.