In situ hydrodeoxygenation of heavy bio-oil using a Ce/Fe-based oxygen carrier in methanol-zero valent aluminum media.

Resource recovery from solid organic wastes, such as degradable plastics, and upgrading raw bio-oil are important ways for reducing carbon and pollution emissions. Hydrodeoxygenation (HDO) is a common thermochemical treatment to upgrade crude bio-oil. In this study, in order to realize in situ HDO during the hydropyrolysis of heavy bio-oil and degradable plastics, a reduced Fe/Ce oxygen carrier (OC) was used to catalytically remove oxygen from organics under the methanol-zero valent aluminum (ZV Al) media, where the hydrogen was produced during pyrolysis instead of a direct hydrogen supply. The results showed that the reduced OC captured the oxygen from the pyrolysis products of heavy bio-oil and degradable plastic, representing the multi-selectivity of reduced OC to phenols, ketones, etc. The ZV Al system promoted the production and utilization of hydrogen, as evidenced by the increased hydrogen content in gas phase and hydrocarbon content in liquid phase. The hydrocarbon component distribution in the liquid phase increased clearly when hydropyrolysis with degradable plastics addtion, but the excess degradable plastics addition caused increasing of the liquid product viscosity, and decreasing of the liquid products yield for the higher ash content in degradable plastic, and a higher ZV Al amount was required to maintain the hydropyrolysis. Molecular dynamics simulations verified the synergistic effect of degradable plastics and bio-oil by the pyrolysis behavior in different systems and temperatures, and the pyrolysis pathways were proposed. This non-autocatalytic system realized the resource recovery and heavy bio-oil upgrading using an Fe/Ce OC.

Mechanism Analysis and Self-Adaptive RBFNN Based Hybrid Soft Sensor Model in Energy Production Process: A Case Study.

Despite hard sensors can be easily used in various condition monitoring of energy production process, soft sensors are confined to some specific scenarios due to difficulty installation requirements and complex work conditions. However, industrial process may refer to complex control and operation, the extraction of relevant information from abundant sensors data may be challenging, and description of complicated process data patterns is also becoming a hot topic in soft-sensor development. In this paper, a hybrid soft sensor model based mechanism analysis and data-driven is proposed, and ventilation sensing of coal mill in a power plant is conducted as a case study. Firstly, mechanism model of ventilation is established via mass and energy conservation law, and object-relevant features are identified as the inputs of data-driven method. Secondly, radial basis function neural network (RBFNN) is used for soft sensor modeling, and genetic algorithm (GA) is adopted for quick and accurate determination of the RBFNN hyper-parameters, thus self-adaptive RBFNN (SA-RBFNN) is proposed to improve the soft sensor performance in energy production process. Finally, effectiveness of the proposed method is verified on a real-world power plant dataset, taking coal mill ventilation soft sensing as a case study.

Study on diffusion mechanism and failure behavior of epoxy coatings focusing on synergistic effect of temperature and water molecules.

The research on the diffusion of water in coatings has been a hot topic in many fields, such as chemistry, coating structure and hydrogen bonding. In this paper, DGEBA epoxy coating was used as a sample to explore the diffusion process of 3 wt.% NaCl solution at different temperatures. Two-stage diffusion was established by immersion experiment and MD simulation. The synergistic effect of temperature and water on DGEBA properties was revealed by FTIR method and adsorption-desorption cyclic testing. The results showed that as the temperature increased, the saturation water content in coatings increased. At different temperatures, the diffusion process of water presented two-phase characteristics, and the influence of temperature on the diffusion process was mainly manifested in the cross-linking density at higher locations. Based on the variation law of swelling coefficient in per unit time (24 h), the conditions for water-coating interaction and formation of water clusters in this paper were proposed. The synergistic effect of water and temperature on DGEBA properties was reflected in two aspects: at lower temperature (20 °C), water would only change the physical structure of the coatings, while the water broke the DGEBA chains at higher temperature (60 °C).