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The wide-scale application in the bio-fuel area of fatty acid methyl esters (FAME) has been limited because of its high oxygen content, awful low temperature flowability, and low heating value. In this work, the hydrodeoxygenation (HDO) of methyl palmitate as fatty acid methyl ester model compounds for long-chain alkane via Nb2O5 modified NiAl2O4 catalysts was investigated. The effect of Nb/Ni atomic ratio (0.05:0.30), reaction temperature (260–340 ℃), time (2–10 h), and H2 pressure (1–5 MPa) on the production of long-chain alkane is exhaustively researched. The results show that the products are mainly pentadecane with a few other alkane hydrocarbons and nickel metal was the main active site. Besides, the added promoter Nb promoted the dispersion of active metal Nickel, increased the acidity, and thus substantially enhanced the HDO activity of methyl palmitate. In response to the best conditions (0.3 g catalyst, 3 g methyl palmitate), the methyl palmitate conversion and pentadecane selectivity over Nb2O5-NiAl2O4 with 0.20 Nb/Ni atomic ratio reached 91.14% and 80.07%, respectively. However, the methyl palmitate conversion and pentadecane selectivity over pure NiAl2O4 catalyst were only 62.53% and 74.67%, respectively. Therefore, Nb2O5-NiAl2O4 catalysts exhibit remarkable catalytic ability for HDO of methyl palmitate to alkanes. The low cost, easy preparation, high catalytic performance, and recycling stability of Nb2O5-NiAl2O4 catalyst demonstrate that catalyst Nb2O5-NiAl2O4 is a promising effective and efficient catalyst for producing long-chain alkane from methyl palmitate. [ABSTRACT FROM AUTHOR]

Surface roughness is an important factor that affects dynamic wetting behavior, which can improve the surface hydrophobicity, so it is of great significance to obtain a better understanding of roughness effect from both theoretical and practical perspectives. In this paper, we studied the influence of macro-size surface roughness on contact angle hysteresis and spreading work and analyzed the relationship between contact angle hysteresis and spreading work. Results showed that as the surface roughness increased, both the advancing contact angle and the receding contact angle continued to increase until their maximum values were reached, and then started to decrease within the range of surface roughness studied, while the contact angle hysteresis presented the opposite trend. In addition, with the increase of surface roughness the spreading work initially increased to a certain maximum value, then continuously decreased to the minimum value, and then began to increase within the range of the surface roughness studied. These trends could be attributed to the surface wetting state (Wenzel state, Cassie state, and transition state) changing with the change of surface roughness. These findings can provide guidance for the preparation of wetted surfaces with specific functions, especially when it is required to change the wettability without changing the surface chemical properties. [ABSTRACT FROM AUTHOR]

Inspired by the total margin algorithm, we extend balanced relative margin machine (BRMM) by introducing surplus variables, and propose a total margin based balanced relative (TM-BRMM). TMBRMM not only solves the loss of information points involved, but also addresses outliers at the outer boundaries that limit the maximum distance from points to separating hyperplane. Furthermore, by means of kernel function, it is easy to solve nonlinear separable datasets. The experiments on UCI datasets verify the feasibility and superiority of TM-BRMM. [ABSTRACT FROM AUTHOR]