Effective production of γ-valerolactone from biomass-derived methyl levulinate over CuO_x-CaCO_3 catalyst

The production of?-valerolactone(GVL)from lignocellulosic biomass has become a focus of research owing to its potential applications in fuels and chemicals.In this study,(n)CuOx-CaCO3(where n is the molar ratio of Cu to Ca)compounds were prepared for the first time and shown to function as efficient bifunctional catalysts for the conversion of biomass-derived methyl levulinate(ML)into GVL,using methanol as the in-situ hydrogen source.Among the catalysts with varied Cu/Ca molar ratios,(3/2)CuOx-CaCO3 provided the highest GVL yield of 95.6% from ML.The incorporation of CaCO3 with CuO resulted in the formation of Cu+species in a CuOx-CaCO3 catalyst,which greatly facilitated the hydrogenation of ML.Notably,CuOx-CaCO3 also displayed excellent catalytic performance in the methanolysis products of cellulose,even in the presence of humins.Therefore,a facile two-step strategy for the production of GVL from cellulose could be developed over this robust and inexpensive catalyst,through the integration of cellulose methanolysis catalyzed by sulfuric acid,methanol reforming,and ML hydrogenation in methanol medium.

基于自由体积理论的沥青分子模型黏度预测

沥青的黏度特性由化学结构决定.然而,目前在分子层面上对沥青动态黏度机理的认识并不清晰.本文采用分子动力学(molecular dynamic,MD)模拟,从自由体积的角度研究了沥青的黏度.基于一定范德瓦耳斯(van der Waals,vdW)半径下的自由体积预测,计算得到了沥青模型黏度与温度之间的关系.结果表明,沥青的动态黏度与自由体积有关;沥青模型的自由体积随vdW半径、沥青模型类型等参数变化,随vdW半径的减小而增大;单组分模型的自由体积明显大于多组分模型.利用不同半径的自由体积对沥青的动态黏度进行了预测,当vdW半径为1.39?时计算出来的自由体积预测的沥青模型黏度平均偏差最低.此外,不同沥青模型的平均偏差不同,四组分模型的平均偏差最小.黏度测试结论与模拟结果吻合较好,说明MD结果是可靠的.本文有助于理解沥青黏度的微观机理及其与分子结构间的关系.

Study on the influence of skid resistance on traffic safety of highway with a high ratio of bridges and tunnels

The safety of highways with a high ratio of bridges and tunnels is related to multiple factors,for example,the skid resistance of the pavement surface.In this study,the distribution of accidents under different conditions was calculated to investigate the relationship between the road skid resistance and the incidence of traffic accidents based on the traffic accident data of the Yuxiang highway.Statistical results show that weather conditions and road alignment may affect traffic accidents.The correlation analysis method was used to study the relationship between three factors and traffic accidents.The results show that road alignment,weather conditions and road skid resistance are related to the incidence of traffic accidents.The traffic accident prediction models were established based on back propagation neural network to verify the correlation analysis results.It is confirmed that road alignment,weather conditions and road skid resistance are the factors that affect traffic accidents.