Supported molybdenum carbide for higher alcohol synthesis from syngas

Molybdenum carbide supported on active carbon, carbon nanotubes, and titanium dioxide, and promoted by K2CO3, has been prepared and tested for methanol and higher alcohol synthesis from syngas. At optimal conditions, the activity and selectivity to alcohols (methanol and higher alcohols) over supported molybdenum carbide are significantly higher compared to the bulk carbide. The CO conversion reaches a maximum, when about 20 wt% Mo2C is loaded on active carbon. The selectivity to higher alcohols increases with increasing Mo2C loading on active carbon and reaches a maximum over bulk molybdenum carbide, while the selectivity to methanol follows the opposite trend. The effect of Mo2C loading on the alcohol selectivity at a fixed K/Mo molar ratio of 0.14 could be related to the amount of K2CO3 actually on the active Mo2C phase and the size, structure and composition of the supported carbide clusters. Unpromoted, active carbon supported Mo2C exhibits a high activity for CO conversion with hydrocarbons as the dominant products. The K 2CO3 promoter plays an essential role in directing the selectivity to alcohols rather than to hydrocarbons. The optimum selectivity toward higher alcohols and total alcohols is obtained at a K/Mo molar ratio of 0.21 over the active carbon supported Mo2C (20 wt%)

How can dairies maximize their profits and properly remunerate their dairy farmers?

ABSTRACT The current pricing process of raw milk in Brazil discourages producers from improving milk composition, which affects both yield and quality of dairy products. Furthermore, small and medium-sized dairies face great difficulties when it comes to planning production. Thus, a linear programming model was developed to price the raw milk and determine the optimal mix (combination of quantities) of dairy products that maximizes total contribution margin (TCM) under daily scenarios of high (January) and low (July) raw milk supplies (summer and winter, respectively) by comparing optimal solutions with actual results. The TCM of optimal and actual mixes were higher in January due to the greater availability of raw material. Packaging was a limiting factor in the production of cheese in optimal mixes. The relationship between unit contribution margin (UCM) and the required amount of raw materials per product unit and resource availability is crucial to defining the mix of dairy products and TCM of the dairy. Casein and raw milk volume showed shadow prices. Under both scenarios, the calculated prices of raw milk were higher than the prices charged by the dairy and were higher in January. The proposed model remunerates the producers based on the quantity and quality of raw milk. The dairy can maximize its TCM by better planning its mix of products with the use of linear programming