InnovativeApproach to Improving Gas-to-Liquid FuelCatalysis via Nanosensor Network Modulation.

Fischer–Tropschsynthesis, a major process for convertingnatural gas to liquid hydrocarbons (GTL), suffers from selectivitylimitations that refer to the ratio of highly useful hydrocarbonsto the total product output. Existing strategies for selectivity improvement,such as manipulation of reactor operating conditions (temperature,pressure, etc.) and catalyst design variables may be classified astop-down approaches. In this work, a bottom-up approach is proposedin which surface processes can be controlled via a nanosensor network(NSN) involving the turning on or off of elementary steps creatingundesired species and redirection of surface efforts to step(s) leadingto the desired products. The overall effect of these nanolevel communicationsoffers superior selectivity to that hitherto possible by reducingthe rate of hydrogenation of surface unsaturated species to paraffin(HTP) reactions. Our numerical and simulation results confirm substantialimprovement of overall selectivity in a catalyst that is equippedwith a highly reliable NSN. [ABSTRACT FROM AUTHOR]