Machine learning prediction on adsorption capacities of steam methane reforming off-gas in silica gels

Deep neural networks have achieved excellent performance in predicting the adsorption capacity of steam methane reforming gas on silica gel, thereby reducing experimental costs and improving the prediction efficiency of adsorption isotherms.