Gas chromatography (GC) is an analytical chemistry tool used to determine the chemical composition of a gas sample by separating sample analytes as they travel through a GC column. Recent efforts have been made to understand and control gas chromatography separations with a negative thermal gradient on the column. The present work presents results from thermal gradient GC separations on two GC columns in different configurations (serpentine and radial) in a stainless-steel plate. Methods to fabricate the GC systems capable of isothermal, temperature programmed and thermal gradient separations are presented. Isothermal experimental data from the serpentine column were used to fit retention and dispersion parameters in a transport model that simulates GC separation for hydrocarbons C12-C14. Transport model simulated retention times and peak widths matched experimental values well for isothermal, temperature programmed and thermal gradient separations. The validated transport model was used to study the effect of static (not varying temporally) thermal gradients on GC separations with varying injection widths, injection band shapes and stationary phase thickness. Resolution results from different heating conditions were considered comparable if retention times for each analyte were within 5%. An optimal, static thermal gradient is shown to reduce analyte band spreading from axially-varying velocity gradients with resolution improvements over isothermal separations of up to 8% for analytes with similar retention factors. Static thermal gradients have a larger effect on fronting peak shape than tailing peak shape. Stationary phase distribution acts similar to a velocity gradient and can be corrected by a thermal gradient. Another transport model was created from isothermal experimental data on a commercial column for hydrocarbons C12-C20. An optimal, static thermal gradient does not improve resolution for all analyte pairs. An optimal, dynamic (varying tempo-rally) thermal gradient is created by uniformly increasing the temperature on an optimal, static thermal gradient. Improvements in resolution of up to 20% are achievable over temperature programmed GC separation. A dynamic thermal gradient can also correct for a poor sample injection by creating a temperature trap at the beginning of the column.