A combination of four instrumental systems and five chemometric methods are shown to improve the efficiency and resolving power (i.e. peak capacity/ peak capacity production) of multi-dimensional gas chromatography (MDGC) as well as provide straightforward, easily interpretable chemical information. Implementation of a high speed pulse flow valve for two-dimensional gas chromatography (GC × GC) is shown to provide ultra-fast modulation with modulation periods (P[subscript]M) as short as 50 ms. Using a commercially available pulse flow valve, this injection technique performs a combination of vacancy chromatography and frontal analysis, whereby each pulse disturbance in the analyte concentration profile as it exits the first column (1D) results in data that is readily converted into a second separation (2D). A three-step process converts the raw data into a format analogous to a GC × GC separation, incorporating signal differentiation, baseline correction and conversion to a GC × GC chromatogram representation. For a P[subscript]M of 250 ms, the apparent peak width on the 2D, 2W[subscript]b, ranged from 12 to 45 ms producing a 2D peak capacity, 2n[subscript]c, of ~ 10, and the total peak capacity, n[subscript]c,2[subscript]D, was 4300 or a peak capacity production of 650 peaks/min. Next, the use of a high temperature diaphragm valve as a modulator for GC × GC facilitated separation temperatures up to 325 °C. Previous diaphragm valve technology limited use to 175 °C if the valve was mounted in the oven or to 265 °C if the valve was face mounted on the outside of the oven. A 44-component mixture was evaluated and the diaphragm valve created narrow, reproducible peaks on the 2D dimension leading to a peak capacity production of 300 peaks/min and had minimal retention time shifting on the 1D and 2D dimensions. In addition, the high temperature diaphragm valve was shown to increase the detection sensitivity by ~8 times compared to one-dimensional gas chromatography due to zone compression. Furthermore, the high temperature diaphragm valve was proven to be compatible with time-of-flight mass spectrometry (TOFMS). Finally a combination of the high temperature diaphragm valve and pulse flow valve yielded a three-dimensional gas chromatography system (GC3) that had a peak capacity production of 1000 peaks/min which is a ~5 times increase in efficiency compared to other GC3 systems. Investigation of novel chemometric techniques for the analysis of GC × GC is shown to be beneficial in extracting useful chemical information from complicated samples. Kerosene-based rocket fuels were analyzed via a GC × GC – FID system that implemented a high temperature diaphragm valve as a modulator. Using leave-one-out cross validation (LOOCV), the summed GC × GC – FID signal of three compound-class selective 2D regions (alkanes, cycloalkanes, and aromatics) was regressed against previously measured ASTM derived values. Additionally, a more detailed partial least squares (PLS) analysis was performed on compound classes (n-alkanes, iso-alkanes, mono-, di-, and tri-cycloalkanes, and aromatics) as well as the physical properties previously determined by ASTM methods (such as net heat of combustion, hydrogen content, density, kinematic viscosity, sustained boiling temperature and vapor rise temperature). The resulting models had low root mean square errors of cross validation (RMSECV) and had similar outcomes to previously reported results using a GC × GC – TOFMS. Using the information gained from the study, a more extensive study of predicting four physical properties (e.g., viscosity, heat of combustion, hydrogen content, and density) was undertaken using 74 different kerosene-based fuels. Highly reliable PLS models were developed that related chemical composition obtained via GC × GC – TOFMS to fuel properties obtained via ASTM methods. The PLS prediction of the four physical properties (e.g., viscosity, heat of combustion, hydrogen content, and density) had relatively low errors of RMSECV values of 0.0434, 38.1, 0.112, and 0.0037, respectively. Investigation of the linear regression vectors (LRVs) indicate the relationship between the chemical composition and physical properties enabling the chemical compositions of fuels to be altered to meet certain industrial specifications. Using a similar fuel set comprised of 36 kerosene-based fuels, the thermal stability was evaluated using a novel instrument, CRAFTI (Compact Rapid Assessment of Fuel Thermal Integrity). Using a chemometrics-based feature discovery algorithim, the chemical information obtained via GC × GC – TOFMS was correlated to the thermal integrity data. Certain forms of carbon that were deposited within the test article of the CRAFTI instrument were found to strongly correlate with increased backpressure and some of the more prevalent compounds were identified. Next, tile-based Fisher ratio (F-ratio) analysis was applied to tandem ionization time-of-flight mass spectrometry (TI – TOFMS) in order to enhance discovery-based analyses. A hard ionization energy (70 eV) and soft ionization energy (14 eV) were collected concurrently, and the discovery of 12 analytes spiked in diesel fuel was shown to be improved when the two ionization energies were used in tandem resulting in a higher discovery rate while also lowering the number of false positives. Using parallel factor analysis (PARAFAC) the analytes that were “discovered” were deconvoluted in order to obtain their identification via match values. Lastly, the limit of detection (LOD) and limit of quantification (LOQ) were improved by a novel integration method. Signal to noise (S/N) enhancement was theoretically studied using simulations and both the LOD and LOQ can be lowered by a factor of 3. When compared to the two-step, a commonly applied method for quantifying one-dimensional and two-dimensional, the integration method resulted in more accurate and precise measurements at low S/N.