# Progressive Cellular Architecture in Microscale Gas Chromatography for Broad Chemical Analyses
## 5 Discussion and Conclusions  
Overall, the experimental results show that PCA3 mv effectively separated analytes with good resolution (\(R_{\rm s}>2.3\)) over a wide range of volatility covering RI 370-1500. Compared to previously reported representative \(\upmu\)GCs (such as [11; 12; 17; 23; 24]), the PCA3 mv results covered analytes with a larger span of retention index while maintaining high separation resolution over the entire span. Further, the PCA3 mv separations only required an average column temperature of 42 \({}^{\circ}\)C and a duration of 12 min, both of which are smaller than those reported for other \(\upmu\)GC architectures [11; 23; 24] underscoring the potential for lower energy consumption. Among the representative one-dimensional \(\upmu\)GCs, [PERSON] [11] reported analytes over an RI range of 590-1183, using an average column temperature of 70 \({}^{\circ}\)C and a duration of 15 min. [PERSON] [12] reported an RI range of 370-1200, using 65 \({}^{\circ}\)C and only 3 min, but in the RI range of 370-500 the separation was less effective (with \(R_{\rm S}<1\)). [PERSON] [17] reported separations performed at room temperature within 10 min, but the analyzed range was smaller (with 500 \(<\) RI \(<\) 1000) and the \(R_{\rm S}\) was modest (\(\approx\)1) for the RI range of 500-600. The representative two-dimensional \(\upmu\)GCs [23; 24] provided adequate separation (with \(R_{\rm S}\geq 1.4\) for most pairs of tested analytes) over relatively small RI ranges (524-831 in [23] and 600-1200 in [24]), while requiring higher average column temperatures of 50-80 \({}^{\circ}\)C and longer separation durations of 14-17 min. The experimental results of the PCA3 mv also showed in humidity tests that Cell 2 and Cell 3 were minimally affected; this was expected because of the lower water sorption of the sorbents used in Precon2 and Precon3 [56]. At 80% RH (Figure 12), the disappearance of the IPA peak in Cell 1 was likely caused by the adsorption of water molecules by the hydrophilic sorbent Carboxen(tm) 1000 in Precon1 [57]. This can be potentially addressed by using a hydrophobic sorbent (e.g., Carboxen(tm) 1003). A characteristic of note for highly adsorptive analytes such as DMMP and DEMP was the peak tailing, where the trailing fraction of the peak was significantly wider than the leading fraction, especially at a height close to the baseline (Figure 9). This can be attributed to surface adsorption in the flow path. It can be reduced in the future by improving the heating uniformity and surface deactivation of the flow path. It can also be reduced by further monolithic integration, which would reduce the fluidic connections. Some analytes such as 1-butanol, toluene, ethylbenzene, benzene, and o-xylene, appeared in two neighboring cells. For these analytes, a primary cell could be identified as the cell that provided sufficient retention of the analytes or dominated the fractional distribution of the analyte molecules. For the more volatile 1-butanol, benzene, and toluene, the peaks in Cell 3 appeared early (within the first 40 s) without proper retention; hence, these peaks should simply be ignored in favor of the corresponding peaks in Cell 2, which represented sufficient retention. For the less volatile ethylbenzene and o-xylene, Cell 3 provided proper separation that was similar to Cell 2 but with larger peak heights; hence, Cell 3 should be used as the primary cell. To the extent that the distribution of the analytes between two cells was deterministic over certain operating conditions, quantitative analysis of these analytes can be provided by calibrating the primary cell for the fractional distribution in addition to the peak heights. For the construction of a chemical library, retention parameters (i.e., retention times at prescribed temperature and flow rate) can be extracted from the primary cell, similar to the process used for conventional one-dimensional architectures. Therefore, although such cross-cell distributions may be a disadvantage, their negative impact is limited and controllable.