## 3 Results and Discussion
The graphene contacts are made under the metal layers and, thus, cannot be analyzed with Raman spectroscopy, although visual SEM inspections indicate a smooth and uniform surface. On the other hand, graphene non-uniformity has been reported as a result of wet PMMA transfers and could also have been the cause of the variation of contact resistance observed here [71]. As a point of comparison, Table 2 shows published large-scale integrated graphene-based devices, their process yield, and the most significant electrical results with their corresponding variation and non-uniformity. As seen in Table 2, variation and non-uniformity between devices can be observed across different graphene-based processes with typical NU values of 150% to 300%. Similar variation is reported across a broad range of processes including top, bottom, or buried gates and in processes targeting high-frequency performance and/or large-area sensors. This work, which is based on a buried local gate process, resulted in a non-uniformity as high as 93% on mobility values. In contrast, the work from [PERSON] et al., which was based on a top gate process, reported a non-uniformity of 300% in mobility [34]. [PERSON] et al. reported the fabrication of global back-gate GFET sensors with hole mobility non-uniformities of 200% [36]. [PERSON] et al. reported the fabrication and test of LIG gas sensors with a non-uniformity of 209% for device sensitivity to benchmarked gases [19]. \begin{table}
\begin{tabular}{c c c c c c} \hline \hline
**Measurement** & **R\({}_{c,\mathbf{p}}\) (k\(\Omega\))** & \(\mu_{\mathbf{0,p}}\) **(cm\({}^{2}\)/V\(\cdot\)s)** & **R\({}_{c,\mathbf{n}}\) (k\(\Omega\))** & \(\mu_{\mathbf{0,n}}\) **(cm\({}^{2}\)/V\(\cdot\)s)** & **n\({}_{0}\) (cm\({}^{-2}\))** \\ \hline No pulse (forward) & 1.37 & 185 & 3.45 & 240 & 3.52 \(\times\) 10\({}^{12}\) \\ \hline No pulse (reverse) & 1.67 & 285 & 3.07 & 355 & 3.18 \(\times\) 10\({}^{12}\) \\ \hline Pulse 0 V (forward) & 1.2 & 157 & 3.5 & 210 & 4.02 \(\times\) 10\({}^{12}\) \\ \hline Pulse 0 V (reverse) & 1.65 & 255 & 3.5 & 335 & 3.52 \(\times\) 10\({}^{12}\) \\ \hline Pulse \(-\)10 V (forward) & 1.41 & 165 & 3.5 & 215 & 3.92 \(\times\) 10\({}^{12}\) \\ \hline Pulse \(-\)10 V (reverse) & 1.65 & 182 & 4 & 255 & 3.81 \(\times\) 10\({}^{12}\) \\ \hline \hline \end{tabular}
\end{table} 
Table 1: Extracted parameters of contact resistance, mobility, and density of carriers at Dirac point for a device from this technology. Figure 7: Total device resistance obtained with forward (fwd) and backward (bwd) sweeps of V\({}_{\text{GS}}\) applied with (**a**) no bias stress, (**b**) a pulsed V\({}_{\text{GS}}\) = 0 V prior to measurement, and (**c**) a pulsed V\({}_{\text{GS}}\) = \(-\)10 V prior to measurement. Markers are experimental data and lines are modeling results. As show in this work through SEM, Raman, AFM, and model fitting, the roughness on the underlying surface of graphene plays a major role in the performance of the device as previously reported [66]. In addition, the graphene transfer process may induce defects or leave residues in the active and contact areas leading to additional variation. The presented analysis provides a framework with which other researchers can analyze and correlate device variation and non-uniformities while methods to reduce this variability are investigated. Device-to-device variability may be mitigated or improved with the use of smoother surfaces that would be beneficial for the fabrication of graphene-based FETs, as well as a more rigid transfer medium than PMMA that does not induce physical defects in the graphene during the transfer process. Advanced techniques such as thermal annealing and electron beam-induced cleaning have been reported to assist in an effective removal of PMMA residue that may induce device to device variabilities [72]. Techniques to obtain a smoother surface include improved deposition techniques, electro-polishing, and/or the use of hBN [29; 67].