Extraction of SnO Subbandgap Defect Density by Numerical Modeling of p-Type TFTs

Recently, p-type tin monoxide (SnO) thin-film transistors (TFTs) have gained interest for all-oxide complementary metal–oxide semiconductor (CMOS) circuits for flexible electronics and back-end-of-line integration with Si. However, most SnO TFTs demonstrated so far exhibit a low on– off-current ratio and limited field effect mobility. To understand and improve SnO TFT performance, it is necessary to quantitatively characterize the subbandgap defects in SnO and at its dielectric interface. In this work, we establish numerical models which provide this understanding. By concurrent fitting of simulated
${I}_{\text{D}}$
–
${V}_{\text{GS}}$
and effective mobility versus
${V}_{\text{GS}}$
to experimentally measured data, we can accurately extract SnO defect state profiles. Using the extracted simulation models, we then identify ways to improve SnO TFT performance. Specifically, a reduction in the density of shallow, bulk Gaussian acceptor states, is necessary to reduce the off-current, while reducing the contact resistance and interface donor-like tail state density can improve the SnO field effect mobility.