A novel characterization method is proposed to extract the optical frequency field-effect mobility () of transparent conductive oxide (TCO) materials by a tunable silicon microring resonator with a heterogeneously integrated titanium-doped indium oxide metal–oxide–semiconductor (MOS) capacitor. By operating the microring in the accumulation mode, the quality factor and resonance wavelength shift are measured and subsequently used to derive the in the ultra-thin accumulation layer. Experimental results demonstrate that the of ITiO increases from 25.3 to with increasing gate voltages, which shows a similar trend as that at the electric frequency.
© 2021 Chinese Laser Press
Metal–oxide–semiconductor (MOS) capacitors are one of the most prevailing electronic device structures, and have laid the foundation of modern transistors that have transformed the entire industry of microelectronics . In recent years, MOS devices have also gained increasing utility in photonic applications, which could pave the way for a new generation of hybrid electronic–photonic systems [2,3]. MOS-driven silicon photonic devices in particular have rapidly become one of the most promising building blocks for future optical interconnect systems due to their enhanced performance in electro-optic (E-O) modulation and scalability of fabrication [4–6]. Photonic devices based on the MOS structure usually operate in the accumulation mode. When a negative bias voltage () is applied, it induces the field effect and modifies the refractive indices of the semiconductor materials through the plasma dispersion effect so that an optical phase shift is induced to the guided light. In addition to their intrinsic advantages, MOS structures provide feasibility of heterogeneous integration with other materials such as graphene, III-V, and transparent conductive oxides (TCOs) on silicon photonics [7–9]. Of these heterogeneously integrated photonic devices, an MOS device with a TCO gate can achieve unity-order refractive index changes in the accumulation layer . Several ultra-efficient Si-TCO photonic devices have been reported using a Mach–Zehnder interferometer, an electro-absorption modulator, a photonic crystal nanocavity, and a microring resonator (MRR) [9,11–13].
Carrier mobility is one of the most pivotal properties of semiconductors, as it can determine the performance of solid-state devices. Carrier mobility represents the velocity of electrons or holes under certain electric fields, and therefore it determines the conductivity and frequency response of electronic devices such as transistors. Thus, the high mobility of semiconductors is critical to achieving high bandwidth and low power dissipation . For photonic devices, the impact of carrier mobility reaches even further. As described by the Drude model, the collision frequency [Eq. (1c)], which is the collision process between free carriers and ionized impurities in TCOs, is inversely proportional to the carrier mobility at the optical frequency [15,16]. Furthermore, the optical loss due to free carrier absorption is determined by the imaginary part of the complex permittivity [Eq. (1a)], which is influenced by the collision frequency as well. Hence, high-mobility semiconductors are critical to low optical loss waveguides. For instance, previous research has shown that high-mobility TCOs can significantly enhance the performance of photonic modulators by increasing the extinction ratio, improving the energy efficiency and quality factor ( factor) [13,17,18].
The carrier mobility of semiconductors at electrical frequency (DC or RF) is usually measured by the Hall effect. It actually measures the bulk mobility (), which is the average mobility of the entire thin film layer [19,20]. For many electronic devices, field-effect mobility () is even more critical to determining the device performance. When a bias is applied to the gate, the field effect induces accumulation or inversion layer at the surface of the semiconductor with the insulator, forming a channel of free charges that are drastically different than those in the bulk materials [10,21]. The carrier mobility in the accumulation or inversion layer, which is also called the field-effect mobility , is generally higher than because the high concentration of free carriers in the channel layer brings an electrostatic screening effect that reduces impurity coulomb scattering . This phenomenon has been verified by thin-film transistors (TFTs) , and TFTs have been used to measure the electric frequency . The measurements of the gate voltage, drain voltage, and drain current are used to extract the electric frequency . For example, experimental results show that the electric frequency of TCOs increases as the increases [24–28].
In contrast to electric frequency mobility, which is limited by ionized-impurity scattering and grain-boundary scattering, the optical frequency mobility () is insensitive to grain-boundary scattering. It is only determined by ionized-impurity scattering because the average electron path length, which is in the range of a few nanometers and under the application of a rapidly oscillating electric field, is much smaller than the grain size . By comparing the difference between electrical and optical frequency carrier mobility, we can observe the contribution from the grain-boundary scattering and ionized-impurity scattering separately . The optical frequency bulk mobility () of a semiconductor film on a thick substrate is usually characterized by a spectroscopic ellipsometry . However, ellipsometry cannot effectively measure the optical frequency field-effect mobility () due to the ultrathin accumulation layer (). The accumulation layer is only around 0.1% of the probing wavelength used in the ellipsometry, which cannot induce meaningful light–matter interaction to calculate the film’s refractive index and thickness. Therefore, a fundamentally different method is needed for the measurement of in the ultra-thin accumulation layer.
In this paper, we propose a novel characterization method to extract the of TCO materials using an MRR on a silicon-on-insulator (SOI) wafer. This method works for all TCOs and can even be applied to other types of semiconductor materials. In this paper, titanium-doped indium oxide (ITiO) is used in the experiment for characterization due to its potential for high mobility. An MOS-driven MRR is fabricated through heterogeneous integration, which can provide orders of magnitude stronger light–matter interaction compared with ellipsometry measurement. By operating the MRR in the accumulation mode with negative , the factors and resonance wavelength shift () values are measured and subsequently used to derive the in the ultra-thin accumulation channel. Experimental results in this work demonstrate that the of ITiO increases from 25.3 to with increasing negative . This proposed measurement technique will provide an effective characterization method for field-effect electro-optic devices, especially for heterogeneously integrated silicon photonic devices.
2. DESIGN AND PRINCIPLE
A. Design of ITiO-gated MOS MRR
To derive the of ITiO in the accumulation layer, an SOI waveguide MRR is driven by a hybrid MOS capacitor operating in the accumulation mode. Figure 1(a) shows the three-dimensional (3D) schematic of the ITiO-gated MOS MRR. The active region consists of a p-type Si (p-Si) waveguide, a silicon dioxide () insulation layer, and an ITiO gate. The p-Si waveguide, which is based on a rib waveguide with a 50 nm partially etched slab, also serves as the bottom substrate of the MOS capacitor with the connection to the ground metal electrodes. The covers the p-Si MRR as the oxide layer and the ITiO layer acts as the top gate, which is connected to the gate electrode. The optical properties of TCO materials can be described by the Drude model :
The plasma frequency () is related to the carrier concentration () by
The plasma collision frequency () is related to the by1(b). Applying a negative on the ITiO gate induces electron accumulation at the interface and hole accumulation at the p- interface. This field effect changes the optical permittivities of ITiO and Si, which influences the resonance wavelengths () and factors of the silicon MRR. The factor can be written as 
The value of is related to the loss by34,35]. is affected by the loss from the accumulation layers of ITiO and p-Si when the negative is applied. Hence, applying a moderate changes while not affecting . At the critical coupling () condition, the transmission at decreases to zero [33,36]. When the loss of the MRR is fixed, the factor can be improved by working at the critical coupling condition .
The can be calculated by the change of the effective index ():
As shown in Fig. 1(a), the ITiO does not cover the whole ring. Therefore, the depends on the length of the microring covered by the ITiO electrode, which can be written as
To understand how the factor and are affected by , we simulated an ITiO-gated MOS MRR with a radius of 6 μm by the finite-difference-eigenmode (FDE) solver in Lumerical MODE software. The carrier concentration distribution is simulated by Silvaco and imported into Lumerical MODE. The simulation results are plotted with dashed lines in Fig. 1(c). When a negative is applied, it increases the , and changes the relative permittivity [Eqs. (1a) and (1b)] of ITiO, which will further modulate the effective index of the guided mode in the microring waveguide calculated by Lumerical. The reduction of the real part of blueshifts the resonance wavelength as given in Eq. (3a), while the increase of the imaginary part of the increases the optical loss and reduces the factor as explained in Eqs. (2a) and (2b). Figure 1(c) shows the downward trend of the factor and blueshift of by applying the .
B. Model Setup
In our previous work , we compared the free carrier distribution using the quantum-moment model and uniform model. The results showed that a significant difference only occurs at very large that can turn TCOs into the ENZ condition. However, we are not characterizing of TCO materials close to the ENZ condition in this paper. Approximating the numerical model by a uniform layer () in the accumulation layer can greatly simplify the analysis without sacrificing the accuracy under a moderate [38,39]. To quantify the influence of the uniform concentration, Fig. 1(c) shows the difference between the distribution and uniform concentration in the accumulation layer. Even at the maximum of , it only induces 5% difference, which is comparable to other error sources. Therefore, we believe that the uniform accumulation layer approximation, as illustrated in Fig. 2(a), can provide acceptable accuracy. The FDE module simulates the optical field intensity () of the bending waveguide with an MOS structure, and the ITiO consists of the bulk layer and accumulation layer, as shown in Fig. 2(b). The and the in the bulk layer are determined by the initial condition (). At the initial condition, there is no field effect on the ITiO, so the carrier concentration and mobility are identical in the bulk and accumulation layer (; ). To achieve the highest factor, it assumes the initial condition is at critical coupling, so equals at .
When a negative is applied, it induces the field effect and changes carrier concentration in the accumulation layer. We can sweep different to simulate different external . We have already known that the electric frequency increases under the field effect because an electrostatic screening effect reduces the ionized-impurities scattering when the concentration of accumulated free carriers increases . As the is also affected by ionized-impurities scattering, we expect that the also changes under the field effect. Hence, we can sweep and in the simulation, which will induce different , , and while running the FDE solver. and are used to calculate the factor with Eqs. (2a) and (2b), and the can be obtained from Eq. (3). After factors and are obtained from the simulation, we can plot the factor map with respect to and , as shown in Fig. 2(c). However, we can see that the factor maps are influenced by the initial conditions, i.e., and . Therefore, the final factor map will be known when the initial condition is measured from the experiment. Finally, we can measure the experimental factor and from the tunable MRR with negative to derive the by mapping the factor with the simulation results. Also, we can observe how the field effect changes the .
3. FABRICATION AND CHARACTERIZATION
A. Fabrication Processes and Testing
The ITiO-gated MRRs are fabricated on an SOI wafer. First, the bus waveguides, microrings, and grating couplers are patterned by two steps of electron beam lithography (EBL) and reactive ion etching (RIE), which has a 250 nm thick rib waveguide and a 50 nm thick slab. The MRRs have a radius of 6 μm, as shown in Figs. 3(a) and 3(b). Further, different gaps of MRRs are fabricated on the same SOI wafer to achieve the critical coupling condition. Figure 3(c) shows the experimental transmission spectrum of the passive MRR. The factor is obtained by the Lorentzian fitting to the experimental data, which is a widely adopted method to quantify high- resonators . The factor is determined by . The passive MRR has a high factor of 13,000.
Next, a 17 nm thick layer is formed by dry oxidation at 1000°C, and a 17 nm ITiO gate is deposited by radio frequency (RF) sputtering at room temperature, followed by a lift-off photolithography process. The ITiO is characterized by Hall effect measurement, which has the of and of . The layer on the Si contact region is etched by hydrofluoric (HF) acid. Finally, the Ni/Au electrodes are thermally evaporated and patterned by regular photolithography. For characterization of the ITiO-gated MOS MRRs, the input and output fibers have a tilt angle of 8°, and the polarization controller is used to make the input light in the TE mode. The light is coupled into and out from the silicon bus waveguide through the waveguide grating couplers. The gate voltage is applied through the GSG electrodes from the GSG probe. Finally, the transmission spectra with different are detected by an optical spectrum analyzer.
B. Experimental Results
In this work, the initial condition of ITiO is measured, which has the of and of . Hence, we can build the experimental factor map with these parameters ( and ), and this factor map can be used to derive the with the experimental results.
Figure 4(a) shows the experimental spectra of the normalized transmission with different negative . Experimental factors and as a function of the are plotted in Fig. 4(b), which shows that the is linearly proportional to when the is beyond . It has an average wavelength tunability of , and the factor is still higher than 4000 when it has a cumulative of 500 pm. Next, we can derive the by mapping the experimental and factor to the simulation results. Figure 4(c) plots the extraction of the .
Since this method is an indirect method to estimate the , we need to discuss its accuracy. The major error sources come from the experimental results in Fig. 4(b) with the simulation in Fig. 1(c). For the wavelength tunability, the experiment (48.5 pm/V) matches the simulation (51.9 pm/V) with a standard deviation of 7%. For the factor, we can first compare it at the initial condition () because it does not have any change of and in the accumulation layer. Therefore, we can directly see the difference between experiment and simulation when we use the same parameters. The experiment matches very well with the simulation at , which only has an error of . Even though the factor error increases when a larger gate bias is applied, it is still less than 5%. The error from the mismatch causes the error of (), which is . The other source of errors comes from the experiment measurement. The experimentally measured factors are . This standard deviation can cause a of . However, in the small region, it can even be as large as of due to the small relative change. In addition, the may have difference during the measurement, which induces of . The measurement errors from and are minor and cause of 0.7 and , respectively. The overall error of is combined with4(c) together with the mobility results. Figure 4(c) results show that the has a large fluctuation in the small region (0 to ). We can determine the accumulation mode region () from Fig. 4(b) since the is linearly proportional to in the accumulation mode . The flat band voltage () is also found to be around from the capacitance–voltage curve of the device, as shown in Fig. 4(d). This method can only achieve meaningful results when the field-effect is obvious. When the is small (0 to ), the change of the carrier concentration is relatively minor compared to the bulk concentration. Therefore, the change of the factor and are difficult to measure accurately, which induces a large fluctuation when is low. In the obvious accumulation mode region (), when the becomes larger, the measurement error does not have a significant influence. Hence, we can see that the increases steadily in the moderate to strong accumulation mode. It shows a trend of increasing from 25.3 to as the negative increases. Interestingly, a similar phenomenon is also mentioned in the TFT measurement when measuring the electric frequency , and it shows a stable growth of electric frequency in accumulation mode but not in the depletion mode [40,41]. When the larger negative is applied, it has a higher in the accumulation layer, reducing the optical absorption loss. Therefore, it can help the ITiO-gated MOS MRR maintain a good factor even though a larger negative is applied.
In conclusion, we invented a new characterization method for quantifying the in the accumulation channel by a tunable MOS-driven MRR. The proposed integrated photonic platform provides dramatically stronger light–matter interaction compared with the traditional ellipsometry measurement. By constructing a comprehensive numerical model, we generated the contour map of the factor of the MRR with respect to and by sweeping and in the simulation. Experimental results of the factor and were measured under the negative and subsequently used to derive the by mapping the data into the simulation results. Our experimental results demonstrated that the of ITiO increases from 25.3 to with increasing , which shows a similar trend in the electric frequency . This method provides a novel pathway to precisely obtain the in-device from an integrated photonics platform that has never been explored. Our approach fills the gap of existing carrier mobility characterization methods for field-effect electro-optic devices, especially for heterogeneously integrated silicon photonic devices.
National Aeronautics and Space Administration (80NSSC21K0230); National Science Foundation Directorate for Engineering (1927271); Air Force Office of Scientific Research (FA9550-17-1-0071).
The authors would like to acknowledge the Oregon State University Materials Synthesis and Characterization Facility (MASC) and Electronic Microscopy Facility for their support in device fabrication, and Prof. Janet Tate at the Department of Physics for the Hall measurement.
The authors declare no conflicts of interest.
1. C. T. Sah, “Evolution of the MOS transistor-from conception to VLSI,” Proc. IEEE 76, 1280–1326 (1988). [CrossRef]
2. H. C. Lin, W. E. Wang, G. Brammertz, M. Meuris, and M. Heyns, “Electrical study of sulfur passivated In0.53Ga0.47As MOS capacitor and transistor with ALD Al2O3 as gate insulator,” Microelectron. Eng. 86, 1554–1557 (2009). [CrossRef]
3. M. K. Kim and J. S. Lee, “Synergistic improvement of long-term plasticity in photonic synapses using ferroelectric polarization in hafnia-based oxide-semiconductor transistors,” Adv. Mater. 32, 1907826 (2020). [CrossRef]
4. A. Liu, R. Jones, L. Liao, D. Samara-Rubio, D. Rubin, O. Cohen, R. Nicolaescu, and M. Paniccia, “A high-speed silicon optical modulator based on a metal-oxide-semiconductor capacitor,” Nature 427, 615–618 (2004). [CrossRef]
5. W. Cai, J. S. White, and M. L. Brongersma, “Power-efficient electrooptic plasmonic modulators,” Nano Lett. 9, 4403–4411 (2009). [CrossRef]
6. K. Debnath, D. J. Thomson, W. Zhang, A. Z. Khokhar, C. Littlejohns, J. Byers, L. Mastronardi, M. K. Husain, K. Ibukuro, F. Y. Gardes, G. T. Reed, and S. Saito, “All-silicon carrier accumulation modulator based on a lateral metal-oxide-semiconductor capacitor,” Photon. Res. 6, 373–379 (2018). [CrossRef]
7. M. Midrio, P. Galli, M. Romagnoli, L. C. Kimerling, and J. Michel, “Graphene-based optical phase modulation of waveguide transverse electric modes,” Photon. Res. 2, A34–A40 (2014). [CrossRef]
8. J. H. Han, F. Boeuf, J. Fujikata, S. Takahashi, S. Takagi, and M. Takenaka, “Efficient low-loss InGaAsP/Si hybrid MOS optical modulator,” Nat. Photonics 11, 486–490 (2017). [CrossRef]
9. R. Amin, R. Maiti, C. Carfano, Z. Ma, M. H. Tahersima, Y. Lilach, D. Ratnayake, H. Dalir, and V. J. Sorger, “0.52 V mm ITO-based Mach-Zehnder modulator in silicon photonics,” APL Photon. 3, 126104 (2018). [CrossRef]
10. E. Feigenbaum, K. Diest, and H. A. Atwater, “Unity-order index change in transparent conducting oxides at visible frequencies,” Nano Lett. 10, 2111–2116 (2010). [CrossRef]
11. Q. Gao, E. Li, and A. X. Wang, “Ultra-compact and broadband electro-absorption modulator using an epsilon-near-zero conductive oxide,” Photon. Res. 6, 277–281 (2018). [CrossRef]
12. E. Li, Q. Gao, S. Liverman, and A. X. Wang, “One-volt silicon photonic crystal nanocavity modulator with indium oxide gate,” Opt. Lett. 43, 4429–4432 (2018). [CrossRef]
13. E. Li, B. A. Nia, B. Zhou, and A. X. Wang, “Transparent conductive oxide-gated silicon microring with extreme resonance wavelength tunability,” Photon. Res. 7, 473–477 (2019). [CrossRef]
14. S. H. Mir, V. K. Yadav, J. K. Singh, and J. K. Singh, “Recent advances in the carrier mobility of two-dimensional materials: a theoretical perspective,” ACS Omega 5, 14203–14211 (2020). [CrossRef]
15. S. D’Elia, N. Scaramuzza, F. Ciuchi, C. Versace, G. Strangi, and R. Bartolino, “Ellipsometry investigation of the effects of annealing temperature on the optical properties of indium tin oxide thin films studied by Drude-Lorentz model,” Appl. Surf. Sci. 255, 7203–7211 (2009). [CrossRef]
16. J. Ederth, A. Hultåker, G. A. Niklasson, P. Heszler, A. R. Van Doorn, M. J. Jongerius, D. Burgard, and C. G. Granqvist, “Thin porous indium tin oxide nanoparticle films: effects of annealing in vacuum and air,” Appl. Phys. A 81, 1363–1368 (2005). [CrossRef]
17. S. Campione, M. G. Wood, D. K. Serkland, S. Parameswaran, J. Ihlefeld, T. S. Luk, J. R. Wendt, K. M. Geib, and G. A. Keeler, “Submicrometer epsilon-near-zero electroabsorption modulators enabled by high-mobility cadmium oxide,” IEEE Photon. J. 9, 2723299 (2017). [CrossRef]
18. B. Zhou, E. Li, Y. Bo, and A. Wang, “High-speed plasmonic-silicon modulator driven by epsilon-near-zero conductive oxide,” J. Lightwave Technol. 38, 3338–3345 (2020). [CrossRef]
19. T. I. Kamins, “Hall mobility in chemically deposited polycrystalline silicon,” J. Appl. Phys. 42, 4357–4365 (1971). [CrossRef]
20. Y. Sago and H. Fujiwara, “Mapping characterization of SnO2:F transparent conductive oxide layers by ellipsometry technique,” Jpn. J. Appl. Phys. 51, 10NB01 (2012). [CrossRef]
21. Z. Ma, Z. Li, K. Liu, C. Ye, and V. J. Sorger, “Indium-tin-oxide for high-performance electro-optic modulation,” Nanophotonics 4, 198–213 (2015). [CrossRef]
22. K. I. Goto, T. H. Yu, J. Wu, C. H. Diaz, and J. P. Colinge, “Mobility and screening effect in heavily doped accumulation-mode metal-oxide-semiconductor field-effect transistors,” Appl. Phys. Lett. 101, 073503 (2012). [CrossRef]
23. J. F. Wager, D. A. Keszler, and R. E. Presley, Transparent Electronics (Springer, 2008).
24. R. L. Huffman, “ZnO-channel thin-film transistors: channel mobility,” J. Appl. Phys. 95, 5813–5819 (2004). [CrossRef]
25. Y. Nitzan, M. Grinshpan, and Y. Goldstein, “Field-effect mobility in quantized accumulation layers on ZnO surfaces,” Phys. Rev. B 19, 4107–4115 (1979). [CrossRef]
26. C. J. Chiu, S. P. Chang, and S. J. Chang, “Transistor using Ta2O5 gate dielectric,” IEEE Electron Device Lett. 31, 1245–1247 (2010).
27. Y. Chen, D. Geng, M. Mativenga, H. Nam, and J. Jang, “High-speed pseudo-CMOS circuits using bulk accumulation a-IGZO TFTs,” IEEE Electron Device Lett. 36, 153–155 (2015). [CrossRef]
28. Y. Shin, S. T. Kim, K. Kim, M. Y. Kim, S. Oh, and J. K. Jeong, “The mobility enhancement of indium gallium zinc oxide transistors via low-temperature crystallization using a tantalum catalytic layer,” Sci. Rep. 7, 10885 (2017). [CrossRef]
29. J. Steinhauser, S. Faÿ, N. Oliveira, E. Vallat-Sauvain, and C. Ballif, “Transition between grain boundary and intragrain scattering transport mechanisms in boron-doped zinc oxide thin films,” Appl. Phys. Lett. 90, 142107 (2007). [CrossRef]
30. H. C. M. Knoops, B. W. H. van de Loo, S. Smit, M. V. Ponomarev, J.-W. Weber, K. Sharma, W. M. M. Kessels, and M. Creatore, “Optical modeling of plasma-deposited ZnO films: electron scattering at different length scales,” J. Vac. Sci. Technol. A 33, 021509 (2015). [CrossRef]
31. H. Fujiwara and M. Kondo, “Effects of carrier concentration on the dielectric function of ZnO:Ga and In2O3:Sn studied by spectroscopic ellipsometry: analysis of free-carrier and band-edge absorption,” Phys. Rev. B 71, 075109 (2005). [CrossRef]
32. G. V. Naik, V. M. Shalaev, and A. Boltasseva, “Alternative plasmonic materials: beyond gold and silver,” Adv. Mater. 25, 3264–3294 (2013). [CrossRef]
33. W. Bogaerts, P. de Heyn, T. van Vaerenbergh, K. de Vos, S. Kumar Selvaraja, T. Claes, P. Dumon, P. Bienstman, D. van Thourhout, and R. Baets, “Silicon microring resonators,” Laser Photon. Rev. 6, 47–73 (2012). [CrossRef]
34. W. Shi, X. Wang, W. Zhang, H. Yun, C. Lin, L. Chrostowski, and N. A. F. Jaeger, “Grating-coupled silicon microring resonators,” Appl. Phys. Lett. 100, 121118 (2012). [CrossRef]
35. J. Xie, L. Zhou, X. Sun, Z. Zou, L. Lu, H. Zhu, X. Li, and J. Chen, “Selective excitation of microring resonances using a pulley-coupling structure,” Appl. Opt. 53, 878–884 (2014). [CrossRef]
36. I. Demirtzioglou, C. Lacava, K. R. H. Bottrill, D. J. Thomson, G. T. Reed, D. J. Richardson, and P. Petropoulos, “Frequency comb generation in a silicon ring resonator modulator,” Opt. Express 26, 790–796 (2018). [CrossRef]
37. X. Cheng, J. Hong, A. M. Spring, and S. Yokoyama, “Fabrication of a high-Q factor ring resonator using LSCVD deposited Si3N4 film,” Opt. Mater. Express 7, 2182–2187 (2017). [CrossRef]
38. Q. Gao, E. Li, and A. X. Wang, “Comparative analysis of transparent conductive oxide electro-absorption modulators [Invited],” Opt. Mater. Express 8, 2850–2862 (2018). [CrossRef]
39. E. Li, Q. Gao, R. T. Chen, and A. X. Wang, “Ultracompact silicon-conductive oxide nanocavity modulator with 0.02 lambda-cubic active volume,” Nano Lett. 18, 1075–1081 (2018). [CrossRef]
40. A. Zeumault and V. Subramanian, “Improved technique for quantifying the bias-dependent mobility of metal-oxide thin-film transistors,” IEEE Trans. Electron Devices 62, 855–861 (2015). [CrossRef]
41. A. Zeumault and V. Subramanian, “Mobility enhancement in solution-processed transparent conductive oxide TFTs due to electron donation from traps in high-k gate dielectrics,” Adv. Funct. Mater. 26, 955–963 (2016). [CrossRef]