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High throughput experimental methods are known to accelerate the rate of research, development, and deployment of electronic materials. For example, thin films with lateral gradients in composition, thickness, or other parameters have been used alongside spatially-resolved characterization to assess how various physical factors affect the material properties under varying measurement conditions. Similarly, multi-layer electronic devices that contain such graded thin films as one or more of their layers can also be characterized spatially in order to optimize the performance. In this work, we apply these high throughput experimental methods to thin film transistors (TFTs), demonstrating combinatorial channel layer growth, device fabrication, and semi-automated characterization using sputtered oxide TFTs as a case study. We show that both extrinsic and intrinsic types of device gradients can be generated in a TFT library, such as channel thickness and length, channel cation compositions, and oxygen atmosphere during deposition. We also present a semi-automated method to measure the 44 devices fabricated on a 50 mm×50 mm substrate that can help to identify properly functioning TFTs in the library and finish the measurement in a short time. Finally, we propose a fully automated characterization system for similar TFT libraries, which can be coupled with high throughput data analysis. These results demonstrate that high throughput methods can accelerate the investigation of TFTs and other electronic devices.
Thin film transistors (TFTs) based on amorphous oxide semiconductors have recently received significant attention[1] due to their application in the control circuit for pixels in displays. When trying to optimize the next-generation channel materials via their compositions,[2] device sizes (like channel width/length,[3] channel thickness[4]), or electrode metals,[5] researchers have traditionally made several separate TFTs with different parameters, but this approach is both time and labor intensive. Due to the rapid development of scientific research and fierce competition in industry, a wide range of synthesis, characterization, and analysis parameters must be covered in a short time. High throughput methods[6,7] have been widely used in the investigation of material properties[8,9] and electronic devices.[10] It would be worthwhile to apply these high throughput methods towards the growth of channel layer and thus the fabrication of TFTs to reduce the time needed to optimize the devices made from new materials.
There have been several examples where high throughput methods were applied to the investigation of oxide thin film transistors. For example, oxide TFT libraries with different In/Ga/Zn ratios were prepared to study the roles of each metallic element in indium–gallium–zinc–oxide (IGZO) TFTs.[11] As another example, (ZnO)x(SnO2)1−x TFTs were fabricated, with the highest electron mobilities observed at x ≈ 0.25 ± 0.05 and 0.80 ± 0.03.[12] Effects of the In fraction on the devices performances and illumination instability of indium zinc oxide (IZO) TFTs were investigated, showing that the mobility and subthreshold swing were improved as In increased.[13] Similar experiments have been attempted for Zn–In–Sn–O TFTs, with the best performance achieved at a composition ratio of Zn : In : Sn = 40 : 20 : 40.[14] There are also reports on high throughput characterization, such as simultaneously testing of multiple TFT devices.[15]
All prior combinatorial TFT studies focused on studying the performance as a function of composition metal elements in the oxide film. However, there are many other important parameters that influence the TFT performance in addition to the metal compositions, such as the device geometry (channel layer thickness and length), oxygen content in the film, placement of electrodes, etc. For example, in the case of CuSbS2 thin film photovoltaic solar cells, it has been shown that the crystallographic orientation and thickness of the active layer, as well as the selection of metal for the back contact, have strong influence on the device performance.[16] It has also been found that the concentration of impurity elements diffusing from the glass can influence the device performance.[17] Thus more combinatorial work is needed to understand the influence of different synthesis, interfacial, and geometric parameters on the TFT performance.
Here we report various types of device gradients that can be generated in a TFT library, such as channel thickness and length as well as chemical compositions of metals and oxygen as illustrated in Fig.
High throughput fabrication of the TFTs was based on the high throughput synthesis of thin films at National Renewable Energy Laboratory (NREL). Channel layer thin films were deposited onto 50 mm×50 mm substrates (100 nm thermal SiO2 on Si) using a combinatorial sputter chamber (AJA International, Orion 8). All the channel layers were deposited at room temperature (RT). Figure
The sputtering and reaction gases (Ar and O2) also play an essential role in high throughput experiments. To this end, uniform and non-uniform gas atmospheres were introduced into the chamber. For uniform gas atmosphere, pure Ar flowed into the chamber through gas lines connected to the sputtering guns, as shown in Fig.
Figure
High throughput characterization of a TFT device library is essential after high throughput fabrication. In these experiments, there are 44 devices in one library which would be cumbersome to measure if contacting the gate/source/drain electrodes one by one. While several tools are available for industrial-scale automated device testing over a wafer, they are now well suited to a research environment, because these instruments are large, expensive, and often only designed to accept a full-wafer of a particular size. Figure
After aligning the sample so that rows/columns are along the movement directions, the measurement steps are as follows. (i) Set the probe stage on measurement position. (ii) Adjust the three probe manipulators to make sure that the probe tips just touch the gate/source/drain electrodes from the 1st sample and conduct the characterization for this sample. (iii) After the characterization, use the control handle to move up the probe stage to the hold position. (iv) Since the probe manipulators are with the probe stage, the probe tips will go up and leave the sample surface at the same time, but their relative positions in x–y plane would not change. (v) Move the sample stage in x direction to the 2nd device. (vi) Use the control handle to move down the probe stage to the lower measurement position. The probe tips will just touch the gate/source/drain electrodes since their relative positions stay the same. (vii) Conduct the test for the 2nd device and repeat steps (i)–(vi) to finish measurements for the other devices. Suggestions on how to automate the device measurement and data analysis processes further using COMBIgor[22] for Igor Pro are presented in supporting information (SI).
This semi-automated measurement can finish 44 tests in a relatively short time compared to using the micromanipulators. It also makes sure that the probe tips touch the electrodes at the same position with the same probe pressure for each device, reducing the characterization error originating from the measurement conditions. Keithley 4200 A-SCS parameter analyzer was utilized to measure the transfer curves for all the TFTs in this experiment. The gate voltage (VG) was scanned from −10 V to +10 V with the drain voltage (VD) fixed at 1 V to obtain the transfer curve for all the devices. Since not all of the 44 devices showed normal TFT performances due to the leakage in some areas of SiO2, some measurements resulted in an abnormal high IG. The transfer curves presented below are shown after excluding those with abnormal gate leakage current, and all the data are shown in Fig. S1 in SI.
The channel thickness is a basic parameter in the investigation of TFTs, as well as for other electronic devices. As a baseline for the thickness-dependent and composition-dependent studies, we produced a uniform thickness in one library by placing two identical IZO guns at angle 180° with respect to each other (gun 1 and gun 3 in Fig.
To investigate the influences of the thickness on the device performance, a thickness gradient can be generated across the sample library when only one instead of two guns is used. The gradient would occur if the sputtering guns are tilted relative to the substrate normal, and the substrate is kept stationary during deposition. By only turning on the IZO target from gun 1, we fabricated IZO layers with an intentional thickness gradient, as shown in Fig.
By placing two different targets in sputter guns opposite to each other, a composition gradient can be created across a sample library. Specifically, in this work, the IGZO channel layers were co-sputtered from a Ga2O3 target (gun 1 in Fig.
Figure
IZO TFTs with uniform thickness were prepared in order to compare the channel length gradient. The source and drain electrodes were patterned by metal deposition through stainless steel shadow masks with graded channel lengths. As shown in the inset of Fig.
Figure
Figure
Previously we reported on sputtering with combinatorial gas gradients, showing that a nitrogen doping gradient can be introduced into the sputtered thin films by carefully selecting the gas outlet positions in the vacuum chamber.[19] Here we used a similar approach to create oxygen gradients in IZO thin films as explained in experimental details above. Gun 1 is an IZO target with pure Ar while gun 3 is IZO with Ar/O2 as the sputtering gas. For this analysis, we simply divided the 44 points into two parts as shown in Fig.
Figure
In this paper, we reported on a case-study of high-throughput fabrication and analysis of TFTs at NREL, and discussed our future plans of fully automated testing and rapid analysis of TFT libraries in supporting information. We showed that high-throughput methods can be applied to determine how both intrinsic (material) and extrinsic (device) parameters, such as the composition, channel thickness, channel size, and oxygen content affect performance of oxide TFTs. The new combinatorial growth technique of thin films can be extended to the preparation of electronic devices. For the IGZO TFTs studied here, we found that the off-current decreases and the threshold voltage increases with increasing Ga content, confirming that Ga can suppress the electron concentration in IZO. In addition, we showed that the on-current decreases and the threshold voltage becomes more positive as the channel length increases, since the longer channel leads to higher resistance. It is also shown that addition of oxygen can decrease the channel current, as observed in the oxygen rich region of one TFT library. All these high-throughput experimental results help to cover a wide range of fabrication conditions for TFTs in relatively short time, which is needed to improve device performance. The results presented here demonstrate how high-throughput methods can accelerate the investigation of TFTs and other electronic devices.
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