Ti-Si-N nanocomposite coatings have been investigated using a hybrid coating system. The elimination of macro particles and the control of Si content should be accompanied to realize high quality of coating layer since macro particles induce corrosive reaction and the Si content of Ti-Si-N coating affects the mechanical properties such as hardness and friction coefficient. We introduced the hybrid coating system which consists of double bending filtered vacuum arc system (DBFVAS) and magnetron sputter cathode to solve two problems such as the macro particles and the control of Si content in Ti-Si-N coatings. The DBFVAS and magnetron sputter equipped with Ti cathode and Si cathode target, respectively. Ar and N2 are used for discharge and reaction gas and operating pressure is 0.6 mTorr. We confirmed that the DBFVAS reduced macro particles effectively and the Si content could be changed by controlling the applied power on magnetron sputtering cathode. The properties of Ti-Si-N coating layer are estimated by X-ray diffraction, X-ray photoelectron spectroscopy, wear test and nano indentation. And we compared Si content with Si emission (594.84 nm) of process chamber using an optical emission spectroscopy.

With materials innovation driving recent logic and memory scaling in the semiconductor industry, High-Productivity Combinatorial™ (HPC) technology can be a powerful tool for finding optimum materials solutions in a cost-effective and efficient manner. This paper will review unique HPC wet processing, physical vapor deposition (PVD), and atomic layer deposition (ALD) capabilities that were developed, enabling site-isolated testing of multiple conditions on a single 300mm wafer. These capabilities were utilized for exploration of new chalcogenide alloys for phase change memory, and for metal gate and high-K dielectric development for high-performance logic. Using an HPC PVD chamber, a workflow was developed in which up to 40 different precisely controlled GeSbTe alloy compositions can be deposited in discrete site-isolated areas on a single 300mm wafer and tested for electrical & material properties, using a custom in-situ high-throughput sheet-resistance measurement setup, to get very accurate measurements of the amorphous – crystalline transition temperature. We will review how resistivity as a function of temperature, crystallization temperature, final and intermediate (if any) crystalline phases were mapped for a section of the GeSbTe phase diagram, using only a few wafers. Another area where HPC can be very valuable is for finding optimum materials for high-k dielectrics and metal gates for high-performance logic transistors. Assessing the effective work-function (EWF) for a given high-k dielectric metal-gate stack for PFET and NFET transistors is a critical step for selecting the right materials before further integration. One way to obtain EWF is by using a terraced oxide wafer with different SiO2 thickness bands underneath the high-k dielectric. We report a HPC workflow using our wet, ALD & PVD capabilities, to quickly assess EWF for multiple different high-k dielectrics and metal gate stacks. This workflow starts with a HPC wet etch of thermal silicon oxide, creating different oxide thicknesses 1–10nm in select areas of the same substrate. This is followed by atomic layer deposition of a high-k dielectric film such as HfO2. Next, a metal e.g., TaN is deposited through a physical mask or patterned post-deposition to complete the formation of MOS capacitors. The final step is C-V measurements and C-V modeling to extract Vfb, high-k dielectric constant, EOT, and EWF from Vfb vs EOT plot. This workflow was used to extract EWF for a TaN metal gate with an ALD HfO2 high-k dielectric using a metal-organic precursor. We will discuss how EWF for this system was affected by annealing post-dielectric deposition & post-metallization, different annealing temperatures & ambients, Hf pre-cursors and interfacial cap layers e.g., La2O3 & Al2O3. Finally, we will also discuss more advanced versions of this workflow where the ALD high-k dielectric and PVD metal gate is also varied on the same wafer using HPC versions of ALD & PVD chambers.

Thermochromic materials change color with temperature. Organic ternary mixtures composed of a dye, developer and solvent can reversibly change color with temperature. Although they are used in many commercial products, little is known about the detailed mechanism of thermochromism. Given the wide range of available components and compositions that could potentially show thermochromic behavior, we have embarked on combinatorial studies using inkjet printing to directly prepare thermochromic mixtures on paper.

In combinatorial method, combinatorial evaluation of thin film library has not been established enough, so efficiency of searching by this method is limited. One of property which has not been available combinatorial evaluation is crystallization temperature (Tx). Conventionally, Tx is measured using differential scanning calorimeter (DSC), but it is impossible to apply to the thin film library. Because its one sample size is 1×1 mm, thickness is several micrometers, and 1,089 samples (33columns and 33 rows) are integrated on one library, so the samples are too small to measure using DSC. In this study, an alternative method using infrared thermography is presented for combinatorial evaluation of Tx. This device detects infrared energy radiated from an object and its temperature can be calculated using its own emissivity.

In crystallization point, electrical resistivity change is lead with structure change, and this derives emissivity change. Low electrical resistivity means less free electron that is low reflectivity and high emissivity. In heating test, while emissivity keeps constant, T-Ta curve (T: true sample temperature, Ta: apparent temperature measured by thermography) gradient is constant, but the point of Tx, T-Ta curve gradient changes by change of emissivity. Therefore transformation point can be detected by T-Ta curve gradient change. This method can be applied to thin film library, because the method requires only observation of sample surface.

PtSi and PdCuSi amorphous alloys were employed to confirm this method. First, homogeneous amorphous alloy thin films were deposited on alumina wafer (20×20mm). Each of these samples was then heated in vacuum chamber with monitoring infrared images and electrical resistivity, in-situ. Obvious emissivity change could be detected at the same temperature of electrical resistivity change. This temperature also agrees enough with DSC results. In case of Pt67Si33, emissivity change was detected at 511K, and DSC result shows Tx at 516K, there is only 5K error between these values. At this temperature, both electrical resistivity and emissivity decreased and it agrees with the theory. Sample crystallization was confirmed after heating test by X-ray diffraction.

Measurement on the thin film library was then considered. A quarter thin film library was used, 256 samples (16×16) are integrated and each sample size is 1×1mm separated 0.2mm grid made by sputtering on alumina wafer. For first inspection, all samples were same composition PdCuSi amorphous alloy. Every 3×3 samples, center sample were blank, i.e. alumina surface, its emissivity is stable so the surface indicated reference temperature of around samples. Alumina emissivity was calibrated using a thermo couple on the sample wafer. 184 samples in the all samples were measured at one time, Tx can be detected in all 184 samples and these value errors ranged in 15K. Therefore, this method has a great of potential in combinatorial method.

Since 1998, Dow has been actively developing and applying high throughput research (HTR) methodologies to increase the speed to market and the probability of successful product introductions. Initially Dow implemented this approach in the area of homogeneous catalysis. Based upon the success in this area, high throughput methods have been expanded into other research areas such as waterborne coatings. Paint formulations offer an excellent opportunity to use the strengths of high throughput research to understand how complex interactions between many components affect final properties. High throughput tools enable the rapid and reproducible development of paints, preparation of coating on substrates, and evaluation of performance. Rapid formulation and testing allows the interactions between formulation variables to be investigated in much more depth and breadth than has been possible in the past. Finally, statistical anaylsis and data mining tools can be used to optimize a desired balance of properties within customer defined constraints. This paper presents an example of using Dow's HTR coatings workflow to improve properties for low VOC / low odor architectural coatings.

We demonstrate how data mining techniques can be applied to complex combinatorial data sets and how data from multiple sources can be aggregated via the developed scientific data management system. An example is shown for the case of aggregated combinatorial data for the study of composition, processing, structure, and property relationships of transparent conducting oxides by applying data mining techniques such as principal component analysis. Data mappings of mined results are shown to effectively enable visualization of data trends, identification of anomalies in Fourier transform infrared spectroscopy patterns, and scientifically interesting libraries and spectral regions.

Instrumented indentation testing (IIT) is a very useful technology for the mechanical characterization of materials. However, existing IIT techniques, which are based on the Hertz model and were developed for hard materials with negligible surface adhesion such as metals and ceramics, are difficult to directly apply to compliant materials such as elastomeric polymers which have viscoelastic hysteresis due to infinitesimal surface/interfacial adhesion. Here we employed some modified model to evaluate the work of adhesion in elastomeric polymer from our previous work, and reinforced our theory and algorithm through empirical approaches so as to consider the time-dependency of viscoelastic material as testing parameter. To do these all, we combined analytic JKR theory and conventional IIT technology to analyze the physical meaning of the theory and then verified our ideas experimentally with elastomeric polymer, PDMS (poly(dimethyl-siloxane)), of various compositions. Our algorithm was developed and verified on a microinstrumented indentation basis and extended even into the nanoinstrumented testing for the micro/nano-scaled applications.