To further enhance performance of in-line XPS metrology we will demonstrate the benefit of an unsupervised machine learning approach to increase precision of critical metal gate film thickness measurements and quantification of doping concentration within source-drain junctions. Unsupervised ML efficiently separates process information from inherent noise in the XPS spectra to enable a noise-filtering that improves result precision. The observed precision improvements were utilized to increase wafer through-put by reducing the acquisition time while preserving precision, accuracy, and sensitivity when supporting high volume manufacturing.
Multiple electron beam direct write lithography is an emerging technology promising to address new markets, such as truly unique chips for security applications. The tool under consideration, the Mapper FLX-1200, exposes long 2.2 μm-wide zones called stripes by groups of 49 beams. The critical dimensions inside and the registration errors between the stripes, called stitching, are controlled by internal tool metrology. Additionally, there is great need for on-wafer metrology of critical dimension and stitching to monitor Mapper tool performance and validate the internal metrology.
Optical Critical Dimension (OCD) metrology is a workhorse technique for various semiconductor manufacturing tools, such as deposition, etching, chemical-mechanical polishing and lithography machines. Previous works have shown the feasibility to measure the critical dimension of non-uniform targets by introducing an effective CD and shown that the non-uniformity can be quantified by a machine learning approach. This paper seeks to extend the previous work and presents a preliminary feasibility study to monitor stitching errors by measuring on a scatterometry tool with multiple optical channels.
A wafer with OCD targets that mimic the various lithographic errors typical to the Mapper technology was created by variable shaped beam (VSB) e-beam lithography. The lithography process has been carefully tuned to minimize optically active systematic errors such as critical dimension gradients. The OCD targets contain horizontal and vertical gratings with a pitch of 100 nm and a nominal CD of 50 nm, and contain various stitching error types such as displacement in X, Y and diagonal gratings.
Sensitivity to all stitching types has been shown. The DX targets showed non-linearity with respect to error size and typically were a factor of 3 less sensitive than the promising performance of DY targets. A similar performance difference has seen in nominally identical diagonal gratings exposed with vertical and horizontal lines, suggesting that OCD metrology for DX cannot be fully characterized due to lithography errors in gratings with vertical lines.
Multi-channel gate all around (GAA) semiconductor devices march closer to becoming a reality in production as their maturity in development continues. From this development, an understanding of what physical parameters affecting the device has emerged. The importance of material property characterization relative to that of other physical parameters has continued to increase for GAA architecture when compared to its relative importance in earlier architectures. Among these materials properties are the concentration of Ge in SiGe channels and the strain in these channels and related films. But because these properties can be altered by many different process steps, each one adding its own variation to these parameters, their characterization and control at multiple steps in the process flow is crucial. This paper investigates the characterization of strain and Ge concentration, and the relationships between these properties, in the PFET SiGe channel material at the earliest stages of processing for GAA devices. Grown on a bulk Si substrate, multiple pairs of thin SiGe/Si layers that eventually form the basis of the PFET channel are measured and characterized in this study. Multiple measurement techniques are used to measure the material properties. In-line X-Ray Photoelectron Spectroscopy (XPS) and Low Energy X-Ray Fluorescence (LE-XRF) are used to characterize Ge content, while in-line High Resolution X-Ray Diffraction (HRXRD) is used to characterize strain. Because both patterned and un-patterned structures were investigated, scatterometry (also called optical critical dimension, or OCD) is used to provide valuable geometrical metrology.
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