We have developed a massive on-cell overlay metrology system based on Mueller matrix measurements. By integrating microscopic techniques into ellipsometry, we achieved high-throughput and extensive sampling coverage, with 1-shot/field per 1-field of view (FOV) measurement capability within a 34 x 34 mm2 FOV. Analyzing the off-diagonal components of the Mueller matrix allowed for on-cell overlay measurement across the wafer. This system provides measurement sensitivity comparable to e-beam-based technologies while offering high coverage, enabling precise reticle correction or high-order overlay correction in photolithography processes. This advancement represents a significant improvement in overlay metrology, offering both sensitivity and resolution for enhanced semiconductor manufacturing processes.
The thickness of the chalcogenide ovonic threshold switching (OTS) layer is one of the most critical parameters for the switch-only memory (SOM) process control. Traditionally, the OTS thickness and composition were measured by XRF using the amounts of Ge, As, and Se. Still, XRF has a few limitations in delivering the required performance, especially for products with multilayer memory architecture. For these products, x-ray fluorescence (XRF) signals overlap and cannot be used to measure the thickness of each layer. In the current paper, we have studied three new alternative approaches for measurements of the OTS thickness on-cell: Spectral Interferometry, Raman spectroscopy, and Hybrid Machine Learning technique. The first method, Spectral interferometry with the Vertical Traveling Scatterometry approach (VTS), allowed OCD modeling of the top of the structure by blocking the complex underlayers and measuring only the top OTS thickness on all targets, including within the chip. The second method, Raman spectroscopy, demonstrated oncell dimensional capabilities with an excellent correlation of the Ge-Se, As-Se, and Ge-Ge bonds of Raman active chalcogenide to TEM OTS thickness values. Finally, the third method used Raman parameters calibrated with TEM as a reference thickness for the ML solution using the VTS spectra on-cell. This ML method is fast, model-free, and requires minimal TEM samples for setup. All three methods have demonstrated capability for on-cell measurements and HVM process control.
Historically when we used to manufacture semiconductor devices for 45 nm or above design rules, IC manufacturing yield was mainly determined by global random variations and therefore the chip manufacturers / manufacturing team were mainly responsible for yield improvement. With the introduction of sub-45 nm semiconductor technologies, yield started to be dominated by systematic variations, primarily centered on resolution problems, copper/low-k interconnects and CMP. These local systematic variations, which have become decisively greater than global random variations, are design-dependent [1, 2] and therefore designers now share the responsibility of increasing yield with manufacturers / manufacturing teams. A widening manufacturing gap has led to a dramatic increase in design rules that are either too restrictive or do not guarantee a litho/etch hotspot-free design. The semiconductor industry is currently limited to 193 nm scanners and no relief is expected from the equipment side to prevent / eliminate these systematic hotspots. Hence we have seen a lot of design houses coming up with innovative design products to check hotspots based on model based lithography checks to validate design manufacturability, which will also account for complex two-dimensional effects that stem from aggressive scaling of 193 nm lithography. Most of these hotspots (a.k.a., weak points) are especially seen on Back End of the Line (BEOL) process levels like Mx ADI, Mx Etch and Mx CMP. Inspecting some of these BEOL levels can be extremely challenging as there are lots of wafer noises or nuisances that can hinder an inspector’s ability to detect and monitor the defects or weak points of interest. In this work we have attempted to accurately inspect the weak points using a novel broadband plasma optical inspection approach that enhances defect signal from patterns of interest (POI) and precisely suppresses surrounding wafer noises. This new approach is a paradigm shift in wafer inspection by leveraging systematic defect locations for high sensitivity inspection, thereby enhancing the discovery and monitoring of yield-limiting defects at traditional optical inspection throughput.
This paper presents a methodology for detecting defects more effectively that have a substantial yield impact on several critical layers using a simulation program, which is considerably helpful in analyzing defects on the wafer. First, this paper presents a simple analysis method that uses mathematical treatment for multi thin film layers. This instantly gives us a highly intuitive idea for selecting an inspection mode based on the reflectivity and transmittivity. Second, we introduce numerical method for wafer defect of interest with finite difference time domain (FDTD) method, and provide correlation between the expectation and experimental results. The goal of these studies is to determine the feasibility of implementing theoretical approaches with numerical method at wafer defect inspection. Overall, this paper discusses the effective wafer inspection methodology and the advantages of defect simulation with numerical analysis at semiconductor manufacturing for accelerated development of advanced design node devices.
Development of an advanced design node for NAND flash memory devices in semiconductor manufacturing requires
accelerated identification and characterization of yield-limiting defect types at critical front-end of line (FEOL) process
steps. This enables a shorter development cycle time and a faster production ramp to meet market demand. This paper
presents a methodology for detecting defects that have a substantial yield impact on a FEOL after-develop inspection
(ADI) layer using an advanced broadband optical wafer defect inspector and a scanning electron microscope (SEM)
review tool. In addition, this paper presents experimental data that demonstrates defect migration from an ADI layer to
an after-clean inspection (ACI) layer, and provides clear differentiation between yield-impacting critical defects and noncritical
defects on the layers. The goal of these studies is to determine the feasibility of implementing an inspection point
at ADI. The advantage of capturing yield-limiting defects on an ADI layer is that wafers can be reworked when an
excursion occurs, an option that is not always possible for ACI layers. Our investigation is divided into two parts: (1)
Inspection of an ADI layer with high sensitivity to find an accurate representation of the defect population and to gain
understanding on the propagation of defects from the ADI layer to the ACI layer; and, (2) Inspection of an ACI layer to
develop an understanding of unique defects generated by the ACI process step. Overall, this paper discusses the
advantages of baselining defectivity at ADI process levels for accelerated development of advanced design node memory
devices.
Distributions of via Depth and bottom CD for TSV wafer have been studied by scanning interference microscopy
(Unifire 7900, Nanometrics Inc.). We plotted whole wafer maps for each via depth and bottom CD and found useful
relationship between them (i.e. via depth is in inverse proportion to bottom CD in general). Average values of via depth
and bottom CD are ~60um and ~4um and their standard deviation values are 1.28% and 5.14% respectively. We also
demonstrated kinds of defects at via top (or bottom) which can cause disturbance of total via count during 3D inspection.
Our results can be a good introduction to scanning interference tool as a monitoring tool for TSV high volume
manufacturing.
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