28nm metal 90nm pitch is one of the most challenging processes for computational lithography due to the resolution limit of DUV scanners and the variety of designs allowed by design rules. Classical two dimensional hotspot simulations and OPC correction isn’t sufficient to obtain required process windows for mass production. This paper shows how three dimensional resist effects like top loss and line end shortening have been calibrated and used during the OPC process in order to achieve larger process window. Yield results on 28FDSOI product have been used to benchmark and validate gain between classical OPC and R3D OPC.
Starting from the 45nm technology node, systematic defectivity has a significant impact on device yield loss with each new technology node. The effort required to achieve patterning maturity with zero yield detractor is also significantly increasing with technology nodes. Within the manufacturing environment, new in-line wafer inspection methods have been developed to identify device systematic defects, including the process window qualification (PWQ) methodology used to characterize process robustness. Although patterning is characterized with PWQ methodology, some questions remain: How can we demonstrate that the measured process window is large enough to avoid design-based defects which will impact the device yield? Can we monitor the systematic yield loss on nominal wafers? From device test engineering point of view, systematic yield detractors are expected to be identified by Automated Test Pattern Generator (ATPG) test results diagnostics performed after electrical wafer sort (EWS). Test diagnostics can identify failed nets or cells causing systematic yield loss [1],[2]. Convergence from device failed nets and cells to failed manufacturing design pattern are usually based on assumptions that should be confirmed by an electrical failure analysis (EFA). However, many EFA investigations are required before the design pattern failures are found, and thus design pattern failure identification was costly in time and resources. With this situation, an opportunity to share knowledge exists between device test engineering and manufacturing environments to help with device yield improvement. This paper presents a new yield diagnostics flow dedicated to correlation of critical design patterns detected within manufacturing environment, with the observed device yield loss. The results obtained with this new flow on a 28nm technology device are described, with the defects of interest and the device yield impact for each design pattern. The EFA done to validate the design pattern to yield correlation are also presented, including physical cross sections. Finally, the application of this new flow for systematic design pattern yield monitoring, compared to classic inline wafer inspection methods, is discussed.
From 28 nm technology node and below optical proximity correction (OPC) needs to
take into account light scattering effects from prior layers when bottom anti-reflective coating
(BARC) is not used, which is typical for ionic implantation layers. These effects are complex,
especially when multiple sub layers have to be considered: for instance active and poly structures
need to be accounted for.
A new model form has been developed to address this wafer topography during model
calibration called the wafer 3D+ or W3D+ model. This model can then be used in verification
(using Tachyon LMC) and during model based OPC to increase the accuracy of mask correction
and verification. This paper discusses an exploration of this new model results using extended
wafer measurements (including SEM). Current results show good accuracy on various
representative structures.
Reflection by wafer topography and underlying layers during optical lithography can cause unwanted
overexposure in the resist [1]. In most cases, the use of bottom anti reflective coating limits this effect. However, this
solution is not always suitable because of process complexity, cost and cycle time penalty, as for ionic implantation
lithography process in 28nm bulk technology. As a consequence, computational lithography solutions are currently under
development to simulate and correct wafer topographical effects [2], [3]. For ionic implantation source drain (SD)
photolithography step, wafer topography influences resulting in implant pattern variation are various: active silicon
areas, Poly patterns, Shallow Trench Isolation (STI) and topographical transitions between these areas. In 28nm bulk SD
process step, the large number of wafer stack variations involved in implant pattern modulation implies a complex
modeling of optical proximity effects. Furthermore, those topography effects are expected to increase with wafer stack
complexity through technology node downscaling evolution. In this context, rigorous simulation can bring significant
value for wafer topography modeling evolution in R and D process development environment. Unfortunately, classical
rigorous simulation engines are rapidly run time and memory limited with pattern complexity for multiple under layer
wafer topography simulation.
A presentation of a fast rigorous Maxwell’s equation solving algorithm integrated into a photolithography
proximity effects simulation flow is detailed in this paper. Accuracy, run time and memory consumption of this fast
rigorous modeling engine is presented through the simulation of wafer topography effects during ionic implantation SD
lithography step in 28nm bulk technology. Also, run time and memory consumption comparison is shown between
presented fast rigorous modeling and classical rigorous RCWA method through simulation of design of interest. Finally,
integration opportunity of such fast rigorous modeling method into OPC flow is discussed in this paper.
KEYWORDS: Semiconducting wafers, Optical proximity correction, Data modeling, Silicon, Calibration, 3D modeling, Photomasks, Modulation, Scanning electron microscopy, Active optics
Ionic implantation photolithography step considered to be non critical started to be influenced by unwanted
overexposure by wafer topography with technology node downscaling evolution [1], [2]. Starting from 2xnm technology
nodes, implant patterns modulated on wafer by classical implant proximity effects are also influenced by wafer
topography which can cause drastic pattern degradation [2], [3]. This phenomenon is expected to be attenuated by the
use of anti-reflecting coating but it increases process complexity and involves cost and cycle time penalty. As a
consequence, computational lithography solutions are currently under development in order to correct wafer
topographical effects on mask [3]. For ionic implantation source Drain (SD) on Silicon bulk substrate, wafer topography
effects are the consequence of active silicon substrate, poly patterns, STI stack, and transitions between patterned wafer
stack.
In this paper, wafer topography aware OPC modeling flow taking into account stack effects for bulk technology
is presented. Quality check of this full chip stack aware OPC model is shown through comparison of mask computational
verification and known systematic defectivity on wafer. Also, the integration of topographical OPC model into OPC
flow for chip scale mask correction is presented with quality and run time penalty analysis.
KEYWORDS: Silicon, Semiconducting wafers, Oxides, Data modeling, Calibration, 3D modeling, Scanning electron microscopy, Photomasks, Process modeling, Optical lithography
Reflection by wafer topography and underlying layers during optical lithography can cause unwanted exposure in the resist [1]. This wafer stack effect phenomenon which is neglected for larger nodes than 45nm, is becoming problematic for 32nm technology node and below at the ionic implantation process. This phenomenon is expected to be attenuated by the use of anti-reflecting coating but increases process complexity and adds cost and cycle time penalty. As a consequence, an OPC based solution is today under evaluation to cope with stack effects involved in ionic implantation patterning [2] [3]. For the source drain (SD) ionic implantation process step on 28nm Fully Depleted Silicon-on-Insulator (FDSOI) technology, active silicon areas, poly silicon patterns, Shallow Trench Isolation (STI), Silicon-on-Insulator (SOI) areas and the transitions between these different regions result in significant SD implant pattern critical dimension variations. The large number of stack variations involved in these effects implies a complex modeling to simulate pattern degradations. This paper deals with the characterization of stack effects on 28nm node using SOI substrates. The large number of measurements allows to highlight all individual and combined stack effects. A new modeling flow has been developed in order to generate wafer stack aware OPC model. The accuracy and the prediction of the model is presented in this paper.
From 28nm technology node and below, Optical Proximity Correction (OPC) needs to take into account light scattering effects from prior layers when bottom anti-reflective coating (BARC) is not used, which is typical for implant layers. In this paper, we implement a sub-layer aware simulation method into a verification tool for Optical Rule Check (ORC) that is used on full 28nm test chip. The sub-layer aware verification can predict defects that are missed by standard ORC. SEM-CD review and defectivity analysis were used to confirm the validity of the sub-layer aware model on wafer.
For mature technology nodes, main yield detractor is random defectivity.
Nevertheless, some devices can show higher defectivity than rest of devices. Out of
process accident, design related defect is one of suspected root cause. Also, design-based
defect category is expected to increase as technology node decreases. Determining origin
of these additional systematic defects is not easy as these defects are usually residual for
technologies in production, not always predictable by OPC simulator (ex: void defect in
active STI structure), and at least hidden by random defectivity after in-line wafer
inspection control.
In this paper, an automatic flow to track systematic defects within global
defectivity is presented. This flow starts with a relevant selection of several inspection
defect files for a given device. Then the Design Based Binning (DBB) tool performs a
fine alignment of the whole multi wafer inspection data set with design file. The resulting
aligned defect file is treated by an efficient pattern matching algorithm to generate a
design-based binning (DBB) defect file. The integration of this output defect file into a
Yield Management System (YMS) allows easy defect analysis and statistical correlation to electrical results. An example of design-based defects tracking analysis and their impact on yield of a mature technology node device is presented in this paper.
In advanced technology nodes, due to accuracy and computing time constraint, OPC has shifted from discrete simulation
to pixel based simulation. The simulation is grid based and then interpolation occurs between grid points. Even if the
sampling is done below Nyquist rate, interpolation can cause some variations for same polygon placed at different
location in the layout. Any variation is rounded during OPC treatment, because of discrete numbers used in OPC output
file. The end result is inconsistency in post-OPC layout, where the same input polygon will give different outputs,
depending on its position and orientation relative to the grid. This can have a major impact in CD control, in structures
like SRAM for example, where mismatching between gates can cause major issue.
There are some workarounds to minimize this effect, but most of them are post-treatment fix. In this paper, we will try to
identify and solve the root cause of the problem. We will study the relationship between the pixel size and the
consistency of post OPC results. The pixel size is often set based on optical parameters, but it might be possible to
optimize it around this value to avoid inconsistency. One can say that the optimization will highly depend on design and
not be possible for a real layout. As the range of pitch used in a design tends to decrease, thanks to fix pitch layouts, we
may optimize pixel size for a full layout.
In the continuous battle to improve critical dimension (CD) uniformity, especially for 45-nanometer (nm) logic
advanced products, one important recent advance is the ability to accurately predict the mask CD uniformity
contribution to the overall global wafer CD error budget. In most wafer process simulation models, mask error
contribution is embedded in the optical and/or resist models. We have separated the mask effects, however, by
creating a short-range mask process model (MPM) for each unique mask process and a long-range CD
uniformity mask bias map (MBM) for each individual mask. By establishing a mask bias map, we are able to
incorporate the mask CD uniformity signature into our modelling simulations and measure the effects on global
wafer CD uniformity and hotspots. We also have examined several ways of proving the efficiency of this
approach, including the analysis of OPC hot spot signatures with and without the mask bias map (see Figure 1)
and by comparing the precision of the model contour prediction to wafer SEM images. In this paper we will
show the different steps of mask bias map generation and use for advanced 45nm logic node layers, along with
the current results of this new dynamic application to improve hot spot verification through Brion Technologies'
model-based mask verification loop.
KEYWORDS: Optical alignment, Semiconducting wafers, Optical lithography, Electron beams, Electron beam direct write lithography, Lithography, Signal to noise ratio, Overlay metrology, Signal detection, Wafer testing
With shrinking dimensions in the semiconductor industry the lithographic demands are exceeding the parameters of the
standard optical lithography. Electron beam direct write (EBDW) presents a good solution to overcome these limits and
to successfully use this technology in R&D as well as in prototyping and some niche applications. For the industrial
application of EBDW an alignment strategy adapted to the industrial standards is required to be compatible with optical
lithography. In this context the crucial factor is the overlay performance, i.e. the maturity of the alignment strategy under
different process conditions. New alignment marks improve the alignment repeatability and increase the window of the
signal-to-noise ratio towards smaller or noisier signals. Particularly the latter has proved to be a major contribution to a
higher maturity of the alignment. A comparison between the double cross and the new Barker mark type is presented in
this paper. Furthermore, the mark reading repeatability and the final overlay results achieved are discussed.
The beam energy is a driving design parameter for electron beam lithography systems. To be able to compare the
differences of low kV (5 kV) and high kV (100 kV) for a high-throughput system the limitations of both types of systems
are evaluated. First the effect on the CD uniformity and throughput is analyzed. For any shot noise limited system the
dose that is needed to obtain a required CD uniformity can be calculated. This dose depends on the total spot size and the
efficiency of the electrons in the resist. For a smaller spot less dose is required than for a large spot. The current in a
single beam is also determined by the spot size. A larger spot has more current. With these parameters an optimization of
the required dose, spot size and single beam current can be made. It is found that although for high kV it is easier to
create a small spot with a high current the low resist-exposure efficiency of the high-energy electrons limits the
throughput, because the required dose is large. It is also found that for 10 wafers per hour multiple lenses or columns are
required. For practical reasons (a high kV lens cannot be made as small as a low kV lens) there is a clear preference for
the use of low energy in high-throughput systems. Another aspect that is crucial in the lithography process is the overlay.
One of the main differences between high and low energy systems is the power that is dissipated in the wafer and the
resulting error due to expansion. It is found that for both energies wafer heating is an issue, but for low kV there seem to
be solutions, while for high kV the problem is 30 times bigger.
At 45 and 32 nm nodes, one of the most critical layers is the Contact one. Due to the use of hyper NA imaging, the
depth of focus starts to be very limited.
Moreover the OPC is rapidly limited because of the increase of the pattern density. The limited surface in the dark field
region of a Contact layer mask enforces the edges movement to stop very quickly.
The use of SRAF (Sub Resolution Assist Feature) has been widely use for DOF enhancement of line and space layers
since many technology node. Recently, SRAF generated using inverse lithography have shown interesting DOF
improvement1. However, the advantage of the ideal mask generated by inverse lithography is lost when switching to a
manufacturable mask with Manhattan structures. For SRAF placed in rule based as well as Manhattan SRAF generated
after inverse lithography, it is important to know what their behavior is, in term of size and placement.
In this article we propose to study the placement of scatter-trenches assist features for the contact layer. For this we have
performed process window simulation with different SRAF sizes and distance to the main OPC. These results permit us
to establish the trends for size and placement of the SRAF.
Moreover we have also take a look of the advantages of using 8 surrounding SRAF (4 in vertical - horizontal and 4 at
45°) versus 4 surrounding SRAF. Based on these studies we have seen that there is no real gain of increasing the
complexity by adding additional SRAF.
KEYWORDS: Modulation, Critical dimension metrology, Electron beam direct write lithography, Point spread functions, Electron beam lithography, Cadmium sulfide, Electron beams, Optical lithography, Manufacturing, Backscatter
After the successful results obtained in the last few years, electron beam direct write (EBDW) lithography for use in integrated circuit manufacturing has now been demonstrated. However, throughput and resolution capabilities need to be improved to push its interest for fast cycle production and advanced research and development applications. In this way, the process development needs good patterns dimensional accuracy, i.e., a better control of the proximity effects caused by backscattering electrons and others phenomenon. In this work, the limitations of the dose modulation method are investigated through the change of dose number steps and the use of a more accurate point spread function. To continue reducing feature sizes, a method to provide a complementary correction to the dose modulation solution is proposed. This rule-based electron beam proximity correction, or REBPC, provides good results down to 40 nm.
KEYWORDS: Monte Carlo methods, Point spread functions, Electron beam direct write lithography, Optical simulations, Electron beam lithography, Electron beams, Convolution, Scattering, Photoresist processing, Laser scattering
Electron Beam Direct Write (EBDW) is involved today in advanced devices
manufacturing and technology node development. As a consequence, EBDW is supporting an
increasing number of technologies and several layers per technology. In this context, an
EBDW simulator can strongly help this development study and reduce process development
cycle time. Today, available EBDW simulators are based on the use of a Point Spread
Function (PSF) to describe the energy absorbed into the resist during exposure and resist
models. Beside a constant improvement of these models limitations are observed in simulation
of sub-45nm nodes. In this paper, several simulation methods are investigated with the
purpose to build a simulation method relevant for sub-45nm nodes. The limitations of classical
EBDW simulation based on a full process flow simulation are evaluated for line width below
100nm. Then, a reduced process flow simulation limited to the exposure step is investigated
with the use of both a simulated PSF and an empirical PSF. We will see that the approach to
use an empirical PSF with the reduced process flow simulation has good predicting
capabilities in simulating structures down to 40nm.
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