For CMOS image sensors fabrication, deep trenches are commonly incorporated in the device to isolate the individual pixel one another within the pixel matrix. These etched structures typically exhibit a high aspect ratio of 1:20 and controlling such narrow and deep object is a challenge for inline metrology. In a manufacturing environment, the preferred method for trench height measurements remains the optical scatterometry (OCD) technique as being very sensitive and reliable. Still, it requires time and resources for model construction and validation. It appears then that an analysis of its predicted sensitivity could be a valuable pre-step before starting any activity on large periodical objects where OCD sensitivity can reach its limits. In this study, we tested this approach for deep trench structures with CD dimension in the range of 100nm to 1400nm and the depth from 100 nm to 5 μm. The periodicity (pitch) was fixed at CD*2. At first, 3D Mueller scatterometry signatures were modelled selecting spectroscopic ellipsometry acquisition configurations according to industrial most common ones. Thanks to an optimized RCWA (Rigorous Coupled Wave Analysis) code developed inhouse, calculation durations were reduced enough to allow massive data generation. By implementing a sensitivity analysis approach that uses Sobol coefficients, the sensitivity of the OCD metrology technique is here evaluated for each CD and depth values. More particulary, it will be illustrated by a CD range of ±10% of 350nm and with the depth of the trench varying from 100nm up to 5μm. As a results, a sensitivity frontier can be estimated at around 3μm, a critical depth value above which OCD in the given configuration is no more sensitive to the metrics determination. Such observation will be further discussed by analysis of convergence evaluation.
On imager devices, color resists are used as optical filters to produce RGB pixel arrays. These layers are deposited through spin coating process towards the end of the fabrication process flow, where complex topography can induce thickness inhomogeneity effect over the wafer surface causing a radial striations signature, predominant at the edge of the wafer. This deviation can induce important yield loss but is hardly detectable with standard inline metrology or defectivity approach. In this study, an interferometry-based metrology system and a reflectometry-based defectivity system were used to gather raw optical responses on the full wafer surface. Individual die cartographies were created from those and a deep learning algorithm was trained from both optical techniques. We then applied the deep learning algorithm on a specific set of test wafers to determine the number of dies affected by striations. From there, we evaluated the correlation of the outcome classification with the final electrical tests done on each die of those wafers.
Nowadays, the accuracy of the metrology is becoming more and more a critical issue for microelectronic manufacturing as new technology nodes necessitate more and more rigorous process control. Scanning Electron Microscope (SEM) is the equipment most typically used to measure pattern dimensions. The aim of this study is to model and simulate a synthetic SEM image. This is fulfilled by taking into account the physical phenomena that take place in the sample during the scanning of the electron beam. The considered phenomena are the kinetics of the drift and the diffusion of the charges during the scanning and the secondary electrons emission from the sample into the vacuum. A system of Partial Differential Equations (PDEs) is obtained which defines a system that will be solved using the Finite Element Method. The escaping of the secondary electrons is modeled by applying a Robin boundary condition on the top surface of the sample. By computing the secondary electron emission that originates from the sample during the beam scan, a synthetic SEM image is created.
KEYWORDS: Scanning electron microscopy, Metrology, Monte Carlo methods, Silicon, Finite element methods, Diffusion, Electron beam lithography, 3D modeling
SEM metrology is widely used in microelectronics to control patterns dimensions after many processes, especially patterning. Process control is achieved by verifying that experimental dimensions match targeted ones. However SEM metrology may give erroneous measurements if strong charging occurs. Charging effect impacts on the SEM image contrast and introduces artefacts. This article intends to report on the modeling of the physical phenomena occurring when the electron gun scans a sample and how charging effect occurs. For this, charge dynamics are modeled by taking into account the drift kinetics and the diffusion of electrons. The corresponding Partial Differential Equation system is solved using FEniCS open software. First, we show that when only top view measurement are modeled, the typical contrast of SEM pictures can not be predicted. Second, cross section views are modeled. This time, the expected contrast behavior is obtained. Finally, a full 3D simulation is presented.
KEYWORDS: Electron beam lithography, Lithography, Calibration, Data modeling, Point spread functions, Statistical modeling, Switches, Electroluminescence, Optimization (mathematics), Chemical analysis
In Electron Beam Lithography (EBL), the modeling of the Proximity Effects (PE) is the key to successfully print
patterns of different size and density at the desired dimension. Although current PE models are increasingly
efficient for nominal process conditions, they do not allow covering a broad exposure dose range, which would
be interesting for extending the process window, for instance.
This paper shows how to improve the accuracy of the dimension estimations of overexposed patterns by EBL by
adding a new term to the existing compact model. This advanced compact model was inspired by the chemical
mechanisms that activate the acid generator embedded in the resist during the EBL exposure. Most of the
existing compact models use the electronic Aerial Image (E AEI) calculated by the convolution product of the
patterns geometry with a Point Spread Function (PSF) and extract pattern contours using a threshold value to
model the non-linear resist behavior [1]. Here the patterns contours are simulated using an Acid Aerial Image (A
AEI) calculated from the initial E_AEI complemented by the Dill transformation [1]. A strong impact is
expected at high exposure doses but no changes should occur on patterns exposed close to their nominal dose.
The modeling and calibration capabilities of Inscale® software was used to validate the new model with
experimental measurements. Calibration and simulations obtained with both standard model and advanced model
were compared on a test design. First it shows that after calibration the PSF of the two models are similar,
meaning that physics is consistent for both models.
The new advanced model allows maintaining the accuracy at nominal dose but increases the overall accuracy by
62 % for a process window of dose with latitude extended up to 20%.
Proximity Effects in electron beam lithography impact feature dimensions, pattern fidelity and uniformity. These effects
are addressed using a mathematical model representing the radial exposure intensity distribution induced by a point
electron source, commonly named as the Point Spread Function (PSF). PSF models are usually employed for predicting
and compensating for effects up to 15μm. It is well known that there are also some process related phenomena that
impact pattern uniformity that have a longer range, namely CMP effects, fogging, etc.
Performing proximity effects corrections can result in lengthy run times as file size and pattern densities continue to
increase exponentially per technology node. Running corrections for extreme long range phenomena becomes
computational and file size prohibitive. Nevertheless, since extreme long range may reach up several millimeters, and
new technology nodes require a high level of precision, a strategy for predicting and compensating these phenomena is
crucial.
In this paper a set of test patterns are presented in order to verify and calibrate the so called extreme long range effects in
the electron beam lithography. Moreover, a strategy to compensate for extreme long range effects based on the pattern
density is presented. Since the evaluation is based on a density map instead of the actual patterns, the computational
effort is feasible.
The proposed method may be performed off-line (in contrast to machine standard in-line correction). The advantage of
employing off-line compensation relies on enhancing the employ of dose and/or geometry modulation. This strategy also
has the advantage of being completely decoupled from other e-beam writer’s internal corrections (like Fogging Effect
Correction - FEC).
KEYWORDS: Calibration, Metrology, Semiconducting wafers, Error analysis, Process modeling, Data modeling, Point spread functions, Opacity, Electron beam lithography, Statistical modeling
In electron proximity effects correction (PEC), the quality of a correction is highly dependent on the quality of the model
used to compute the effects. Therefore it is of primary importance to have a reliable methodology to extract the
parameters and assess the quality of a model. Usually, model calibration procedures consist of one or more cycles of
exposure and measurements on the calibration stage. The process and metrology variability may play a key role in the
quality of the final model and, hence, of the PEC result. Therefore, it is important to determine at which level these
variations may impact a calibration procedure and how a calibration design may be implemented in order to enable more
robustness to the resulting model.
In this work, metrology variability was evaluated by measuring the same wafer using two different CD-SEM tools. The
information coming from these analyses was used as reference to a variation induced calibration test using synthetic
data. By inserting variability in synthetic data it was possible to evaluate its impact on the resulting parameter values and
in the final model error evaluation.
In electron proximity effect correction (PEC), the quality of a correction is highly dependent on the quality of the model.
Therefore it is of primary importance to have a reliable methodology to extract the parameters and assess the quality of a
model. Among others the model describes how the energy of the electrons spreads out in the target material (via the
Point Spread Function, PSF) as well as the influence of the resist process. There are different models available in
previous studies, as well as several different approaches to obtain the appropriate value for their parameters. However,
those are restricted in terms of complexity, or require a prohibitive number of measurements, which is limited for a
certain PSF model.
In this work, we propose a straightforward approach to obtain the value of parameters of a PSF. The methodology is
general enough to apply for more sophisticated models as well. It focused on improving the three steps of model
calibration procedure: First, it is using a good set of calibration patterns. Secondly, it secures the optimization step and
avoids falling into a local optimum. And finally the developed method provides an improved analysis of the calibration
step, which allows quantifying the quality of the model as well as enabling a comparison of different models. The
methodology described in the paper is implemented as specific module in a commercial tool.
In this paper, an ill-posed inverse ellipsometric problem for thin film characterization is studied. The aim is to determine the thickness, the refractive index and the coefficient of extinction of homogeneous films deposited on a substrate without assuming any a priori knowledge of the dispersion law. Different methods are implemented for the benchmark. The first method considers the spectroscopic ellipsometer as an addition of single wavelength ellipsometers coupled only via the film thickness. The second is an improvement of the first one and uses Tikhonov regularization in order to smooth out the parameter curve. Cross-validation technique is used to determine the best regularization coefficient. The third method consists in a library searching. The aim is to choose the best combination of parameters inside a pre-computed library. In order to be more accurate, we also used multi-angle and multi-thickness measurements combined with the Tikhonov regularization method. This complementary approach is also part of the benchmark. The same polymer resist material is used as the thin film under test, with two different thicknesses and three angles of measurement. The paper discloses the results obtained with these different methods and provides elements for the choice of the most efficient strategy.
A new methodology that allows monitoring the deprotection kinetic of UV sensitive thin resist films was recently
developed at LTM. This tool measures by ellipsometry changes in optical properties of thin resist films heated at a PEB
temperature and exposed to UV.
This article presents results of the deprotection kinetic of model resist supplied by Rohm and Haas. Films thicknesses
range from 58nm to 150nm. Two thermal protocols were used to check an impact of the film thickness on the
deprotection kinetic. The first one is a thermal ramp were temperature increases at a given rate. Prior to this ramp the
sample was exposed to UV for 60s with the help of a broadband Xe lamp. This protocol allows detecting the temperature
that initiates the deprotection reaction into the film. The second test consists in heating the samples at a fixed temperature
for a given time and to expose to UV the film at this temperature. This studies supplies information on the deprotection
kinetic occurring in the film at this temperature.
The work we did on 193 nm resist films clearly shows that this technique can monitor both the thermal initiation of the
deprotection and the real time measurement of the compaction kinetic of the film during the PEB. The initial film
thickness impact on the deprotection kinetic is presented in this paper to check whether lithography processes should be
adapted to the film thickness.
In this study we investigate the pattern collapse mechanism of dense patterns with resolution under 60nm printed in Extreme Ultra Violet (EUV-IL) and Electron Beam Lithographies (EBL). Pattern collapse occurs when physical properties of the material can't imbalanced the capillary force exerted on the pattern during the drying of the rinse liquid. In former simulation models, the height of the pattern at which collapse occurs (critical height, Hc) was predicted using either elastic deformation properties, or plasticizing limit value of the resist. Experimental observations of unstuck patterns, lead us to develop 2 new models considering the adhesion properties of the resist film on the substrate. By comparing simulated to experimental results for varying pattern pitchs printed in 2 Chemically Amplified Resists (CARS), we show that pattern collapse behaviour of EUV-IL and EBL patterns is not only ruled by rigidity or strength of the resist but can be perfectly described with equation defining the unsticking of a non bending pattern. Finally by using surfactinated solution on sub-60nm dense patterns, great improvements in Hc values and increase of process window latitude are shown. However, due to larger capillary force, this efficiency decreases with pattern pitch and appears limited on patterns width smaller than 40 nm.
Obtaining highly aggressive resolution with E-Beam direct writing needs accurate simulation tools. SIGMA-C software SELIDTM allows simulating patterns profiles transferred into a resist film in the case of a Shaped Beam system. However EBeam tools that allow achieving very high resolution, especially for dense patterns, are Gaussian Beam systems. This article deals with the comparison of experimental lines obtained with a Gaussian Beam writing system and with simulation by SELIDTM of such lines. A negative chemically amplified photo resist (NEB22, Sumitomo) was exposed by our Leica UHR 100 keV. By using a high beam step size with a Gaussian spot 5 nm of FWHM (Full Width at Half Maximum), we showed that Shaped Beam simulations obtained with SELIDTM are accurate compared to experiments.
Future lithography tools will have to address the 32 nm node. EUV lithography at 13.4 nm wavelength is the technology that may achieve such resolution if chemically amplified EUV resists show high enough resolution capabilities. However for sub 100 nm line width patterns, the pattern collapse, generated during the drying step of the developing process, becomes a serious limiting phenomenon. We performed ultra high resolution exposures of EUV positive chemically amplified resists using either electron beam lithography (EBL), or EUV interferometry Lithography (IL) produced in a synchrotron. Two theoretical models have been compared with experimental results. One is mainly dealing with adhesion failure and the other with the line deformation. Adhesion failure occurs when capillarity pressure on the pattern become stronger than the attractive Van der Walls forces assuring the pattern adhesion on the substrate. Mechanical failure occurs once the lines deflection exceeds the mechanical breaking resistance of the resist. We highlighted that pattern collapse mode depends on resist thickness. Collapsing of patterns with thickness>100 nm are properly fitted with the deformation model of the resist; whereas for pattern height under 60 nm, experimental results obtained by EUVIL and EBL are properly predicted with the adhesion failure model. To push resolution further and avoid pattern collapse, we targeted to expose sub 100 nm thick resist films. AFM3D measurements on EBL patterns show that reducing the resist thickness increases their top Line Width Roughness (LWR) testifying of physical resist properties variations in the resist interfacial layers. However we pointed out an optimum resist thickness, hence an optimal dilution. By tuning developer normality and puddle time, straight resist profiles were obtained. Finally we reached dense 40/40 nm lines in XP9947W150 resist using both exposure tools and validate the process compatibility with future etching steps by transferring 40/40 nm dense lines patterned with EBL into a metallic hard mask.
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