The reflection of back-scattered electrons (BSE) at the objective lens of an electron beam writer leads to a diffuse resist
exposure which extends over several millimetres. The deposed energy of this unintentional exposure is much lower than
the direct one. However, if the area of the direct electron beam exposure is large enough the accumulated energy is no
longer negligible and may cause significant CD variations. Therefore, it is of crucial importance to study possible ways
of reducing this dose contribution to a minimum and in order to perform a correct proximity correction targeting to
determine its radial distribution.
In this work a model of a 50kV E-Beam writer was developed, consisting of a resist-coated silicon wafer and an opposing low-reflection disk mounted at the pole piece of the objective lens. In order to improve the low-reflection disk, different material compositions as well as an optimized surface topography of the disk are modelled.
Proc. SPIE. 7638, Metrology, Inspection, and Process Control for Microlithography XXIV
KEYWORDS: Edge detection, Detection and tracking algorithms, Image processing, Scanning electron microscopy, Printing, Monte Carlo methods, Image filtering, Photomasks, Algorithm development, 3D image processing
We present a comparison of different methods to extract area information from images. Two different physical-based
algorithms were tested which determine the areas of arbitrarily shaped 3D nano-structures on wafers or photo-masks
(e.g. contact holes) using secondary electron images of scanning electron microscopy (SEM). One of these algorithms,
called NANOAREA, was developed by the PTB. The other one is the software package MaskEXPRESS, which was
developed by Toppan Printing Co., Ltd.
In addition to real SEM images we used Monte Carlo generated SEM images of contact holes of different shapes and
sizes. For this, the Monte Carlo simulation program MCSEM, developed at PTB, was applied. MCSEM simulates the
electron diffusion and secondary electron generation and transport in solid state material and provides simulated SEM
images of arbitrary 3D specimen structures.
NANOAREA uses basic image processing routines to estimate the edge position of a structure. Then, one-dimensional
profiles which intersect the structure boundary perpendicularly are extracted. A one-dimensional edge detection
algorithm determines the edge position on each profile. Finally these detected edge positions are used to calculate
the polygon area using the triangle method. NANOAREA showed a very small underestimation of the area of about
0.3 % with regard to the Monte Carlo simulations (i.e. sub-pixel deviation).
MaskEXPRESS has a similar approach, however employs a different edge detection algorithm. For quadratic contact
holes a very high correlation coefficient r larger than 0.99 of the CDs was seen with an offset of about 0.3 nm for the
two tested programs. Here the critical dimension (CD) is defined as the square root of the area. The deviations from
the mean offset were smaller than 1 nm over the whole investigated range. For analysis of arbitrarily shaped features
we used a double T-shaped structure. Also here almost perfect correlation was found (r = 0.98). The observed mean
offset in this case was also about 0.3 nm. The offsets depend on the length of the edge and can vary with the shape of
the structure, too.
Here we report the excellent correlation of the investigated algorithms and programs to determine area parameters
from SEM images. The results found are an important prerequisite for harmonized area measurement based on
independent algorithms and pave the way to a standardized approach to area determination and reporting of
We present the Monte Carlo simulation program MCSEM, developed at the Physikalisch-Technische Bundesanstalt
(PTB), Germany, for the simulation of Scanning Electron Microscopy (SEM) image formation at arbitrary specimen
structures (e.g. layout structures of wafers or photomasks).
The program simulates the different stages of the SEM image formation process: the probe forming, the probe-sample
interaction and the detection process. A modular program structure is used for an easy adaptation of the program to new
Arbitrarily shaped 3D structured specimen models can be applied and different electron probe shapes are modeled.
Various physical models for electron scattering in solid state material are included.
Secondary electron (SE) detection modeling is based on SE raytracing, detectors for backscattered electrons (BSE) and
transmitted electrons (TE) are also available. An electromagnetic field solver is used to simulate charging of the
specimen and the transport of the SE within the electromagnetic field. Some examples of simulation results are presented
together with comparisons with experimental results.
Scanning electron microscopy (SEM) is widely used as a fast and high resolution measurement method capable to per-form characterizations of the smallest isolated and dense features which are to be specified and produced on photomasks and wafers down to the 32 nm node and below. Furthermore, electron beam writing tools for mask or direct wafer patterning need electron beam based metrology capabilities for the required high precision alignment purposes. All of these applications benefit from a proper physical understanding of the electron interaction processes in the measured features of interest and suitable simulation capabilities in order to model the measured SEM image or signal contrasts.
In this contribution we will report on a new Monte Carlo based modular simulation package, developed at the PTB and called MCSEM, which allows to model secondary as well as backscattered electron image contrasts on 3-dimensional object features. The fundamentals, basic features as well as first applications of the new simulation package MCSEM in the nanometrology field will be explained. Where appropriate, also other existing Monte Carlo based simulation pack-ages still are in use at the PTB, examples and comparisons with the new MCSEM simulation will be given.
In this work, we investigated possible geometry optimizations of backscattered electron (BSE) detectors in order to significantly improve the signal to noise ratio (SNR) of shallow Si-topographic marks. To achieve this, Monte Carlo simulations of the BSE angular distribution as well as of the BSE exit position were performed. A comparison of some theoretical calculations with the respective experimental results allowed us to qualify the theoretical results. Based on these results, we are able to present an optimized BSE detector design featuring a significant improvement of the measured SNR.