We demonstrate the results of a strain (stress) evaluation obtained from Raman spectroscopy measurements with the super-resolution method (the so-called super-resolution Raman spectroscopy) for a Si substrate with a patterned SiN film (serving as a strained Si sample). To improve the spatial resolution of Raman spectroscopy, we used the super-resolution method and a high-numerical-aperture immersion lens. Additionally, we estimated the spatial resolution by an edge force model (EFM) calculation. One- and two-dimensional stress distributions in the Si substrate with the patterned SiN film were obtained by super-resolution Raman spectroscopy. The results from both super-resolution Raman spectroscopy and the EFM calculation were compared and were found to correlate well. The best spatial resolution, 70 nm, was achieved by super-resolution Raman measurements with an oil immersion lens. We conclude that super-resolution Raman spectroscopy is a useful method for evaluating stress in miniaturized state-of-the-art transistors, and we believe that the super-resolution method will soon be a requisite technique.
Raman spectroscopy is used as a stress evaluation method for strained Si, which is a technique for improving device performance. State-of-the-art metal-oxide-semiconductor field-effect transistors (MOSFETs) with strained Si have been scaled down and have become complicated. There is a significant demand to measure the strain induced in such Si nanodevices, because the electrical properties of transistors considerably depend on the strain. Various methods of nanoscale strain (stress) evaluation have been demonstrated, including convergent-beam electron diffraction (CBED), micro-Raman spectroscopy, and micro-X-ray diffraction (XRD) [
In this study, we improved the spatial resolution of Raman spectroscopy by the use of the super-resolution method and a high NA immersion lens. The super-resolution method is the digital technique of improving for spatial resolution. It is possible to combine the super-resolution method with other techniques of improving spatial resolution. Moreover, we demonstrated results obtained by Raman spectroscopy measurements with the super-resolution method for a Si substrate with a patterned SiN film. The SiN films are used in the state-of-the-art MOSFETs to enhance the electron and hole mobilities. Additionally, we checked the validation of the super-resolution algorithm and estimated the spatial resolution by edge force model (EFM) calculation.
To evaluate the spatial resolution of Raman spectroscopy, a Si substrate with a patterned SiN film was used as a strained Si sample. The structures of the samples are shown in Figure
(a) Cross-sectional view of Si with patterned SiN structures and (b) plan views of etched L&S pattern.
bird’s-eye view
plan view
UV-Raman spectroscopy was performed to obtain stress distributions. An Ar-ion laser (
The every steps of the recurrence formula of BTV deconvolution method.
The EFM with corrections for detection depth and beam spot size [
The stress dependences on (a)
Figures
One-dimensional profiles of Raman shifts in the center of L&S pattern obtained by the Raman spectroscopy and EFM calculation with conventional lens (in space widths of (a) 5, (b) 3, and (c) 1
One-dimensional profiles of the Raman shifts in the center of L&S pattern obtained by the Raman spectroscopy and EFM calculation with immersion lens (in space widths of (a) 5, (b) 3, and (c) 1
Figure
Two-dimensional distributions of the Raman shifts in the end of L&S pattern obtained by (a) conventional and (b) super-resolution Raman measurements with conventional lens.
One-dimensional profiles of Raman shifts in the center of L&S pattern obtained by super-resolution Raman spectroscopy and EFM calculation with conventional lens (in space widths of (a) 5, (b) 3, and (c) 1
Figure
One-dimensional profiles of Raman shifts in the center of L&S pattern obtained by super-resolution Raman spectroscopy and EFM calculation with immersion lens (in space widths of (a) 5, (b) 3, and (c) 1
Figure
One-dimensional profiles of Raman wavenumber shifts for the Si substrate with a patterned SiN film (0.3
In this paper, the spatial resolution of Raman spectroscopy was improved by the use of digital processing technology provided by the super-resolution method, along with a high-numerical-aperture lens. A Si substrate with a patterned SiN film was used as a strained Si sample. The digital processing enabled us to evaluate a sharp Raman shift distribution, and very high tensile and compressive stress of a maximum of 1.3 GPa was obtained. Moreover, to evaluate the spatial resolution of Raman spectroscopy, an EFM calculation with corrections for detection depth and beam spot size was used for curve fitting. As a result, correlation between the results of super-resolution Raman spectroscopy and the EFM calculation was good. The best spatial resolution, 70 nm, was achieved by the super-resolution Raman measurements with the oil immersion lens. This value was an improvement over the 350 nm obtained by a conventional oil immersion Raman measurement and was approximately 0.093 times the 750 nm obtained by a conventional measurement. The spatial resolution of 70 nm is close to the size of the state-of-the-art MOSFETs. We consider super-resolution Raman spectroscopy to be very useful for nanoscale stress evaluation. However, the profile with the low signal-to-noise ratio was not improved by the super-resolution algorithm, because the Raman shift profiles were assumed to be noise caused by the super-resolution algorithm. It is necessary that we obtain the observed data with a high signal-to-noise ratio. The super-resolution technique is advantageous because it is not influenced by the sample since it includes digital processing. If we can solve the signal-to-noise ratio problem, super-resolution Raman spectroscopy will be a powerful technique for nanoscale stress evaluation. We believe that the super-resolution method will be indispensable to for evaluating future MOSFETs, which will surely surpass the present ones in complexity.
This study was partly supported by the Semiconductor Technology Academic Research Center (STARC).