|
1.IntroductionExtreme ultraviolet (EUV) lithography is the most advanced lithographic technology to fabricate nm node devices. Pattern size shrinkage to requires an exposure tool with a higher numerical aperture (NA), and the high NA leads to an increase in the chief ray angle (CRA) of EUV light as shown in Fig. 1(a).1 As a result, mask three-dimensional effects, such as the shadowing effect, become larger with a conventional stacked absorber-type EUV mask structure [Fig. 1(b)],2 and thus, the lithography process margin decreases. Recently, Kamo et al. proposed that the binary etched multilayer (ML) mask is very effective to overcome this issue as shown in Fig. 1(c).3–6 Moreover, Kim et al. also confirmed this observation by numerical analysis.7,8 However, the mask structure should be taken into account when dealing with the mask fabrication processes, such as patterned mask inspection,9–13 critical dimension measurement (CD metrology),14,15 mask repair,16,17 and cleaning.18 Takai et al. reported that the reduction of the ML stack down to 20 pairs effectively avoided the collapse of the lines by the cleaning process.19 However, patterned mask inspection, CD metrology, and repair of this mask structure continue to pose challenges that need to be addressed. In these processes, electron beam (EB) techniques are often used; therefore, charging effects tend to cause some degradation of process accuracy. Takai et al. also reported that a conductive layer between the substrate [or some low thermal expansion material (LTEM)] and ML was effective to avoid an electrical floating of the EUV mask inside a black border of etched ML. With this approach, the EB image quality of the mask was effectively improved.20 As a result, the repeatability of metrology and the sensitivity of inspection for this type of EUV mask were also improved.20 However, the optimization of the material and structure of the conductive layer is critical, because this issue should be studied with taking into account the conductivity, durability for cleaning, oxidization, roughness, and etching selectivity of the material and the impact on the image contrast. We have learned that the image contrast is determined by the secondary electron emission coefficients (SEECs) of materials that the EUV mask is composed of and by the geometries involved. They also influence the defect detection sensitivity of a projection electron microscope (PEM) inspection system.21–25 The PEM has the advantage of a much higher throughput than what is achievable in the case of a conventional scanning electron microscope (SEM) type inspection system.9,11–13,21–26 That is because PEM probes a sample target with large field illumination, whereas SEM probes a sample with a spot beam. In this paper, we investigated the defect detectability of etched ML-EUV masks, and we propose a better and more feasible structure, which would improve the processing accuracy in working with EB systems. 2.ExperimentalCandidate materials to serve as the conductive layers were selected among the familiar materials used in photomasks. TaN, Ru, CrN, TiN, and Si are materials commonly used in EUV and conventional photomasks. is also widely studied as an interdiffusion barrier between Mo and Si for EUV reflective ML mirrors,27 and as a capping layer of the ML.28 In order to evaluate the PEM image contrast of a line-and-space (L/S) pattern, the SEECs of these materials with 100 nm thickness deposited on quartz substrates were measured using a specially designed scanning Auger microscope.29 It should be noted that the obtained data were measured in as-is (as-deposited) conditions, with their native oxide films on their surface, in order to demonstrate the actual mask surface condition. The electrical resistivities of these films were measured by a four-point probe method with 0.3 mm spacings between the neighboring probes. In order to evaluate the defect detection sensitivity of a PEM inspection system, simulated PEM images were obtained using a CHARIOT Monte Carlo software (Abeam Technologies Inc.).30 The simulated PEM images take into account the characteristics of electron imaging optics, such as their aberrations, electron transmittance, and aperture stops, because these images are obtained at a conjugate image plane of the real application.25,26 For these simulations, the illumination and imaging system used were originally designed with an inspection capability for pattern sizes as narrow as half pitch (hp) 64 nm.26 Moreover, this system design allows the detection of defect sizes as small as 16 nm (on mask).26 Thus, based on the defect signal intensity of 16-nm-sized defects, the defect detectability in etched ML-EUV masks (of various structures) were evaluated and compared. The MLs consist of 20 and 40 pairs of 3-nm-thick Mo and 4-nm-thick Si with a 2.5-nm-thick Ru capping layer. The hp 44 to 32 nm L/S patterns on mask (corresponding to hp 11 to 8 nm technology on wafer) were utilized in anticipation of pattern sizes at high-NA exposure.1,2 A detailed method of simulated PEM image acquisition is described elsewhere.25,26 In order to improve the reliability of the simulation results, the SEECs of the utilized materials were employed for the calibration of the simulation results. The difference between the simulated PEM image with defects and that without defects is defined as the difference image. In order to define the sensitivity of defect detection, we identified the signal intensity in the difference image with more than 10 times the intensity of the standard deviation of the background intensity levels as a defect (). Image processing operations were applied to the simulated image to enhance the to enhance the defect signal intensities.22,31 The image contrast of the L/S pattern is expressed as a modulation transfer function (MTF), defined as []. 3.Results and Discussion3.1.Analysis of the Secondary Electron Emission Coefficients of Utilized Materials and Their Impacts on Projection Electron Microscope Image ContrastFigure 2(a) shows the experimentally obtained SEECs of TaN, CrN, TiN, Si, films, and Ru-capped ML. The SEEC curves of CrN and TiN are almost identical, and the overall SEECs of is the lowest among all these materials. These results make sense because the SEEC increases with the atomic number Z in general.32 We have learned that the SEEC difference between lines and spaces determines the gray level difference of the captured images corresponding to the material contrasts.22,24,25 As shown in Fig. 2(b), the SEEC difference between ML and turns out to be the largest. In the case of TaN, the SEEC difference shows a negative value because the SEECs of TaN is larger than those of ML. This result indicates that the combination of Ru-capped ML and TaN exhibits the image contrast reversal as compared with the other materials. The image contrast is also affected by the sample geometry. Especially for the etched ML mask, the aspect ratio of the L/S pattern is considerably high, as shown in Fig. 3. The secondary electrons (SEs) generated from the bottom of the space are blocked by the sidewalls of the lines. Therefore, the SE signals from the space decrease as the aspect ratio becomes high.13,22,24,33 Hence, this effect enhances the L/S pattern image contrast when the SEEC of the space material (conductive layer) is lower than that of ML. Figure 4 shows the apparent SEEC and SEEC difference change of a high aspect ratio pattern on the Si layer. SEEC itself is one of the physical constants. However, a decrease in the SE signals from the bottom of the space can be considered as an apparent SEEC decrease for a better understanding of the phenomenon. As the percentage of the SE signals from the bottom decreases, the apparent SEEC becomes low as shown in Fig. 4(a); while the apparent SEEC difference between ML and Si increases, and the peak of the curve is shifted to the lower incident beam energy as shown in Fig. 4(b). These results indicate that as the aspect ratio becomes high, the optimal incident beam energy to obtain the highest image contrast becomes low. Furthermore, when the SE signal from the bottom is extremely low (1%), the SEEC difference curve becomes identical to the SEEC curve of ML. As a result, the optimal condition is determined by the peak of the ML. This result is in good agreement with our previous work for the investigation of the optimal incident beam energy to detect the small intrusion defect.22,24 In order to confirm the impact of the conductive layer on the image contrast, simulated PEM images were obtained using a sample structure with an hp 40 nm L/S pattern in 40-pair-ML on various conductive layers as shown in Fig. 5. Incident beam energy of 300 eV creates the most sensitive condition for defect detection in this sample geometry. In the case of Ru, the L/S pattern is hardly identifiable in spite of the high aspect ratio of 7.2 because the material contrast between Ru-capped ML and Ru conductive layer is very low.23 Moreover, the MTF of the TaN sample is lower than that of the Ru one because the higher SEEC of TaN cancels out the effect of a high aspect ratio. On the other hand, by reducing 40-pair ML to 20-pair ML, the MTF value of the TaN sample increases, and the contrast of the L/S pattern is reversed as compared with the CrN, Si, and samples as shown in Fig. 6. These image contrasts correspond to their material contrasts derived from the SEEC curves as shown in Fig. 2. Furthermore, the MTF values of Si and show a significant difference for the case with 20-pair ML (0.22 and 0.25, respectively), whereas the values for the case with 40-pair ML are about the same (0.26 and 0.25, respectively). These results indicate that the conductive layer underlying 20-pair ML has a greater impact on the EB image contrast than in the case of 40-pair ML and that the sample has the highest image contrast of the L/S pattern. It is also noted that the optimal incident beam energy for defect detection in the geometry of 20-pair-ML is higher than that of the 40-pair ML, due to an increase in the percentage of the detectable SEs from the conductive layer as shown in Fig. 4(b). 3.2.Investigation of the Impact of Aspect Ratio and Conductive Layer on Defect DetectabilityIn order to investigate the impact of the aspect ratio and conductive layer on the defect detectability of a PEM inspection system for etched ML-EUV masks, a die-to-die inspection is demonstrated using simulated PEM images with and without defects. Figure 7 shows the difference images for the cases of a 40-pair ML on an Si layer. A set of extrusion and intrusion defects with 22 and 16 nm sizes are detected more than in all the cases of hp 44, 40, and 32 nm L/S patterns. As shown in Figs. 3(a)–3(c), their aspect ratios are 6.5, 7.2, and 9.0, respectively. The illumination and the imaging systems used for this simulation are designed for an hp 64 nm L/S pattern (hp 16 nm on wafer). Therefore the spatial resolution is not sufficient for smaller hp L/S patterns, such as less than hp 40 nm (hp 10 nm on wafer). Thus, the defect detection sensitivity degrades along with the pattern size shrink in spite of the increase of aspect ratio. We have learned that the spatial resolution has a great impact on the defect detectability, especially for small defects.13 In order to increase the detectability, the spatial resolution needs to be improved, and we are now developing a new PEM inspection system designed for 11 nm node.34 Figure 8 shows the difference images for the cases of 20-pair ML with an hp 40 nm L/S pattern on various conduction layers. By reducing 40-pair ML to 20-pair ML, 16-nm-sized extrusion defects on the Si layer become undetectable. Only in the case of the sample, 16-nm-sized extrusion defects are detected more than . These results indicate that the selection of a conductive layer with higher material contrast is critical for high sensitivity pattern inspection of an etched 20-pair ML EUV mask. In order to confirm the threshold level for defect detection, the difference images with various threshold levels are shown in Fig. 9. In the case of , a 16 nm extrusion defect is detected even on Si, but some false defects are also observed in all samples. On increasing the threshold, the false defects decrease, and then, in the case of , a 16-nm-sized extrusion defect is detected without any false defects on the sample. This result indicates that is the required condition for inspection without false defects. In order to prevent any oxidation of the etched part, several researchers proposed that the etched part be replaced by other materials as shown in Fig. 10.7 In this study, Si is filled up to the same level as the Ru capping layer. In this case also, 16- and 22-nm-sized extrusion and intrusion defects are detected. It is to be noted that the optimal incident beam energy (600 eV) is different from the case of the as-etched (before Si is filled with the etched part) mask (500 eV). This energy shift can be explained by using Fig. 4(b). When the surface of Si is leveled with that of the ML, the SEs from the Si reach the detector without being blocked by the sidewalls of the trench [the case of 100% in Fig. 4(b)]. Therefore, the optimal condition is shifted toward the higher energy. It is also noteworthy that the 16-nm-sized extrusion defect is detected in the refilled structure, whereas the same defect is not detected in the Si conductive layer as shown in Fig. 8(b). However, the SEEC difference for the case of 100% (refilled structure) is lower than that of the 80% (40-pair ML as-etched). This phenomenon can be explained by the electron scattering near the edge of the etched ML. In the case of the as-etched structure, strongly scattered electrons near the edge become a source of noise, and they degrade the signal-to-noise ratio (SNR) of the defect signal. On the other hand, in the case of the refilled structure, no such electron scattering is encountered since in this case the surface happens to be flat. Hence, the SNR of the defect signal is improved. A detailed explanation of the phenomena was described earlier.24 By using a conductive layer, a residual-type defect (etching residue)21,35,36 can also be detected with high sensitivity. However, the sensitivity depends on the surface material of the etching residue as shown in Fig. 11. When the surface of the defect is covered by Mo, only the 5-nm-thick defect is detectable, whereas in the case of Si, even a 10-nm-thick defect cannot be detected. This is because the SEEC difference between Mo and is much larger than that between Si and as shown in Fig. 12. In the case of the real defect, the surface of the defect is often not flat but shows some slopes. Therefore, in most cases, both Mo and Si appear on the defect’s surface. Hence, most of the real residual-type defects can be detected. 3.3.Analysis of Electrical Conductivity and Charging Effect of the Candidate MaterialsIn order to investigate the electrical conductivity and surface charging effect of the candidate materials, electrical resistivity and the dependence of beam probe current on the SEEC are evaluated. Table 1 shows the resistivity of the candidate materials with various structures. TiN, CrN, and TaN have good conductivities. In the case of Si, the resistivity of p- or n-type crystal Si is known as 1.0 to . However, crystal layers are hardly grown on noncrystalline substrates such as quartz and LTEM. Especially for the case of sputtered films, amorphous Si with high resistivity tends to be deposited. On the other hand, with 100 nm has a comparatively good conductivity, but the electric resistance of 5-nm-thick film on substrate goes up to an unmeasurable level. From the standpoint of EB repair technique, a resistivity should be as low as possible to demonstrate the precise repair process.16,17 These results show that an Si conductive layer has a technical problem with depositions onto photomask substrates, and a film does not seem to be sufficiently conductive to maximize the accuracy of the repair process and CD metrology, and the sensitivity of pattern inspection. In order to maximize the effect of low SEEC and electrical conductivity, a conductive layer with double-layer structure with 2.5-nm-thick on metal film is proposed. The resistivity of this type of conductive layer is better than those of TiN, CrN, and TaN. In order to reconfirm the conductivity and investigate the effect of surface charging when the electron beam is irradiated, the dependence of the beam current on the SEEC changes was examined for the three types of samples as shown in Fig. 13. Table 1Electrical resistivity of the candidate layers (Ωcm).
The SEECs of 100-nm-thick film and 2.5-nm-thick on metal film remain almost constant as the incident electron beam current increases. On the other hand, the SEEC of the 5-nm-thick film shows a significant decrease with the increasing beam current because the emitted SEs return back to the sample surface due to the strong positive charges involved as shown in Fig. 14.24,37,38 When the film is sufficiently thick, the injected electrons or generated holes can be discharged through the thick film. However, these charges are stored in the thin film due to its extreme high resistance. On the other hand, in the case of the double-layer structure, the charges are discharged along with the underlying metal film. We have already reported that the SEEC of the nondoped Si layer with the resistivity of shows a similar decrease along with the increasing beam current, whereas the SEECs of the Ru-capped ML remain almost constant.24 Moreover, the lateral and vertical conductivities of Ru-capped ML are empirically known to be sufficiently high to avoid any charging effect in spite of 4-nm-thick sputtered Si layers being included.20 These results indicate that the charging effect attributed to the 2.5-nm-thick is negligibly small, and the SE signal from the double structured conductive layer is not changed regardless of the electron dosage. 3.4.Other Items to Be Taken into Account in Selecting the Conductive LayerIn order to select the conductive layer, the following “other” items are to be taken into account: (1) influence of native oxide, (2) etching selectivity, and (3) additional phase defects.
4.Summary and ConclusionsPatterned mask inspection for an etched ML-EUV mask was investigated. In order to optimize the mask structure not only from the standpoint of a pattern inspection using PEM but also considering other fabrication processes using EB technique such as CD metrology and mask repair, we focus on a conductive layer between the ML and substrate. Candidate materials to serve as the conductive layer were selected from the familiar materials used in photomasks, such as TaN, Ru, CrN, TiN, Si, and . By measuring the SEECs of the candidate materials for the conductive layer, the combination of conductive layer and Ru-capped ML was found to have the best pattern image contrast due to its highest SEEC difference. In the cases of 40-pair ML, 16-nm-sized extrusion and intrusion defects were found to be detectable more than in hp 44, 40, and 32 nm L/S patterns. Although reduction of 40-pair ML to 20-pair ML degraded the image contrast and the defect detectability, 16-nm-sized defects remained detectable in the case of sample. These defects were detected after the etched part was refilled with Si. Moreover, the simulation shows a high sensitivity for detecting the residual-type defects (etching residues). In order to maximize the effect of low SEEC and electrical conductivity, a double-layer structured conductive layer with 2.5-nm-thick on metal film was proposed. This conductive layer was found to have sufficient conductivity () and also was found to be free from the surface charging effect and any influence of native oxide. AcknowledgmentsThe authors would like to thank T. Kamo, K. Takai, M. Naka, R. Yoshikawa, S. Kanamitsu, and T. Hirano of Toshiba Corporation for useful discussions. This work was supported by the New Energy and Industrial Technology Development Organization. ReferencesB. Kneer et al.,
“EUV lithography optics for sub-9nm resolution,”
Proc. SPIE, 9422 94221G
(2015). http://dx.doi.org/10.1117/12.2175488 PSISDG 0277-786X Google Scholar
J. T. Neumann et al.,
“Interactions of 3D mask effects and NA in EUV lithography,”
Proc. SPIE, 8522 852211
(2012). http://dx.doi.org/10.1117/12.2009117 PSISDG 0277-786X Google Scholar
B. La Fontaine et al.,
“Architectural choices for EUV lithography masks: patterned absorbers and patterned reflectors,”
Proc. SPIE, 5374 300
(2004). http://dx.doi.org/10.1117/12.539074 PSISDG 0277-786X Google Scholar
T. Schmoeller et al.,
“The impact of mask design on EUV imaging,”
Proc. SPIE, 7379 73792H
(2009). http://dx.doi.org/10.1117/12.824331 PSISDG 0277-786X Google Scholar
C. Chovino et al.,
“EUV mask making: an approach based on the direct patterning of the EUV reflector,”
Proc. SPIE, 5256 566
(2003). http://dx.doi.org/10.1117/12.518259 PSISDG 0277-786X Google Scholar
K. Takai et al.,
“Patterning of EUVL binary etched multilayer mask,”
Proc. SPIE, 8880 88802M
(2013). http://dx.doi.org/10.1117/12.2033258 PSISDG 0277-786X Google Scholar
G. J. Kim et al.,
“Etched multilayer mask is better than conventional absorber mask,”
Proc. SPIE, 9256 92560R
(2014). http://dx.doi.org/10.1117/12.2069885 PSISDG 0277-786X Google Scholar
G. J. Kim et al.,
“Etched multilayer mask in EUV lithography for 16 nm node and below,”
Proc. SPIE, 9256 92560Q
(2014). http://dx.doi.org/10.1117/12.2069404 PSISDG 0277-786X Google Scholar
S. Yamaguchi et al.,
“Performance of EBeyeM for EUV mask inspection,”
Proc. SPIE, 8166 81662F
(2011). http://dx.doi.org/10.1117/12.898790 PSISDG 0277-786X Google Scholar
T. Shimomura et al.,
“Electron beam inspection of 16 nm hp node EUV masks,”
Proc. SPIE, 8522 85220L
(2012). http://dx.doi.org/10.1117/12.976017 PSISDG 0277-786X Google Scholar
R. Hirano et al.,
“Development of extreme ultraviolet mask pattern inspection technology using projection electron beam optics,”
J. Micro/Nanolith. MEMS MOEMS, 12 021003
(2013). http://dx.doi.org/10.1117/1.JMM.12.2.021003 Google Scholar
R. Hirano et al.,
“Patterned mask inspection technology with projection electron microscope technique on extreme ultraviolet masks,”
J. Micro/Nanolith. MEMS MOEMS, 13 013009
(2014). http://dx.doi.org/10.1117/1.JMM.13.1.013009 Google Scholar
S. Iida et al.,
“Dependence of defect size and shape on detectability for EUV patterned mask inspection,”
Proc. SPIE, 9422 942225
(2015). http://dx.doi.org/10.1117/12.2085655 PSISDG 0277-786X Google Scholar
Y. Nishiyama et al.,
“Influence of the charging effect on the precision of measuring EUV mask features,”
Proc. SPIE, 7971 79710C
(2011). http://dx.doi.org/10.1117/12.878728 PSISDG 0277-786X Google Scholar
S. Babin et al.,
“CD-metrology of EUV masks in the presence of charging: measurement and simulation,”
Proc. SPIE, 8441 844108
(2012). http://dx.doi.org/10.1117/12.999462 PSISDG 0277-786X Google Scholar
S. Kanamitsu, T. Hirano and O. Suga,
“Prospect of EUV mask repair technology using e-beam tool,”
Proc. SPIE, 7823 782322
(2010). http://dx.doi.org/10.1117/12.864288 PSISDG 0277-786X Google Scholar
S. Kanamitsu, K. Morishita and T. Hirano,
“Application of EB repair for high durable MoSi PSM,”
Proc. SPIE, 9256 92560U
(2014). http://dx.doi.org/10.1117/12.2070019 PSISDG 0277-786X Google Scholar
U. Dietze et al.,
“Effective EUVL mask cleaning technology solutions for mask manufacturing and in-fab mask maintenance,”
Proc. SPIE, 7985 79850N
(2011). http://dx.doi.org/10.1117/12.896911 PSISDG 0277-786X Google Scholar
K. Takai et al.,
“Capability of etched multilayer EUV mask fabrication,”
Proc. SPIE, 9235 923515
(2014). http://dx.doi.org/10.1117/12.2067892 PSISDG 0277-786X Google Scholar
K. Takai et al.,
“Improvement of EUVL mask structure with black border of etched multilayer,”
Proc. SPIE, 8701 87010Y
(2013). http://dx.doi.org/10.1117/12.2031582 PSISDG 0277-786X Google Scholar
S. Iida et al.,
“Identification of residual-type defect on extreme ultraviolet mask by projection electron microscope using Monte Carlo simulation,”
J. Vac. Sci. Technol. B, 30 06F503
(2012). http://dx.doi.org/10.1116/1.4758924 JVTBD9 1071-1023 Google Scholar
S. Iida et al.,
“Extreme ultraviolet mask defect inspection with a half pitch 16-nm node using simulated projection electron microscope images,”
J. Micro/Nanolith. MEMS MOEMS, 12 023013
(2013). http://dx.doi.org/10.1117/1.JMM.12.2.023013 Google Scholar
S. Iida et al.,
“Impact of electron scattering in extreme ultraviolet reflective multilayer on electron image,”
J. Vac. Sci. Technol. B, 31
(6), 06F601
(2013). http://dx.doi.org/10.1116/1.4819300 JVTBD9 1071-1023 Google Scholar
S. Iida et al.,
“Impact of capping layer for extreme ultraviolet mask on the sensitivity of patterned mask inspection using a projection electron microscope,”
J. Micro/Nanolith. MEMS MOEMS, 13 043015
(2014). http://dx.doi.org/10.1117/1.JMM.13.4.043015 Google Scholar
S. Iida et al.,
“Simulation technique for pattern inspection using a projection electron microscope,”
J. Vac. Sci. Technol. B, 33
(6), 06FN02
(2015). http://dx.doi.org/10.1116/1.4931932 JVTBD9 1071-1023 Google Scholar
S. Iida et al.,
“Analysis of image distortion on projection microscope image,”
Jpn. J. Appl. Phys., 53 116602
(2014). http://dx.doi.org/10.7567/JJAP.53.116602 Google Scholar
S. Bajt et al.,
“Improved reflectance and stability of Mo/Si multilayers,”
Opt. Eng., 41 1797
(2002). http://dx.doi.org/10.1117/1.1489426 Google Scholar
I. Y. Jang et al.,
“Ruthenium (Ru) peeling and predicting robustness of the capping layer using finite element method (FEM) modeling,”
Proc. SPIE, 9256 92560I
(2014). http://dx.doi.org/10.1117/12.2069991 PSISDG 0277-786X Google Scholar
M. Kadowaki et al.,
“Investigation of factors causing difference between simulation and real SEM image,”
Proc. SPIE, 7272 72723I
(2009). http://dx.doi.org/10.1117/12.814036 PSISDG 0277-786X Google Scholar
S. Babin et al.,
“CHARIOT: software tool for modeling SEM signal and e-beam lithography,”
Phys. Procedia, 1 305
(2008). http://dx.doi.org/10.1016/j.phpro.2008.07.110 PPHRCK 1875-3892 Google Scholar
H. Watanabe et al.,
“EUV patterned mask inspection system using a projection electron microscope technique,”
Proc. SPIE, 8880 88800U
(2013). http://dx.doi.org/10.1117/12.2027566 PSISDG 0277-786X Google Scholar
Y. Lin and D. C. Joy,
“A new examination of secondary electron yield data,”
Surf. Interface Anal., 37 895
(2005). http://dx.doi.org/10.1002/sia.2107 SIANDQ 0142-2421 Google Scholar
D. Bizen, Y. Sohda and H. Kazumi,
“Dependence of secondary-electron yield on aspect ratio of several trench patterns,”
Proc. SPIE, 9050 90500K
(2014). http://dx.doi.org/10.1117/12.2044662 PSISDG 0277-786X Google Scholar
R. Hirano et al.,
“Extreme ultraviolet lithography patterned mask defect detection performance evaluation toward 16- to 11-nm half-pitch generation,”
J. Micro/Nanolith. MEMS MOEMS, 14 033512
(2015). http://dx.doi.org/10.1117/1.JMM.14.3.033512 Google Scholar
T. Amano et al.,
“Residual-type mask defect printability for extreme ultraviolet lithography,”
J. Vac. Sci. Technol. B, 30
(6), 06F501
(2012). http://dx.doi.org/10.1116/1.4756934 JVTBD9 1071-1023 Google Scholar
T. Amano et al.,
“Observation of residual-type thin absorber defect on extreme ultraviolet lithography mask using an extreme ultraviolet microscope,”
Appl. Phys. Express, 6 046501
(2013). http://dx.doi.org/10.7567/APEX.6.046501 APEPC4 1882-0778 Google Scholar
S. Aoyagi and K. Ura,
“Initialization by erasing the surface potential of negatively charged insulators in scanning electron microscope (SEM) observation,”
J. Electron Microsc., 48 555
(1999). http://dx.doi.org/10.1093/oxfordjournals.jmicro.a023715 Google Scholar
M. Miyoshi and K. Ura,
“Negative charging-up contrast formation of multilayered structures with a nonpenetrating electron beam in scanning-electron microscope,”
J. Vac. Sci. Technol. B, 23 2763
(2005). http://dx.doi.org/10.1116/1.2101757 JVTBD9 1071-1023 Google Scholar
T. Amano and T. Terasawa,
“Propagation of surface topography of extreme ultraviolet blank substrate through multilayer and impact of phase defect structure on wafer image,”
J. Micro/Nanolith. MEMS MOEMS, 12 033015
(2013). http://dx.doi.org/10.1117/1.JMM.12.3.033015 Google Scholar
T. Harada et al.,
“Phase defect characterization on an extreme-ultraviolet blank mask using microcoherent extreme-ultraviolet scatterometry microscope,”
J. Vac. Sci. Technol. B, 31 06F605
(2013). http://dx.doi.org/10.1116/1.4826249 JVTBD9 1071-1023 Google Scholar
BiographySusumu Iida received his BS and MS degrees in 1995 and 1997, respectively, and in 2000, he earned his PhD in electronics, all from Shizuoka University, Japan. He joined the Research and Development Center at Toshiba Corporation. In 2011, he was assigned to EIDEC, and since then he has been engaged in the development of patterned mask inspection. |