Open Access
Add to BibSonomy
Abstract
The undesirable optical proximity effect (OPE) that appeared in the digital micro-mirrors device (DMD) based maskless lithography directly influences the final exposure pattern and decreases the lithography quality. In this manuscript, a convenient method of intensity modulation applied for the maskless lithography is proposed to optimize such an effect. According to the pulse width modulation based image recognition of DMD, we replaced the digital binary mask with a special digital grayscale mask to modulate the UV intensity distribution to be closer to the expectation in a way of point-by-point modification. The exposure result applying the grayscale mask has a better consistency with the design pattern than that for the case in which the original binary mask is used. The effectiveness of this method was analyzed by the image subtraction technique. Experimental data revealed that the matching rate between the exposure pattern and the mask pattern has been improved from 78% to 91%. Besides, more experiments have been conducted to verify the validity of this method for the optical proximity optimization and its potential in the high-fidelity DMD based maskless lithography.
© 2020 Optical Society of America under the terms of the OSA Open Access Publishing Agreement
1. Introduction
The application of using a digital micro-mirrors device (DMD) to modulate the optical field has been widely researched [1–3]. On that basis, novelty digital lithography methods such as maskless lithography [4,5] or micro-stereolithography [6] were proposed. By replacing the physical mask with the DMD based digital virtual mask, such techniques have been shown to produce complex patterns with superiorities like high efficiency and low cost. Moreover, the ability to refresh the virtual mask on a sub-millisecond timescale not only avoids the mask-alignment error but also supplies considerable throughput and flexibility for the fabrication of multiple-layer structures, such as slicing based 3-D micro-relief [7] or additive fabrication [8]. Therefore, these lithography techniques have been extensively investigated among the micro-nano fabrication related fields such as MEMS [9,10], micro-optical elements [11,12], PCB [13] and 3-D printing structures [14,15].
Although such techniques get benefits from the DMD, the disadvantage of applying such a device is also inevitable. Previous work has verified the conspicuous phenomenon of optical proximity effect (OPE) in the fabrication of sub-2µm scale patterns under i-line illumination [16]. This influence is more obvious for the DMD based lithography due to the DMD is a reflecting device composed of micro-mirrors and the cracks between them [17]. For the physical mask based i-line projection lithography, the undesirable effect can be solved by the optical proximity corrections (OPCs) such as adding sub-resolution assist features (SRAFs) or modifying the mask pattern [18–20]. However, few OPC methods are suitable for the DMD based maskless lithography, for that the virtual mask is composed of pixels and each one of the pixels will be clearly projected on the wafer [21].
In this work, a special OPC method applied for the DMD based maskless lithography was proposed to optimize such a problem by combining the intensity modulation. Section 2 introduces the model of DMD based lithography system and the way DMD modulates the UV intensity according to the grayscale of the pixel on the digital image. In the next section 3, aerial analysis and practical exposure experiments of a reversed “L” pattern were primarily conducted to verify the OPE phenomenon that appeared in the DMD based maskless lithography. The following part explains the criterion that we selected grayscale for each pixel on the mask pattern according to the intensity modulation effect. Finally, a special digital grayscale pattern was generated and loaded to the DMD as a virtual mask to enable the UV field to be closer with the ideal distribution in a way of point-by-point adjustment. The final exposure result has a better profile than the original pattern. Quantified by the image subtraction technique, the matching rate between the actual exposure pattern and the design pattern has been improved from the original 78% to 91%.
2. DMD based maskless lithography
2.1 Experiment setups
The basic sketch of the DMD based maskless lithography as shown in Fig. 1(a) is composed of the exposure system, the focus measurement system, and the common parts. The DMD chip (Wintech DLP 4100 0.7’’ XGA, Texas Instruments, USA) we applied in this work consists of 1024×768 micro-mirrors with each one at a size of 13.68µm×13.68µm. Once the digital pattern is loaded to the DMD, the micro-mirrors corresponding to the white pixels will rotate 12° (the “ON” status), thus the UV-light (i-line, Central wavelength λ=365nm) from the light source will be transferred into the microscope lens (Nikon, Plan flour, −10x, NA = 0.3) and finally focused on the wafer with the minimum resolution at about 1.3µm. On the contrary, the micro-mirrors corresponding to the black pixels will rotate −12°, which means the micro-mirror is working at the “OFF” status and the UV light will be reflected in another direction (see Fig. 1(b)). The differential structured illumination microscopy based focus measurement system precisely provides the vertical altitude information of the wafer. Cooperate with the X-Y-Z working stage, the mask pattern can be diverted to the photoresist with high quality.
Fig. 1. (a) The sketch of DMD based maskless lithography, (b) the working principle of DMD. (c) A simple digital image at the size of 1024*768. (d) Picture of DMD when this image is uploaded.
2.2 UV intensity modulation of DMD
For each micro-mirror on the DMD, the UV dose through it can be further divided into eight parts for that the DMD is working on the basis of Pulse-Width-Modulation (PWM). To be more specific, the grayscale of each pixel (from 0 to 255) on the digital pattern is transformed into eight-bit binary code from bit0 to bit7 (from “00000000” to “11111111”). The corresponding working time of the adjacent code position is increasing by two times based on the PWM. During the working time of each code position, the micro-mirror recognizes the bit value (0 or 1) to determine whether its working status is “ON” or “OFF”. Combined with the high-frequency rotation of micro-mirrors, the UV dose through the single micro-mirror is different for each grayscale level and its mathematical model can be represented by the following formula:
The above equation is the same as the following for that the UV dose is the multiplication of the UV intensity and exposure time.
In fact, the distribution of reflected UV light intensity I is increasing from edge to center, which is close to the Gaussian distribution [22]. Therefore, the light field of a single micro-mirror is usually described by the Gaussian formula given below:Hence, while the grayscale pattern is loaded to DMD, the light intensity distribution of a single micro-mirror can be described as Eq. (4). This equation explains the way that DMD modulates the UV intensity peak value and the FWHM according to the grayscale. Moreover, for the better visualization of, a schematic diagram is shown in Fig. 2.
3. OPC method for the DMD based maskless lithography
3.1 The pattern distortion of OPE
The micro-mirror which is working on the “ON” status can be regarded as an independent diffraction element. Its diffraction light is superimposed on the light field of surrounding micro-mirrors. Therefore, the UV intensity of center micro-mirrors is much stronger than the marginal micro-mirrors. Besides, part of high-frequency information is missing while passing through the projection lens, for example, the orthogonal corner. These factors will cause the distortion of the final exposure pattern such as line-width variation, line-length shrinking and corner rounding. The simulated results of the UV distribution and the exposure pattern of a reversed “L” pattern with the minimum line-width at two pixels are displayed in Figs. 3(a) and 3(b).
It is obvious that the simulated exposure pattern is little different from the mask pattern, which may result in the mismatching between the performance of the fabricated micro structure and the actual requirements. To precisely verify this OPE distortion, practical experiments were conducted using the AZ1500 positive photoresist. The mask pattern which mainly composed of the 1-pixel line, 2-pixels line and the reversed “L” pattern was applied as a virtual mask. The concrete exposure result captured by a microscope lens is displayed in Fig. 4. As the “L” pattern is not as dense as the grating line, less diffraction light was superimposed. Therefore, the photoresist of such a pattern is unable to be completely removed with the same exposure dose as the grating line.
Furthermore, we increased the exposure dose for another experiment with the virtual mask made up of the “L” pattern. Both the corner and the line end of the exposure pattern shown in Fig. 5 are not as consistent as the mask pattern for the above reasons. Besides, the line-width in the vertical and horizontal direction is little asymmetric which should be caused by the aberration of the optical elements.
3.2 OPC for the DMD based maskless lithography
According to Eq. (4), the DMD is able to independently modulate the UV intensity of a single micro-mirror, which means the full width at half max (FWHM) of UV light is also enlarged. Thus, for the distortion of the UV field of single a micro-mirror, it is effective to use lower grayscale pixels for the area of which the radius of the UV field is larger than ideal. Similarly, for the area such as the concave corner and the line end, pixels at higher grayscale should be applied. Therefore, by using a special digital mask composed of pixels with the designed grayscale instead of the normal mask, the defects of the UV light field appeared in the DMD based maskless lithography should be effectively modified.
Although Eq. (2) has revealed the mathematical relationship between the grayscale of pixels on DMD and the average UV intensity, such relationship is not always linear as the ideal calculation for the reason that some of the UV energy is lost during the rotation of micro-mirrors. Hence, an ultraviolet intensity meter (UIT-250, USHIO Japan, Inc., Japan) was used to measure the actual UV intensity of digital masks filled by different grayscale. The experiment results are shown in Fig. 6. For the better modulation of the UV intensity, the steady-growing grayscale section among 140-200 was chosen for this experiment. The corresponding UV intensity is from 1.98mW/cm2 to 5.3mW/cm2.
Following, series of the reversed “L” pattern, same as Fig. 3 shows but the grayscale of pixels is replaced by the grayscale from 140 to 200, were uploaded to the DMD as virtual masks to test the distortion of the exposure line-width. The exposure time was 30s to make sure that the minimum exposure dose is less than the photoresist threshold and the maximum dose is larger than the threshold (AZ1500 photoresist, prebake at 90°C for 2min). In this way, the UV intensity has a more extensive range for the adjustment. The exposure patterns were divided into several units to match the pixels on the mask pattern. Then we calculated the difference between the practical exposure size of each unit and the ideal size. Concrete results of the pixels placed at (Row 1, Column 4) and (Row 3, Column 1) were displayed in Fig. 7, in which the less-exposure grayscale is not listed. Finally, according to the difference we calculated, the original grayscale of pixels on the mask was replaced by the corresponding grayscale in the polynomial fitting curve. This process can be basically quantified as the following experiential formula:
Where the symbol x is the original grayscale of pixels, L means the corresponding exposure line width of using the x grayscale. G presents the grayscale in the mathematical curve shown in Fig. 7. For instance, the line-width of most pixels in the horizontal and vertical direction were closest to the ideal value while the grayscale was 164 and 145, respectively. As for the pixel placed at (Row 5, Column 2), it has a line-width at nearly 1.57µm for the grayscale 160. Thus, the optimized grayscale should be 152 according to the above equation.Fig. 7. Relationship between the exposure line-width and the grayscale of (a) pixel at (Row 3, Column 1), (b) pixel at (Row 1, Column 4).
Since all the pixels on the mask were basically modified, this mask was reloaded to the DMD for the further experiments. The improvement process was conducted for several circulations until the final exposure results were satisfied with the requirement. Figure 8 displays the final OPC digital mask of the reversed “L” pattern applied in this DMD based maskless lithography.
4. Results and discussions
Same as the exposure parameters mentioned in section 3.2, this OPC mask was loaded to the DMD to conduct the exposure process. The final exposure pattern on the AZ1500 photoresist was shown in Fig. 9. It is uncomplicated to find that the pattern has a more sharp profile than the original (see Fig. 5). The optimization on the corner is more obvious than the line end for that the line end can be simply regarded as two closely adjacent corners. Therefore, these two corners have less range for the adjustment. Besides, the change of the UV intensity of one corner will directly influence the UV intensity of another corner, which makes it more difficult to keep the balance between the two corners.
Moreover, the image subtraction technique is applied to assess the matching rate between the exposure pattern and the mask pattern. The calculation process was displayed as following. Figs. 10(a) and 10(d) show the binary image of the original exposure pattern and the optimized exposure pattern respectively, the middle pictures are the binary image of mask, and the final Figs. 10(c) and 10(f) are obtained by taking the absolute value of the subtraction results between the binary exposure image and mask pattern. The following concrete calculation formula is the same as Eq. (6) shows, in which the D (i, j) is the pixels on the binary mask image and B (i, j) means the pixels on the binary image of exposure pattern. By this technique, the matching rate of the two kinds of exposure results was calculated as 78% and 91%, respectively, which basically verified the efficiency of our method. Besides, the matching-rate should be higher if the optimization process is conducted for more times.
Fig. 11. The exposure results using: (a) original mask of a cross pattern, (b) original mask of letters “IOE”, (c) optimized mask of the cross pattern, (d) optimized mask of letters “IOE”. Scale bar: 2µm.
5. Conclusion
In this article, a special method was proposed to optimize the OPE phenomenon that appeared in the DMD based maskless lithography. The intensity modulation effect of DMD was primarily quantified via theoretical derivation. Besides, practical experiments were conducted to measure the difference between the actual exposure UV distribution and the ideal one. Further, a digital grayscale image composed of pixels with different grayscale was loaded to the DMD as a virtual mask to abate the difference in a way of point-by-point modulation of the UV light-field. The availability of this method was verified by practical exposure using the designed mask. The final result shows that the matching rate between exposure pattern “L” and mask image was improved from 78% to 91%. The optimization is much obvious for the corner and the line end. This method, utilizing the ability of DMD based intensity modulation effect to modify the UV light-field point-by-point, has demonstrated its good effect on optimizing the OPE distortion appeared in the DMD based maskless lithography with the advantages of low cost and convenience.
Funding
National Natural Science Foundation of China (61604154, 61605232, 61675206, 61875201); Sichuan Province Science and Technology Support Program (2018JY0203); Pearl River S and T Nova Program of Guangzhou (201710010058); South China University of Technology (2018MS16).
Disclosures
The authors declare no conflicts of interest.
References
1. K. J. Mitchell, S. Turtaev, M. J. Padgett, T. Cizmar, and D. B. Phillips, “High-speed spatial control of the intensity, phase and polarisation of vector beams using a digital micro-mirror device,” Opt. Express 24(25), 29269–29283 (2016). [CrossRef]
2. S. Shin, K. Kim, J. Yoon, and Y. Park, “Active illumination using a digital micromirror device for quantitative phase imaging,” Opt. Lett. 40(22), 5407–5410 (2015). [CrossRef]
3. Y. X. Ren, R. D. Lu, and L. Gong, “Tailoring light with a digital micromirror device,” Ann. Phys. (Berlin) 527(7-8), 447–470 (2015). [CrossRef]
4. K. F. Chan, Z. Q. Feng, R. Yang, A. Ishikawa, and W. H. Mei, “High-resolution maskless lithography,” J. Micro/Nanolithogr., MEMS, MOEMS 2(4), 331–339 (2003). [CrossRef]
5. R. Menon, A. Patel, D. Gil, and H. I. Smith, “Maskless lithography,” Mater. Today 8(2), 26–33 (2005). [CrossRef]
6. C. Sun, N. Fang, D. M. Wu, and X. Zhang, “Projection micro-stereolithography using digital micro-mirror dynamic mask,” Sens. Actuators, A 121(1), 113–120 (2005). [CrossRef]
7. S. L. Aristizabal, G. A. Cirino, A. N. Montagnoli, A. A. Sobrinho, J. B. Rubert, M. Hospital, and R. D. Mansano, “Microlens array fabricated by a low-cost grayscale lithography maskless system,” Opt. Eng. 52(12), 125101 (2013). [CrossRef]
8. D. J. Heath, T. H. Rana, R. A. Bapty, J. A. Grant-Jacob, Y. Xie, R. W. Eason, and B. Mills, “Ultrafast multi-layer subtractive patterning,” Opt. Express 26(9), 11928–11933 (2018). [CrossRef]
9. W. Iwasaki, T. Takeshita, Y. Peng, H. Ogino, H. Shibata, Y. Kudo, R. Maeda, and R. Sawada, “Maskless Lithographic Fine Patterning on Deeply Etched or Slanted Surfaces, and Grayscale Lithography, Using Newly Developed Digital Mirror Device Lithography Equipment,” Jpn. J. Appl. Phys. 51, 06FB05 (2012). [CrossRef]
10. L. Erdmann, A. Deparnay, G. Maschke, M. L. Langle, and R. Brunner, “MOEMS-based lithography for the fabrication of micro-optical components,” J. Micro/Nanolithogr., MEMS, MOEMS 4(4), 5 (2005). [CrossRef]
11. B. A. Yang, J. Y. Zhou, Q. M. Chen, L. Lei, and K. H. Wen, “Fabrication of hexagonal compound eye microlens array using DMD-based lithography with dose modulation,” Opt. Express 26(22), 28927–28937 (2018). [CrossRef]
12. J. B. Kim and K. H. Jeong, “Batch fabrication of functional optical elements on a fiber facet using DMD based maskless lithography,” Opt. Express 25(14), 16854–16859 (2017). [CrossRef]
13. E. J. Hansotte, E. C. Carignan, and W. D. Meisburger, “High speed maskless lithography of printed circuit boards using digital micromirrors,” in Emerging Digital Micromirror Device Based Systems and Applications Iii, M. R. Douglass and P. I. Oden, eds. (Spie-Int Soc Optical Engineering, Bellingham, 2011).
14. A. P. Zhang, X. Qu, P. Soman, K. C. Hribar, J. W. Lee, S. C. Chen, and S. L. He, “Rapid Fabrication of Complex 3D Extracellular Microenvironments by Dynamic Optical Projection Stereolithography,” Adv. Mater. 24(31), 4266–4270 (2012). [CrossRef]
15. M. P. Lee, G. J. T. Cooper, T. Hinkley, G. M. Gibson, M. J. Padgett, and L. Cronin, “Development of a 3D printer using scanning projection stereolithography,” Sci. Rep. 5(1), 9875 (2015). [CrossRef]
16. A. Yen, A. Tritchkov, J. P. Stirniman, G. Vandenberghe, R. Jonckheere, K. Ronse, and L. Vandenhove, “Characterization and correction of optical proximity effects in deep-ultraviolet lithography using behavior modeling,” J. Vac. Sci. Technol., B: Microelectron. Process. Phenom. 14(6), 4175–4178 (1996). [CrossRef]
17. L. W. Liang, J. Y. Zhou, L. Lei, B. Wang, Q. Wang, and K. H. Wen, “Suppression of imaging crack caused by the gap between micromirrors in maskless lithography,” Opt. Eng. 56(10), 1 (2017). [CrossRef]
18. J. F. Chen, T. Laidig, K. E. Wampler, and R. Caldwell, “Optical proximity correction for intermediate-pitch features using sub-resolution scattering bars,” J. Vac. Sci. Technol., B: Microelectron. Process. Phenom. 15(6), 2426–2433 (1997). [CrossRef]
19. C. Dolainsky and W. Maurer, Application of a simple resist model to fast optical proximity correction, Optical Microlithography X (Spie - Int Soc Optical Engineering, Bellingham, 1997), Vol. 3051, pp. 774–780.
20. R. Luo, “Optical proximity correction using a multilayer perceptron neural network,” J. Opt. 15(7), 075708 (2013). [CrossRef]
21. Z. Xiong, H. Liu, R. H. Chen, J. Xu, Q. K. Li, J. H. Li, and W. J. Zhang, “Illumination uniformity improvement in digital micromirror device based scanning photolithography system,” Opt. Express 26(14), 18597–18607 (2018). [CrossRef]
22. G. Frankowski, M. Chen, and T. Huth, “Real-time 3D shape measurement with digital stripe projection by texas instruments micromirror devices DMD (TM),” in Three-Dimensional Image Capture and Applications Iii, B. D. Corner and J. H. Nurre, eds. (Spie-Int Soc Optical Engineering, Bellingham, 2000), pp. 90–105.
