{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,28]],"date-time":"2026-09-28T05:20:51Z","timestamp":1790572851159,"version":"4.1.0"},"reference-count":23,"publisher":"MDPI AG","issue":"8","license":[{"start":{"date-parts":[[2025,7,28]],"date-time":"2025-07-28T00:00:00Z","timestamp":1753660800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100012166","name":"National Key R&amp;D Program of China","doi-asserted-by":"publisher","award":["2016YFB0500200"],"award-info":[{"award-number":["2016YFB0500200"]}],"id":[{"id":"10.13039\/501100012166","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100012166","name":"National Key R&amp;D Program of China","doi-asserted-by":"publisher","award":["62075220"],"award-info":[{"award-number":["62075220"]}],"id":[{"id":"10.13039\/501100012166","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"The National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["2016YFB0500200"],"award-info":[{"award-number":["2016YFB0500200"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"The National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["62075220"],"award-info":[{"award-number":["62075220"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Micromachines"],"abstract":"<jats:p>This study proposes a deep learning-based method to improve overlay alignment precision in laser direct writing systems. Alignment errors arise from multiple sources in nanoscale processes, including optical aberrations, mechanical drift, and fiducial mark imperfections. A significant portion of the residual alignment error stems from the interpretation of mark coordinates by the vision system and algorithms. Here, we developed a convolutional neural network (CNN) model to predict the coordinates calculation error of 66,000 sets of computer-generated defective crosshair marks (simulating real fiducial mark imperfections). We compared 14 neural network architectures (8 CNN variants and 6 feedforward neural network (FNN) configurations) and found a well-performing, simple CNN structure achieving a mean squared error (MSE) of 0.0011 on the training sets and 0.0016 on the validation sets, demonstrating 90% error reduction compared to the FNN structure. Experimental results on test datasets showed the CNN\u2019s capability to maintain prediction errors below 100 nm in both X\/Y coordinates, significantly outperforming traditional FNN approaches. The proposed method\u2019s success stems from the CNN\u2019s inherent advantages in local feature extraction and translation invariance, combined with a simplified network architecture that prevents overfitting while maintaining computational efficiency. This breakthrough establishes a new paradigm for precision enhancement in micro\u2013nano optical device fabrication.<\/jats:p>","DOI":"10.3390\/mi16080871","type":"journal-article","created":{"date-parts":[[2025,7,28]],"date-time":"2025-07-28T14:50:03Z","timestamp":1753714203000},"page":"871","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["Improving Laser Direct Writing Overlay Precision Based on a Deep Learning Method"],"prefix":"10.3390","volume":"16","author":[{"given":"Guohan","family":"Gao","sequence":"first","affiliation":[{"name":"Institute of Optics and Electronics, Chinese Academy of Sciences, Chengdu 610209, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jiong","family":"Wang","sequence":"additional","affiliation":[{"name":"Institute of Optics and Electronics, Chinese Academy of Sciences, Chengdu 610209, China"},{"name":"National Key Laboratory of Optical Field Manipulation Science and Technology, Chinese Academy of Sciences, Chengdu 610209, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5006-8375","authenticated-orcid":false,"given":"Xin","family":"Liu","sequence":"additional","affiliation":[{"name":"Institute of Optics and Electronics, Chinese Academy of Sciences, Chengdu 610209, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Junfeng","family":"Du","sequence":"additional","affiliation":[{"name":"Institute of Optics and Electronics, Chinese Academy of Sciences, Chengdu 610209, China"},{"name":"National Key Laboratory of Optical Field Manipulation Science and Technology, Chinese Academy of Sciences, Chengdu 610209, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jiang","family":"Bian","sequence":"additional","affiliation":[{"name":"Institute of Optics and Electronics, Chinese Academy of Sciences, Chengdu 610209, China"},{"name":"National Key Laboratory of Optical Field Manipulation Science and Technology, Chinese Academy of Sciences, Chengdu 610209, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Hu","family":"Yang","sequence":"additional","affiliation":[{"name":"Institute of Optics and Electronics, Chinese Academy of Sciences, Chengdu 610209, China"},{"name":"National Key Laboratory of Optical Field Manipulation Science and Technology, Chinese Academy of Sciences, Chengdu 610209, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2025,7,28]]},"reference":[{"key":"ref_1","first-page":"130","article-title":"Laser writing systems and technologies for fabrication of binary and continuous-relief diffractive optical elements-art. no. 67320X","volume":"Volume 6732","author":"Poleshchuk","year":"2007","journal-title":"Proceedings of the International Conference on Lasers, Applications, and Technologies 2007: Laser-Assisted Micro-and Nanotechnologies"},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"367","DOI":"10.1016\/j.optlastec.2013.08.027","article-title":"Fabrication of continuous relief micro-optic elements using real-time maskless lithography technique based on DMD","volume":"56","author":"Zhong","year":"2014","journal-title":"Opt. Laser Technol."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"110205","DOI":"10.1016\/j.optlastec.2023.110205","article-title":"Femtosecond laser micro-machining of three-dimensional surface profiles on flat single crystal sapphire","volume":"170","author":"Ng","year":"2024","journal-title":"Opt. Laser Technol."},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"587","DOI":"10.15330\/pcss.25.3.587-594","article-title":"Advantages of Direct Laser Writing for Enhancing the Resolution of Diffractive Optical Element Fabrication Processes","volume":"25","author":"Petrov","year":"2024","journal-title":"Phys. Chem. Solid State"},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"e2402014","DOI":"10.1002\/adma.202402014","article-title":"Direct Laser Writing: From Materials Synthesis and Conversion to Electronic Device Processing","volume":"36","author":"Pinheiro","year":"2024","journal-title":"Adv. Mater."},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"1604","DOI":"10.1038\/s41563-024-02031-7","article-title":"Direct laser 3D nanowriting of metals and their alloys","volume":"23","author":"Reiser","year":"2024","journal-title":"Nat. Mater."},{"key":"ref_7","first-page":"545","article-title":"Pattern recognition and data mining techniques to identify factors in wafer processing and control determining overlay error","volume":"Volume 9424","author":"Lam","year":"2015","journal-title":"Metrology, Inspection, and Process Control for Microlithography XXIX"},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"320","DOI":"10.1109\/TSM.2019.2913391","article-title":"Robust Control of Overlay Errors in Photolithography Processes","volume":"32","author":"Haq","year":"2019","journal-title":"IEEE Trans. Semicond. Manuf."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"362","DOI":"10.1117\/12.275996","article-title":"Minimization of total overlay errors on product wafers using an advanced optimization scheme","volume":"Volume 3051","author":"Harry","year":"1997","journal-title":"Optical Microlithography X"},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"212","DOI":"10.1109\/TSM.2019.2907790","article-title":"Marker Layout for Optimizing the Overlay Alignment in a Photolithography Process","volume":"32","author":"Lee","year":"2019","journal-title":"IEEE Trans. Semicond. Manuf."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"043002","DOI":"10.1117\/1.JMM.12.4.043002","article-title":"Characterization of wafer geometry and overlay error on silicon wafers with nonuniform stress","volume":"12","author":"Timothy","year":"2013","journal-title":"J. Micro\/Nanolithography MEMS MOEMS"},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"106356","DOI":"10.1016\/j.optlastec.2020.106356","article-title":"Large aperture diffractive optical telescope: A review","volume":"130","author":"Zhang","year":"2020","journal-title":"Opt. Laser Technol."},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"106944","DOI":"10.1016\/j.optlaseng.2021.106944","article-title":"Evaluation of wavefront aberrations induced by overlay errors in stitching computer-generated holograms","volume":"152","author":"Bai","year":"2022","journal-title":"Opt. Lasers Eng."},{"key":"ref_14","doi-asserted-by":"crossref","unstructured":"Ma, S., Ying, H., Ng, B., and Tok, M.K. (2025, January 5\u20138). Process Challenges attributing to Lithography Overlay Misalignment: A Case Study on BEOL Lithography Process. 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Express"},{"key":"ref_18","doi-asserted-by":"crossref","unstructured":"Gao, G., Wang, L., Shi, H., Liu, D., Fan, B., and Guan, C. (2020). Facile large-area uniform photolithography of membrane diffractive lens based on vacuum assisted self contact method. Sci. Rep., 10.","DOI":"10.1038\/s41598-020-65990-2"},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"1249","DOI":"10.1364\/OE.479611","article-title":"Wavefront Measurement of Large Aperture High Image Quality Off-axis Fresnel Lens","volume":"31","author":"Luo","year":"2022","journal-title":"Opt. Express"},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"21574","DOI":"10.1364\/OE.26.021574","article-title":"Machine learning for 3D simulated visualization of laser machining","volume":"26","author":"Heath","year":"2018","journal-title":"Opt. Express"},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"17245","DOI":"10.1364\/OE.26.017245","article-title":"Predictive capabilities for laser machining via a neural network","volume":"26","author":"Mills","year":"2018","journal-title":"Opt. Express"},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"89","DOI":"10.1126\/science.add4667","article-title":"Machine learning\u2013aided real-time detection of keyhole pore generation in laser powder bed fusion","volume":"379","author":"Ren","year":"2023","journal-title":"Science"},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"436","DOI":"10.1038\/nature14539","article-title":"Deep learning","volume":"521","author":"LeCun","year":"2015","journal-title":"Nature"}],"container-title":["Micromachines"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2072-666X\/16\/8\/871\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,9]],"date-time":"2025-10-09T18:17:30Z","timestamp":1760033850000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2072-666X\/16\/8\/871"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,7,28]]},"references-count":23,"journal-issue":{"issue":"8","published-online":{"date-parts":[[2025,8]]}},"alternative-id":["mi16080871"],"URL":"https:\/\/doi.org\/10.3390\/mi16080871","relation":{},"ISSN":["2072-666X"],"issn-type":[{"value":"2072-666X","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025,7,28]]}}}