Roughness-driven compressive sensing AFM for accurate nanoscale surface characterization in functional material systems
Surface roughness significantly affects the functional performance of advanced materials, necessitating accurate nanoscale characterization via Atomic Force Microscopy (AFM). However, AFM’s high sampling requirements prolong measurement time and accelerate probe wear. To enhance efficiency, compress...
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| Format: | Article |
| Language: | English |
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Elsevier
2025-08-01
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| Series: | Materials & Design |
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| Online Access: | http://www.sciencedirect.com/science/article/pii/S0264127525007713 |
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| author | Yusong Li Jialin Shi Gongxin Li Shenghang Zhai Xiao Li Boyu Wu Chanmin Su Lianqing Liu |
| author_facet | Yusong Li Jialin Shi Gongxin Li Shenghang Zhai Xiao Li Boyu Wu Chanmin Su Lianqing Liu |
| author_sort | Yusong Li |
| collection | DOAJ |
| description | Surface roughness significantly affects the functional performance of advanced materials, necessitating accurate nanoscale characterization via Atomic Force Microscopy (AFM). However, AFM’s high sampling requirements prolong measurement time and accelerate probe wear. To enhance efficiency, compressed sensing (CS) has been applied to improve AFM sampling strategies. Our literature review indicates that existing CS approaches primarily target high-quality image reconstruction, neglecting the accurate recovery of surface roughness information—a key objective in precision surface metrology. In this study, we propose a roughness-driven CS strategy to boost the efficiency and precision of AFM-based roughness measurements. We also theoretically demonstrate a nonlinear relationship between conventional CS evaluation metrics and surface roughness. Experimental results show that, compared to traditional image-based CS strategies, our method improves nanoscale roughness measurement accuracy by more than 80 %. This advancement not only reduces sampling requirements but also maintains high fidelity in roughness characterization, offering a robust tool for precise and efficient nanoscale analysis. Our approach supports performance-driven development of functional materials in fields such as microelectronics, optics, and nanomanufacturing. |
| format | Article |
| id | doaj-art-2f148a4c52eb4c2e92543b9d1913c319 |
| institution | Kabale University |
| issn | 0264-1275 |
| language | English |
| publishDate | 2025-08-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Materials & Design |
| spelling | doaj-art-2f148a4c52eb4c2e92543b9d1913c3192025-08-20T03:33:37ZengElsevierMaterials & Design0264-12752025-08-0125611435110.1016/j.matdes.2025.114351Roughness-driven compressive sensing AFM for accurate nanoscale surface characterization in functional material systemsYusong Li0Jialin Shi1Gongxin Li2Shenghang Zhai3Xiao Li4Boyu Wu5Chanmin Su6Lianqing Liu7State Key Laboratory of Robotics, Shenyang Institute of Automation, Chinese Academy of Sciences, Shenyang 110016, China; University of Chinese Academy of Sciences, Beijing 100049, ChinaState Key Laboratory of Robotics, Shenyang Institute of Automation, Chinese Academy of Sciences, Shenyang 110016, China; Corresponding author.Key Laboratory of Advanced Process Control for Light Industry (Ministry of Education), Institute of Automation, Jiangnan University, Wuxi 214122, ChinaState Key Laboratory of Robotics, Shenyang Institute of Automation, Chinese Academy of Sciences, Shenyang 110016, China; University of Chinese Academy of Sciences, Beijing 100049, ChinaInnovation Institute of Intelligent Robotics Shenyang Co., Ltd, ChinaInnovation Institute of Intelligent Robotics Shenyang Co., Ltd, ChinaState Key Laboratory of Robotics, Shenyang Institute of Automation, Chinese Academy of Sciences, Shenyang 110016, ChinaState Key Laboratory of Robotics, Shenyang Institute of Automation, Chinese Academy of Sciences, Shenyang 110016, ChinaSurface roughness significantly affects the functional performance of advanced materials, necessitating accurate nanoscale characterization via Atomic Force Microscopy (AFM). However, AFM’s high sampling requirements prolong measurement time and accelerate probe wear. To enhance efficiency, compressed sensing (CS) has been applied to improve AFM sampling strategies. Our literature review indicates that existing CS approaches primarily target high-quality image reconstruction, neglecting the accurate recovery of surface roughness information—a key objective in precision surface metrology. In this study, we propose a roughness-driven CS strategy to boost the efficiency and precision of AFM-based roughness measurements. We also theoretically demonstrate a nonlinear relationship between conventional CS evaluation metrics and surface roughness. Experimental results show that, compared to traditional image-based CS strategies, our method improves nanoscale roughness measurement accuracy by more than 80 %. This advancement not only reduces sampling requirements but also maintains high fidelity in roughness characterization, offering a robust tool for precise and efficient nanoscale analysis. Our approach supports performance-driven development of functional materials in fields such as microelectronics, optics, and nanomanufacturing.http://www.sciencedirect.com/science/article/pii/S0264127525007713Nanoscale surface roughnessAtomic force microscope (AFM)Compressive sensingImproved efficiencyHigh accuracy |
| spellingShingle | Yusong Li Jialin Shi Gongxin Li Shenghang Zhai Xiao Li Boyu Wu Chanmin Su Lianqing Liu Roughness-driven compressive sensing AFM for accurate nanoscale surface characterization in functional material systems Materials & Design Nanoscale surface roughness Atomic force microscope (AFM) Compressive sensing Improved efficiency High accuracy |
| title | Roughness-driven compressive sensing AFM for accurate nanoscale surface characterization in functional material systems |
| title_full | Roughness-driven compressive sensing AFM for accurate nanoscale surface characterization in functional material systems |
| title_fullStr | Roughness-driven compressive sensing AFM for accurate nanoscale surface characterization in functional material systems |
| title_full_unstemmed | Roughness-driven compressive sensing AFM for accurate nanoscale surface characterization in functional material systems |
| title_short | Roughness-driven compressive sensing AFM for accurate nanoscale surface characterization in functional material systems |
| title_sort | roughness driven compressive sensing afm for accurate nanoscale surface characterization in functional material systems |
| topic | Nanoscale surface roughness Atomic force microscope (AFM) Compressive sensing Improved efficiency High accuracy |
| url | http://www.sciencedirect.com/science/article/pii/S0264127525007713 |
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