{"title":"Three-dimensional visualization of large-area, nanoscale topography measurements.","authors":"Eva Natinsky, Liam G Connolly, Michael Cullinan","doi":"10.1088/1361-6528/ad8165","DOIUrl":null,"url":null,"abstract":"<p><p>High-resolution metrology is a critical area of development for nanoscale manufacturing, especially as it affects production throughput and fabrication quality. Atomic force microscopy (AFM) is one of the most popular tools for nanometrology, and high-resolution AFM often requires a significant time commitment and produces datasets of several million points. It is therefore critical for the development of data processing techniques to keep pace with the requirements of analyzing this type of data, and for these techniques to be portable as miniaturization in AFM is becoming more common. This work presents a data fitting algorithm designed for reducing the parameters of large-area data sets which utilizes well-established spline fitting techniques. In this paper we show that basis-spline fitting can be used to accurately represent large AFM data sets, including data sets with noisy data and sharp features, while achieving at least 90% parameter reduction in all test cases.</p>","PeriodicalId":19035,"journal":{"name":"Nanotechnology","volume":null,"pages":null},"PeriodicalIF":2.9000,"publicationDate":"2024-09-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Nanotechnology","FirstCategoryId":"88","ListUrlMain":"https://doi.org/10.1088/1361-6528/ad8165","RegionNum":4,"RegionCategory":"材料科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"MATERIALS SCIENCE, MULTIDISCIPLINARY","Score":null,"Total":0}
引用次数: 0
Abstract
High-resolution metrology is a critical area of development for nanoscale manufacturing, especially as it affects production throughput and fabrication quality. Atomic force microscopy (AFM) is one of the most popular tools for nanometrology, and high-resolution AFM often requires a significant time commitment and produces datasets of several million points. It is therefore critical for the development of data processing techniques to keep pace with the requirements of analyzing this type of data, and for these techniques to be portable as miniaturization in AFM is becoming more common. This work presents a data fitting algorithm designed for reducing the parameters of large-area data sets which utilizes well-established spline fitting techniques. In this paper we show that basis-spline fitting can be used to accurately represent large AFM data sets, including data sets with noisy data and sharp features, while achieving at least 90% parameter reduction in all test cases.
期刊介绍：
The journal aims to publish papers at the forefront of nanoscale science and technology and especially those of an interdisciplinary nature. Here, nanotechnology is taken to include the ability to individually address, control, and modify structures, materials and devices with nanometre precision, and the synthesis of such structures into systems of micro- and macroscopic dimensions such as MEMS based devices. It encompasses the understanding of the fundamental physics, chemistry, biology and technology of nanometre-scale objects and how such objects can be used in the areas of computation, sensors, nanostructured materials and nano-biotechnology.
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