Automated Tip Functionalization via Machine Learning in Scanning Probe Microscopy

dc.contributorAalto-yliopistofi
dc.contributorAalto Universityen
dc.contributor.authorAlldritt, Benjaminen_US
dc.contributor.authorUrtev, Fedoren_US
dc.contributor.authorOinonen, Nikoen_US
dc.contributor.authorAapro, Markusen_US
dc.contributor.authorKannala, Juhoen_US
dc.contributor.authorLiljeroth, Peteren_US
dc.contributor.authorFoster, Adam S.en_US
dc.contributor.departmentDepartment of Applied Physicsen
dc.contributor.departmentDepartment of Computer Scienceen
dc.contributor.groupauthorProfessorship Kannala Juhoen
dc.contributor.groupauthorSurfaces and Interfaces at the Nanoscaleen
dc.contributor.groupauthorAtomic Scale Physicsen
dc.contributor.groupauthorComputer Science Professorsen
dc.contributor.groupauthorComputer Science - Artificial Intelligence and Machine Learning (AIML)en
dc.contributor.groupauthorComputer Science - Visual Computing (VisualComputing)en
dc.date.accessioned2021-12-31T13:54:50Z
dc.date.available2021-12-31T13:54:50Z
dc.date.issued2022-04en_US
dc.description| openaire: EC/H2020/788185/EU//E-DESIGN
dc.description.abstractAuto-CO-AFM is an open-source software package for scanning probe microscopes that enables the automatic functionalization of scanning probe tips with carbon monoxide molecules. This enables machine operators to specify the quality of the tip needed utilizing a pre-trained library with off-the-shelf software. From a single image, the software package can determine which molecules on a surface are carbon monoxide, perform the necessary tip functionalization procedures, interface with microscope software to control the tip position, and determine the centeredness of the tip after a successful functionalization. This is of particular interest for atomic force microscopy imaging of molecules on surfaces, where the tip functionalization is a necessary and time consuming step needed for sub-molecular resolution imaging. This package is freely available under the MIT License.en
dc.description.versionPeer revieweden
dc.format.mimetypeapplication/pdfen_US
dc.identifier.citationAlldritt, B, Urtev, F, Oinonen, N, Aapro, M, Kannala, J, Liljeroth, P & Foster, A S 2022, ' Automated Tip Functionalization via Machine Learning in Scanning Probe Microscopy ', Computer Physics Communications, vol. 273, 108258 . https://doi.org/10.1016/j.cpc.2021.108258en
dc.identifier.doi10.1016/j.cpc.2021.108258en_US
dc.identifier.issn0010-4655
dc.identifier.issn1879-2944
dc.identifier.otherPURE UUID: 01927076-c327-45f7-b15c-d1db6c7d667ben_US
dc.identifier.otherPURE ITEMURL: https://research.aalto.fi/en/publications/01927076-c327-45f7-b15c-d1db6c7d667ben_US
dc.identifier.otherPURE LINK: http://www.scopus.com/inward/record.url?scp=85121563131&partnerID=8YFLogxKen_US
dc.identifier.otherPURE FILEURL: https://research.aalto.fi/files/77785520/Automated_tip_functionalization_via_machine_learning_in_scanning_probe_microscopy.pdfen_US
dc.identifier.urihttps://aaltodoc.aalto.fi/handle/123456789/111928
dc.identifier.urnURN:NBN:fi:aalto-2021123111068
dc.language.isoenen
dc.publisherElsevier Science B.V.
dc.relationinfo:eu-repo/grantAgreement/EC/H2020/788185/EU//E-DESIGNen_US
dc.relation.ispartofseriesComputer Physics Communicationsen
dc.rightsopenAccessen
dc.titleAutomated Tip Functionalization via Machine Learning in Scanning Probe Microscopyen
dc.typeA1 Alkuperäisartikkeli tieteellisessä aikakauslehdessäfi

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