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+<?xml version="1.0" encoding="utf-8" ?>
+<!DOCTYPE article PUBLIC "-//NLM//DTD JATS (Z39.96) Journal Publishing DTD v1.2 20190208//EN"
+                  "JATS-publishing1.dtd">
+<article xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink" dtd-version="1.2" article-type="other">
+<front>
+<journal-meta>
+<journal-id></journal-id>
+<journal-title-group>
+<journal-title>Journal of Open Source Software</journal-title>
+<abbrev-journal-title>JOSS</abbrev-journal-title>
+</journal-title-group>
+<issn publication-format="electronic">2475-9066</issn>
+<publisher>
+<publisher-name>Open Journals</publisher-name>
+</publisher>
+</journal-meta>
+<article-meta>
+<article-id pub-id-type="publisher-id">6028</article-id>
+<article-id pub-id-type="doi">10.21105/joss.06028</article-id>
+<title-group>
+<article-title>Scanbot: An STM Automation Bot</article-title>
+</title-group>
+<contrib-group>
+<contrib contrib-type="author" corresp="yes">
+<contrib-id contrib-id-type="orcid">https://orcid.org/0000-0003-3990-8852</contrib-id>
+<name>
+<surname>Ceddia</surname>
+<given-names>Julian</given-names>
+</name>
+<xref ref-type="aff" rid="aff-1"/>
+<xref ref-type="aff" rid="aff-2"/>
+<xref ref-type="corresp" rid="cor-1"><sup>*</sup></xref>
+</contrib>
+<contrib contrib-type="author">
+<contrib-id contrib-id-type="orcid">https://orcid.org/0000-0003-2282-8223</contrib-id>
+<name>
+<surname>Hellerstedt</surname>
+<given-names>Jack</given-names>
+</name>
+<xref ref-type="aff" rid="aff-1"/>
+<xref ref-type="aff" rid="aff-2"/>
+</contrib>
+<contrib contrib-type="author">
+<contrib-id contrib-id-type="orcid">https://orcid.org/0000-0002-5157-7737</contrib-id>
+<name>
+<surname>Lowe</surname>
+<given-names>Benjamin</given-names>
+</name>
+<xref ref-type="aff" rid="aff-1"/>
+<xref ref-type="aff" rid="aff-2"/>
+</contrib>
+<contrib contrib-type="author">
+<contrib-id contrib-id-type="orcid">https://orcid.org/0000-0003-1140-8485</contrib-id>
+<name>
+<surname>Schiffrin</surname>
+<given-names>Agustin</given-names>
+</name>
+<xref ref-type="aff" rid="aff-1"/>
+<xref ref-type="aff" rid="aff-2"/>
+</contrib>
+<aff id="aff-1">
+<institution-wrap>
+<institution>School of Physics &amp; Astronomy, Monash University,
+Clayton, Victoria 3800, Australia</institution>
+</institution-wrap>
+</aff>
+<aff id="aff-2">
+<institution-wrap>
+<institution>ARC Centre of Excellence in Future Low-Energy Electronics
+Technologies, Monash University, Clayton, Victoria 3800,
+Australia</institution>
+</institution-wrap>
+</aff>
+</contrib-group>
+<author-notes>
+<corresp id="cor-1">* E-mail: <email></email></corresp>
+</author-notes>
+<pub-date date-type="pub" publication-format="electronic" iso-8601-date="2023-03-13">
+<day>13</day>
+<month>3</month>
+<year>2023</year>
+</pub-date>
+<volume>9</volume>
+<issue>99</issue>
+<fpage>6028</fpage>
+<permissions>
+<copyright-statement>Authors of papers retain copyright and release the
+work under a Creative Commons Attribution 4.0 International License (CC
+BY 4.0)</copyright-statement>
+<copyright-year>2022</copyright-year>
+<copyright-holder>The article authors</copyright-holder>
+<license license-type="open-access" xlink:href="https://creativecommons.org/licenses/by/4.0/">
+<license-p>Authors of papers retain copyright and release the work under
+a Creative Commons Attribution 4.0 International License (CC BY
+4.0)</license-p>
+</license>
+</permissions>
+<kwd-group kwd-group-type="author">
+<kwd>Python</kwd>
+<kwd>Scanning Tunneling Microscopy</kwd>
+<kwd>STM</kwd>
+<kwd>Automation</kwd>
+</kwd-group>
+</article-meta>
+</front>
+<body>
+<sec id="summary">
+  <title>Summary</title>
+  <p>Scanning Tunnelling Microscopes (STM) are capable of capturing
+  images of surfaces with atomic-scale resolution. This is achieved by
+  scanning an atomically sharp probe across the surface of the sample
+  while monitoring an electric current. However, the quality of STM data
+  relies heavily on the atomic-scale geometry and composition of the
+  scanning probe apex, as well as the roughness and cleanliness of the
+  scanned region. For instance, blunt tips result in blurry images while
+  contaminated tips can lead to noisy images due to interactions with
+  the sample. As a result, optimal STM data acquisition commonly
+  requires time-consuming tasks such as probe conditioning—i.e.,
+  sharpening via “tip-shaping”, where the apex of the probe can be
+  refined by poking it into a clean metal surface—and identification of
+  areas of interest of the sample. Moreover, the quality of the probe
+  can vary during a scan, especially when scanning over debris or
+  excessively rough areas, necessitating additional tip-shaping.</p>
+  <p>Here, we present Scanbot, a program that fully automates common STM
+  data acquisition techniques, as well as tip-shaping and sample
+  surveying. Scanbot relies on a dual sample holder (DSH;
+  <xref alt="[fig:1]" rid="figU003A1">[fig:1]</xref>), where a sample of
+  interest is mounted alongside a clean reference metal surface, which
+  is ideal for tip preparation. Scanbot is able to analyse STM images
+  and identify when the probe requires conditioning, subsequently moving
+  it from the sample of interest to the clean reference metal, where it
+  will prepare a scanning probe capable of obtaining high-quality STM
+  images. This is accomplished using built-in piezoceramic scanners to
+  maneuver the STM tip while tracking its position through a camera
+  feed; <xref alt="[fig:1]" rid="figU003A1">[fig:1]</xref>b). Once
+  Scanbot determines that the probe has been conditioned adequately, it
+  moves the tip back to the sample of interest and STM data acquisition
+  resumes.</p>
+  <fig>
+    <caption><p>Tracking and maneuvering the STM probe above the dual
+    sample holder (DSH). <bold>a)</bold> Schematic of the STM tip over
+    the dual sample holder setup. A sample of interest is mounted next
+    to a clean reference metal substrate (e.g. Au(111)) which is ideal
+    for tip shaping. <bold>b)</bold> Image from the camera feed used by
+    Scanbot to track and maneuver the STM probe automatically from the
+    sample to the clean reference metal, where it can be refined. The
+    red (green) marker indicates the probe apex position (target
+    position, respectively). See Scanbot
+    <ext-link ext-link-type="uri" xlink:href="https://new-horizons-spm.github.io/scanbot/automation/">documentation</ext-link>
+    for a video example.
+    <styled-content id="figU003A1"></styled-content></p></caption>
+    <graphic mimetype="image" mime-subtype="png" xlink:href="TipTracking.png" />
+  </fig>
+  <p><xref alt="[fig:2]" rid="figU003A2">[fig:2]</xref> demonstrates
+  Scanbot’s ability to recondition a ‘bad’ tip on a clean reference
+  metal surface. Scanbot can gently impinge the scanning probe apex onto
+  a clean, flat region of the metal surface, which results in an imprint
+  associated with the geometry of the tip. This imprint can then be
+  scanned, and the resulting image is similar to the auto-correlation
+  function of the tip’s apex. The quality of the tip can be assessed by
+  measuring the area and circularity of the imprint. If the imprint does
+  not meet the desired criteria, a more aggressive tip shaping action is
+  carried out, and the process is repeated until a high-quality tip is
+  achieved.</p>
+  <fig>
+    <caption><p>Successive STM images (left to right) of the tip’s
+    imprint on a clean metal surface, each following a more agressive
+    tip-shaping action in a different location. The area and circularity
+    of each imprint reflects the geometry of the apex of the scanning
+    probe. Thus the process is repeated until a desired geometry is
+    achieved.<styled-content id="figU003A2"></styled-content></p></caption>
+    <graphic mimetype="image" mime-subtype="png" xlink:href="AutoTipShaping.png" />
+  </fig>
+</sec>
+<sec id="statement-of-need">
+  <title>Statement of need</title>
+  <p>To reduce the time-intensive nature of STM experiments, various
+  innovative solutions have been implemented to automate specific tasks.
+  For instance, Wang et al. created a Python package that automates
+  probe conditioning for Scanning Tunneling Spectroscopy
+  (<xref alt="Wang et al., 2021" rid="ref-Wang_2021" ref-type="bibr">Wang
+  et al., 2021</xref>). However, this package still requires manual
+  preparation of the tip such that it can acquire clean images. Some
+  researchers have employed the use of machine learning algorithms to
+  analyse acquired images and determine when a probe needs refining
+  (<xref alt="Gordon et al., 2020" rid="ref-Gordon_2020" ref-type="bibr">Gordon
+  et al., 2020</xref>;
+  <xref alt="Rashidi &amp; Wolkow, 2018" rid="ref-Rashidi_2018" ref-type="bibr">Rashidi
+  &amp; Wolkow, 2018</xref>), then Reinforcement Learning (RL) agents
+  can condition the probe accordingly
+  (<xref alt="Krull et al., 2020" rid="ref-Schiffrin_2020" ref-type="bibr">Krull
+  et al., 2020</xref>). Although these approaches have significantly
+  advanced automation in STM experiments, they are often tailored to
+  specific surfaces and STM equipment, making it challenging to transfer
+  them directly to other labs studying different kinds of samples or
+  working with different STM systems.</p>
+  <p>To overcome these limitations, we have developed Scanbot, a Python
+  robot that is compatible with a broader range of STMs, specifically
+  those compatible with the Nanonis V5 software
+  (<xref alt="Ceddia et al., 2022" rid="ref-Ceddia_2022" ref-type="bibr">Ceddia
+  et al., 2022</xref>;
+  <xref alt="Specs-GmBH, 2015" rid="ref-Nanonis_2015" ref-type="bibr">Specs-GmBH,
+  2015</xref>). Additionally, our package incorporates Scanbot’s
+  distinctive approach to tip shaping, which involves monitoring the
+  tip’s motion above a dual sample holder. This method is particularly
+  beneficial in experiments where the sample’s properties might make it
+  challenging to achieve a high-quality scanning probe without needing
+  to manually switch out the sample for a clean metal on which the tip
+  can be prepared.</p>
+  <p>Scanbot has been developed in a modular fashion, which means its
+  functionality can easily be expanded or improved through contributions
+  from the open-source community. Furthermore, through the use of
+  <ext-link ext-link-type="uri" xlink:href="https://new-horizons-spm.github.io/scanbot/hooks/">hooks</ext-link>,
+  users can customise or replace key funcionalities that are system- or
+  lab-specific, without rewriting Scanbot’s source code. This has the
+  advantage of being able to update Scanbot to the latest version
+  without losing customised code. Such hooks can also be used to improve
+  Scanbot’s existing functionality or test potential new features. For
+  instance, Scanbot’s algorithmic approach to automated tip shaping
+  might benefit the integration of an RL agent. This could be achieved
+  by leveraging the hook
+  <ext-link ext-link-type="uri" xlink:href="https://new-horizons-spm.github.io/scanbot/hooks/#hk_tipshape">hk_tipShape</ext-link>,
+  where important parameters related to tip shaping can be adjusted
+  based on images of the tip’s imprint. Complete documentation for
+  Scanbot, including how such hooks can be leveraged, can be found at
+  <ext-link ext-link-type="uri" xlink:href="https://new-horizons-spm.github.io/scanbot">https://new-horizons-spm.github.io/scanbot</ext-link>.</p>
+</sec>
+<sec id="acknowledgements">
+  <title>Acknowledgements</title>
+  <p>A.S. acknowledges funding support from the ARC Future Fellowship
+  scheme (FT150100426). J.C., B.L., and J.H. acknowledge funding support
+  from the Australian Research Council (ARC) Centre of Excellence in
+  Future Low-Energy Electronics Technologies (CE170100039). J.C., and
+  B.L. are supported through an Australian Government Research Training
+  Program (RTP) Scholarship.</p>
+</sec>
+</body>
+<back>
+<ref-list>
+  <title></title>
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