<?xml version="1.0" encoding="utf-8"?>
<export-example>
  <doc>
    <id>51391</id>
    <completedYear/>
    <publishedYear>2018</publishedYear>
    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst>229</pageFirst>
    <pageLast>234</pageLast>
    <pageNumber/>
    <edition/>
    <issue/>
    <volume>89</volume>
    <type>conferenceobject</type>
    <publisherName>World Scientific</publisherName>
    <publisherPlace>New Jersey</publisherPlace>
    <creatingCorporation/>
    <contributingCorporation/>
    <belongsToBibliography>1</belongsToBibliography>
    <completedDate>--</completedDate>
    <publishedDate>--</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="eng">Mathematical and statistical tools for online NMR spectroscopy in chemical processes</title>
    <abstract language="eng">Monitoring chemical reactions is the key to chemical process control. Today, mainly optical online methods are applied, which require excessive calibration effort. NMR spectroscopy has a high potential for direct loop process control while exhibiting short set-up times. Compact NMR instruments make NMR spectroscopy accessible in industrial and harsh environ¬ments for advanced process monitoring and control, as demonstrated within the European Union’s Horizon 2020 project CONSENS.&#13;
We present a range of approaches for the automated spectra analysis moving from conventional multivariate statistical approach, (i.e., Partial Least Squares Regression) to physically motivated spectral models (i.e., Indirect Hard Modelling and Quantum Mechanical calculations). By using the benefits of traditional qNMR experiments data analysis models can meet the demands of the PAT community (Process Analytical Technology) regarding low calibration effort/calibration free methods, fast adaptions for new reactants or derivatives and robust automation schemes.</abstract>
    <parentTitle language="eng">Advanced Mathematical and Computational Tools in Metrology and Testing XI</parentTitle>
    <identifier type="isbn">978-9-813-27429-7</identifier>
    <enrichment key="eventName">Advanced Mathematical and Computational Tools in Metrology and Testing conference</enrichment>
    <enrichment key="eventPlace">Glasgow, United Kingdom</enrichment>
    <enrichment key="eventStart">29.08.2017</enrichment>
    <enrichment key="eventEnd">31.08.2017</enrichment>
    <enrichment key="date_peer_review">06.10.2020</enrichment>
    <author>Simon Kern</author>
    <author>Svetlana Guhl</author>
    <author>Klas Meyer</author>
    <author>Lukas Wander</author>
    <author>Andrea Paul</author>
    <author>Wolfram Bremser</author>
    <author>Michael Maiwald</author>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Online NMR Spectroscopy</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Process Control</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Partial Least Squares Regression</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Indirect Hard Modelling</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Quantum Mechanics</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>First Principles</value>
    </subject>
    <collection role="literaturgattung" number="">Verlagsliteratur</collection>
    <collection role="fulltextaccess" number="">Datei im Netzwerk der BAM verfügbar ("Closed Access")</collection>
  </doc>
  <doc>
    <id>43252</id>
    <completedYear/>
    <publishedYear>2017</publishedYear>
    <thesisYearAccepted/>
    <language>deu</language>
    <pageFirst>61</pageFirst>
    <pageLast>66</pageLast>
    <pageNumber/>
    <edition/>
    <issue/>
    <volume/>
    <type>conferenceobject</type>
    <publisherName>AMA Service GmbH</publisherName>
    <publisherPlace>Berlin</publisherPlace>
    <creatingCorporation>AMA Verband für Sensorik und Messtechnik e.V.</creatingCorporation>
    <contributingCorporation/>
    <belongsToBibliography>0</belongsToBibliography>
    <completedDate>--</completedDate>
    <publishedDate>--</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="deu">Innen hui und außen pfui – Smarte Prozess-Sensoren in der gegenwärtigen Automatisierungslandschaft der Prozessindustrie</title>
    <abstract language="deu">Der Wandel von der aktuellen Automation zum smarten Sensor ist im vollen Gange. Automatisierungstechnik, sowie die Informations- und Kommunikationstechnik (IKT) verschmelzen zunehmend. Eine Topologie für smarte Sensoren, die das Zusammenwirken mit daten- und modellbasierten Steuerungen bis hin zur Softsensorik beschreibt gibt es bis heute jedoch noch nicht. Um zu einer störungsfreien Kommunikation aller Komponenten auf Basis eines einheitlichen Protokolls zu kommen sollte die Prozessindustrie die Weichen für eine smarte und sichere Kommunikationsarchitektur stellen. Sie verwehrt stattdessen die Entwicklungen ihrer Zulieferer und wartet lieber ab. Der Beitrag greift die Anforderungen der Technologie-Roadmap „Prozess-Sensoren 4.0“ auf und zeigt Möglichkeiten zu ihrer Realisierung am Beispiel eines Online-NMR-Analysators, der im Rahmen eines EU-Projekts entwickelt wurde.</abstract>
    <parentTitle language="deu">Tagungsband 13. Dresdner Sensor-Symposium</parentTitle>
    <identifier type="doi">10.5162/13dss2017/2.1</identifier>
    <identifier type="url">https://www.ama-science.org/proceedings/details/2717</identifier>
    <identifier type="isbn">978-3-9816876-5-1</identifier>
    <enrichment key="eventName">13. Dresdner Sensor Symposium</enrichment>
    <enrichment key="eventPlace">Dresden, Germany</enrichment>
    <enrichment key="eventStart">04.12.2017</enrichment>
    <enrichment key="eventEnd">06.12.2017</enrichment>
    <author>Michael Maiwald</author>
    <author>Patrick Gräßer</author>
    <author>Lukas Wander</author>
    <author>Svetlana Guhl</author>
    <author>Klas Meyer</author>
    <author>Simon Kern</author>
    <subject>
      <language>deu</language>
      <type>uncontrolled</type>
      <value>Smarte Feldgeräte</value>
    </subject>
    <subject>
      <language>deu</language>
      <type>uncontrolled</type>
      <value>Process Control</value>
    </subject>
    <subject>
      <language>deu</language>
      <type>uncontrolled</type>
      <value>Modulare Produktion</value>
    </subject>
    <subject>
      <language>deu</language>
      <type>uncontrolled</type>
      <value>Online-NMR-Spektroskopie</value>
    </subject>
    <subject>
      <language>deu</language>
      <type>uncontrolled</type>
      <value>Indirect Hard Modeling</value>
    </subject>
    <subject>
      <language>deu</language>
      <type>uncontrolled</type>
      <value>Industrie 4.0</value>
    </subject>
    <collection role="ddc" number="543">Analytische Chemie</collection>
    <collection role="fulltextaccess" number="">Datei im Netzwerk der BAM verfügbar ("Closed Access")</collection>
    <collection role="literaturgattung" number="">Graue Literatur</collection>
  </doc>
  <doc>
    <id>43254</id>
    <completedYear/>
    <publishedYear>2017</publishedYear>
    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst>P2, 209</pageFirst>
    <pageLast>212</pageLast>
    <pageNumber/>
    <edition/>
    <issue/>
    <volume/>
    <type>conferenceobject</type>
    <publisherName>AMA Service GmbH</publisherName>
    <publisherPlace>Berlin</publisherPlace>
    <creatingCorporation>AMA Verband für Sensorik und Messtechnik e.V.</creatingCorporation>
    <contributingCorporation/>
    <belongsToBibliography>0</belongsToBibliography>
    <completedDate>--</completedDate>
    <publishedDate>--</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="eng">Mathematical and statistical tools for online NMR spectroscopy in chemical processes</title>
    <abstract language="eng">Monitoring chemical reactions is the key to chemical process control. Today, mainly optical online methods are applied, which require excessive calibration effort. NMR spectroscopy has a high potential for direct loop process control while exhibiting short set-up times. Compact NMR instruments make NMR spectroscopy accessible in industrial and harsh environments for advanced process Monitoring and control, as demonstrated within the European Union’s Horizon 2020 project CONSENS.&#13;
We present a range of approaches for the automated spectra analysis moving from conventional multivariate statistical approach, (i.e., Partial Least Squares Regression) to physically motivated spectral models (i.e., Indirect Hard Modelling and Quantum Mechanical calculations). By using the benefits of traditional qNMR experiments data analysis models can meet the demands of the PAT community (Process Analytical Technology) regarding low calibration effort/calibration free methods, fast adaptions for new reactants or derivatives and robust automation schemes.</abstract>
    <parentTitle language="deu">Tagungsband 13. Dresdner Sensor-Symposium</parentTitle>
    <identifier type="doi">10.5162/13dss2017/P2.07</identifier>
    <identifier type="url">https://www.ama-science.org/proceedings/details/2748</identifier>
    <identifier type="isbn">978-3-9816876-5-1</identifier>
    <enrichment key="eventName">13. Dresdner Sensor Symposium</enrichment>
    <enrichment key="eventPlace">Dresden, Germany</enrichment>
    <enrichment key="eventStart">04.12.2017</enrichment>
    <enrichment key="eventEnd">06.12.2017</enrichment>
    <author>Simon Kern</author>
    <author>Svetlana Guhl</author>
    <author>Klas Meyer</author>
    <author>Lukas Wander</author>
    <author>Andrea Paul</author>
    <author>Michael Maiwald</author>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Online NMR spectroscopy</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Process control</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Partial least squares regression</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Indirect hard modeling</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Quantum mechanics</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>First principles</value>
    </subject>
    <collection role="ddc" number="543">Analytische Chemie</collection>
    <collection role="fulltextaccess" number="">Datei im Netzwerk der BAM verfügbar ("Closed Access")</collection>
    <collection role="literaturgattung" number="">Graue Literatur</collection>
  </doc>
  <doc>
    <id>43552</id>
    <completedYear/>
    <publishedYear>2017</publishedYear>
    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst>1</pageFirst>
    <pageLast>31</pageLast>
    <pageNumber/>
    <edition/>
    <issue/>
    <volume/>
    <type>report</type>
    <publisherName/>
    <publisherPlace/>
    <creatingCorporation/>
    <contributingCorporation/>
    <belongsToBibliography>0</belongsToBibliography>
    <completedDate>--</completedDate>
    <publishedDate>--</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="eng">Validation report on NMR</title>
    <abstract language="eng">The departure from the current automation landscape to next generation automation concepts for the process industry has already begun. Smart functions of sensors simplify their use and enable plug and play integration, even though they may appear to be more complex at first sight. Smart sensors enable concepts like self-diagnostics, self-calibration, and self-configuration/ parameterization whenever our current automation landscape allows it.&#13;
Here we summarize the currently discussed general requirements for process sensors 4.0 and introduce a smart online NMR sensor module as example, which was developed for an intensified industrial process funded by the EU’s Horizon 2020 research and innovation programme (www.consensspire.eu).</abstract>
    <identifier type="urn">urn:nbn:de:kobv:b43-435521</identifier>
    <licence>Creative Commons - CC BY-NC-ND - Namensnennung - Nicht kommerziell - Keine Bearbeitungen 4.0 International</licence>
    <author>Simon Kern</author>
    <author>Svetlana Guhl</author>
    <author>Klas Meyer</author>
    <author>Michael Maiwald</author>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Process Monitoring</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Online NMR Spectroscopy</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Indirect Hard Modeling</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Process Control</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Process Analytical Technology</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>CONSENS</value>
    </subject>
    <collection role="ddc" number="543">Analytische Chemie</collection>
    <collection role="fulltextaccess" number="">Datei für die Öffentlichkeit verfügbar ("Open Access")</collection>
    <collection role="literaturgattung" number="">Graue Literatur</collection>
    <collection role="unnumberedseries" number="">Wissenschaftliche Artikel der BAM</collection>
    <thesisPublisher>Bundesanstalt für Materialforschung und -prüfung (BAM)</thesisPublisher>
    <file>https://opus4.kobv.de/opus4-bam/files/43552/2017-12-31_CONSENS_Deliverable_1.9_NMR-Sensor_final_report.pdf</file>
  </doc>
  <doc>
    <id>45901</id>
    <completedYear/>
    <publishedYear>2018</publishedYear>
    <thesisYearAccepted/>
    <language>deu</language>
    <pageFirst>1236</pageFirst>
    <pageLast>1236</pageLast>
    <pageNumber/>
    <edition/>
    <issue>9</issue>
    <volume>90</volume>
    <type>conferenceobject</type>
    <publisherName>Wiley-VCH Verlag GmbH &amp; Co. KGaA</publisherName>
    <publisherPlace>Weinheim</publisherPlace>
    <creatingCorporation>DECHEMA, Gesellschaft für Chemische Technik und Biotechnologie e.V.</creatingCorporation>
    <contributingCorporation/>
    <belongsToBibliography>0</belongsToBibliography>
    <completedDate>--</completedDate>
    <publishedDate>--</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="deu">Produzieren Sie schon oder kalibrieren Sie noch? – Online-NMR-Spektrometer als Smarte Feldgeräte</title>
    <abstract language="deu">Der Vortrag zeigt allgemeine Anforderungen an "smarte Feldgeräte" und deren Entwicklung in den vergangenen Jahren. Am Beispiel eines smarten Online-NMR-Sensors, der in einem EU-Projekt von der BAM entwickelt wurde, wird die Umsetzung der Anforderung aufgezeigt. Schließlich werden weitere Technologieanforderungen und Lösungsansätze vorgestellt.</abstract>
    <parentTitle language="deu">Chemie Ingenieur Technik</parentTitle>
    <identifier type="doi">10.1002/cite.201855229</identifier>
    <identifier type="url">https://onlinelibrary.wiley.com/doi/abs/10.1002/cite.201855229</identifier>
    <identifier type="issn">0009-286X</identifier>
    <note>Geburtsname von Bornemann-Pfeiffer, Martin: Bornemann, M. -  Birth name of Bornemann-Pfeiffer, Martin: Bornemann, M.</note>
    <enrichment key="eventName">ProcessNet-Jahrestagung und 33. DECHEMA-Jahrestagung der Biotechnologen</enrichment>
    <enrichment key="eventPlace">Aachen, Germany</enrichment>
    <enrichment key="eventStart">10.09.2018</enrichment>
    <enrichment key="eventEnd">13.09.2018</enrichment>
    <author>Svetlana Guhl</author>
    <author>Simon Kern</author>
    <author>Klas Meyer</author>
    <author>Lukas Wander</author>
    <author>Martin Bornemann-Pfeiffer</author>
    <author>Michael Maiwald</author>
    <subject>
      <language>deu</language>
      <type>uncontrolled</type>
      <value>Prozessanalytik</value>
    </subject>
    <subject>
      <language>deu</language>
      <type>uncontrolled</type>
      <value>Prozessindustrie</value>
    </subject>
    <subject>
      <language>deu</language>
      <type>uncontrolled</type>
      <value>Online-NMR-Spektroskopie</value>
    </subject>
    <subject>
      <language>deu</language>
      <type>uncontrolled</type>
      <value>Datenkonzepte</value>
    </subject>
    <subject>
      <language>deu</language>
      <type>uncontrolled</type>
      <value>Datenanalyse</value>
    </subject>
    <subject>
      <language>deu</language>
      <type>uncontrolled</type>
      <value>CONSENS</value>
    </subject>
    <collection role="ddc" number="543">Analytische Chemie</collection>
    <collection role="literaturgattung" number="">Verlagsliteratur</collection>
    <collection role="fulltextaccess" number="">Datei im Netzwerk der BAM verfügbar ("Closed Access")</collection>
  </doc>
  <doc>
    <id>45902</id>
    <completedYear/>
    <publishedYear>2018</publishedYear>
    <thesisYearAccepted/>
    <language>deu</language>
    <pageFirst>1237</pageFirst>
    <pageLast>1237</pageLast>
    <pageNumber/>
    <edition/>
    <issue/>
    <volume>90</volume>
    <type>conferenceobject</type>
    <publisherName>Wiley-VCH Verlag GmbH &amp; Co. KGaA</publisherName>
    <publisherPlace>Weinheim</publisherPlace>
    <creatingCorporation>DECHEMA, Gesellschaft für Chemische Technik und Biotechnologie e.V.</creatingCorporation>
    <contributingCorporation/>
    <belongsToBibliography>0</belongsToBibliography>
    <completedDate>--</completedDate>
    <publishedDate>--</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="deu">PAT-basierte iterative Optimierung der Fahrweise eines kontinuierlichen organischen Syntheseprozesses</title>
    <abstract language="deu">Im Zuge der Digitalisierung der Prozessindustrie werden zunehmend modellbasiere Echtzeitoptimierungsverfahren eingesetzt, sog. „Advanced Process Control“. Mithilfe der sogenannten Modifier-Adaptation ist eine iterative Betriebspunktoptimierung auch mit ungenauen Modellen möglich, sofern zuverlässige Prozessdaten zur Verfügung stehen. Am Beispiel eines smarten Online-NMR-Sensors, der in einem EU-Projekt von der BAM entwickelt wurde, konnte das Konzept in einer modularen Produktionsanlage zur Herstellung eines pharmazeutischen Wirkstoffs erfolgreich getestet werden.</abstract>
    <parentTitle language="deu">Chemie Ingenieur Technik</parentTitle>
    <identifier type="doi">10.1002/cite.201855233</identifier>
    <identifier type="url">https://onlinelibrary.wiley.com/doi/abs/10.1002/cite.201855233</identifier>
    <identifier type="issn">0009-286X</identifier>
    <enrichment key="eventName">ProcessNet-Jahrestagung und 33. DECHEMA-Jahrestagung der Biotechnologen</enrichment>
    <enrichment key="eventPlace">Aachen, Germany</enrichment>
    <enrichment key="eventStart">10.09.2018</enrichment>
    <enrichment key="eventEnd">13.09.2018</enrichment>
    <author>A. R. Gottu Mukkula</author>
    <author>S. Engell</author>
    <author>Simon Kern</author>
    <author>Svetlana Guhl</author>
    <author>Klas Meyer</author>
    <author>Michael Maiwald</author>
    <subject>
      <language>deu</language>
      <type>uncontrolled</type>
      <value>Prozessanalytik</value>
    </subject>
    <subject>
      <language>deu</language>
      <type>uncontrolled</type>
      <value>Echtzeitoptimierungsverfahren</value>
    </subject>
    <subject>
      <language>deu</language>
      <type>uncontrolled</type>
      <value>Modifier-Adaptation</value>
    </subject>
    <subject>
      <language>deu</language>
      <type>uncontrolled</type>
      <value>Prozess-Steuerung</value>
    </subject>
    <subject>
      <language>deu</language>
      <type>uncontrolled</type>
      <value>Betriebspunktoptimierung</value>
    </subject>
    <subject>
      <language>deu</language>
      <type>uncontrolled</type>
      <value>CONSENS</value>
    </subject>
    <collection role="ddc" number="543">Analytische Chemie</collection>
    <collection role="literaturgattung" number="">Verlagsliteratur</collection>
    <collection role="fulltextaccess" number="">Datei im Netzwerk der BAM verfügbar ("Closed Access")</collection>
  </doc>
  <doc>
    <id>44847</id>
    <completedYear/>
    <publishedYear>2018</publishedYear>
    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst>3349</pageFirst>
    <pageLast>3360</pageLast>
    <pageNumber/>
    <edition/>
    <issue>14</issue>
    <volume>410</volume>
    <type>article</type>
    <publisherName>Springer</publisherName>
    <publisherPlace>Berlin, Heidelberg</publisherPlace>
    <creatingCorporation/>
    <contributingCorporation/>
    <belongsToBibliography>1</belongsToBibliography>
    <completedDate>--</completedDate>
    <publishedDate>--</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="eng">Online low-field NMR spectroscopy for process control of an industrial lithiation reaction—automated data analysis</title>
    <abstract language="eng">Monitoring specific chemical properties is the key to chemical process control. Today, mainly optical online methods are applied, which require time- and cost-intensive calibration effort. NMR spectroscopy, with its advantage being a direct comparison method without need for calibration, has a high potential for closed-loop process control while exhibiting short set-up times. Compact NMR instruments make NMR spectroscopy accessible in industrial and rough environments for process monitoring and advanced process control strategies.&#13;
We present a fully automated data analysis approach which is completely based on physically motivated spectral models as first principles information (Indirect Hard Modelling – IHM) and applied it to a given pharmaceutical lithiation reaction in the framework of the European Union’s Horizon 2020 project CONSENS. Online low-field NMR (LF NMR) data was analysed by IHM with low calibration effort, compared to a multivariate PLS-R (Partial Least Squares Regression) approach, and both validated using online high-field NMR (HF NMR) spectroscopy.</abstract>
    <parentTitle language="eng">Analytical and Bioanalytical Chemistry</parentTitle>
    <identifier type="doi">10.1007/s00216-018-1020-z</identifier>
    <identifier type="url">https://link.springer.com/article/10.1007/s00216-018-1020-z</identifier>
    <identifier type="issn">1618-2642</identifier>
    <identifier type="issn">1618-2650</identifier>
    <enrichment key="date_peer_review">07.05.2018</enrichment>
    <author>Simon Kern</author>
    <author>Klas Meyer</author>
    <author>Svetlana Guhl</author>
    <author>Patrick Gräßer</author>
    <author>Andrea Paul</author>
    <author>R. King</author>
    <author>Michael Maiwald</author>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Online NMR spectroscopy</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Process analytical technology</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Partial Least Squares Regression</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Indirect Hard Modeling</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Benchtop NMR Spectroscopy</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Smart Sensors</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>CONSENS</value>
    </subject>
    <collection role="ddc" number="543">Analytische Chemie</collection>
    <collection role="literaturgattung" number="">Verlagsliteratur</collection>
    <collection role="fulltextaccess" number="">Datei im Netzwerk der BAM verfügbar ("Closed Access")</collection>
  </doc>
  <doc>
    <id>48063</id>
    <completedYear/>
    <publishedYear>2018</publishedYear>
    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst/>
    <pageLast/>
    <pageNumber/>
    <edition/>
    <issue/>
    <volume/>
    <type>researchdata</type>
    <publisherName>Zenodo</publisherName>
    <publisherPlace>Geneva</publisherPlace>
    <creatingCorporation/>
    <contributingCorporation/>
    <belongsToBibliography>0</belongsToBibliography>
    <completedDate>--</completedDate>
    <publishedDate>--</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="eng">Raw data of pilot plant runs for CONSENS project (Case study 1)</title>
    <abstract language="eng">In case study one of the CONSENS project, two aromatic substances were coupled by a lithiation reaction, which is a prominent example in pharmaceutical industry. The two aromatic reactants (Aniline and o-FNB) were mixed with Lithium-base (LiHMDS) in a continuous modular plant to produce the desired product (Li-NDPA) and a salt (LiF). The salt precipitates which leads to the formation of particles. The feed streams were subject to variation to drive the plant to its optimum. &#13;
&#13;
The uploaded data comprises the results from four days during continuous plant operation time. Each day is denoted from day 1-4 and represents the dates 2017-09-26, 2017-09-28, 2017-10-10, 2017-10-17.&#13;
&#13;
In the following the contents of the files are explained.</abstract>
    <identifier type="doi">10.5281/zenodo.1438233</identifier>
    <enrichment key="ScientificResourceTypeGeneral">Datensatz</enrichment>
    <enrichment key="RelatedIdentifier">https://nbn-resolving.org/urn:nbn:de:kobv:b43-480623</enrichment>
    <licence>Creative Commons - CC BY - Namensnennung 4.0 International</licence>
    <author>Simon Kern</author>
    <author>Lukas Wander</author>
    <author>Klas Meyer</author>
    <author>Svetlana Guhl</author>
    <author>A. R. Gottu Mukkula</author>
    <author>M. Holtkamp</author>
    <author>M. Salge</author>
    <author>C. Fleischer</author>
    <author>N. Weber</author>
    <author>S. Engell</author>
    <author>Andrea Paul</author>
    <author>R. King</author>
    <author>Michael Maiwald</author>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Process Analytical Technology</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Multivariate Data Analysis</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Nuclear Magnetic Resonance</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Near Infrared Spectroscopy</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Continuous Manufacturing</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>CONSENS</value>
    </subject>
    <collection role="ddc" number="543">Analytische Chemie</collection>
    <collection role="fulltextaccess" number="">Datei für die Öffentlichkeit verfügbar ("Open Access")</collection>
    <collection role="literaturgattung" number="">Graue Literatur</collection>
    <collection role="unnumberedseries" number="">Forschungsdatensätze der BAM</collection>
    <thesisPublisher>Bundesanstalt für Materialforschung und -prüfung (BAM)</thesisPublisher>
  </doc>
  <doc>
    <id>40229</id>
    <completedYear/>
    <publishedYear>2017</publishedYear>
    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst>72</pageFirst>
    <pageLast>73</pageLast>
    <pageNumber/>
    <edition/>
    <issue/>
    <volume/>
    <type>conferenceobject</type>
    <publisherName/>
    <publisherPlace>Frankfurt a. M.</publisherPlace>
    <creatingCorporation>DECHEMA e. V., Frankfurt</creatingCorporation>
    <contributingCorporation/>
    <belongsToBibliography>0</belongsToBibliography>
    <completedDate>--</completedDate>
    <publishedDate>--</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="eng">Design and Validation of a Compact NMR Analyser</title>
    <abstract language="eng">Monitoring chemical reactions is the key to chemical process control. Today, mainly&#13;
optical online methods are applied. NMR spectroscopy has a high potential for direct&#13;
loop process control. Compact NMR instruments based on permanent magnets&#13;
are robust and relatively inexpensive analysers, which feature advantages like low&#13;
cost, low maintenance, ease of use, and cryogen-free operation. Instruments for&#13;
online NMR measurements equipped with a flow-through cell, possessing a good&#13;
signal-to-noise-ratio, sufficient robustness, and meeting the requirements for&#13;
integration into industrial plants (i.e., explosion safety and fully automated data&#13;
analysis) are currently not available off the rack.&#13;
Intensified continuous processes are in focus of current research. Flexible (modular)&#13;
chemical plants can produce different products using the same equipment with short&#13;
down-times between campaigns and quick introduction of new products to the&#13;
market. In continuous flow processes online sensor data and tight closed-loop control&#13;
of the product quality are mandatory. If these are not available, there is a huge risk of&#13;
producing large amounts of out-of-spec (OOS) products. This is addressed in the&#13;
European Unionʼs Research Project CONSENS (Integrated Control and Sensing)&#13;
by development and integration of smart sensor modules for process monitoring and&#13;
control within such modular plant setups.&#13;
The presented NMR module is provided in an explosion proof housing of 57 x 57 x&#13;
85 cm module size and involves a compact 43.5 MHz NMR spectrometer together&#13;
with an acquisition unit and a programmable logic controller for automated data&#13;
preparation (phasing, baseline correction) and evaluation. Indirect Hard Modeling&#13;
(IHM) was selected for data analysis of the low-field NMR spectra. A set-up for&#13;
monitoring continuous reactions in a thermostated 1/8” tubular reactor using&#13;
automated syringe pumps was used to validate the IHM models by using high-field&#13;
NMR spectroscopy as analytical reference method.</abstract>
    <parentTitle language="eng">Processdings of 4th European Conference on Process Analytics and Control Technology (EuroPACT 2017)</parentTitle>
    <enrichment key="eventName">4th European Conference on Process Analytics and Control Technology (EuroPACT 2017)</enrichment>
    <enrichment key="eventPlace">Potsdam, Germany</enrichment>
    <enrichment key="eventStart">10.05.2017</enrichment>
    <enrichment key="eventEnd">12.05.2017</enrichment>
    <author>Simon Kern</author>
    <author>Svetlana Guhl</author>
    <author>Klas Meyer</author>
    <author>Andrea Paul</author>
    <author>Lukas Wander</author>
    <author>Patrick Gräßer</author>
    <author>Michael Maiwald</author>
    <subject>
      <language>deu</language>
      <type>uncontrolled</type>
      <value>Prozessanalytik</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Reaction Monitoring</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Online NMR Spectrsocopy</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Process Analytical Technology</value>
    </subject>
    <subject>
      <language>deu</language>
      <type>uncontrolled</type>
      <value>Industrie 4.0</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>EuroPACT</value>
    </subject>
    <collection role="ddc" number="543">Analytische Chemie</collection>
    <collection role="fulltextaccess" number="">Datei im Netzwerk der BAM verfügbar ("Closed Access")</collection>
    <collection role="literaturgattung" number="">Graue Literatur</collection>
  </doc>
  <doc>
    <id>40231</id>
    <completedYear/>
    <publishedYear>2017</publishedYear>
    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst>103</pageFirst>
    <pageLast>103</pageLast>
    <pageNumber/>
    <edition/>
    <issue/>
    <volume/>
    <type>conferenceobject</type>
    <publisherName/>
    <publisherPlace>Frankfurt a. M.</publisherPlace>
    <creatingCorporation>DECHEMA e. V., Frankfurt</creatingCorporation>
    <contributingCorporation/>
    <belongsToBibliography>0</belongsToBibliography>
    <completedDate>--</completedDate>
    <publishedDate>--</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="eng">Online NMR Spectroscopy for Process Monitoring in Intensified Continuous Production Plants</title>
    <abstract language="eng">Process analytical techniques are extremely useful tools for chemical production and manufacture and are of particular interest to the pharmaceutical, food and (petro-) chemical industries.&#13;
Today, mainly optical online methods are applied. NMR spectroscopy has a high potential for direct loop process control. Compact NMR instruments based on permanent magnets are robust and relatively inexpensive analysers, which feature advantages like low cost, low maintenance, ease of use, and cryogen-free operation. Instruments for online NMR measurements equipped with a flow-through cell, possessing a good signal-to-noise-ratio, sufficient robustness, and meeting the requirements for integration into industrial plants (i.e., explosion safety and fully automated data analysis) are currently not available off the rack.&#13;
A major advantage of NMR spectroscopy is that the method features a high linearity between absolute signal area and sample concentration, which makes it an absolute analytical comparison method which is independent of the matrix. This is an important prerequisite for robust data evaluation strategies within a control concept and reduces the need for extensive maintenance of the evaluation model over the time of operation. Additionally, NMR spectroscopy provides orthogonal, but complimentary physical information to conventional, e.g., optical spectroscopy. It increases the accessible information for technical processes, where aromatic-toaliphatic conversions or isomerizations occur and conventional methods fail due to only minor changes in functional groups.&#13;
As a technically relevant example, the catalytic hydrogenation of 2-butyne-1,4-diol and further pharmaceutical reactions were studied using an online NMR sensor based on a commercially available low-field NMR spectrometer within the framework of the EU project CONSENS (Integrated Control and Sensing).</abstract>
    <parentTitle language="eng">Processdings of 4th European Conference on Process Analytics and Control Technology (EuroPACT 2017)</parentTitle>
    <enrichment key="eventName">4th European Conference on Process Analytics and Control Technology (EuroPACT 2017)</enrichment>
    <enrichment key="eventPlace">Potsdam, Germany</enrichment>
    <enrichment key="eventStart">10.05.2017</enrichment>
    <enrichment key="eventEnd">12.05.2017</enrichment>
    <author>Svetlana Guhl</author>
    <author>Simon Kern</author>
    <author>Klas Meyer</author>
    <author>Patrick Gräßer</author>
    <author>Lukas Wander</author>
    <author>Michael Maiwald</author>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Process Monitoring</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>CONSENS</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Online NMR Spectroscopy</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Process Analytical Technology</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Process control</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Hydration</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>EuroPACT</value>
    </subject>
    <collection role="fulltextaccess" number="">Datei im Netzwerk der BAM verfügbar ("Closed Access")</collection>
    <collection role="literaturgattung" number="">Graue Literatur</collection>
  </doc>
  <doc>
    <id>52453</id>
    <completedYear/>
    <publishedYear>2020</publishedYear>
    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst>11773</pageFirst>
    <pageLast>11779</pageLast>
    <pageNumber/>
    <edition/>
    <issue>2</issue>
    <volume>53</volume>
    <type>article</type>
    <publisherName>Elsevier</publisherName>
    <publisherPlace>Amsterdam</publisherPlace>
    <creatingCorporation/>
    <contributingCorporation/>
    <belongsToBibliography>1</belongsToBibliography>
    <completedDate>--</completedDate>
    <publishedDate>--</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="eng">An Application of Modifier Adaptation with Quadratic Approximation on a Pilot Scale Plant in Industrial Environment</title>
    <abstract language="eng">The goal of this work is to identify the optimal operating input for a lithiation reaction that is performed in a highly innovative pilot scale continuous flow chemical plant in an industrial environment, taking into account the process and safety constraints. The main challenge is to identify the optimum operation in the absence of information about the reaction mechanism and the reaction kinetics. We employ an iterative real-time optimization scheme called modifier adaptation with quadratic approximation (MAWQA) to identify the plant optimum in the presence of plant-model mismatch and measurement noise. A novel NMR PAT-sensor is used to measure the concentration of the reactants and of the product at the reactor outlet. The experiment results demonstrate the capabilities of the iterative optimization using the MAWQA algorithm in driving a complex real plant to an economically optimal operating point in the presence of plant-model mismatch and of process and measurement uncertainties.</abstract>
    <parentTitle language="eng">IFAC-PapersOnLine</parentTitle>
    <identifier type="issn">1522-2640</identifier>
    <identifier type="doi">10.1016/j.ifacol.2020.12.685</identifier>
    <identifier type="urn">urn:nbn:de:kobv:b43-524531</identifier>
    <enrichment key="opus.source">publish</enrichment>
    <enrichment key="date_peer_review">24.06.2021</enrichment>
    <licence>Creative Commons - CC BY-NC-ND - Namensnennung - Nicht kommerziell - Keine Bearbeitungen 4.0 International</licence>
    <author>A. R. Gottu Mukkula</author>
    <author>Simon Kern</author>
    <author>M. Salge</author>
    <author>M. Holtkamp</author>
    <author>Svetlana Guhl</author>
    <author>C. Fleischer</author>
    <author>Klas Meyer</author>
    <author>M. Remelhe</author>
    <author>Michael Maiwald</author>
    <author>S. Engell</author>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Process Analytical Technology</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Online NMR Spectroscopy</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Process Industry</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Iterative real-time optimization</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Modifier adaptation</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Plant-model mismatch</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Reactor control</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>CONSENS</value>
    </subject>
    <collection role="ddc" number="543">Analytische Chemie</collection>
    <collection role="institutes" number="">1 Analytische Chemie; Referenzmaterialien</collection>
    <collection role="institutes" number="">1.4 Non-Target-Analytik</collection>
    <collection role="themenfelder" number="">Umwelt</collection>
    <collection role="themenfelder" number="">Chemie und Prozesstechnik</collection>
    <collection role="themenfelder" number="">Chemische Charakterisierung und Spurenanalytik</collection>
    <collection role="literaturgattung" number="">Verlagsliteratur</collection>
    <collection role="fulltextaccess" number="">Datei für die Öffentlichkeit verfügbar ("Open Access")</collection>
    <collection role="unnumberedseries" number="">Wissenschaftliche Artikel der BAM</collection>
    <collection role="themenfelder" number="">Sensorik</collection>
    <thesisPublisher>Bundesanstalt für Materialforschung und -prüfung (BAM)</thesisPublisher>
    <file>https://opus4.kobv.de/opus4-bam/files/52453/IFAC_53_2020_11773-11779_Gottu-Mukula_Modifier_Adaptation_CONSENS.pdf</file>
  </doc>
  <doc>
    <id>47715</id>
    <completedYear/>
    <publishedYear>2019</publishedYear>
    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst/>
    <pageLast/>
    <pageNumber/>
    <edition/>
    <issue/>
    <volume/>
    <type>poster</type>
    <publisherName/>
    <publisherPlace/>
    <creatingCorporation/>
    <contributingCorporation/>
    <belongsToBibliography>0</belongsToBibliography>
    <completedDate>--</completedDate>
    <publishedDate>--</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="eng">Flexible Automation with compact NMR instruments</title>
    <abstract language="eng">Modular plants using intensified continuous processes represent an appealing concept to produce pharmaceuticals. It can improve quality, safety, sustainability, and profitability compared to batch processes, and it enables plug-and-produce reconfiguration for fast product changes. To facilitate this flexibility by real-time quality control, we developed a solution that can be adapted quickly to new processes and includes a compact Nuclear Magnetic Resonance (NMR) spectrometer for online quality monitoring as well as a new model-based control approach. The NMR sensor is a benchtop device enhanced to the requirements of automated chemical production including ro-bust evaluation of sensor data. &#13;
Here, we present alternatives for the quantitative determination of the analytes using modular, physically motivated models. These models can be adapted to new substances solely by the use of their corresponding pure component spectra, which can either be derived from experimental spectra as well as from quantum mechanical models or NMR predictors. Modular means that spec-tral models can simply be exchanged together with alternate reagents and products. Beyond that, we comprehensively calibrated an NIR spectrometer based on online NMR process data for the first time within an industrial plant. The integrated solution was developed for a metal organic reac-tion running on a commercial-scale modular pilot plant and it was tested under industrial conditions.</abstract>
    <enrichment key="eventName">7th Annual PANIC Conference</enrichment>
    <enrichment key="eventPlace">Hilton Head Island, South Carolina, USA</enrichment>
    <enrichment key="eventStart">03.03.2019</enrichment>
    <enrichment key="eventEnd">07.03.2019</enrichment>
    <enrichment key="opus.doi.autoCreate">false</enrichment>
    <enrichment key="opus.urn.autoCreate">true</enrichment>
    <author>Simon Kern</author>
    <author>Lukas Wander</author>
    <author>Klas Meyer</author>
    <author>Svetlana Guhl</author>
    <author>A. R. Gottu Mukkula</author>
    <author>M. Holtkamp</author>
    <author>M. Salge</author>
    <author>C. Fleischer</author>
    <author>N. Weber</author>
    <author>R. King</author>
    <author>S. Engell</author>
    <author>Andrea Paul</author>
    <author>M. Pereira Remelhe</author>
    <author>Michael Maiwald</author>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Online NMR Spectroscopy</value>
    </subject>
    <collection role="ddc" number="543">Analytische Chemie</collection>
    <collection role="fulltextaccess" number="">Datei im Netzwerk der BAM verfügbar ("Closed Access")</collection>
    <collection role="literaturgattung" number="">Präsentation</collection>
  </doc>
  <doc>
    <id>48062</id>
    <completedYear/>
    <publishedYear>2019</publishedYear>
    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst>3037</pageFirst>
    <pageLast>3046</pageLast>
    <pageNumber/>
    <edition/>
    <issue>14</issue>
    <volume>411</volume>
    <type>article</type>
    <publisherName>Springer Nature</publisherName>
    <publisherPlace>Heidelberg</publisherPlace>
    <creatingCorporation/>
    <contributingCorporation/>
    <belongsToBibliography>1</belongsToBibliography>
    <completedDate>--</completedDate>
    <publishedDate>--</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="eng">Flexible automation with compact NMR spectroscopy for continuous production of pharmaceuticals</title>
    <abstract language="eng">Modular plants using intensified continuous processes represent an appealing concept for the production of pharmaceuticals. It can improve quality, safety, sustainability, and profitability compared to batch processes; besides, it enables plug-and-produce reconfiguration for fast product changes. To facilitate this flexibility by real-time quality control, we developed a solution that can be adapted quickly to new processes and is based on a compact nuclear magnetic resonance (NMR) spectrometer. The NMR sensor is a benchtop device enhanced to the requirements of automated chemical production including robust evaluation of sensor data. Beyond monitoring the product quality, online NMR data was used in a new iterative optimization approach to maximize the plant profit and served as a reliable reference for the calibration of a near-infrared (NIR) spectrometer. The overall approach&#13;
was demonstrated on a commercial-scale pilot plant using a metal-organic reaction with pharmaceutical relevance.</abstract>
    <parentTitle language="eng">Analytical and Bioanalytical Chemistry</parentTitle>
    <identifier type="doi">10.1007/s00216-019-01752-y</identifier>
    <identifier type="issn">1618-2642</identifier>
    <identifier type="urn">urn:nbn:de:kobv:b43-480623</identifier>
    <identifier type="issn">1618-2650</identifier>
    <enrichment key="date_peer_review">27.05.2019</enrichment>
    <enrichment key="RelatedIdentifier">https://nbn-resolving.org/urn:nbn:de:kobv:b43-480630</enrichment>
    <licence>Creative Commons - CC BY - Namensnennung 4.0 International</licence>
    <author>Simon Kern</author>
    <author>Lukas Wander</author>
    <author>Klas Meyer</author>
    <author>Svetlana Guhl</author>
    <author>A. R. Gottu Mukkula</author>
    <author>M. Holtkamp</author>
    <author>M. Salge</author>
    <author>C. Fleischer</author>
    <author>N. Weber</author>
    <author>S. Engell</author>
    <author>Andrea Paul</author>
    <author>M. Pereira Remelhe</author>
    <author>Michael Maiwald</author>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>NMR Spectroscopy</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>NIR Spectroscopy</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Real-time process monitoring</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Real-time quality control</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Continuous processes</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>CONSENS</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Data Fusion</value>
    </subject>
    <collection role="ddc" number="543">Analytische Chemie</collection>
    <collection role="literaturgattung" number="">Verlagsliteratur</collection>
    <collection role="fulltextaccess" number="">Datei für die Öffentlichkeit verfügbar ("Open Access")</collection>
    <collection role="unnumberedseries" number="">Wissenschaftliche Artikel der BAM</collection>
    <thesisPublisher>Bundesanstalt für Materialforschung und -prüfung (BAM)</thesisPublisher>
    <file>https://opus4.kobv.de/opus4-bam/files/48062/ABC_411_2019_3037-3046_Kern.pdf</file>
  </doc>
  <doc>
    <id>38562</id>
    <completedYear/>
    <publishedYear>2016</publishedYear>
    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst/>
    <pageLast/>
    <pageNumber/>
    <edition/>
    <issue/>
    <volume/>
    <type>poster</type>
    <publisherName/>
    <publisherPlace/>
    <creatingCorporation/>
    <contributingCorporation/>
    <belongsToBibliography>0</belongsToBibliography>
    <completedDate>--</completedDate>
    <publishedDate>--</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="eng">Process monitoring of an intensified continuous production unit with compact NMR spectroscopy</title>
    <abstract language="eng">Monitoring chemical reactions is the key to chemical process control. Today, mainly optical online methods are applied. NMR spectroscopy has a high potential for direct loop process control. Compact NMR instruments based on permanent magnets are robust and relatively inexpensive analyzers, which feature advantages like low cost, low maintenance, ease of use, and cryogen-free operation. Instruments for online NMR measurements equipped with a flow-through cell, possessing a good signal-to-noise-ratio, sufficient robustness, and meeting the requirements for integration into industrial plants (i.e., explosion safety and fully automated data analysis) are currently not available off the rack. Recently, promising benchtop NMR instruments with acceptable performance came to market and process integrated sensors developed on basis of such laboratory instruments are on their way.&#13;
&#13;
Intensified continuous processes are in focus of current research. Compared to traditional batch processes, these are giving admittance to new and difficult to produce compounds, leading to better product uniformity, and dras-tically reducing the consumption of raw materials and energy. Flexible (modular) chemical plants can produce different products using the same equipment with short down-times between campaigns, and quick introduction of new products to the market. Typically, such plants have smaller scale than big size facilities for production of basic chemicals but are still capable to produce kilograms to tons of specialty products each day. Such flexible (modular) plants can be provided in the size of 20 ft freight containers and represent a promising approach by their ability of easy transfer to production sites as well as the possibility of increasing production capacity by a simple numbering-up-approach. &#13;
&#13;
However, full automation is a prerequisite to realize such benefits of intensified continuous production. In continu-ous flow processes steady automated measurements and tight closed-loop control of the product quality are mandatory. If these are not available, there is a huge risk of producing large amounts of out-of-spec (OOS) prod-ucts. This is addressed in the European Union’s Research Project CONSENS (Integrated Control and Sensing) by development and integration of smart sensor modules for process monitoring and control within such modular plant setups.</abstract>
    <identifier type="urn">urn:nbn:de:kobv:b43-385628</identifier>
    <enrichment key="eventName">12. Kolloquium des Arbeitskreises Prozessanalytik</enrichment>
    <enrichment key="eventPlace">Berlin, Germany</enrichment>
    <enrichment key="eventStart">28.11.2016</enrichment>
    <enrichment key="eventEnd">30.11.2016</enrichment>
    <licence>Creative Commons - Namensnennung - Nicht kommerziell - Keine Bearbeitung 3.0</licence>
    <author>Svetlana Guhl</author>
    <author>Klas Meyer</author>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Low field NMR spectroscopy</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Modular production units</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Online NMR spectroscopy</value>
    </subject>
    <collection role="ddc" number="543">Analytische Chemie</collection>
    <collection role="fulltextaccess" number="">Datei für die Öffentlichkeit verfügbar ("Open Access")</collection>
    <collection role="literaturgattung" number="">Präsentation</collection>
    <collection role="unnumberedseries" number="">BAM Präsentationen</collection>
    <thesisPublisher>Bundesanstalt für Materialforschung und -prüfung (BAM)</thesisPublisher>
    <file>https://opus4.kobv.de/opus4-bam/files/38562/Poster_CONSENS_AK_PAT_2016_1.pdf</file>
  </doc>
  <doc>
    <id>38364</id>
    <completedYear/>
    <publishedYear>2016</publishedYear>
    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst>P17, 75</pageFirst>
    <pageLast>77</pageLast>
    <pageNumber/>
    <edition/>
    <issue/>
    <volume/>
    <type>conferenceobject</type>
    <publisherName/>
    <publisherPlace/>
    <creatingCorporation/>
    <contributingCorporation/>
    <belongsToBibliography>0</belongsToBibliography>
    <completedDate>--</completedDate>
    <publishedDate>--</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="eng">Process monitoring of an intensified continuous production unit with compact NMR spectroscopy</title>
    <abstract language="eng">Monitoring chemical reactions is the key to chemical process control. Today, mainly optical online methods are applied. NMR spectroscopy has a high potential for direct loop process control. Compact NMR instruments based on permanent magnets are robust and relatively inexpensive analyzers, which feature advantages like low cost, low maintenance, ease of use, and cryogen-free operation. Instruments for online NMR measurements equipped with a flow-through cell, possessing a good signal-to-noise-ratio, sufficient robustness, and meeting the requirements for integration into industrial plants (i.e., explosion safety and fully automated data analysis) are cur-rently not available off the rack. Recently, promising benchtop NMR instruments with acceptable performance came to market and process integrated sensors developed on basis of such laboratory instruments are on their way.</abstract>
    <parentTitle language="deu">Tagungsband – 12. Kolloquium Prozessanalytik</parentTitle>
    <identifier type="urn">urn:nbn:de:kobv:b43-383646</identifier>
    <enrichment key="eventName">12. Kolloquium des Arbeitskreises Prozessanalytik</enrichment>
    <enrichment key="eventPlace">Berlin, Germany</enrichment>
    <enrichment key="eventStart">28.11.2016</enrichment>
    <enrichment key="eventEnd">30.11.2016</enrichment>
    <licence>Creative Commons - Namensnennung - Nicht kommerziell - Keine Bearbeitung 3.0</licence>
    <author>Svetlana Guhl</author>
    <author>Klas Meyer</author>
    <author>Simon Kern</author>
    <author>Patrick Gräßer</author>
    <author>Michael Maiwald</author>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Online NMR spectroscopy</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Modular production units</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Low field NMR spectroscopy</value>
    </subject>
    <collection role="ddc" number="543">Analytische Chemie</collection>
    <collection role="fulltextaccess" number="">Datei für die Öffentlichkeit verfügbar ("Open Access")</collection>
    <collection role="literaturgattung" number="">Graue Literatur</collection>
    <collection role="unnumberedseries" number="">Wissenschaftliche Artikel der BAM</collection>
    <thesisPublisher>Bundesanstalt für Materialforschung und -prüfung (BAM)</thesisPublisher>
    <file>https://opus4.kobv.de/opus4-bam/files/38364/2016-Tagungsband_12_Kolloquium_Prozessanalytik_Berlin_final_P17.pdf</file>
  </doc>
  <doc>
    <id>41577</id>
    <completedYear/>
    <publishedYear>2017</publishedYear>
    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst>628</pageFirst>
    <pageLast>631</pageLast>
    <pageNumber/>
    <edition/>
    <issue/>
    <volume>1</volume>
    <type>conferenceobject</type>
    <publisherName>MDPI</publisherName>
    <publisherPlace>Basel</publisherPlace>
    <creatingCorporation/>
    <contributingCorporation/>
    <belongsToBibliography>0</belongsToBibliography>
    <completedDate>--</completedDate>
    <publishedDate>--</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="eng">Strangers in the Night—Smart Process Sensors in Our Current Automation Landscape</title>
    <abstract language="eng">The departure from the current automation landscape to next generation automation concepts for the process industry has already begun. Smart functions of sensors simplify their use and enable plug-and-play integration, even though they may appear to be more complex at first sight. Smart sensors enable concepts like self-diagnostics, self-calibration, and self-configuration/parameterization whenever our current automation landscape allows it. Here we summarize the currently discussed general requirements for process sensors 4.0 and introduce a smart online NMR sensor module as example, which was developed for an intensified industrial process funded by the EU’s Horizon 2020 research and innovation programme (www.consens-spire.eu).</abstract>
    <parentTitle language="eng">Proceedings</parentTitle>
    <identifier type="doi">10.3390/proceedings1040628</identifier>
    <identifier type="url">http://www.mdpi.com/2504-3900/1/4/628</identifier>
    <identifier type="urn">urn:nbn:de:kobv:b43-415772</identifier>
    <enrichment key="eventName">Eurosensors 2017 Conference</enrichment>
    <enrichment key="eventPlace">Paris, France</enrichment>
    <enrichment key="eventStart">03.09.2017</enrichment>
    <enrichment key="eventEnd">06.09.2017</enrichment>
    <licence>Creative Commons - Namensnennung 3.0</licence>
    <author>Michael Maiwald</author>
    <author>Patrick Gräßer</author>
    <author>Lukas Wander</author>
    <author>Nicolai Zientek</author>
    <author>Svetlana Guhl</author>
    <author>Klas Meyer</author>
    <author>Simon Kern</author>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Process Monitoring</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Smart Sensors</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>CONSENS</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Online NMR Spectroscopy</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Mini-plant</value>
    </subject>
    <collection role="ddc" number="543">Analytische Chemie</collection>
    <collection role="literaturgattung" number="">Verlagsliteratur</collection>
    <collection role="fulltextaccess" number="">Datei für die Öffentlichkeit verfügbar ("Open Access")</collection>
    <collection role="unnumberedseries" number="">Wissenschaftliche Artikel der BAM</collection>
    <thesisPublisher>Bundesanstalt für Materialforschung und -prüfung (BAM)</thesisPublisher>
    <file>https://opus4.kobv.de/opus4-bam/files/41577/proceedings-01-00628.pdf</file>
  </doc>
  <doc>
    <id>39138</id>
    <completedYear/>
    <publishedYear>2017</publishedYear>
    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst/>
    <pageLast/>
    <pageNumber/>
    <edition/>
    <issue/>
    <volume/>
    <type>poster</type>
    <publisherName/>
    <publisherPlace/>
    <creatingCorporation/>
    <contributingCorporation/>
    <belongsToBibliography>0</belongsToBibliography>
    <completedDate>--</completedDate>
    <publishedDate>--</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="eng">Process monitoring of an intensified continuous production unit with compact NMR spectroscopy</title>
    <abstract language="eng">Monitoring chemical reactions is the key to chemical process control. Today, mainly optical online methods are applied. NMR spectroscopy has a high potential for direct loop process control. Compact NMR instruments based on permanent magnets are robust and inexpensive analysers, which feature advantages like low maintenance, ease of use, and cryogen-free operation. Instruments for online NMR measurements equipped with a flow-through cell, possessing a good signal-to-noise-ratio, robustness, and meeting the requirements for integration into industrial plants (i.e., explosion safety and fully automated data analysis) are currently not available off the rack.&#13;
Intensified continuous processes are in focus of current research. Flexible (modular) chemical plants can produce different products using the same equipment with short down-times between campaigns and quick introduction of new products to the market. In continuous flow processes online sensor data and tight closed-loop control of the product quality are mandatory. Otherwise there is a huge risk of producing large amounts of out-of-spec (OOS) products. This is addressed in the European Union’s Research Project CONSENS by development and integration of smart sensor modules for process monitoring and control within such modular plant setups.&#13;
The presented NMR module is provided in an explosion proof housing with a module size of 57 x 57 x 85 cm and involves a compact 43.5 MHz NMR spectrometer together with an acquisition unit and a programmable logic controller for automated data preparation (phasing, baseline correction) and evaluation. Indirect Hard Modeling (IHM) was selected for data analysis of the low-field NMR spectra. A set-up for monitoring continuous reactions in a thermostated 1/8” tubular reactor using automated syringe pumps was used to validate the IHM models by using high-field NMR spectroscopy as analytical reference method.</abstract>
    <identifier type="urn">urn:nbn:de:kobv:b43-391386</identifier>
    <enrichment key="eventName">Workshop for Process Industry - Tackling the Future of Plant Operation</enrichment>
    <enrichment key="eventPlace">Frankfurt am Main, Germany</enrichment>
    <enrichment key="eventStart">25.01.2017</enrichment>
    <enrichment key="eventEnd">25.01.2017</enrichment>
    <licence>Creative Commons - Namensnennung - Nicht kommerziell - Keine Bearbeitung 3.0</licence>
    <author>Svetlana Guhl</author>
    <author>Klas Meyer</author>
    <author>Simon Kern</author>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Online NMR spectroscopy</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Process analytical technology</value>
    </subject>
    <subject>
      <language>deu</language>
      <type>uncontrolled</type>
      <value>Prozessanalytik</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Process control</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>CONSENS</value>
    </subject>
    <collection role="ddc" number="543">Analytische Chemie</collection>
    <collection role="fulltextaccess" number="">Datei für die Öffentlichkeit verfügbar ("Open Access")</collection>
    <collection role="literaturgattung" number="">Präsentation</collection>
    <collection role="unnumberedseries" number="">BAM Präsentationen</collection>
    <thesisPublisher>Bundesanstalt für Materialforschung und -prüfung (BAM)</thesisPublisher>
    <file>https://opus4.kobv.de/opus4-bam/files/39138/2017-01_CONSENS Poster_v2.pdf</file>
  </doc>
</export-example>
