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    <title language="eng">Modular production involving benchtop NMR - Current Application Examples Driven by Digitalization</title>
    <abstract language="eng">The demand for increasing product diversity in the chemical and pharmaceutical industry calls for new production processes that enable greater flexibility. Therefore, plants are needed which can be adapted to new processes in a fast manner and be scaled up and down easily to volatile market demands. Modular production techniques in combination with advanced process analytical technology (PAT) are considered as a promising solution able to fulfil these requirements.&#13;
The success and acceptance of modular concepts in both new and existing plants is dependent of its reliability, easy applicability, and standardization. In recent past, enormous efforts were made to overcome existing barriers in a superordinate level, e.g. DEXPI, ENPRO, or MTP naming just a few. Here, we’d like to present a few, more hands-on, application examples which are shown in Figure 1 aiming to increase process flexibility and applicability.</abstract>
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    <title language="eng">Modular production involving benchtop NMR Current Application Examples Driven by Digitalization</title>
    <abstract language="eng">The demand for increasing product diversity in the chemical and pharmaceutical industry calls for new production processes that enable greater flexibility. Therefore, plants are needed which can be adapted to new processes in a fast manner and be scaled up and down easily to volatile market demands. Modular production techniques in combination with advanced process analytical technology (PAT) are considered as a promising solution able to fulfil these requirements.&#13;
The success and acceptance of modular concepts in both new and existing plants is dependent of its reliability, easy applicability, and standardization. In recent past, enormous efforts were made to overcome existing barriers in a superordinate level, e.g. DEXPI, ENPRO, or MTP naming just a few. Here, we’d like to present a few, more hands-on, application examples which are shown in Figure 1 aiming to increase process flexibility and applicability.</abstract>
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    <title language="eng">Modular production involving benchtop NMR Current Application Examples Driven by Digitalization</title>
    <abstract language="eng">The demand for increasing product diversity in the chemical and pharmaceutical industry calls for new production processes that enable greater flexibility. Therefore, plants are needed which can be adapted to new processes in a fast manner and be scaled up and down easily to volatile market demands. Modular production techniques in combination with advanced process analytical technology (PAT) are considered as a promising solution able to fulfil these requirements.&#13;
The success and acceptance of modular concepts in both new and existing plants is dependent of its reliability, easy applicability, and standardization. In recent past, enormous efforts were made to overcome existing barriers in a superordinate level, e.g. DEXPI, ENPRO, or MTP naming just a few. Here, we’d like to present a few, more hands-on, application examples which are shown in Figure 1 aiming to increase process flexibility and applicability.</abstract>
    <enrichment key="eventName">AK Prozessanalytik Jahrestagung 2022</enrichment>
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    <author>Martin Bornemann-Pfeiffer</author>
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      <language>eng</language>
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      <value>Process analytical technology</value>
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    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>NMR spectroscopy</value>
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      <language>eng</language>
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      <value>Digitization</value>
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      <language>eng</language>
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      <value>Additive manufacturing</value>
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    <id>50456</id>
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    <publishedYear>2020</publishedYear>
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    <title language="eng">Training data of quantitative online NMR spectroscopy for artificial neural networks</title>
    <abstract language="eng">Data set of low-field NMR spectra of continuous synthesis of nitro-4’-methyldiphenylamine (MNDPA). 1H spectra (43 MHz) were recorded as single scans.&#13;
Two different approaches for the generation of artificial neural networks training data for the prediction of reactant concentrations were used: (i) Training data based on combinations of measured pure component spectra and (ii) Training data based on a spectral model.&#13;
&#13;
Synthetic low-field NMR spectra&#13;
First 4 columns in MAT-files represent component areas of each reactant within the synthetic mixture spectrum.&#13;
Xi (“pure component spectra dataset”)&#13;
Xii (“spectral model dataset”)&#13;
&#13;
Experimental low-field NMR spectra from MNDPA-Synthesis&#13;
This data set represents low-field NMR-spectra recorded during continuous synthesis of nitro-4’-methyldiphenylamine (MNDPA). Reference values from high-field NMR results are included.</abstract>
    <identifier type="doi">10.5281/zenodo.3677139</identifier>
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    <enrichment key="RelatedIdentifier">https://opus4.kobv.de/opus4-bam/frontdoor/index/index/docId/54481</enrichment>
    <licence>Creative Commons - CC BY - Namensnennung 4.0 International</licence>
    <author>Simon Kern</author>
    <author>Sascha Liehr</author>
    <author>Lukas Wander</author>
    <author>Martin Bornemann-Pfeiffer</author>
    <author>S. Müller</author>
    <author>Michael Maiwald</author>
    <author>Stefan Kowarik</author>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>NMR spectroscopy</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Real-time process monitoring</value>
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    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Artificial neural networks</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Online NMR spectroscopy</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Automation</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Process industry</value>
    </subject>
    <collection role="ddc" number="543">Analytische Chemie</collection>
    <collection role="ddc" number="620">Ingenieurwissenschaften und zugeordnete Tätigkeiten</collection>
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  <doc>
    <id>53803</id>
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    <publishedYear>2021</publishedYear>
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    <title language="eng">Modular production involving Benchtop NMR: Current application examples driven by digitalization</title>
    <abstract language="eng">The demand for increasing product diversity in the chemical and pharmaceutical industry calls for new production processes that enable greater flexibility. Therefore, plants are needed which can be adapted to new processes in a fast manner and be scaled up and down easily to volatile market demands. Modular production techniques in combination with advanced process analytical technology (PAT) are considered as a promising solution able to fulfil these requirements.&#13;
The success and acceptance of modular concepts in both new and existing plants is dependent of its reliability, easy applicability, and standardization. In recent past, enormous efforts were made to overcome existing barriers in a superordinate level, e.g. DEXPI [1], ENPRO [2], or MTP [3] naming just a few. Here, we’d like to present a few, more hands-on, application examples which are shown in Figure 1 aiming to increase process flexibility and applicability.&#13;
This includes:&#13;
a) The development of an additively manufactured mixer—flow reactor combination for the application inside of NMR instruments. [4]&#13;
b) The application of automated, model-based approaches for model development and spectra evaluation.&#13;
c) The application of machine-assisted spectral model building as a genuine alternative to classical model-based approaches [5]&#13;
d) Improvement of NIR calibration through online available NMR reference data. [6]&#13;
These examples represent miscellaneous use cases but result of the same fact: the increased use and availability of data through advanced PAT and therefore new opportunities utilizing them.</abstract>
    <enrichment key="eventName">SMASH - Small Molecule NMR Conference</enrichment>
    <enrichment key="eventPlace">Online meeting</enrichment>
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    <author>Martin Bornemann-Pfeiffer</author>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Process analytical technology</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>NMR spectroscopy</value>
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    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Automation</value>
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    <collection role="fulltextaccess" number="">Datei im Netzwerk der BAM verfügbar ("Closed Access")</collection>
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  <doc>
    <id>53804</id>
    <completedYear/>
    <publishedYear>2021</publishedYear>
    <thesisYearAccepted/>
    <language>deu</language>
    <pageFirst/>
    <pageLast/>
    <pageNumber/>
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    <issue/>
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    <title language="deu">Additively manufactured Flow Cells for Inline Mixing and Reaction Monitoring with Low-Field NMR Spectroscopy</title>
    <abstract language="deu">The demand for increasing product diversity in the chemical process industry calls for new production processes that enable greater flexibility. Therefore, plants are needed that produce significant quantities for market supply that can be scaled up to several tons per year. Compared to traditional batch processes, intensified continuous production enables not only flexibility but also the production of compounds that are difficult to produce. Custom-designed small-scale reactors significantly improve heat and mass transfer through micro mixing and can improve safety, e.g. in the case of high grade exothermic or high-pressure reactions, and might play an important role for customized, modular production facilities.1 Combined with optimally designed flow cells, compact NMR instruments currently present promising analytical tools for use in flow chemistry applications.2,3 In recent process monitoring applications, the flow cell and the mixing unit are usually separated parts leading to a severe time delay between mixing and first data acquisition.&#13;
In this work, we present a comprehensive workflow for the design of a flow cell−mixer combination based on CFD simulation and other design principles.4 Due to the increasing opportunities in additive manufacturing of ceramics, it was possible to realize an optimized SMX-type mixer with a fully integrated NMR flow cell (cf. Fig. 1).&#13;
Validation studies exhibited 1H NMR spectra with a quality comparable to common NMR glass tubes. So far, the mixing performance of the system has been evaluated for different mass flow rates within the intended working range of 5–120 seconds region and compared to ideally mixed samples. Thus, the integrated flow cell−static mixer combination can be used for different purposes such as evaluation of fluid properties, equilibration studies, or reaction monitoring of two instantaneously mixed samples.&#13;
The ceramic flow cell was additively manufactured and analyzed through x-ray microtomography revealing surface characteristics due to the manufacturing process (cf. Fig. 2). Furthermore, the working range of the whole system was characterized leading to an operational specification for further applications.&#13;
In summary, the role of custom-designed components for modular, chemical production, amongst other essential factors like fast development of reliable evaluation models is discussed.&#13;
References&#13;
[1] Bornemann-Pfeiffer et al., Chem. Ing. Tech. (2021), 93: 1–10&#13;
[2] Kern et al., Anal. Bioanal. Chem. (2018) 410: 3349–3360&#13;
[3] Kern et al., Anal. Bioanal. Chem. (2019) 411: 3037–3046&#13;
[4] Bornemann et al., Ind. Eng. Chem. Res. (2019), 58: 19562−19570</abstract>
    <enrichment key="eventName">EUROPACT - European Conference on Process Analytics and Control Technology</enrichment>
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    <author>Martin Bornemann-Pfeiffer</author>
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      <language>eng</language>
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      <value>Process analytical technology</value>
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    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>NMR spectroscopy</value>
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    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Additive manufacturing</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Computational fluid dynamics</value>
    </subject>
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    <collection role="literaturgattung" number="">Präsentation</collection>
  </doc>
  <doc>
    <id>53126</id>
    <completedYear/>
    <publishedYear>2021</publishedYear>
    <thesisYearAccepted/>
    <language>mul</language>
    <pageFirst>1</pageFirst>
    <pageLast>6</pageLast>
    <pageNumber/>
    <edition/>
    <issue>43</issue>
    <volume>60</volume>
    <type>article</type>
    <publisherName>Wiley-VCH</publisherName>
    <publisherPlace>Weinheim</publisherPlace>
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    <contributingCorporation/>
    <belongsToBibliography>1</belongsToBibliography>
    <completedDate>--</completedDate>
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    <title language="mul">Standardization and control of Grignard reactions in a universal chemical synthesis machine using online NMR</title>
    <title language="deu">Standardisierung und Kontrolle von Grignard-Reaktionen mittels Online-NMR in einer universellen chemischen Syntheseplattform</title>
    <abstract language="eng">A big problem with the chemistry literature is that it is not standardized with respect to precise operational parameters, and real time corrections are hard to make without expert knowledge. This lack of context means difficult reproducibility because many steps are ambiguous, and hence depend on tacit knowledge. Here we present the integration of online NMR into an automated chemical synthesis machine (CSM aka. “Chemputer” which is capable of small-molecule synthesis using a universal programming language) to allow automated analysis and adjustment of reactions on the fly. The system was validated and benchmarked by using Grignard reactions which were chosen due to their importance in synthesis. The system was monitored in real time using online-NMR, and spectra were measured continuously during the reactions. This shows that the synthesis being done in the Chemputer can be dynamically controlled in response to feedback optimizing the reaction conditions according to the user requirements.</abstract>
    <abstract language="deu">Ein Problem der chemischen Literatur ist die fehlende Standardisierung bezüglich genauer Bedingungen, auch Echtzeit-Korrekturen sind ohne Expertenwissen nur schwer möglich. Dieser Mangel an Details erschwert experimentelle Reproduzierbarkeit, da Schritte oft mehrdeutig sind und daher von implizitem Wissen abhängen. Hier präsentieren wir die Integration von Online-NMR Spektroskopie in eine automatisierte chemische Syntheseplattform (CSM aka. “Chemputer”, unter Verwendung einer universellen Programmiersprache zur Synthese kleiner Moleküle fähig), um eine automatisierte Analyse und Anpassung von Reaktionen im laufenden Betrieb zu ermöglichen. Das System wurde anhand von Grignard-Reaktionen, die aufgrund ihrer Bedeutung für die Synthese ausgewählt wurden, validiert und einem Härtetest unterzogen. Synthesen wurden in Echtzeit mit Online-NMR überwacht, und die Spektren wurden während der Reaktionen kontinuierlich aufgenommen und analysiert. Dies zeigt, dass der Chemputer dynamisch mittels einer Regelung kontrolliert werden kann, um die Reaktionsbedingungen entsprechend den Anforderungen des Benutzers zu optimieren.</abstract>
    <parentTitle language="deu">Angewandte Chemie - International Edition</parentTitle>
    <identifier type="doi">10.1002/anie.202106323</identifier>
    <identifier type="issn">1521-3773</identifier>
    <identifier type="urn">urn:nbn:de:kobv:b43-531260</identifier>
    <identifier type="issn">1433-7851</identifier>
    <note>Bibliografische Angaben für die deutsche Version: Angewandte Chemie 2021, Jg. 133, S. 1–7, ISSN 0044-8249, ISSN 1521-3757, https://doi.org/10.1002/ange.202106323 - Bibliographic information for the German version: Angewandte Chemie 2021, vol. 133, p. 1–7, ISSN 0044-8249, ISSN 1521-3757, https://doi.org/10.1002/ange.202106323</note>
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    <enrichment key="date_peer_review">23.08.2021</enrichment>
    <licence>Creative Commons - CC BY - Namensnennung 4.0 International</licence>
    <author>Martin Bornemann-Pfeiffer</author>
    <author>Jakob Wolf</author>
    <author>Klas Meyer</author>
    <author>S. Kern</author>
    <author>D. Angelone</author>
    <author>A. Leonov</author>
    <author>L. Cronin</author>
    <author>Franziska Emmerling</author>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Grignard reaction</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>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>deu</language>
      <type>uncontrolled</type>
      <value>Grignard-Reaktion</value>
    </subject>
    <subject>
      <language>deu</language>
      <type>uncontrolled</type>
      <value>NMR-Spektroskopie</value>
    </subject>
    <subject>
      <language>deu</language>
      <type>uncontrolled</type>
      <value>Prozessanalytik</value>
    </subject>
    <subject>
      <language>deu</language>
      <type>uncontrolled</type>
      <value>Prozesskontrolle</value>
    </subject>
    <collection role="ddc" number="543">Analytische Chemie</collection>
    <collection role="ddc" number="620">Ingenieurwissenschaften und zugeordnete Tätigkeiten</collection>
    <collection role="institutes" number="">1 Analytische Chemie; Referenzmaterialien</collection>
    <collection role="institutes" number="">1.4 Non-Target-Analytik</collection>
    <collection role="institutes" number="">6 Materialchemie</collection>
    <collection role="institutes" number="">6.3 Strukturanalytik</collection>
    <collection role="themenfelder" number="">Umwelt</collection>
    <collection role="themenfelder" number="">Material</collection>
    <collection role="themenfelder" number="">Chemie und Prozesstechnik</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="institutes" number="">6.0 Abteilungsleitung und andere</collection>
    <collection role="themenfelder" number="">Materialdesign</collection>
    <collection role="themenfelder" number="">Sensorik</collection>
    <thesisPublisher>Bundesanstalt für Materialforschung und -prüfung (BAM)</thesisPublisher>
    <file>https://opus4.kobv.de/opus4-bam/files/53126/2021-Angewandte_BornemannPfeiffer_Wolf.pdf</file>
    <file>https://opus4.kobv.de/opus4-bam/files/53126/2021-Angewandte_BornemannPfeiffer_Wolf_GERMAN.pdf</file>
  </doc>
</export-example>
