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Nicolle A, Deng S, Ihme M, Kuzhagaliyeva N, Ibrahim EA, Farooq A. Mixtures Recomposition by Neural Nets: A Multidisciplinary Overview. J Chem Inf Model 2024; 64:597-620. [PMID: 38284618 DOI: 10.1021/acs.jcim.3c01633] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/30/2024]
Abstract
Artificial Neural Networks (ANNs) are transforming how we understand chemical mixtures, providing an expressive view of the chemical space and multiscale processes. Their hybridization with physical knowledge can bridge the gap between predictivity and understanding of the underlying processes. This overview explores recent progress in ANNs, particularly their potential in the 'recomposition' of chemical mixtures. Graph-based representations reveal patterns among mixture components, and deep learning models excel in capturing complexity and symmetries when compared to traditional Quantitative Structure-Property Relationship models. Key components, such as Hamiltonian networks and convolution operations, play a central role in representing multiscale mixtures. The integration of ANNs with Chemical Reaction Networks and Physics-Informed Neural Networks for inverse chemical kinetic problems is also examined. The combination of sensors with ANNs shows promise in optical and biomimetic applications. A common ground is identified in the context of statistical physics, where ANN-based methods iteratively adapt their models by blending their initial states with training data. The concept of mixture recomposition unveils a reciprocal inspiration between ANNs and reactive mixtures, highlighting learning behaviors influenced by the training environment.
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Affiliation(s)
- Andre Nicolle
- Aramco Fuel Research Center, Rueil-Malmaison 92852, France
| | - Sili Deng
- Massachusetts Institute of Technology, Cambridge 02139, Massachusetts, United States
| | - Matthias Ihme
- Stanford University, Stanford 94305, California, United States
| | | | - Emad Al Ibrahim
- King Abdullah University of Science and Technology, Thuwal 23955, Saudi Arabia
| | - Aamir Farooq
- King Abdullah University of Science and Technology, Thuwal 23955, Saudi Arabia
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2
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Bornemann‐Pfeiffer M, Wolf J, Meyer K, Kern S, Angelone D, Leonov A, Cronin L, Emmerling F. Standardisierung und Kontrolle von Grignard‐Reaktionen mittels Online‐NMR in einer universellen chemischen Syntheseplattform. Angew Chem Int Ed Engl 2021. [DOI: 10.1002/ange.202106323] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/08/2022]
Affiliation(s)
- Martin Bornemann‐Pfeiffer
- Bundesanstalt für Materialforschung und -prüfung Richard-Willstätter-Straße 11 12489 Berlin Deutschland
- Chair of Chemical and Process Engineering Technische Universität Berlin Marchstr. 23 10587 Berlin Germany
| | - Jakob Wolf
- Bundesanstalt für Materialforschung und -prüfung Richard-Willstätter-Straße 11 12489 Berlin Deutschland
| | - Klas Meyer
- Bundesanstalt für Materialforschung und -prüfung Richard-Willstätter-Straße 11 12489 Berlin Deutschland
| | - Simon Kern
- S-PACT GmbH Burtscheiderstr. 1 52064 Aachen Deutschland
| | - Davide Angelone
- School of Chemistry University of Glasgow Glasgow G12 8QQ UK
| | - Artem Leonov
- School of Chemistry University of Glasgow Glasgow G12 8QQ UK
| | - Leroy Cronin
- School of Chemistry University of Glasgow Glasgow G12 8QQ UK
| | - Franziska Emmerling
- Bundesanstalt für Materialforschung und -prüfung Richard-Willstätter-Straße 11 12489 Berlin Deutschland
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3
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Bornemann‐Pfeiffer M, Wolf J, Meyer K, Kern S, Angelone D, Leonov A, Cronin L, Emmerling F. Standardization and Control of Grignard Reactions in a Universal Chemical Synthesis Machine using online NMR. Angew Chem Int Ed Engl 2021; 60:23202-23206. [PMID: 34278673 PMCID: PMC8597166 DOI: 10.1002/anie.202106323] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/11/2021] [Indexed: 11/17/2022]
Abstract
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.
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Affiliation(s)
- Martin Bornemann‐Pfeiffer
- Department 1: Analytical Chemistry, Reference MaterialsBundesanstalt für Materialforschung und -prüfungRichard-Willstätter-Straße 1112489BerlinGermany
- Chair of Chemical and Process EngineeringTechnische Universität BerlinMarchstr. 2310587BerlinGermany
| | - Jakob Wolf
- Department 1: Analytical Chemistry, Reference MaterialsBundesanstalt für Materialforschung und -prüfungRichard-Willstätter-Straße 1112489BerlinGermany
| | - Klas Meyer
- Department 1: Analytical Chemistry, Reference MaterialsBundesanstalt für Materialforschung und -prüfungRichard-Willstätter-Straße 1112489BerlinGermany
| | - Simon Kern
- S-PACT GmbHBurtscheiderstr. 152064AachenGermany
| | | | - Artem Leonov
- School of ChemistryUniversity of GlasgowGlasgowG12 8QQUK
| | - Leroy Cronin
- School of ChemistryUniversity of GlasgowGlasgowG12 8QQUK
| | - Franziska Emmerling
- Department 1: Analytical Chemistry, Reference MaterialsBundesanstalt für Materialforschung und -prüfungRichard-Willstätter-Straße 1112489BerlinGermany
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Bornemann‐Pfeiffer M, Kern S, Maiwald M, Meyer K. Calibration‐Free Chemical Process and Quality Control Units as Enablers for Modular Production. CHEM-ING-TECH 2020. [DOI: 10.1002/cite.202000150] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/06/2022]
Affiliation(s)
- Martin Bornemann‐Pfeiffer
- Bundesanstalt für Materialforschung und -prüfung (BAM) Richard-Willstaetter-Straße 11 12489 Berlin Germany
- Technical University of Berlin Chemical and Process Engineering Fraunhoferstraße 33–36 10587 Berlin Germany
| | - Simon Kern
- Bundesanstalt für Materialforschung und -prüfung (BAM) Richard-Willstaetter-Straße 11 12489 Berlin Germany
- S-PACT GmbH Burtscheider Straße 1 52064 Aachen Germany
| | - Michael Maiwald
- Bundesanstalt für Materialforschung und -prüfung (BAM) Richard-Willstaetter-Straße 11 12489 Berlin Germany
| | - Klas Meyer
- Bundesanstalt für Materialforschung und -prüfung (BAM) Richard-Willstaetter-Straße 11 12489 Berlin Germany
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Nestle N, Lim ZJ, Böhringer T, Abtmeyer S, Arenz S, Leinweber FC, Weiß T, von Harbou E. Taking compact NMR to monitoring real reactions in large-scale chemical industries-General considerations and learnings from a lab-scale test case. MAGNETIC RESONANCE IN CHEMISTRY : MRC 2020; 58:1213-1221. [PMID: 32526070 DOI: 10.1002/mrc.5061] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/08/2019] [Revised: 06/03/2020] [Accepted: 06/04/2020] [Indexed: 06/11/2023]
Abstract
The considerations for use of compact nuclear magnetic resonance in a large-scale industrial environment clearly differ from those in academic and educational settings and even from those in smaller companies. In the first part of this article, these differences will be discussed along with the additional requirements that need to be fulfilled for successful applicability in different use cases. In the second part of the article, outcomes from different research activities aiming to fulfill these requirements will be presented with a focus on an online reaction-monitoring study on a lab-scale nucleophilic chlorination reaction.
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Affiliation(s)
- Nikolaus Nestle
- Material Physics and Analytics, BASF SE, Carl-Bosch-Straße, Ludwigshafen am Rhein, 67056, Germany
| | - Zi Jian Lim
- Center of Expertise for Process Analytical Technology, BASF SE, Carl-Bosch-Straße, Ludwigshafen am Rhein, 67056, Germany
| | - Tobias Böhringer
- Center of Expertise for Process Analytical Technology, BASF SE, Carl-Bosch-Straße, Ludwigshafen am Rhein, 67056, Germany
| | - Sarah Abtmeyer
- Center of Expertise for Process Analytical Technology, BASF SE, Carl-Bosch-Straße, Ludwigshafen am Rhein, 67056, Germany
| | - Sven Arenz
- Material Physics and Analytics, BASF SE, Carl-Bosch-Straße, Ludwigshafen am Rhein, 67056, Germany
| | - Felix C Leinweber
- Center of Expertise for Process Analytical Technology, BASF SE, Carl-Bosch-Straße, Ludwigshafen am Rhein, 67056, Germany
| | - Thomas Weiß
- Material Physics and Analytics, BASF SE, Carl-Bosch-Straße, Ludwigshafen am Rhein, 67056, Germany
| | - Erik von Harbou
- Process Research and Chemical Engineering, BASF SE, Carl-Bosch-Straße, Ludwigshafen am Rhein, 67056, Germany
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Flexible automation with compact NMR spectroscopy for continuous production of pharmaceuticals. Anal Bioanal Chem 2019; 411:3037-3046. [PMID: 30903225 PMCID: PMC6526149 DOI: 10.1007/s00216-019-01752-y] [Citation(s) in RCA: 36] [Impact Index Per Article: 7.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/16/2019] [Revised: 02/13/2019] [Accepted: 03/04/2019] [Indexed: 11/24/2022]
Abstract
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 was demonstrated on a commercial-scale pilot plant using a metal-organic reaction with pharmaceutical relevance. Graphical abstract ![]()
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Forte E, Jirasek F, Bortz M, Burger J, Vrabec J, Hasse H. Digitalization in Thermodynamics. CHEM-ING-TECH 2019. [DOI: 10.1002/cite.201800056] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/11/2022]
Affiliation(s)
- Esther Forte
- University of Kaiserslautern; Laboratory of Engineering Thermodynamics (LTD); Erwin-Schrödinger-Straße 44 67663 Kaiserslautern Germany
- Evonik Technology & Infrastructure GmbH; Rodenbacher Chaussee 4 63457 Hanau-Wolfgang Germany
| | - Fabian Jirasek
- University of Kaiserslautern; Laboratory of Engineering Thermodynamics (LTD); Erwin-Schrödinger-Straße 44 67663 Kaiserslautern Germany
| | - Michael Bortz
- Fraunhofer Institute for Industrial Mathematics (ITWM); Fraunhofer-Platz 1 67663 Kaiserslautern Germany
| | - Jakob Burger
- Technical University of Munich; Campus Straubing for Biotechnology and Sustainability; Chair of Chemical Process Engineering; Schulgasse 16 94315 Straubing Germany
| | - Jadran Vrabec
- Technical University Berlin; Thermodynamics and Process Engineering; Ernst-Reuter-Platz 1 10587 Berlin Germany
| | - Hans Hasse
- University of Kaiserslautern; Laboratory of Engineering Thermodynamics (LTD); Erwin-Schrödinger-Straße 44 67663 Kaiserslautern Germany
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Online low-field NMR spectroscopy for process control of an industrial lithiation reaction—automated data analysis. Anal Bioanal Chem 2018; 410:3349-3360. [DOI: 10.1007/s00216-018-1020-z] [Citation(s) in RCA: 34] [Impact Index Per Article: 5.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/16/2018] [Revised: 02/22/2018] [Accepted: 03/12/2018] [Indexed: 01/13/2023]
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