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CC BY 4.0 · Pharmaceutical Fronts 2023; 05(04): e209-e218
DOI: 10.1055/s-0043-1776906
Review Article

A Review of Inline Infrared and Nuclear Magnetic Resonance Applications in Flow Chemistry

Yan Zhang
1   Key Laboratory for Green Pharmaceutical Technologies and Related Equipment of Ministry of Education and Key Laboratory of Pharmaceutical Engineering of Zhejiang Province, Collaborative Innovation Center of Yangtze River Delta Region Green Pharmaceuticals, Zhejiang University of Technology, Hangzhou, People's Republic of China
,
Wei-Ke Su
1   Key Laboratory for Green Pharmaceutical Technologies and Related Equipment of Ministry of Education and Key Laboratory of Pharmaceutical Engineering of Zhejiang Province, Collaborative Innovation Center of Yangtze River Delta Region Green Pharmaceuticals, Zhejiang University of Technology, Hangzhou, People's Republic of China
2   Zhejiang Governor Triangle Biomedical Industrial Technology Research Park, Huzhou, People's Republic of China
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Abstract

As a safe and efficient synthesis technique, flow chemistry has recently gained attention in the pharmaceutical, materials, and environmental protection industries. However, researchers always face challenges in handling samples and selecting sufficiently flexible analytical techniques. Generally, real-time process analysis is crucial for monitoring reactions. The combination of flow chemistry with real-time process analysis can be beneficial for studying reaction kinetics and thermodynamics, monitoring, and control of the chemical synthesis processes, reaction optimization of macro and microreactors, and qualitative and quantitative analyses of compounds. Thus far, studies investigating the combination of flow chemistry with inline monitoring have included ultraviolet–infrared spectroscopy, Raman spectroscopy, gas chromatography, mass spectrometry, liquid chromatography, nuclear magnetic resonance (NMR) spectroscopy, and other automated conventional or unconventional methods. This review sheds light on applying inline infrared and inline NMR spectroscopies in flow chemistry.

Keywords

flow chemistry - inline IR - inline NMR - real-time process analysis - automation


Publikationsverlauf

Eingereicht: 06. Juli 2023

Angenommen: 26. Oktober 2023

Artikel online veröffentlicht:
01. Dezember 2023

© 2023. The Author(s). This is an open access article published by Thieme under the terms of the Creative Commons Attribution License, permitting unrestricted use, distribution, and reproduction so long as the original work is properly cited. (https://creativecommons.org/licenses/by/4.0/)

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Rüdigerstraße 14, 70469 Stuttgart, Germany

 

  • Reference

  • 1 Brandão P, Pineiro M, Pinhoe Melo TMVD. Flow chemistry: towards a more sustainable heterocyclic synthesis. Eur J Org Chem 2019; 2019 (43) 7188-7217
    CrossrefGoogle Scholar
  • 2 Workman Jr J, Lavine B, Chrisman R, Koch M. Process analytical chemistry. Anal Chem 2011; 83 (12) 4557-4578
    CrossrefPubMedGoogle Scholar
  • 3 Morin MA, Zhang WP, Mallik D, Organ MG. Sampling and analysis in flow: the keys to smart, more controllable, and sustainable fine-chemical manufacturing. Angew Chem Int Ed Engl 2021; 60 (38) 20606-20626
    CrossrefPubMedGoogle Scholar
  • 4 Lee WG, Zell MT, Ouchi T, Milton MJ. NMR spectroscopy goes mobile: using NMR as process analytical technology at the fume hood. Magn Reson Chem 2020; 58 (12) 1193-1202
    CrossrefPubMedGoogle Scholar
  • 5 Fabry DC, Sugiono E, Rueping M. Online monitoring and analysis for autonomous continuous flow self-optimizing reactor systems. React Chem Eng 2016; 1 (02) 129-133
    CrossrefGoogle Scholar
  • 6 Littwin G. Heat transport characteristics of additively manufactured periodic open cellular structures as novel catalyst supports. Chemieingenieurtechnik (Weinh) 2020; 92 (09) 1345
    Google Scholar
  • 7 Fath V, Kockmann N, Otto J, Röder T. Self-optimising processes and real-time-optimisation of organic syntheses in a microreactor system using Nelder–Mead and design of experiments. React Chem Eng 2020; 5 (07) 1281-1299
    CrossrefGoogle Scholar
  • 8 Fitzpatrick DE, Battilocchio C, Ley SV. A novel internet-based reaction monitoring, control, and autonomous self-optimization platform for chemical synthesis. Org Process Res Dev 2015; 20 (02) 386-394
    CrossrefGoogle Scholar
  • 9 Ingham RJ, Battilocchio C, Hawkins JM, Ley SV. Integration of enabling methods for the automated flow preparation of piperazine-2-carboxamide. Beilstein J Org Chem 2014; 10: 641-652
    CrossrefPubMedGoogle Scholar
  • 10 Skilton RA, Parrott AJ, George MW, Poliakoff M, Bourne RA. Real-time feedback control using online attenuated total reflection Fourier transform infrared (ATR FT-IR) spectroscopy for continuous flow optimization and process knowledge. Appl Spectrosc 2013; 67 (10) 1127-1131
    CrossrefPubMedGoogle Scholar
  • 11 Moore JS, Jensen KF. Automated multitrajectory method for reaction optimization in a microfluidic system using online IR analysis. Org Process Res Dev 2012; 16 (08) 1409-1415
    CrossrefGoogle Scholar
  • 12 Moore JS, Jensen KF. “Batch” kinetics in flow: online IR analysis and continuous control. Angew Chem Int Ed Engl 2014; 53 (02) 470-473
    CrossrefPubMedGoogle Scholar
  • 13 Sagmeister P, Williams JD, Kappe O. The rocky road to a digital lab. Chimia (Aarau) 2023; 77 (05) 300-306
    CrossrefPubMedGoogle Scholar
  • 14 Andrews GP, Jones DS, Senta-Loys Z. et al. The development of an inline Raman spectroscopic analysis method as a quality control tool for hot melt extruded ramipril fixed-dose combination products. Int J Pharm 2019; 566: 476-487
    CrossrefPubMedGoogle Scholar
  • 15 Ładosz A, Kuhnle C, Jensen KF. Characterization of reaction enthalpy and kinetics in a microscale flow platform. React Chem Eng 2020; 5 (11) 2115-2122
    CrossrefGoogle Scholar
  • 16 Fath V, Lau P, Greve C, Weller P, Kockmann N, Röder T. Simultaneous self-optimisation of yield and purity through a successive combination of inline FT-IR spectroscopy and online mass spectrometry in flow reactions. J Flow Chem 2021; 11 (03) 285-302
    CrossrefGoogle Scholar
  • 17 Brächer A, Kreußer LM, Qamar S, Seidel-Morgenstern A, von Harbou E. Application of quantitative inline NMR spectroscopy for investigation of a fixed-bed chromatographic reactor process. Chem Eng J 2018; 336: 518-530
    CrossrefGoogle Scholar
  • 18 Poljanšek I, Šebenik U, Krajnc M. Characterization of phenol-urea-formaldehyde resin by inline FTIR spectroscopy. J Appl Polym Sci 2006; 99 (05) 2016-2028
    CrossrefGoogle Scholar
  • 19 Marchand A, Mishra R, Bernard A, Dumez JN. Online reaction monitoring with fast and flow-compatible diffusion NMR spectroscopy. Chemistry 2022; 28 (52) e202201175
    CrossrefPubMedGoogle Scholar
  • 20 Brächer A, Hoch S, Albert K. et al. Thermostatted micro-reactor NMR probe head for monitoring fast reactions. J Magn Reson 2014; 242: 155-161
    CrossrefPubMedGoogle Scholar
  • 21 Brächer A, Behrens R, von Harbou E, Hasse H. Application of a new micro-reactor 1 H NMR probe head for quantitative analysis of fast esterification reactions. Chem Eng J 2016; 306: 413-421
    CrossrefGoogle Scholar
  • 22 Schmid E, Rondeau S, Rudszuck T, Nirschl H, Guthausen G. Inline NMR via a dedicated V-shaped sensor. Sensors (Basel) 2023; 23 (05) 2388
    CrossrefPubMedGoogle Scholar
  • 23 Cardoza LA, Almeida VK, Carr A, Larive CK, Graham DW. Separations coupled with NMR detection. Trends Analyt Chem 2003; 22 (10) 766-775
    CrossrefGoogle Scholar
  • 24 Fath V, Lau P, Greve C, Kockmann N, Röder T. Efficient kinetic data acquisition and model prediction: continuous flow microreactors, inline fourier transform infrared spectroscopy, and self-modeling curve resolution. Org Process Res Dev 2020; 24 (10) 1955-1968
    CrossrefGoogle Scholar
  • 25 Fath V, Szmais S, Lau P, Kockmann N, Röder T. Model-based scale-up predictions: from micro- to millireactors using inline fourier transform infrared spectroscopy. Org Process Res Dev 2019; 23 (09) 2020-2030
    CrossrefGoogle Scholar
  • 26 Heinze M, Starke S, Händler M. et al. Combination of nuclear magnetic resonance spectroscopy and nonlinear methods to analyze the copolymerization of phosphonic acid derivatives. J Appl Polym Sci 2019; 136: 48256
    CrossrefGoogle Scholar
  • 27 Bazzoni M, Lhoste C, Bonnet J. et al. In-line multidimensional NMR monitoring of photochemical flow reactions. Chemistry 2023; 29 (20) e202203240
    CrossrefPubMedGoogle Scholar
  • 28 Scheithauer A, Brächer A, Grützner T. et al. Online 1H NMR spectroscopic study of the reaction kinetics in mixtures of acetaldehyde and water using a new microreactor probe head. Ind Eng Chem Res 2014; 53 (45) 17589-17596
    CrossrefGoogle Scholar
  • 29 Wakabayashi S, Takumi M, Kamio S, Wakioka M, Ohki Y, Nagaki A. Flow-chemistry-enabled synthesis of 5-diethylboryl-2,3′-bipyridine and its self-assembly dynamics. Chemistry 2023; 29 (09) e202202882
    CrossrefPubMedGoogle Scholar
  • 30 Bernstein MA, Stefinović M, Sleigh CJ. Optimising reaction performance in the pharmaceutical industry by monitoring with NMR. Magn Reson Chem 2007; 45 (07) 564-571
    CrossrefPubMedGoogle Scholar
  • 31 Sagmeister P, Poms J, Williams JD, Kappe CO. Multivariate analysis of inline benchtop NMR data enables rapid optimization of a complex nitration in flow. React Chem Eng 2020; 5 (04) 677-684
    CrossrefGoogle Scholar
  • 32 Rubens M, Van Herck J, Junkers T. Automated polymer synthesis platform for integrated conversion targeting based on inline benchtop nmr. ACS Macro Lett 2019; 8 (11) 1437-1441
    CrossrefPubMedGoogle Scholar
  • 33 Van Herck J, Abeysekera I, Buckinx AL. et al. Operator-independent high-throughput polymerization screening based on automated inline NMR and online SEC. Digit Discov 2022; 1 (04) 519-526
    CrossrefGoogle Scholar
  • 34 Lange H, Carter CF, Hopkin MD. et al. A breakthrough method for the accurate addition of reagents in multi-step segmented flow processing. Chem Sci (Camb) 2011; 2 (04) 765-769
    CrossrefGoogle Scholar
  • 35 Qian Z, Baxendale IR, Ley SV. A continuous flow process using a sequence of microreactors with in-line IR analysis for the preparation of N,N-diethyl-4-(3-fluorophenylpiperidin-4-ylidenemethyl)benzamide as a potent and highly selective δ-opioid receptor agonist. Chemistry 2010; 16 (41) 12342-12348
    CrossrefPubMedGoogle Scholar
  • 36 Schnoor JK, Schulte LD, Liauw MA. Heat on – calibration of ir spectroscopy at process conditions for continuous esterification. Chemieingenieurtechnik (Weinh) 2020; 92 (10) 1467-1473
    Google Scholar
  • 37 Wu B, Aspers RLEG, Kentgens APM, Zhao EW. Operando benchtop NMR reveals reaction intermediates and crossover in redox flow batteries. J Magn Reson 2023; 351: 107448
    CrossrefPubMedGoogle Scholar
  • 38 Simon K, Sagmeister P, Munday R, Leslie K, Hone CA, Kappe CO. Automated flow and real-time analytics approach for screening functional group tolerance in heterogeneous catalytic reactions. Catal Sci Technol 2022; 12 (06) 1799-1811
    CrossrefGoogle Scholar
  • 39 Van den Broek SAMW, Leliveld JR, Becker R. et al. Continuous flow production of thermally unstable intermediates in a microreactor with inline IR-analysis: controlled vilsmeier–haack formylation of electron-rich arenes. Org Process Res Dev 2012; 16 (05) 934-938
    CrossrefGoogle Scholar
  • 40 Brodmann T, Koos P, Metzger A, Knochel P, Ley SV. Continuous preparation of arylmagnesium reagents in flow with inline IR monitoring. Org Process Res Dev 2011; 16 (05) 1102-1113
    CrossrefGoogle Scholar
  • 41 Menges-Flanagan G, Deitmann E, Gössl L, Hofmann C, Löb P. Scalable continuous synthesis of grignard reagents from in situ-activated magnesium metal. Org Process Res Dev 2020; 24 (02) 315-321
    CrossrefGoogle Scholar
  • 42 Henry C, Bolien D, Ibanescu B. et al. Generation and trapping of ketenes in flow. Eur J Org Chem 2015; 2015 (07) 1491-1499
    CrossrefPubMedGoogle Scholar
  • 43 Rueping M, Bootwicha T, Sugiono E. Continuous-flow catalytic asymmetric hydrogenations: reaction optimization using FTIR inline analysis. Beilstein J Org Chem 2012; 8: 300-307
    CrossrefPubMedGoogle Scholar
  • 44 Schotten C, Howard JL, Jenkins RL, Codina A, Browne DL. A continuous flow-batch hybrid reactor for commodity chemical synthesis enabled by inline NMR and temperature monitoring. Tetrahedron 2018; 74 (38) 5503-5509
    CrossrefGoogle Scholar
  • 45 Koch C, Posch AE, Goicoechea HC, Herwig C, Lendl B. Multi-analyte quantification in bioprocesses by Fourier-transform-infrared spectroscopy by partial least squares regression and multivariate curve resolution. Anal Chim Acta 2014; 807: 103-110
    CrossrefPubMedGoogle Scholar
  • 46 Rao KS, St-Jean F, Kumar A. Quantitation of a ketone enolization and a vinyl sulfonate stereoisomer formation using inline IR spectroscopy and modeling. Org Process Res Dev 2019; 23 (05) 945-951
    CrossrefGoogle Scholar
  • 47 Maiwald M, Fischer HH, Ott M. et al. Quantitative NMR spectroscopy of complex liquid mixtures: methods and results for chemical equilibria in formaldehyde-water-methanol at temperatures up to 383 k. Ind Eng Chem Res 2003; 42 (02) 259-266
    CrossrefGoogle Scholar
  • 48 Tang D, Gong M, Yu J, Guo L, Di J. System-level performance prediction for infrared systems based on energy redistribution in infrared images. IEEE Trans Ind Electron 2022; 69 (02) 2000-2011
    CrossrefGoogle Scholar
  • 49 Svatunek D, Eilenberger G, Denk C. et al. Live monitoring of strain-promoted azide alkyne cycloadditions in complex reaction environments by inline ATR-IR spectroscopy. Chemistry 2020; 26 (44) 9851-9854
    CrossrefPubMedGoogle Scholar
  • 50 Zhou G, Emerson K, Majusiak E, Anderson C, Sudah O. Safe scale-up of processes containing hazardous species in the headspace with inline IR. Org Process Res Dev 2012; 16 (02) 204-213
    CrossrefGoogle Scholar
  • 51 Freudenberg J, Binder WH. Chirality control of screw-sense in aib-polymers: synthesis and helicity of amino acid-functionalized polymers. ACS Macro Lett 2020; 9 (05) 686-692
    CrossrefPubMedGoogle Scholar