A continuous-flow electrochemical synthesis platform has been developed to enable self-optimization of reaction conditions of organic electrochemical reactions using attenuated total reflection Fourier transform infrared spectroscopy (ATR FT-IR) and gas chromatography (GC) as online real-time monitoring techniques. We have overcome the challenges in using ATR FT-IR as the downstream analytical methods imposed when a large amount of hydrogen gas is produced from the counter electrode by designing two types of gas–liquid separators (GLS) for analysis of the product mixture flowing from the electrochemical reactor. In particular, we report an integrated GLS with an ATR FT-IR probe at the reactor outlet to give a facile and low-cost solution to determining the concentrations of products in gas–liquid two-phase flow. This approach provides a reliable method for quantifying low-volatile analytes, which can be problematic to be monitored by GC. Two electrochemical reactions the methoxylation of 1-formylpyrrolidine and the oxidation of 3-bromobenzyl alcohol were investigated to demonstrate that the optimal conditions can be located within the pre-defined multi-dimensional reaction parameter spaces without intervention of the operator by using the stable noisy optimization by branch and FIT (SNOBFIT) algorithm.
PlumbK.. “Continuous Processing in the Pharmaceutical Industry: Changing the Mind Set”. Chem. Eng. Res. Des2005. 83(6): 730-738.
3.
LeeS.L.O’ConnorT.F.YangX., et al. “Modernizing Pharmaceutical Manufacturing: From Batch to Continuous Production”. J. Pharm. Innov. 2015. 10(3): 191-199.
4.
BordawekarS.ChandaA.DalyA.M., et al. “Industry Perspectives on Process Analytical Technology: Tools and Applications in API Manufacturing”. Org. Process Res. Dev2015. 19(9): 1174-1185.
5.
YuL.X.AmidonG.KhanM.A., et al. “Understanding Pharmaceutical Quality by Design”. AAPS J. 2014. 16(4): 771-783.
6.
SagmeisterP.WilliamsJ.D.HoneC.A.KappeC.O.. “Laboratory of the Future: A Modular Flow Platform with Multiple Integrated PAT Tools for Multistep Reactions”. React. Chem. Eng. 2019. 4(9): 1571-1578.
7.
KrishnadasanS.BrownR.J.C.DemelloA.J.DemelloJ.C.. “Intelligent Routes to the Controlled Synthesis of Nanoparticles”. Lab Chip. 2007. 7(11): 1434-1441.
8.
McMullenJ.P.StoneM.T.BuchwaldS.L.JensenK.F.. “An Integrated Microreactor System for Self-Optimization of a Heck Reaction: From Micro- to Mesoscale Flow Systems”. Angew. Chem. Int. Ed. 2010. 49(39): 7076-7080.
9.
McMullenJ.P.JensenK.F.. “An Automated Microfluidic System for Online Optimization in Chemical Synthesis”. Org. Process Res. Dev. 2010. 14(5): 1169-1176.
10.
BourneR.A.SkiltonR.A.ParrottA.J., et al. “Adaptive Process Optimization for Continuous Methylation of Alcohols in Supercritical Carbon Dioxide”. Org. Process Res. Dev. 2011. 15(4): 932-938.
11.
HoubenC.LapkinA.A.. “Automatic Discovery and Optimization of Chemical Processes”. Curr. Opin. Chem. Eng. 2015. 9: 1–7.
12.
FabryD.C.SugionoE.RuepingM.. “Online Monitoring and Analysis for Autonomous Continuous Flow Self-Optimizing Reactor Systems”. React. Chem. Eng. 2016. 1(2): 129-133.
13.
GioielloA.MancinoV.FilipponiP., et al. “Concepts and Optimization Strategies of Experimental Design in Continuous-Flow Processing”. J. Flow Chem. 2016. 6(3): 167-180.
14.
ReizmanB.J.JensenK.F.. “Feedback in Flow for Accelerated Reaction Development”. Acc. Chem. Res. 2016. 49(9): 1786-1796.
15.
SansV.CroninL.. “Towards Dial-a-Molecule by Integrating Continuous Flow, Analytics and Self-Optimisation”. Chem. Soc. Rev. 2016. 45(8): 2032-2043.
16.
PlutschackM.B.PieberB.GilmoreK.SeebergerP.H.. “The Hitchhiker’s Guide to Flow Chemistry(II)”. Chem. Rev. 2017. 117(18): 11796-11893.
17.
GromskiP.S.HensonA.B.GrandaJ.M.CroninL.. “How to Explore Chemical Space Using Algorithms and Automation”. Nat. Rev. Chem2019. 3(2): 119-128.
18.
BourneR.A.HiiK.K.ReizmanB.J.. “Introduction to Synthesis 4.0: Towards an Internet of Chemistry”. React. Chem. Eng. 2019. 4(9): 1504-1505.
19.
WyvrattB.M.McMullenJ.P.GrosserS.T.. “Multidimensional Dynamic Experiments for Data-Rich Process Development of Reactions in Flow”. React. Chem. Eng. 2019. 4(9): 1637-1645.
20.
WaldronC.PankajakshanA.QuaglioM., et al. “An Autonomous Microreactor Platform for the Rapid Identification of Kinetic Models”. React. Chem. Eng. 2019. 4(9): 1623-1636.
21.
SchenkC.ShortM.RodriguezJ.S., et al. “Introducing KIPET: A Novel Open-Source Software Package for Kinetic Parameter Estimation from Experimental Datasets Including Spectra”. Comput. Chem. Eng. 2020. 134: 106716.
22.
ClaytonA.D.MansonJ.A.TaylorC.J., et al. “Algorithms for the Self-Optimisation of Chemical Reactions”. React. Chem. Eng. 2019. 4(9): 1545-1554.
23.
RossoV.AlbrechtJ.RobertsF.JaneyJ.M.. “Uniting Laboratory Automation, DoE Data, and Modeling Techniques to Accelerate Chemical Process Development”. React. Chem. Eng. 2019. 4(9): 1646-1657.
24.
CambieD.BottecchiaC.StraathofN.J.W., et al. “Applications of Continuous-Flow Photochemistry in Organic Synthesis, Material Science, and Water Treatment”. Chem. Rev. 2016. 116(17): 10276-10341.
AtobeM.TatenoH.MatsumuraY.. “Applications of Flow Microreactors in Electrosynthetic Processes”. Chem. Rev. 2018. 118(9): 4541-4572.
33.
MitsudoK.KurimotoY.YoshiokaK.SugaS.. “Miniaturization and Combinatorial Approach in Organic Electrochemistry”. Chem. Rev. 2018. 118(12): 5985-5999.
34.
PletcherD.GreenR.A.BrownR.C.D.. “Flow Electrolysis Cells for the Synthetic Organic Chemistry Laboratory”. Chem. Rev. 2018. 118(9): 4573-4591.
35.
NoelT.CaoY.LaudadioG.. “The Fundamentals Behind the Use of Flow Reactors in Electrochemistry”. Acc. Chem. Res. 2019. 52(10): 2858-2869.
36.
PoscharnyK.FabryD.C.HeddrichS., et al. “Machine Assisted Reaction Optimization: A Self-Optimizing Reactor System for Continuous-Flow Photochemical Reactions”. Tetrahedron. 2018. 74(25): 3171-3175.
37.
MansonJ.A.ClaytonA.D.NiñoC.G., et al. “A Hybridised Optimisation of An Automated Photochemical Continuous Flow Reactor”. CHIMIA. 2019. 73(10): 817-822.
38.
QiuZ.TaiC.W.NiklassonG.A.EdvinssonT.. “Direct Observation of Active Catalyst Surface Phases and the Effect of Dynamic Self-Optimization in NiFe-Layered Double Hydroxides for Alkaline Water Splitting”. Energy Environ. Sci. 2019. 12(2): 572-581.
39.
JumbamD.N.SkiltonR.A.ParrottA.J., et al. “The Effect of Self-Optimisation Targets on the Methylation of Alcohols Using Dimethyl Carbonate in Supercritical CO2”. J. Flow Chem. 2012. 2: 24-27.
40.
SkiltonR.A.ParrottA.J.GeorgeM.W., et al. “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.
41.
AmaraZ.StrengE.S.SkiltonR.A., et al. “Automated Serendipity with Self-Optimizing Continuous-Flow Reactors”. Eur. J. Org. Chem. 2015. 2015(28): 6141-6145.
42.
SkiltonR.A.BourneR.A.AmaraZ., et al. “Remote-Controlled Experiments with Cloud Chemistry”. Nat. Chem. 2015. 7(1): 1-5.
43.
ParrottA.J.BourneR.A.AkienG.R., et al. “Self-Optimizing Continuous Reactions in Supercritical Carbon Dioxide”. Angew. Chem., Int. Ed. 2011. 50(16): 3788-3792.
44.
StrengE.S.LeeD.S.GeorgeM.W.PoliakoffM.. “Continuous N-Alkylation Reactions of Amino Alcohols Using Gamma-Al2O3 and Supercritical CO2: Unexpected Formation of Cyclic Ureas and Urethanes by Reaction with CO2”. Beilstein J. Org. Chem2017. 13: 329-337.
45.
HolmesN.AkienG.R.BlackerA.J., et al. “Self-Optimization of the Final Stage in the Synthesis of EGFR Kinase Inhibitor AZD9291 Using an Automated Flow Reactor”. React. Chem. Eng2016. 1(4): 366-371.
46.
HolmesN.AkienG.R.SavageR.J.D., et al. “Online Quantitative Mass Spectrometry for the Rapid Adaptive Optimisation of Automated Flow Reactors”. React. Chem. Eng. 2016. 1(1): 96-100.
47.
JeraalM.I.HolmesN.AkienG.R.BourneR.A.. “Enhanced Process Development Using Automated Continuous Reactors by Self-Optimisation Algorithms and Statistical Empirical Modelling”. Tetrahedron. 2018. 74(25): 3158-3164.
48.
GreenR.A.BrownR.C.D.PletcherD.. “Electrosynthesis in Extended Channel Length Microfluidic Electrolysis Cells”. J. Flow Chem. 2016. 6(3): 191-197.
GreenR.A.JolleyK.E.Al-HadediA.A.M., et al. “Electrochemical Deprotection of Para-Methoxybenzyl Ethers in a Flow Electrolysis Cell”. Org. Lett. 2017. 19(8): 2050-2053.
51.
GreenR.A.BrownR.C.D.PletcherD.HarjiB.. “A Microflow Electrolysis Cell for Laboratory Synthesis on the Multigram Scale”. Org. Process Res. Dev. 2015. 19(10): 1424-1427.
52.
GreenR.A.BrownR.C.D.PletcherD.. “Understanding the Performance of a Microfluidic Electrolysis Cell for Routine Organic Electrosynthesis”. J. Flow Chem. 2015. 5(1): 31-36.
53.
HuyerW.NeumaierA.. “SNOBFIT: Stable Noisy Optimization by Branch and Fit”. ACM Trans. Math. Software. 2008. 35(2): 1-25.
54.
O’HaverT.C.. “Pragmatic Introduction to Signal Processing: Applications in Scientific Measurement”. 2018. https://terpconnect.umd.edu/~toh/spectrum/ [accessed Dec 9 2021].
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