Online quantitative mass spectrometry for the rapid adaptive optimisation of automated flow reactors

Chemistry

Text available via DOI:

https://doi.org/10.1039/C5RE00083A
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Research output: Contribution to Journal/Magazine › Journal article › peer-review

Published

Standard

Online quantitative mass spectrometry for the rapid adaptive optimisation of automated flow reactors. / Holmes, Nicholas; Akien, Geoffrey R.; Savage, Robert J. D. et al.
In: Reaction Chemistry and Engineering, Vol. 2016, No. 1, 2016, p. 96-100.

Research output: Contribution to Journal/Magazine › Journal article › peer-review

Harvard

Holmes, N, Akien, GR, Savage, RJD, Stanetty, C, Baxendale, IR, Blacker, AJ, Taylor, BA, Woodward, RL, Meadows, RE & Bourne, RA 2016, 'Online quantitative mass spectrometry for the rapid adaptive optimisation of automated flow reactors', Reaction Chemistry and Engineering, vol. 2016, no. 1, pp. 96-100. https://doi.org/10.1039/C5RE00083A

APA

Holmes, N., Akien, G. R., Savage, R. J. D., Stanetty, C., Baxendale, I. R., Blacker, A. J., Taylor, B. A., Woodward, R. L., Meadows, R. E., & Bourne, R. A. (2016). Online quantitative mass spectrometry for the rapid adaptive optimisation of automated flow reactors. Reaction Chemistry and Engineering, 2016(1), 96-100. https://doi.org/10.1039/C5RE00083A

Vancouver

Holmes N, Akien GR, Savage RJD, Stanetty C, Baxendale IR, Blacker AJ et al. Online quantitative mass spectrometry for the rapid adaptive optimisation of automated flow reactors. Reaction Chemistry and Engineering. 2016;2016(1):96-100. Epub 2015 Dec 1. doi: 10.1039/C5RE00083A

Author

Holmes, Nicholas ; Akien, Geoffrey R. ; Savage, Robert J. D. et al. / Online quantitative mass spectrometry for the rapid adaptive optimisation of automated flow reactors. In: Reaction Chemistry and Engineering. 2016 ; Vol. 2016, No. 1. pp. 96-100.

Bibtex

@article{7e678b43686d43028421091957853274,

title = "Online quantitative mass spectrometry for the rapid adaptive optimisation of automated flow reactors",

abstract = "An automated continuous reactor for the synthesis of organic compounds, which uses online mass spectrometry (MS) for reaction monitoring and product quantification, is presented. Quantitative and rapid MS monitoring was developed and calibrated using HPLC. The amidation of methyl nicotinate with aqueous MeNH2 was optimised using design of experiments and a self-optimisation algorithm approach to produce >93% yield.",

author = "Nicholas Holmes and Akien, {Geoffrey R.} and Savage, {Robert J. D.} and Christian Stanetty and Baxendale, {Ian R.} and Blacker, {A. John} and Taylor, {Brian A.} and Woodward, {Robert L.} and Meadows, {Rebecca E.} and Bourne, {Richard A.}",

year = "2016",

doi = "10.1039/C5RE00083A",

language = "English",

volume = "2016",

pages = "96--100",

journal = "Reaction Chemistry and Engineering",

publisher = "Royal Society of Chemistry",

number = "1",

}

RIS

TY - JOUR

T1 - Online quantitative mass spectrometry for the rapid adaptive optimisation of automated flow reactors

AU - Holmes, Nicholas

AU - Akien, Geoffrey R.

AU - Savage, Robert J. D.

AU - Stanetty, Christian

AU - Baxendale, Ian R.

AU - Blacker, A. John

AU - Taylor, Brian A.

AU - Woodward, Robert L.

AU - Meadows, Rebecca E.

AU - Bourne, Richard A.

PY - 2016

Y1 - 2016

N2 - An automated continuous reactor for the synthesis of organic compounds, which uses online mass spectrometry (MS) for reaction monitoring and product quantification, is presented. Quantitative and rapid MS monitoring was developed and calibrated using HPLC. The amidation of methyl nicotinate with aqueous MeNH2 was optimised using design of experiments and a self-optimisation algorithm approach to produce >93% yield.

AB - An automated continuous reactor for the synthesis of organic compounds, which uses online mass spectrometry (MS) for reaction monitoring and product quantification, is presented. Quantitative and rapid MS monitoring was developed and calibrated using HPLC. The amidation of methyl nicotinate with aqueous MeNH2 was optimised using design of experiments and a self-optimisation algorithm approach to produce >93% yield.

U2 - 10.1039/C5RE00083A

DO - 10.1039/C5RE00083A

M3 - Journal article

VL - 2016

SP - 96

EP - 100

JO - Reaction Chemistry and Engineering

JF - Reaction Chemistry and Engineering

IS - 1

ER -

Research

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