A self optimizing synthetic organic reactor system using real-time in-line NMR spectroscopy

Article abstract of DOI:10.1039/c4sc03075c

A configurable platform for synthetic chemistry incorporating an in-line benchtop NMR that is capable of monitoring and controlling organic reactions in real-time is presented. The platform is controlled via a modular LabView software control system for t

Full text of DOI:10.1039/c4sc03075c

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A self optimizing synthetic organic reactor system
using real-time in-line NMR spectroscopy†
Cite this: DOI: 10.1039/c4sc03075c
Victor Sans,‡ Luzian Porwol,‡ Vincenza Dragone‡ and Leroy Cronin‡*
A configurable platform for synthetic chemistry incorporating an in-line benchtop NMR that is capable of
monitoring and controlling organic reactions in real-time is presented. The platform is controlled via a
modular LabView software control system for the hardware, NMR, data analysis and feedback
optimization. Using this platform we report the real-time advanced structural characterization of
Received 8th October 2014
Accepted 14th November 2014
19 13
19
reaction mixtures, including F, C, DEPT, 2D NMR spectroscopy (COSY, HSQC and F-COSY) for the
first time. Finally, the potential of this technique is demonstrated through the optimization of a catalytic
organic reaction in real-time, showing its applicability to self-optimizing systems using criteria such as
stereoselectivity, multi-nuclear measurements or 2D correlations.
DOI: 10.1039/c4sc03075c
www.rsc.org/chemicalscience
as kinetic and mechanistic studies, as well as the character-
ization of the reaction mixture under the relevant process
Introduction
The use of continuous ow approaches in synthetic chemistry is conditions. Finally we also show how the system can be used to
an ever expanding eld for both organic and inorganic self-optimize a reaction in real-time, exploiting feedback from
1,2
synthesis. This is because the use of a ow-reactor manifold the spectroscopic measurements, leading to a self-optimizing
allows chemical transformations to be performed under continuous-ow process. This self-optimization is possible due
conditions that are not available with traditional batch chem- to the real-time monitoring of the product distribution via
istry; for example at high pressure and temperatures above the NMR, thereby allowing direct control of the reactor, reagent
2
boiling point of the solvent, exploiting supported reagents, and inputs, and process conditions. This control is used to direct
catalysts. This also provides enhanced safety against runaway the reaction towards a desired product distribution in real-time,
reactions as the amount of material being transformed is as a result of the feedback from the reactor system.
smaller and the surface area to volume ratios mean that heat
The benchtop NMR employed in this work (Spinsolve from
3
management is much easier. These developments have been Magritek) uses a compact permanent magnet (43 MHz) based
19,20
supported in recent years by the integration of in-line analytical on the Hallbach design.
The magnet from Spinsolve is
4
5,6
7,8
techniques, including UV-Vis, IR, and MS. This has repre- optimized to maximize sample volume, making it possible to
sented a major step forward, enabling the characterization of work with standard 5 mm NMR tubes. The cavity is therefore the
the products and the optimization of the reaction conditions in ideal to accommodate uorinated polytetrauoroethylene
real-time. Despite being one of the most powerful spectroscopic (PTFE) tubing allowing the reaction mixture to be owed
techniques, the use of NMR integrated into processing set-ups through the core of the device. Recently it was demonstrated
has mostly been reported using ‘by-pass’ congurations, ow that NMR spectra can be obtained employing this congura-
cells in high eld NMR machines, or micro coils for micro- tion, resulting in an ideal system for acquiring NMR data in an
9
–18
21

uidic applications.
We therefore hypothesized that the design and development magnet, Spinsolve has remarkable sensitivity and stability, and
of an integrated synthetic ow platform incorporating in-line permits acquiring spectra from several different nuclei
ordinary research laboratory. Despite the low eld of the
1
13
19
NMR for synthetic chemistry, at the milli-uidic scale, could be including H, C and F (Scheme 1).
employed to characterize and monitor organic reactions ‘on-
The reactor design employed in this work consists of a set
the-y’. Herein we present such a platform and we also of programmable syringe pumps (C3000, Tricontinent)
demonstrate its potential for a wide range of applications, such controlled via LabView. They were connected with standard
0
0
Omnit 1/16 OD tubing and standard connectors to a passive
0
0
micromixer. A tubular reactor was made of PTFE (1/16 OD,
0
WestCHEM, School of Chemistry, The University of Glasgow, Glasgow G12 8QQ, UK.
E-mail: Lee.Cronin@glasgow.ac.uk; Web: http://www.croninlab.com
00
.8 mm ID and 1/8 OD, 1.5 mm ID) with variable lengths
†
Electronic supplementary information (ESI) available: Details about the depending on the residence time required by the reaction.
methodology, LabView scripts, experimental set-ups, additional spectra and More detailed information about the experimental set-up can
self-optimization can be found in the SI. See DOI: 10.1039/c4sc03075c
be found in the ESI.†
‡
The authors contributed equally.
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reactor at controlled ow rates to ensure a 1 : 1 mixture with
controlled residence times before reaching the sensor. It is
important to mention that Spinsolve can work with non-
deuterated solvents. This reduces the cost of operation, elimi-
nates undesired isotopic effects, and permits working under
real processing conditions. The experiments were carried out at
decreasing ow rates (increasing residence times). Under these
1
conditions, the H signal of the aldehyde proton at 9.4 ppm
progressively disappeared, while the corresponding imine
proton at 7.9 ppm increased accordingly (Fig. 1). Although the
acquisition time (10 s) could be limiting, we chose reactions
that fell within the timescale of the NMR for this proof of
concept study.
The results are consistent with our previous report of the
same reaction system under ow employing 3D-printed milli-
27

uidic devices. The data ts to second order kinetics, typically
observed in imine synthesis. An advantage of NMR compared to
the previous methods employed to monitor organic trans-
28
formations in-line, like ATR-IR is that the signals observed are
proportional to the concentration of the analytes. Hence, it is
possible to calculate conversion and yields without the need of
additional calibration or corrections.
Scheme
1 Top: scheme of the flow-NMR platform. Examples
1
13
acquired in flow of H (red) and C (blue). Bottom: photograph of the
entire NMR setup (A) and a zoom in of the reactor system on top of the
machine (B).
Advanced in-line structural characterization
Employing a benchtop NMR as an in-line sensor allows us to
obtain an unprecedented amount of chemical information
during the reaction in real-time. To develop this further, we
designed and built a glass ow-cell which was employed to
maximize the sensitivity of the signal to be measured (see ESI,
Results and discussion
Kinetic studies
As a proof of concept, and as a test conguration for the in-line
NMR, the condensation reaction between benzaldehyde (1) and
benzylamine (2) to produce the corresponding imine N-bezyli-
denbenzylamine (3) was employed, see Scheme 2; this also
serves to demonstrate the suitability and simplicity of employ-
ing Spinsolve for monitoring organic reactions (see ESI,
Scheme S1†).
1
3
Fig. S2† for more details). Fig. 2 shows the C NMR spectrum of
the reaction mixture corresponding to the imine synthesis
between benzaldehyde (2 M in CH
3
CN) and benzylamine (2 M in
CH CN) mixed in a 1 : 1 volumetric ratio with a residence time
3
of 30 minutes to ensure full conversion was achieved. The total
acquisition time was 17 minutes and the peaks corresponding
to the imine, aliphatic and aromatic carbons were clearly
identied. DEPT sequences were also acquired showing the
difference between CH, CH and CH groups, see ESI, Fig. S7.†
22
Imine formation is very important in synthetic chemistry
23–26
and in self-assembly
forming highly complex 3D molecules
and materials. In a simple conguration, a 3-way mixer was
located above the aperture for the sample in the NMR spec-
trometer and a length of PTFE tubing (1.5 mm ID) was con-
nected in a down ow conguration and was used as a reactor
2
3
(see ESI, Fig. S6† for more details). At the start of the reaction
the ow rates were adjusted to ensure the full magnetization of
the reaction mixture before it reached the detector and to
ensure the correct residence time; so well-dened sections of
the solution were in the detector during each acquisition pulse.
A 1 M solution of each reagent in MeOH was pumped into the
Fig. 1 Imine synthesis monitored by in-line NMR. Left: superimposi-
tion of the spectra recorded. Right up: yield as a function of the resi-
Scheme 2 Imine synthesis employed as a test reaction for the flow- dence time. Yield calculated as Aim/(Aim + Aald). Right down: fitting of
NMR.
the experimental results to second-order kinetics.
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offers the possibility not only of monitoring the reaction in real-
time, but also of potentially observing intermediate steps, and
hence the ability of obtaining valuable mechanistic insights.
The test reaction selected was the a-uorination with Selectuor
of ethyl-3-oxo-3-phenylpropanoate (4) to study the formation
process of ethyl-2-uoro-3-oxo-3-phenylpropanoate (5), see
Scheme 3.
3
Initially, a solution of 4 (0.5 M in CH CN) was pumped
1
through the ow system and the H NMR showed the tauto-
meric equilibrium (see Fig. 4, red spectrum). In the next step,
this solution was mixed with a saturated solution of Selectuor
(
ca. 0.15 M in CH CN) and was pumped together in a 1 : 1
3
volumetric ratio with a residence time of 20 minutes. Under
these conditions the peaks corresponding to the tautomer were
1
strongly reduced and two new peaks were observed in the H
NMR spectrum (Fig. 4, blue spectrum).
This observation is consistent with an electrophilic uori-
nation, as we assume that this shi is consistent with the uoro-
olen structure 4, which is formed from the enol-tautomer
through electrophilic addition of the F-cation. The shi of the
1
3
Fig. 2
C NMR under flow conditions of compound 3. The spectrum
ꢀ1
corresponds to 64 scans (17 minutes) at a flow rate of 0.125 mL min
.
2
D NMR correlation spectroscopy can be performed in a
simple and straightforward manner employing our platform. A
number of 2D sequences including HSQC, HMBC, HMQC,

uorine in this position is consistent with similar structures
32
reported.
The monouorinated product could also be
1
9
19
1
19
HETCOR, COSY, J-RES, F-COSY, F-JRES and H– F COSY
correlations are possible and can be easily acquired under ow
conditions. Other sequences being targeted will enable inter-
esting experiments like DOSY. Fig. 3 shows an example of an
HSQC and a COSY spectra corresponding to the same studied
synthesis. The spectra clearly reect the correlation between
protons and carbons from the product molecule.
assigned to the coupling constant of 47.7 Hz in the proton
spectra, see Fig. 5. This shi is in agreement with the F NMR
spectra collected in a high eld 400 MHz NMR Bruker machine
19
(see ESI, Fig. S8†).
Electrophilic uorinations
Fluorinations are very important synthetic reactions with
applications in medicinal chemistry and positron electron
tomography, requiring rapid handling of the radioactive
Scheme 3 Synthesis of ethyl-2-fluoro-3-oxo-3-phenylpropanoate
29
reagents. In particular, electrophilic uorinations employing with Selectfluor.
Selectuor have attracted a great deal of attention because of
the mild and safe conditions employed when compared to
30
traditional uorinating agents such as F
2
.
Recently, the effi-
cient synthesis of uorinated compounds employing Selectuor
31
under ow conditions has been demonstrated. Our approach
Fig. 3 2D NMR correlation spectra acquired under flow conditions
corresponding to the synthesis of compound 3 in CH CN. Left: COSY Fig. 4 Results of monitoring of a tautomerisation reaction employing
spectrum indicating H interactions. Total acquisition time: 9 min. flow-NMR. Red: tautomeric equilibrium of the starting solution
3
1
1
13
1
1
Right: HSQC spectrum showing the H– C correlations. Total monitored employing flow H NMR. Blue: H NMR spectrum after
acquisition time: 38 min.
mixing 4 with Selectfluor under flow conditions.
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Table 1 Yield and selectivity corresponding to the cycloaddition
reaction between acrolein and cyclopentadiene
Entry
Cat./mol%
R
t /min
Yield/%
endo/exo
1
2
3
4
0
0.5
1
49
47
45
38
27.6
59.6
79.2
87
3.1
7.4
6.3
5.6
3
1
19
Fig. 5 Correlation between the J-coupling in the H and F NMR
1
spectra (J ¼ 47.7 Hz) corresponding to the fluorinated product 2. (A) H
both the yield and selectivity were strongly dependent on the
amount of catalyst employed. An increase in catalyst led to a
steady increase in yield. On the other hand the endo/exo ratio
has a maximum at 0.5 mol% of catalyst, with higher amounts of
catalyst leading to slightly lower ratios, (see ESI, Fig. S10†). The
endo product corresponds to the thermodynamic product, while
the exo corresponds to the kinetic.
NMR of the reaction mixture showing a new doublet. (B) Doublet
19
observed at ꢀ192 ppm in the F NMR.
On-the-y monitoring of stereoselectivity
1
H NMR is a very powerful spectroscopic technique, especially
for the elucidation of the stereoselectivity of a reaction, and
could be used to explore the optimization of the desired
stereochemical conguration of a given reaction mixture in real-
time. We therefore set out to explore this concept by using in-
Self-optimization of ow conditions
line NMR in a ow set-up, aiming for real-time feedback control As eluded to before, a very powerful yet unreported application
of the reaction. As a proof of concept we simultaneously of ow-NMR is in the realization of a self-optimizing reactor
monitored the yield and selectivity of a Diels–Alder cycloaddi- system able to adjust reaction trajectories under ow in real-
33–38
tion between cyclopentadiene and acrolein in real-time, dis- time.
Indeed, the use of an NMR-based sensor to enable
tinguishing both adducts (endo and exo isomers) though in-line feedback control of the operation conditions opens up a wide
analytics is possible with NMR. The ow set-up was modied to new range of possibilities for self-optimization, like uorination
1
3
mix a 2 M solution of cyclopentadiene in THF, acrolein (2 M in reactions, C signals, etc. As a proof of principle, we chose the
THF) and Sc(OTf) (0.02 M in THF) as a catalyst. The solutions catalytic synthesis of an imine derived from the 4-uo-
were mixed in a PTFE 4-way connector employing three pumps. robenzaldehyde (1 M in CH CN) and aniline (2 M in CH CN),
3
3
3
Increasing amounts of catalyst were added to a 1 : 1 mixture employing diluted triuoroacetic acid (TFA, 0.05 M in CH CN)
3
0
0
(
mol/mol) of both reagents and a total reactor volume of as a catalyst. Each reagent was pumped to a 1/8 mixer
2.47 mL was employed to allow enough residence time for the employing a tubular reactor with a total reactor volume of 3.75
reaction to occur. The endo and exo peaks were observed in the mL before entering into the NMR cell (Fig. 7A), and the signal
1
NMR spectra with some degree of overlap with the acrolein corresponding to the H NMR was collected at the end of each
peaks (Fig. 6).
reaction cycle. Aer applying an autophase algorithm based on
The band corresponding to the acrolein was expected to a entropy minimization of the zero and rst-order phase
39
appear as a doublet. However, as a consequence of the low corrections and a weighted least square baseline correction
40
magnetic eld, the coupling is of similar magnitude to the algorithm, the areas corresponding to the imine and the
magnetic eld, thus appearing as a multiplet due to the strong
coupling, (see ESI, Fig. S10†). As can be observed in Table 1,
Fig. 6 Simultaneous determination of yield and selectivity in a Diels–
Alder reaction. Left: yield observed as a function of the amount of
catalyst added. Right: deconvolution of the aldehyde region to eluci- Fig. 7 Self-optimization reaction of an imine synthesis under flow
date the endo/exo ratio and the yield.
employing in-line NMR to feedback the signal.
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starting aldehyde were integrated to assess the yield of the Table 2 Self-optimization of an imine synthesis derived from the 4-
fluorobenzaldehyde and aniline employing TFA as a catalyst
reaction.
A
im
Entry
Iteration
x1
tR/min
Yield/%
J
ꢀ
1
J ¼ A
x
1
t
R
(1)
(2)
im þ Aald
1
2
3
4
5
6
7
1
5
0.03
0.49
0.45
0.66
0.48
0.63
0.71
9.1
2
4.4
2
2
2
76.5
11.5
89
0.003
0.028
0.092
0.019
0.192
0.158
0.264
P
x
i
¼ 1; 2 # t
R
# 10
10
15
20
25
29
5.6
80.7
50.4
73.9
The tness function employed was related to the space-time-
yield of the reaction (eqn (1)), where Aim and Aald are the cor-
responding integrated areas of the imine and the aldehyde in
2
the experimental spectra respectively; x
1
corresponds to the
volumetric fraction of aldehyde and t is the residence time of
R
A modied version of the Nelder–Mead algorithm was
the reaction mixture before reaching the detector. This tness
function aims to maximize the yield at the highest concentra-
tion of aldehyde and at the minimum possible residence time.
The total reactor volume was 3.75 mL and each reaction cycle
pumped a total of 5 mL of reaction mixture. The algorithm,
shown graphically in Scheme 4, chooses the composition and
residence time of each experiment. A volume of uid larger than
the reactor was pumped in each cycle to ensure that the steady
state was achieved and the ow cell was lled with the reaction
mixture. Aer each iteration the cell was ushed with 5 mL of
CH CN. The parameters are the composition (x ) and the resi-
41
employed for the self-optimization. The simplex is allowed to
expand and reduce to a minimum the number of steps required
to achieve the optimum. There are 3 degrees of freedom in the
system, which means that the simplex is formed by 4 randomly
selected points. Aer evaluating these points, the system starts
to optimize aiming to maximize the J value.
The imine synthesis selected is more challenging than the
previous case studied. Indeed, without the addition of an acid
catalyst, the reaction yield is below 15% aer 10 minutes.
Fig. 7B shows an example of the spectra collected, processed
and employed for the self-optimization. The imine signal is
stronger than the starting aldehyde, thus indicating a high
degree of conversion. Throughout the iterations (Fig. 7C and
Table 2) J values consistently increase, reaching a maximum
value of 0.264 in iteration 29. This value is correlated with the
space-time-yield (STY) and productivity.
3
i
dence time with boundaries between 2 and 10 minutes (eqn (2)).
The reaction volume was xed in each cycle.
In fact, multiplying this J value by the concentration of the
starting aldehyde solution and the molecular weight of the
ꢀ
1
ꢀ1
product a STY of 3152 kg h
L
is obtained. In the same way,
multiplying this J value by the reactor volume (3.75 mL) the
ꢀ
1
productivity observed is 11.82 kg h
.
Conclusions
To sum up, a fully automated and novel platform incorporating
ow in-line NMR has been presented. A range of applications

1
3
19
have been demonstrated for the rst time, including C,
F
and 2D NMR spectra of reaction mixtures under ow condi-
tions. Furthermore, this technique allows a variety of kinetic
and mechanistic studies. Finally the self-optimization of ow
1
reactors has been demonstrated employing in-line H NMR.
This study opens the door to the employment of benchtop NMR
as an analytical tool in ow-chemistry set-ups for advanced
characterization of chemical reactions in real-time and for the
self-optimization of chemical processes based on single or
multiple NMR signatures. Indeed, future processes allowing us
to synthetically ‘dial-a-molecule’ will undoubtedly require
Scheme 4 A flow diagram showing how the self-optimizing reactor
system is programmed; physical events are shown by the blue boxes
and computational steps by the orange boxes. In step 1 a random
starting point for the reaction parameters is selected and the reaction
42,43
is run in step 2. As the reaction is started the in-line analysis continuous systems with feedback control.
commences in step 3 and then in step 4 the J evaluation is conducted.
In future work we
will explore the use of algorithmic control of organic synthesis
not only for methodology development, but for the discovery of
new compounds, as well as the optimization of time-critical
processes such as the synthesis of radioactive uorine-con-
taining compounds under ow (Scheme 5).
If this is the first experiment then the cycle repeats so a comparative
analysis can be done and the algorithm makes a decision in step 5. In
step 6 the reaction conditions are changed followed by the analysis, J
evaluation and cycles as before. Successive cycles are conducted until
the finishing criteria are reached.
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