Microreactors in Discovery and Development Klavs F. Jensen Department of Chemical Engineering Massachusetts Institute of Technology Cambridge, MA 02139 [email protected]web.mit.edu/jensenlab PoaC Symposium, Eindhoven May 22, 2013 Advantages of continuous synthesis • Safety - Small scale, no headspace, no accumulation of reactive/toxic intermediates • Expansion of reaction space/toolbox/feasibility - Many “Forbidden Reactions” become feasible • Robustness, stability, QbD - Steady-state, continuous processes • Scalability – scale-up faster and reliable • Versatility and flexibility - customizable and adjustable equipment • Leverage and efficiency - increase in throughput, with a dramatically reduced equipment footprint
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Microreactors in Discovery and Development · Microreactors in Discovery and Development Klavs F. Jensen Department of Chemical Engineering Massachusetts Institute of Technology Cambridge,
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Microreactors in Discovery and Development
Klavs F. JensenDepartment of Chemical Engineering
Massachusetts Institute of TechnologyCambridge, MA 02139
• Model based methodsParameters: temperature, residence time, catalyst/ligand loading, solvent composition, ionic strength, pH
J.P. McMullen and K.F. Jensen, Annu. Rev. Anal. Chem. 3, 19–42 (2010).Org. Proc. Res. Dev. 14, 1169–1176 (2010)
Yield = 80%T = 88°C RT= 50s
• Nelder-Mead Simplex algorithm for online optimization
• 46 automated experiments to move from benzaldehyde yield of 21% to 80%
• Achieved 1 experiment per 10 minute throughput rate
11
Multi-variable reaction optimization
J.P. McMullen and K.F. Jensen, Org. Proc. Res. Dev. 2010 , 14, 1169–1176.
Online optimization with ReactIRflow cell
Conjugate GradientSteepest Descent
• Black box optimization is feasible with a variety of optimization techniques.• The choice of methods significantly influences the number of experiments
J.S. Moore et al, Org. Procss. Des. Devel. 2012, 16 ,1409–1415 12
Microreactors can produce chemical kinetics in relatively few experiments
• Benefits of using integrated microreactors for kinetic studies:
• With the appropriate approach, microreactors yield:– Rate law (mechanism formulation)
– Rate parameters
Better control of residence time and temperature
Study reactions at unconventionalconditions
Small amounts of expensive reagent material required
Intelligent design of sequential experiments
Easier to scale up Investigate fast reactions
No temperature gradient No head space
No mixing gradient Accurate sampling
13
No informationPlenty ofinformation
Rat
e
Time
J.P. McMullen and K.F. Jensen, Org. Process Res. Dev., 15 398–407 (2011)13
Reaction example
Use automated microreactor system to investigate reaction
– Select rate model from small list of potential rate forms
– After rate model is chosen, estimate rate parameters
– Optimize reaction conditions
by a small number of experiments varying time and inlet concentrations
14J.P. McMullen and K.F. Jensen, Org. Process Res. Dev., 15 398–407 (2011)
Determine rate parameters
Optimize conditions
Scale-up
After 8 experiments
Parameter Estimate CI
EA (kJ/mol) 50.7 ± 0.9 (1.8%)
A x 105 (M-1 s-1) 1.71 ± 0.6 (35.5%)
Scale-up based on kinetics and reactor models
• Use chemistry information with reactor flow and heat transfer models to predict performance of scaled up system
– Example: incorporating kinetics from microreactor to scale up by a factor of 500 using a Corning Advanced Flow Reactor System
– Predicted performance agrees with experimental data
15
120 L 60 mL
Entry Time (min) Temp. (oC) Experimental Predicted
1 1.5 110 78.1 ± 0.4 79.3
2 2.0 100 82.6 ± 0.1 83.7
3 2.5 110 85.2 ± 1.0 86.5
4 1.0 126 83.5 ± 3.1 83.9
J.P. McMullen and K.F. Jensen, Org. Process Res. Dev., 15 398–407 (2011)
Using high pressure and temperature to accelerate reactions - Aminolysis of epoxides
Flow reactor yields similar to microwave batch yields without headspace issues, shorter reaction times, reduced bis-alkylation, and scalable performance – performance scales to larger reactors
16M.W. Bedore, et al. Org. Proc. Res. Dev. 2010, 14, 432-440
A
BC
A Metoprolol B C
CB
Kinetics and scaling of Aminolysis of epoxides
• Single preparation of two reagent solutions, 0.5 to 2 g of each reagent to scan up to 35 sets of conditions with samples in triplicate, generating over 100 data points within one 8-h period.
• Scale from 0.12 mL to 12 mL with accurate prediction of yield
• Dean flow off-sets increased dispersion
O
PhNH2
Ph
OH
NH
Ph
OH
NPh
OH
3
1
Ph NH
OH
OPh
Ph
OH
N
Ph
OH
Ph
HON
Ph
OH
2
6
4
5
7
27.2 kJ/mol
16.2 kJ/mol
8.4 kJ/mol
12.2 kJ/mol
Sudarsan, Ugaz, PNAS. 2006, 103, 7228-7233.
N. Zaborenko, et al. Org. Proc. Res. Dev. 2011, 15, 131-139. 17
Continuous flow systems for manufacturing
• Production scale systems can be achieved by scale-out or scale-up
• Scale-out – parallelization of microreactors– Retain heat and mass transfer benefits– Large challenges in fluidic connections
and control• Scale-up – increasing size of reactor
– Realize higher production rates – Retain heat transfer advantages– Reduce micro-scale concerns (i.e.
– Leaching of catalyst, especially metal centers , requiring the use of downstream metal capture beds
– Solvent selection
– Sufficiently low and sharp molecular cut-off and solvent stability of membranes
K.D. Nagy and K.F. Jensen, ChimicaOggi/Chemistry Today, 29 (4) (2011).
Recycling of homogeneous catalysts
• Continuous recycling of unmodified homogeneous palladium catalysts via liquid-liquid phase separation
• Continuous catalyst recycling in palladium catalyzedhydroxylation of aryl halides. 5 runs with nearly constant yield of ~80%, but then slow degradation of the catalyst.
Li, P. et al. ChemCatChem 2013
Br OMe HO OMe[Pd] L3
toluene, 2M KOH,
TBAB 5 mol%, 100 oC
P(t-Bu)2
i-Pr i-Pr
i-Pr
OMe
MeO
L3
Continuous nano-filtration and recycle of a metathesis catalyst in a micro flow system
• Evonik Puramem® 280 membrane retains catalyst in the system
• Low co-fee of catalyst to make up for deactivated catalyst
• Continuous ethylene removal to reduce catalyst deactivation
E. O’Neal
Continuous nanofiltration and recycle of a metathesis catalyst in a micro flow system
• TOF ~ 750 h-1 at the start of the experiment
• 10 minute residence time with > 94% product at the reactor outlet
• Total TON of 935 was obtained using this system.
E. O’Neal
0
20
40
60
80
100
120
140
0 15 30 45 60 75
Reactor Volumes, t/
Re
lati
ve P
res
su
re D
rop
Constriction
Bridging
Exploring the origins of clogging
• Handling of solid reagents and products raise challenges for microreactors
R. Hartman et al., Org. Proc. Res. Dev. 2010 14 (6), 1347–1357
Salt by-product
37
Teflon reactor with integrated ultrasound
• Continuous operation without plugging
• Piezo @ 50kHz, 30 Watt
0.00
0.02
0.04
0.06
0.08
0.10
0.12
0.14
0.16
0 1 10 100 1000
Particle size [m]
Par
ticl
e si
ze f
ract
ion
no sonication
40kHz
50kHz
60kHz
Kuhn, S. et al., Lab Chip 11 2488-92 (2011) 38
Precursors
solventligands∆
• Optical properties and average size depend on factors difficult to control: injection, local temperature and concentration fluctuations, mixing and cooling rates
• Controlled growth of heterostructures difficult to realize, specifically core/shells and graded alloys
PO
Si, Ge, InAs,
InGaN, …
CdSe, CdS, ZnS,
PbSe
Injection
In(MA)3(TMS)3P
Batch synthesis has numerous challenges and limits realization of novel nanostructures
Two stage system : Separate investigations of mixing and aging processes
ConstantAging Temp.320°C
ConstantMixing Temp.170°C
Aging temperature is significant
J. Baek, et al., Angew. Chem. Int. Ed., 2011, 50, 627 –630.
• Residence time : 4 min (fixed)• Solvent, octane at 65 Bar
Reactor design for gradual addition
Side Stream 1
Main Stream
Side Stream 2
Product
• Consideration Distribution of each side flows Viscosity and flowrate changes Residence time after each injection Reactor size restriction Prevent back flows
R1 R2 R3 R4 R5 R6
R8
R7 R9
R10
R11
R12
R13
R14
R15
R16
R17
F2
F1
F3
α∙(F1+F2+F3)
Sequential addition of molecular precursors increase InP QD size
J. Baek, et al., Angew. Chem. Int. Ed., 2011, 50, 627 – 630.
Hierarchical assembly nanostructures for catalysis: nanoparticle synthesis
S.K. Lee, et al., Lab Chip, 2012, 12, 4080 - 4084
Hierarchical assembly nanostructures for catalysis: self assembly
S.K. Lee, et al., Lab Chip, 2012, 12, 4080 - 4084
Hierarchical assembly nanostructures for catalysis: Microreactor application
Oxidation of 4-isopropyl benzaldehyde
S.K. Lee, et al., Lab Chip, 2012, 12, 4080 - 4084
Summary
• Microreactors are coming of age
• Understanding of reaction and mass transfer enables implementation and scaling of flow processes
• Automated tools for extraction of chemical kinetics by using statistical techniques
• Automated optimization based on black box approaches, or better, models with chemical kinetics
• Scaling of homogeneous systems can be accomplished with classical reaction engineering concepts
• Quantitative understanding of heat and mass transfer needed for scaling of multiple phase systems
• Emerging techniques for handling of solids, including the synthesis of nanoparticles
• Ability to synthesize complex micro-nano structures
AcknowledgementsMIT Colleagues:
Moungi G. Bawendi, Peter M. Allen,S. L. Buchwald, Pengfei Li T.F. Jamison, Bo Shen , David Snead
Students and postdocs: Andrea Adamo, Jinyoung Baek, Stephen Born, Patrick Heider, Simon Kuhn, Xiaoying Liu, Amol Kulkarni, Seung-Kon Lee, Jonathan McMullen, Jean Christophe Monbaliu, Jason Moore, Kevin Nagy, Maria-Jose Nieves Remacha, Everett O’Neal, Victor Sebastian, N. Weeranoppanant, Yanjie Zhang
Funding: Corning, DARPA, ISN, NSF, Novartis-MIT Center for Continuous Manufacture,