1. Reaction Engineering for Environmentally Benign Processes Reactor Selection Strategy M.P. Dudukovic Module 6  Homogeneous systems  Heterogeneous systems  Systems (multi-scale) approach S1

2. Approach to Reactor Selection 1.Identify number of phases present at reaction conditions (thermodynamics) –Single – Homogeneous system –Multiple – Heterogeneous systems 2.Identify stoichiometry, number of reactions, energy requirements (e.g. adiabiatic temperature rise/fall) 3.Identify mechanism (if possible) and plausible reaction pathways and active intermediates 4.Decide on the purpose of reactor selection  Evaluation of kinetic data  Data for scale-up  Commercial design S2

3. Chemical Reaction Engineering Basics  Molecular Level –Mechanisms and kinetic rates  Eddy (Particle) Level –Micromixing & kinetics –Intra phase diffusional effects (Thiele modulus, effectiveness factor) –Inter phase transport effects  Reactor Level –Ideal flow patterns (CSTR, PFR) –Non-ideal flow patterns between phases –Contacting patterns –Mixing S3

4. For Homogeneous Systems:  Identify the magnitude of heat transfer requirement  Assess the effect of ideal flow patterns on volumetric productivity and selectivity  Select the best ideal flow pattern (batch, semi-batch, continuous flow stirred tank reactor – CSTR, plug flow reactor – PFR)  Optimize your objective function (related to profit) using as manipulative variables: -Feed reactant concentrations and their ratio -Feed temperature -Reactor temperature or temperature profile Keep things simple whenever possible!  Approach the ideal by practical design as much as possible. S4

5. HOMOGENEOUS SYSTEMS (Optimizing Volumetric Productivity) Batch Reactor Plug Flow Reactor (PFR) Continuous Flow Stirred Tank Reactor (CSTR) F A0 C A0 F A = F A0 (1-X A ) T = const. F A0 C A0 F A = F A0 (1-X A ) S5

6. where is the ratio of stoichiometric coefficients Volumetric Productivity for Product P then is For CSTR For PFR The ratio of volumetric productivities in the two systems Is the ratio of average reaction rate in a PFR and the reaction rate at exit conditions of the CSTR S6

7. Homogeneous Systems (optimizing selectivity) A + B Pdesired product 2nd Order A + A Sundesired product 2nd Order Which is the optimal flow pattern ? What is the optimal selectivity ? (at fixed feed concentrations, feed ratio of F A0 /F B0 and conversion of B) B PFR A P+S A PFR B BP+S PFR A B A P+S initially only B A initially only A B S7

8. In multiple reactions it is useful to consider the point yield behavior Then in CSTR While in PFR Production rate of R is maximized:  In a CSTR for systems with d  /dC A <0 (undesired reactions of higher order than the desired one)  CACA  CACA  CACA  In a reactor combination for nonmonotonic yield curve  In a PFR for systems with df/dCA>0 (undesired reactions of lower order than the desired one) S8

9. Other Simple Rules Worth Remembering  In consecutive reactions production of intermediate is always more favored in a PFR than in a CSTR  For exothermic reactions maximum volumetric productivity is reached at an optimal temperature which is a function of conversion  When desired reaction has the highest activation energy select the highest temperature for best selectivity  When desired reaction has the lowest activation energy lowest practical temperature optimizes selectivity  For intermediate activation energy of desired reaction an optimal temperature or temperature profile can be found For lumping complex reaction schemes into patterns to analyze see Levenspiel, O., Chem. React. Eng. S9

10. Recognize that selected ideal flow patterns may only be approached in practice. Determine the deviation from ideal flow patterns by examining the residence time distribution (RTD) of the system either derived from the solution of the flow field or experimentally determined on a reactor prototype (cold flow model), pilot plant or on the actual unit. E t E E t PFRCSTR Between PFR & CSTR exponential decay t S10

11. Characteristic reaction time In between micromixing models needed! Characteristic diffusion time In scale-up of systems with broad RTD we need to assess whether transport limitations can develop on a micro-scale (i.e. in bringing reactants in contact or in supplying them to the soluble catalyst, enzyme or cell). This is particularly important for non-premixed feeds. We need to assess the scale of the smallest turbulent eddies in the system which is determined by the amount of energy dissipated per unit mass of the system. For example molecular diffusivity S11

12. All reactions with  R > O(1 second ) will not cause transport limitations. Reactors with large can be considered in maximum mixedness condition Only reactions with  R > 10 5 (s) will not cause transport limitations. For most systems mixing and reaction occur simultaneously and proper micromixing model is needed. Proper treatment of this topic is not available in most standard reaction engineering text. References and related notes can be obtained upon request. Example: S12

13. 1.Segregated Flow – All fluid elements remain segregated by age on their sojourn through the system and elements of different ages mix only at the exit. Two extreme micromixing models are: 2.Maximum Mixedness – All fluid elements of same life expectancy are together at all times. S13

14. Micromixing Effect A P1st order k1k1 2A S2nd order k2k2 k 2 C A0 /k 1 = 0.5 Reactions: System:CSTR, = 48 min;Exponential RTD Laboratory System:1 L vessel, 1500 rpm Large System:5000 gallon vessel; 300 rpm Selectivity in the Lab.:C P /C S = 98 at X A = 0.98 Selectivity in the Large Unit: C P /C S = 15 at X A = 0.98+ Model Predictions: Maximum Mixedness Flow:C P /C S = 100 Segregated Flow:C P /C s = 4.5 S14

15. Key issues associated with selection and scale-up of reactors for homogeneous reactions  Developing sufficient knowledge of molecular level events to propose mechanism and establish reaction pathways, key reactions and their parameters.  Determining optimal ideal flow pattern and maintaining the same flow pattern (same and with scale-up).  Avoiding bypassing and stagnancy with scale-up.  Maintaining same level of micromixing with scale-up is needed but hard as power dissipated per unit volume decays with scale and affects micromixing adversely.  Maintaining adequate heat transfer rate with scale-up is difficult as heat evolved by reaction  volume and heat removed  surface. With scale-up in general S/V is reduced which may lead to problems unless corrective steps are taken.  Control of temperature, pressure, pH etc. becomes more difficult with increased scale.  Homogenous catalyst or soluble enzyme recovery, a cinch in the lab, becomes a major chore in large units.  Solvent separation is a problem.  Heterogenize the system whenever possible, do not use solvents unless absolutely necessary! S15

16. The objective in multiphase reactor selection and design is to minimize the manufacturing costs in producing the desired marketable product. For conversion cost-intensive processes one must achieve both high volumetric productivity and high product concentration. For recovery cost intensive processes (e.g. often encountered in biotechnology) one must achieve high product concentration c p (kg/m 3 ). In either case proper reactor selection is required since reactor type and performance affects significantly the whole process. S16

17. feed, Q product, Q Reactor performance determines the number of separation units and their load and hence profoundly affects process economics and profitability. -Conversion- Flow Rates- Kinetics- Macro -Selectivity- Inlet Conc. & Temp.- Transport- Micro -Production Rate - Heat Removal LHSRHS S17

18. In heterogeneous systems the volume averaged reaction rate (volumetric productivity) is a function of:  Molecular scale – kinetics and rate forms  Single particle (single eddy) scale effects on diffusion and reaction in the particle, specific phase interfacial area effect on inter-phase mass and heat transfer  Reactor scale effect via contacting pattern and phase RTD influence on the average rate and via flow regime effect on phase holdups and inter-phase transport coefficients. S18

19. As a reminder consider the diffusional effects on the rate in a porous particle with uniformly deposited active catalyst in pores Where typically With Thiele modulus True kinetics, activation energy is observed. Doubling catalyst activity doubles the rate. Rate independent of S p /V p 1 - 0.1- 0.01 - 0.001 - 10-4 - 0.010.11.0101001000 |||||||| Approximately ½ E observed. Reduced order S19

20. Now one must also consider inter-phase transport And for first order reaction one gets The denominator contains the sum of external resistance and internal + kinetic resistance. Of course we need the rate per unit reactor volume so Clearly how much catalyst we packed in (bed voidage  B ) affect also volumetric productivity. Finally flow pattern will affect how (-R A ) bulk is averaged and flow pattern affects transport coefficient k s. Approximately ½ E observed. Reduced order S20

21. Gas Limiting Reactant (Completely Wetted Catalyst) S21

22. A System Approach to Multiphase Reactor Selection Process Requirements Maximum selectivity Maximum conversion Maximum productivity Stable Easy scale-up Operability Environmental Constraints Minimum pollution Why System Approach? Number of configurations extremely large Limits to intuitive decision making Innovations are possible Reactor Type & Contacting Pattern? Economics Reactants Products S22

23. Multiphase Reactor Selection Methodology I.Volume / Interfacial Area for the Phases ~ d p for gas-solid systems ~  for gas-liquid systems ~d p and  for G-L-S systems II.Contacting & Flow Pattern a) RTD for each phase (PF, backmixed) b) Co – Counter – Cross current? c)  Split addition  Product removal in situ, etc. III.Flow Regime  Homogeneous  Churn turbulent  Dense phase riser (air lift)  Dilute phase riser (spray) S23

24. Example: Recovery of Oil From Oil Shale Process Requirements (Wish List) Maximize “oil” recovery (99%+) Scale-up to mega-size units (  500 kg/s feed) Minimize reactor volume Handle fines well >200 G-S Reactor Configurations possible! After Krishna (1989) S24

25. S25

26. Shell’s SPHER 3 Bed Concept Chevron’s STB (staged turbulent bed) S26

27. Decisions to be made: I.Particle Size II.Contacting Pattern III.Gas-Solid Fluidization Regime a. Overall contacting flow pattern of gas and solid phases: b. RTD of each phase: Krishna (1992), Adv. Chem. Eng. S27

28. Kinetics & Transport Phenomena Affecting Process Performance Oil Shale Pyrolysis Wallman et al (1980), AIChE Meeting, San Francisco S28

29. Large throughputs  minimize reactor Volume  need small residence times  need particles in range I  need plug flow of solids Residence time required for heating up of particle to 95% of T g = 482°C Residence time required for isothermal backmixed reactor (174 min) Conversion of kerogen 99% Residence time required for isothermal plug flow reactor (8 min) S29

30. Desired product (heavy oil) yield improved with small particle size (dp < 2mm). In grinding shale to make 2mm particles fines may be formed too. S30

31. III. Flow Regime Selection Tree II. Contacting Flow Pattern Selection Tree I. Particle Size Selection Tree S31

32. Wilkins et al (1981), 2 nd World Congress, Montreal To reduce oil degradation, must remove oil as soon as formed  in situ product removal S32

33. A.Counter-Current Contacting B.Co-Current Contacting C.Cross-Current Contacting Reactor volume requirement  need plug flow of solids Rapid oil removal  cross flow for gas S33

34. Proper fluidization regime should now be chosen to accommodate: Desired particle size (small) Desired solids holdup (large) Desired contacting pattern (solids-plug flow, gas short contact time) Excellent heat transfer S34

35. The “Ideal” Reactor: Multi-Stage Cross-Current Fluidized Bed Meets the criteria: Small particles Plug flow of solids Short vapor residence time (cross-flow) Good mixing and heat transfer Scale-up possible – study one train Shell Shale Retorting Process (Shell Research) Krishna (1992) S35

36. For Shale Example Possible Reactor Combinations Sequential design making leads to success without brute force evaluation of all options. Choice of wish list effects final result. Add: Choice should be based on known technology  Moving bed reactor S36

37. This example illustrates how consideration of all scales leads to successful reactor selection It also teaches that in situ separation when possible is of high value and can sometimes be achieved by:  Catalytic distillation Selective adsorption or absorption Membrane separation Other means (e.g. dynamic reactor operation, etc.) Think Out of the Box! S37

38. Clearly is determined by transport limitations and by reactor type and flow regime. Improving only improves if we are not already transport limited. Our task in catalytic reactor selection, scale-up and design is to either maximize volumetric productivity, selectivity or product concentration or an objective function of all of the above. The key to our success is the catalyst. For each reactor type considered we can plot feasible operating points on a plot of volumetric productivity versus catalyst concentration. S38

39. S39

40. Schematic of Bubble Column Type of Photo Reactors (Commercially Used) A train of bubble columns (sparged reactors) through which liquid toluene and chlorinated products flow in series while chlorine is added into each column and hydrogen is removed from the column. Typical selectivity to benzyl chloride: 90% But Toluene conversion is less than 30%. Can one do better? S40

41. Schematic of Photo Reactive Distillation System Configured into a Semi-Batch Model Allows in situ product removal and toluene recycle. Selectivity to benzyl chloride: 96% + up to toluene conversion of 98%. Z. Xu (1998) S41

42. PROBLEM Production of herbicide intermediate, aryl amino-alcohol (AA) via hydrogenation of aryl nitro-alcohol (NA) Reaction System:complex Current Reactor:semi-batch dribbling liquid reactor with suspended catalyst slurry DISADVANTAGES:  Low volumetric productivity  Poor selectivity  Catalyst filtration and separation problems  Pressure limitations (due to shaft) Khadilkar et al., AIChE J., 44(4), 912 (1998) Khadilkar et al., AIChE J., 44(4), 921 (1998) S42

43. Reaction Network S43

44. Conclusions  Liquid trickling flow pattern is preferable to a suspended catalyst mixed slurry to obtain the desired yield and productivity of Amino Alcohol.  Yield improvement is observed with decreasing feed concentration, liquid flow rate and temperature due to suppression of NA decomposition and subsequent side reactions.  Productivity of AA is a complex function of flow, feed concentration and temperature with optimal productivity being determined by the level of acceptable by-product concentrations.  Laboratory trickle bed performance data is shown to be an effective means to obtain the network kinetic parameters by proposing a plausible mechanism and optimizing the reactor model generated data. This is particularly effective in cases where conventional slurry and basked methods are rendered ineffective by the dominance of side reactions. S44

45. References 1.Dudukovic, M.P., Larachi, F., Mills, P.L., “Multiphase Reactors – Revisited”, Chem. Eng. Science, 541, 1975- 1995 (1999). 2.Dudukovic, M.P., Larachi, F., Mills, P.L., “Multiphase Catalytic Reactors: A Perspective on Current Knowledge and Future Trends”, Catalysis Reviews, 44(11), 123-246 (2002). 3.Levenspiel, Octave, Chemical Reaction Engineering, 3 rd Edition, Wiley, 1999. 4.Tranbouze, P., Euzen, J.P., “Chemical Reactors – From Design to Operation”, IFP Publications, Editions TECHNIP, Paris, France (2002). S45