Modeling and Optimization of Semi- Interpenetrating Polymer Network (SIPN) Particle Process

Transcription

1 Modeling and Optimization of Semi- Interpenetrating Polymer Network (SIPN) Particle Process Weijie Lin, Lorenz T. Biegler, Annette Jacobson Chemical Engineering Department Carnegie Mellon University, Pittsburgh, PA, EWO Meeting September 28, 2009, Pittsburgh

2 Presentation Outline Project overview and previous status review Progress updates Kinetic modeling on crosslinking Parameter study and simulation Future work discussion Summary

3 Project Overview SIPN -- An Advanced Polymer Process Semi-Interpenetrating Polymer Network (SIPN) Particle Process Polymer A Polymer B Full network Seminetwork Fig 1. Interpenetrating polymer network structure SIPNs, are polymeric composites obtained by interpenetration of a linear or branched polymer within a network of another crosslinked polymer Wide applications 3

4 Project Overview SIPN Manufacturing Seeded suspension polymerization -- In situ reaction Monomer Initiator Polymerization reactor Seed particle Monomer droplet Aqueous media Fig 2. SIPN reactor Monomer Monomer / initiator Seed polymer 4

5 Polymer Reaction Kinetics (Cont. ) 5

6 Stage-wise Modeling Strategy I. Swelling II. Polymerization III. Crosslinking System dependent Monomer and seed selection Semi-batch operation Production rate limiting step Particle properties determining factor Networking reaction Macromolecular structure End-use properties 6

7 Stage-wise Modeling Strategy I. Swelling II. Polymerization III. Crosslinking Imbedded in parameter estimation Single Particle Model Extended for crosslinking reaction 7

8 Stage-wise Modeling Strategy I. Swelling II. Polymerization Kinetic mechanism in state II modeling Imbedded in parameter estimation Single Particle Model 8

9 Generalized reaction diffusion model Coupled differential-integral-algebraic equations Moving boundary condition Initial condition 160 differential equations ; 103 algebraic equations 9

10 Stage-wise Modeling Strategy Stage III: higher temperature, seed polymer grafting and crosslinking Initiation -A-A-A-A-A- A- B-B-B- Termination I * -B-B-B* -A-A-A*-A- -A-A-A-A*-A-A- B-B-B- -A-A-A*-A- Polymer chain can be initialized -A-A-A-A*-A-A- B-B-B- Termination reaction can happen between all types of free radicals -A-A-A-A-A-A- B-B-B- -A-A-A-A- III. Crosslinking Extended for crosslinking reaction 10

11 Extending the kinetic model to include network fraction calculation Separate representation for two polymers = + = + Classified by different types of free radicals 11

12 Statistical and Sectional Grid Approach (1) Chain combination and breakup Fixed pivot technique Fig 4. A general grid for fixed pivot technique (Number and mass are preserved by set f(v) to zeroth and first properties) 12

13 Statistical and Sectional Grid Approach (1) Representative grids Discrete section Fig 5. An illustration example of sectional grid approach Assume equal possibility for combination reaction At grid point Between grid points

14 Statistical and Sectional Grid Approach (2) Break up / aggregation kernel function More details of seed polymer chain properties will be able to consider Nonlinear structure is modeled by statistical distribution New model capabilities Gel fraction / Gel composition Branching frequency Joint molecular weight distribution 14

15 Grafting & Crosslinking Simulation (Stage III) a) Grafting reaction development b) Networking reaction development Homo-PS B Grafted-PS -B Co onversion ratio Scaled time 0 1 Scaled time Fig 6. Nominal Value Simulation of Stage III Simulation observations: Initiation of monomer and polymer are competitive reactions in the third stage Homo B is the major form of B in the competition Network formation takes place after monomer consumptions Seed polymer gelation increases with time 15

16 Study of Grafting Parameters Ratio (100%) Determine parameters: initiator initiation and chain transfer Homo-B nominal Grafted-B nominal Homo-B k2' = 5k2 Grafted-B k2' = 5k2 Homo-B kfb' = 5kfb Grafted-B kfb' = 5kfb Gel wei eight fraction (100%) Nominal Value K2' = 5 K2 Kfb' = 5 Kfb Scaled Time Fig Scaled Time Observations: Grafting ratio is mainly determined by Initiator initiation and chain transfer Initiator initiation and chain transfer effect are coupled for grafting ratio Two reactions have different effect on gelation 16

17 Study of Crosslinking Parameters Determine factor: the ratio of chain termination and chain breakage 50 Gel weight fraction (100%) A-A-A-A-* Increasing chain length AAAAAAAA Decreasing chain length AA* + AA Scaled Time Fig k t / k β 17

18 Effect of Processing Condition (1) Effect of initiator concentration Nominal Higher Initiator Ratio Observation: Gel weight fractio on (100%) Higher initiator concentration leads to earlier gelation Gel fraction increases with initiator concentration Scaled Time Fig 9. Gel fraction development at varied initiator concentration 18

19 Effect of Processing Condition (2) Effect of Seed Polymer Property 60 Nominal Higher Seed Mw( +10%) 50 Observation (100%) Gel weight fraction Gel fraction increases with seed polymer molecular weight Scaled Time Fig 10. Gel fraction development at varied seed polymer Mw 19

20 Current Modeling Challenges o Apparent kinetic rates are conversion dependent. Possible changes during networking reaction o Modeling kinetic rate function o Complexity Reduction of process condition is desired for parameter estimation o Experiment design o Advanced characteristic approach for network polymer o Experimental data acquisition 20

21 Future Work Discussion On-going work : Stage II model improvement Optimal feeding policy for different grade of product Parameter estimation for crosslinking and grafting materials characterization methods Parameter ranking and subset selection Design of Experiment 21

22 Conclusions A novel approach that combines statistical and sectional grid techniques is developed for simulation of nonlinear molecular weight distribution and network fraction for SIPN product. Kinetic parameters and process conditions are studied by model simulation Simulation results are consistent with experimental observation Grafting, crosslinking kinetic parameters will need to be estimated from additional materials characterization methods 22