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Kinetics reaction scheme_v1.2
The document outlines a systematic approach to investigating reaction kinetics, starting with fundamental thermodynamics and kinetic databases, and moving on to constructing reaction networks and rate expressions. It emphasizes the importance of simple reactor models and experimental work, including parameter estimation and design of experiments to improve kinetic estimates. Finally, it discusses the challenges of translating uncertainties from kinetic models to industrial reactor performance.
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Kinetics reaction scheme_v1.2
- 1. Funda- Previous slide Next slide mentals Thermo- Dynamics Kinetic Data bases Micro- kinetics Ab-initio methods Starting point: If you intend to perform a thorough investigation of the reaction kinetics, you should start with the fundamental basis: search for thermodynamics and kinetic databases (if available). Additionally, microkinetics and ab-initio modelling (e.g. using the DFT theory) could be considered.
- 2. Funda- Create reaction network Previous slide Next slide mentals Construct rate expressions Initial parameer estimates Thermo- Dynamics Kinetic Data bases Micro- kinetics Ab-initio methods Second step: The basic information is often prerequisite to allow to draw the reaction network, followed by construction of the reaction rate equations and make rough estimates of the kinetic parameters to be used as starting values in the parameter estimation. Besides open literature, information from comparable systems are important sources of information.
- 3. Funda- Create reaction network Previous slide Next slide Reactor model mentals Construct rate expressions Preferentially simple models Also: Dynamic operation Initial parameer estimates Thermo- Dynamics Kinetic Data bases Micro- kinetics Ab-initio methods Modelling: The next step is to set up your reactor model, based on the conservation of momentum, mass, and energy. In order to concentrate the effort on the reaction kinetics, these reactor models should be preferentially simple (i.e. ideally stirred tank or plug-flow reactor). Non-steady state operation may be considered to increase the amount of information about the reaction system.
- 4. Funda- Create reaction network Previous slide Next slide Reactor model mentals Construct rate expressions Preferentially simple models Also: Dynamic operation Initial parameer estimates Thermo- Dynamics Experimental data Kinetic (without transport limitations) Data bases Micro- kinetics Ab-initio methods Experimental work: After selecting a suitable test reactor and suitable test conditions at which one can exclude disturbing phenomena such as transport limitations, non-homogeneous flow distribution, and insufficient mixing can be excluded, a series of experiments should be carried out.
- 5. Funda- Create reaction network Previous slide Next slide Reactor model mentals Construct rate expressions Preferentially simple models Also: Dynamic operation Initial parameer estimates Thermo- Dynamics Parameter estimation Experimental data Kinetic (without transport limitations) Data bases _ Micro- + kinetics Ab-initio Reaction kinetics methods Parameter estimation: The unknown kinetic rate parameters are optimized to fit to the experimental data as well as possible using a suitable software package, which should also provide proper statistical information concerning the fit(s) obtained.
- 6. Funda- Create reaction network Previous slide Next slide Reactor model mentals Construct rate expressions Preferentially simple models Also: Dynamic operation Initial parameer estimates Thermo- Dynamics Parameter estimation New Experimental data Kinetic (without transport limitations) Data bases _ Micro- + kinetics Design of experiments for: 1) Model discrimination Ab-initio 2) Improving parameter Reaction kinetics estimates methods Improving the kinetics: In many cases the fit obtained with the initial set of experiments yields too unreliable kinetics. By using software suitable for (sequential) experimental design, you may determine the most suitable experimental conditions for additional experiments to facilitate model discrimination and to reduce the uncertainty ranges of the rate parameters.
- 7. Funda- Create reaction network Previous slide Next slide Reactor model mentals Construct rate expressions Preferentially simple models Also: Dynamic operation Initial parameer estimates Thermo- Dynamics Parameter estimation New Experimental data Kinetic (without transport limitations) Data bases _ Micro- + kinetics Design of experiments for: 1) Model discrimination Ab-initio 2) Improving parameter Reaction kinetics estimates methods Effects of uncertainties Translation to the production scale: An important but not easy step is to translate the remaining uncertainties in the kinetic model obtained to the uncertainty in the performance of the large-scale industrial reactor.