The operation method of a continuous biological reaction simulator needs to be combined with its working principle and core control parameters, covering four stages: start-up preparation, parameter setting, operation monitoring, and termination processing, and achieving stable operation through mathematical modeling and dynamic adjustment. The following are specific operating methods and key points:
1、 Start preparation phase
Equipment inspection and cleaning
Ensure that the reactor body, sensors, controllers, feeding devices, and other equipment are securely installed without any risk of leakage.
Clean the inside of the reactor to avoid pollutants interfering with the experimental results. For example, in microbial cultivation, residual impurities may lead to microbial contamination or metabolic abnormalities.
Preparation of reactants
Configure culture medium, nutrients, buffer solution, etc. according to experimental requirements, and confirm their quality and concentration. For example, in continuous fermentation, it is necessary to precisely control the ratio of carbon and nitrogen sources to maintain microbial growth balance.
If microbial inoculation is involved, it is necessary to activate the strain in advance and adjust it to the logarithmic growth stage to ensure that the initial bacterial concentration meets the requirements.
Environmental condition control
Set basic parameters such as reactor temperature, pH value, dissolved oxygen, etc. For example, mammalian cell culture typically requires maintenance at 37 ℃ pH7.2-7.4、 Dissolved oxygen 5% -10%.
Start the stirring device to ensure that the reactants are mixed evenly and avoid local concentrations that are too high or too low.
2、 Parameter setting and dynamic adjustment stage
Key parameter setting
Flow control: Calculate the feed flow rate (F=V/τ) based on the reactor volume (V) and residence time (τ). For example, if a 10L reactor takes 10 hours to process the material, the flow rate is set to 1L/h.
Dilution rate (D) adjustment: Control cell growth rate by adjusting the ratio of feed flow rate to reactor volume (D=F/V). For example, D=0.1h ⁻¹ means replacing 10% of the reaction solution every hour.
Temperature and pH feedback control: Maintain the set value using a PID controller. For example, when the pH deviates from the target value, an acid/alkali solution is automatically injected for calibration.
Mathematical Model Assisted Optimization
Establish a material balance model, such as the matrix concentration equilibrium equation for a single-stage CSTR.
Optimize operating conditions by fitting parameters such as reaction rate constant (k) and maximum reaction rate through experimental data.
Multi level series and loop design
For complex reactions such as multi-stage fermentation, multi-stage CSTR series or cyclic PFR (push flow reactor) can be used to improve conversion rate. For example, a two-stage series reactor can increase product yield by 30% -50%.
In cyclic PFR, the residence time distribution of reactants is controlled by adjusting the cycle ratio to reduce backmixing effects.
3、 Operation monitoring and data collection stage
Real time parameter monitoring
Using sensors to continuously record temperature pH、 Dissolved oxygen, pressure and other key indicators, and generate trend charts through data acquisition systems such as PLC or SCADA.
Regularly sample and analyze reactant concentration, cell density, product generation, etc. to verify the accuracy of model predictions.
Exception handling and adjustment
If parameters deviate from the set range (such as a sudden drop in pH or insufficient dissolved oxygen), immediately check the status of the feeding system, mixing device, or sensor, and manually intervene and adjust.
In continuous cultivation, if the growth rate of bacterial cells decreases, growth can be stimulated by increasing the concentration of nutrients in the feed or adjusting the dilution rate.
4、 Termination processing and data analysis phase
Reaction termination operation
Determine the termination timing based on the experimental objectives, such as achieving a specific product concentration or reaction time.
Turn off the feed pump, stirring device, and temperature control system, discharge the reaction solution, and perform subsequent treatments such as centrifugation, filtration, and purification.
Data organization and model validation
Summarize operational data, plot curves of reactant concentration and product generation over time, and analyze reaction kinetics characteristics.
Compare experimental data with model predictions and adjust parameters such as reaction rate constants and mass transfer coefficients to improve model accuracy.