Calculator Inputs
Use the grid below to test operating ranges, economic assumptions, and weighting priorities for a chemistry process optimization study.
Example Data Table
| Scenario | Temperature (°C) | pH | Catalyst (%) | Reaction Time (min) | Mixing Rate (rpm) | Yield Goal (%) |
|---|---|---|---|---|---|---|
| Lab Batch A | 70 | 6.0 | 1.5 | 90 | 220 | 84 |
| Lab Batch B | 76 | 6.3 | 2.0 | 120 | 250 | 89 |
| Pilot Trial C | 80 | 6.5 | 2.5 | 140 | 280 | 92 |
| Pilot Trial D | 86 | 6.8 | 3.0 | 150 | 300 | 90 |
Formula Used
This calculator uses a weighted search model across temperature, pH, and catalyst dosage. It evaluates every tested combination and keeps the best objective score.
Predicted Yield
Yield = 92 − 0.075(T − Topt)2 − 3.6(pH − pHopt)2 − 0.52(C − Copt)2 + 2.2 ln(time + 1) + 0.011 × mixing
Predicted Purity
Purity = 97.8 − 0.032(T − Topt)2 − 1.35(pH − pHopt)2 − 0.21(C − Copt)2 + 0.004 × mixing
Energy Use
Energy = 0.14|T − 25| + 0.018 × mixing + 0.09 × time + 0.03 × catalyst
Process Cost
Cost = raw material cost + (energy × energy cost) + 0.42 × catalyst + 0.08 × time
Objective Score
Objective = (Yield Weight × Yield) + (Purity Weight × Purity) − (Cost Weight × Cost) − (Energy Weight × Energy)
The solver selects the combination with the highest objective score. Squared terms penalize conditions that move away from target operating values.
How to Use This Calculator
- Enter minimum, maximum, and step values for temperature.
- Enter pH limits and catalyst dosage range.
- Set reaction time, mixing rate, and cost assumptions.
- Adjust the weights for yield, purity, cost, and energy.
- Enter reference optimum points from lab or pilot data.
- Click Solve Optimization to rank all tested conditions.
- Review the best solution, top results, and graph.
- Export the displayed table as CSV or PDF.
FAQs
1. What does this chemistry optimization solver do?
It tests many operating combinations and ranks them by one objective score. The score rewards yield and purity, then penalizes cost and energy use.
2. Is this suitable for real plant design?
It is best for screening and comparison. Use plant data, kinetics, safety limits, and engineering review before applying any final operating conditions.
3. Why are reference optimum values needed?
They act like target centers in the response model. Conditions farther away usually receive lower predicted yield and purity values.
4. What happens if I increase weight for cost?
Higher cost weight makes the solver prefer cheaper conditions. That can reduce the final temperature, catalyst level, or operating intensity.
5. Can I use this for catalyst screening?
Yes, for simple comparative screening. Treat catalyst percentage as a decision variable and compare how objective score changes across tested ranges.
6. Why does the graph use top-ranked solutions?
Top solutions are easier to compare visually. They highlight the strongest tradeoffs without clutter from many lower-performing combinations.
7. Does the calculator use exact chemical kinetics?
No. It uses a practical response-style optimization model. Replace coefficients with validated experimental values for deeper technical work.
8. What export options are included?
You can download the ranked result table as CSV or PDF. Both exports use the values currently displayed on the page.