Enter your reaction, feedstock, and target spec. ReactorMind optimizes temperature, pressure, catalyst loading, and residence time for maximum yield — then predicts batch cycle time, energy cost, and runaway risk, grounded in real reaction engineering.
Pick your reaction and reactor on the left. The engine runs real reaction engineering — Arrhenius kinetics, van’t Hoff equilibrium, selectivity trade-offs, and thermal-stability analysis — and returns a complete reactor recipe.
Define the chemistry
Set your reaction parameters and hit Optimize reactor conditions.
| ConservativeSafe | OptimalAI pick | AggressiveMax output |
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Energy model assumes $0.12/kWh, a 25 °C feed, generic Cp ≈ 2.2 kJ/kg·K, and a refrigeration COP of 3 for heat removal. Estimates are derived from standard reaction-engineering correlations — validate against a heat-and-material balance before commissioning.
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A physics-aware optimizer that thinks like your best process engineer — and never forgets a hazard.
Temperature, pressure, catalyst loading, and residence time tuned to your exact reaction and reactor type for maximum yield.
Arrhenius kinetics and van’t Hoff equilibrium map conversion and selectivity across temperature to find the true yield optimum.
Charge, heat-up, reaction, cool-down, discharge, and CIP combine into a full batch cycle so you can plan capacity and quote lead times.
Heating, cooling duty, compression, and pumping resolve into a live specific-energy cost per kg so you can cut utility spend.
A HAZOP-style radar scores thermal runaway, overpressure, toxicity, and controllability — flagging hazards before the reactor does.
See conservative, optimal, and aggressive recipes side by side and pick the trade-off that fits the campaign.
Real reaction engineering, wrapped in a one-click workflow.
Reaction class, reactor type, feed purity, scale, priority, and cooling capacity — the same things you’d hand a process design package.
Arrhenius rate laws, van’t Hoff equilibrium, and selectivity trade-offs evaluate the full temperature and pressure window.
The engine trades conversion against selectivity, energy, and runaway margin to find the sweet spot for your plant.
A complete operating envelope with predicted yield, cycle time, energy cost, and a HAZOP risk profile — ready for the DCS.
Apprend Technologies brings AI-driven process optimization to chemical plants of every size. Lift yield, cut energy, and de-risk every campaign.
Sign in to your plant workspace
Skip — sign in as a demo role
Demo site — any username and password will work.
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