Bioreactor Simulator
How to use: pick a mode and organism, set the kinetics, then press Run to watch the culture grow in real time. Dragging any slider re-runs instantly. Built on the Monod model with RK4 integration.
Organism preset
Growth kinetics
μmax (h⁻¹)0.60
Ks (g/L) ?0.05
Yx/s (g/g)0.45
Reactor
Initial substrate S0 (g/L)20
Inoculum X0 (g/L)0.05
Options
Speed
DO Batch
0.0
X (g/L)
0.0
S (g/L)
0.00
μ (h⁻¹)
100
DO (%)
0.0
time (h)
Press Run to start the culture.

A live bioreactor simulator, not a static calculator

This bioreactor simulator integrates the Monod growth model in real time so you can watch a fermentation unfold rather than read off a single number. The core is the unstructured mass-balance system dX/dt = μX, dS/dt = −μX/Yx/s, with μ = μmax·S/(Ks+S), solved with a fourth-order Runge–Kutta (RK4) scheme entirely in your browser. Optional terms add Haldane substrate inhibition, Luedeking–Piret product formation and dissolved-oxygen limitation, so the same engine covers a wide range of teaching scenarios.

Switch between batch, fed-batch and chemostat modes to see how operating strategy changes the outcome. In batch the culture grows until substrate is exhausted; in fed-batch an exponential μ-setpoint feed keeps biomass accumulating; in chemostat the dilution rate sets the steady-state growth rate, and pushing it past the critical dilution rate produces washout. The steady-state and productivity curves reveal the operating point that maximises volumetric productivity. As biomass climbs, the dissolved-oxygen gauge falls and growth becomes oxygen-limited — the same ceiling that real vessels hit, set by kLa.

For the point calculations behind this simulator, pair it with the Monod kinetics calculator and the growth curve fitter; for the oxygen side, predict transfer with the OTR & kLa estimator and watch the gassing-out measurement in the kLa simulator; and plan feeding with the fed-batch calculator.

Further reading

Related Tools & Articles

Monod Kinetics Calculator
Compute specific growth rate from µmax, Ks and substrate.
Growth Curve Fitter
Fit µmax and lag from your OD/biomass time series.
kLa Simulator
Dynamic gassing-out and oxygen transfer, animated.
Fed-Batch Calculator
Design exponential feed profiles for your fermentation.

Frequently Asked Questions

What is the Monod model in a bioreactor simulator?

The Monod model relates specific growth rate to the limiting substrate: μ = μmax·S/(Ks+S). Coupled with dX/dt = μX and dS/dt = −μX/Yx/s it reproduces the classic batch growth curve. This simulator integrates that system in real time with RK4 and animates the vessel, so you can see how μmax, Ks and yield shape the trajectory.

Batch vs fed-batch vs chemostat?

Batch adds nothing: cells grow until substrate runs out. Fed-batch feeds substrate over time (constant or exponential) so biomass keeps accumulating and volume rises. Chemostat flows medium in and culture out at rate D; at steady state μ = D, and above the critical dilution rate the culture washes out. This simulator runs all three on the same kinetics.

What is washout in a chemostat?

Washout is when cells leave the vessel faster than they grow, so biomass falls to zero. At steady state D = μ, and since μ cannot exceed μmax, raising D above Dcrit = μmax·SF/(Ks+SF) washes the culture out. The productivity curve (D·X) peaks below Dcrit — that peak is the best continuous operating point.

How does dissolved-oxygen limitation work here?

As biomass rises, oxygen uptake (OUR = qO2·X) climbs toward the transfer ceiling and DO falls. When DO drops, growth is scaled by an oxygen Monod term DO/(KO2+DO), so the culture self-limits — the same density ceiling real vessels hit, set by kLa. Predict your kLa with the OTR & kLa estimator.

Is it accurate enough for process design?

It is a teaching and exploration tool built on unstructured Monod-family kinetics with representative literature parameters. It captures the qualitative behaviour and trade-offs very well, but it is not a validated organism-specific digital twin — real design needs parameters fitted to your strain and medium and, for cases like E. coli acetate overflow or CHO multi-substrate metabolism, organism-specific models. Use it to build intuition and screen scenarios.