Reactant tokens (grey dots) stream into the central reactor from the top lane. Each one is converted deterministically — using the exact fraction set by the sliders, not a random per-atom coin flip like a 3D scatter — into product (green, exits right into the collection ring) or waste by-product (orange/red, drains left into the waste tank). Atom economy is the fraction of reactant mass that ends up in the wanted product; the green route raises the ceiling on how high that fraction can climb for the same slider value. Catalyst loading lowers the activation barrier, cutting both side-reactions and the energy needed to drive the reaction. Solvent hazard is independent of the reaction split — a hazardous solvent adds extra mass straight to the waste tank even at perfect atom economy, since it must eventually be disposed of or recovered.
atom economy = mass(product) / mass(all reactants) ×100%
E-factor = mass(waste) / mass(product) (ideal green chemistry → 0)
waste fraction = (1 − economy)·(1 − 0.5·catalyst)·routeMul + solvent_hazard·k
routeMul = 0.55 (green route) or 1.0 (traditional)
- Traditional vs green route — the green route caps the waste fraction lower and needs less energy for the same atom economy, modelling a redesigned synthesis with fewer steps.
- E-factor trend chart — plots the running E-factor every second so you can watch it settle as the reactor reaches steady state after you change a slider.
- Route-compare bar — a live stacked bar showing the product/waste split of everything processed so far in this route, updated token by token.
- E-factor — the standard green-chemistry metric: kilograms of waste per kilogram of product. Pharmaceutical manufacturing often runs 25–100+; the target of green chemistry is to push it toward 0.
Real-world relevance: pharmaceutical and fine-chemical manufacturers redesign routes for exactly this reason — a higher atom economy and a benign solvent cut disposal costs and environmental impact even when the product yield looks similar on paper.