Skip to content
Technology How it works Breeder — Hyperion Burner — Aegis Burner — MetroVolt AI-Native Architecture Magnets Fuel cycle Safety Roadmap
Solutions AI & Data Centers Defense & Government Grid & Baseload Neutron Detection Quantum
Learn Technical Library
Proof Publications Whitepapers Technical Library Open Science & Reproducibility The Honest Gates
Company About / Mission Leadership Environment Health & Safety Investors Careers Press Contact
3D Model
EHS › Fuel & Sustainability
Fuel & Sustainability

Tritium Breeding Ratio As A Design Lever

The tritium breeding ratio measures how much tritium a machine makes per unit consumed; the breeder studies it across values of 1.1, 1.5, and 1.8.

What the breeding ratio means

Deuterium-tritium fusion consumes tritium, which is not abundant in nature. A fusion plant must therefore breed its own tritium in a lithium blanket surrounding the plasma. The tritium breeding ratio (TBR) is the number of tritium atoms produced per tritium atom burned. A TBR above one means the plant makes more than it consumes.

Tritium breeding ratio treated as a design leverTBR 1.1 — near self-sufficientmodest marginTBR 1.5 — comfortable marginsupports fleet growthTBR 1.8 — strong marginfaster fuel accumulationTBR = tritium atoms produced per tritium atom consumed

Why it is treated as a lever, not a fixed number

The achievable TBR depends on blanket geometry, lithium enrichment, neutron multipliers, and how much of the neutron flux the structure captures. Rather than assert a single value, the breeder (Hyperion) design studies span 1.1, 1.5, and 1.8 to bracket the trade space. Higher ratios build a fuel surplus faster; lower ratios are easier to engineer.

Honest note

These are design-study values, not demonstrated blanket performance. Reconciling local versus net breeding is an open engineering question the program tracks explicitly. See tritium self-sufficiency and the neutron economy.

Why bracketing beats a single claim

Quoting one breeding ratio would imply a precision the physics does not yet support. By reporting a sweep across 1.1, 1.5, and 1.8, the design study makes its assumptions visible and lets each downstream conclusion be traced to a stated value. This honesty also foregrounds the key uncertainty — the gap between what is bred locally and what is delivered after losses — rather than hiding it inside a single confident number.

Content reviewed August 2026 · design-and-simulation stage