Bridging the Chasm: From Scientific Gain to Commercial Fusion Power

Fusion gain is a milestone in plasma physics, but commercial electricity requires a favorable balance across an entire plant and its operating life. This selective technical synthesis separates plasma gain, laser-target gain, gross electrical gain, net electrical output, and economic performance. An explicit power balance shows how heating efficiency, recoverable heat, and auxiliary consumption set different gain requirements. In a deliberately simplified example with 40% thermal conversion, 40% heating efficiency, no credit for recovered heating, and auxiliary demand equal to 2% of fusion power, net electrical break-even occurs at plasma gain 6.58; a gross-to-recirculating electrical ratio of ten requires gain 125. Neither number is a universal reactor requirement. Recovering injected heating changes these values, and fixed auxiliary loads impose a gain ceiling even at ignition. Dated experimental milestones are distinguished from design targets. The engineering discussion connects confinement and control to heat exhaust, neutron damage, tritium self-sufficiency, maintainability, and cost. A compact model, generated scenarios, and figures make the accounting reproducible without implying a validated reactor simulation or a cost forecast. Commercial fusion must demonstrate useful net electricity, a closed operational fuel cycle, replaceable components, and economic performance together; no single gain record can establish all four. Scope and reproducibility: Selective technical synthesis with illustrative, uncalibrated power-accounting calculations. No new experimental measurements, validated reactor simulation, or commercial cost forecast is reported. The accompanying archive contains LaTeX/Markdown sources, calculation code, 54 generated scenarios, figures, and a claim audit. Not peer reviewed. Assistance disclosure: The supplied draft names Google Antigravity as its AI synthesis instrument. ChatGPT assisted the revision, literature checking, calculations and formatting. Mayone Maha Rajan is the author and accepts responsibility for the release. AI tools are not authors. No external endorsement is claimed.