"""
Fusion Energy Progress Monitor (Roadmap #392)
Tracks fusion energy R&D milestones, funding, and company progress
toward commercial fusion power generation using public data sources.
"""
import json
from datetime import datetime, timedelta
from typing import Dict, List, Optional
# Major fusion projects and their public milestones
FUSION_PROJECTS = {
"ITER": {
"type": "tokamak",
"location": "Cadarache, France",
"status": "under_construction",
"target_first_plasma": "2035",
"budget_bn_usd": 22.0,
"members": ["EU", "US", "China", "India", "Japan", "Korea", "Russia"],
"url": "https://www.iter.org"
},
"Commonwealth Fusion Systems": {
"type": "compact_tokamak",
"location": "Devens, MA, USA",
"status": "development",
"funding_raised_bn": 2.0,
"reactor": "SPARC",
"target_demo": "2028",
},
"TAE Technologies": {
"type": "field_reversed_config",
"location": "Foothill Ranch, CA, USA",
"status": "development",
"funding_raised_bn": 1.2,
},
"Helion Energy": {
"type": "field_reversed_config",
"location": "Everett, WA, USA",
"status": "development",
"funding_raised_bn": 0.6,
"target_demo": "2028",
},
"General Fusion": {
"type": "magnetized_target",
"location": "Richmond, BC, Canada",
"status": "development",
"funding_raised_bn": 0.3,
},
"Tokamak Energy": {
"type": "spherical_tokamak",
"location": "Oxfordshire, UK",
"status": "development",
"funding_raised_bn": 0.25,
},
"Zap Energy": {
"type": "z_pinch",
"location": "Everett, WA, USA",
"status": "development",
"funding_raised_bn": 0.2,
},
"NIF (National Ignition Facility)": {
"type": "inertial_confinement",
"location": "Livermore, CA, USA",
"status": "research",
"milestone": "Net energy gain achieved Dec 2022",
},
}
FUSION_APPROACHES = {
"tokamak": {"description": "Magnetic confinement using toroidal chamber", "maturity": "highest"},
"stellarator": {"description": "Twisted magnetic confinement", "maturity": "high"},
"inertial_confinement": {"description": "Laser-driven implosion", "maturity": "high"},
"compact_tokamak": {"description": "High-field compact magnetic confinement", "maturity": "medium"},
"field_reversed_config": {"description": "Self-organized plasma confinement", "maturity": "medium"},
"magnetized_target": {"description": "Hybrid magnetic-inertial", "maturity": "medium"},
"spherical_tokamak": {"description": "Compact spherical geometry", "maturity": "medium"},
"z_pinch": {"description": "Axial current pinch confinement", "maturity": "low"},
}
def get_fusion_landscape() -> Dict:
"""
Get overview of the global fusion energy landscape including
all tracked projects, approaches, and aggregate funding.
"""
total_private_funding = sum(
p.get("funding_raised_bn", 0) for p in FUSION_PROJECTS.values()
)
approaches_count = {}
for proj in FUSION_PROJECTS.values():
t = proj.get("type", "unknown")
approaches_count[t] = approaches_count.get(t, 0) + 1
return {
"total_projects_tracked": len(FUSION_PROJECTS),
"total_private_funding_bn_usd": round(total_private_funding, 2),
"approaches_distribution": approaches_count,
"approach_details": FUSION_APPROACHES,
"projects": {k: v for k, v in FUSION_PROJECTS.items()},
"as_of": datetime.utcnow().isoformat(),
}
def get_project_detail(project_name: str) -> Optional[Dict]:
"""
Get detailed info on a specific fusion project by name (case-insensitive partial match).
"""
for name, data in FUSION_PROJECTS.items():
if project_name.lower() in name.lower():
return {"name": name, **data}
return None
def estimate_fusion_timeline() -> Dict:
"""
Estimate commercial fusion timeline based on current project targets
and historical milestone pace.
"""
milestones = [
{"year": 1958, "event": "First tokamak concept (Sakharov/Tamm)"},
{"year": 1968, "event": "T-3 tokamak plasma temperature record"},
{"year": 1997, "event": "JET 16MW fusion power record"},
{"year": 2022, "event": "NIF achieves net energy gain (ignition)"},
{"year": 2025, "event": "Multiple private companies targeting demo reactors"},
]
targets = []
for name, proj in FUSION_PROJECTS.items():
if "target_demo" in proj:
targets.append({"project": name, "demo_target": proj["target_demo"]})
if "target_first_plasma" in proj:
targets.append({"project": name, "first_plasma_target": proj["target_first_plasma"]})
return {
"historical_milestones": milestones,
"upcoming_targets": targets,
"estimated_first_commercial": "2035-2045",
"key_challenges": [
"Plasma containment stability at scale",
"Tritium breeding and supply chain",
"Material science (neutron-resistant first wall)",
"Regulatory framework for fusion power plants",
"Cost competitiveness with renewables + storage",
],
}
def fusion_investment_summary() -> Dict:
"""
Summarize private and public fusion energy investment trends.
"""
private = []
for name, proj in FUSION_PROJECTS.items():
if "funding_raised_bn" in proj:
private.append({
"company": name,
"funding_bn_usd": proj["funding_raised_bn"],
"approach": proj.get("type", "unknown"),
})
private.sort(key=lambda x: x["funding_bn_usd"], reverse=True)
return {
"private_sector": private,
"total_private_bn": round(sum(p["funding_bn_usd"] for p in private), 2),
"major_public_programs": [
{"name": "ITER", "budget_bn_usd": 22.0, "members": 7},
{"name": "NIF/LLNL", "budget_bn_usd": 3.5, "country": "US"},
{"name": "Wendelstein 7-X", "budget_bn_usd": 1.1, "country": "Germany"},
{"name": "JT-60SA", "budget_bn_usd": 0.6, "country": "Japan/EU"},
],
"trend": "Private fusion investment accelerating since 2020, >$6B cumulative by 2025",
}
