{
  "schema": "semiagora.process-simulation.v1",
  "experiment_id": "SA-PROC-FEOL-OXDIFF-001",
  "title": "Thermal oxidation and diffusion budget",
  "execution_mode": "precomputed-only",
  "model_boundary": "Educational front-end process replay. It is not a calibrated furnace recipe, TCAD deck, dopant-activation model, or facility process window.",
  "process": {
    "family": "front-end thermal processing",
    "methods": ["thermal oxidation", "dopant diffusion"],
    "nominal_temperature_c": 1000,
    "tracked_knobs": [
      "oxidation ambient",
      "furnace time",
      "silicon consumed by oxide growth",
      "diffusion drive-in time"
    ]
  },
  "oxidation": {
    "time_min": [5, 10, 20, 40, 80, 120],
    "silicon_consumption_factor": 0.46,
    "cases": [
      {
        "id": "dry-o2-teaching-curve",
        "label": "Dry O2 teaching curve",
        "oxide_thickness_nm": [12, 18, 28, 43, 65, 83],
        "silicon_consumed_nm": [5.5, 8.3, 12.9, 19.8, 29.9, 38.2],
        "note": "Slower, cleaner oxide-growth replay used to teach the time-to-thickness tradeoff."
      },
      {
        "id": "wet-o2-teaching-curve",
        "label": "Wet O2 teaching curve",
        "oxide_thickness_nm": [45, 72, 112, 174, 270, 350],
        "silicon_consumed_nm": [20.7, 33.1, 51.5, 80, 124.2, 161],
        "note": "Faster oxide-growth replay used to show why oxide thickness alone does not specify the process."
      }
    ]
  },
  "diffusion": {
    "drive_in_time_min": [10, 30, 60, 120],
    "lateral_sigma_nm": [35, 61, 86, 122],
    "junction_depth_nm": [85, 128, 170, 235],
    "note": "Square-root-like broadening replay for first-pass intuition. No point-defect or concentration-dependent diffusion is included."
  },
  "derived_metrics": {
    "dry_40_min_oxide_nm": 43,
    "wet_40_min_oxide_nm": 174,
    "wet_40_min_silicon_consumed_nm": 80,
    "drive_in_60_min_sigma_nm": 86,
    "public_claim": "Thermal steps must report both target thickness and consumed thermal budget."
  },
  "methods": [
    "Use saved oxide-thickness arrays to compare dry and wet ambient trends.",
    "Compute silicon consumed as 0.46 times oxide thickness for a teaching-level mass-balance marker.",
    "Use diffusion broadening as a square-root-of-time replay, not a calibrated dopant model.",
    "Keep oxidation and diffusion on the same page because real process flows accumulate thermal budget."
  ],
  "limitations": [
    "No Deal-Grove coefficients, furnace loading, initial oxide, doping-enhanced oxidation, stress, or bird's-beak geometry is modeled.",
    "No dopant species, dose, segregation, electric-field effects, transient enhanced diffusion, or activation physics is modeled.",
    "No recipe, facility setting, wafer qualification, or production process recommendation is implied.",
    "Measured ellipsometry, SIMS, furnace logs, and rights-clean process notes are required before calibrated claims."
  ],
  "sources": [
    {
      "label": "MIT OCW 6.774 readings",
      "url": "https://ocw.mit.edu/courses/6-774-physics-of-microfabrication-front-end-processing-fall-2004/pages/readings/",
      "use": "Public reading map for oxidation, Deal/Grove framing, Fick's laws, ion implantation, and annealing topics."
    },
    {
      "label": "MIT OCW 6.152J Micro/Nano Processing Technology",
      "url": "https://ocw.mit.edu/courses/6-152j-micro-nano-processing-technology-fall-2005/",
      "use": "Public course context for diffusion, oxidation, photolithography, CVD, and micro/nano fabrication techniques."
    }
  ]
}