Overview

General comment

Production covered

Silicon-carbide power wafer: a boule grown by physical vapor transport, sliced and epitaxially finished, then implanted, gate-oxidized and metallized. This variant represents fabrication at ST Catania / Infineon SiC (EU proxy) using Germany grid electricity.

This dataset represents operation with moderate PFC gas recovery and moderate water recycling.

Modelling choices

Support energy is allocated using 5,000 wafer starts per month. That capacity represents one fab phase or production module at a high-volume site, not the combined output of a multi-phase campus.

Gas abatement (POU + central scrubber) is allocated as a flat per-wafer facility charge, not scaled per etch/CVD pass.

Scope in detail

Operational scenario scope: the scenario changes fluorinated-gas emissions to air (SF6, CF4, C4F8, CHF3 and the CF4/COF2/SO2F2 abatement byproducts that scale on destroyed mass), the NET purchased quantity of the two gases wired to recovery on the purchase side rather than the emission side (neon, and EUV-lithography hydrogen where the process carries EUV passes - which is why those two purchase rows move between scenario cells), and fresh-water intake and wastewater. It does not change NF3, whose remote-plasma clean consumes the large majority of the charge inside the chamber, so the industry control is abatement of the small residue rather than recovery; nor the cryogenic HF/PF3 etch feeds, which are scrubbed rather than captured; nor any in-chamber reaction product. The utilisation and recovery fractions behind those statements are stated with the scenario definition that this dataset's name carries.

Manufacturing-region scope: the regional options of this family swap the electricity market this dataset draws from, and the regional supplier entry for those few upstream chemicals and gases whose supplier data is published by region. They change nothing else. Facility heating, ventilation and cooling energy stays on the region the process data was built for, so per-unit energy is the same across the regional options; water, process chemicals, gases, materials, process emissions and solid waste are the same as well. Every inventory row of these regional datasets is therefore expected to match. What the separate datasets carry is the background market each region draws on.

Technology: SiC 150mm, wide bandgap
Geography: Representative region: Germany (EU proxy for the Wolfspeed US / ST Italy / Infineon Austria SiC mix; per-technology region). A United States option (US-RFC, Wolfspeed Mohawk Valley class) ships as a separate dataset.

Terms used above

PFC perfluorinated compounds; in power-supply contexts, power-factor correction
POU point of use

System boundary

The figure groups this dataset's unit processes by class. It is not a count of manufacturing steps — each process runs over as many passes as the flow requires, and those pass counts ship with the dataset.

Download this figure (SVG)

Data quality and references

Composite DQI 2.4 Good

Reliability

2.9

Completeness

2.5

Temporal

2.2

Geographic

2.0

Technological

2.7

How the score is calculated: Sources used across more manufacturing steps have more influence. Sources that define assumptions for the whole model account for 63.3% of the total weighting.

Pedigree scores follow the ecoinvent data-quality matrix: 1 is the best attainable, 5 the weakest. The composite is their aggregate.

Sampling procedure: Component vendor specifications, academic papers, industry literature
Coverage status: Partial
Pedigree-scored source files: 13 — the source records behind this dataset's manufacturing operations. Each carries the five pedigree axes above; the composite DQI aggregates them.

Technosphere inputs

14 flows. Quantities are not published; they ship with the dataset on Circa.

Water supply (municipal) Waterm3

Derivation basis: Calculated from process-water and ultrapure-water demand across all manufacturing operations, plus facility water allocated to each finished unit. The fresh intake shown is that demand less the share reused under the water-recycling scenario this dataset assumes, and wastewater follows the same balance.

No source is attached to this row.
Source citations: Not stated
Upstream REEL dataset: Water Supply (Municipal)
Background dataset: Modelled by REEL; see the upstream dataset above.
Notes: Net fresh-water intake, supplied as municipal water
Uncertainty: A minimum-maximum range is defined for this flow. Bounds ship with the dataset on Circa.
Unit: m3

Electricity, Germany (DE) ElectricitykWh · -11.7% / +13%

Derivation basis: Calculated from equipment energy across all manufacturing operations, plus facility support such as cleanroom HVAC, ultrapure water, cooling, gas abatement, and bulk gases.

The sources below come from the manufacturing operations behind this row.
Sources (inherited): Inherited, rolled up from the contributing process steps:

IAAM and PMC thermal field optimization

Compound Semiconductor and Orbit & Skyline

Orbit & Skyline and MDPI SiC growth

IAAM SiC powder source study

Power Electronics News and PMC

CAE Online: Teradyne Catalyst Specifications

EE Journal: "Advantest Unveils New Ultra-High-Current Power Supply" (2024)

4Semi: TEL Precio Wafer Prober Specifications

FormFactor Summit 11000/12000 Facility Planning Guide

3D InCites: "ERS Electronic Introduces High Power Dissipation Thermal Chuck" (2023)

Abachy: "How Much Energy and Water Are Required for Wafer Fabrication" (2025)

Veeco LSA specifications and MDPI study

MDPI Photonics - 'Laser Annealing of Si Wafers Based on a Pulsed CO2 Laser', Photonics 2025, 12(4), 359

Applied Materials Vantage Astra and SPIE study
Background data: ecoinvent 3.12
Background dataset: electricity, high voltage
Uncertainty: -11.7% / +13% around the published quantity. The bounds themselves ship with the dataset on Circa.
Unit: kWh

Ar Process gasg

Derivation basis: Calculated from per-operation consumption, operation counts, and manufacturing yield.

No source is attached to this row.
Source citations: Not stated
Background data: ecoinvent 3.12
Background dataset: argon, liquid
Uncertainty: A minimum-maximum range is defined for this flow. Bounds ship with the dataset on Circa.
Unit: g

SiH₄ Process gasg · -40% / +60%

Derivation basis: IAAM and Orbit & Skyline SiC growth studies

The sources for this row are listed below.
Source citations: IAAM and PMC thermal field optimization
Compound Semiconductor and Orbit & Skyline
Orbit & Skyline and MDPI SiC growth
IAAM SiC powder source study
Power Electronics News and PMC
Background data: ecoinvent 3.12
Background dataset: silicon tetrahydride
Uncertainty: -40% / +60% around the published quantity. The bounds themselves ship with the dataset on Circa.
Unit: g

C₃H₈ Process gasg · -33.3% / +66.7%

Derivation basis: IAAM and Orbit & Skyline SiC growth studies

The sources for this row are listed below.
Source citations: IAAM and PMC thermal field optimization
Compound Semiconductor and Orbit & Skyline
Orbit & Skyline and MDPI SiC growth
IAAM SiC powder source study
Power Electronics News and PMC
Background data: ecoinvent 3.12
Background dataset: propane
Uncertainty: -33.3% / +66.7% around the published quantity. The bounds themselves ship with the dataset on Circa.
Unit: g

H₂ Process gasg · -25% / +50%

Derivation basis: IAAM and Orbit & Skyline SiC growth studies

The sources for this row are listed below.
Source citations: IAAM and PMC thermal field optimization
Compound Semiconductor and Orbit & Skyline
Orbit & Skyline and MDPI SiC growth
IAAM SiC powder source study
Power Electronics News and PMC
Background data: ecoinvent 3.12
Background dataset: hydrogen, gaseous, low pressure
Uncertainty: -25% / +50% around the published quantity. The bounds themselves ship with the dataset on Circa.
Unit: g

N₂ Process gasg

Derivation basis: Most of this quantity is a facility nitrogen allocation rather than an operation-by-operation consumption: a per-wafer base rate for a reference fab capacity is rescaled to this model's assumed capacity through a sub-linear power law, and only the smaller per-lithography-pass and per-etch/CVD-pass purge terms follow the process flow. The base rate and the exponent are modelling estimates with no published derivation, so two models at the same technology node and wafer size can differ on this row by more than their process flows do. The uncertainty interval shown covers the per-pass terms; the facility base is a point estimate and carries none.
IAAM and Orbit & Skyline SiC growth studies

The sources for this row are listed below.
Source citations: IAAM and PMC thermal field optimization
Compound Semiconductor and Orbit & Skyline
Orbit & Skyline and MDPI SiC growth
IAAM SiC powder source study
Power Electronics News and PMC
Veeco LSA specifications and MDPI study
MDPI Photonics - 'Laser Annealing of Si Wafers Based on a Pulsed CO2 Laser', Photonics 2025, 12(4), 359
Applied Materials Vantage Astra and SPIE study
Background data: ecoinvent 3.12
Background dataset: nitrogen, liquid
Uncertainty: A minimum-maximum range is defined for this flow. Bounds ship with the dataset on Circa.
Unit: g

O₂ Process gasg · -1.5% / +4.5%

Derivation basis: Calculated from per-operation consumption, operation counts, and manufacturing yield.

No source is attached to this row.
Source citations: Not stated
Background data: ecoinvent 3.12
Background dataset: oxygen, liquid
Uncertainty: -1.5% / +4.5% around the published quantity. The bounds themselves ship with the dataset on Circa.
Unit: g

H₂O Process gasg · -50% / +100%

Source citations: patents.google.com (date not recorded). US 2007/0207627 A1, "Reducing nitrogen concentration with in-situ steam generation" (ProMOS Technologies).
Background data: ecoinvent 3.12
Background dataset: water, deionised
Uncertainty: -50% / +100% around the published quantity. The bounds themselves ship with the dataset on Circa.
Unit: g

HCl Process gasg · -50% / +150%

Derivation basis: Calculated from per-operation consumption, operation counts, and manufacturing yield.

No source is attached to this row.
Source citations: Not stated
Background data: ecoinvent 3.12
Background dataset: hydrochloric acid, without water, in 30% solution state
Uncertainty: -50% / +150% around the published quantity. The bounds themselves ship with the dataset on Circa.
Unit: g

Compressed air Process gasg · ±33.3%

Source citations: CAE Online: Teradyne Catalyst Specifications
EE Journal: "Advantest Unveils New Ultra-High-Current Power Supply" (2024)
4Semi: TEL Precio Wafer Prober Specifications
FormFactor Summit 11000/12000 Facility Planning Guide
3D InCites: "ERS Electronic Introduces High Power Dissipation Thermal Chuck" (2023)
Abachy: "How Much Energy and Water Are Required for Wafer Fabrication" (2025)
Background data: ecoinvent 3.12
Background dataset: compressed air, 700 kPa gauge
Uncertainty: ±33.3% around the published quantity. The bounds themselves ship with the dataset on Circa.
Unit: g

Graphite Crucible Materialg

Derivation basis: Calculated from per-operation consumption, operation counts, and manufacturing yield.

No source is attached to this row.
Source citations: Not stated
Background data: ecoinvent 3.12
Background dataset: graphite
Uncertainty: No range defined.
Unit: g

Aluminium (p-type ion-source charge) Process chemicalg · -50% / +150.1%

Derivation basis: Atom-for-atom substitution on the parent silicon ion-implant process record's p-type dopant supply

No source is attached to this row.
Source citations: Not stated
Background data: proxy-mapped
Background dataset: aluminium, cast alloy
Uncertainty: -50% / +150.1% around the published quantity. The bounds themselves ship with the dataset on Circa.
Unit: g

Silicon carbide source powder (PVT feedstock) Materialg · ±2%

Source citations: iopscience.iop.org (date not recorded). Nakamura and Nishizawa, Reconstruction of physical-vapor-transport SiC growth setup for large crystal height, Applied Physics Express 18 (2025) 105501.
sanan-ic.com (date not recorded). San'an 150 mm 4H-N Type SiC Substrate Preliminary Specification.
Background data: proxy-mapped
Background dataset: silicon carbide
Uncertainty: ±2% around the published quantity. The bounds themselves ship with the dataset on Circa.
Unit: g

Outputs and waste

Wastewater Wastewaterm3

Derivation basis: Calculated from the water balance: fresh-water input minus evaporation.

No source is attached to this row.
Source citations: Not stated
Background data: carried, no background dataset
Background dataset: No treatment route recorded for this output.
Uncertainty: A minimum-maximum range is defined for this flow. Bounds ship with the dataset on Circa.
Unit: m3

Silicon Carbide Dust (kerf) Solid wasteg

Derivation basis: Calculated from the mass balance of spent materials and consumables, with treatment selected from the waste classification.

No source is attached to this row.
Source citations: Not stated
Background data: ecoinvent 3.12 treatment route
Background dataset: treatment of inert waste, sanitary landfill
Uncertainty: No range defined.
Unit: g

Scrapped wafers (line yield) Solid wasteg · -72.2% / +58.8%

Derivation basis: Line-yield reject of the geometry-derived finished-wafer mass

No source is attached to this row.
Source citations: Not stated
Background data: ecoinvent 3.12 treatment route
Background dataset: treatment of inert waste, sanitary landfill
Uncertainty: -72.2% / +58.8% around the published quantity. The bounds themselves ship with the dataset on Circa.
Unit: g

Crucible (graphite) Solid wasteg

Derivation basis: Calculated from the mass balance of spent materials and consumables, with treatment selected from the waste classification.

No source is attached to this row.
Source citations: Not stated
Background data: ecoinvent 3.12 treatment route
Background dataset: treatment of inert waste, sanitary landfill
Uncertainty: No range defined.
Unit: g

Intact un-eroded sputter target body (Ni) Solid wasteg · -33.3% / +66.7%

Source citations: Methods of rejuvenating sputtering targets - H.C. Starck Inc
materion.com (date not recorded). Enhance Your Sputter Deposition Yield With The Materion Approach.
materion.com (date not recorded). Sputtering Target Recycling Solutions at Materion. Vendor web page.
Background data: ecoinvent 3.12 treatment route
Background dataset: material recovery (material dependent - typically recycled)
Uncertainty: -33.3% / +66.7% around the published quantity. The bounds themselves ship with the dataset on Circa.
Unit: g

Spent sputter targets (Ni) Solid wasteg · -44.5% / +44.4%

Source citations: Methods of rejuvenating sputtering targets - H.C. Starck Inc
materion.com (date not recorded). Enhance Your Sputter Deposition Yield With The Materion Approach.
materion.com (date not recorded). Sputtering Target Recycling Solutions at Materion. Vendor web page.
Background data: ecoinvent 3.12 treatment route
Background dataset: material recovery (material dependent - typically recycled)
Uncertainty: -44.5% / +44.4% around the published quantity. The bounds themselves ship with the dataset on Circa.
Unit: g

Emissions to air

3 elementary flows released to air by this dataset's own operations. Quantities are not published; they ship with the dataset on Circa.

H₂O Emission to airg

Source citations: patents.google.com (date not recorded). US 2007/0207627 A1, "Reducing nitrogen concentration with in-situ steam generation" (ProMOS Technologies).
Compartment: Air (non-urban air or from high stacks)
CAS number: 7732-18-5
ecoinvent 3.12 elementary flow: Water
Uncertainty: A minimum-maximum range is defined for this flow. Bounds ship with the dataset on Circa.
Unit: g

HCl Emission to airg

Derivation basis: Calculated as an air release, from a mass balance on the process gases going in, with the destruction or removal efficiency of any point-of-use abatement applied.

No source is attached to this row.
Source citations: Not stated
Compartment: Air (non-urban air or from high stacks)
CAS number: 7647-01-0
ecoinvent 3.12 elementary flow: Hydrochloric acid
Uncertainty: A minimum-maximum range is defined for this flow. Bounds ship with the dataset on Circa.
Unit: g

Carbon dioxide, fossil Emission to airg

Derivation basis: This flow is a byproduct of the manufacturing operation. The model reads it from the operation's own inventory rather than deriving it from this dataset's own balance of process gases.

The sources for this row are listed below.
Source citations: arxiv.org (date not recorded). A comparative study of SiC epitaxial growth in vertical hotwall CVD reactor using silane and dichlorosilane precursor gases.
epa.gov (date not recorded). Electronics Manufacturing - Subpart I, Greenhouse Gas Reporting Program. PDF document.
tekvac.com (date not recorded). Burnbox & Scrubber.
idealvac.com (date not recorded). Exhaust Management for Semiconductor Processes. PDF document.
Compartment: Air (non-urban air or from high stacks)
Formula: CO₂
CAS number: 124-38-9
ecoinvent 3.12 elementary flow: Carbon dioxide, fossil
Uncertainty: A minimum-maximum range is defined for this flow. Bounds ship with the dataset on Circa.
Unit: g

Emissions to water

1 elementary flow released to water by this dataset's own operations. Quantities are not published; they ship with the dataset on Circa.

Cl- Emission to waterg

Source citations: pca.state.mn.us (date not recorded). Minnesota Pollution Control Agency, Alternatives for addressing chloride in wastewater effluent, wq-wwprm2-18, December 2018 - chloride conservative through conventional treatment; MN WQS 230 chronic / 860 acute mg/L. Government report.
Compartment: Water (surface water)
CAS number: 16887-00-6
ecoinvent 3.12 elementary flow: Chloride
Uncertainty: A minimum-maximum range is defined for this flow. Bounds ship with the dataset on Circa.
Unit: g

Flows not quantified

2 flows are recorded for this dataset but carry no quantity — cut off below the significance threshold, or with no background dataset available. They remain inside the declared system boundary; each is listed with its reason.

Cut off - below the significance threshold (1)

Ni sputtering target Materialkg · -21.4% / +38.1%

Derivation basis: This flow is a consumable of the manufacturing operation. The model reads it from the operation's own inventory rather than from the product's bill of materials.

The sources for this row are listed below.
Source citations: freepatentsonline.com (date not recorded). US 6,852,202 B2 - Applied Materials, small planar magnetron with non-uniform erosion. Patent.
freepatentsonline.com (date not recorded). US 2007/0068804 A1 - TSMC, PVD target end-of-service-life determination. Patent.
Methods of rejuvenating sputtering targets - H.C. Starck Inc
materion.com (date not recorded). Enhance Your Sputter Deposition Yield With The Materion Approach.
Background data: cut off
Background dataset: Not applicable: this flow is not quantified in the inventory.
Reason: The sputtering target is recorded at its authored mass. No representative production dataset for the target metal is available, so its upstream burden is left unlinked rather than approximated with an unrelated metal.
Uncertainty: -21.4% / +38.1% around the published quantity. The bounds themselves ship with the dataset on Circa.
Unit: kg

Not quantified - no background dataset available (1)

Diamond wire Materialm

Derivation basis: Calculated from per-operation consumption, operation counts, and manufacturing yield.

The sources for this row are listed below.
Source citations (dataset-level): IAAM and PMC thermal field optimization
Compound Semiconductor and Orbit & Skyline
Orbit & Skyline and MDPI SiC growth
IAAM SiC powder source study
Power Electronics News and PMC
Background data: no background dataset
Background dataset: Not applicable: this flow is not quantified in the inventory.
Reason: The diamond-abrasive wire that saws the boule into wafers. Silicon carbide is too hard to cut any other way, and no production dataset for a diamond-abrasive sawing wire exists in the background database used for linkage. The consumed length is recorded here and its upstream production is left unlinked.
Uncertainty: No range defined.
Unit: m

Limitations and unquantified flows (2)

Limits this dataset declares about itself: first any limit stated in its own description, then any limit it declares flow by flow, grouped by channel. Each entry below is the model's own disclosure.

From the dataset description

Part of the process electricity on this dataset is a facility overhead allowance that the substrate growth record carries inside its own published total, covering cleanroom, abatement and cooling for the substrate line. The facility support calculated for this dataset covers the same services for the wafer as a whole. Neither record apportions the overlap and no registered source divides it, so both allowances are published as they stand and the electricity on this dataset should be read as an upper bound on the facility services it charges.

General

Some consumable pulls referenced by the modelled process steps did not resolve to an inventory row and are absent from this dataset. They are itemised in the dataset's own export audit.

The flows above are this dataset's own records. What follows are the scope rules set once for the whole database in the methodology report, repeated here so every dataset page carries them.

Database-wide boundary policy — applies to every REEL dataset

These boundaries are set once for the whole database, in Chapter 2 of the methodology report, and apply to this dataset wherever they are relevant to it. The excluded flows listed above are specific to this dataset.

Use phase: Product operation is outside the cradle-to-gate scope.
End-of-life treatment: Recycling and disposal are outside the cradle-to-gate scope.
Distribution and retail: The gate is a finished component ready for integration into a higher-level assembly.
Inbound transport of raw materials: Transport of purchased raw materials to the manufacturing facility is already inside the upstream "market for" datasets that users link to a background database, so it is not modelled a second time here. This does not cover freight between REEL production stages, which is modelled where a dataset authors it.
Returnable shipping containers: Where freight between production stages is modelled, the mass moved is the product itself. The shipping container (FOSB, SEMI M31) is returnable capital equipment whose per-trip share is unsourced, so its tare is excluded from the transport effort.
Photomask fabrication: A mask set's embodied burden is amortised across a high-volume production run and is not attributed per wafer. Users assessing low-volume production should add mask fabrication separately; the methodology report gives the basis for the exclusion.
Employee transport, administration and R&D overhead: Employee transportation, facility administration and R&D/pilot-production overhead are outside scope.
Capital goods: Manufacturing equipment, cleanroom construction and facility infrastructure are excluded, on the grounds of absent public data on equipment embodied energy, uncertainty in equipment lifetime and allocation, common practice in electronics LCA, and a focus on the operational inventory. Future versions may include capital goods when sufficient public data becomes available.
Precious metal recovery credits: Scrap recovery credits for precious metals are excluded pending data availability.
Wafer reclaim: Test wafers and scrap are outside the system boundary.

Inside the boundary, linked rather than modelled

Silicon ingot growth and wafer slicing: Inside the cradle-to-gate scope, but treated as upstream material inputs linked to background databases rather than modelled as REEL processes.
Freight between production stages: Where a dataset's product moves between REEL production stages - wafer fabrication to the packaging site, for example - that leg is authored as a transport service and linked to an ecoinvent freight activity. It is measured as a transport effort in tonne-kilometres, not as a mass. Route distances are authored per route class with a stated band; a lower bound of zero is a modelling statement that the two sites can be co-located, not a missing value.

Cut-off criteria

A flow is excluded from a process inventory when it contributes less than 1 % of the total mass of inputs to that unit process, or less than 1 % of its total energy input. The denominator is total process inputs, not product mass. That distinction matters in semiconductor manufacturing, where the input mass of water, chemicals and gases greatly exceeds the product mass, so the threshold removes only genuinely minor flows.

Included regardless of the cut-off

Perfluorocarbons (CF4, C2F6, SF6, NF3) - high GWP, EPA regulated
Heavy metals (Pb, Cd, Hg, Cr(VI)) - RoHS regulated, high toxicity
Volatile organics (photoresist solvents, PGMEA) - air quality
Precious metals (Au, Ag, Pd, Pt) - high embodied impacts
Ozone-depleting substances (legacy CFCs, HCFCs) - Montreal Protocol