Overview

General comment

Production covered

Silicon power-discrete wafer built on a thick epitaxial drift layer, with field oxide, junction implant and contact metallization. This variant represents fabrication at Infineon-dominant Si power discretes (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 20,000 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: Power Discrete Silicon 200mm, power discrete
Geography: Representative region: Germany (Infineon-led power-discrete fleet; EU proxy per the reviewed fab-region table; per-technology region).

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

2.8

Completeness

2.4

Temporal

2.1

Geographic

2.0

Technological

2.9

How the score is calculated: Sources used across more manufacturing steps have more influence. Sources that define assumptions for the whole model account for 75.0% 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: 11 — 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 · -6% / +7.6%

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: -6% / +7.6% around the published quantity. The bounds themselves ship with the dataset on Circa.
Unit: m3

Silicon wafer, single-crystal Substrate materialm2 · -7.2% / +5.9%

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: single-Si wafer, for electronics
Notes: Polished CZ wafer substrate (200mm diameter, 0.031416 m2)
Uncertainty: -7.2% / +5.9% around the published quantity. The bounds themselves ship with the dataset on Circa.
Unit: m2

Electricity, Germany (DE) ElectricitykWh · -17% / +20.8%

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:

Single-wafer epitaxy reactor estimate; PELCA IGBT calibration anchor

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: electricity, high voltage
Uncertainty: -17% / +20.8% around the published quantity. The bounds themselves ship with the dataset on Circa.
Unit: kWh

SiHCl₃ Process gasg · -50% / +100%

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

The sources below come from the manufacturing operations behind this row.
Source citations (specific to this process): Inherited, rolled up from the contributing process steps:

Saxena and Kumar 2012 power-MOSFET dimensions; eeNews backside metallurgy
Background data: CarbonMinds
Background dataset: trichlorosilane
Uncertainty: -50% / +100% around the published quantity. The bounds themselves ship with the dataset on Circa.
Unit: g

H₂ Process gasg · -50% / +100%

Derivation basis: Silicon epitaxy carrier-gas basis

No source is attached to this row.
Source citations: Not stated
Background data: ecoinvent 3.12
Background dataset: hydrogen, gaseous, low pressure
Uncertainty: -50% / +100% around the published quantity. The bounds themselves ship with the dataset on Circa.
Unit: g

PH₃ Process gasg · -59.7% / +101.7%

Derivation basis: Power-device n-type drift doping basis

The sources for this row are listed below.
Source citations: sst.semiconductor-digest.com (date not recorded). Arnó, Farha, Morris et al. (NuMat Technologies; Axcelis Technologies) - 'Next generation dopant gas delivery system for ion implant applications', Semiconductor Digest (SST), 2018. Trade publication.
axcelis.com (date not recorded). Axcelis Technologies - Purion H High Current Ion Implantation product page (500 WPH end station). Vendor datasheet.
axcelis.com (date not recorded). Axcelis Technologies - Purion XE Series High Energy Ion Implantation product page (4.5 MeV, 500 WPH). Vendor datasheet.
Background data: proxy-mapped
Background dataset: phosphorus, white, liquid
Uncertainty: -59.7% / +101.7% around the published quantity. The bounds themselves ship with the dataset on Circa.
Unit: g

HCl Process gasg · -66.5% / +100.6%

Derivation basis: TCS epitaxy in-situ chamber clean

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: -66.5% / +100.6% around the published quantity. The bounds themselves ship with the dataset on Circa.
Unit: g

O₂ Process gasg · -2.9% / +8.7%

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: -2.9% / +8.7% 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

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.

The sources below come from the manufacturing operations behind this row.
Source citations (specific to this process): Inherited, rolled up from the contributing process steps:

sst.semiconductor-digest.com (date not recorded). Arnó, Farha, Morris et al. (NuMat Technologies; Axcelis Technologies) - 'Next generation dopant gas delivery system for ion implant applications', Semiconductor Digest (SST), 2018. Trade publication.

axcelis.com (date not recorded). Axcelis Technologies - Purion H High Current Ion Implantation product page (500 WPH end station). Vendor datasheet.

axcelis.com (date not recorded). Axcelis Technologies - Purion XE Series High Energy Ion Implantation product page (4.5 MeV, 500 WPH). Vendor datasheet.
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

BF₃ Process gasg · -50% / +150.4%

Source citations: sst.semiconductor-digest.com (date not recorded). Arnó, Farha, Morris et al. (NuMat Technologies; Axcelis Technologies) - 'Next generation dopant gas delivery system for ion implant applications', Semiconductor Digest (SST), 2018. Trade publication.
axcelis.com (date not recorded). Axcelis Technologies - Purion H High Current Ion Implantation product page (500 WPH end station). Vendor datasheet.
axcelis.com (date not recorded). Axcelis Technologies - Purion XE Series High Energy Ion Implantation product page (4.5 MeV, 500 WPH). Vendor datasheet.
Background data: ecoinvent 3.12
Background dataset: boron trifluoride
Uncertainty: -50% / +150.4% around the published quantity. The bounds themselves ship with the dataset on Circa.
Unit: g

AsH₃ Process gasg · -50% / +150.2%

Source citations: sst.semiconductor-digest.com (date not recorded). Arnó, Farha, Morris et al. (NuMat Technologies; Axcelis Technologies) - 'Next generation dopant gas delivery system for ion implant applications', Semiconductor Digest (SST), 2018. Trade publication.
axcelis.com (date not recorded). Axcelis Technologies - Purion H High Current Ion Implantation product page (500 WPH end station). Vendor datasheet.
axcelis.com (date not recorded). Axcelis Technologies - Purion XE Series High Energy Ion Implantation product page (4.5 MeV, 500 WPH). Vendor datasheet.
Background data: ecoinvent 3.12
Background dataset: arsine
Uncertainty: -50% / +150.2% around the published quantity. The bounds themselves ship with the dataset on Circa.
Unit: g

Ar Process gasg · ±0.1%

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: ±0.1% 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

Outputs and waste

Wastewater Wastewaterm3 · -6% / +7.6%

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: -6% / +7.6% around the published quantity. The bounds themselves ship with the dataset on Circa.
Unit: m3

Spent scrubber media Solid wasteg · -95% / +50%

Source citations: patents.google.com (date not recorded). US 7,364,603 B2 - Applied Materials / ATMI (Sweeney, Marganski, Olander), sorbent system for hazardous gas abatement. Patent.
cscleansystemsbenelux.com (date not recorded). CS Clean Solutions - Exhaust Gas Treatment product catalogue (CLEANSORB dry-bed chemisorption). Vendor catalogue.
cdn.thomasnet.com (date not recorded). Hertzler, C. and Hui, V. (TecHarmonic, Inc.), "Point of Use Abatement Tool Selection and Evaluation". Conference paper.
Background data: ecoinvent 3.12 treatment route
Background dataset: treatment of hazardous waste, underground deposit
Uncertainty: -95% / +50% around the published quantity. The bounds themselves ship with the dataset on Circa.
Unit: g

Intact un-eroded sputter target body (Al) 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: market for aluminium scrap, new
Uncertainty: -33.3% / +66.7% around the published quantity. The bounds themselves ship with the dataset on Circa.
Unit: g

Spent sputter targets (Al) 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: market for aluminium scrap, new
Uncertainty: -44.5% / +44.4% around the published quantity. The bounds themselves ship with the dataset on Circa.
Unit: g

Scrapped material (line yield) Solid wastem2 · -72.2% / +58.8%

Source citations: iedm23.mapyourshow.com (date not recorded). Boakes et al., "Cradle-to-gate Life Cycle Assessment of CMOS Logic Technologies", IEDM 2023, 28-1. PDF document.
escholarship.org (date not recorded). Boyd, "Life-cycle Assessment of Semiconductors" (UC Berkeley dissertation, escholarship qt8bv2s63d). PDF document.
microlab.berkeley.edu (date not recorded). Leachman & Hodges, "Benchmarking Semiconductor Manufacturing" (CSM 28-fab IRW paper). PDF document.
ieor.berkeley.edu (date not recorded). Leachman (ed.), "The Competitive Semiconductor Manufacturing Survey - Third Report on Results of the Main Phase" (CSM-52), UC Berkeley, 2002. PDF document.
Background data: ecoinvent 3.12 treatment route
Background dataset: treatment of waste electric and electronic equipment, shredding
Notes: Calculated reject material after accounting for a manufacturing yield of 90%. Wafer starts that do not complete processing, at the modeled line yield of 90 percent. Line yield here counts test, monitor, and damaged wafers against wafers processed - the inclusive convention of the cited fab benchmarking and life cycle studies. The 0.85 to 0.97 uncertainty band on the yield spans measured multi-fab benchmarking: the low end reflects below-average lines and deep multi-layer flows; the high end reflects the best benchmarked lines, which reach about 97 to 98 percent.
Uncertainty: -72.2% / +58.8% around the published quantity. The bounds themselves ship with the dataset on Circa.
Unit: m2

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.

SiHCl₃ 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 corresponding ecoinvent dataset or flow was identified for this entry, so it is published with its own quantity and no background link

The sources below come from the manufacturing operations behind this row.
Source citations (specific to this process): Inherited, rolled up from the contributing process steps:

Saxena and Kumar 2012 power-MOSFET dimensions; eeNews backside metallurgy

IPCC 2019 Guidelines Vol 3 Ch 6

EPA 40 CFR Part 98 Subpart I (2024)
Compartment: Air (non-urban air or from high stacks)
CAS number: 10025-78-2
ecoinvent 3.12 elementary flow: Not stated
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: TCS epitaxy in-situ chamber clean

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

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

Emissions to water

4 elementary flows 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

F- Emission to waterg

Derivation basis: Mass balance from BF3 input

The sources below are this dataset's own bibliography. They are not tied to this row.
Source citations (dataset-level): Inherited from this dataset's own bibliography, not tied to this row:

sst.semiconductor-digest.com (date not recorded). Arnó, Farha, Morris et al. (NuMat Technologies; Axcelis Technologies) - 'Next generation dopant gas delivery system for ion implant applications', Semiconductor Digest (SST), 2018. Trade publication.

axcelis.com (date not recorded). Axcelis Technologies - Purion H High Current Ion Implantation product page (500 WPH end station). Vendor datasheet.

axcelis.com (date not recorded). Axcelis Technologies - Purion XE Series High Energy Ion Implantation product page (4.5 MeV, 500 WPH). Vendor datasheet.
Compartment: Water (surface water)
CAS number: 16984-48-8
ecoinvent 3.12 elementary flow: Fluoride
Uncertainty: No range defined.
Unit: g

PO4 3- Emission to waterg

Derivation basis: Mass balance from PH3 input

The sources below are this dataset's own bibliography. They are not tied to this row.
Source citations (dataset-level): Inherited from this dataset's own bibliography, not tied to this row:

sst.semiconductor-digest.com (date not recorded). Arnó, Farha, Morris et al. (NuMat Technologies; Axcelis Technologies) - 'Next generation dopant gas delivery system for ion implant applications', Semiconductor Digest (SST), 2018. Trade publication.

axcelis.com (date not recorded). Axcelis Technologies - Purion H High Current Ion Implantation product page (500 WPH end station). Vendor datasheet.

axcelis.com (date not recorded). Axcelis Technologies - Purion XE Series High Energy Ion Implantation product page (4.5 MeV, 500 WPH). Vendor datasheet.
Compartment: Water (surface water)
Formula: PO43-
CAS number: 14265-44-2
ecoinvent 3.12 elementary flow: Phosphate
Uncertainty: No range defined.
Unit: g

As Emission to waterg

Derivation basis: Mass balance from AsH3 input

The sources below are this dataset's own bibliography. They are not tied to this row.
Source citations (dataset-level): Inherited from this dataset's own bibliography, not tied to this row:

sst.semiconductor-digest.com (date not recorded). Arnó, Farha, Morris et al. (NuMat Technologies; Axcelis Technologies) - 'Next generation dopant gas delivery system for ion implant applications', Semiconductor Digest (SST), 2018. Trade publication.

axcelis.com (date not recorded). Axcelis Technologies - Purion H High Current Ion Implantation product page (500 WPH end station). Vendor datasheet.

axcelis.com (date not recorded). Axcelis Technologies - Purion XE Series High Energy Ion Implantation product page (4.5 MeV, 500 WPH). Vendor datasheet.
Compartment: Water (surface water)
CAS number: 7440-38-2
ecoinvent 3.12 elementary flow: Arsenic ion
Uncertainty: No range defined.
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)

Al 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)

Scrubber media (dry-bed chemisorbent) Process chemicalg · -95% / +50%

Source citations: patents.google.com (date not recorded). US 7,364,603 B2 - Applied Materials / ATMI (Sweeney, Marganski, Olander), sorbent system for hazardous gas abatement. Patent.
cscleansystemsbenelux.com (date not recorded). CS Clean Solutions - Exhaust Gas Treatment product catalogue (CLEANSORB dry-bed chemisorption). Vendor catalogue.
cdn.thomasnet.com (date not recorded). Hertzler, C. and Hui, V. (TecHarmonic, Inc.), "Point of Use Abatement Tool Selection and Evaluation". Conference paper.
Background data: no background dataset
Background dataset: Not applicable: this flow is not quantified in the inventory.
Reason: Purchased granulate for point-of-use dry-bed abatement of hydride process gases. No chemisorbent or sorbent abatement-medium activity exists in the background database used for linkage. Its burden is dominated by the impregnated reactive phase that makes it a scavenger, and vendors do not disclose that chemistry, so a generic carbon-supported substitute would carry the wrong material. The quantity is recorded here and its upstream production is left unlinked.
Uncertainty: -95% / +50% around the published quantity. The bounds themselves ship with the dataset on Circa.
Unit: g

Limitations and unquantified flows (1)

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.

Wafer-dicing kerf and filter-cake outputs on this dataset are carried unchanged from the dicing process file's reference wafer, which is a larger-diameter silicon wafer than the one modelled here, and are not rescaled to this wafer's diameter, thickness or substrate. That file publishes no wafer thickness, no substrate density and no cut length to rescale from, and states its kerf width three different ways, so no consumer-specific value can be derived from it; the filter cake is a wastewater-treatment residue with no geometric basis at all. Treat both rows as the reference wafer's figures rather than this product's.

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