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Overview

General comment

Production covered

Memory 3D NAND 232L wafer fabrication.

This variant represents operation with moderate PFC gas recovery and moderate water recycling; conventional high-aspect-ratio etching with C4F8/C4F6 fluorocarbons at near-room temp.

Modelling choices

Assumes 88% line yield.

Support energy is allocated using 120,000 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.

Technology
3D NAND 232L, nand flash memory
Geography
Global average data from equipment vendor specifications, academic literature, and semiconductor industry reports
Terms used above
  • PFC perfluorinated compounds; in power-supply contexts, power-factor correction
  • POU point of use

System boundary

System boundary - 3D NAND 232L wafer, 300mm, moderate scenario, conventional etchSystem boundary figure: identity, gate in, entering flows, the dashed system boundary and the unit processes inside it, the reference product, emissions and waste, and below it the flows that are recorded but not quantified. No inventory quantities.3D NAND 232L wafer, 300mm, moderate scenario, conventional etchGATE INIncoming polished 300mm silicon waferENTERING FLOWSElectricityWaterProcess gasesProcess chemicalsMaterialsSubstrate materialSYSTEM BOUNDARYMODELLED UNIT PROCESSES, BY CLASSDepositionThermal oxidationCVD polyCVD tungstenCVD oxideCVD nitrideALD HfO2OtherTarget changeout eolCleanWet cleanChamber clean NF3ImplantIon implantEtchHAR etch 3dnandHAR etch 3dnand per modulePlasma etch oxideAsh resistLithographyLitho immersionInterconnectBEOL metal layerPlanarisationCMP metal tungstenCMP oxideTestWafer probe testREFERENCE PRODUCT3D NAND 232L wafer, 300mm,moderate scenario, conventionaletchCompleted memory wafer with finalpassivation and testEMISSIONS AND WASTEEmissions to airEmissions to waterWaste routesRECORDED BUT NOT QUANTIFIEDIn scope, left out of the quantified inventoryCut off below the significance threshold, or with no background dataset available - each is listed with its reason8FLOWSsystem boundaryreference flowentering flowemission / waste

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 2.1 Good
Reliability
3.0
Completeness
1.8
Temporal
1.8
Geographic
2.0
Technological
2.3
How the score is calculated: Sources used across more manufacturing steps have more influence. Sources that define assumptions for the whole model account for 63.8% 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
Equipment vendor specifications, academic papers, corporate sustainability reports, SEMI standards
Coverage status
Partial
Pedigree-scored source files
31 — the source records behind this dataset's manufacturing operations. Each carries the five pedigree axes above; the composite DQI aggregates them.

Technosphere inputs

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

WF6 production Process gasg · -55% / +70%
Derivation basis
  • Calculated by the manufacturing model. The linked REEL dataset carries the upstream life cycle sources.

The sources below come from the manufacturing operations behind this row.

Sources (inherited)
Inherited, rolled up from the contributing process steps:
Upstream REEL dataset
Tungsten hexafluoride (WF6)
Background dataset
Modelled by REEL; see the upstream dataset above.
Uncertainty
-55% / +70% around the published quantity. The bounds themselves ship with the dataset on Circa.
Unit
g
C4F8 production Process gasg · -41.6% / +89.5%
Source citations
  • Plasma etching of high aspect ratio features in SiO2 using Ar/C4F8/O2 mixtures: A computational investigation JVA 2019
  • Extreme low-k porous pSiCOH dielectrics. JVB 2017
Upstream REEL dataset
Octafluorocyclobutane (c-C4F8)
Background dataset
Modelled by REEL; see the upstream dataset above.
Uncertainty
-41.6% / +89.5% around the published quantity. The bounds themselves ship with the dataset on Circa.
Unit
g
C4F6 production Process gasg · -40.6% / +98.5%
Derivation basis
  • Calculated by the manufacturing model. The linked REEL dataset carries the upstream life cycle sources.

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:
  • Effect of NF3, WF6, and MoF6 Additive Gases on High Aspect Ratio Contact SiO2 Etching in c-C4F8/C4F6/Ar/O2 Plasmas (2025)
  • Characteristics of SiO2 Etching with a C4F8/Ar/CHF3/O2 Gas Mixture in 60-MHz/2-MHz Dual-frequency Capacitively Coupled Plasmas (2011)
  • Effect of C4F8 Isomers on High Aspect Ratio Contact SiO2 Etching and Greenhouse Gas Emission (2015)
  • Etch characteristics of nanoscale ultra low-k dielectric using C3H2F6 (2020)
  • PROCESS FOR ETCHING OXIDE USING HEXAFLUOROBUTADIENE OR RELATED FLUOROCARBONS AND MANIFESTING A WIDE PROCESS WINDOW (2001)
  • Study of Silicon Nitride Inner Spacer Formation in Process of Gate-all-around Nano-Transistors (2020)
Upstream REEL dataset
Hexafluoro-1,3-butadiene (C4F6)
Background dataset
Modelled by REEL; see the upstream dataset above.
Uncertainty
-40.6% / +98.5% around the published quantity. The bounds themselves ship with the dataset on Circa.
Unit
g
CF4 production Process gasg · ±33.3%
Derivation basis
  • Calculated by the manufacturing model. The linked REEL dataset carries the upstream life cycle sources.

No source is attached to this row.

Source citations
Not stated
Upstream REEL dataset
Carbon tetrafluoride (CF4)
Background dataset
Modelled by REEL; see the upstream dataset above.
Uncertainty
±33.3% around the published quantity. The bounds themselves ship with the dataset on Circa.
Unit
g
NF3 production Process gasg · -50.7% / +49.3%
Derivation basis
  • Calculated by the manufacturing model. The linked REEL dataset carries the upstream life cycle sources.

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:
  • Effect of NF3, WF6, and MoF6 Additive Gases on High Aspect Ratio Contact SiO2 Etching in c-C4F8/C4F6/Ar/O2 Plasmas (2025)
  • Characteristics of SiO2 Etching with a C4F8/Ar/CHF3/O2 Gas Mixture in 60-MHz/2-MHz Dual-frequency Capacitively Coupled Plasmas (2011)
  • Effect of C4F8 Isomers on High Aspect Ratio Contact SiO2 Etching and Greenhouse Gas Emission (2015)
  • Etch characteristics of nanoscale ultra low-k dielectric using C3H2F6 (2020)
  • PROCESS FOR ETCHING OXIDE USING HEXAFLUOROBUTADIENE OR RELATED FLUOROCARBONS AND MANIFESTING A WIDE PROCESS WINDOW (2001)
  • Study of Silicon Nitride Inner Spacer Formation in Process of Gate-all-around Nano-Transistors (2020)
Upstream REEL dataset
Nitrogen trifluoride (NF3)
Background dataset
Modelled by REEL; see the upstream dataset above.
Uncertainty
-50.7% / +49.3% around the published quantity. The bounds themselves ship with the dataset on Circa.
Unit
g
Elemental fluorine (F2) Process gasg · -70% / +400.8%
Source citations
Upstream REEL dataset
Fluorine (F2)
Background dataset
Modelled by REEL; see the upstream dataset above.
Uncertainty
-70% / +400.8% around the published quantity. The bounds themselves ship with the dataset on Circa.
Unit
g
ArF Photoresist Process chemicalg · -56% / +10.1%
Source citations
Upstream REEL dataset
ArF Photoresist (193nm)
Background dataset
Modelled by REEL; see the upstream dataset above.
Uncertainty
-56% / +10.1% around the published quantity. The bounds themselves ship with the dataset on Circa.
Unit
g
TMAH Developer (2.38% solution) Process chemicalg · ±15.4%
Source citations
Background dataset
Modelled by REEL; see the upstream dataset above.
Uncertainty
±15.4% around the published quantity. The bounds themselves ship with the dataset on Circa.
Unit
g
CMP Slurry (Copper) Process chemicalg · ±23.1%
Source citations
  • CMP process water and slurry consumption. NMFRC
  • Estimating CMP Process Mass Intensity. NCCAVS 2024
Upstream REEL dataset
Copper CMP Slurry
Background dataset
Modelled by REEL; see the upstream dataset above.
Uncertainty
±23.1% around the published quantity. The bounds themselves ship with the dataset on Circa.
Unit
g
BARC Process chemicalg · ±33.3%
Source citations
  • 300mm wafer photoresist dispense. SPIE
Upstream REEL dataset
ArF Photoresist (193nm)
Background dataset
Modelled by REEL; see the upstream dataset above.
Uncertainty
±33.3% around the published quantity. The bounds themselves ship with the dataset on Circa.
Unit
g
CMP Slurry (Tungsten) Process chemicalg · ±33.3%
Derivation basis
  • Industry-typical estimate. The source may ambiguously report either flow rate multiplied by time or a per-operation volume; supporting notes document this limitation.

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:
Upstream REEL dataset
Tungsten CMP Slurry
Background dataset
Modelled by REEL; see the upstream dataset above.
Uncertainty
±33.3% around the published quantity. The bounds themselves ship with the dataset on Circa.
Unit
g
BARC/TARC (Anti-Reflective Coatings) Process chemicalg · ±26.8%
Source citations
Upstream REEL dataset
ArF Photoresist (193nm)
Background dataset
Modelled by REEL; see the upstream dataset above.
Uncertainty
±26.8% around the published quantity. The bounds themselves ship with the dataset on Circa.
Unit
g
Topcoat Process chemicalg · -80.8% / +92.3%
Upstream REEL dataset
ArF Photoresist (193nm)
Background dataset
Modelled by REEL; see the upstream dataset above.
Uncertainty
-80.8% / +92.3% around the published quantity. The bounds themselves ship with the dataset on Circa.
Unit
g
CMP Slurry (Oxide) Process chemicalg · -40% / +20%
Derivation basis
  • Calculated by the manufacturing model. The linked REEL dataset carries the upstream life cycle sources.

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:
Upstream REEL dataset
Oxide CMP Slurry
Background dataset
Modelled by REEL; see the upstream dataset above.
Uncertainty
-40% / +20% around the published quantity. The bounds themselves ship with the dataset on Circa.
Unit
g
Water supply (municipal) Waterm3 · -24.3% / +25.6%
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.

The sources below come from the manufacturing operations behind this row.

Sources (inherited)
Inherited, rolled up from the contributing process steps:
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
-24.3% / +25.6% around the published quantity. The bounds themselves ship with the dataset on Circa.
Unit
m3
Silicon wafer, single-crystal Substrate materialm2 · -9.3% / +3.5%
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
single-Si wafer, for electronics
Notes
Polished CZ wafer substrate (300mm diameter, 0.070686 m2)
Uncertainty
-9.3% / +3.5% around the published quantity. The bounds themselves ship with the dataset on Circa.
Unit
m2
CMP pad material Materialkg · -51.9% / +677.6%
Derivation basis
  • REEL derivation: CMP pad mass from pad geometry and polyurethane density
  • 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
Background data
ecoinvent 3.12
Background dataset
polyurethane, rigid foam
Uncertainty
-51.9% / +677.6% around the published quantity. The bounds themselves ship with the dataset on Circa.
Unit
kg
Electricity, South Korea (KR) ElectricitykWh · -25.6% / +35%
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:
Background data
ecoinvent 3.12
Background dataset
electricity, high voltage
Uncertainty
-25.6% / +35% around the published quantity. The bounds themselves ship with the dataset on Circa.
Unit
kWh
O2 Process gasg · -39.9% / +41.1%
Source citations
  • Plasma etching of high aspect ratio features in SiO2 using Ar/C4F8/O2 mixtures: A computational investigation JVA 2019
  • Extreme low-k porous pSiCOH dielectrics. JVB 2017
Background data
ecoinvent 3.12
Background dataset
oxygen, liquid
Uncertainty
-39.9% / +41.1% around the published quantity. The bounds themselves ship with the dataset on Circa.
Unit
g
H2O Process gasg · -50% / +100%
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 · ±1.6%
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.
  • Engineering estimate for batch LPCVD
  • Estimated from typical ALD purge flows

The sources for this row are listed below.

Source citations
  • Applied Materials Endura Impulse PVD
Background data
ecoinvent 3.12
Background dataset
nitrogen, liquid
Uncertainty
±1.6% 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
SiH4 Process gasg · -44.8% / +45.2%
Derivation basis
  • Calculated from per-operation consumption, operation counts, and manufacturing yield.

The sources below come from the manufacturing operations behind this row.

Sources (inherited)
Inherited, rolled up from the contributing process steps:
Background data
ecoinvent 3.12
Background dataset
silicon tetrahydride
Uncertainty
-44.8% / +45.2% around the published quantity. The bounds themselves ship with the dataset on Circa.
Unit
g
BF3 Process gasg · -50.1% / +149.2%
Background data
ecoinvent 3.12
Background dataset
boron trifluoride
Uncertainty
-50.1% / +149.2% around the published quantity. The bounds themselves ship with the dataset on Circa.
Unit
g
PH3 Process gasg · -50% / +149.8%
Background data
proxy-mapped
Background dataset
phosphorus, white, liquid
Uncertainty
-50% / +149.8% around the published quantity. The bounds themselves ship with the dataset on Circa.
Unit
g
AsH3 Process gasg · -49.9% / +150.7%
Background data
ecoinvent 3.12
Background dataset
arsine
Uncertainty
-49.9% / +150.7% around the published quantity. The bounds themselves ship with the dataset on Circa.
Unit
g
H2 Process gasg · -20.5% / +41%
Derivation basis
  • Calculated from per-operation consumption, operation counts, and manufacturing yield.

The sources below come from the manufacturing operations behind this row.

Sources (inherited)
Inherited, rolled up from the contributing process steps:
Background data
ecoinvent 3.12
Background dataset
hydrogen, gaseous, low pressure
Uncertainty
-20.5% / +41% around the published quantity. The bounds themselves ship with the dataset on Circa.
Unit
g
Ar Process gasg · -9.3% / +10.7%
Source citations
  • Plasma etching of high aspect ratio features in SiO2 using Ar/C4F8/O2 mixtures: A computational investigation JVA 2019
  • Applied Materials Endura Impulse PVD
  • Cymer Inc., US Patent 5,978,406, "Fluorine control system for excimer lasers" (1999)
  • Praxair (now Linde), "Specialty Gases and Equipment Reference Guide", p. 148 (excimer premix specifications)
Background data
ecoinvent 3.12
Background dataset
argon, liquid
Uncertainty
-9.3% / +10.7% around the published quantity. The bounds themselves ship with the dataset on Circa.
Unit
g
Si(OC2H5)4 Process gasg · -37.5% / +50%
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:
  • Thaiyotin, L., et al. NECTEC PECVD study
  • University of Pennsylvania PECVD Recipes
  • Thin Solid Films - Gas utilization efficiency study
  • Utrecht University NH3 utilization study
  • JEOL USA - Analysis of Reaction Gases in PECVD Chamber
Background data
ecoinvent 3.12
Background dataset
tetraethyl orthosilicate
Uncertainty
-37.5% / +50% around the published quantity. The bounds themselves ship with the dataset on Circa.
Unit
g
NH3 Process gasg · -58.9% / +57.9%
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:
  • EPA Subpart I
Background data
ecoinvent 3.12
Background dataset
ammonia, anhydrous, liquid
Uncertainty
-58.9% / +57.9% around the published quantity. The bounds themselves ship with the dataset on Circa.
Unit
g
Hf[N(CH3)(C2H5)]4 Process gasg · -33.7% / +38.5%
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:
  • Process and electrical characteristics of MO-ALD HfO2 films for high-K gate applications grown in a production-worthy 300 mm deposition system (TEMAH flow rates)
  • Energy and material flow analysis of ALD Al2O3 (TMA mass, Energy)
  • Applied Materials Olympia ALD system specifications
  • BTBAS ALD modeling (Inlet flows)
  • ACS Applied Electronic Materials
Background data
proxy-mapped
Background dataset
hafnium sponge
Uncertainty
-33.7% / +38.5% around the published quantity. The bounds themselves ship with the dataset on Circa.
Unit
g
O3 Process gasg · -33.3% / +38.9%
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:
  • Process and electrical characteristics of MO-ALD HfO2 films for high-K gate applications grown in a production-worthy 300 mm deposition system (TEMAH flow rates)
  • Energy and material flow analysis of ALD Al2O3 (TMA mass, Energy)
  • Applied Materials Olympia ALD system specifications
  • BTBAS ALD modeling (Inlet flows)
  • ACS Applied Electronic Materials
Background data
ecoinvent 3.12
Background dataset
ozone, liquid
Uncertainty
-33.3% / +38.9% 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
Low-k Precursor (3MS/DEMS) Process chemicalg · ±33.3%
Source citations
  • Extreme low-k porous pSiCOH dielectrics. JVB 2017
  • PECVD low-k dielectric deposition. Patent US2018
Background data
proxy-mapped
Background dataset
silicone product
Uncertainty
±33.3% around the published quantity. The bounds themselves ship with the dataset on Circa.
Unit
g
EBR Solvent (PGMEA) Process chemicalg · ±33.3%
Source citations
  • 300mm wafer photoresist dispense. SPIE
Background data
CarbonMinds
Background dataset
propylene glycol methyl ether acetate (PGMEA)
Uncertainty
±33.3% around the published quantity. The bounds themselves ship with the dataset on Circa.
Unit
g
EBR Solvent (PGMEA/PGME) Process chemicalg · ±53.8%
Source citations
Background data
CarbonMinds
Background dataset
propylene glycol methyl ether acetate (PGMEA)
Uncertainty
±53.8% around the published quantity. The bounds themselves ship with the dataset on Circa.
Unit
g
Ammonium Hydroxide Process chemicalg · ±25%
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
ammonia, anhydrous, liquid
Uncertainty
±25% around the published quantity. The bounds themselves ship with the dataset on Circa.
Unit
g
Hydrogen Peroxide (for SC-1) Process chemicalg · ±45.5%
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
hydrogen peroxide, without water, in 50% solution state
Uncertainty
±45.5% around the published quantity. The bounds themselves ship with the dataset on Circa.
Unit
g
Hydrochloric Acid Process chemicalg · ±50%
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% around the published quantity. The bounds themselves ship with the dataset on Circa.
Unit
g
Hydrogen Peroxide (for SC-2) Process chemicalg · ±50%
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
hydrogen peroxide, without water, in 50% solution state
Uncertainty
±50% around the published quantity. The bounds themselves ship with the dataset on Circa.
Unit
g
Sulfuric Acid Process chemicalg · -40% / +100%
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
sulfuric acid
Uncertainty
-40% / +100% around the published quantity. The bounds themselves ship with the dataset on Circa.
Unit
g
Hydrogen Peroxide (for SPM) Process chemicalg · -40% / +100%
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
hydrogen peroxide, without water, in 50% solution state
Uncertainty
-40% / +100% around the published quantity. The bounds themselves ship with the dataset on Circa.
Unit
g
Hydrofluoric Acid (diluted) Process chemicalg · -60% / +100%
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
hydrogen fluoride
Uncertainty
-60% / +100% around the published quantity. The bounds themselves ship with the dataset on Circa.
Unit
g
Natural gas, burned in industrial furnace (POU abatement, low-NOx) Process chemicalMJ · -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
heat production, natural gas, at industrial furnace low-NOx >100kW
Uncertainty
-50% / +150% around the published quantity. The bounds themselves ship with the dataset on Circa.
Unit
MJ

Outputs and waste

Wastewater Wastewaterm3 · -24.3% / +25.6%
Derivation basis
  • Calculated from the water balance: fresh-water input minus evaporation.

The sources below come from the manufacturing operations behind this row.

Sources (inherited)
Inherited, rolled up from the contributing process steps:
Background data
carried, no background dataset
Background dataset
No treatment route recorded for this output.
Uncertainty
-24.3% / +25.6% around the published quantity. The bounds themselves ship with the dataset on Circa.
Unit
m3
Spent scrubber media Solid wasteg · -95% / +50%
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
Chamber deposits (W, WFx) Solid wasteg · -66.7% / +100.2%
Source citations (dataset-level)
Inherited from this dataset's own bibliography, not tied to this row:
Background data
ecoinvent 3.12 treatment route
Background dataset
treatment of hazardous waste, underground deposit
Uncertainty
-66.7% / +100.2% around the published quantity. The bounds themselves ship with the dataset on Circa.
Unit
g
Fluoride precipitation sludge Solid wasteg · ±33.1%
Derivation basis
  • Calculated from the mass balance of spent materials and consumables, with treatment selected from the waste classification.

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:
Background data
ecoinvent 3.12 treatment route
Background dataset
treatment of hazardous waste, underground deposit
Uncertainty
±33.1% around the published quantity. The bounds themselves ship with the dataset on Circa.
Unit
g
Chamber deposits (cleaning byproduct) Solid wasteg
Derivation basis
  • Calculated from the mass balance of spent materials and consumables, with treatment selected from the waste classification.

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:
  • Plasma etching of high aspect ratio features in SiO2 using Ar/C4F8/O2 mixtures: A computational investigation JVA 2019
  • Extreme low-k porous pSiCOH dielectrics. JVB 2017
  • Applied Materials Endura Impulse PVD
  • Cymer Inc., US Patent 5,978,406, "Fluorine control system for excimer lasers" (1999)
  • Praxair (now Linde), "Specialty Gases and Equipment Reference Guide", p. 148 (excimer premix specifications)
  • Thaiyotin, L., et al. NECTEC PECVD study
  • University of Pennsylvania PECVD Recipes
  • Thin Solid Films - Gas utilization efficiency study
  • Utrecht University NH3 utilization study
  • JEOL USA - Analysis of Reaction Gases in PECVD Chamber
  • University of Twente materials database
  • patents.google.com (1998). Method for nucleation of CVD tungsten films (US5795824A). United States Patent and Trademark Office.
  • Patent US6905543
  • patents.google.com (2005). Method for nucleation of CVD tungsten films (US5795824A); Methods of forming tungsten nucleation layer (US6905543B1). United States Patent and Trademark Office.
  • IPCC 2019 Guidelines Vol 3 Ch 6
  • EPA 40 CFR Part 98 Subpart I (2024)
Background data
ecoinvent 3.12 treatment route
Background dataset
treatment of hazardous waste, underground deposit
Uncertainty
No range defined.
Unit
g
CMP slurry waste Solid wasteg · ±23.1%
Source citations (specific to this process)
  • CMP process water and slurry consumption. NMFRC
  • Estimating CMP Process Mass Intensity. NCCAVS 2024
Source citations (specific to this process)
Inherited, rolled up from the contributing process steps:
  • CMP process water and slurry consumption. NMFRC
  • Estimating CMP Process Mass Intensity. NCCAVS 2024
Background data
ecoinvent 3.12 treatment route
Background dataset
treatment of hazardous waste, underground deposit
Uncertainty
±23.1% around the published quantity. The bounds themselves ship with the dataset on Circa.
Unit
g
Spent photoresist (liquid spin-off) Solid wasteg · -57.6% / +27.7%
Source citations
Background data
ecoinvent 3.12 treatment route
Background dataset
treatment of hazardous waste, hazardous waste incineration, with energy recovery
Uncertainty
-57.6% / +27.7% around the published quantity. The bounds themselves ship with the dataset on Circa.
Unit
g
Spent EBR solvent (PGMEA) Solid wasteg · ±33.3%
Background data
ecoinvent 3.12 treatment route
Background dataset
treatment of hazardous waste, hazardous waste incineration, with energy recovery
Uncertainty
±33.3% around the published quantity. The bounds themselves ship with the dataset on Circa.
Unit
g
Chamber deposits Solid wasteg · -26.7% / +24.2%
Derivation basis
  • Calculated from the mass balance of spent materials and consumables, with treatment selected from the waste classification.

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:
  • Applied Materials Endura Impulse PVD
  • EPA Subpart I
  • 300mm wafer photoresist dispense. SPIE
  • University of Twente materials database
  • patents.google.com (1998). Method for nucleation of CVD tungsten films (US5795824A). United States Patent and Trademark Office.
  • Patent US6905543
  • patents.google.com (2005). Method for nucleation of CVD tungsten films (US5795824A); Methods of forming tungsten nucleation layer (US6905543B1). United States Patent and Trademark Office.
  • Plasma etching of high aspect ratio features in SiO2 using Ar/C4F8/O2 mixtures: A computational investigation JVA 2019
  • Cymer Inc., US Patent 5,978,406, "Fluorine control system for excimer lasers" (1999)
  • Praxair (now Linde), "Specialty Gases and Equipment Reference Guide", p. 148 (excimer premix specifications)
  • Copper Electroplating Fundamentals. Qnity Electronics
  • Extreme low-k porous pSiCOH dielectrics. JVB 2017
  • PECVD low-k dielectric deposition. Patent US2018
  • Process and electrical characteristics of MO-ALD HfO2 films for high-K gate applications grown in a production-worthy 300 mm deposition system (TEMAH flow rates)
  • Energy and material flow analysis of ALD Al2O3 (TMA mass, Energy)
  • Applied Materials Olympia ALD system specifications
  • BTBAS ALD modeling (Inlet flows)
  • ACS Applied Electronic Materials
  • IPCC 2019 Guidelines Vol 3 Ch 6
  • EPA 40 CFR Part 98 Subpart I (2024)
Background data
ecoinvent 3.12 treatment route
Background dataset
treatment of hazardous waste, underground deposit
Uncertainty
-26.7% / +24.2% around the published quantity. The bounds themselves ship with the dataset on Circa.
Unit
g
Chamber parts (quartz, ceramics) Solid wasteg · -57.2% / +121.9%
Background data
ecoinvent 3.12 treatment route
Background dataset
treatment of inert waste, sanitary landfill
Uncertainty
-57.2% / +121.9% around the published quantity. The bounds themselves ship with the dataset on Circa.
Unit
g
CMP slurry waste (tungsten polish) Solid wasteg · ±33.3%
Derivation basis
  • Tungsten CMP slurry (the dispensed-volume input row on this record)

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:
Background data
ecoinvent 3.12 treatment route
Background dataset
treatment of hazardous waste, underground deposit
Uncertainty
±33.3% around the published quantity. The bounds themselves ship with the dataset on Circa.
Unit
g
Spent CMP pads Solid wasteg · -51.8% / +678%
Derivation basis
  • REEL derivation: CMP pad mass from pad geometry and polyurethane density

The sources for this row are listed below.

Source citations
Background data
ecoinvent 3.12 treatment route
Background dataset
treatment of hazardous waste, underground deposit
Uncertainty
-51.8% / +678% around the published quantity. The bounds themselves ship with the dataset on Circa.
Unit
g
Intact un-eroded sputter target body (Ta) Solid wasteg · -33.3% / +66.7%
Source citations
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 (Cu) Solid wasteg · -44.5% / +44.4%
Source citations
Background data
ecoinvent 3.12 treatment route
Background dataset
market for copper scrap, sorted, pressed
Uncertainty
-44.5% / +44.4% around the published quantity. The bounds themselves ship with the dataset on Circa.
Unit
g
Spent photoresist (retained film) Solid wasteg · -37.6% / +42.4%
Background data
ecoinvent 3.12 treatment route
Background dataset
treatment of hazardous waste, hazardous waste incineration, with energy recovery
Uncertainty
-37.6% / +42.4% around the published quantity. The bounds themselves ship with the dataset on Circa.
Unit
g
Wastewater treatment sludge Solid wasteg · -97.8% / +2547.1%
Derivation basis
  • Estimated from treatment chemistry

No source is attached to this row.

Source citations
Not stated
Background data
ecoinvent 3.12 treatment route
Background dataset
treatment of hazardous waste, underground deposit
Uncertainty
-97.8% / +2547.1% around the published quantity. The bounds themselves ship with the dataset on Circa.
Unit
g
CMP slurry waste (oxide polish) Solid wasteg · -40% / +20%
Derivation basis
  • CMP slurry consumption (the dispensed-volume input row on this record)

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:
Background data
ecoinvent 3.12 treatment route
Background dataset
treatment of hazardous waste, underground deposit
Uncertainty
-40% / +20% around the published quantity. The bounds themselves ship with the dataset on Circa.
Unit
g
Slurry treatment sludge Solid wasteg · -45.7% / +125.7%
Derivation basis
  • Estimated from slurry input + treatment chemistry

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:
Background data
ecoinvent 3.12 treatment route
Background dataset
treatment of inert waste, sanitary landfill
Uncertainty
-45.7% / +125.7% around the published quantity. The bounds themselves ship with the dataset on Circa.
Unit
g
Diamond conditioner (allocated) Solid wasteg · -51% / +149%
Derivation basis
  • Calculated from the mass balance of spent materials and consumables, with treatment selected from the waste classification.

The sources below come from the manufacturing operations behind this row.

Sources (inherited)
Inherited, rolled up from the contributing process steps:
Background data
ecoinvent 3.12 treatment route
Background dataset
treatment of inert waste, sanitary landfill
Uncertainty
-51% / +149% around the published quantity. The bounds themselves ship with the dataset on Circa.
Unit
g
Metal Fluorides Solid wasteg
Derivation basis
  • Calculated from the mass balance of spent materials and consumables, with treatment selected from the waste classification.
  • 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.

No source is attached to this row.

Source citations
Not stated
Background data
ecoinvent 3.12 treatment route
Background dataset
treatment of hazardous waste, underground deposit
Uncertainty
No range defined.
Unit
g
Silicon dust Solid wasteg
Derivation basis
  • Calculated from the mass balance of spent materials and consumables, with treatment selected from the waste classification.
  • 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.

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 material (line yield) Solid wastem2 · -77.3% / +29.4%
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 88%. Wafer starts that do not complete processing, at the modeled line yield of 88 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. The 88 percent memory value traces to a published life cycle study of CMOS logic wafers at the 65 and 45 nanometer generations; carrying it for memory wafers while logic wafers carry 90 percent is a retained legacy modelling convention, not independently sourced. Measured memory-fab benchmarking spans roughly 87 to 99 percent per twenty mask layers.
Uncertainty
-77.3% / +29.4% around the published quantity. The bounds themselves ship with the dataset on Circa.
Unit
m2

Emissions to air

10 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
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
Hydrogen fluoride 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)
Formula
HF
CAS number
7664-39-3
ecoinvent 3.12 elementary flow
Hydrogen fluoride
Notes
Aggregated from 2 contributing steps: etch/CVD byproduct scrubber slip (dominant) + WF6 + 3H2O → WO3 + 6HF (scrubber hydrolysis; post-DRE slip only; the fluoride released to water is carried by the tungsten CVD process record)
Uncertainty
A minimum-maximum range is defined for this flow. Bounds ship with the dataset on Circa.
Unit
g
C4F8 Emission to airg
Source citations
  • Plasma etching of high aspect ratio features in SiO2 using Ar/C4F8/O2 mixtures: A computational investigation JVA 2019
  • Extreme low-k porous pSiCOH dielectrics. JVB 2017
Compartment
Air (non-urban air or from high stacks)
CAS number
115-25-3
ecoinvent 3.12 elementary flow
Tetrafluoromethane
Notes
Proxied to CF4 (Tetrafluoromethane) for ecoinvent linking. The two substances are not equivalent: this one has the substantially greater warming effect of the pair, so any characterization performed through this proxy link understates it. Use the substance's own factor rather than the proxy's.
Uncertainty
A minimum-maximum range is defined for this flow. Bounds ship with the dataset on Circa.
Unit
g
NH3 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.

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:
  • EPA Subpart I
  • 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
7664-41-7
ecoinvent 3.12 elementary flow
Ammonia
Uncertainty
A minimum-maximum range is defined for this flow. Bounds ship with the dataset on Circa.
Unit
g
CF4 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
75-73-0
ecoinvent 3.12 elementary flow
Tetrafluoromethane
Uncertainty
A minimum-maximum range is defined for this flow. Bounds ship with the dataset on Circa.
Unit
g
NF3 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
7783-54-2
ecoinvent 3.12 elementary flow
Nitrogen fluoride
Uncertainty
A minimum-maximum range is defined for this flow. Bounds ship with the dataset on Circa.
Unit
g
F2 Emission to airg
Source citations
Compartment
Air (non-urban air or from high stacks)
CAS number
7782-41-4
ecoinvent 3.12 elementary flow
Fluorine
Uncertainty
A minimum-maximum range is defined for this flow. Bounds ship with the dataset on Circa.
Unit
g
Silicon fluorides (SiFxHy) 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
Compartment
Air (non-urban air or from high stacks)
Formula
SiFxHy
ecoinvent 3.12 elementary flow
Silicon tetrafluoride
Notes
No exact ecoinvent elementary flow represents this unresolved SiFxHy mixture. Silicon tetrafluoride is the nearest silicon-fluoride flow and is used only as a linkage proxy; the UUID must not be read as a SiF4 speciation claim.
Uncertainty
A minimum-maximum range is defined for this flow. Bounds ship with the dataset on Circa.
Unit
g
Silicon tetrafluoride 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.
  • 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.

No source is attached to this row.

Source citations
Not stated
Compartment
Air (non-urban air or from high stacks)
Formula
SiF4
CAS number
7783-61-1
ecoinvent 3.12 elementary flow
Silicon tetrafluoride
Uncertainty
A minimum-maximum range is defined for this flow. Bounds ship with the dataset on Circa.
Unit
g

Emissions to water

6 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
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
SiO2 Emission to waterg
Compartment
Water (surface water)
ecoinvent 3.12 elementary flow
Suspended solids, unspecified
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
  • Calculated from HF 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:
Compartment
Water (surface water)
CAS number
16984-48-8
ecoinvent 3.12 elementary flow
Fluoride
Uncertainty
A minimum-maximum range is defined for this flow. Bounds ship with the dataset on Circa.
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:
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:
Compartment
Water (surface water)
CAS number
7440-38-2
ecoinvent 3.12 elementary flow
Arsenic ion
Uncertainty
No range defined.
Unit
g
Ammonium Emission to waterg
Source citations
Compartment
Water (surface water)
Formula
NH4+
CAS number
14798-03-9
ecoinvent 3.12 elementary flow
Ammonium
Notes
TMAH biodegrades in WWTP; NH4+ mass fraction 18.04/91.15
Uncertainty
No range defined.
Unit
g

Flows not quantified

8 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 (5)

Cu sputtering target Materialkg · ±33.3%
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
  • Applied Materials Endura Impulse PVD
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
±33.3% around the published quantity. The bounds themselves ship with the dataset on Circa.
Unit
kg
Ta sputtering target Materialkg · ±33.3%
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
  • Applied Materials Endura Impulse PVD
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
±33.3% around the published quantity. The bounds themselves ship with the dataset on Circa.
Unit
kg
Cu electroplating anode Materialkg · ±14.3%
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
  • Copper Electroplating Fundamentals. Qnity Electronics
Background data
cut off
Background dataset
Not applicable: this flow is not quantified in the inventory.
Reason
The plating anode for wafer damascene copper is recorded at its authored mass. This dataset carries no separate copper material entry that already accounts for it, so the anode mass is kept here and its upstream burden is left unlinked.
Uncertainty
±14.3% around the published quantity. The bounds themselves ship with the dataset on Circa.
Unit
kg
CMP pad conditioner Materialkg · -51% / +149%
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
Background data
cut off
Background dataset
Not applicable: this flow is not quantified in the inventory.
Reason
Evaluated cutoff. The CMP pad conditioner is a multi-use consumable, not a capital good, so it is assessed for significance rather than excluded as equipment. No vendor publishes a conditioner-disc net mass or a single-number wafer lifetime, so both are bounded from public dimensions, materials and conditioning hours: a Diamonex construction patent for the disc class, a Chia Ping (cpdia) spec table for the largest published disc, a 3M product datasheet for the common class, a published range of conditioning hours from the JEES CMP pad-conditioning operations guide, and a sourced between-wafer conditioning time from a process patent, with an explicit unsourced duty allowance applied as conservatism. The bound treats the whole disc as if it were the significant constituent, because no vendor or standard located publishes the per-disc diamond weight, so no constituent split is claimed. Amortised over the disc's life the contribution stays far below the mass significance line on every affected process, and displacing any material share of process electricity would require an embodied intensity for a steel-bodied abrasive tool orders of magnitude above any plausible value. A shorter alternative lifetime that no primary source corroborates is retained rather than resolved; the cutoff holds under it too. The constituent classes (stainless steel, Ni bond/braze, diamond as carbon) raise no toxicity, resource-depletion or water flag at this scale, so insignificance holds across all impact categories. No ecoinvent target exists to proxy against: the background database carries no synthetic-diamond or diamond-grit activity. The dataset export carries the full bounding arithmetic and the complete patent and vendor citations omitted here.
Uncertainty
-51% / +149% around the published quantity. The bounds themselves ship with the dataset on Circa.
Unit
kg
Ne Process gasg · -45.8% / +33.3%
Source citations
Background data
cut off
Background dataset
Not applicable: this flow is not quantified in the inventory.
Reason
Neon consumption (excimer-laser buffer gas) is recorded in this inventory. Upstream production is excluded under the declared cut-off criteria. It is an inert noble gas recovered as a byproduct of cryogenic air separation, with a contribution below the significance threshold.
Uncertainty
-45.8% / +33.3% around the published quantity. The bounds themselves ship with the dataset on Circa.
Unit
g

Not modelled (1)

Slurry solids (silica/ceria) Process chemicalg · -51.6% / +141.9%
Derivation basis
  • Calculated from slurry volume and solids content

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:
Background data
not modelled
Background dataset
Not applicable: this flow is not quantified in the inventory.
Reason
Abrasive solids are a constituent of the CMP slurry inputs already carried in this inventory; attaching a separate upstream dataset here would count the same material twice.
Uncertainty
-51.6% / +141.9% around the published quantity. The bounds themselves ship with the dataset on Circa.
Unit
g

Not quantified - no background dataset available (2)

Reticle/Photomask Materialunits · -0% / +9900%
Source citations
Background data
no background dataset
Background dataset
Not applicable: this flow is not quantified in the inventory.
Reason
The lithography pattern master, treated as a consumable rather than as capital equipment and amortised across the production run it prints. No photomask production dataset exists in the background database used for linkage, and no substitute is attached. The amortised quantity is recorded here and its upstream production is left unlinked.
Uncertainty
-0% / +9900% around the published quantity. The bounds themselves ship with the dataset on Circa.
Unit
units
Scrubber media (dry-bed chemisorbent) Process chemicalg · -95% / +50%
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 (3)

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

  • The fate of the copper removed at the back-end metal-layer polishing step is unresolved in this inventory. No route is asserted for it, so no row here identifies that copper leaving in the wastewater or in the polishing residue.
  • Scenario selection changes gas-recovery emissions and water recycling; process and facility electricity do not change because recovery-equipment energy is outside the current model.

General

  • Not quantifiedHelium consumed by fab support systems - chiefly electrostatic-chuck backside wafer cooling, with smaller purges on deep-ultraviolet laser optics, leak detection and carrier-gas duty - is not quantified in this inventory. No public evidence resolves those routes to a per-wafer amount, so fab helium is under-reported here.

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