Amines, di-C16-18-alkylmethyl

Adsorption / desorption

Link to relevant study record(s)

Reference

Endpoint:

adsorption / desorption: screening

Type of information:

(Q)SAR

Adequacy of study:

key study

Study period:

2023

Reliability:

2 (reliable with restrictions)

Rationale for reliability incl. deficiencies:

results derived from a valid (Q)SAR model and falling into its applicability domain, with adequate and reliable documentation / justification

Justification for type of information:

1. SOFTWARE
EPI Suite v4.11

2. MODEL (incl. version number)
KOCWIN v2.00

3. SMILES OR OTHER IDENTIFIERS USED AS INPUT FOR THE MODEL

Only constituents that are present at ≥2% w/w were considered in the fragment-based calculations.

N-methyl-N-tetradecylhexadecan-1-amine
Smiles: CCCCCCCCCCCCCCN(C)CCCCCCCCCCCCCCCC

N-hexadecyl-N-methylhexadecan-1-amine
Smiles: CCCCCCCCCCCCCCCCN(C)CCCCCCCCCCCCCCCC

N-hexadecyl-N-methyloctadecan-1-amine
Smiles: CCCCCCCCCCCCCCCCN(C)CCCCCCCCCCCCCCCCCC

N-methyldioctadecylamine
Smiles: CCCCCCCCCCCCCCCCCCN(C)CCCCCCCCCCCCCCCCCC

Before calculations, weight percentages of constituents are converted to molar percentages using their respective molecular weight (MW).
IUPAC name Cas No.: SMILES MW %w/w Mole %
N-methyl-N-tetradecylhexadecan-1-amine 102091-39-4 CCCCCCCCCCCCCCN(C)CCCCCCCCCCCCCCCC 451.8 2.30 2.6
N-hexadecyl-N-methylhexadecan-1-amine 16724-61-1 CCCCCCCCCCCCCCCCN(C)CCCCCCCCCCCCCCCC 479.9 12.90 13.7
N-Hexadecyl-N-methyloctadecan-1-amine 102091-40-7 CCCCCCCCCCCCCCCCN(C)CCCCCCCCCCCCCCCCCC 508 38.30 38.4
N-methyldioctadecylamine 4088-22-5 CCCCCCCCCCCCCCCCCCN(C)CCCCCCCCCCCCCCCCCC 536 40.50 38.4
94.0 93.1

Abbrev. Cas No.: w/w% Mole % Log Koc Log Koc Log Koc Log Koc
est MCI frac MCI est Kow frac Kow
C14-16 DAM 102091-39-4 2.30 2.6 8.20 0.21 8.49 0.22
C16-16 DAM 16724-61-1 12.90 13.7 8.72 1.20 9.03 1.24
C16-18 DAM 102091-40-7 38.30 38.4 9.25 3.55 9.57 3.68
C18-18 DAM 4088-22-5 40.50 38.4 9.77 3.75 10.12 3.89
94.0 93.1 Weighted*: 9.35 Weighted* 9.69
average average
* Corrected to a mole fraction of 100%


4. SCIENTIFIC VALIDITY OF THE (Q)SAR MODEL
- Defined endpoint: Log Koc (organic carbon/water partition coefficient)
- Unambiguous algorithm: see the method description attached
- Defined domain of applicability: see the method description attached
- Appropriate measures of goodness-of-fit and robustness and predictivity: see the method description attached
- Mechanistic interpretation: see the method description attached
The Log Koc values selected for the KOCWIN training and validation datasets are available via: http://esc.syrres.com/interkow/EpiSuiteData.htm

5. APPLICABILITY DOMAIN
- Model domain: Currently there is no universally accepted definition of model domain. However, users may wish to consider the possibility that bioconcentration factor estimates are less accurate for compounds outside the MW and log Kow/Koc ranges of the training set compounds, and/or that have more instances of a given correction factor than the maximum for all training set compounds. In general, the intended application domain for all models embedded in EPISuite is organic chemicals.
The training set molecular weights are within the range of 68.08 to 991.8 with an average molecular weight of 244 , the log Koc values range from 9.35 to 9.69. This range is however outside the advised range from EUSES which suggests to limit the Koc to 1* 10^6 L/kg. This value will therefore be used for risk assessment purposes.

- Mechanistic domain:
Both QSAR models included in the KOCWIN model in EPISUITE (i.e. Log Koc-MCI and LogKoc-Kow) estimate the Koc using two separate estimation methodologies: (1) estimation using first order Molecular Connectivity Index (MCI) which mathematically describes the shape and charge distribution of the atoms on a molecule and then calculates the distribution accordingly between water and organic carbon is estimated and (2) estimate based on data the distribution of the substance between octanol and water (log Kow) . These log Kow values are mainly obtained empirically. In the absence of experimental values, the values are estimated by KOCWIN using KOWWIN. In general, the MCI methodology is considered to be slightly more accurate (R2 = 0.916) than the Log Kow methodology (R2 = 0.86), although both methods yield good results. KOCWIN calculated the Koc values based on the following equations: Estimation with MCI: log Koc c = 0.5213 MCI + 0.60 Estimation with Log Kow: Log Koc = (0.55313*logKow + 0.9251) and applying substance specific correction factors. This approach is applied to different types of organic compounds including acids and bases. No charged nitrogen compounds (nitrogen with a +5 valence such as quaternary ammonium compounds) can be calculated.
The Log Kow/Koc values selected for the KOCWIN training and validation datasets are available via: http://esc.syrres.com/interkow/EpiSuiteData_ISIS_SDF.htm. This data comes from PHYSPROP (The Physical Properties Database), a collection of a wide variety of resources built by Syracuse Research Corporation (SRC).


- Similarity with analogues in the training set:
Unknown

- Other considerations (as appropriate):
-

6. ADEQUACY OF THE RESULT
The calculated average value calculated from the main fragments of the substance shows that the substance is predicted to sorb strongly to organic carbon. The training set molecular weights are within the range of 68.08 to 991.8 with an average molecular weight o about 500 g/mol, the log Koc values range from 9.35 to 9.69. This range is however outside the advised range from EUSES which suggests to limit the Koc to 1* 10^6 L/kg. This value will therefore be used for risk assessment purposes and is in the absence of measured data considered to be adequate.

Guideline:

other: REACH guidance on QSAR's R.6

Principles of method if other than guideline:

See attached documentation

GLP compliance:

no

Type of method:

other: QSAR

Media:

soil

Radiolabelling:

no

Sample No.:

#1

Phase system:

solids-water in soil

Remarks:

Modelled partitioning between the organic carbon fraction in soil and water (Koc)

Type:

other: The predicted organic carbon normalized equilibrium constant for partitioning between soil and water (Koc)

Value:

1 000 000 L/kg

Temp.:

21 °C

pH:

7

Matrix:

Organic carbon normalized partitioning coefficient considered to be independent of the matrix

Conclusions:

Amines, di-C16-18-alkylmethyl is predicted to sorb strongly to the organic carbon fraction in soil, sediment and sludge.

Executive summary:

No actual data are available for characterizing the partitioning to organic carbon in water (Koc) for Amines, di-C16-18-alkylmethyl . Modelled data are therefore considered to assess this parameter. The result obtained indicates that Amines, di-C16-18-alkylmethyl has an estimated Koc of > 1*10^6 L/kg calculated for its major constituents. On this basis it can be assumed that Amines, di-C16-18-alkylmethyl will not be mobile in soil and sediment.

Because the substance is also readily biodegradable the substance will either be sorbed or biodegraded.

Description of key information

No actual data are available for characterizing the sorption to soil or sediment organic carbon  of Amines, di-C16-18-alkylmethyl . Modelled data are therefore considered to assess this parameter. The result obtained indicates that Amines, di-C16-18-alkylmethyl has an estimated Log Koc of 9.35 to 9.69 L/kg calculated for its major constituents. On this basis it can be assumed that Amines, di-C16-18-alkylmethyl has a high sorption potential and will not be mobile in soil or sediment. 

This range is however outside the advised range from EUSES which suggests to limit the Koc to 1* 10^6 L/kg. This threshold value will therefore be used for risk assessment purposes.

Key value for chemical safety assessment

Koc at 20 °C:

1 000 000

Additional information

Amines, di-C16-18-alkylmethyl has an estimated Log Koc of 9.35 to 9.69 L/kg calculated for its major constituents. This range is however outside the advised range from EUSES which suggests to limit the Koc to 1* 10^6 L/kg. This threshold value will therefore be used for risk assessment purposes.