Registration Dossier

Data platform availability banner - registered substances factsheets

Please be aware that this old REACH registration data factsheet is no longer maintained; it remains frozen as of 19th May 2023.

The new ECHA CHEM database has been released by ECHA, and it now contains all REACH registration data. There are more details on the transition of ECHA's published data to ECHA CHEM here.

Diss Factsheets

Physical & Chemical properties

Partition coefficient

Currently viewing:

Administrative data

Link to relevant study record(s)

Referenceopen allclose all

Endpoint:
partition coefficient
Type of information:
experimental study
Adequacy of study:
key study
Reliability:
2 (reliable with restrictions)
Rationale for reliability incl. deficiencies:
other: Non-GLP, guideline, available as an unpublished report, acceptable with restrictions
Qualifier:
according to guideline
Guideline:
OECD Guideline 117 (Partition Coefficient (n-octanol / water), HPLC Method)
GLP compliance:
not specified
Remarks:
No data reported
Type of method:
HPLC method
Partition coefficient type:
octanol-water
Analytical method:
high-performance liquid chromatography
Type:
log Pow
Partition coefficient:
7.6 - 7.8
Temp.:
20 °C
pH:
7
Details on results:
Temperature and pH not stated therefore assumed standard.
The test item is a mixture of several constituents. For these mixtures which result in an unresolved band, upper and lower kimits of log Pow are dertermined.
Conclusions:
The partition co-efficient for tributene was determined to be 7.6 to 7.8 (Log Pow).
Executive summary:

The partition co-efficient for tributene was determined to be 7.6 to 7.8 (Log Pow). This study reports no details on GLP compliance but follows a standard guideline and is considered reliable and suitable for use as a key study for this endpoint.

Endpoint:
partition coefficient
Type of information:
(Q)SAR
Adequacy of study:
key study
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:
Episuite and the KOWWIN models are well documented and commonly used QSAR for predicting the partition coefficient of chemicals. Substances within LOA fall within the applicability domain of these models and they have been recommended by ECHA in the Information Requiement Guidelines.
Reason / purpose for cross-reference:
(Q)SAR model reporting (QMRF)
Qualifier:
no guideline required
Principles of method if other than guideline:
KOWWIN (the Log Octanol-Water Partition Coefficient Program) estimates the logarithmic octanol-water partition coefficient (log P) of organic compounds and gives relevant experimental data, if available. KOWWIN requires only a chemical structure to estimate a log P using an atom/fragment contribution method. The model is based on methodlogies laid out in Meylan et al. (1995).
Specific details on test material used for the study:
UVCB: CAS number: 7756-94-7 Representative SMILES structure: CC(C)CCC(C)CCC(C)=C
Key result
Type:
log Pow
Partition coefficient:
6.01
Remarks on result:
other: Result from QSAR prediciton
Conclusions:
The predicted log Kow for this substance is 6.01.
Executive summary:

The log Kow for this substance has been predicted using the EPISUITE v4.11 (2017) program that uses methodology described by Meylan et al. (1995). The predicted log Kow for this substance is 6.01.

Endpoint:
partition coefficient
Type of information:
(Q)SAR
Adequacy of study:
key study
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:
Episuite and the KOWWIN models are well documented and commonly used QSAR for predicting the partition coefficient of chemicals. Substances within LOA fall within the applicability domain of these models and they have been recommended by ECHA in the Information Requiement Guidelines.
Reason / purpose for cross-reference:
(Q)SAR model reporting (QMRF)
Qualifier:
no guideline required
Principles of method if other than guideline:
KOWWIN (the Log Octanol-Water Partition Coefficient Program) estimates the logarithmic octanol-water partition coefficient (log P) of organic compounds and gives relevant experimental data, if available. KOWWIN requires only a chemical structure to estimate a log P using an atom/fragment contribution method. The model is based on methodlogies laid out in Meylan et al. (1995).
Specific details on test material used for the study:
UVCB: CAS number: 42278-27-3 Representative SMILES structure: C=C(C)CCC(C)CCC(C)CCC(C)CCC(C)C
Key result
Type:
log Pow
Partition coefficient:
9.79
Remarks on result:
other: Result from QSAR prediciton
Conclusions:
The predicted log Kow for this substance is 9.79.
Executive summary:

The log Kow for this substance has been predicted using the EPISUITE v4.11 (2017) program that uses methodology described by Meylan et al. (1995). The predicted log Kow for this substance is 9.79.

Endpoint:
partition coefficient
Type of information:
(Q)SAR
Adequacy of study:
key study
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:
Episuite and the KOWWIN models are well documented and commonly used QSAR for predicting the partition coefficient of chemicals. Substances within LOA fall within the applicability domain of these models and they have been recommended by ECHA in the Information Requiement Guidelines.
Reason / purpose for cross-reference:
(Q)SAR model reporting (QMRF)
Qualifier:
no guideline required
Principles of method if other than guideline:
KOWWIN (the Log Octanol-Water Partition Coefficient Program) estimates the logarithmic octanol-water partition coefficient (log P) of organic compounds and gives relevant experimental data, if available. KOWWIN requires only a chemical structure to estimate a log P using an atom/fragment contribution method. The model is based on methodlogies laid out in Meylan et al. (1995).
Specific details on test material used for the study:
SMILES structure: C=C(CC(C)(C)C)C
Key result
Type:
log Pow
Partition coefficient:
4.08
Remarks on result:
other: Result from QSAR prediciton
Conclusions:
The predicted log Kow for this substance is 4.08.
Executive summary:

The log Kow for this substance has been predicted using the EPISUITE v4.11 (2017) program that uses methodology described by Meylan et al. (1995). The predicted log Kow for this substance is 4.08.
.

Endpoint:
partition coefficient
Type of information:
(Q)SAR
Adequacy of study:
key study
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:
Episuite and the KOWWIN models are well documented and commonly used QSAR for predicting the partition coefficient of chemicals. Substances within LOA fall within the applicability domain of these models and they have been recommended by ECHA in the Information Requiement Guidelines.
Reason / purpose for cross-reference:
(Q)SAR model reporting (QMRF)
Qualifier:
no guideline required
Principles of method if other than guideline:
KOWWIN (the Log Octanol-Water Partition Coefficient Program) estimates the logarithmic octanol-water partition coefficient (log P) of organic compounds and gives relevant experimental data, if available. KOWWIN requires only a chemical structure to estimate a log P using an atom/fragment contribution method. The model is based on methodlogies laid out in Meylan et al. (1995).
Specific details on test material used for the study:
UVCB: CAS number: 91053-00-8 Representative SMILES structure: CC(C)CCC(C)CCC(C)CC=C(C)C
Key result
Type:
log Pow
Partition coefficient:
7.82
Remarks on result:
other: Result from QSAR prediciton
Conclusions:
The predicted log Kow for this substance is 7.82.
Executive summary:

The log Kow for this substance has been predicted using the EPISUITE v4.11 (2017) program that uses methodology described by Meylan et al. (1995). The predicted log Kow for this substance is 7.82.
.

Endpoint:
partition coefficient
Type of information:
(Q)SAR
Adequacy of study:
key study
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:
Episuite and the KOWWIN models are well documented and commonly used QSAR for predicting the partition coefficient of chemicals. Substances within LOA fall within the applicability domain of these models and they have been recommended by ECHA in the Information Requiement Guidelines.
Reason / purpose for cross-reference:
(Q)SAR model reporting (QMRF)
Qualifier:
no guideline required
Principles of method if other than guideline:
KOWWIN (the Log Octanol-Water Partition Coefficient Program) estimates the logarithmic octanol-water partition coefficient (log P) of organic compounds and gives relevant experimental data, if available. KOWWIN requires only a chemical structure to estimate a log P using an atom/fragment contribution method. The model is based on methodlogies laid out in Meylan and Howard (1995).
Specific details on test material used for the study:
UVCB: CAS number: 91053-01-9 Representative SMILES structure: CC(C)CCC(C)CCC(C)C
Key result
Type:
log Pow
Partition coefficient:
6.01
Remarks on result:
other: Result from QSAR prediciton
Conclusions:
The predicted log Kow for this substance is 6.01.
Executive summary:

The log Kow for this substance has been predicted using the EPISUITE v4.11 (2017) program that uses methodology described by Meylan and Howard (1995). The predicted log Kow for this substance is 6.01.

Endpoint:
partition coefficient
Type of information:
(Q)SAR
Adequacy of study:
key study
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:
Episuite and the KOWWIN models are well documented and commonly used QSAR for predicting the partition coefficient of chemicals. Substances within LOA fall within the applicability domain of these models and they have been recommended by ECHA in the Information Requiement Guidelines.
Reason / purpose for cross-reference:
(Q)SAR model reporting (QMRF)
Qualifier:
no guideline required
Principles of method if other than guideline:
KOWWIN (the Log Octanol-Water Partition Coefficient Program) estimates the logarithmic octanol-water partition coefficient (log P) of organic compounds and gives relevant experimental data, if available. KOWWIN requires only a chemical structure to estimate a log P using an atom/fragment contribution method. The model is based on methodlogies laid out in Meylan et al. (1995).
Specific details on test material used for the study:
UVCB: CAS number: 9003-29-6 Representative SMILES structure: C=C(CC)C(C)C(C)CC(CC)C(C(C)C)
Key result
Type:
log Pow
Partition coefficient:
7.82
Remarks on result:
other: Result from QSAR prediciton
Conclusions:
The predicted log Kow for this substance is 7.82.
Executive summary:

The log Kow for this substance has been predicted using the EPISUITE v4.11 (2017) program that uses methodology described by Meylan et al. (1995). The predicted log Kow for this substance is 7.82.

Endpoint:
partition coefficient
Type of information:
(Q)SAR
Adequacy of study:
key study
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:
Episuite and the KOWWIN models are well documented and commonly used QSAR for predicting the partition coefficient of chemicals. Substances within LOA fall within the applicability domain of these models and they have been recommended by ECHA in the Information Requiement Guidelines.
Reason / purpose for cross-reference:
(Q)SAR model reporting (QMRF)
Qualifier:
no guideline required
Principles of method if other than guideline:
KOWWIN (the Log Octanol-Water Partition Coefficient Program) estimates the logarithmic octanol-water partition coefficient (log P) of organic compounds and gives relevant experimental data, if available. KOWWIN requires only a chemical structure to estimate a log P using an atom/fragment contribution method. The model is based on methodlogies laid out in Meylan et al. (1995).
Specific details on test material used for the study:
UVCB: CAS number: 97280-83-6 Representative SMILES structure: C=C(C)CCCCCCCCC
Key result
Type:
log Pow
Partition coefficient:
6.15
Remarks on result:
other: Result from QSAR prediciton
Conclusions:
The predicted log Kow for this substance is 6.15.
Executive summary:

The log Kow for this substance has been predicted using the EPISUITE v4.11 (2017) program that uses methodology described by Meylan et al. (1995). The predicted log Kow for this substance is 6.15.

Description of key information

The partition co-efficient for tributene (C12) was determined to be 7.6 to 7.8 (Log Kow), based on the OECD Guideline 117 (Partition Coefficient (n-octanol / water), HPLC Method).

In the absence of measured data for other butylene oligomers, the partition coefficient was estimated using KOWWIN in EPISuite 4 (v4 .1). The predicted log Kow for the butylene oligomers (C8 -C20) ranged from 4.08 - 9.79.

Key value for chemical safety assessment

Additional information