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EC number: 212-611-1 | CAS number: 831-82-3
- Life Cycle description
- Uses advised against
- Endpoint summary
- Appearance / physical state / colour
- Melting point / freezing point
- Boiling point
- Density
- Particle size distribution (Granulometry)
- Vapour pressure
- Partition coefficient
- Water solubility
- Solubility in organic solvents / fat solubility
- Surface tension
- Flash point
- Auto flammability
- Flammability
- Explosiveness
- Oxidising properties
- Oxidation reduction potential
- Stability in organic solvents and identity of relevant degradation products
- Storage stability and reactivity towards container material
- Stability: thermal, sunlight, metals
- pH
- Dissociation constant
- Viscosity
- Additional physico-chemical information
- Additional physico-chemical properties of nanomaterials
- Nanomaterial agglomeration / aggregation
- Nanomaterial crystalline phase
- Nanomaterial crystallite and grain size
- Nanomaterial aspect ratio / shape
- Nanomaterial specific surface area
- Nanomaterial Zeta potential
- Nanomaterial surface chemistry
- Nanomaterial dustiness
- Nanomaterial porosity
- Nanomaterial pour density
- Nanomaterial photocatalytic activity
- Nanomaterial radical formation potential
- Nanomaterial catalytic activity
- Endpoint summary
- Stability
- Biodegradation
- Bioaccumulation
- Transport and distribution
- Environmental data
- Additional information on environmental fate and behaviour
- Ecotoxicological Summary
- Aquatic toxicity
- Endpoint summary
- Short-term toxicity to fish
- Long-term toxicity to fish
- Short-term toxicity to aquatic invertebrates
- Long-term toxicity to aquatic invertebrates
- Toxicity to aquatic algae and cyanobacteria
- Toxicity to aquatic plants other than algae
- Toxicity to microorganisms
- Endocrine disrupter testing in aquatic vertebrates – in vivo
- Toxicity to other aquatic organisms
- Sediment toxicity
- Terrestrial toxicity
- Biological effects monitoring
- Biotransformation and kinetics
- Additional ecotoxological information
- Toxicological Summary
- Toxicokinetics, metabolism and distribution
- Acute Toxicity
- Irritation / corrosion
- Sensitisation
- Repeated dose toxicity
- Genetic toxicity
- Carcinogenicity
- Toxicity to reproduction
- Specific investigations
- Exposure related observations in humans
- Toxic effects on livestock and pets
- Additional toxicological data
Partition coefficient
Administrative data
Link to relevant study record(s)
- Endpoint:
- partition coefficient
- Type of information:
- (Q)SAR
- Adequacy of study:
- weight of evidence
- 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 limited documentation / justification
- Justification for type of information:
- 1. SOFTWARE
and MODEL
EPI Suite version 4.11
Kowwin v1.68 (september 2010)
2. SMILES OR OTHER IDENTIFIERS USED AS INPUT FOR THE MODEL
SMILES : O(c(ccc(O)c1)c1)c(cccc2)c2
NAME : Phenol, 4-phenoxy-
CAS Number : 831-82-3
3. SCIENTIFIC VALIDITY OF THE (Q)SAR MODEL
No formal QMRF assessment of the model is currently available, however, the user's guide describes all the information.
- Defined endpoint: Partition coefficient
- Methodology : KOWWIN uses a "fragment constant" methodology to predict log P. In a "fragment constant" method, a structure is divided into fragments (atom or larger functional groups) and coefficient values of each fragment or group are summed together to yield the log P estimate. KOWWIN’s methodology is known as an Atom/Fragment Contribution (AFC) method. Coefficients for individual fragments and groups were derived by multiple regression of 2447 reliably measured log P values. KOWWIN’s "reductionist" fragment constant methodology (i.e. derivation via multiple regression) differs from the "constructionist" fragment constant methodology of Hansch and Leo (1979) that is available in the CLOGP Program (Daylight, 1995). See the Meylan and Howard (1995) journal article for a more complete description of KOWWIN’s methodology.
To estimate log P, KOWWIN initially separates a molecule into distinct atom/fragments. In general, each non-hydrogen atom (e.g. carbon, nitrogen, oxygen, sulfur, etc.) in a structure is a "core" for a fragment; the exact fragment is determined by what is connected to the atom. Several functional groups are treated as core "atoms"; these include carbonyl (C=O), thiocarbonyl (C=S), nitro (-NO2), nitrate (ONO2), cyano (-C/N), and isothiocyanate (-N=C=S). Connections to each core "atom" are either general or specific; specific connections take precedence over general connections.
4. APPLICABILITY DOMAIN
No formal QMRF assessment of the model is currently available, however, the user's guide describes all the information.
- Descriptor domain: organic chemical
- Structural and mechanistic domains:
Training Set Molecular Weights: Minimum MW: 18.02 Maximum MW: 719.92 Average MW: 199.98
Appendix D of the KOWWIN Help gives the maximum number of fragments that occur in any individual compound of the training set.
- Similarity with analogues in the training set: The KOWWIN training and validation datasets can be downloaded from the Internet at http://esc.syrres.com/interkow/KowwinData.htm
5. References
Daylight. 1995. CLOGP Program. Daylight Chemical Information Systems. Von Karman Ave., Irvine, CA 92715. (web-site as of March 2008: http://www.daylight.com/)
Hansch, C and Leo, A.J. 1979. Substituent Constants for Correlation Analysis in Chemistry and Biology; Wiley: New York, 1979.
Meylan, W.M. and P.H. Howard. 1995. Atom/fragment contribution method for estimating octanol-water partition coefficients. J. Pharm. Sci. 84: 83-92. - Guideline:
- other: REACH guidance on QSARs R.6
- Principles of method if other than guideline:
- - Software tool(s) used including version:
Kowwin v1.68 (september 2010)
- Model(s) used: Kowwin v1.68 (september 2010)
- Model description: see field 'Justification for type of information"
- Justification of QSAR prediction: see field 'Attached justification' - GLP compliance:
- no
- Specific details on test material used for the study:
- SMILES : O(c(ccc(O)c1)c1)c(cccc2)c2
- Type:
- log Pow
- Partition coefficient:
- ca. 3.57
- Remarks on result:
- other: QSAR predicted value
- Conclusions:
- KOWWIN predicted that 4 -Phenoxyphenol has a logKow = 3.57
- Executive summary:
KOWWIN predicted that 4 -Phenoxyphenol has a logKow = 3.57
- Endpoint:
- partition coefficient
- Type of information:
- (Q)SAR
- Adequacy of study:
- weight of evidence
- 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
and MODEL
OPERA-Model for Octanol-water partition
OPERA v1.5
2. SMILES OR OTHER IDENTIFIERS USED AS INPUT FOR THE MODEL
SMILES : O(c(ccc(O)c1)c1)c(cccc2)c2
NAME : Phenol, 4-phenoxy-
CAS Number : 831-82-3
3. SCIENTIFIC VALIDITY OF THE (Q)SAR MODEL
See QMRF_LogKow_PhenoxyPhenol-OPERA_Q17-16-0016_document
4. APPLICABILITY DOMAIN
See QMRF_LogKow_PhenoxyPhenol-OPERA_Q17-16-0016_document - Guideline:
- other: REACH guidance on QSARs R.6
- Principles of method if other than guideline:
- - Software tool(s) used including version:
OPERA-model for octano-water paritition
- Model(s) used: v1.5 (2016)
- Model description: see field 'Justification for type of information"
- Justification of QSAR prediction: see field 'Attached justification' - GLP compliance:
- no
- Specific details on test material used for the study:
- SMILES : O(c(ccc(O)c1)c1)c(cccc2)c2
- Type:
- log Pow
- Partition coefficient:
- ca. 3.38
- Remarks on result:
- other: QSAR predicted value
- Conclusions:
- OPERA predicted that 4 -Phenoxyphenol has a logKow = 3.38
- Executive summary:
OPERA predicted that 4 -Phenoxyphenol has a logKow = 3.38
- Endpoint:
- partition coefficient
- Type of information:
- (Q)SAR
- Adequacy of study:
- weight of evidence
- 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
Vega Version 1.1.4
Calculation core version 1.2.4
2. MODEL
Three models are used :
LogPModel version 1.1.4
MLogP Model Version 1.0.0
ALogP Model 1.0.0
3. SMILES OR OTHER IDENTIFIERS USED AS INPUT FOR THE MODEL
SMILES : O(c(ccc(O)c1)c1)c(cccc2)c2
4. SCIENTIFIC VALIDITY OF THE (Q)SAR MODEL AND APPLICABILITY DOMAIN
See QMRF_LogKow_PhenoxyPhenol-VEGA-AlogP-LogP-MLogP - Guideline:
- other: REACH guidance on QSARs R.6
- Principles of method if other than guideline:
- - Software tool(s) used including version:
Vega Version 1.1.4 - Calculation core version 1.2.4
- Model(s) used: LogPModel version 1.1.4 ; MLogP Model Version 1.0.0 ; ALogP Model 1.0.0
- Model description: see field 'Justification for type of information"
- Justification of QSAR prediction: see field 'Attached justification' - GLP compliance:
- no
- Specific details on test material used for the study:
- SMILES : O(c(ccc(O)c1)c1)c(cccc2)c2
- Type:
- log Pow
- Partition coefficient:
- ca. 3.57
- Remarks on result:
- other: QSAR predicted value (LogP model)
- Remarks:
- Good reliability
- Type:
- log Pow
- Partition coefficient:
- ca. 2.78
- Remarks on result:
- other: QSAR predicted value (MLogP)
- Remarks:
- Moderate reliability
- Type:
- log Pow
- Partition coefficient:
- ca. 3.12
- Remarks on result:
- other: QSAR Predicted (ALogP)
- Remarks:
- Good reliability
- 3.57 with LogPmodel (good reliability)
- 3.12 with ALogP (good reliability)
- 2.78 with MLogP (moderate reliability)
- Conclusions:
- Vega predicted three logKow values for 4 -Phenoxyphenol :
3.57 with LogPmodel (good reliability)
3.12 with ALogP (good reliability)
2.78 with MLogP (moderate reliability)
The predicted logKow values with Vega is [3.12 - 3.57] - Executive summary:
VEGA predicted that 4 -Phenoxyphenol has a logKow : 3.12 or 3.57 (good reliability)
- Endpoint:
- partition coefficient
- Type of information:
- experimental study
- Adequacy of study:
- other information
- Reliability:
- 4 (not assignable)
- Rationale for reliability incl. deficiencies:
- secondary literature
- Principles of method if other than guideline:
- Not specified
- GLP compliance:
- not specified
- Partition coefficient type:
- octanol-water
- Specific details on test material used for the study:
- Not specified
- Type:
- log Pow
- Partition coefficient:
- ca. 3.35
- Conclusions:
- Hansch and al. determined that 4-phenoxyphenol has a log Kow = 3.35
- Executive summary:
Hansch and al. determined that 4-phenoxyphenol has a log Kow = 3.35
Referenceopen allclose all
KOWWIN predicted that 4 -Phenoxyphenol has a logKow = 3.57
OPERA predicted that 4 -Phenoxyphenol has a logKow = 3.38
Vega predicted three logKow values for 4 -Phenoxyphenol :
Description of key information
- 3.57 with Kowwin
- 3.38 with OPERA
- 3.12 and 3.57 with Vega
QSAR prediction with a good reliability predicted that 4 -PhenoxyPhenol has a logKow:
One Experimental Data was identified for Phenol, 4-Phenoxy, the log Kow is 3.35. This study has a Klimisch cotation 4, it cannot be used has a Key study.
It was therefore retained a value of 3.38 (QSAR value closest to the experimental value and in the mean of the range of predicted values).
Key value for chemical safety assessment
- Log Kow (Log Pow):
- 3.38
- at the temperature of:
- 25 °C
Additional information
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