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Diss Factsheets
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EC number: 230-796-7 | CAS number: 7324-02-9
- 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
![](https://echa.europa.eu/o/diss-blank-theme/images/factsheets/A-REACH/factsheet/print_physical-and-chemical-properties.png)
Density
Administrative data
- Endpoint:
- relative density
- 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
ACD/Percepta
2. MODEL (incl. version number)
ACD/Labs Release 2020.2.0
3. SMILES OR OTHER IDENTIFIERS USED AS INPUT FOR THE MODEL
SMILES : C=C(C#N)C(=O)OCC=C
4. SCIENTIFIC VALIDITY OF THE (Q)SAR MODEL
Algorithms for Calculating Basic Physicochemical Properties
At the heart of the additive-constitutive calculation algorithm of all physicochemical properties in ACD/Percepta lies the presumption that these properties can be estimated using additive atomic or group increments. Apart from molecular weight (MW), which is trivial to calculate, the algorithms may be divided into three general groups:
## Basic macroscopic properties: molar volume (MV), molar refractivity (MR), and parachor (Pr)
## Derived macroscopic properties: density (d), refractive index (n), and surface tension (γ)
## The dielectric constant ε (Permittivity)
Basic macroscopic properties such as molar volume (MV), molar refractivity (MR), and the parachor (Pr) are calculated first for the input structure. The atomic additive increments in such an algorithm depend on the bonds (single, double, aromatic, etc.) of this atom and on neighboring atoms. ACD/Percepta rapidly analyzes the input structure to determine the class of each atom, i.e., whether it is cyclic, aromatic, aliphatic, etc.
The prediction algorithms for density (d), refractive index (n) and surface tension (γ) are founded on well-known physicochemical formula which can be found in literature on physicochemical properties of compounds. They express d, n, and γ as functions of MV, MR, or Pr. Once the MV, MR, or Pr, have been predicted by additive means, it is straightforward to predict d, n, and γ using these formula.
The determination of the additive-constitutive atomic increments for MV, MR, and Pr were obtained internally by ACD/Labs scientists using large experimental databases relating structure to density, refractive index, and surface tension. The MV, MR, and Pr were recalculated from d, n, and γ. These parameters are proprietary information of ACD/Labs, Inc.
The prediction of the dielectric constant ε (permittivity) resembles very closely the prediction of boiling point, which is available as a separate Prediction Module in ACD/Percepta. Senior scientists at ACD/Labs discovered an additive function, which relates the dielectric constant to other macroscopic properties which can be additively treated, such as MV. Once this relationship was discovered, the additive-constitutive atomic increments for this function were obtained using large databases consisting of molecular structures and their observed dielectric constants. Using the function and estimated MV for the input structure, its dielectric constant can be quickly predicted.
Molar Volume, MV
By definition,
MV = MW / d
ACD/Percepta calculates molar volume from additive increments. The additive atomic increments were obtained using a database of density and calculated MW.
Note: The obtained MV value is used as an input parameter for further calculations, but is not displayed in the module interface itself.
Molar Refractivity, MR
The Lorentz-Lorenz equation relates refractive index, density, and refractive index:
MR = (n2 - 1) / (n2 + 2) x MW / d
ACD/Percepta calculates molar refractivity from additive increments. The additive atomic increments were obtained using a database of density, refractive index, and calculated MW.
Note: The obtained MR value is used as an input parameter for further calculations, but is not displayed in the module interface itself.
Parachor, Pr
By definition,
Pr = (MW / d) γ1/4
ACD/Percepta calculates the parachor from additive increments. The additive atomic increments were obtained using a database of density, surface tension, and calculated MW.
Density, d
By definition,
d = MW / MV
ACD/Percepta calculates the density from MW and the calculated molar volume (see above).
Data source
Reference
- Title:
- ACD/Labs Release 2020.2.0
- Year:
- 2 021
- Bibliographic source:
- ACD/Percepta PhysChem
Materials and methods
Test guideline
- Guideline:
- other: REACH Guidance on QSARs R.6
Test material
- Reference substance name:
- Allyl 2-cyanoacrylate
- EC Number:
- 230-796-7
- EC Name:
- Allyl 2-cyanoacrylate
- Cas Number:
- 7324-02-9
- Molecular formula:
- C7H7NO2
- IUPAC Name:
- prop-2-en-1-yl 2-cyanoprop-2-enoate
- Test material form:
- liquid
1
- Specific details on test material used for the study:
- C=C(C#N)C(=O)OCC=C
Results and discussion
Density
- Key result
- Type:
- relative density
- Density:
- 1.05 g/cm³
- Temp.:
- 20 °C
- Remarks on result:
- other: QSAR predicted value
Applicant's summary and conclusion
- Conclusions:
- ACD/Percepta predicted that allyl 2-cyanoacrylatehas a relative density of 1.05.
Information on Registered Substances comes from registration dossiers which have been assigned a registration number. The assignment of a registration number does however not guarantee that the information in the dossier is correct or that the dossier is compliant with Regulation (EC) No 1907/2006 (the REACH Regulation). This information has not been reviewed or verified by the Agency or any other authority. The content is subject to change without prior notice.
Reproduction or further distribution of this information may be subject to copyright protection. Use of the information without obtaining the permission from the owner(s) of the respective information might violate the rights of the owner.
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