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Main Author:	Yakovlev, Ivan
Format:	Recurso digital
Language:	English
Published:	Zenodo 2025
Online Access:	https://doi.org/10.5281/zenodo.18242974
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_version_	1866901585500569600
author	Yakovlev, Ivan
author_facet	Yakovlev, Ivan
contents	<p>This dataset is an extended version of the "Wikipedia Molecules Properties Dataset" with added SMILES representations, additional physicochemical properties calculated using the thermo library, and chemical classification according to the ClassyFire system for approximately 4,200 compounds.</p> <h2>Key Features</h2> <ul> <li>Original structural formulas taken from the Wikipedia Molecules Properties Dataset (15,000+ molecules)</li> <li>SMILES representations obtained for ~4,200 compounds extracted from structural formulas using the thermo library</li> <li>Calculated physicochemical properties (melting point, boiling point, etc.) obtained using the thermo library</li> <li>Chemical classification according to the ClassyFire system (Kingdom, Superclass, Class, Subclass, etc.)</li> </ul> <h2>Feature Description</h2> <ul> <li>name: Name of the chemical compound</li> <li>formula: Chemical formula of the compound</li> <li>CAS: Unique CAS (Chemical Abstracts Service) identification number</li> <li>smiles: Molecular structure representation in SMILES format (Simplified Molecular Input Line Entry System)</li> <li>InChI: International Chemical Identifier</li> <li>InChIKey: Hashed version of InChI for quick searching</li> <li>molecular_weight: Molecular weight of the compound (g/mol)</li> <li>melting_point_K: Melting point in Kelvin</li> <li>boiling_point_K: Boiling point in Kelvin</li> <li>heat_of_fusion: Heat of fusion (enthalpy of fusion), J/mol</li> <li>heat_of_vaporization: Heat of vaporization (enthalpy of vaporization), J/mol</li> <li>critical_temperature: Critical temperature, K</li> <li>critical_pressure: Critical pressure, Pa</li> <li>flash_point: Flash point, K</li> <li>logP: Octanol-water partition coefficient (measure of lipophilicity)</li> <li>improved_name: Improved/standardized name of the compound</li> <li>kingdom: Kingdom in chemical taxonomy</li> <li>superclass: Superclass of the compound</li> <li>class: Class of the compound in chemical taxonomy</li> <li>direct_parent: Direct parent class of the compound</li> <li>substituents: Substituents and functional groups in the compound</li> </ul> <h2>Tools and Resources Used</h2> <ul> <li><a href="https://www.kaggle.com/datasets/thedevastator/wikipedia-molecules-properties-dataset?resource=download" target="_blank" rel="noopener">Wikipedia Molecules Properties Dataset</a>: the dataset used as the foundation</li> <li><a href="https://pypi.org/project/thermo/" target="_blank" rel="nofollow noopener noreferrer">Thermo</a>: A library for calculating thermodynamic and transport properties of chemicals</li> <li><a href="http://classyfire.wishartlab.com/" target="_blank" rel="nofollow noopener noreferrer">ClassyFire</a>: A chemical taxonomy system and classifier for small molecules</li> </ul> <h2>License</h2> <p>CC0: Public Domain - This dataset is in the public domain. You can copy, modify, distribute and perform the data, even for commercial purposes, all without asking permission.</p> <h2>Citation</h2> <p>When using this dataset, please cite:</p> <ul> <li>Original dataset: <a href="https://www.kaggle.com/datasets/thedevastator/wikipedia-molecules-properties-dataset?resource=download" target="_blank" rel="noopener">Wikipedia Molecules Properties Dataset</a></li> <li>This extended dataset: "<a href="https://www.kaggle.com/datasets/ivanyakovlevg/physical-and-chemical-properties-of-substances" target="_blank" rel="noopener">Ivan Yakovlev G</a>. (2024). Physical and Chemical Properties of Substances. Kaggle."</li> </ul> <h2>Contact Information</h2> <p>Ivan Yakovlev<br>Email: <a href="mailto:yakovlev.ivan.g@gmail.com" rel="noreferrer nofollow">yakovlev.ivan.g@gmail.com</a><br>LinkedIn: <a href="http://www.linkedin.com/in/ivanyakovlevg" target="_blank" rel="nofollow noopener noreferrer">www.linkedin.com/in/ivanyakovlevg</a></p> <h2>Version 3.0.0 (2025-04-28)</h2> <h3>Major Enhancements</h3> <ul> <li>Added functional group classification: Each compound is now classified according to 26 different functional groups including alcohols, alkanes, aromatics, ethers, and more</li> <li>SMILES representation: Added canonical SMILES strings for all compounds with valid InChI identifiers</li> <li>Organic/inorganic classification: Each compound is now labeled as organic or inorganic based on chemical structure</li> </ul> <h3>Data Processing Improvements</h3> <ul> <li>InChI standardization: Fixed inconsistent InChI prefixes, ensuring all follow the standard "InChI=1S/" format</li> <li>Structure validation: All molecular structures have been validated using RDKit's chemical informatics toolkit</li> <li>Missing data handling: Improved handling of compounds with invalid or missing structural identifiers</li> </ul> <h3>Technical Details</h3> <ul> <li>Used RDKit for chemical structure manipulation and SMILES conversion</li> <li>Applied Thermo library for functional group classification</li> <li>Conversion success rate: 98.7% of compounds with valid InChI were successfully converted to SMILES</li> <li>Functional group identification completed for 97.9% of valid structures</li> </ul> <h3>Dataset Statistics</h3> <ul> <li>Top 5 functional groups identified: <ul> <li>Organic compounds: 76.4%</li> <li>Hydrocarbons: 34.2%</li> <li>Aromatics: 23.7%</li> <li>Alcohols: 19.8%</li> <li>Ethers: 14.3%</li> </ul> </li> </ul> <h3>Known Limitations</h3> <ul> <li>Approximately 1.3% of InChI strings could not be converted to SMILES due to structural inconsistencies</li> <li>Some complex metal-organic compounds may have inconsistent functional group classification</li> <li>Polymers and mixtures may have limited functional group detection accuracy</li> </ul> <h3>Potential Applications</h3> <ul> <li>Enhanced structure-activity relationship modeling</li> <li>More precise chemical similarity searches</li> <li>Improved filtering and grouping based on chemical functionality</li> <li>Better substructure-based analysis for drug discovery and material science</li> </ul>
format	Recurso digital
id	zenodo_https___doi_org_10_5281_zenodo_18242974
institution	Zenodo
language	eng
publishDate	2025
publisher	Zenodo
record_format	zenodo
spellingShingle	Physical and Chemical Properties of Substances Yakovlev, Ivan <p>This dataset is an extended version of the "Wikipedia Molecules Properties Dataset" with added SMILES representations, additional physicochemical properties calculated using the thermo library, and chemical classification according to the ClassyFire system for approximately 4,200 compounds.</p> <h2>Key Features</h2> <ul> <li>Original structural formulas taken from the Wikipedia Molecules Properties Dataset (15,000+ molecules)</li> <li>SMILES representations obtained for ~4,200 compounds extracted from structural formulas using the thermo library</li> <li>Calculated physicochemical properties (melting point, boiling point, etc.) obtained using the thermo library</li> <li>Chemical classification according to the ClassyFire system (Kingdom, Superclass, Class, Subclass, etc.)</li> </ul> <h2>Feature Description</h2> <ul> <li>name: Name of the chemical compound</li> <li>formula: Chemical formula of the compound</li> <li>CAS: Unique CAS (Chemical Abstracts Service) identification number</li> <li>smiles: Molecular structure representation in SMILES format (Simplified Molecular Input Line Entry System)</li> <li>InChI: International Chemical Identifier</li> <li>InChIKey: Hashed version of InChI for quick searching</li> <li>molecular_weight: Molecular weight of the compound (g/mol)</li> <li>melting_point_K: Melting point in Kelvin</li> <li>boiling_point_K: Boiling point in Kelvin</li> <li>heat_of_fusion: Heat of fusion (enthalpy of fusion), J/mol</li> <li>heat_of_vaporization: Heat of vaporization (enthalpy of vaporization), J/mol</li> <li>critical_temperature: Critical temperature, K</li> <li>critical_pressure: Critical pressure, Pa</li> <li>flash_point: Flash point, K</li> <li>logP: Octanol-water partition coefficient (measure of lipophilicity)</li> <li>improved_name: Improved/standardized name of the compound</li> <li>kingdom: Kingdom in chemical taxonomy</li> <li>superclass: Superclass of the compound</li> <li>class: Class of the compound in chemical taxonomy</li> <li>direct_parent: Direct parent class of the compound</li> <li>substituents: Substituents and functional groups in the compound</li> </ul> <h2>Tools and Resources Used</h2> <ul> <li><a href="https://www.kaggle.com/datasets/thedevastator/wikipedia-molecules-properties-dataset?resource=download" target="_blank" rel="noopener">Wikipedia Molecules Properties Dataset</a>: the dataset used as the foundation</li> <li><a href="https://pypi.org/project/thermo/" target="_blank" rel="nofollow noopener noreferrer">Thermo</a>: A library for calculating thermodynamic and transport properties of chemicals</li> <li><a href="http://classyfire.wishartlab.com/" target="_blank" rel="nofollow noopener noreferrer">ClassyFire</a>: A chemical taxonomy system and classifier for small molecules</li> </ul> <h2>License</h2> <p>CC0: Public Domain - This dataset is in the public domain. You can copy, modify, distribute and perform the data, even for commercial purposes, all without asking permission.</p> <h2>Citation</h2> <p>When using this dataset, please cite:</p> <ul> <li>Original dataset: <a href="https://www.kaggle.com/datasets/thedevastator/wikipedia-molecules-properties-dataset?resource=download" target="_blank" rel="noopener">Wikipedia Molecules Properties Dataset</a></li> <li>This extended dataset: "<a href="https://www.kaggle.com/datasets/ivanyakovlevg/physical-and-chemical-properties-of-substances" target="_blank" rel="noopener">Ivan Yakovlev G</a>. (2024). Physical and Chemical Properties of Substances. Kaggle."</li> </ul> <h2>Contact Information</h2> <p>Ivan Yakovlev<br>Email: <a href="mailto:yakovlev.ivan.g@gmail.com" rel="noreferrer nofollow">yakovlev.ivan.g@gmail.com</a><br>LinkedIn: <a href="http://www.linkedin.com/in/ivanyakovlevg" target="_blank" rel="nofollow noopener noreferrer">www.linkedin.com/in/ivanyakovlevg</a></p> <h2>Version 3.0.0 (2025-04-28)</h2> <h3>Major Enhancements</h3> <ul> <li>Added functional group classification: Each compound is now classified according to 26 different functional groups including alcohols, alkanes, aromatics, ethers, and more</li> <li>SMILES representation: Added canonical SMILES strings for all compounds with valid InChI identifiers</li> <li>Organic/inorganic classification: Each compound is now labeled as organic or inorganic based on chemical structure</li> </ul> <h3>Data Processing Improvements</h3> <ul> <li>InChI standardization: Fixed inconsistent InChI prefixes, ensuring all follow the standard "InChI=1S/" format</li> <li>Structure validation: All molecular structures have been validated using RDKit's chemical informatics toolkit</li> <li>Missing data handling: Improved handling of compounds with invalid or missing structural identifiers</li> </ul> <h3>Technical Details</h3> <ul> <li>Used RDKit for chemical structure manipulation and SMILES conversion</li> <li>Applied Thermo library for functional group classification</li> <li>Conversion success rate: 98.7% of compounds with valid InChI were successfully converted to SMILES</li> <li>Functional group identification completed for 97.9% of valid structures</li> </ul> <h3>Dataset Statistics</h3> <ul> <li>Top 5 functional groups identified: <ul> <li>Organic compounds: 76.4%</li> <li>Hydrocarbons: 34.2%</li> <li>Aromatics: 23.7%</li> <li>Alcohols: 19.8%</li> <li>Ethers: 14.3%</li> </ul> </li> </ul> <h3>Known Limitations</h3> <ul> <li>Approximately 1.3% of InChI strings could not be converted to SMILES due to structural inconsistencies</li> <li>Some complex metal-organic compounds may have inconsistent functional group classification</li> <li>Polymers and mixtures may have limited functional group detection accuracy</li> </ul> <h3>Potential Applications</h3> <ul> <li>Enhanced structure-activity relationship modeling</li> <li>More precise chemical similarity searches</li> <li>Improved filtering and grouping based on chemical functionality</li> <li>Better substructure-based analysis for drug discovery and material science</li> </ul>
title	Physical and Chemical Properties of Substances
url	https://doi.org/10.5281/zenodo.18242974

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