Computational Exploration of Small Hydrocarbon Networks: A Stochastic Generation and DFT Refinement Framework

Small hydrocarbons are central to astrochemistry due to their prevalence and chemical reactivity across diverse interstellar environments. Here, we present HydroMol, an open-access computational platform designed for systematic exploration and analysis of hydrocarbon chemical spaces, featuring over 2700 neutral <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:semantics> <mml:mrow> <mml:msub><mml:mrow><mml:mtext>C</mml:mtext></mml:mrow> <mml:mrow><mml:mi>n</mml:mi></mml:mrow> </mml:msub> <mml:msub><mml:mrow><mml:mtext>H</mml:mtext></mml:mrow> <mml:mrow><mml:mi>m</mml:mi></mml:mrow> </mml:msub> <mml:mo>(</mml:mo> <mml:mi>n</mml:mi> <mml:mo>,</mml:mo> <mml:mi>m</mml:mi> <mml:mo>=</mml:mo> <mml:mn>1</mml:mn> <mml:mo>-</mml:mo> <mml:mn>10</mml:mn> <mml:mo>)</mml:mo></mml:mrow> <mml:annotation>$$ {\mathrm{C}}_n{\mathrm{H}}_m\left(n,m=1-10\right) $$</mml:annotation></mml:semantics> </mml:math> hydrocarbon structures generated stochastically and refined via density functional theory at B3LYP-D3BJ/def2-SVP level. HydroMol provides detailed molecular geometries, thermodynamic parameters, and electronic properties critical for interpreting astrochemical phenomena and identifying promising observational targets. Our database, hosted within a lightweight client-side web application for rapid search and visualization, introduces approximately 2000 previously unreported hydrocarbons absent in major chemical repositories such as PubChem. Statistical analysis highlights the predominance of structurally simple monocyclic and bicyclic species, characterized by HOMO and LUMO energies centered at approximately <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:semantics><mml:mrow><mml:mo>-</mml:mo> <mml:mn>6</mml:mn></mml:mrow> <mml:annotation>$$ -6 $$</mml:annotation></mml:semantics> </mml:math> and <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:semantics><mml:mrow><mml:mo>-</mml:mo> <mml:mn>2</mml:mn></mml:mrow> <mml:annotation>$$ -2 $$</mml:annotation></mml:semantics> </mml:math> eV, respectively, and typical HOMO-LUMO gaps around 4-5 eV. The methodology is readily extendable to heavier elements and expanded property datasets, providing a valuable resource for astrochemical modeling, molecular spectroscopy, and computational hydrocarbon discovery. The HydroMol web application is freely accessible at https://hydromol.github.io.

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Journal
Journal of Computational Chemistry
Published
2025-09-27
DOI
https://doi.org/10.1002/jcc.70236
Primary Topic
Advanced Chemical Physics Studies
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article
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article

Computational Exploration of Small Hydrocarbon Networks: A Stochastic Generation and DFT Refinement Framework

Anakuthil Anoop, Tarun Kumar Roy, Subhas Ghosal, Sayon Satpati et al.
Journal of Computational Chemistry
Advanced Chemical Physics Studies
article

Computational Exploration of Small Hydrocarbon Networks: A Stochastic Generation and DFT Refinement Framework

Anakuthil Anoop, Tarun Kumar Roy, Subhas Ghosal, Sayon Satpati, Sandip Giri
article en

Abstract

Small hydrocarbons are central to astrochemistry due to their prevalence and chemical reactivity across diverse interstellar environments. Here, we present HydroMol, an open-access computational platform designed for systematic exploration and analysis of hydrocarbon chemical spaces, featuring over 2700 neutral <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:semantics> <mml:mrow> <mml:msub><mml:mrow><mml:mtext>C</mml:mtext></mml:mrow> <mml:mrow><mml:mi>n</mml:mi></mml:mrow> </mml:msub> <mml:msub><mml:mrow><mml:mtext>H</mml:mtext></mml:mrow> <mml:mrow><mml:mi>m</mml:mi></mml:mrow> </mml:msub> <mml:mo>(</mml:mo> <mml:mi>n</mml:mi> <mml:mo>,</mml:mo> <mml:mi>m</mml:mi> <mml:mo>=</mml:mo> <mml:mn>1</mml:mn> <mml:mo>-</mml:mo> <mml:mn>10</mml:mn> <mml:mo>)</mml:mo></mml:mrow> <mml:annotation>$$ {\mathrm{C}}_n{\mathrm{H}}_m\left(n,m=1-10\right) $$</mml:annotation></mml:semantics> </mml:math> hydrocarbon structures generated stochastically and refined via density functional theory at B3LYP-D3BJ/def2-SVP level. HydroMol provides detailed molecular geometries, thermodynamic parameters, and electronic properties critical for interpreting astrochemical phenomena and identifying promising observational targets. Our database, hosted within a lightweight client-side web application for rapid search and visualization, introduces approximately 2000 previously unreported hydrocarbons absent in major chemical repositories such as PubChem. Statistical analysis highlights the predominance of structurally simple monocyclic and bicyclic species, characterized by HOMO and LUMO energies centered at approximately <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:semantics><mml:mrow><mml:mo>-</mml:mo> <mml:mn>6</mml:mn></mml:mrow> <mml:annotation>$$ -6 $$</mml:annotation></mml:semantics> </mml:math> and <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:semantics><mml:mrow><mml:mo>-</mml:mo> <mml:mn>2</mml:mn></mml:mrow> <mml:annotation>$$ -2 $$</mml:annotation></mml:semantics> </mml:math> eV, respectively, and typical HOMO-LUMO gaps around 4-5 eV. The methodology is readily extendable to heavier elements and expanded property datasets, providing a valuable resource for astrochemical modeling, molecular spectroscopy, and computational hydrocarbon discovery. The HydroMol web application is freely accessible at https://hydromol.github.io.

Journal of Computational ChemistryVol. 46(25)
Indian Institute of Technology Kharagpur (IN), National Institute of Technology Durgapur (IN), University of Kerala (IN), Digital Science (United States) (US)
Openalex Percentile: Top 79%
Advanced Chemical Physics Studies
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