Publications

Preprints and full-text links are available on my ORCID profile.

2026

  1. Hojin Jung, Sabari Kumar, Sumin Song, and Seonah Kim. Fine-tuning Chemical Foundation Models for Property Prediction with ClAY: Cluster Augmentation for Y-properties. In preparation, 2026.
    BibTeX
    @unpublished{jung2026clay,
        author = "Jung, Hojin and Kumar, Sabari and Song, Sumin and Kim, Seonah",
        title = "{Fine-tuning Chemical Foundation Models for Property Prediction with ClAY: Cluster Augmentation for Y-properties}",
        year = "2026",
        note = "In preparation"
    }
    
  2. Sabari Kumar, Sumin Song, and Seonah Kim. PECAN: Peptide Electrostatics with Conformationally Agnostic Networks. In preparation, 2026.
    BibTeX
    @unpublished{kumar2026pecan,
        author = "Kumar, Sabari and Song, Sumin and Kim, Seonah",
        title = "{PECAN: Peptide Electrostatics with Conformationally Agnostic Networks}",
        year = "2026",
        note = "In preparation"
    }
    
  3. Sabari Kumar, Shree Sowndarya Santhanalakkshmi Vejaykummar, Peter St. John, Yeonjoon Kim, Robert S. Paton, and Seonah Kim. ALFABET3: Extending Predictions of Homolytic Bond Dissociation Energy to Ring Systems. In preparation, 2026.
    BibTeX
    @unpublished{kumar2026alfabet3,
        author = "Kumar, Sabari and Vejaykummar, Shree Sowndarya Santhanalakkshmi and John, Peter St. and Kim, Yeonjoon and Paton, Robert S. and Kim, Seonah",
        title = "{ALFABET3: Extending Predictions of Homolytic Bond Dissociation Energy to Ring Systems}",
        year = "2026",
        note = "In preparation"
    }
    

2025

  1. Hojin Jung, Christopher D. Stubbs, Sabari Kumar, Raúl Pérez-Soto, Sumin Song, Yeonjoon Kim, and Seonah Kim. Enhancing Predictive Models for Solubility in Multi-Solvent Systems using Semi-Supervised Graph Neural Networks. Digital Discovery, 2025.
    BibTeX
    @article{jung2025multisolvent,
        author = "Jung, Hojin and Stubbs, Christopher D. and Kumar, Sabari and P\'erez-Soto, Ra\'ul and Song, Sumin and Kim, Yeonjoon and Kim, Seonah",
        title = "{Enhancing Predictive Models for Solubility in Multi-Solvent Systems using Semi-Supervised Graph Neural Networks}",
        journal = "Digital Discovery",
        year = "2025"
    }
    
  2. Sabari Kumar, Olivia Harman, Sumin Song, Yeonjoon Kim, Robert Paton, and Seonah Kim. Combining Geometry and Topology for Accurate Protein Solubility Prediction. ChemRxiv, 2025. Submitted. URL: https://doi.org/10.26434/chemrxiv-2025-jmzwn.
    BibTeX
    @article{kumar2025solubility,
        author = "Kumar, Sabari and Harman, Olivia and Song, Sumin and Kim, Yeonjoon and Paton, Robert and Kim, Seonah",
        title = "{Combining Geometry and Topology for Accurate Protein Solubility Prediction}",
        journal = "ChemRxiv",
        year = "2025",
        url = "https://doi.org/10.26434/chemrxiv-2025-jmzwn",
        note = "Submitted"
    }
    
  3. Raúl Pérez-Soto, Mihai V. Popescu, Sabari Kumar, Leticia Adao Gomes, Changyeob Lee, Steven A. Lopez, Robert S. Paton, and Seonah Kim. A Fragment-Based Approach Towards Curating, Comparing and Developing Machine Learning Models Applied in Photochemistry. Chemical Science, 2025. Equal contribution: Pérez-Soto, Popescu, Kumar. URL: https://doi.org/10.1039/D5SC05615B.
    BibTeX
    @article{perezsoto2025fragment,
        author = "P\'erez-Soto, Ra\'ul and Popescu, Mihai V. and Kumar, Sabari and Gomes, Leticia Adao and Lee, Changyeob and Lopez, Steven A. and Paton, Robert S. and Kim, Seonah",
        title = "{A Fragment-Based Approach Towards Curating, Comparing and Developing Machine Learning Models Applied in Photochemistry}",
        journal = "Chemical Science",
        year = "2025",
        url = "https://doi.org/10.1039/D5SC05615B",
        note = "Equal contribution: P\'erez-Soto, Popescu, Kumar"
    }
    

2024

  1. Ga-Un Jeong, Zhanhong Xiang, Sabari Kumar, Collin Hansen, Adri van Duin, Seonah Kim, Charles S. McEnally, Lisa D. Pfefferle, and Yuan Xuan. Experimental and Numerical Study of the Decomposition, Product Spectrum, and Sooting Properties of Adamantane Fuels. Fuel, 378:132886, 2024.
    BibTeX
    @article{jeong2024adamantane,
        author = "Jeong, Ga-Un and Xiang, Zhanhong and Kumar, Sabari and Hansen, Collin and van Duin, Adri and Kim, Seonah and McEnally, Charles S. and Pfefferle, Lisa D. and Xuan, Yuan",
        title = "{Experimental and Numerical Study of the Decomposition, Product Spectrum, and Sooting Properties of Adamantane Fuels}",
        journal = "Fuel",
        volume = "378",
        pages = "132886",
        year = "2024"
    }
    
  2. Hojin Jung, Jaeyoung Cho, Yeonjoon Kim, Zhanhong Xiang, Sabari Kumar, Piper Barnard, Charles S. McEnally, Lisa D. Pfefferle, and Seonah Kim. Sooting Tendency of Substituted Aromatic Oxygenates: The Role of Functional Groups and Positional Isomerism in Vanillin Isomers. Proceedings of the Combustion Institute, 40:105669, 2024.
    BibTeX
    @article{jung2024vanillin,
        author = "Jung, Hojin and Cho, Jaeyoung and Kim, Yeonjoon and Xiang, Zhanhong and Kumar, Sabari and Barnard, Piper and McEnally, Charles S. and Pfefferle, Lisa D. and Kim, Seonah",
        title = "{Sooting Tendency of Substituted Aromatic Oxygenates: The Role of Functional Groups and Positional Isomerism in Vanillin Isomers}",
        journal = "Proceedings of the Combustion Institute",
        volume = "40",
        pages = "105669",
        year = "2024"
    }
    
  3. Yeonjoon Kim, Hojin Jung, Sabari Kumar, Robert S. Paton, and Seonah Kim. Designing Solvent Systems Using Self-Evolving Solubility Databases and Graph Neural Networks. Chemical Science, 15:923–939, 2024. ChemSci Pick of the Week.
    BibTeX
    @article{kim2024solvent,
        author = "Kim, Yeonjoon and Jung, Hojin and Kumar, Sabari and Paton, Robert S. and Kim, Seonah",
        title = "{Designing Solvent Systems Using Self-Evolving Solubility Databases and Graph Neural Networks}",
        journal = "Chemical Science",
        volume = "15",
        pages = "923--939",
        year = "2024",
        note = "ChemSci Pick of the Week"
    }
    
  4. Lisa D. Pfefferle, Seonah Kim, Sabari Kumar, Charles S. McEnally, Raúl Pérez-Soto, Zhanhong Xiang, and Yuan Xuan. Sooting Tendencies: Combustion Science for Designing Sustainable Fuels with Improved Properties. Proceedings of the Combustion Institute, 40:105750, 2024.
    BibTeX
    @article{pfefferle2024sooting,
        author = "Pfefferle, Lisa D. and Kim, Seonah and Kumar, Sabari and McEnally, Charles S. and P\'erez-Soto, Ra\'ul and Xiang, Zhanhong and Xuan, Yuan",
        title = "{Sooting Tendencies: Combustion Science for Designing Sustainable Fuels with Improved Properties}",
        journal = "Proceedings of the Combustion Institute",
        volume = "40",
        pages = "105750",
        year = "2024"
    }
    

2023

  1. Yeonjoon Kim, Sabari Kumar, Jaeyoung Cho, Nimal Naser, Wonjong Ko, Peter C. St. John, Robert L. McCormick, and Seonah Kim. Designing High-Performance Fuels through Graph Neural Networks for Predicting Cetane Number of Multicomponent Surrogate Mixtures. SAE Technical Paper 2023-32-0052, 2023. Equal contribution: Y. Kim, S. Kumar.
    BibTeX
    @article{kim2023cetane,
        author = "Kim, Yeonjoon and Kumar, Sabari and Cho, Jaeyoung and Naser, Nimal and Ko, Wonjong and John, Peter C. St. and McCormick, Robert L. and Kim, Seonah",
        title = "{Designing High-Performance Fuels through Graph Neural Networks for Predicting Cetane Number of Multicomponent Surrogate Mixtures}",
        journal = "SAE Technical Paper 2023-32-0052",
        year = "2023",
        note = "Equal contribution: Y. Kim, S. Kumar"
    }
    

2022

  1. Yeonjoon Kim, Jaeyoung Cho, Nimal Naser, Sabari Kumar, Keunhong Jeong, Robert L. McCormick, Peter C. St. John, and Seonah Kim. Physics-informed Graph Neural Networks for Predicting Cetane Number with Systematic Data Quality Analysis. Proceedings of the Combustion Institute, 39:4969–4978, 2022.
    BibTeX
    @article{kim2022cetane,
        author = "Kim, Yeonjoon and Cho, Jaeyoung and Naser, Nimal and Kumar, Sabari and Jeong, Keunhong and McCormick, Robert L. and John, Peter C. St. and Kim, Seonah",
        title = "{Physics-informed Graph Neural Networks for Predicting Cetane Number with Systematic Data Quality Analysis}",
        journal = "Proceedings of the Combustion Institute",
        volume = "39",
        pages = "4969--4978",
        year = "2022"
    }