profile/publications.html at main · surajitdas09/profile · GitHub

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        <title>My Publications</title>
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        <big><b>Research Papers</b></big>

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            <li>
                <b>Das, S.</b> & Ramakrishnan, R. (2026).
                Enhancing NMR Shielding Predictions of Atoms-in-Molecules Machine Learning Models with Neighborhood-Informed Representations.
                <i>J. Chem. Phys.</i>, <b>164</b>(4), 044106.
                DOI: <a href="https://doi.org/10.1063/5.0306349" class="papers">10.1063/5.0306349</a>
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            <li>
                Banchode, R., <b>Das, S.</b>, Raghunathan, S., & Ramakrishnan, R. (2025).
                Machine-Learned Potentials for Solvation Modeling.
                <i>J. Phys.: Condens. Matter</i>, <b>38</b>(1), 013002.
                DOI: <a href="https://doi.org/10.1088/1361-648X/ae2177" class="papers">10.1088/1361-648X/ae2177</a>
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            <li>
                Majumdar, A., <b>Das, S.</b>, & Ramakrishnan, R. (2025).
                Unlocking Inverted Singlet-Triplet Gap in Alternant Hydrocarbons with Heteroatoms.
                <i>Chem. Sci.</i>, <b>16</b>(31), 14392-14407.
                DOI:<a href="https://doi.org/10.1039/D5SC02309B" class="papers">10.1039/D5SC02309B</a>
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            <li>
                Tripathy, <b>S., Das</b>, S., Jindal, S., & Ramakrishnan, R. (2024).
                Chemical Space-Informed Machine Learning Models for Rapid Predictions of X-ray Photoelectron Spectra of Organic Molecules.
                <i>Mach. Learn.: Sci. Technol.</i>, <b>5</b>(4), 045023.
                DOI:<a href="https://iopscience.iop.org/article/10.1088/2632-2153/ad871d" class="papers">10.1088/2632-2153/ad871d</a>
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            <li>
                Majumdar, A., Jindal, K., <b>Das, S.</b>, & Ramakrishnan, R. (2024).
                Influence of pseudo-Jahn-Teller activity on the singlet-triplet gap of azaphenalenes.
                <i>Phys. Chem. Chem. Phys.</i>, <b>26</b>(42), 26723-26733.
                DOI:<a href="https://pubs.rsc.org/en/content/articlelanding/2024/cp/d4cp02761b" class="papers">10.1039/D4CP02761B</a>
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