8 papers
Assessing excited-state geometry optimization strategies for adiabatic photophysical energies
Amrita Bera, Atreyee Majumdar, Raghunathan Ramakrishnan
Accurate prediction of adiabatic - excited-state energies is crucial for modeling molecular photophysical processes. Here, we benchmark computational strategies for evaluatin…
A Chemical Space Perspective on Diastereomeric Barriers in Alkylperoxy-to-Hydroperoxyalkyl Isomerization
Raghunathan Ramakrishnan
Low-temperature hydrocarbon autooxidation involves radical intermediates whose reactivity depends not only on the stereochemistry of the intermediates themselves, but also on that…
Insights into Symmetry and Substitution Patterns Governing Singlet-Triplet Energy Gap in the Chemical Space of Azaphenalenes
Atreyee Majumdar, Raghunathan Ramakrishnan
Molecules that violate Hund's rule by exhibiting an inverted singlet-triplet gap (STG), where the first excited singlet (S) lies below the triplet (T), are rare but hold gr…
Enhancing NMR Shielding Predictions of Atoms-in-Molecules Machine Learning Models with Neighborhood-Informed Representations
Surajit Das, Raghunathan Ramakrishnan
Accurate prediction of nuclear magnetic resonance (NMR) shielding with machine learning (ML) models remains a central challenge for data-driven spectroscopy. We present atomic vari…
Machine-Learned Potentials for Solvation Modeling
Roopshree Banchode, Surajit Das, Shampa Raghunathan +1
Solvent environments play a central role in determining molecular structure, energetics, reactivity, and interfacial phenomena. However, modeling solvation from first principles re…
Leveraging the Bias-Variance Tradeoff in Quantum Chemistry for Accurate Negative Singlet-Triplet Gap Predictions: A Case for Double-Hybrid DFT
Atreyee Majumdar, Raghunathan Ramakrishnan
Molecules that have been suggested to violate the Hund's rule, having a first excited singlet state (S) energetically below the triplet state (T), are rare. Yet, they hold…