69 citations · 626 across the 34 of their papers we have counts for
8 papers · 1 filter
Stereo-Electronic Factors Influencing the Stability of Hydroperoxyalkyl Radicals: Transferability of Chemical Trends across Hydrocarbons and ab initio Methods
Saurabh Chandra Kandpal, Kgalaletso P. Otukile, Shweta Jindal +5
The hydroperoxyalkyl radicals (.QOOH) are known to play a significant role in combustion and tropospheric processes, yet their direct spectroscopic detection remains challenging. I…
Understanding the role of intramolecular ion-pair interactions in conformational stability using an ab initio thermodynamic cycle
Sabyasachi Chakraborty, Kalyaneswar Mandal, Raghunathan Ramakrishnan
Intramolecular ion-pair interactions yield shape and functionality to many molecules. With proper orientation, these interactions overcome steric factors and are responsible for th…
Data-Driven Modeling of S0 -> S1 Excitation Energy in the BODIPY Chemical Space: High-Throughput Computation, Quantum Machine Learning, and Inverse Design
Amit Gupta, Sabyasachi Chakraborty, Debashree Ghosh +1
Derivatives of BODIPY are popular fluorophores due to their synthetic feasibility, structural rigidity, high quantum yield, and tunable spectroscopic properties. While the characte…
Resolution-vs.-Accuracy Dilemma in Machine Learning Modeling of Electronic Excitation Spectra
Prakriti Kayastha, Sabyasachi Chakraborty, Raghunathan Ramakrishnan
In this study, we explore the potential of machine learning for modeling molecular electronic spectral intensities as a continuous function in a given wavelength range. Since prese…
Troubleshooting Unstable Molecules in Chemical Space
Salini Senthil, Sabyasachi Chakraborty, Raghunathan Ramakrishnan
A key challenge in automated chemical compound space explorations is ensuring veracity in minimum energy geometries---to preserve intended bonding connectivities. We discuss an ite…
Revving up 13C NMR shielding predictions across chemical space: Benchmarks for atoms-in-molecules kernel machine learning with new data for 134 kilo molecules
Amit Gupta, Sabyasachi Chakraborty, Raghunathan Ramakrishnan
The requirement for accelerated and quantitatively accurate screening of nuclear magnetic resonance spectra across the small molecules chemical compound space is two-fold: (1) a ro…
Critical Benchmarking of the G4(MP2) Model, the Correlation Consistent Composite Approach and Popular Density Functional Approximations on a Probabilistically Pruned Benchmark Dataset of Formation Enthalpies
Sambit Kumar Das, Sabyasachi Chakraborty, Raghunathan Ramakrishnan
First-principles calculation of the standard formation enthalpy, (298K), in such large scale as required by chemical space explorations, is amenable only with density…
The Chemical Space of B, N-substituted Polycyclic Aromatic Hydrocarbons: Combinatorial Enumeration and High-Throughput First-Principles Modeling
Sabyasachi Chakraborty, Prakriti Kayastha, Raghunathan Ramakrishnan
Combinatorial introduction of heteroatoms in the two-dimensional framework of aromatic hydrocarbons opens up possibilities to design compound libraries exhibiting desirable photovo…