Copertina

Resilience of Hund's rule in the Chemical Space of Small Organic Molecules

Fuente: arXiv

Salvato in:

Dettagli Bibliografici
Autori principali:	Majumdar, Atreyee, Ramakrishnan, Raghunathan
Natura:	Preprint
Pubblicazione:	2024
Soggetti:	Chemical Physics
Accesso online:	Acceder al recurso
Tags:	Aggiungi Tag Nessun Tag, puoi essere il primo ad aggiungerne!!

Documenti analoghi

Insights into Symmetry and Substitution Patterns Governing Singlet-Triplet Energy Gap in the Chemical Space of Azaphenalenes
di: Majumdar, Atreyee, et al.
Pubblicazione: (2025)

Leveraging the Bias-Variance Tradeoff in Quantum Chemistry for Accurate Negative Singlet-Triplet Gap Predictions: A Case for Double-Hybrid DFT
di: Majumdar, Atreyee, et al.
Pubblicazione: (2025)

Unlocking Inverted Singlet-Triplet Gap in Alternant Hydrocarbons with Heteroatoms
di: Majumdar, Atreyee, et al.
Pubblicazione: (2025)

Assessing excited-state geometry optimization strategies for adiabatic photophysical energies
di: Bera, Amrita, et al.
Pubblicazione: (2026)

Influence of Pseudo-Jahn-Teller Activity on the Singlet-Triplet Gap of Azaphenalenes
di: Majumdar, Atreyee, et al.
Pubblicazione: (2024)

A Chemical Space Perspective on Diastereomeric Barriers in Alkylperoxy-to-Hydroperoxyalkyl Isomerization
di: Ramakrishnan, Raghunathan
Pubblicazione: (2026)

Chemical Space-Informed Machine Learning Models for Rapid Predictions of X-ray Photoelectron Spectra of Organic Molecules
di: Tripathy, Susmita, et al.
Pubblicazione: (2024)

Enhancing NMR Shielding Predictions of Atoms-in-Molecules Machine Learning Models with Neighborhood-Informed Representations
di: Das, Surajit, et al.
Pubblicazione: (2025)

Insights Into Symmetry and Substitution Patterns Governing Singlet–Triplet Energy Gap in the Chemical Space of Azaphenalenes
di: Atreyee Majumdar, et al.
Pubblicazione: (2026)

Machine-Learned Potentials for Solvation Modeling
di: Banchode, Roopshree, et al.
Pubblicazione: (2025)

Leveraging the Bias‐Variance Tradeoff in Quantum Chemistry for Accurate Negative Singlet‐Triplet Gap Predictions: A Case for Double‐Hybrid DFT
di: Atreyee Majumdar, et al.
Pubblicazione: (2025)

QMe14S, A Comprehensive and Efficient Spectral Dataset for Small Organic Molecules
di: Yuan, Mingzhi, et al.
Pubblicazione: (2025)

Transfer Learning across Different Chemical Domains: Virtual Screening of Organic Materials with Deep Learning Models Pretrained on Small Molecule and Chemical Reaction Data
di: Zhang, Chengwei, et al.
Pubblicazione: (2023)

Musical Molecules: Sonifying the IR Spectra and Modeling Intramolecular Vibrational Energy Redistribution of Small Molecules
di: Kim, Sophia H., et al.
Pubblicazione: (2026)

Theoretical Investigation of The X-Ray Stark Effect in Small Molecules
di: Datar, Avdhoot, et al.
Pubblicazione: (2022)

GridFF: Efficient Simulation of Organic Molecules on Rigid Substrates
di: Mal, Indranil, et al.
Pubblicazione: (2025)

Chiral Vibrational Modes in Small Molecules
di: Feng, Jichen, et al.
Pubblicazione: (2025)

Comparative Analysis of GFN Methods in Geometry Optimization of Small Organic Semiconductor Molecules: A DFT Benchmarking Study
di: Kouam, Steve Cabrel Teguia, et al.
Pubblicazione: (2025)

Comparative Analysis of search Approaches to Discover Donor Molecules for Organic Solar Cells
di: Azzouzi, Mohammed, et al.
Pubblicazione: (2024)

GPU Accelerated Minimal Auxiliary Basis Approach TDDFT for Large Organic Molecules
di: Zhou, Zehao, et al.
Pubblicazione: (2026)

Can the Infamous Boundary Be Found in Macromolecules? Also, von Neumann vs. Schroedinger ensembles, and `Hund's Paradox' in quantum chemistry
di: Wick, W. David
Pubblicazione: (2025)

Representative Random Sampling of Chemical Space
di: Monterrubio-Chanca, Diego J., et al.
Pubblicazione: (2025)

MACE-OFF: Transferable Short Range Machine Learning Force Fields for Organic Molecules
di: Kovács, Dávid Péter, et al.
Pubblicazione: (2023)

Computation of Auger Electron Spectra in Organic Molecules with Multiconfiguration Pair-Density Functional Theory
di: Fouda, Adam E. A., et al.
Pubblicazione: (2025)

Benchmark Phaseless Auxiliary-Field Quantum Monte Carlo Method for Small Molecules
di: Sukurma, Z., et al.
Pubblicazione: (2023)

Implicit Neural Representations for Chemical Reaction Paths
di: Ramakrishnan, Kalyan, et al.
Pubblicazione: (2025)

Towards Linearly Scaling and Chemically Accurate Global Machine Learning Force Fields for Large Molecules
di: Kabylda, Adil, et al.
Pubblicazione: (2022)

Enhancing Accuracy and Feature Insights in Hydration Free Energy Predictions for Small Molecules with Machine Learning
di: Han, Mingjun, et al.
Pubblicazione: (2024)

ORION: Unifying Top-Down and Bottom-Up Chemical Space Sampling for a Universal Organic Force Field
di: Chen, Zherui, et al.
Pubblicazione: (2026)

Unveiling the Role of Lewis Base Strength in Small-Molecule Passivation of Defect Perovskites
di: Wu, Yi-Chen, et al.
Pubblicazione: (2024)

AceFF: A State-of-the-Art Machine Learning Potential for Small Molecules
di: Farr, Stephen E., et al.
Pubblicazione: (2026)

Evaluating the Progression of Large Language Model Capabilities for Small-Molecule Drug Design
di: Chennakesavalu, Shriram, et al.
Pubblicazione: (2026)

The Phase-Space Way To Electronic Structure Theory and Subsequently Chemical Dynamics
di: Bian, Xuezhi, et al.
Pubblicazione: (2025)

QeMFi: A Multifidelity Dataset of Quantum Chemical Properties of Diverse Molecules
di: Vinod, Vivin, et al.
Pubblicazione: (2024)

SITH: A Quantum-Chemical Framework for Predicting Bond Destabilization in Stretched Molecules
di: Sucerquia, Daniel, et al.
Pubblicazione: (2026)

Quadruply Bonded Mo$_2$ Molecules Acting as an Inborn Emitter-Resonator Quantum System in Free Space
di: Meng, Miao, et al.
Pubblicazione: (2024)

Navigating Chemical Space: Multi-Level Bayesian Optimization with Hierarchical Coarse-Graining
di: Walter, Luis J., et al.
Pubblicazione: (2025)

Hammett-Inspired Product Baseline for Data-efficient $Δ$-ML in Chemical Space
di: Rakotonirina, V. Diana, et al.
Pubblicazione: (2023)

A Phase-Space Electronic Hamiltonian for Molecules in a Static Magnetic Field I: Conservation of Total Pseudomomentum and Angular Momentum
di: Bhati, Mansi, et al.
Pubblicazione: (2024)

Navigating Chemical Space with Latent Flows
di: Wei, Guanghao, et al.
Pubblicazione: (2024)