ArticleJournal of chemical theory and computation2023
Cost-Effective Simulations of Vibrationally-Resolved Absorption Spectra of Fluorophores with Machine-Learning-Based Inhomogeneous Broadening.
Article in Journal of chemical theory and computation, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
What it found
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Who cites it
5 citing papers in PubMed.
- A Contrastive-Learning-Based Pre-Training Framework for Optical Property Prediction of Low-Data Rhodamines with Interpretable Multitask Graph Neural Networks.Molecules (Basel, Switzerland) · 2026Article
- A fluorescent probe under the microscope showing dual recognition of B-DNA and G-quadruplex DNA.Communications chemistry · 2026Article
- Enhanced Prediction of Absorption and Emission Wavelengths of Organic Compounds through Hybrid Graph Neural Network Architectures.ACS omega · 2025Article
- Tailoring Spectral Response and First Hyperpolarizability of Aryl-Substituted BODIPY-Based 'Push-Pull' Chromophores: Influence of Medium and Structural Modifications.The journal of physical chemistry. A · 2025Article
- Simulations of Two-Photon Absorption Spectra of Fluorescent Dyes: The Impact of Non-Condon Effects.Journal of chemical theory and computation · 2025Article
Corrections and comments
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Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The results of electronic and vibrational structure simulations are an invaluable support for interpreting experimental absorption/emission spectra, which stimulates the development of reliable and cost-effective computational protocols. In this work, we contribute to these efforts and propose an efficient first-principle protocol for simulating vibrationally-resolved absorption spectra, including nonempirical estimations of the inhomogeneous broadening. To this end, we analyze three key aspects:
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Registered trials
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