Evidence map›Paper›PMID 37604820›Full record

ArticleScientific data2023

Two excited-state datasets for quantum chemical UV-vis spectra of organic molecules.

Massimiliano Lupo Pasini, Kshitij Mehta, Pilsun Yoo, Stephan Irle

Abstract readDataset
In one paragraph

Article in Scientific data, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

5 citing papers in PubMed.

  1. Article
  2. Article
  3. Predicting SJournal of chemical theory and computation · 2026
    Article
  4. Article
  5. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Massimiliano Lupo Pasini *Oak Ridge National Laboratory, Computational Sciences and Engineering Division, Oak Ridge, 37831, USA. lupopasinim@ornl.gov.
Kshitij Mehta *Oak Ridge National Laboratory, Computer Science and Mathematics Division, Oak Ridge, 37831, USA.
Pilsun YooOak Ridge National Laboratory, Computational Sciences and Engineering Division, Oak Ridge, 37831, USA.
Stephan IrleOak Ridge National Laboratory, Computational Sciences and Engineering Division, Oak Ridge, 37831, USA. irles@ornl.gov.ORCID http://orcid.org/0000-0003-4995-4991

Funding

DOE | LDRD | Oak Ridge National Laboratory (ORNL) DE-AC05-00OR22725
6 · The paper itself

Abstract

We present two open-source datasets that provide time-dependent density-functional tight-binding (TD-DFTB) electronic excitation spectra of organic molecules. These datasets represent predictions of UV-vis absorption spectra performed on optimized geometries of the molecules in their electronic ground state. The GDB-9-Ex dataset contains a subset of 96,766 organic molecules from the original open-source GDB-9 dataset. The ORNL_AISD-Ex dataset consists of 10,502,904 organic molecules that contain between 5 and 71 non-hydrogen atoms. The data reveals the close correlation between the magnitude of the gaps between the highest occupied molecular orbital (HOMO) and the lowest unoccupied molecular orbital (LUMO), and the excitation energy of the lowest singlet excited state energies quantitatively. The chemical variability of the large number of molecules was examined with a topological fingerprint estimation based on extended-connectivity fingerprints (ECFPs) followed by uniform manifold approximation and projection (UMAP) for dimension reduction. Both datasets were generated using the DFTB+ software on the "Andes" cluster of the Oak Ridge Leadership Computing Facility (OLCF).

Identifiers

PMID37604820
PMCPMC10442335

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.