Evidence map›Paper›PMID 40605405›Full record

ArticleJournal of computational chemistry2025

Accurate Prediction of HOMO-LUMO Gap Using DFT Functional and Application to Next-Generation Organic Telluro[n]Helicenes Materials.

Rahul Kumar, Rahul Kar, Dilip K Maity

Abstract read
In one paragraph

Article in Journal of computational chemistry, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing 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

7 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. 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

3 authors.

Rahul KumarHomi Bhabha National Institute, Training School Complex, Mumbai, India.ORCID https://orcid.org/0000-0003-1214-5541
Rahul KarDepartment of Chemistry, Dibrugarh University, Dibrugarh, India.
Dilip K MaityHomi Bhabha National Institute, Training School Complex, Mumbai, India.ORCID https://orcid.org/0000-0003-4284-3578

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The present work purposes and establishes an accurate prediction of HOMO-LUMO energies of thiophene-, selenophene-, and tellurophene-based helicenes using 15 different DFT methodologies. DFT functionals used in this work are PBE, PBE0, B3LYP, B3LYP-D, B3LYP-D3, M06, MN15, HSE06, LC-BLYP, CAM-B3LYP, LC-ωPBE, ωΒ97XD and B2PLYP. DFT HOMO-LUMO gaps are compared with the fundamental gaps calculated at the CCSD(T) level of theory. The LANL2DZ basis set is used for tellurium atoms, and the 6-311++G(d,p) basis set is used for other elements. Statistical error analysis suggests that the HOMO-LUMO energy gaps can be accurately obtained using ωB97XD functional, with geometry optimization performed at the same theoretical level. However, geometry optimization using the B3LYP functional, followed by single-point energy calculation with the ωB97XD functional, provides a more cost-effective method with similar accuracy for energy gap prediction. HOMO-LUMO gaps of telluro[n]helicenes ([n]TeH) are redshifted compared with their S- and Se-analogs. Tellurophene-based helicenes ([n]TeH) systems are easy to oxidize in contrast to their S- and Se-analogs. Dimerization studies have found that substituted [7]TeH

Indexed as

accurate HOMO–LUMO energiesdimerization studyhelicenesnext‐generation organic materialsstatistical error analysistelluropheneUV–visible spectra

Identifiers

PMID40605405
PMCPMC12223471

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.