Evidence map›Paper›PMID 42209533›Full record

ArticleScientific reports2026

Innovative approach to synthesizing polyhydroquinoline and dihydropyrimidine derivatives from alcohols by g-C

Abbas Moradi, Hossein Ghafuri, Sharif Kaamyabi, Zeinab Tajik, Peyman Hanifehnejad

Abstract read
In one paragraph

Article in Scientific reports, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Graphitic Carbon Nitride (g-CMolecules (Basel, Switzerland) · 2026
    Review
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

5 authors.

Abbas MoradiNovel Catalyst Research Laboratory, Department of Chemistry, Iran University of Science and Technology, Tehran, 16846‑13114, Iran.
Hossein GhafuriNovel Catalyst Research Laboratory, Department of Chemistry, Iran University of Science and Technology, Tehran, 16846‑13114, Iran. ghafuri@iust.ac.ir.
Sharif KaamyabiDepartment of Chemistry, Farhangian University, P.O. Box 15875-4874, Tehran, Iran.
Zeinab TajikNovel Catalyst Research Laboratory, Department of Chemistry, Iran University of Science and Technology, Tehran, 16846‑13114, Iran.
Peyman HanifehnejadNovel Catalyst Research Laboratory, Department of Chemistry, Iran University of Science and Technology, Tehran, 16846‑13114, Iran.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This study introduces an innovative and sustainable approach for synthesizing polyhydroquinoline and dihydropyrimidine derivatives directly from alcohols via in situ oxidation to aldehydes, using a nanocomposite catalyst composed of graphitic carbon nitride (g-C₃N₄), polyaniline (PANI), and copper ions (Cu²⁺). The g-C₃N₄/PANI/Cu²⁺ catalyst exhibited excellent catalytic performance, affording yields of 63-84% under relatively mild and environmentally acceptable conditions. Comprehensive characterization by Fourier transform infrared spectroscopy (FT-IR), energy-dispersive X-ray spectroscopy (EDS), X-ray diffraction (XRD), and field-emission scanning electron microscopy (FE-SEM) supported the successful formation and structural stability of the nanocomposite. Mechanistic insights suggest that cooperative interactions among g-C₃N₄, PANI, and Cu²⁺ species facilitate the in situ oxidation of alcohols and subsequent multicomponent condensation, leading to heterocyclic frameworks. Overall, this methodology provides an efficient and sustainable catalytic pathway for synthesizing biologically relevant heterocycles with potential applications in pharmaceuticals and materials science.

Indexed as

Aromatic alcoholDihydropyrimidineg-C3N4/PANI/Cu2+NanocompositePolyhydroquinoline

Identifiers

PMID42209533
PMCPMC13478194

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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.