Evidence map›Paper›PMID 42819505›Full record

ArticlePrecision chemistry2026

Excitonic Engineering in 2D-SiC through Organic Donor-Acceptor Adsorption.

Masoud Mansouri, Fernando Martín

Abstract read
In one paragraph

Article in Precision chemistry, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

2 authors.

Masoud MansouriDepartamento de Química, Módulo 13, Universidad Autónoma de Madrid, Madrid 28049, Spain.ORCID https://orcid.org/0000-0003-1960-7446
Fernando MartínDepartamento de Química, Módulo 13, Universidad Autónoma de Madrid, Madrid 28049, Spain.ORCID https://orcid.org/0000-0002-7529-925X

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Controlling electronic excitations at molecule-semiconductor interfaces is key to designing hybrid optoelectronics. Using many-body perturbation theory, we study monolayer and bilayer SiC and their interfaces with four organic molecules bearing donor and/or acceptor substituents. Pristine monolayer SiC hosts strongly bound excitons with optical activity in the ultraviolet. Upon stable physisorption, new molecule-derived excitons emerge in the visible range. Through a detailed quantitative analysis of these excitons and the corresponding free-standing molecular excitations, we show that donor-acceptor molecules with predominant intramolecular charge-transfer excitation largely retain their character upon adsorption and undergo only modest optical redshifts in response to the substrate-induced screening. In contrast, donor-only or acceptor-only molecules with predominantly localized excitations exhibit significantly larger redshifts after adsorption. Bilayer SiC with stronger screening amplifies these shifts. The magnitude of the optical redshift reflects the competition between quasiparticle gap renormalization and the simultaneous reduction in exciton binding energy. This balance is controlled by the spatial distribution of the frontier orbitals at the interface and by the extent of electron-hole overlap within the exciton. Our results highlight the interplay between intrinsic molecular polarizability, excitonic characteristics, and substrate-induced screening effects as complementary knobs for tuning interfacial level alignment and optical functionality in molecule-semiconductor heterostructures.

Indexed as

charge-transfer and localized excitonsexciton renormalizationinterfacial screeningmany-body perturbation theorymolecule-SiC heterostructures

Identifiers

PMID42819505
PMCPMC13625919

What OpenQuestion holds

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Registered trials

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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.