Evidence map›Paper›PMID 30057655›Full record

ArticleThe journal of physical chemistry. C, Nanomaterials and interfaces2018

Excitonic Energy Transfer within InP/ZnS Quantum Dot Langmuir-Blodgett Assemblies.

Houman Bahmani Jalali, Rustamzhon Melikov, Sadra Sadeghi, Sedat Nizamoglu

Open access · bronzeAbstract read
In one paragraph

Article in The journal of physical chemistry. C, Nanomaterials and interfaces, 2018. 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
2.0field-weighted citation impact, top 13% of its field
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, 34 citations in OpenAlex.

  1. Article
  2. Optoelectronic Neural Interfaces Based on Quantum Dots.ACS applied materials & interfaces · 2022
    Review
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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 at 1 institution in 1 country.

Houman Bahmani JalaliDepartment of Biomedical Science and Engineering, Koç University, Istanbul 34450, Turkey.
Rustamzhon MelikovDepartment of Electrical and Electronics Engineering, Koç University, Istanbul 34450, Turkey.
Sadra SadeghiDepartment of Material Science and Engineering, Koç University, Istanbul 34450, Turkey.
Sedat NizamogluDepartment of Biomedical Science and Engineering, Koç University, Istanbul 34450, Turkey.
Koç University · TR

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Interparticle energy transfer offers great promise to a diverse range of applications ranging from artificial solar energy harvesting to nanoscale rulers in biology. Here, we assembled InP/ZnS core/shell quantum dot monolayers via the Langmuir-Blodgett technique and studied the effect of ZnS shell thickness on the excitonic energy transfer within these core/shell quantum dots. Three types of InP-based core/shell quantum dot Langmuir-Blodgett assemblies with different ZnS shell thicknesses were assembled. The structural and optical properties of colloidal quantum dots reveal the successful multiple ZnS shell growth, and atomic force microscopy studies show the smoothness of the assembled monolayers. Time-resolved photoluminescence (PL) and fluorescence lifetime imaging microscopy (FLIM) studies of the thick-shell QD monolayer reveal narrower lifetime distribution in comparison with the thin-shell QD monolayer. The interparticle excitonic energy transfer was studied by spectrally resolved PL traces, and higher energy transfer was observed for the thin-shell InP/1ZnS QD monolayer. Finally, we calculated the average exciton energy and indicated that the energy transfer induced exciton energy shift decreased significantly from 95 to 27 meV after multiple ZnS shell growth.

Identifiers

PMID30057655
PMCPMC6057685
OpenAlexW2799773255

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.