Evidence map›Paper›PMID 40791185›Full record

ArticleAdvanced science (Weinheim, Baden-Wurttemberg, Germany)2025

Bright Light Emission from Deep Energy States.

Lian Xiao, Sihang Liu, Zhan Yu, Yong Yi, Rui Duan, Quanchao Du, Yugang Zhao, Xuehong Zhou, Van Duong Ta, Edwin Kok Lee Yeow and 3 more

Abstract read
In one paragraph

Article in Advanced science (Weinheim, Baden-Wurttemberg, Germany), 2025. 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. Bright Light Emission from Deep Energy States.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2025
    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

13 authors.

Lian XiaoSchool of Physics, East China University of Science and Technology, Shanghai, 200237, China.ORCID https://orcid.org/0000-0002-8840-5613
Sihang LiuResearch Institute of Aero-Engine, Beihang University, No.37 XueYuan Road, Haidian District, Beijing, 100083, China.
Zhan YuBeijing An Zhen Hospital, Affiliated of Capital University of Medical Sciences, Beijing, 100029, China.
Yong YiCenter of Growth, Metabolism and Aging, Key Laboratory of Bio-Resource and Eco-Environment of Ministry of Education, College of Life Sciences, Sichuan University, Chengdu, 610064, China.
Rui DuanInstitute of Applied Physics and Materials Engineering, University of Macau, Macao, SAR, 999078, China.
Quanchao DuSchool of Chemistry, Chemical Engineering & Biotechnology, Nanyang Technological University, Singapore, 637371, Singapore.
Yugang ZhaoShanghai Key Laboratory of Multiphase Flow and Heat Transfer in Power Engineering, School of Energy and Power Engineering, University of Shanghai for Science and Technology, Shanghai, 200093, China.
Xuehong ZhouDivision of Physics and Applied Physics, School of Physical and Mathematical Sciences, Nanyang Technological University, 21 Nanyang Link, Singapore, 637371, Singapore.
Van Duong TaDepartment of Optical Devices, Le Quy Don Technical University, Hanoi, 100000, Vietnam.
Edwin Kok Lee YeowSchool of Chemistry, Chemical Engineering & Biotechnology, Nanyang Technological University, Singapore, 637371, Singapore.
Yi HuangResearch Institute of Aero-Engine, Beihang University, No.37 XueYuan Road, Haidian District, Beijing, 100083, China.
Zhi-Gang ZhengSchool of Physics, East China University of Science and Technology, Shanghai, 200237, China.
Handong SunInstitute of Applied Physics and Materials Engineering, University of Macau, Macao, SAR, 999078, China.

Funding

H.D.S. acknowledges the support from CPG2024-00006H.D.S. acknowledges the support from CPG2025-00034-IAPMEH.D.S. acknowledges the support from SRG2023-00025Innovation Program of Shanghai Municipal Education Commission, Scientific Committee of Shanghai 2021-01-07-00-02-E00107National Key Research and Development Program of China 2022YFA1203700National Natural Science Foundation of China 52276079National Natural Science Foundation of China 52320105001National Natural Science Foundation of China 62275081Science and Technology Development Fund (FDCT), Macao SAR 0122/2023/RIA2
6 · The paper itself

Abstract

Deep energy states, a fundamental concept in semiconductor physics, play a pivotal role in determining the optical performance of semiconductor materials. They are generally regarded as undesirable defects, as they can serve as efficient centers for non-radiative recombination. Thus, the prevailing consensus is that deep energy states must be passivated and mitigated to enhance the optical properties of semiconductors. In this work, however, it is demonstrated that these " undesirable" deep energy states can be harnessed as " desirable" states to enable bright light emission. This is achieved by proposing a deep energy state regulation mechanism, termed "surface ionization annealing", which transforms the randomly and broadly distributed non-radiative deep energy levels into a narrower energy range. This transformation results in a high density of states and band-edge-like absorption originating from deep energy states in sulfur quantum dots. The regulation is realized through precise control of surface charge and surface dangling bonds. Simultaneously, surface ionization annealing eliminates non-radiative deep energy states, significantly enhancing the photoluminescence quantum yield (PLQY) of sulfur quantum dots to 15.6%. Consequently, the simultaneous realization of a high density of states and high PLQY enables bright light emission from deep energy states.

Indexed as

bright light emissiondeep energy statesdensity of statessulfur quantum dots

Identifiers

PMID40791185
PMCPMC12591114

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.