Evidence map›Paper›PMID 42505432›Full record

ReviewBiosensors2026

Green Synthesis of Fluorescent Carbon Dots and AI-Driven New Paradigms: A Comprehensive Review.

Qian Wang, Huiyao Liang, Xiaofeng Chang, Huili He, Rong Li, Jian Mao, Weiwei Han, Ying Tang, Yongfei Li, Maogang Li and 1 more

Abstract readReview
In one paragraph

Review in Biosensors, 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

11 authors.

Qian WangShaanxi University Engineering Research Center of Oil and Gas Field Chemistry, Xi'an Shiyou University, Xi'an 710065, China.ORCID 0009-0004-2208-1873
Huiyao LiangShaanxi Engineering Research Center of Green Low-Carbon Energy Materials and Processes, Xi'an Shiyou University, Xi'an 710065, China.
Xiaofeng ChangCCDC Changqing General Drilling Company, Xi'an 710021, China.
Huili HeKaramay Sanda High-Tech Co., Ltd., Karamay 834000, China.
Rong LiKaramay Sanda High-Tech Co., Ltd., Karamay 834000, China.
Jian MaoState Key Laboratory of Heavy Oil Processing and Center for Bioengineering and Biotechnology, China University of Petroleum (East China), Qingdao 266580, China.
Weiwei HanShaanxi Engineering Research Center of Green Low-Carbon Energy Materials and Processes, Xi'an Shiyou University, Xi'an 710065, China.
Ying TangShaanxi University Engineering Research Center of Oil and Gas Field Chemistry, Xi'an Shiyou University, Xi'an 710065, China.
Yongfei LiShaanxi University Engineering Research Center of Oil and Gas Field Chemistry, Xi'an Shiyou University, Xi'an 710065, China.ORCID 0000-0003-2195-3575
Maogang LiShaanxi Engineering Research Center of Green Low-Carbon Energy Materials and Processes, Xi'an Shiyou University, Xi'an 710065, China.ORCID 0000-0002-0375-1438
Qunzheng ZhangShaanxi University Engineering Research Center of Oil and Gas Field Chemistry, Xi'an Shiyou University, Xi'an 710065, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Carbon dots (CDs) have been widely employed in diverse fields by virtue of their excellent water solubility, low toxicity, high fluorescence stability, and favorable biocompatibility. Nevertheless, traditional preparation methods for CDs generally suffer from drawbacks that run counter to the concept of green chemistry. This review comprehensively summarizes the green synthesis technologies, machine learning (ML)-assisted synthesis strategies, and diversified application fields of fluorescent CDs. Specifically, it discusses the characteristics of synthetic organic molecular/polymeric materials and natural sources (e.g., plants and fruit peels, etc.) and elaborates on the top-down and bottom-up green synthesis methods, analyzing their advantages. It also focuses on ML's core role in precisely regulating CD emission wavelengths, enhancing and predicting fluorescence quantum yields to optimize synthesis processes. Additionally, this review highlights the representative biological applications of CDs, including biosensing and biomedicine (e.g., bioimaging, drug delivery, and photodynamic therapy), while briefly covering their applications in other fields. Finally, the review points out current challenges in green synthesis, ML-assisted applications and industrial translation, and puts forward future research directions, aiming to promote the greenization, intellectualization and large-scale development of CDs.

Indexed as

Carbon Quantum DotsFluorescent DyesGreen Chemistry TechnologyAnimalsCatalysisFluorescenceHumansMachine LearningOxidation-ReductionFluorescent Dyesbioimagingcarbon dotscatalysisgreen synthesismachine learningsensing

Identifiers

PMID42505432
PMCPMC13406746

What OpenQuestion holds

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LicenceCC BY
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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.