Sensors for the environmental pollutant detection: Are we already there?

Zhang, Yi; Zeng, Zhuotong; Zeng, Guangming; Xiao, Rong; Wang, Yingrong; Hu, Yi; Tang, Lin; Feng, Chongling

doi:10.1016/j.ccr.2020.213681

Cited by 60 publications

(26 citation statements)

References 211 publications

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“…However, these techniques are rather cumbersome and are not suitable for in situ measurements . In the realm of nanotechnology, also sensors based on graphene, carbon dots, − fluorescent quantum dots, carbon nanotubes, and so on , have been often reported in the literature. Among these, very low detection thresholds have been obtained in particular for Hg ions: for example, Zhang et al have reached attomolar mercury detection by combining graphene with Au NPs; Amiri et al have even achieved a zeptomolar detection limit by using double-stranded DNA on a gold electrode .…”

Section: Resultsmentioning

confidence: 99%

“…The results are very promising in view of the engineering of boron-based nanomaterials for nanosensing and other prospective nanotechnologies. In fact, the important ease of the synthesis of our nanosensors constitutes a noteworthy matter of interest in the field of environmental monitoring, since it typically requires a huge implementation scale to be really useful …”

Section: Introductionmentioning

confidence: 99%

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Fluorescent Boron Oxide Nanodisks as Biocompatible Multi-messenger Sensors for Ultrasensitive Ni²⁺ Detection

Terracina

Mauro

Balle

et al. 2023

ACS Appl. Nano Mater.

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Boron-based nanocomposites are very promising for a wide range of technological applications, spanning from microelectronics to nanomedicine. A large variety of B-based nanomaterials has been already observed, such as borospherene, B nanotubes and nanoparticles, and boron nitride nanoparticles. However, their fabrication usually involves toxic precursors or leads to very low yields or small boron atom concentration. In this work, we report the synthesis of nanometric B 2 O 3 nanodisks, a family of nanomaterials with a quasi-2D morphology capable of intense fluorescence in the visible range. Such as boron-based nanomaterial, which we synthesized by pulsed laser ablation of a boron target, is water-dispersible and nontoxic, and displays a highly crystalline structure. Moreover, its bright blue photoluminescence is highly sensitive and selective for the presence of Ni 2+ ions in solution, down to extremely small concentrations in the picomolar range. The results are very promising in view of the use of such novel B 2 O 3 nanodisks as ultrasensitive multi-messenger Ni 2+ nanosensors.

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Section: Resultsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Fluorescent Boron Oxide Nanodisks as Biocompatible Multi-messenger Sensors for Ultrasensitive Ni²⁺ Detection

Terracina

Mauro

Balle

et al. 2023

ACS Appl. Nano Mater.

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show abstract

“…In environmental pollutant detection, the proposed AI approach may help further simplify and automate the analysis process of the atmosphere pollutant composition such as VOCs. [ 43 ] And, in the field of healthcare, the proposed AI approach may inspire the design of smart sensors for detecting the human secretions (such as urine, [ 44 ] sweat, [ 45 ] and exhale breath [ 46 ] ) which can be used for health monitoring and disease diagnosis.…”

Section: Discussionmentioning

confidence: 99%

Selective Detection of Mixtures via a Single Nonselective Sensor—Making the Unworkable Sensor Workable by Machine Learning

Liu

et al. 2022

Advanced Intelligent Systems

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Highly selective and sensitive detection of chemical mixtures by a single sensor consistently suffers from overlapping response signals. Previous researchers have to make a detour to avoid overlapping through preparing selective sensor materials, tedious preseparation, and time‐consuming operation. Nowadays, machine learning (ML), as one remarkable branch of artificial intelligence (AI), possesses advantages to modernize pathways to approach chemical challenges and provides a novel short cut for chemical mixture detection. Herein, a challenging example of a single nonselective cataluminescence (CTL) sensor with nonequilibrium and especially nonlinear responses is taken for chemical mixture detection. Intelligent recurrent neural networks (RNNs) with gated recurrent units are applied to directly predict mixture component contents from overlapping signals and achieve 100% and 92.22% of prediction accuracy for known and unknown samples, respectively. Furthermore, the physical law of response overlapping is revealed to support the mechanism of the proposed approach. The introduction of RNN into selective sensing not only initiates a distinctive and simple pathway for selective quantitative detection of mixtures via a single nonselective sensor but also can inspire future intelligent detection approaches in analytical chemistry, biological analysis, environmental monitoring, healthcare, clinical therapy, etc.

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“…Various functional materials are also used in environmental sensors, such as graphene, carbon nanotubes, graphitic carbon nitride, nano metals and their oxide materials, conductive polymer materials, nanoparticles, and mesoporous materials. The sensing method for the detection of environmental pollutants is still in the laboratory research stage, but they have good potential because of the attributes they have such as low cost, flexibility, portability, high selectivity, and high accuracy (Zhang et al, 2021).…”

Section: Techniques For the Detection Of Pollutantsmentioning

confidence: 99%

Recent advances in the elimination of persistent organic pollutants by photocatalysis

Gaur

Dutta

Singh

et al. 2022

Front. Environ. Sci.

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The non-ending needs of growing human population are being met by rapid industrialization and globalization, which have nowadays become an indispensable component of growth. Although these activities have led to phenomenal growth of the human civilization, at the same time, they have resulted in severe environmental pollution by discharge of highly toxic waste. This waste is severely detrimental not only for the environment but also for the health of the human population. Among different classes of pollutants, one being considered as one of the highly toxic ones is that of persistent organic pollutants (POPs). Advanced oxidation technologies (AOTs) play a major role in the degradation of pollutants by converting organic pollutants into CO2, H2O, and mineralized inorganic ions. AOTs include UV-based photocatalysis, ozonation, electrochemical oxidation, and Fenton and Fenton-like processes There are some difficulties and challenges associated with AOT, such as being highly capital intensive and high consumption of energy. To overcome these bottlenecks, photocatalytic degradation is a promising method that uses solar energy for the degradation of such pollutants. Photocatalysis is further classified into homogenous and heterogenous photocatalysis. As a part of heterogenous photocatalysis, semiconductor photocatalysts have received great attention; but because of their drawbacks such as the recombination of the electron/hole pair, low adsorption rate, and low surface area coverage, nanotechnology was considered for bringing a novel and enhanced remediation photocatalysis process. To this end, the designing of a more efficient photocatalyst by modifying morphology, composition, and structure and reducing toxicity is the need of the hour for the abatement of environmental pollutants. This review focuses on the degradation and removal of highly toxic persistent organic pollutants by using photocatalytic degradation with a detailed account of the various pollutants, their degradation mechanism, process shortcomings, remedial measures, and future prospects.

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Sensors for the environmental pollutant detection: Are we already there?

Cited by 60 publications

References 211 publications

Fluorescent Boron Oxide Nanodisks as Biocompatible Multi-messenger Sensors for Ultrasensitive Ni²⁺ Detection

Fluorescent Boron Oxide Nanodisks as Biocompatible Multi-messenger Sensors for Ultrasensitive Ni²⁺ Detection

Selective Detection of Mixtures via a Single Nonselective Sensor—Making the Unworkable Sensor Workable by Machine Learning

Recent advances in the elimination of persistent organic pollutants by photocatalysis

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Sensors for the environmental pollutant detection: Are we already there?

Cited by 60 publications

References 211 publications

Fluorescent Boron Oxide Nanodisks as Biocompatible Multi-messenger Sensors for Ultrasensitive Ni2+ Detection

Fluorescent Boron Oxide Nanodisks as Biocompatible Multi-messenger Sensors for Ultrasensitive Ni2+ Detection

Selective Detection of Mixtures via a Single Nonselective Sensor—Making the Unworkable Sensor Workable by Machine Learning

Recent advances in the elimination of persistent organic pollutants by photocatalysis

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Product

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Fluorescent Boron Oxide Nanodisks as Biocompatible Multi-messenger Sensors for Ultrasensitive Ni²⁺ Detection

Fluorescent Boron Oxide Nanodisks as Biocompatible Multi-messenger Sensors for Ultrasensitive Ni²⁺ Detection