Low-cost devices with fluorescence spots brightness and size dual-mode readout for the rapid detection of Cr(VI) based on smartphones

High-efficient nickel-doped lignin carbon dots as a fluorescent and smartphone-assisted sensing platform for sequential detection of Cr(VI) and ascorbic acid

Using lignin as a raw material to prepare fluorescent nanomaterials represents a significant pathway toward the high-value utilization of waste biomass. In this study, Ni-doped lignin carbon dots (Ni-LCDs) were rapidly synthesized with a yield of 63.22 % and a quantum yield of 8.25 % using a green and simple hydrothermal method. Exploiting the inner filter effect (IFE), Cr(VI) effectively quenched the fluorescence of the Ni-LCDs, while the potent reducing agent ascorbic acid (AA) restored the quenched fluorescence, thus establishing a highly sensitive fluorescence switch sensor platform for the sequential detection of Cr(VI) and AA. Importantly, the integration of a smartphone facilitated the portability of Cr(VI) and AA detection, enabling on-site, in-situ, and real-time monitoring. Ultimately, the developed fluorescence and smartphone-assisted sensing platform was successfully applied to detect Cr(VI) in actual water samples and AA in various fruits. This study not only presents an efficient method for the conversion and utilization of waste lignin but also broadens the application scope of the CDs in the field of smart sensors.

Rapid and sensitive smartphone non-enzymatic colorimetric assay for the detection of glucose in food based on peroxidase-like activity of Fe3O4@Au nanoparticles

A low-cost and reliable analytical method based on the combination of a newly designed Fe3O4@Au as peroxidase mimetics, supported on smartphone analysis software package was proposed for the determination of glucose content in food samples. The nanocomposite was prepared by self-assembling technique, and the characterization was carried out using transmission electron microscopy (TEM), Fourier transforms infrared, and X-ray diffractometer. Record the color change of the solution with a smartphone camera and optimize the operation parameters and reaction conditions. A smartphone with a free self-developed app was accustomed live the RGB (red-greenblue) values of color intensity within the Fe3O4@Au system and were processed with Image J software before computationally convert them glucose concentrations. At the optimization experiment, reaction temperature of 60 °C, reaction time of 50 min and the amount of addition of Fe3O4@Au 0.0125 g was the optimal combination of detecting glucose smartphone color detection system. Hereon, the accuracy of the proposed method was evaluated by comparison between smartphone colorimetry and UV-vis spectrophotometer, a linear calibration in the range of 0.25 ∼ 15 mmol/L glucose was obtained with minimum detection limit of 1.83 and 2.25 μmol/L, respectively. The proposed method was applied effectively to the detection of glucose in actual samples. The results were in accordance with the conventional UV-vis spectrophotometer method.

Application of three-dimensional printing technology in environmental analysis: A review

The development of environmental analysis devices with high performance is essential to assess the potential risks of environmental pollutants. However, it is still challenging to develop environmental analysis equipment with miniaturization, portability, and high sensitivity based on traditional processing techniques. In recent years, the popularity of 3D printing technology (3DP) with high precision, low cost, and unlimited design freedom has provided opportunities to solve the existing challenges of environmental analysis. 3D printing has brought solutions to promote the high performance and versatility of environmental analysis equipment by optimizing printing materials, enhancing equipment structure, and integrating multidisciplinary technology. In this paper, we comprehensively review the latest progress in 3D printing in various aspects of environmental analysis procedures, including but not limited to sample collection, pretreatment, separation, and detection. We highlight their advantages and challenges in determining various environmental contaminants through passive sampling, solid-phase extraction, chromatographic separation, and mass spectrometry detection. The manufacturing of 3D-printed environmental analysis devices is also discussed. Finally, we look forward to their development prospects and challenges.

A Low-Cost Microfluidic-Based Detection Device for Rapid Identification and Quantification of Biomarkers-Based on a Smartphone

The sensitive and rapid detection of microsamples is crucial for early diagnosis of diseases. The short response times and low sample volume requirements of microfluidic chips have shown great potential in early diagnosis, but there are still shortcomings such as complex preparation processes and high costs. We developed a low-cost smartphone-based fluorescence detection device (Smartphone-BFDD) without precision equipment for rapid identification and quantification of biomarkers on glass capillary. The device combines microfluidic technology with RGB image analysis, effectively reducing the sample volume to 20 μL and detection time to only 30 min. For the sensitivity of the device, we constructed a standard sandwich immunoassay (antibody-antigen-antibody) in a glass capillary using the N-protein of SARS-CoV-2 as a biological model, realizing a low limit of detection (LOD, 40 ng mL^-1). This device provides potential applications for different biomarkers and offers wide use for rapid biochemical analysis in biomedical research.

Analytical applications of smartphones for agricultural soil analysis

Soil is one of the most important farming resources. Appropriate managing of its quality promotes productive and sustainable agriculture. The valuable farm practice in soil quality managing is based on regular soil analysis with the aim of determining the exact amount of nutrients or other chemical, physical, and biological soil properties. Soil analysis usually requires sample collection at the desired sampling depth followed by sample delivery to chemical laboratories. However, laboratory analyses are resource-intensive and costly, and require a lot of time, effort, and equipment. A low-cost, fast, and effective alternative for soil quality control is the application of smartphones to perform chemical analyses directly in the field or on the farm. In this paper, an overview of recent developments on smartphone-based methodologies for agricultural purposes and portable evaluation of soil quality and its properties is presented. The discussion focuses on recent applications of smartphone-based devices for the determination of basic soil parameters, content of organic matter, mineral fertilizers, and organic or inorganic pollutants. Obvious advantages of using smartphones, such as convenience and simplicity of use, and the main shortcomings, such as relatively poor precision of the results obtained, are also discussed. The general trend shows the huge interest from researchers to move the technology into the field with the aim of providing cost-effective and rapid soil analysis. This paper can broaden the understanding of using smartphones for chemical analysis of soil samples, as it is a relatively new area and is expected to be developed rapidly.

Dandelion-like covalent organic frameworks with high-efficiency fluorescence for ratiometric sensing and visual tracking-by-detection of Fe3

Iron ions, one of the most common heavy metal pollutants in industrial waste materials, are continuously actively or passively delivered to the environment. Meanwhile, the importance of Fe³⁺ in biological processes in vivo can not be neglected due to its crucial role in maintaining normal physiological function. Therefore, a ratiometric fluorescence covalent organic framework (TD-COF) was constructed for tracking-by-detection of Fe³⁺. Alkynes-extended 1,3,6,8-tetrakis(4-ethynyl benzaldehyde)-pyrene (TEBPY) with complete planar structure and 2,5-dihydroxyterephthalohydrazide (DHTH) with functional group -OH were selected as the building blocks. The ratiometric fluorescence TD-COF with a dandelion-like structure exhibited its dual emission peaked at 510 nm and 630 nm. It displayed an obvious fluorescence color variation of yellow-red-black in the presence of Fe³⁺. Benefiting from the high luminescent efficiency (QY of 36.4%) and multiple identical binding sites, TD-COF exhibited a wide linear range to Fe³⁺ (0.005-50 μM) with a detection limit of 10.9 nM. Additionally, a smartphone visual sensing platform integrated with TD-COF was developed based on the color transformation and successfully applied to visual smart real-time monitoring Fe³⁺. More surprisingly, the maximum adsorption capacity of TD-COF towards Fe³⁺ was 833.3 mg/g due to the coordination interaction and cationic π-effect. The practicability of the smartphone-integrated ratiometric sensing platform for visual tracking-by-detection of Fe³⁺ was verified by choosing tap water as the actual sample, and the recoveries were calculated to be 98.71-100.88%. This work thus developed COF-based ratiometric sensing of Fe³⁺, which is an attractive candidate for further application in fluorescent sensing and visual monitoring.

Environmental application of a cost-effective smartphone-based method for COD analysis: Applicability in the electrochemical treatment of real wastewater

This study aims to develop a cheap method for the evaluation of quality of water or the assessment of the treatment of water by chemical oxygen demand (COD) measurements throughout the use of the HSV color model in digital devices. A free application installed on a smartphone was used for analyzing the images in which the colors were acquired before to be quantified. The proposed method was also validated by the standard and spectrophotometric methods, demonstrating that no significant statistical differences were attained (average accuracy of 97 %). With these results, the utilization of this smartphone-based method for COD analysis was used/evaluated, for first time, by treating electrochemically a real water matrix with substantial organic and salts content using BDD and Pt/Ti anodes. Aiming to understand the performance of both anodes, bulk experiments were performed under real pH by applying current densities (j) of 15, 30, and 60 mA cm^-2. COD abatement results (which were achieved with this novel smart water security solution) clearly showed that different organic matter removal efficiencies were achieved, depending on the electrocatalytic material used as well as the applied current density (42 %, 45 %, and 85 % for Ti/Pt while 93 %, 97 % and total degradation for BDD by applying 15, 30, and 60 mA cm^-2, respectively). However, when the persulfate-mediated oxidation approach was used, with the addition of 2 or 4 g Na₂SO₄ L^-1, COD removal efficiencies were enhanced, obtaining total degradation with 4 g Na₂SO₄ L^-1 and by applying 15 mA cm^-2. Finally, this smartphone imaging-based method provides a simple and rapid method for the evaluation of COD during the use of electrochemical remediation technology, developing and decentralizing analytics technologies for smart water solutions which play a key role in achieving the Sustainable Development Goal 6 (SDG6).

Enzyme-free and rapid visual quantitative detection for pesticide residues utilizing portable smartphone integrated paper sensor

Serious toxicity for organisms from pesticide glyphosate (Gly) residues to the ecosystem and human health has become a consensus. Rapid and selective detection of glyphosate, especially using a simple and portable instrument, is highly desired. In this work, we develop a novel enzyme-free rapid and visual ratiometric fluorescence sensor for selectively quantitative detecting glyphosate by integrating the designed blue carbon nanodots (CDs) and gold nanoclusters (Au NCs). The fluorescence of CDs can be quickly quenched via aggregation-caused quenching (ACQ) within 2 s after introducing glyphosate, resulting from the formation of CDs-Gly-CDs complex aggregation. While the Au NCs serve as the reference signal without any change, therefore leading to obvious and instant ratiometric fluorescence variation from blue to pink to orange. The broad linear range was obtained from 0 to 180 nM with a satisfactory detection limit of 4.19 nM. Furthermore, this approach was successfully applied to detect glyphosate in real samples and a portable smartphone platform integrated paper sensor was developed for in-site visual quantitative glyphosate detection, offering a promising strategy for the construction of enzyme-free trace hazard detection system.

A handheld multifunctional smartphone platform integrated with 3D printing portable device: On-site evaluation for glutathione and azodicarbonamide with machine learning

Azodicarbonamide (ADA) in flour can be easily decomposed to semi-carbazide and biuret, exhibiting strong genotoxicity in vitro and carcinogenicity. Glutathione (GSH) can be conjugated with some ketone-containing compounds and unsaturated aldehydes to form toxic metabolites. Here, a novel ratio fluorescence probe based on blue emitting biomass-derived carbon dots (BCDs) and yellow emitting 2,3-diaminophenazine (OxOPD) was prepared for the bifunctional determination of glutathione (GSH) and ADA. This strategy includes three processes: (1) Ag⁺ oxidizes o-phenylenediamine (OPD) to produce OxOPD. The peak at 562 nm was enhanced, and the peak at 442 nm was reduced due to fluorescence resonance energy transfer (FRET), (2) glutathione binds Ag⁺ and inhibits the production of OxOPD, (3) ADA oxidizes GSH to form GSSG, resulting in the release of Ag⁺ by GSH. Therefore, the newly designed ratio fluorescence probe can be based on the intensity ratio (I₄₄₂/I₅₆₂) changes and significant fluorescent color changes to detect GSH and ADA. Moreover, a smartphone WeChat applet and a yolov3-assisted deep learning classification model have been developed to quickly detect GSH and ADA on-site based on an image processing algorithm. These results indicate that smartphone ratiometric fluorescence sensing combined with machine learning has broad prospects for biomedical analysis.