Crosslink-enhanced strategy to achieve multicolor long-lived room temperature phosphorescent films with excellent photostability

Machine learning-assisted fluorescence visualization for sequential quantitative detection of aluminum and fluoride ions

The presence of aluminum (Al3+) and fluoride (F-) ions in the environment can be harmful to ecosystems and human health, highlighting the need for accurate and efficient monitoring. In this paper, an innovative approach is presented that leverages the power of machine learning to enhance the accuracy and efficiency of fluorescence-based detection for sequential quantitative analysis of aluminum (Al3+) and fluoride (F-) ions in aqueous solutions. The proposed method involves the synthesis of sulfur-functionalized carbon dots (C-dots) as fluorescence probes, with fluorescence enhancement upon interaction with Al3+ ions, achieving a detection limit of 4.2 nmol/L. Subsequently, in the presence of F- ions, fluorescence is quenched, with a detection limit of 47.6 nmol/L. The fingerprints of fluorescence images are extracted using a cross-platform computer vision library in Python, followed by data preprocessing. Subsequently, the fingerprint data is subjected to cluster analysis using the K-means model from machine learning, and the average Silhouette Coefficient indicates excellent model performance. Finally, a regression analysis based on the principal component analysis method is employed to achieve more precise quantitative analysis of aluminum and fluoride ions. The results demonstrate that the developed model excels in terms of accuracy and sensitivity. This groundbreaking model not only showcases exceptional performance but also addresses the urgent need for effective environmental monitoring and risk assessment, making it a valuable tool for safeguarding our ecosystems and public health.

Unveiling the potential of triphenylphosphine salts in tuning organic room temperature phosphorescence

Triphenylphosphine (TPP) salt derivatives, with their rich chemistry of core-substitution, have emerged as promising candidates for ultralong room temperature phosphorescence (RTP) materials owing to their distinct molecular structures, high quantum efficiency and exceptional phosphorescence properties. This feature article highlights the vast potential of TPP salt derivatives in tunable RTP properties by exploring some factors such as the alkyl chains, halogen anions, through-space charge transfer states, etc., and recent advancements in multi-level information encryption, high-level anticounterfeiting tags and X-ray imaging applications. We anticipate that this article will assist in directing future analyses based on the mechanisms underlying the RTP behavior of TPP derivatives and offer guidance for the rational design of high-performance RTP materials.

Achieving Efficient Dark Blue Room-Temperature Phosphorescence with Ultra-Wide Range Tunable-Lifetime

Tunable-lifetime room-temperature phosphorescence (RTP) materials have been widely studied due to their broad applications. However, only few reports have achieved wide-range lifetime modulation. In this work, ultra-wide range tunable-lifetime efficient dark blue RTP materials were realized by doping methyl benzoate derivatives into polyvinyl alcohol (PVA) matrix. The phosphorescence lifetimes of the doped films can be increased from 32.8 ms to 1925.8 ms. Such wide range of phosphorescence lifetime modulation is extremely rare in current reports. Moreover, the phosphorescence emission of the methyl 4-hydroxybenzoate-doped film is located in the dark blue region and the phosphorescence quantum yield reaches as high as 15.4 %, which broadens their applications in organic optoelectronic information. Further studies demonstrated that the reason for the tunable lifetime was that the magnitude of the electron-donating ability of the substituent group modulates the HOMO-LUMO and singlet-triplet energy gap of methyl benzoate derivatives, as well as the ability to non-covalent interactions with PVA. Moreover, the potential applications of luminescent displays and optical anti-counterfeiting of these high-performance dark blue RTP materials have been conducted.

Construction of smartphone-adapted signal visualization platform for dual-mode detection of H2S based on integrated metal-organic framework nanoprobes

Hydrogen sulfide (H2S) is a toxic contaminant and has great influence on many physiological processes. Due to various pathophysiological roles and environmental pollution problems, it is necessary to construct and develop simple and portable monitoring sensors for the precise detection of H2S. Herein, we developed a smartphone-adapted dual-mode detection platform by integrating the colorimetric and photothermal imaging analysis into a metal-organic framework-based chip (ZIF-8/Cu). Due to the nanoconfinement effect of ZIF-8, small-sized plasmonic CuS could be in-situ formed during the detection procedure of H2S and endowed the chips with excellent photothermal properties. By constructing a smartphone-adapted photothermal imager, the metal-organic framework-based chip could achieve a portable photothermal imaging analysis of H2S. Moreover, as the formed CuS was a good peroxidase-like nanozyme, the chips could also be used to trigger the enzymic catalytic reaction toward the chromogenic reaction of 3,3',5,5'-tetramethylbenzidine (TMB)-H2O2, thus providing another colorimetric sensing mode by using a smartphone App. In this smartphone-adapted visualization platform, the portable chemosensors could simultaneously achieve double detection modes at one electrode, which provided a new pathway for the accurate detection of H2S and circumvented the false-positive or negative errors during the detection process. Besides, by using the finite difference time domain (FDTD) simulation method, the in-depth mechanism, including the plasmonic effect and spatial electromagnetic field distribution, was explored to provide a possible reason for the excellent sensing performance of the dual-mode visualization platform. This work provides a new insight into the construction of the accurate, portable and smart sensing platform in the visual screening of H2S.

Intelligent quantitative recognition of sulfide using machine learning-based ratiometric fluorescence probe of metal-organic framework UiO-66-NH2/Ppix

Sulfides possess either high toxicity or play crucial physiological role such as gas transmitter dependent upon dosage, hence the significant for their rapid sensitive and selective concentration determination. Herein, a machine learning enhanced ratiometric fluorescence sensor was engineered for sulfide determination by incorporating the nanometal-organic framework (UiO-66-NH2) along with protoporphyrin IX (Ppix). The blue fluorescence at 431 nm originated from the moiety of UiO-66-NH2 by 365 nm excitation serves as an internal calibration reference signal, while the red fluorescence at 629 nm from the moiety of Ppix serves as the analytical signal, and the intensity is correlated to the amount of sulfides. The fluorescence color of the sensor gradually varies from blue to red upon sequential addition of copper and sulfide ions, resulting in RGB (Red, Green, Blue) feature values for corresponding sulfide concentrations, which facilities the advanced data processing techniques using machine learning algorithms. On the basis of fluorescence image fingerprint extraction and machine learning algorithms, an online data analysis model was developed to improve the precision and accuracy of sulfide determination. The established model employed Linear Discriminant Analysis (LDA) and was subjected to rigorous cross-validation to ensure its robustness. By analyzing the correlation between RGB feature values and sulfide concentrations, the study highlighted a significant positive relationship between the red feature values and sulfide concentrations. The application of machine learning techniques on the ratiometric fluorescence signal of the UiO-66-NH2/Ppix probe demonstrated its potential for intelligent quantitative determination of sulfides, offering a valuable and efficient tool for pollution detection and real-time rapid environmental monitoring.

Paper-based microfluidics and tailored gold nanoparticles for visual colorimetric detection of multiplex allergens

The highly efficient and accurate recognition of targeted allergens is an essential element in the diagnosis of allergic diseases and follow-up desensitization treatment in clinic. The current clinical methods widely used to detect sIgE are high cost, time-consuming procedures, and bulky equipment. Herein, a multiplex microfluidic paper-based device (multi-μPAD) was developed that combined with tailored gold nanoparticles for simultaneously visual, colorimetric detection of different allergens in serum. This device could be used as quantitative detection of sIgE with LOD as low as 0.246 KUA/L in colorimetric method. In vitro results also showed that this device possessed good repeatability, high accuracy and incredible stability in different pH (6.0-7.4) and temperature (24-37 °C), as well as long-term storage within 90-day. Finally, this method was successfully utilized for assessing clinical multi-sample screening in 35 allergic patients. After the addition of the samples from allergic patients, the agreement rate of clinical results with commercial enzyme-linked immunosorbent assay (ELISA) kit reached more than 97%, which further indicated that this device had the advantages of efficient, accurate and sensitive to screen various allergens in real clinical serum samples. Therefore, by simply altering antigens and antibodies, this device can also be used for high-throughput detection of other allergens, making it considerable potential for clinical diagnosis of allergic diseases.

Full-color persistent room temperature phosphorescent elastomers with robust optical properties

Persistent room temperature phosphorescent materials with unique mechanical properties and robust optical properties have great potential in flexible electronics and photonics. However, developing such materials remains a formidable challenge. Here, we present highly stretchable, lightweight, and multicolored persistent luminescence elastomers, produced by incorporating ionic room temperature phosphorescent polymers and polyvinyl alcohol into a polydimethylsiloxane matrix. These prepared elastomers exhibit high optical transparency in daylight and emit bright persistent luminescence after the removal of 365 nm excitation. The homogeneous distribution of polymers within the matrix has been confirmed by confocal fluorescence microscopy, scanning electron microscopy, and atomic force microscopy. Mechanical property investigations revealed that the prepared persistent luminescence elastomers possess satisfactory stretchability. Impressively, these elastomers maintain robust optical properties even under extensive and repeated mechanical deformations, a characteristic previously unprecedented. These fantastic features make these persistent luminescence elastomers ideal candidates for potential applications in wearable devices, flexible displays, and anti-counterfeiting.