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This study introduces a novel photoelectrochemical (PEC) sensor for the highly selective detection of sulfur dioxide (SO2) using an organic photoactive molecule probe (OPM). OPM is synthesized through a one‐step coupling reaction, featuring a typical photosensitizer D‐π‐A structure. By covalently bonding OPM with a TiO2 substrate, a PEC sensor is constructed, exhibiting a significant photocurrent response under visible light excitation. The specific addition reaction between SO2 and OPM disrupts its conjugated structure, reducing the photocurrent response and achieving highly selective detection of SO2. The sensor demonstrates excellent performance in real water samples, emphasizing its practical applications. [ABSTRACT FROM AUTHOR]

Highly thermostable RhB@Zr-Eddc composites with the Rhodamine B (RhB) enclosed into the nanocages of Zr-Eddc was synthesized by one-pot method under hydrothermal conditions, whose structure, morphology and stability were characterized through the X-ray powder diffractometry (XRD), scanning electron microscopy (SEM) and thermogravimetric analysis (TGA). RhB@Zr-Eddc showed the highly thermal stability up to 550°C and emitted the bright red-light emission at 605 nm, which could highly selective detect the nitrofurazone (NFZ) among eleven other antibiotics in aqueous solution. Furthermore, via combining the RhB@Zr-Eddc with commercial green phosphor (Y3Al5O12:Ce3+, Ga3+), the mixture was encapsulated onto a 455 nm blue LED chip, creating an excellent white light emitting diode (WLED) device with the correlated colour temperature (CCT) of 4710 K, luminous efficiency (LE) of 43.17 lm/w and Color Rendering Index (CRI) of 89.2. [ABSTRACT FROM AUTHOR]

Two imidazole‐based color‐changing fluorescent probes 4‐(4,5‐bis(4‐chlorophenyl)‐1H‐imidazol‐2‐yl)‐N, N‐diphenylaniline (CIN) and 4‐(4,5‐di(furan‐2‐yl)‐1H‐imidazol‐2‐yl)‐N, N‐diphenylaniline (FIN) were synthesized and characterized. The new probes CIN and FIN exhibit excellent selectivity and sensitivity towards Fe3+ with relatively low detection limits (0.26 μM and 0.10 μM) and strong anti‐interference properties. Both the probes CIN and FIN complex 1 : 1 with Fe3+ ion, and the complexation constants were 1.165×105 M−1 (CIN) and 1.899×105 M−1 (FIN), respectively. Moreover, CIN and FIN could be recycled by EDTA and could effectively monitor Fe3+ ions at pH 4–10, which ensures the sensor's potential for detecting Fe3+ in actual aqueous solutions. The probes were further applied to the detection of Fe3+ in the actual reaction of Fe2+ oxidation, and the filter paper and the probe solution are combined to make an indicator to detect Fe3+ more conveniently and quickly. [ABSTRACT FROM AUTHOR]

The main contribution of semiconductor nanomaterials to surface-enhanced Raman scattering (SERS) comes from charge transfer (CT) between the absorbing molecules and the semiconductor. However, it is still challenging to realize the combined effects of the electromagnetic mechanism (EM) and the chemical mechanism (CM) for semiconductor-based SERS substrates. Herein, we demonstrate and design double-shelled ZnO (ZnO-DS) hollow microspheres by a modified hydrothermal/solvothermal process. SERS experiments and theoretical simulations proved that the excellent SERS activity is mainly attributed to the combined effect of Mie resonances generated by the nanocavities in the unique hollow double-shell nanoparticles and the CT effect excited by special structure ZnO. Particularly, the produced ZnO-DS SERS substrates exhibited a low limit of detection (LOD, 1 × 10–7 M for 4-MPY), outstanding sensitivity (EF = 1.2 × 104), and high stability (RSD = 10.4%, over 30 days of storage at room temperature). Furthermore, benefiting from the matching of energy levels of the ZnO-DS substrate and probe molecules, the sulfhydryl molecules with similar structures could be selectively distinguished in complex environments. We visualize that this work will resolve the current dilemma between sensitivity and selective detection of SERS substrates and expect to enable the monitoring of target molecules in the environment containing complex mixtures such as food safety and environmental protection. [ABSTRACT FROM AUTHOR]

Alendronate-functionalized graphene quantum dots (ALEN-GQDs) with a quantum yield of 57% were synthesized via a two-step route: preparation of graphene quantum dots (GQDs) by pyrolysis method using citric acid as the carbon source and post functionalization of GQDs via a hydrothermal method with alendronate sodium. After careful characterization of the obtained ALEN-GQDs, they were successfully employed as sensing materials with superior selectivity and sensitivity for the detection of nanomolar levels of arsenic ions (As(III)). According to the mechanistic investigation, arsenic ions can quench the fluorescence intensity of ALEN-GQDs through metal-ligand interaction between the As(III) ions and the surface functional groups of the fluorescent probe. This probe provided a rapid method to monitor As(III) with a wide detection range (44 nM–1.30 µM) and a low detection limit of 13 nM. Finally, to validate the applicability, this novel fluorescent probe was successfully applied for the quantitative determination of As(III) in rice and water samples. [ABSTRACT FROM AUTHOR]

Highly thermostable RhB@Zr-Eddc composites with the Rhodamine B (RhB) enclosed into the nanocages of Zr-Eddc was synthesized by one-pot method under hydrothermal conditions, whose structure, morphology and stability were characterized through the X-ray powder diffractometry (XRD), scanning electron microscopy (SEM) and thermogravimetric analysis (TGA). RhB@Zr-Eddc showed the highly thermal stability up to 550°C and emitted the bright red-light emission at 605 nm, which could highly selective detect the nitrofurazone (NFZ) among eleven other antibiotics in aqueous solution. Furthermore, via combining the RhB@Zr-Eddc with commercial green phosphor (Y3Al5O12:Ce3+, Ga3+), the mixture was encapsulated onto a 455 nm blue LED chip, creating an ex-cellent white light emitting diode (WLED) device with the correlated colour temperature (CCT) of 4710 K, luminous efficiency (LE) of 43.17 lm/w and Color Rendering Index (CRI) of 89.2.

A novel optical probe has been successfully developed for the selective detection of Os(VIII) ions. This osmium-sensing platform was intricately designed by incorporating 4-(thiazol-2-yldiazenyl)benzene-1,3-diol (TDBD) as the ionophore within a plasticized PVC membrane, and tributylphosphate (TBP) serving as the plasticizer. Upon exposure to Os(VIII) ions in a 0.5 M HClO4 acid milieu, the sensing membrane undergoes a distinctive chromatic transition, shifting from a yellow to a pink hue. The preparation of the sensor and the methodology for Os(VIII) determination were meticulously refined to achieve optimal performance. Under these carefully optimized experimental conditions, the proposed optode demonstrated an impressive linear detection range spanning from 2.5 × 10−9 to 2.5 × 10−5 M for Os(VIII), alongside remarkable detection and quantification limits of 7.24 × 10−10 and 2.4 × 10−9 M, respectively. The sensor consistently delivered highly reproducible results, as evidenced by relative standard deviation (RSD) values of 1.45% and 1.30% for Os(VIII) concentrations at 7.5 × 10−7 and 2.5 × 10−6 M, respectively, underscoring its precision and reliability. Furthermore, the sensor exhibited a swift response time of 3.0 min, further emphasizing its efficiency. The incorporation of PIMs into the sensor architecture led to a remarkable eight-fold enhancement in its response compared to counterparts lacking PIMs, signifying a significant performance improvement. In assessing potential interference, an investigation into the influence of other ions on Os(III) determination revealed that the prepared sensor displayed exceptional selectivity for Os(VIII) ions, with negligible responses observed in the presence of common ions. Collectively, these experimental findings underscore the sensor's efficacy as an invaluable tool for the precise analysis of osmium content in water samples, aligning it with the rigorous standards of international scientific research.

AbstractOptimizing materials and associated structures for detecting various environmental gas pollutant concentrations has been a major challenge in environmental sensing technology. Semiconducting metal oxides (SMOs) fabricated at the nanoscale are a class of sensor technology in which metallic species are functionalized with various dopants to modify their chemiresistivity and crystalline scaffolding properties. Studies focused on recent advances of gas sensors utilizing metal oxide nanostructures with a special emphasis on the structure-surface property relationships of some typical n-type and p-type SMOs for efficient gas detection are presented. Strategies to enhance the gas sensor performances are also discussed. These oxide material sensors have several advantages such as ease of handling, portability, and doped-based SMO sensing detection ability of environmental gas pollutants at low temperatures. SMO sensors have displayed excellent sensitivity, selectivity, and robustness. In addition, the hybrid SMO sensors showed exceptional selectivity to some CWAs when irradiated with visible light while also displaying high reversibility and humidity independence. Results showed that TiO2 surfaces can sense 50 ppm SO2 in the presence of UV light and under operating temperatures of 298–473 K. Hybrid SMO displayed excellent gas sensing response. For example, a CuO–ZnO nanoparticle network of a 4:1 vol.% CuO/ZnO ratio exhibited responses three times greater than pure CuO sensors and six times greater than pure ZnO sensors toward H2S. This review provides a critical discussion of modified gas pollutant sensing capabilities of metal oxide nanoparticles under ambient conditions, focusing on reported results during the past two decades on gas pollutants sensing. [ABSTRACT FROM AUTHOR]

Silver nanocubes monolayer-modified polydimethylsiloxane (Ag NC/PDMS) flexible SERS substrates have been prepared by a three-phase interface self-assembly procedure. The combination of this method with membrane technology brings nanoparticles in close proximity, densely, and regularly arranged in monolayers over a large area, leading to excellent SERS properties. Considering the complexity of practical detection, molecular imprinted polymers (MIPs) were anchored on the surface of SERS substrate and applied to selective detection of microcystin-LR (MC-LR). It is worth mentioning that the SERS imprinted membranes (AP-MIMs) were still clearly detected at a concentration of 0.1 µg·L−1 of MC-LR in drinking water, and the detection limit was as low as 0.0067 µg·L−1. The substrate exhibited excellent uniformity with a relative standard deviation (RSD) of 6.1%. In the presence of interference molecules, AP-MIMs exhibited excellent selectivity for MC-LR. Furthermore, in the spiking and recovery tests of practical lake water samples, the method showed excellent recoveries ranging from 96.47 to 105.31%. It has been demonstrated that the prepared AP-MIMs can be applied to sensitive and specific detection of trace amounts of MC-LR in drinking water. [ABSTRACT FROM AUTHOR]

In chronic hepatitis B (CHB) patients, quantification of HBV pgRNA in plasma has the potential to provide information on disease prognosis and liver injury or histopathology. However, current methods for detecting HBV pgRNA present technical difficulties due to the co-existence of HBV DNA in plasma samples. We have successfully established a novel one-step RT-PCR assay that allows selective quantification of HBV pgRNA. Two cohorts of participants were recruited for assay validation, including treatment-naïve patients with CHB and HBeAg-positive CHB patients who were treated with Tenofovir and monitored for 6 months to assess the predictive value of baseline HBV RNA for HBeAg seroclearance. Statistical analysis was performed using MedCalc version 20.019 software. The novel selective one-step RT-PCR assay for detecting HBV pgRNA was validated with a limit of detection of 100 copies/mL. The assay was able to selectively measure HBV pgRNA even in the presence of excess HBV rcDNA. In treatment-naïve CHB patients, HBV pgRNA levels were significantly lower than HBV DNA concentration. Serum HBV DNA levels and HBeAg status were positively associated with HBV pgRNA. Baseline serum HBV pgRNA levels were found to be strong predictors of HBeAg seroclearance after 6 months of Tenofovir treatment. The study presents a novel RT-PCR assay that allows accurate measurement of plasma HBV pgRNA in chronic hepatitis B patients, even in the presence of excess HBV DNA. The assay is highly selective and represents a significant advancement with potential for further breakthroughs in understanding the clinical significance of HBV pgRNA. [ABSTRACT FROM AUTHOR]

Several studies have demonstrated that Ag2S QDs are promising near-infrared II-emitting nanoprobes. They Ag2S QDs can be used in the fields of bio-imaging, fluorescence detection and photodetectors. In this work, we achieved the first successful construction of a dual-input logic gate IMPLICATION gate based on the specific detection of Fe3+ by silver sulfide quantum dots and the reduction of Fe3+ by ascorbic acid. The Ag2S QDs were successfully prepared from glutathione and silver nitrate and characterized by fluorescence spectroscopy analysis, XPS analysis, and transmission electron microscopy TEM analysis. The prepared Ag2S QDs can achieve selective detection of Fe3+ with a detection limit of LOD of 0.15 mM. This work provides a new method for the detection of Fe3+.

MXene quantum dots (MXene QDs) are considered an excellent emerging zero-dimensional nanomaterial in recent times due to their excellent photophysical and chemical properties. Excitation-dependent emission properties, biocompatibility, photostability, and dispersion stability of these QDs undoubtedly prove to be active potential candidates for environmental and biomedical applications. This review paper focuses on the progress of MXene quantum dots synthesis via various approaches, their sensing toward various analytes, and bioimaging applications from the year 2017 to date. Varied types of approaches have been summarized to prepare high-quality dispersive MXene QDs with a good fluorescence quantum yield. Their formation mechanism via fragmentation and different characterizations has been well represented. The detailed analysis behind fluorescence from QDs has been also discussed. Next, selective recognition of various analytes, including metal ions, proteins, enzymes, drug molecules, and reactive oxygen species via the fluorescence modulation of the quantum dots, has been detailed and documented along with an in-depth mechanism. Their bioimaging application has also been represented. Finally, challenges and perspectives have been enlightened at the end. [ABSTRACT FROM AUTHOR]

WO 3 has attracted great attention for chemical gas sensing applications. However, the synthesis of WO 3 is mainly performed by using hazardous organic solvents and corrosive acidic solutions, which can result in environmental and health issues. The development of safe synthesis procedures using green compounds and solvents is in great demand to overcome the aforementioned drawbacks. Therefore, the effect of different eco-friendly chemical compounds on the growth of WO 3 materials has yet to be thoroughly studied. Meanwhile, the fabrication of material at the nanoscale with specific crystalline properties may improve its sensitivity to the target gas. In this work, we report an efficient method for the synthesis of WO 3 nanopowder by using water and a green surfactant such as vitamin C. The growth mechanism of the structure is analyzed considering the nature of solutions and surfactants. The studies indicate that the surfactant has a crucial effect on the formation of nanoparticles. Furthermore, the experimental findings show that the fabricated monoclinic WO 3 material is highly sensitive and selective to low concentrations of acetone. Moreover, the structure exhibits quite stable functionalities at different levels of environmental humidity. Hence, this work may have a considerable impact on the existing techniques for the preparation of WO 3 nanomaterials providing new insights into their green synthesis procedures. In addition, it can significantly affect the development of high-performance gas sensors and other catalytic devices based on WO 3 nanostructures. [Display omitted] [ABSTRACT FROM AUTHOR]

eDNA, also known as environmental DNA, has garnered significant attention due to its potential applications in various fields such as biodiversity assessment, species distribution monitoring, ecological interaction analysis, and quantitative analysis. However, the presence of non-selective DNA signals in eDNA samples poses challenges in accurately detecting species, assessing biodiversity, and conducting quantitative analysis. To address these limitations, this study developed a novel method for selectively detecting iDNA from specific species in eDNA samples. The method involved the application of PMA treatment to Alexandrium spp. effectively preventing the detection of non-selective exDNA signals. Additionally, by optimizing the filter size used in the sampling process, the researchers were able to selectively collect and analyze iDNA from species of interest, particularly Alexandrium spp. Furthermore, the study successfully demonstrated the selective collection and analysis of iDNA from Alexandrium spp. cysts present in the sediment layer, further strengthening the findings. The results indicated that the combined use of PMA treatment and filter size optimization significantly enhanced the selective detection capability of iDNA. The successful selective detection of iDNA from eDNA in the sediment layer highlights the practical applicability of the developed method. This study holds promise for advancing eDNA monitoring technology by providing a selective iDNA detection method utilizing PMA. Moreover, these findings lay the foundation for effectively utilizing iDNA in environmental conservation, monitoring, and ecological research.

With the recently increasing prevalence of deep learning, both academia and industry exhibit substantial interest in neuromorphic computing, which mimics the functional and structural features of the human brain. To realize neuromorphic computing, an energy‐efficient and reliable artificial synapse must be developed. In this study, the synaptic ferroelectric field‐effect‐transistor (FeFET) array is fabricated as a component of a neuromorphic convolutional neural network. Beyond the single transistor level, the long‐term potentiation and depression of synaptic weights are achieved at the array level, and a successful program‐inhibiting operation is demonstrated in the synaptic array, achieving a learning accuracy of 79.84% on the Canadian Institute for Advanced Research (CIFAR)‐10 dataset. Furthermore, an efficient self‐curing method is proposed to improve the endurance of the FeFET array by tenfold, utilizing the punch‐through current inherent to the device. Low‐frequency noise spectroscopy is employed to quantitatively evaluate the curing efficiency of the proposed self‐curing method. The results of this study provide a method to fabricate and operate reliable synaptic FeFET arrays, thereby paving the way for further development of ferroelectric‐based neuromorphic computing. [ABSTRACT FROM AUTHOR]

The substrate N1, N3, N5-tris(2-hydroxyphenyl)benzene-1,3,5-tricarboxamide (Sensor A) was prepared in the reaction of 1,3,5-benzenetricarboxylic acid (trimesic acid) and o-aminophenol in ethanol. The prepared organic sensor fulfills the chemiluminescent requirements including a luminophore, spacer, and suitable binding receptor that distress the probe's luminescent features, providing selective and sensitive detection of mercury and iron ions in aqueous solutions. The sensor selectively detects mercury and iron ions in a water matrix containing various metal ions, including sodium, calcium, magnesium, zinc, and nickel. Strong and immediate binding was observed between mercury ions and the substrate at pH 7.0 with a binding affinity toward Hg2+ 9-fold higher than that observed for iron sensor binding affinity, which makes the substrate a distinctive luminescence sensor for mercury detection at ambient conditions. The sensor shows a linear response toward Hg2+ in the concentration range from 50 ppb to 100 ppm (2.0 × 10−8 to 4.2 × 10−5 M) with a limit of detection of 2 ppb (1.0 × 10−8 M). Further, Sensor A provides linear detection for iron ions in the range from 10 ppb to 1000 ppm (1.5 × 10−8 to 1.5 × 10−3 M). The measured adsorption capacity of Sensor A toward mercury ions ranged from 1.25 to 1.97 mg/g, and the removal efficiency from water samples reached 98.8% at pH 7.0. The data demonstrate that Sensor A is an excellent probe for detecting and removing mercury ions from water bodies. [ABSTRACT FROM AUTHOR]

Reliable and direct detection of dopamine (DA), which is a crucial neurotransmitter, is required to diagnose dopamine-related diseases. However, the plasmonic colloidal sensing systems without prefunctionalization (e.g., aptamer, receptor, antibody, etc.) have not been well-established for trace DA detection yet. Herein, we develop a synchronous colorimetric and liquid-surface-enhanced Raman scattering (SERS) sensing system for the sensitive and selective detection of DA neurotransmitters using Au–Ag core–shell nanoparticles (Au@Ag CSNPs). The DA-mediated aggregation of Au@Ag CSNPs changed their plasmon resonance, leading to a distinct color change of the CSNP dispersion and generation of strong electromagnetic "hot spots" in the clustered CSNPs. Notably, the addition of Fe3+ ions to the CSNP dispersion intensified the DA-mediated aggregation of CSNPs, which significantly improved the colorimetric response and liquid-SERS detection of DA in the nanomolar range. Notably, the dual-mode sensing system without prefunctionalization demonstrated highly selective detection of the DA analyte against similar catecholamines (such as norepinephrine and epinephrine), which can be potentially applied to the selective discrimination of trace DA in real samples. [ABSTRACT FROM AUTHOR]

[Display omitted] Electronic skins detect external variables and have applications in smart scenarios. However, an isolated device is limited by its intrinsic properties and is only applicable in a limited number of cases. Electronic skins still face challenges in achieving multimodal performance while improving their key parameters. Therefore, multifunctional materials and device architectures are essential in multimodal electronic skins for efficient transfer of external stimuli into electrical signals. This review elaborates on the ideas and specific methods for constructing multimodal electronic skins from the following four aspects: distinguishing external stimuli, decomposing external stimuli, suppressing interference, and decoupling electrical output. The review focuses on sensing materials, mechanisms, structures, and signal decoupling in multimodal electronic skins. Conclusions concerning the effective approaches to immediate problems and potential opportunities in multimodal electronic skins are also provided. [ABSTRACT FROM AUTHOR]

Concerns about indoor and outdoor air quality, industrial gas leaks, and medical diagnostics are driving the demand for high-performance gas sensors. Owing to their structural variety and large surface area, reducible metal oxides hold great promise for constructing a gas-sensing system. While many earlier reports have successfully obtained a sufficient response to various types of target gases, the selective detection of target gases remains challenging. In this work, a novel method, low-frequency noise (LFN) spectroscopy is presented, to achieve selective detection using a single FET-type gas sensor. The LFN of the sensor is accurately modeled by considering the charge fluctuation in both the sensing material and the FET channel. Exposure to different target gases produces distinct corner frequencies of the power spectral density that can be used to achieve selective detection. In addition, a 3D vertical-NAND flash array is used with the fast Fourier transform method via in-memory-computing, significantly improving the area and power efficiency rate. The proposed system provides a novel and efficient method capable of selectively detecting a target gas using in-memory-computed LFN spectroscopy and thus paving the way for the further development in gas sensing systems. [ABSTRACT FROM AUTHOR]

Abstract With the recently increasing prevalence of deep learning, both academia and industry exhibit substantial interest in neuromorphic computing, which mimics the functional and structural features of the human brain. To realize neuromorphic computing, an energy‐efficient and reliable artificial synapse must be developed. In this study, the synaptic ferroelectric field‐effect‐transistor (FeFET) array is fabricated as a component of a neuromorphic convolutional neural network. Beyond the single transistor level, the long‐term potentiation and depression of synaptic weights are achieved at the array level, and a successful program‐inhibiting operation is demonstrated in the synaptic array, achieving a learning accuracy of 79.84% on the Canadian Institute for Advanced Research (CIFAR)‐10 dataset. Furthermore, an efficient self‐curing method is proposed to improve the endurance of the FeFET array by tenfold, utilizing the punch‐through current inherent to the device. Low‐frequency noise spectroscopy is employed to quantitatively evaluate the curing efficiency of the proposed self‐curing method. The results of this study provide a method to fabricate and operate reliable synaptic FeFET arrays, thereby paving the way for further development of ferroelectric‐based neuromorphic computing.

Abstract Concerns about indoor and outdoor air quality, industrial gas leaks, and medical diagnostics are driving the demand for high‐performance gas sensors. Owing to their structural variety and large surface area, reducible metal oxides hold great promise for constructing a gas‐sensing system. While many earlier reports have successfully obtained a sufficient response to various types of target gases, the selective detection of target gases remains challenging. In this work, a novel method, low‐frequency noise (LFN) spectroscopy is presented, to achieve selective detection using a single FET‐type gas sensor. The LFN of the sensor is accurately modeled by considering the charge fluctuation in both the sensing material and the FET channel. Exposure to different target gases produces distinct corner frequencies of the power spectral density that can be used to achieve selective detection. In addition, a 3D vertical‐NAND flash array is used with the fast Fourier transform method via in‐memory‐computing, significantly improving the area and power efficiency rate. The proposed system provides a novel and efficient method capable of selectively detecting a target gas using in‐memory‐computed LFN spectroscopy and thus paving the way for the further development in gas sensing systems.

A water-stable cesium lead bromide (CsPbBr3/Cs4PbBr6) perovskite nanocrystal (PNC) was synthesized and studied as a fluorescence probe for the selective detection of folic acid (FA). The as-prepared PNCs emitted strong green fluorescence at 525 nm, and their structure was systematically characterized by X-ray powder diffraction, X-ray photoelectron spectroscopy, and transmission electron microscopy. The interaction between the PNCs and small biological molecules was investigated and the results indicated that the fluorescence of the PNCs could be selectively quenched by FA. The quenching rate has a linear relationship with the concentration of FA in the concentration range from 10 to 800 μM, with a correlation coefficient R2 of 0.9841, and a limit of detection (LOD, 3σ) of 1.69 μM. The mechanism of the interaction between the PNCs and FA was discussed, and the reliability of the method for real sample detection was also verified by the standard addition method. The method proposed here, using a fluorescence PNCs probe, provided a simple alternative strategy for detecting FA that will play an important role in biochemical analysis. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

• The 2,4,5-triaryl imidazole derivative 3aa-3bg was synthesized by NCS as a catalyst. • Fe3+ ions could be quickly detected using probe 3bd with high selectivity and immunity to interference. • Fe3+ ions in HepG-2 live cells could be imaged by probe 3bd with low toxicity to cells. In this study, an efficient synthesis of 2,4,5-trisubstituted imidazoles was developed via cyclocondensation starting from o -dione, substituted aromatic aldehyde and ammonium acetate using catalyst NCS, and was characterized by HR-MS, FT-IR, 1H and 13C NMR spectroscopy. A novel fluorescence sensor 4-(1 H -phenanthro[9,10- d ]imidazol-2-yl)- N, N -diphenylaniline (3bd) was discovered for the detection of Fe3+ ions. The probe 3bd exhibited strong blue radiation in solution. In the presence of Fe3+ ions, a significant fluorescence change of blue light to green light was observed in the EtOH/H 2 O (4/1, v/v) solution of 3bd (Ag+, Al3+, Ba2+, Ca2+, Cd2+, Co2+, Cr3+, Cu2+, Fe2+, Fe3+, Hg2+, Mg2+, Mn2+, Pb2+, Sr2+, Zn2+). The limits of detection of probe 3bd for Fe3+ ions was calculated to be as low as 0.70 μ M, and it had excellent anti-interference ability. The probe 3bd complexed with Fe3+ ions at 1:1, and the complexation constant was 3.93 × 104 M−1. The probe 3bd realized the detection of Fe2+ oxidation to Fe3+, and the pH showed fine stability in the environment between 4.0–7.0, which ensured its potential application prospects. It also showed good reversibility upon addition of EDTA. Furthermore, the viability of 3bd to Fe3+ had practical application in live cell imaging. [Display omitted] [ABSTRACT FROM AUTHOR]

Silicon nano and micropillars have received considerable attention because they can be readily produced on wafer scale using conventional top-down techniques, and the compatibility with standard semiconductor fabrication makes them an attractive platform for a wide variety of applications. Here, we fabricate silicon pillars (SiPs) with p-n junction on 200 mm wafer using a top-down process and decorate them with carboxylated single-walled carbon nanotubes (SWCNT-COOH) for sensing gases and vapors. Compared to planar p-n junction devices with SWCNT-COOH, the SiP devices show higher sensor response due to enlarged surface area and more hydrophobic surface of the pillars as evidenced by the increased contact angle. Increase in relative humidity level decreases the sensor response of all devices as expected. A large 32 % response is seen for ammonia detection with negligible cross sensitivity to CO 2. • Wafer-scale silicon micro pillar arrays with SWCNT-COOH for gas sensing applications. • Pillar devices benefit from enlarged surface area and superhydrophobic surface. • Sensor response to ammonia is found to be bias dependent. • Sensor response of all devices degrades with increasing humidity. • The cross sensitivity to CO 2 is negligible. [ABSTRACT FROM AUTHOR]

[Display omitted] • In column derivatisation (ICD) improved HPLC post-column derivatisation (PCD). • Guide comparing ICD of different reaction loops vs. PCD 500 μL reaction loop assays. • ICD 500 μL ninhydrin assay decreased noise and background artefacts. • ICD 80 μL o -phthalaldehyde assay gained up to 167 % plates & 70 % peak area. • ICD 200 μL fluorescamine assay gained up to 324 % plates & 68 % S/N. In column derivatisation (ICD) has been applied to antioxidants in food and agricultural matrices. ICD's ability to reduce the post-column reaction loop volume is critical to investigate chromatographically before future applications are established. Due to the large number of post-column derivatisation (PCD) assays, this is out of the scope of this study to cover in one article. Hence, in this communication, we strictly focused on implementing ICD and its ability to reduce the post-column volume associated to the PCD's reaction loop. Specifically, reversed phase (RP) separations where we take three different reaction schemes: (i) amino acids derivatised with ninhydrin, (ii) amino acids derivatised with o -phthalaldehyde (OPA), and (iii) sulfonamides derivatised with fluorescamine to exemplify three different case scenarios. This communication can be used as a practical guide for analysts. In the order of the workflow's largest reduction in the reaction loop volume: (i) the amino acids derivatised with OPA, the ICD enabled the post-column volume to be reduced significantly from 500 µL down to 80 µL. This drastic reduction resulted in the chromatographic gain in performance – number of theoretical plates (N) (55–167 %) and peak height sensitivity (35–181 %). For the sulfonamides derivatised with fluorescamine, the ICD setup reduced the post-column volume from 500 µL down to 200 µL, and demonstrated significant improvements in efficiency – N (33–324 %), and peak height sensitivity (4–33 %). The amino acids derivatised with ninhydrin, the PCD reaction loop could not be decreased, and ICD demonstrated decreased signal to noise (S/N). [ABSTRACT FROM AUTHOR]

• Enhanced gas sensing performance: the study demonstrates that the SnO 2 -graphene sensor exhibits improved gas sensing properties compared to a pure SnO 2 sensor. This suggests that the incorporation of graphene into the SnO 2 sensor enhances its sensitivity and detection capabilities for SF 6 decomposition products. • Improved selectivity towards SF 6 decomposition products: The SnO 2 -graphene sensor shows enhanced selectivity towards SF 6 decomposition products. This means that it can effectively distinguish and detect specific gases or compounds associated with SF 6 decomposition, making it a promising sensor for monitoring SF 6 gas in various applications. • Lower operating temperature requirement: The research findings indicate that the SnO 2 -graphene sensor requires a lower operating temperature for gas sensing. This is significant as it reduces the energy consumption and potential safety risks associated with high-temperature operation, making the sensor more practical and efficient for real-world applications. Based on theoretical calculation and experimental detection, SnO 2 -modified graphene (SnO 2 -graphene) was proposed as a gas-sensing material for the SF 6 characteristic decomposition products (SO 2 , H 2 S, SOF 2 , SO 2 F 2) in SF 6 -insulated equipment. Based on density functional theory calculations, the most stable modifying structure of single and double SnO 2 on the surface of graphene is optimized. The adsorption structure, adsorption energy, and charge transfer of four gas molecules on the surface of SnO 2 -graphene are calculated and analyzed. Then the total density of states (DOS) and partial density of states (PDOS) of the system before and after gas adsorption were compared and analyzed to explore the interaction mechanism between different gases and SnO 2 -graphene. In experimental study, graphene was prepared by the modified Hummers oxidation–reduction method in the laboratory. four concentration gradients of SnO 2 modified on the surface of graphene, and then specific gas sensing experiments were carried out with 10, 25, 50, 100 ppm of the SF 6 characteristic decomposition products. The gap between simulation and experiment is compared and analyzed, which lays a theoretical and experimental foundation for the development of new specific sensors. [Display omitted] [ABSTRACT FROM AUTHOR]

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.

The present paper demonstrated the impedance analysis of Au/TiO2 nanoparticles/Siâ€"Al capacitive sensor for selective detection of volatile organic compounds (VOCs) at different frequency regimes. TiO2 nanoparticles (NP) were synthesized through the solution process and characterized by field-emission scanning electron microscopy, x-ray diffraction analysis, photoluminescence spectroscopy, and atomic force microscopy. The gas sensitivity of Au/TiO2 - NP/Siâ€"Al was investigated, with the effect of temperature modulation (25 °Câ€"250 °C) and dielectric variation in the vicinity of nanoparticles. Impedance spectroscopy of TiO2 - NP was carried out to obtain resonant peaks over the frequency ranging from 0.05 to 225 kHz and fitted with a complex nonlinear least-squares method. The optimum sensor response of 136%, 63%, 152%, and 174% was found at resonant frequencies of 0.38 kHz, 0.22 kHz, 0.15 kHz, and 0.1 kHz for the exposure of 2-propanol, acetone, ethanol, and methanol, respectively. The fastest response time and recovery time were found to be 32/21 s, 31.2/8 s, 32.5/9 s, and 40/26 s for acetone, 2-propanol, ethanol, and methanol, respectively. Selective detection of different VOCs at various resonant frequencies has correlated with the dielectric variation of the NPs and their associated void region under gas exposure. [ABSTRACT FROM AUTHOR]

Porous aromatic framework materials with high stability, sensitivity, and selectivity have great potential to provide new sensors for optoelectronic/fluorescent probe devices. In this work, a luminescent porous aromatic framework material (LNU-23) was synthesized via the palladium-catalyzed Suzuki cross-coupling reaction of tetrabromopyrene and 1,2-bisphenyldiborate pinacol ester. The resulting PAF solid exhibited strong fluorescence emission with a quantum yield of 18.31%, showing excellent light and heat stability. Because the lowest unoccupied molecular orbital (LUMO) of LNU-23 was higher than that of the nitro compounds, there was an energy transfer from the excited LNU-23 to the analyte, leading to the selective fluorescence quenching with a limit of detection (LOD) ≈ 1.47 × 10−5 M. After integrating the luminescent PAF powder on the paper by a simple dipping method, the indicator papers revealed a fast fluorescence response to gaseous nitrobenzene within 10 s, which shows great potential in outdoor fluorescence detection of nitro compounds. [ABSTRACT FROM AUTHOR]

Tau aggregates are present in multiple neurodegenerative diseases known as "tauopathies," including Alzheimer's disease, Pick's disease, progressive supranuclear palsy, and corticobasal degeneration. Such misfolded tau aggregates are therefore potential sources for selective detection and biomarker discovery. Six human tau isoforms present in brain tissues and both 3R and 4R isoforms have been observed in the neuronal inclusions. To develop selective markers for AD and related rare tauopathies, we first used an engineered tau protein fragment 4RCF as the substrate for ultrasensitive real-time quaking-induced conversion analyses (RT-QuIC). We showed that misfolded tau from diseased AD and other tauopathy brains were able to seed recombinant 4RCF substrate. We further expanded to use six individual recombinant tau isoforms as substrates to amplify misfolded tau seeds from AD brains. We demonstrated, for the first time to our knowledge, that misfolded tau from the postmortem AD brain tissues was able to specifically seed all six full-length human tau isoforms. Our results demonstrated that RT-QuIC analysis can discriminate AD and other tauopathies from non-AD normal controls. We further uncovered that 3R-tau isoforms displayed significantly faster aggregation kinetics than their 4R-tau counterparts under conditions of both no seeding and seeding with AD brain homogenates. In summary, our work offers potential new avenues of misfolded tau detection as potential biomarkers for diagnosis of AD and related tauopathies and provides new insights into isoform-specific human tau aggregation. [ABSTRACT FROM AUTHOR]

Inspired by the iron porphyrin structure of natural horseradish peroxidase (HRP), an efficient carbon-based nanozyme was fabricated using nitrogen-doped graphene quantum dots (NGQDs) and iron ion (Fe3+) nanocomposite, enabling selective distinguishment of hydroquinone (HQ) from its isomers. NGQDs with good dispersibility and uniform size were synthesized via a one-step hydrothermal process. NGQDs lacked peroxidase-like activity but the formed nanocomposite (Fe3+-NGQDs) upon Fe3+ addition possessed high peroxidase-like activity. Fe3+-NGQDs nanocomposite exhibited shuttle-shaped structure (∼30 nm), the lattice structure of NGQDs and electron transfer between Fe3+ and NGQDs. The Fe3+-NGQDs nanocomposite can catalyze the production of superoxide radicals (•O 2 −) from H 2 O 2. The Michaelis constant (K m) of Fe3+-NGQDs (0.115 mM) was lower than that of natural HRP (0.434 mM) with 3,3′,5,5′-tetramethylbenzidine (TMB) as the substrate and the maximum initial reaction rate (V max , 16.47 × 10−8 M/s) was nearly 4 times higher than that of HRP using H 2 O 2 substrate. HQ, unlike its isomers catechol (CC) and resorcinol (RE), could consume •O 2 − generated from the decomposition of H 2 O 2 catalyzed by Fe3+-NGQDs nanocomposite, reducing the oxidation of TMB. This principle enabled selective colorimetric determination of HQ ranged from 1 μM to 70 μM and a limit of detection (LOD) of 0.2 μM. Successful determination of HQ in pond water was also realized. [Display omitted] • Nitrogen-doped graphene quantum dots (NGQDs) were one-step synthesized with high yield. • NGQDs formed nanocomposite (Fe3+-NGQDs) upon Fe3+ addition. • Fe3+-NGQDs nanocomposite possessed high peroxidase-like activity. • Selective colorimetric detection of hydroquinone (HQ) from its isomers using Fe3+-NGQDs nanozyme. [ABSTRACT FROM AUTHOR]

The substrate N1, N3, N5-tris(2-hydroxyphenyl)benzene-1,3,5-tricarboxamide (Sensor A) was prepared in the reaction of 1,3,5-benzenetricarboxylic acid (trimesic acid) and o-aminophenol in ethanol. The prepared organic sensor fulfills the chemiluminescent requirements including a luminophore, spacer, and suitable binding receptor that distress the probe’s luminescent features, providing selective and sensitive detection of mercury and iron ions in aqueous solutions. The sensor selectively detects mercury and iron ions in a water matrix containing various metal ions, including sodium, calcium, magnesium, zinc, and nickel. Strong and immediate binding was observed between mercury ions and the substrate at pH 7.0 with a binding affinity toward Hg2+ 9-fold higher than that observed for iron sensor binding affinity, which makes the substrate a distinctive luminescence sensor for mercury detection at ambient conditions. The sensor shows a linear response toward Hg2+ in the concentration range from 50 ppb to 100 ppm (2.0 × 10−8 to 4.2 × 10−5 M) with a limit of detection of 2 ppb (1.0 × 10−8 M). Further, Sensor A provides linear detection for iron ions in the range from 10 ppb to 1000 ppm (1.5 × 10−8 to 1.5 × 10−3 M). The measured adsorption capacity of Sensor A toward mercury ions ranged from 1.25 to 1.97 mg/g, and the removal efficiency from water samples reached 98.8% at pH 7.0. The data demonstrate that Sensor A is an excellent probe for detecting and removing mercury ions from water bodies.

In this research, the effect of gamma ray doses on volatile organic compound (VOC) sensing properties of Cu doped TiO 2 nanoparticles are studied to further improve the VOC sensing performance. Pure and Cu doped TiO 2 nanoparticles have been prepared by sol-gel technique on Au interdigitated plexiglas substrate and irradiated by gamma-rays with doses varying from 1 to 150 KGy. The irradiation was performed by using 60Co as gamma source. The structural, morphology and modifications were analyzed with X-ray diffraction (XRD), scanning electron microscopy (SEM), and Atomic Force Microscopy (AFM) techniques. The sensing performance of these films toward ethanol, methanol, 2-propanol, benzene, toluene, xylene and ammonia vapors has been tested. It was observed that no remarkable sensor response to any vapors except ammonia was observed at room temperature. Changes in sensor' ammonia sensitivity have been correlated with the gamma radiation dose and Cu doping ratio. Maximum sensing performance was observed with 3% Cu doped TiO 2 exposed to gamma radiation dose of 150 kGy. • Highly selective sensing of ammonia can be achieved by using Cu doped TiO 2. • Ammonia sensing performance of Cu doped TiO 2 can be controlled by the doping ratio. • The influence of gamma ray dose on the ammonia sensing performance. • Ammonia sensing performance of Cu-doped TiO 2 can be significantly improved with gamma radiation dose. [ABSTRACT FROM AUTHOR]

• MOF-based selective sensor for detection of environmental contaminants. • A new MOF [Co(Cei)]nis synthesized with the ligand Bis(2-Carboxyethyl)isocyanurate at room temperaturewith face-centered cubic (fcu) topology. • [Co(Cei)]ncan effectively detect trichloroacetic acid (TCA) in model and real human urine samples showing detecting concentrations as low as 1.09 ppm in real human urine. • MOF-based photocatalyst for degradation of dyes without producing secondary pollution. • Future challenges, opportunities and perspectives discussed. The Co(II) ion was combined with the ligand Bis(2-Carboxyethyl)isocyanurate at room temperature to form a new MOF, [Co(Cei)] n. This polymer was then characterised using various techniques including FT-IR analysis, Powder X-ray diffraction, thermal analysis, and SEM-EDAX analysis. Single crystal X-ray analysis reveals that the compound [Co(Cei)] n forms a 12-c connected uninodal net with a point symbol of {324.436.56}. This net has an underlying net with face-centred cubic ( fcu ) topology, which can effectively detect TCA in human urine. Furthermore, it demonstrates exceptional specificity by detecting concentrations as low as 1.09 ppm in real human urine. Extensive study has been conducted on the recyclability and photocatalytic effectiveness of [Co(Cei)] n for the degradation of organic dyes. Out of the 13 dyes studied, the photocatalytic breakdown efficiency of [Co(Cei)] n is highest for the potentially dangerous organic dyes Neutral Red (NR), with highest percentages of degradation i.e. 93.44 %. [Display omitted] [ABSTRACT FROM AUTHOR]

In order to detect bisphenol A (BPA), one of representative endocrine disrupting chemicals (EDCs), in aqueous solution, a carbon quantum dot (CQD) was prepared using 1,3,6-trinitropyrene as a precursor by a hydrothermal synthesis method. STEM, Raman spectroscopy, FT-IR, and XPS were used for the characterization of the purified CQD (p-CD) in this work. The prepared material had a size of about 5 nm, contained many hydroxyl functional groups, and was found to have an amorphous graphene structure. In the concentration range used in this work (0 µM to 0.5 µM), p-CD showed a tendency to increase in fluorescence intensity with high linearity (R2=0.99749) as the BPA aqueous solution concentration increased. By measuring and comparing the fluorescence excitation wavelength of p-CD and the fluorescence emission wavelength of BPA, it was found that this fluorescence change occurred by the Forster resonance energy transfer (FRET) mechanism. Fluorescence experiments were also performed using benzoic acid, hydroquinone, and naphthalene, which have similar molecular structure to BPA as comparative materials. The p-CD exhibited high selectivity for BPA detection while exhibiting a 5-fold greater change in fluorescence intensity for BPA than other target substances. [ABSTRACT FROM AUTHOR]

The potential emergence of fluorescence‐based techniques has propelled research towards developing probes that can sense trace metal ions specifically. Although luminescent metal‐organic frameworks (MOFs) are well suited for this application, the role of building blocks towards detection is not fully understood. In this work, a systematic screening by varying number of Lewis basic (pyridyl‐N atoms) sites is carried out in a series of isostructural, robust UiO‐67 MOFs, and targeting a model metal ion‐Fe3+. All the three fluorescent MOFs are seen to present quenching response towards Fe3+ ions in water. However, UiO‐67@N exhibits highly selective and sensitive response, whereas emission of both UiO‐67 and UiO‐67@NN is quenched by several metal ions. Detailed experimental and theoretical mechanistic investigation is carried out in addition to demonstration of UiO‐67@N being able to sense trace amount of Fe3+ ions in synthetic biological water sample. Further, UiO‐67@N based mixed‐matrix membrane (MMM) has been prepared and employed to mimic the real time Fe3+ ions detection in water. [ABSTRACT FROM AUTHOR]

A novel fluorescent probe L based on benzimidazole derivative for selective CN− detection was designed and synthesized, and its structure was identified by spectral analysis. In DMSO/H2O (v/v=7 : 3, pH=9) solvent system, the fluorescence intensity for L enhances and the color change from yellow to colorless and purple was immediately observed at 426 nm, but there was no obvious color change when other anions instead of CN− was added to the system. The mechanism on CN− recognition was also studied by 1H NMR, IR, MS analysis and theoretical calculations. The probe L for CN− detection exhibited high sensitivity, and the molar ratio and lowest detection limit was 1 : 1 and 8.2×10−7 mol L−1, respectively. In addition, the probe L could be successfully applied to the detection of CN− in bitter almond, and was also used as a test paper, which indicated that the probe L might conveniently carried out the quick identification and detection of cyanide ion in the environment and food samples through its fluorescent color change under UV lamp. [ABSTRACT FROM AUTHOR]

The retina, the most crucial unit of the human visual perception system, combines sensing with wavelength selectivity and signal preprocessing. Incorporating energy conversion into these superior neurobiological features to generate core visual signals directly from incoming light under various conditions is essential for artificial optoelectronic synapses to emulate biological processing in the real retina. Herein, self‐powered optoelectronic synapses that can selectively detect and preprocess the ultraviolet (UV) light are presented, which benefit from high‐quality organic asymmetric heterojunctions with ultrathin molecular semiconducting crystalline films, intrinsic heterogeneous interfaces, and typical photovoltaic properties. These devices exhibit diverse synaptic behaviors, such as excitatory postsynaptic current, paired‐pulse facilitation, and high‐pass filtering characteristics, which successfully reproduce the unique connectivity among sensory neurons. These zero‐power optical‐sensing synaptic operations further facilitate a demonstration of image sharpening. Additionally, the charge transfer at the heterojunction interface can be modulated by tuning the gate voltage to achieve multispectral sensing ranging from the UV to near‐infrared region. Therefore, this work sheds new light on more advanced retinomorphic visual systems in the post‐Moore era. [ABSTRACT FROM AUTHOR]

Abstract The retina, the most crucial unit of the human visual perception system, combines sensing with wavelength selectivity and signal preprocessing. Incorporating energy conversion into these superior neurobiological features to generate core visual signals directly from incoming light under various conditions is essential for artificial optoelectronic synapses to emulate biological processing in the real retina. Herein, self‐powered optoelectronic synapses that can selectively detect and preprocess the ultraviolet (UV) light are presented, which benefit from high‐quality organic asymmetric heterojunctions with ultrathin molecular semiconducting crystalline films, intrinsic heterogeneous interfaces, and typical photovoltaic properties. These devices exhibit diverse synaptic behaviors, such as excitatory postsynaptic current, paired‐pulse facilitation, and high‐pass filtering characteristics, which successfully reproduce the unique connectivity among sensory neurons. These zero‐power optical‐sensing synaptic operations further facilitate a demonstration of image sharpening. Additionally, the charge transfer at the heterojunction interface can be modulated by tuning the gate voltage to achieve multispectral sensing ranging from the UV to near‐infrared region. Therefore, this work sheds new light on more advanced retinomorphic visual systems in the post‐Moore era.

Of all modern nanosensors using the principle of measuring variations in electric conductance, point-contact sensors stand out in having a number of original sensor properties not manifested by their analogues. The nontrivial nature of point-contact sensors is based on the unique properties of Yanson point contacts used as the sensing elements. The quantum properties of Yanson point contacts enable the solution of some of the problems that could not be solved using conventional sensors measuring conductance. In the present paper, we demonstrate this by showing the potential of quantum point-contact sensors to selectively detect components of a gas mixture in real time. To demonstrate the high efficiency of the proposed approach, we analyze the human breath, which is the most complex of the currently known natural gas mixtures with extremely low concentrations of its components. Point-contact sensors allow us to obtain a spectroscopic profile of the mixture. This profile contains information about the complete set of energy interactions occurring in the point contact/breath system when the breath constituents adsorb to and desorb from the surface of the point-contact conduction channel. With this information we can unambiguously characterize the analyzed system, since knowing the energy parameters is key to successfully identifying and modeling the physicochemical properties of various quantum objects. Using the point-contact spectroscopic profile of a complex gas mixture it is possible to get a functional dependence of the concentration of particular breath components on the amplitude of the sensor output signal. To demonstrate the feasibility of the proposed approach, we analyze the point-contact profiles from the breath of several patients and compare them with the concentrations of serotonin and cortisol in the body of each patient. The obtained results demonstrate that the proposed methodology allows one to get an effective calibration function for a non-invasive analysis of the level of serotonin and cortisol in the human body using the point-contact breath test. The present study indicates some necessary prerequisites for the design of fast detection methods using differential sensor analysis in real time, which can be implemented in various areas of science and technology, among which medicine is one of the most important.

A water-stable cesium lead bromide (CsPbBr3/Cs4PbBr6) perovskite nanocrystal (PNC) was synthesized and studied as a fluorescence probe for the selective detection of folic acid (FA). The as-prepared PNCs emitted strong green fluorescence at 525 nm, and their structure was systematically characterized by X-ray powder diffraction, X-ray photoelectron spectroscopy, and transmission electron microscopy. The interaction between the PNCs and small biological molecules was investigated and the results indicated that the fluorescence of the PNCs could be selectively quenched by FA. The quenching rate has a linear relationship with the concentration of FA in the concentration range from 10 to 800 μM, with a correlation coefficient R2 of 0.9841, and a limit of detection (LOD, 3σ) of 1.69 μM. The mechanism of the interaction between the PNCs and FA was discussed, and the reliability of the method for real sample detection was also verified by the standard addition method. The method proposed here, using a fluorescence PNCs probe, provided a simple alternative strategy for detecting FA that will play an important role in biochemical analysis.

Measurement levels of As3+ and Fe3+ ions have attracted considerable research attention for environmental and living being's health safety issues. Herein, we report a green synthetic approach to prepare bright yellow fluorescent carbon dots (C-dots) from a o-phenylenediamine and pyrazole mixture. A large Stokes shift of up to 145 nm was observed under an excitation wavelength of 415 nm. The metal ion sensing study affirmed that the C-dots' aqueous dispersion underwent a strong fluorescence quenching for selective As3+ and Fe3+ ion sensing with detection limits of 24.4 and 63.4 nM, respectively. In addition, a red shift of the C-dots' emission was noticed in the case of Fe3+ ion incubation. Furthermore, the C-dots were coated on a simple paper strip and embedded in a solid silica aerogel porous matrix in which detection was carried out through the visible and fluorescence color changes. The quenching of the C-dots' fluorescence was ascribed to the static quenching effect, which was proved by UV–vis absorbance and time-resolved fluorescence spectroscopy techniques. In addition, this method was successfully used to detect these ions in real water samples in the presence of other contaminants. Moreover, intracellular detection of the ions has been successfully performed in living cells at a lower concentration. The methodology reported here opens a new window in real and on-site applications. [ABSTRACT FROM AUTHOR]

In the current study, on the basis of 1,3,5-tris(2-methylimidazol-1-yl)benzene (timb), a designed tripodal connector, two new transition metal coordination polymers (CPs), {[Cu4(timb)2(Br–IPA)4]·5H2O}n (1) and {[Zn(timb)0.5(NH2–IPA)]·4H2O}n (2) have been generated with the mixed ligand method by the reaction between the timb and corresponding metal salts in the existence of dissimilar functional isophthalic acid (H2IPA) ligands. Furthermore, the Zn(II)-based complex 2 displays high sensitivity in the detection of Cu(II) ion in water. The neural stem cells proliferation after treated via compounds was detected with Cell Counting Kit-8 detection assay. And the real time reverse transcription polymerase chain reaction was carried out for the investigation of the differentiation function of the neural stem cells after the compound 1 treatment and compound 2 treatment. Further, molecular docking simulations confirmed that the biological activity that has been observed from experiments were from the carboxyl group on the Cu complex, in contrast, the imidazole groups were only used for binding with the Cu metal ion to retain the complex structure. [ABSTRACT FROM AUTHOR]

Reaction flow (RF) chromatography is a powerful and efficient approach that utilizes conventional high-performance liquid chromatography (HPLC)–ultraviolet (UV)–visible detection. This technique exploits a novel column end-fitting and an extra HPLC pump that delivers a reagent specific for selective detection, in particular the antioxidant profiling of natural products. This study employed RF for the first time to identify antioxidants in a commercial ginger sample. This demonstrated the previously validated assay’s ease and power to extract information about the natural product’s antioxidant properties. Due to the simplicity involved with data analysis and peak matching process, the following information was revealed between the chemical and antioxidant profiles: three of the strongest antioxidant activity peaks in the ginger sample (593 nm) did not correlate with the three most abundant chemical profile peaks (UV absorbance at 254 and 280 nm); the ratio of seven antioxidant peaks may be potentially used for food authenticity purposes, and future research should target these peaks for the early discovery of novel antioxidants sourced in ginger. Utilization of this previously validated assay provided the resolution of numerous peaks in the ginger extract and information associated with their antioxidant attributes and chemical abundance. This approach is more informative than total antioxidant assays that lack compound specificity information. Furthermore, it is superior to mass spectrometric (MS) assays that cannot evaluate each compound’s antioxidant strength, and does not involve the expense involved in the acquisition and maintenance of the MS detection hardware, and does not require the high level of expertise needed to conduct the MS data analysis. [ABSTRACT FROM AUTHOR]