Ability Of Complexes Research Articles

Twisted and Disconnected Chains: Flexible Linear Tetracuprous Arrays and a Decanuclear CuI Cluster as Blue- and Green/Yellow-Light Emitters.

Defined arrays of transition metal ions embedded in tailored polydentate ligand scaffolds allow for a systematic design of their physical properties. Such molecular strings of closed-shell transition metal centers are particularly interesting for Group 11 metal ions in the oxidation state +1 if they undergo metallophilic d10···d10 contact interactions since these clusters are oftentimes efficient photoluminescence (PL) emitters. Copper is particularly attractive as a sustainable earth-abundant coinage metal source and because of the ability of several CuI complexes to serve as powerful thermally activated delayed fluorescence (TADF) emitters in molecular/organic light-emitting devices (OLEDs). Our combined synthetic, crystallographic, photophysical, and computational study describes a straight tetracuprous array possessing a centrally disconnected CuI2···CuI2 chain and a continuous helically bent CuI4 complex. This molecular helix undergoes a facile rearrangement in diethyl ether solution, yielding an unprecedented nanosized CuI10 cluster (2.9 × 2.0 nm) upon crystallization. All three clusters show either bright blue phosphorescence, TADF, or green/yellow multiband phosphorescence with quantum yields between 6.5 and 67%, which is persistent under hydrostatic pressure up to 30 kbar. Temperature-dependent PL investigations in combination with time-dependent density-functional theory (TD-DFT) calculations and void space analyses of the crystal packings complement a comprehensive correlation between the molecular structures and photoluminescence properties.

Predicting the PCM-incorporated building's performance using optimized linear kernel and tree-based machine learning methods

The devising of a precise machine learning-based energy consumption prediction model holds significant importance for taking effective decisions during the early stages of phase change material (PCM) incorporated building design to reduce energy consumption. Few researchers have developed prediction models for estimating the consumption of energy in PCM incorporated buildings. However, there is a need to develop the best-performing machine learning-based prediction model, which is less complex, involve a lower number of hyperparameters, and has a greater ability to generalize hidden patterns among the dependent and independent variables. To address the above shortcomings, the linear kernel and tree model-based prediction models were formulated for PCM-incorporated buildings located in eight cities of subtropical highland climate, considering the variations in their hyperparameters. The evaluation and validation of the formulated models for prediction were performed utilizing several statistical metrics. Test results substantiated that the ensemble-boosted tree-based prediction model (EBT20) exhibited superior efficacy in estimating the energy consumption for PCM-integrated building, having an average R2 > 0.93, NMBE <4 %, and CV-RMSE <8 %. The developed model showed less complexity and better generalization ability at the optimized values of ensemble boosted tree hyperparameters, which are as follows: minimum leaf size = 32, number of learners = 99, and learning rate = 0.1. From comprehensive evaluation conducted to evaluate the interpretability of the prediction model, it was found that the building orientation and PCMs melting temperature are the most influential parameters for achieving energy savings of up to 33 % in the selected climate zone.

Efficiency of Alginic Acid, Sodium Carboxymethylcellulose, and Potassium Polyaspartate as Calcium Tartrate Stabilizers in Wines.

The instability of calcium tartrate (CaT) in wines occurs when the effective concentration of ions surpasses the solubility product, leading to the formation of CaT crystals. Unlike potassium hydrogen tartrate (KHT), temperature has little effect on the rate of CaT precipitation, making cold stabilization ineffective. Additives like metatartaric acid and carboxymethylcellulose (CMC) have been used to mitigate this problem, but metatartaric acid's effectiveness is limited due to hydrolysis. Additionally, potassium polyaspartate (KPA), commonly used as a KHT stabilizer, has been reported to reduce wine stability regarding CaT instability. Therefore, exploring alternative stabilization methods is crucial. Alginic acid, permitted as a processing aid in winemaking, can be an alternative to CMC and metatartaric acid due to its strong negative charge and ability to bind calcium ions. This study aimed to assess alginic acid's efficacy as a CaT stabilizer compared to CMC and investigate the impact of KPA on CaT instability. The results showed that KPA did not increase CaT instability and even improved its stability in some wines. Alginic acid outperformed both CMC and KPA in mitigating CaT instability, possibly due to its higher zeta potential and calcium ion complexation ability. This study is the first to investigate the use of alginic acid for CaT stability in wine.

The Noteworthiness of Constructive Feedback and Student-Reflection to Approach Competence-Based Curriculum: An Explanatory Study of Medical Schools in Indonesia

Background: Competence-based medical curriculum requires the acquisition of complex abilities that should be assessed longitudinally. The programmatic assessment model can facilitate a complete picture of students' competencies. The five components of learning, assessment, supporting activities; and intermediate to final evaluation provide holistic learning experiences for students and mentors to participate in the learning strategies. We aim to assess the application of longitudinal components of the programmatic assessment model to the current assessment system based on student perceptions.Methods: This study used a cross-sectional mixed-method sequential explanatory design at six medical schools in Surabaya, East Java of Indonesia. The instrument was 43 items of validated questionnaire based on the five components and the focus group discussions. Results: This study obtained 442 respondents. The results reflected high reliability with a Cronbach alpha value of 0.969, and the validity test showed R arithmetic &gt; R table (R table 0.128 for n 442). The current assessment system was perceived as ‘good’, with 3.9 on 5 points Likert scale; but the ‘supporting activities’ where reflection and feedback lied; was at the lowest score although insignificant. Students underlined the lack of formative aspects (reflection, feedback, mentorship, and middle evaluation).Conclusion: The overall assessment system is well-perceived by the students; however, the 'supportive activities' component has been minimally applied. So the 'assessment of previous learning' is still prominent in the current assessment system.

Theoretical study of the ability of symmetric and asymmetric N-donor ligands to separate Am(III) and Eu(III) and the bonding nature

In the reprocessing of spent nuclear fuel, nitrogen-donor extractants are more effective in separating actinides and lanthanides. In this article, a series of heterocyclic N-donor ligands with different backbones and different side chain substituents are systematically investigated to analyze their extraction selectivity and complexation abilities for Am(Ⅲ) and Eu(Ⅲ) by using scalar relativistic density functional theory (DFT). Through the analysis of geometric structures and bond properties of the complexes by means of the NBO and QTAIM methods, it was observed that the coordination ability of the N-donor ligand with Am(Ⅲ) was stronger than with Eu(Ⅲ). Thermodynamic analysis showed that these ligands have good extraction ability and separation performance for Am(III) and Eu(III), the backbone and side chain substituents of the ligands and also the organic solvents have significant influences on the extraction selectivity of the ligands for Am(III) and Eu(III) ions. This work provides some theoretical insights for the design of N-donor extractants with good separation performance for lanthanides and actinides.

Physicochemical properties of pectin-Fe(III) gained by HG-type hawthorn with different esterification degree

In this study, the complexation ability of HG-type hawthorn pectin with trivalent iron ions after de-esterification was investigated. The moderate esterification reaction could significantly increase the iron content in HG-type hawthorn pectin. Fourier transform infrared spectroscopy (FT-IR) and X-ray photoelectron spectroscopy (XPS) experiments proved that -OH and -COOH in the pectin acted as a bridge connecting Fe3+ leading to the formation of β-FeOOH structure, and the trivalent iron ions were successfully complexed into the HG-type hawthorn pectin. In addition, infrared and ultraviolet spectroscopic scans, particle size, and potentiometric measurements were carried out to demonstrate the complexation coordination mechanism of hawthorn pectin with Fe3+, and there were differences in the complexation effect of HG-type hawthorn pectin with different degrees of esterification. The gelling properties of HG-type hawthorn pectin were subsequently verified by in vitro gastrointestinal tract simulation experiments to aid the smooth passage of ferric ions through the gastric juices and reduce irritation. The success of the experiments demonstrated that HG-type hawthorn pectin is an excellent raw material for metal complexation, and the degree of esterification is one of the important factors affecting its complexation effect, which proves its potential application value as an iron supplement.

Phosphorylation of DNA-binding domains of CLOCK–BMAL1 complex for PER-dependent inhibition in circadian clock of mammalian cells

In mammals, CLOCK and BMAL1 proteins form a heterodimer that binds to E-box sequences and activates transcription of target genes, including Period (Per). Translated PER proteins then bind to the CLOCK-BMAL1 complex to inhibit its transcriptional activity. However, the molecular mechanism and the impact of this PER-dependent inhibition on the circadian clock oscillation remain elusive. We previously identified Ser38 and Ser42 in a DNA-binding domain of CLOCK as phosphorylation sites at the PER-dependent inhibition phase. In this study, knockout rescue experiments showed that nonphosphorylatable (Ala) mutations at these sites shortened circadian period, whereas their constitutive-phospho-mimetic (Asp) mutations completely abolished the circadian rhythms. Similarly, we found that nonphosphorylatable (Ala) and constitutive-phospho-mimetic (Glu) mutations at Ser78 in a DNA-binding domain of BMAL1 also shortened the circadian period and abolished the rhythms, respectively. The mathematical modeling predicted that these constitutive-phospho-mimetic mutations weaken the DNA binding of the CLOCK-BMAL1 complex and that the nonphosphorylatable mutations inhibit the PER-dependent displacement (reduction of DNA-binding ability) of the CLOCK-BMAL1 complex from DNA. Biochemical experiments supported the importance of these phosphorylation sites for displacement of the complex in the PER2-dependent inhibition. Our results provide direct evidence that phosphorylation of CLOCK-Ser38/Ser42 and BMAL1-Ser78 plays a crucial role in the PER-dependent inhibition and the determination of the circadian period.

Changes in processing speed during early abstinence from alcohol dependence.

Processing speed is a task-independent construct underpinning more complex goal-related abilities. Processing speed is impaired in alcohol dependence (AD) and is linked to relapse, as are the functions it underpins. Reliable measurement of processing speed may allow tracking of AD recovery trajectories and identify patients requiring additional support. To assess changes in reaction time (RT) from baseline (at the start of a detoxification programme) across early abstinence. Vibrotactile RT was assessed in early recovery between days 3 and 7 of treatment in 66 individuals with AD (25 females; aged 19-74, 44.60 ± 10.60 years) and against 35 controls tested on one occasion (19 females; 41.00 ± 13.60), using two multivariate multiple regressions. A mixed multivariate analysis of covariance (MANCOVA) of available AD data (n = 45) assessed change in RT between timepoints and between treatment settings (outpatient vs inpatient). The group (AD vs control) significantly predicted choice RT at baseline and follow-up but did not significantly predict simple RT or RT variability, which is inconsistent with previous findings. At follow-up, mental fatigue was also predicted by the group, and MANCOVA indicated that this had worsened in inpatients but improved in outpatients. Recovery of RT measures so early in the treatment journey was not in line with previous research which indicates persisting deficits. The interaction between setting and timepoint indicates that despite being typically less medically complex, outpatients require ongoing support and monitoring during their recovery.

Photocatalytic water oxidation by iron and copper phthalocyanine complexes immobilized on Fe3O4@SiO2@TiO2 under visible light irradiation

In this research, the heterogeneous catalysts of Fe3O4@SiO@TiO‐FePc and Fe3O4@SiO@TiO‐ CuPcN (FePc = iron (II) phthalocyanine and CuPcN = copper (II) tetraazaphthalocyanine), termed respectively as nanocomposites 1 and 2, were prepared by immobilizing the FePc and CuPcN complexes on the Fe3O4@SiO@TiO surface and used for the photocatalytic water oxidation reaction. Since phthalocyanine complexes have received very little attention as photocatalysts for water oxidation, the advantage of the synthesized photocatalyst owes to the ability of the phthalocyanine complex grafted on the titanium substrate to oxidize water in the photocatalytic reaction. The prepared nanocomposites were then studied by diffraction (XRD), scanning electron microscopy (SEM), energy‐dispersive X‐ray (EDX), Fourier transform infrared (FT‐IR) spectroscopies, thermal gravimetric analysis (TGA), transmission electron microscopy (TEM), inductively coupled plasma‐optical emission spectroscopy (ICP‐OES), Brunauer–Emmett–Teller (BET) analysis, ultraviolet diffuse reflectance (DRS), and photoluminescence (PL) spectroscopies. The photocatalytic response of water oxidation by nanocomposites 1 and 2 was investigated in the presence of silver nitrate as an electron recipient at ambient temperature. The progress of the water oxidation reaction was monitored with an oxygen meter. The amount of oxygen generated in the presence of nanocomposites 1 and 2 under visible light irradiation was found to be 2.6 and 2.1 mg L−1, respectively. Owing to the existence of magnetic material, these nanocomposites can be effortlessly removed from the response medium with an external magnet. The involved nanocomposites can be used up to three times in catalytic water oxidation reactions with no significant change in their photocatalytic activity.

Evolution of soil DOM during thermal remediation below 100 °C: concentration, spectral characteristics and complexation ability

Evolution of soil DOM during thermal remediation below 100 °C: concentration, spectral characteristics and complexation ability

A learning numerical spiking neural P system for classification problems

In recent years, classification problems have been widely studied as one of the critical research directions in artificial intelligence. Efficiently simulating the human brain’s ability to solve deterministic classification problems has become a prominent research branch in the field of classification problems. Numerical spiking neural P systems (NSN P systems) with the characteristics of the highly flexible spiking neural P (SNP)systems architecture and addressing numerical variants have special advantages for solving classification problems in the real world. This paper proposes, a novel NSN P system, namely, a learning numerical spiking neural P system (LNSN P system), is proposed to solve classification problems. In LNSN P systems, each neuron contains not only discrete spikes and rules that must be described by regular expressions but also numerical variables and production functions that can be in any form, overcoming the discontinuity of traditional SN P systems. In addition, an ascending structure without an outer encoder has been designed in this study to encode information from low-dimensional indivisible space to high-dimensional divisible space. At the same time, an adaptive learning mechanism has been introduced to improve algorithm convergence and precision. Finally, the experimental results obtained using eight benchmark datasets from the machine learning repository demonstrate the feasibility and effectiveness of the proposed LNSN P system. Moreover, the proposed LNSN P system exhibits lower space complexity and better generalisation ability than the existing SN P systems with the learning ability to solve different classification problems.

Effect of negative emotion on prospective memory and its different components

Prospective memory is an important and complex social cognitive ability, which is easily disturbed by negative emotions. According to the relationship between prospective memory cues and ongoing tasks, prospective memory can be divided into focal prospective memory and non-focal prospective memory. This study focuses on the influence of negative emotions on different types of prospective memory. In Experiment 1, 117 participants were recruited, using a 2 (emotion: negative, neutral) × 2 (cue focality: focal, non-focal) between-subjects design to initially explore whether negative emotions can interfere with the prospective memory of both focal cue and non-focal cue. The results show that negative emotions simultaneously reduce both types of prospective memory performance. At the same time, negative emotions occupy additional attention resources and impair the prospective component of prospective memory with non-focal cues. In Experiment 2, 64 participants were recruited to improve the difficulty of the retrospective component of prospective memory with non-focal cues, and the influence of negative emotions on different components of prospective memory with non-focal cues was further explored. The results show that negative emotions can impair both the prospective and retrospective components of prospective memory. In short, the results of this study indicate that negative emotion can impair prospective memory, and the impairment effect is not limited by the cue type of prospective memory. Meanwhile, negative emotion will occupy more attentional resources and simultaneously affect the prospective and retrospective components of prospective memory.

An efficient visual servo tracker for herd monitoring by UAV

It is a challenging and meaningful task to carry out UAV-based livestock monitoring in high-altitude (more than 4500 m on average) and cold regions (annual average – 4 °C) on the Qinghai Tibet Plateau. The purpose of artificial intelligence (AI) is to execute automated tasks and to solve practical problems in actual applications by combining the software technology with the hardware carrier to create integrated advanced devices. Only in this way, the maximum value of AI could be realized. In this paper, a real-time tracking system with dynamic target tracking ability is proposed. It is developed based on the tracking-by-detection architecture using YOLOv7 and Deep SORT algorithms for target detection and tracking, respectively. In response to the problems encountered in the tracking process of complex and dense scenes, our work (1) Uses optical flow to compensate the Kalman filter, to solve the problem of mismatch between the target bounding box predicted by the Kalman filter (KF) and the input when the target detection in the current frame is complex, thereby improving the prediction accuracy; (2) Using a low confidence trajectory filtering method to reduce false positive trajectories generated by Deep SORT, thereby mitigating the impact of unreliable detection on target tracking. (3) A visual servo controller has been designed for the Unmanned Aerial Vehicle (UAV) to reduce the impact of rapid movement on tracking and ensure that the target is always within the field of view of the UAV camera, thereby achieving automatic tracking tasks. Finally, the system was tested using Tibetan yaks on the Qinghai Tibet Plateau as tracking targets, and the results showed that the system has real-time multi tracking ability and ideal visual servo effect in complex and dense scenes.

MLMSign: Multi-lingual multi-modal illumination-invariant sign language recognition

Sign language (SL) serves as a visual communication tool bearing great significance for deaf people to interact with others and facilitate their daily life. Wide varieties of SLs and the lack of interpretation knowledge necessitate developing automated sign language recognition (SLR) systems to attenuate the communication gap between the deaf and hearing communities. Despite numerous advanced static SLR systems, they are not practical and favorable enough for real-life scenarios once assessed simultaneously from different critical aspects: accuracy in dealing with high intra- and slight inter-class variations, robustness, computational complexity, and generalization ability. To this end, we propose a novel multi-lingual multi-modal SLR system, namely MLMSign, by taking full strengths of hand-crafted features and deep learning models to enhance the performance and the robustness of the system against illumination changes while minimizing computational cost. The RGB sign images and 2D visualizations of their hand-crafted features, i.e., Histogram of Oriented Gradients (HOG) features and a∗ channel of L∗a∗b∗ color space, are employed as three input modalities to train a novel Convolutional Neural Network (CNN). The number of layers, filters, kernel size, learning rate, and optimization technique are carefully selected through an extensive parametric study to minimize the computational cost without compromising accuracy. The system’s performance and robustness are significantly enhanced by jointly deploying the models of these three modalities through ensemble learning. The impact of each modality is optimized based on their impact coefficient determined by grid search. In addition to the comprehensive quantitative assessment, the capabilities of our proposed model and the effectiveness of ensembling over three modalities are evaluated qualitatively using the Grad-CAM visualization model. Experimental results on the test data with additional illumination changes verify the high robustness of our system in dealing with overexposed and underexposed lighting conditions. Achieving a high accuracy (>99.33%) on six benchmark datasets (i.e., Massey, Static ASL, NUS II, TSL Fingerspelling, BdSL36v1, and PSL) demonstrates that our system notably outperforms the recent state-of-the-art approaches with a minimum number of parameters and high generalization ability over complex datasets. Its promising performance for four different sign languages makes it a feasible system for multi-lingual applications.

Study on the Mechanism of Competing Endogenous Network of 'Scutellaria barbata D.Don-Houttuynia cordata- Radix Scutellariae' in the Treatment of NSCLC based on Bioinformatics, Molecular Dynamics and Experimental Verification.

Non-small cell lung cancer (NSCLC) is the most common type of lung cancer. Traditional Chinese medicine, known for its multi-target and multi-pathway characteristics, offers a potential treatment approach for NSCLC. This study aimed to explore the mechanism of the competitive endogenous network of 'Scutellaria barbata D.Don-Houttuynia cordata-Radix Scutellariae' in treating NSCLC through bioinformatics analysis and in vitro experiments. Various databases and ceRNA networks were utilized to collect and screen components and target genes, molecular docking and molecular dynamics simulations to determine the binding ability of ligand-receptor complexes. In vitro experiments were conducted to validate the effects of active ingredients of 'Scutellaria barbata D.Don-Houttuynia cordata- Radix Scutellariae' on non-small cell lung cancer cell line A549. The key target proteins CCL2, EDN1, MMP9, PPARG, and SPP1 were docked well with their corresponding TCM ligands. Among the ligand-receptor complexes, MMP9-Luteolin and MMP9-Quercetin demonstrated the weaking binding force, while the SPP1-Quercetin complex, associated with NSCLC prognosis, exhibited stable structure formation through hydrogen bond interaction during MD simulation. In vitro experiments confirmed the inhibitory effect of Quercetin on SPP1 expression, as well as the proliferation and migration of A549 cells. The findings suggest that 'Scutellaria barbata D.Don-Houttuynia cordata-Radix Scutellariae' may potentially treat lung cancer by suppressing the expression of SPP1. This study provides valuable insights and novel research directions for understanding the mechanism of traditional Chinese medicine in combating lung cancer.

The actin binding sites of talin have both distinct and complementary roles in cell-ECM adhesion.

Cell adhesion requires linkage of transmembrane receptors to the cytoskeleton through intermediary linker proteins. Integrin-based adhesion to the extracellular matrix (ECM) involves large adhesion complexes that contain multiple cytoskeletal adapters that connect to the actin cytoskeleton. Many of these adapters, including the essential cytoskeletal linker Talin, have been shown to contain multiple actin-binding sites (ABSs) within a single protein. To investigate the possible role of having such a variety of ways of linking integrins to the cytoskeleton, we generated mutations in multiple actin binding sites in Drosophila talin. Using this approach, we have been able to show that different actin-binding sites in talin have both unique and complementary roles in integrin-mediated adhesion. Specifically, mutations in either the C-terminal ABS3 or the centrally located ABS2 result in lethality showing that they have unique and non-redundant function in some contexts. On the other hand, flies simultaneously expressing both the ABS2 and ABS3 mutants exhibit a milder phenotype than either mutant by itself, suggesting overlap in function in other contexts. Detailed phenotypic analysis of ABS mutants elucidated the unique roles of the talin ABSs during embryonic development as well as provided support for the hypothesis that talin acts as a dimer in in vivo contexts. Overall, our work highlights how the ability of adhesion complexes to link to the cytoskeleton in multiple ways provides redundancy, and consequently robustness, but also allows a capacity for functional specialization.

Improving Critical Thinking by Using Technology in the Learning Process

Improving Critical Thinking by Using Technology in the Learning Process

Solving the puzzle of 2-hydroxypropyl β-cyclodextrin: Detailed assignment of the substituent distribution by NMR spectroscopy

2-Hydroxypropyl-β-cyclodextrin (HPBCD) is one of the most important cyclodextrin derivatives, finding extensive applications in the pharmaceutical sector. Beyond its role as an excipient, HPBCD achieved orphan drug status in 2015 for Niemann-Pick type C disease treatment, prompting research into its therapeutic potential for various disorders. However, the acceptance of HPBCD as an active pharmaceutical ingredient may be impeded by its complex nature. Indeed, HPBCD is not a single entity with a well-defined structure, instead, it is a complex mixture of isomers varying in substituent positions and the degree of hydroxypropylation, posing several challenges for unambiguous characterization. Pharmacopoeias' methods only address the average hydroxypropylation extent, lacking a rapid approach to characterize the substituent positions on the CD scaffold. Recognizing that the distribution of substituents significantly influences the complexation ability and overall activity of the derivative, primarily by altering cavity dimensions, we present a straightforward and non-destructive method based on liquid state NMR spectroscopy to analyze the positions of the hydroxypropyl sidechains. This method relies on a single set of routine experiments to establish quantitative assignment and it provides a simple yet effective tool to disclose the substitution pattern of this complex material, utilizing easily accessible (400 MHz NMR) instrumentation.

Symmetrical Ligand's Fabricated Porous Silicon Surface Based Photoluminescence Sensor for Metal Detection and Entrapment.

This study was based on the development of surface-based photoluminescence sensor for metal detection, quantification, and sample purification employing the solid sensory chip having the capability of metal entrapment. The Co(II), Cu(II) and Hg(II) sensitive fluorescence sensor (TP) was first synthesized and characterized its sensing abilities towards tested metal ions by using fluorescence spectral investigation while the synthesis and complexation of the receptor was confirmed by the chromogenic, optical, spectroscopic and spectrometric analysis. Under optical investigation, the ligand solution exhibited substantial chromogenic changes as well as spectral variations upon reacting with copper, cobalt, and mercuric ions, while these behaviors were not seen for the rest of tested metallic ions i.e., Na+, Ag+, Ni2+, Mn2+, Pd2+, Pb2+, Cd2+, Zn2+, Sn2+, Fe2+, Fe3+, Cr3+, and Al3+. These colorimetric alterations and spectral shifting could potentially be employed to detect and quantify these specific metal ions. After the establishment of the ligand's selective complexation ability towards selected metals, it was fabricated over the substituted porous silicon surface (FPS) keeping in view of the development of surface-based photoluminescence sensor (TP-FPS) for the selected metal sensation and entrapment to purify the sample just be putting off the metal entrapped sensory solid chip. Surface characterization and ligand fabrication was inspected by plan and cross sectional electron microscopic investigations, vibrational and electronic spectral analysis. The sensitivity of the ligand (TP) in the solution phase metal discrimination was determined by employing the fluorescence titration analysis of the ligand solution after progressive induction of Co2+, Cu2+, and Hg2+, which afford the detection limit values of 2.14 × 10- 8, 3.47 × 10- 8 and 3.13 × 10- 3, respectively. Concurrently, photoluminescence titration of the surface fabricated sensor (TP-FPS) revealed detection limit values of 3.14 × 10- 9, 7.43 × 10- 9, and 8.21 × 10- 4, respectively, for the selected metal ions.

Detection of copper in tea and water sample: A click-oriented azomethine-based 1,2,3-triazole fluorescent chemosensor with reversible INHIBIT logic gate behavior and computational aspects

A fluorescent azomethine-scaffolded-1,2,3-triazole linked chemosensor was synthesized utilizing alkyne and azidomethylbenzene via Cu(I)-catalyzed click chemistry. The compounds (3–5 and L6) were analyzed using FTIR, 1H NMR, 13C NMR, and GCMS–. The exploration of ion sensing ability of L6 complex, using UV–Vis and fluorescence spectroscopy in ACN:H2O (4:1) medium resulted in detection of Cu(II) ions, exclusively. Further L6-Cu(II) complex was characterized via FTIR, FE-SEM, LCMS and supported by DFT studies. A significant structural modification has rendered the current probe as highly selective for Cu2+ ions, with ‘Turn-On’ response. The chemical receptor (L6) establishes 1:1 molar ratio with Cu(II) ions with binding constant of 6.0 × 104 M−1 and excellent detection limit of 20 nM. In addition, the sensitive reversible behavior of probe (L6) with two chemical inputs (Cu2+ and EDTA) contributes to the construction of an INHIBIT logic circuit. The Copper ion detection was effectively monitored for real-world samples like Black Tea with precise quantification of Copper(II) ions.