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Carbon dots (CDs), as a fascinating carbon nanomaterial, have important applications in various fields due to their unique properties. The physical and chemical properties of CDs can be fine-tuned using heteroatom doping and surface functionalisation. Here, we synthesised N-doped carbon dots (N-CDs) by reacting Citric acid, which serve as the carbon core, with twenty amino acids under microwave irradiation. The fluorescence quenching of each amino acid doped CDs by Hg(II) ions was experimentally measured. Then the effect of the molecular features and chemical properties of amino acids on the fluorescence quenching of N-CDs by Hg(II) ions was investigated by using the quantitative structure–property relationship (QSPR) method. Applying different machine learning techniques including correlation-based and ReliefF algorithm feature selection approaches to choose relevant descriptors, multi-linear regression, and support vector machine to construct QSPR model, some reliable and predictive models were developed. Based on the variables used throughout the final QSPR models, hydrophobic interactions, in addition to hydrogen bonding interactions, can be considered a major factor governing the photoluminescence behaviour of different N-CDs quenched by Hg(II) ions. N-CDs derived from amino acids bearing larger hydrophobic surfaces show greater fluorescence quenching, indicating that a greater capacity to interact with Hg(II) metal ions resulting in further fluorescence quenching.

Background: A Vortex-assisted dispersive liquid-liquid microextraction (VA-DLLME) method is presented for the determination of aspirin (acetylsalicylic acid) in human urine by spectrofluorimetry. Objective: To determine trace levels of aspirin in biologic samples by using green and low-cost method development. Methods: For the microextraction procedure, chloroform and acetonitrile were used as extraction and disperser solvent, respectively. The factors affecting the efficiency of extraction such as volume of chloroform, volumes of acetonitrile, ionic strength, sample pH, centrifuging time, and extraction time were investigated. Then significant variables were optimized by the response surface method using the Box- Behnken design. Results: Under the optimum extraction conditions, a linear calibration curve in the range of 0.1 to 130 ng mL-1 with a correlation coefficient of R2 = 0.998 was obtained. The limits of detection (LOD) and limits of quantification (LOQ) were 0.031 and 0.103 ng mL-1, respectively. The relative standard deviations (RSD) were less than 4%. Conclusion: Enrichment factor and recoveries were achieved for the extraction of aspirin in human urine. This method gives a rapid, simple, sensitive and environmentally friendly for the measurement of trace amount aspirin.

Stability constants prediction plays a critical role in the identification and optimization of ligand design for selective complexation of metal ions in solution. Thus, it is important to assess the potential of metal-binding ligand organic in the complex formation process. However, quantitative structure-activity/property relationships (QSAR/QSPR) provide a time-and cost-efficient approach to predict the stability constants of compounds. To this end, we applied a free alignment three-dimensional QSPR technique by generating GRid-INdependent Descriptors (GRINDs) to rationalize the underlying factors effecting on stability constants of transition metals; 105 (Y3+), 186 (La3+), and 66 (UO2 2+) with diverse organic ligands in aqueous solutions at 298 K and an ionic strength of 0.1 M. Kennard– Stone algorithm was employed to split data set to a training set of 75% molecules and a test set of 25% molecules. Fractional factorial design (FFD) and genetic algorithm (GA) applied to derive the most relevant and optimal 3 D molecular descriptors. The selected descriptors using various feature selection were correlated with stability constants by partial least squares (PLS). GA-PLS models were statistically validated (R2 = 0.96, q2 = 0.82 and R2 pred=0.81 for Y3+; R2 = 0.90, q2 = 0.73 and R2 pred=0.82 for La3+ and R2 = 0.95, q2 = 0.81 and R2 pred=0.88 for UO2 2+), and from the information derived from the graphical results confirmed that hydrogen bonding properties, shape, size, and steric effects are the main parameters influencing stability constant of metal complexation. The provided information in this research can predict the stability constant of the new organic ligand with the transition metals without experimental processes.