In this work, the radial basis function neural network (RBFNN) and random forest (RF) algorithms were employed to develop generic AI models predicting mass transfer coefficient in amine‐based CO2 absorber. The models with operating parameters as input gave quite different prediction performance in different CO2 absorption systems. To secure better applicability, extra parameters related to amine type and packing characteristics were introduced to reasonably describe mass transfer behaviors, respectively. Moreover, the generic models were proposed by considering all influencing factors of mass transfer in CO2 absorber column. Furthermore, the performance of BPNN, RBFNN, and RF models was completely compared and fully discussed in terms of AARE. All three generic models could predict mass transfer coefficient of CO2 absorber very well. It was found that the BPNN models provide the best predication with AAREs of below 5%. The developed generic model could serve as a fast and efficient tool for preliminary selection and evaluation of potential amines for CO2 absorption. The framework of generic ML model development was also clearly presented, which could provide theoretical basis and practical guidance for the implementation and application of ML models in the carbon capture field.

The ratiometric fluorescence chemodosimeter N-butyl-4-(prop-1-en-1-yloxy)-1,8-naphthalic anhydride (NT-VE) was designed for Hg 2+ recognition by oxymercuration at ambient temperature with high selectivity and no interference from other metal cations such as Cu 2+ , Ag + , Au 3+ , Fe 3+ , etc. The NT-VE could be incorporated into sodium dodecyl-benzenesulfonate (SDBS) micelles, which was confirmed by the clear emission enhancement observed in 0.1 mM SDBS. The hydrophobic core of the SDBS enhanced the solubility of NT-VE, enabling the detection of Hg 2+ in aqueous solution, and the negatively charged micelle surface increased the local concentration of Hg 2+ for amplified sensitivity. This work demonstrated the excellent performance of the NT-VE chemodosimeter for ratiometric detection of Hg 2+ in aqueous solution. The NT-VE/SDBS system could detect Hg 2+ over a linear range of 0.05-10 mM and a detection limit of 9 ppb (45 nM) in water.

An intercalated organic montmorillonite DOPO-MMT was prepared through the melting method using 9,10-dihydro-9-oxa-10-phosphaphenanthrene-10-oxide (DOPO) as a modifier. Epoxy resin (EP) composites were prepared with DOPO-MMT, DOPO, MMT, and the physical mixtures of DOPO+MMT as flame retardants. The microstructure of the flame retardants and EP samples were characterized by X-ray diffraction (XRD), scanning electron microscopy (SEM), and transmission electron microscopy (TEM). The flame retardant properties, thermal stability, and residual char structure of the EPs were studied by the limited oxygen index (LOI) test, the UL-94 vertical burning test, thermogravimetric analysis (TGA), the differential scanning calorimeter (DSC) test, the cone calorimeter (CONE) test as well as other characterization methods. The results showed that the intercalated organic montmorillonite DOPO-MMT can be successfully prepared by the melting method and that the MMT is evenly dispersed in the EP/DOPO-MMT composite in the form of nanosheets. The EP/DOPO-MMT nanocomposites showed the optimal flame retardancy (LOI, UL-94, PHRR, etc.) among the EPs with DOPO, MMT, and the physical mixture of DOPO+MMT. The flame-retardant grade of the material reached V-0.

A triphenylphosphine-assisted highly sensitive fluorescent chemosensor for ratiometric detection of palladium in solution and living cells was developed.

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