Phytoremediation of nitrogen and phosphorus pollutants from glass industry effluent by using water hyacinth (Eichhornia crassipes (Mart.) Solms): Application of RSM and ANN techniques for experimental optimization.

The present study aimed to assess the efficiency of the water hyacinth (Eichhornia crassipes (Mart.) Solms) plant for the reduction of nitrogen and phosphorus pollutants from glass industry effluent (GIE) as batch mode phytoremediation experiments. For this, response surface methodology (RSM) and artificial neural networks (ANN) methods were adopted to evidence the optimization and prediction performances of E. crassipes for total Kjeldahl's nitrogen (TKN) and total phosphorus (TP) removal. The control parameters, i.e., GIE concentration (0, 50, and 100%) and plant density (1, 3, and 5 numbers) were used to optimize the best reduction conditions of TKN and TP. A quadratic model of RSM and feed-forward backpropagation algorithm-based logistic model (input layer: 2 neurons, hidden layer: 10 neurons, and output layer: 1 neuron) of ANN showed good fitness results for experimental optimization. Optimization results showed that maximum reduction of TKN (93.86%) and TP (87.43%) was achieved by using 60% of GIE concentration and nearly five plants. However, coefficient of determination (R2) values showed that ANN models (TKN: 0.9980; TP: 0.9899) were superior in terms of prediction performance as compared to RSM (TKN: 0.9888; TP: 0.9868). Therefore, the findings of this study concluded that E. crassipes can be effectively used to remediate nitrogen and phosphorus loads of GIE and minimize environmental hazards caused by its unsafe disposal.

Simple Preparation of Multifunctional Luminescent Textile for Smart Packaging.

Linen has been a significant material for textile packaging. Thus, the application of the simple spray-coating method to coat linen fibers with a flame-retardant, antimicrobial, hydrophobic, and anticounterfeiting luminescent nanocomposite is an innovative technique. In this new approach, the ecologically benign room-temperature vulcanizing (RTV) silicone rubber was employed to immobilize the environmentally friendly Exolit AP 422 (Ex) and lanthanide-doped strontium aluminum oxide (RESAO) nanoscale particles onto the linen fibrous surface. Both morphological properties and elemental compositions of RESAO and treated fabrics were examined by transmission electron microscopy (TEM), scanning electron microscopy (SEM), wavelength-dispersive X-ray fluorescence (WD-XRF), Fourier transform infrared (FTIR) spectroscopy, and energy-dispersive X-ray spectroscopy (EDX). In the fire resistance test, the treated linen fabrics produced a char layer, giving them the property of self-extinguishing. Furthermore, the coated linen samples' fire-retardant efficacy remained intact after 35 washing cycles. As the concentration of RESAO increased, so did the treated linen superhydrophobicity. Upon excitation at 366 nm, an emission band of 519 nm was generated from a colorless luminescent film deposited onto the linen surface. The coated linen displayed a luminescent activity by changing color from off-white beneath daylight to green beneath UV source, which was proved by CIE Lab parameters and photoluminescence spectral analysis. The photoluminescence effect was identified in the treated linen as reported by emission, excitation, and decay time spectral analysis. The comfort properties of coated linen fabrics were measured to assess their mechanical and comfort features. The treated linen exhibited excellent UV shielding and improved antimicrobial performance. The current simple strategy could be useful for large-scale production of multifunctional smart textiles such as packaging textiles.