A novel approach for the synthesis of nanostructured Ag3PO4 from phosphate rock: high catalytic and antibacterial activities

Establishing a productive heterogeneous catalyst based on silver nanoparticles supported on a crosslinked vinyl polymer for the reduction of nitrophenol

The treatment of toxic nitrophenols in industrial wastewater is urgently needed from environmental, health, and economic points of view. The current study addresses the synthesis of the crosslinked vinyl polymer poly(acrylonitrile-co-2-acrylamido-2-methylpropane sulfonic acid) (poly(AN-co-AMPS)) through free radical copolymerization techniques using acrylonitrile (AN) and 2-acrylamido-2-methylpropane sulfonic acid (AMPS) monomers with different ratios and potassium persulfate (KPS) as an initiator in an aqueous medium. The prepared copolymer was utilized as a supporting matrix for silver nanoparticles (AgNPs) via the chemical reduction of silver nitrate within the copolymer framework. Different techniques were employed to characterize the prepared poly(AN-co-AMPS) and Ag/poly(AN-co-AMPS) composites, such as Fourier transform infrared (FTIR) spectroscopy, thermal gravimetric analysis (TGA), X-ray diffraction (XRD), transmission electron microscopy (TEM), and Brunauer-Emmett-Teller (BET) analysis. The results exhibit that silver metal was excellently dispersed across the surface of poly(AN-co-AMPS) without any agglomeration, presenting as nanocrystals with an average particle size equal to 6.21 nm. Also, BET analysis confirmed that the Ag/poly(AN-co-AMPS) composite exhibits mesoporous characteristics with a surface area of 59.615 m2 g-1. Moreover, the Ag/poly(AN-co-AMPS) composite was effectively applied as a heterogeneous catalyst for the catalytic reduction of hazardous 4-nitrophenols (4-NP) with a rate constant equal to 0.28 min-1 and half-life time equal to 2.47 min to a less toxic compound in the presence of NaBH4 as a reductant. Furthermore, the reusability experiment confirmed the excellent stability of Ag/poly(AN-co-AMPS). The catalyst can be easily separated from the reaction mixture using a simple centrifuge and directly reused for up to four successive cycles without a remarkable decrease in its catalytic activity. The conversion percentage of 4-NP after the four cycles was found to be 93%.

Cluster energy prediction based on multiple strategy fusion whale optimization algorithm and light gradient boosting machine

BACKGROUND

Clusters, a novel hierarchical material structure that emerges from atoms or molecules, possess unique reactivity and catalytic properties, crucial in catalysis, biomedicine, and optoelectronics. Predicting cluster energy provides insights into electronic structure, magnetism, and stability. However, the structure of clusters and their potential energy surface is exceptionally intricate. Searching for the global optimal structure (the lowest energy) among these isomers poses a significant challenge. Currently, modelling cluster energy predictions with traditional machine learning methods has several issues, including reliance on manual expertise, slow computation, heavy computational resource demands, and less efficient parameter tuning.

RESULTS

This paper introduces a predictive model for the energy of a gold cluster comprising twenty atoms (referred to as Au20 cluster). The model integrates the Multiple Strategy Fusion Whale Optimization Algorithm (MSFWOA) with the Light Gradient Boosting Machine (LightGBM), resulting in the MSFWOA-LightGBM model. This model employs the Coulomb matrix representation and eigenvalue solution methods for feature extraction. Additionally, it incorporates the Tent chaotic mapping, cosine convergence factor, and inertia weight updating strategy to optimize the Whale Optimization Algorithm (WOA), leading to the development of MSFWOA. Subsequently, MSFWOA is employed to optimize the parameters of LightGBM for supporting the energy prediction of Au20 cluster.

CONCLUSIONS

The experimental results show that the most stable Au20 cluster structure is a regular tetrahedron with the lowest energy, displaying tight and uniform atom distribution, high geometric symmetry. Compared to other models, the MSFWOA-LightGBM model excels in accuracy and correlation, with MSE, RMSE, and R2 values of 0.897, 0.947, and 0.879, respectively. Additionally, the MSFWOA-LightGBM model possesses outstanding scalability, offering valuable insights for material design, energy storage, sensing technology, and biomedical imaging, with the potential to drive research and development in these areas.

A Novel Approach to Prepare Cellulose-g-Hydroxyapatite Originated from Natural Sources as an Efficient Adsorbent for Heavy Metals: Batch Adsorption Optimization via Response Surface Methodology

In the present research, we describe a novel approach for in situ synthesis of cellulose microfibrils-grafted-hydroxyapatite (CMFs-g-HAPN (8%)) as an adsorbent using phosphate rock and date palm petiole wood as alternative and natural Moroccan resources. The synthesized CMFs-g-HAPN (8%) was extensively characterized by several instrumental techniques like thermogravimetry analysis, Fourier transform infrared spectroscopy, X-ray diffraction, 31P nuclear magnetic resonance, scanning electron microscopy, and Brunauer-Emmett-Teller analysis. The developed adsorbent was used to remove Pb(II) and Cu(II) from aqueous solutions. The influences of different adsorption parameters such as contact time, initial metal concentration, and amount of adsorbent were also investigated thoroughly using response surface methodology in order to optimize the batch adsorption process. The results confirmed that the adsorption process follows a polynomial quadratic model as high regression parameters were obtained (R 2 value = 99.8% for Pb(II) and R 2 value = 92.6% for Cu(II)). According to kinetics and isotherm modeling, the adsorption process of both studied ions onto CMFs-g-HAPN (8%) followed the pseudo-second-order model, and the equilibrium data at 25 °C were better fitted by the Langmuir model. The maximum adsorption capacities of the CMFs-g-HAPN (8%) adsorbent toward Pb(II) and Cu(II) are 143.80 and 83.05 mg/g, respectively. Moreover, the experiments of multicycle adsorption/desorption indicated that the CMFs-g-HAPN (8%) adsorbent could be regenerated and reused up to three cycles. The high adsorption capacities of both studied metals and regeneration performances of the CMFs-g-HAPN (8%) suggest its applicability as a competitive adsorbent for large-scale utilization.

Aluminum Doping and Nanostructuring Enabled Designing of Magnetically Recoverable Hexaferrite Catalysts

We demonstrate an approach based on substituting a magnetic cation with a carefully chosen isovalent non-magnetic cation to derive catalytic activity from otherwise catalytically inactive magnetic materials. Using the model system considered, the results illustratively present that the catalytically inactive but highly magnetic strontium hexaferrite (SrFe12O19; SFO) system can be transformed into a catalytically active system by simply replacing some of the magnetic cation Fe3+ by a non-magnetic cation Al3+ in the octahedral coordination environment in the SFO nanocrystals. The intrinsic SFO and Al-doped SrFe12O19 (SrFe11.5Al0.5O19; Al-SFO) nanomaterials were synthesized using a simple, eco-friendly tartrate-gel technique, followed by thermal annealing at 850 °C for 2 h. The SFO and Al-SFO were thoroughly characterized for their structure, phase, morphology, chemical bonding, and magnetic characteristics using X-ray diffraction, Fourier-transform infrared spectroscopy, and vibrating sample magnetometry techniques. Catalytic performance evaluated toward 4-nitrophenol, which is the toxic contaminant at pharmaceutical industries, reduction reaction using NaBH4 (mild reducing agent), the Al-doped SFO samples exhibit a reasonably good performance compared to intrinsic SFO. The results indicate that the catalytic activity of Al-SFO is due to Al-ions occupying the octahedral sites of the hexaferrite lattice; as these sites are on the surface of the catalyst, they facilitate electron transfer. Furthermore, surface/interface characteristics of nanocrystalline Al-SFO coupled with magnetic properties facilitate the catalyst recovery by simple, inexpensive methods while readily allowing the reusability. Moreover, the activity remains the same even after five successive cycles of experiments. Deriving the catalytic activity from otherwise inactive compounds as demonstrated in the optimized, engineered nanoarchitecture of Al-doped-Sr-hexaferrite may be useful in adopting the approach in exploring further options and designing inexpensive and recyclable catalytic materials for future energy and environmental technologies.