Blighia sapida Waste Biochar in Batch and Fixed-Bed Adsorption of Chloroquine Phosphate: Efficacy Validation Using Artificial Neural Networks.

The present study investigated the potency of biochar prepared from Blighia sapida seedpods (BSSPs) in the uptake of chloroquine phosphate (CQP) from single-component batch and multicomponent fixed-bed adsorption systems. BSSPs presented a highly porous structure with a BET surface area of 1122.05 m2/g, to which adsorption efficiency correlated. The Dubinin-Radushkevich isotherm energy was obtained as 129.09 kJ/mol, confirming the chemisorption nature of the BSSP-CQP adsorption system. The efficiency of the artificial neural network (ANN) was evaluated using the lowest mean square error (MSE = 7.27) and highest correlation coefficient (R2 = 0.9910). A good agreement between the experimental results and the ANN-predicted data indicated the efficiency of the model. The percentage removal of 95.78% obtained for the column adsorption studies indicated the effectiveness of BSSPs in a multicomponent system. The mechanism of the interaction proceeded via hydrogen bonding and electrostatic attraction. This was confirmed by the high desorption efficiency (69.11%) with a HCl eluent. The degree of reversibility was found to be 2.95, indicating the reusability potential of BSSPs. BSSPs are therefore considered multilayered adsorbents with potential applications in pharmaceutical wastewater treatment.

Unveiling the drives behind tetracycline adsorption capacity with biochar through machine learning.

This study aimed to develop a robust predictive model for tetracycline (TC) adsorption onto biochar (BC) by employing machine learning techniques to investigate the underlying driving factors. Four machine learning algorithms, namely Random Forest (RF), Gradient Boosting Decision Tree (GBDT), eXtreme Gradient Boosting (XGBoost) and Artificial Neural Networks (ANN), were used to model the adsorption of TC on BC using the data from 295 adsorption experiments. The analysis revealed that the RF model had the highest predictive accuracy (R2 = 0.9625) compared to ANN (R2 = 0.9410), GBDT (R2 = 0.9152), and XGBoost (R2 = 0.9592) models. This study revealed that BC with a specific surface area (S (BET)) exceeding 380 cm3·g-1 and particle sizes ranging between 2.5 and 14.0 nm displayed the greatest efficiency in TC adsorption. The TC-to-BC ratio was identified as the most influential factor affecting adsorption efficiency, with a weight of 0.595. The concentration gradient between the adsorbate and adsorbent was demonstrated to be the principal driving force behind TC adsorption by BC. A predictive model was successfully developed to estimate the sorption performance of various types of BC for TC based on their properties, thereby facilitating the selection of appropriate BC for TC wastewater treatment.

In Vivo Antiplasmodial Potential of the Leaf, Mesocarp, and Epicarp of the Raphia hookeri Plant in Mice Infected with Plasmodium berghei NK65.

Results: The presence of alkaloids, fats and oils, phenolic, and flavonoids was detected via the qualitative test which was confirmed from the result obtained from the GC-MS chromatogram of ethanolic leaves extract. The GC-MS chromatogram of the constituents analogous to the twenty peaks was analyzed as follows: dodecanoic acid (1.94%), 2-undecanone (3.42%), hexadecanoic acid (44.84%), oleic acid (7.45%), octadecanoic acid (8.41%), narcissidine (2.38%), 1-dotriacontanol (2.38%), α-sitosterol (2.02%), and lupeol (1.42%). The total phenolics and flavonoids of 118 and 23.3702 mg/g were analyzed in the leaves extract. The leave extract exhibited inhibitory activity of 73.49% against free radicals which could lead to inflammation. The extracts and chloroquine-treated groups showed significant decrease in percentage parasitaemia with pronounced activity observed in chloroquine groups. Conclusion: The curative and scavenging potencies of studied plant could be attributed to the metabolites analyzed and could guide the formulation of new pharmacophores against malaria infections and inflammations.

Rhodamine B dye sequestration using Gmelina aborea leaf powder.

Chemically prepared activated carbon derived from Gmelina aborea leaves (GALAC) were used as adsorbent for the removal of Rhodamine B (Rh-B) dye from aqueous solutions. The adsorptive characteristics of activated carbon (AC) prepared from Gmelina aborea leaves (GAL) were studied using SEM, FTIR, pH point of zero charge (pHpzc) and Boehm Titration (BT) techniques respectively. The effects of pH, contact time, initial dye concentration and solution temperature were also examined. Experimental data were analyzed using four different isotherm models: Langmuir, Freundlich, Temkin and Dubinin-Radushkevich. Four adsorption kinetic models: Pseudo-first-order (PFO), Pseudo-second-order (PSO), Elovich and Intraparticle diffusion models to establish the kinetics of adsorption process. The RhB dye adsorption on GALAC was best described by Langmuir isotherm model with maximum monolayer coverage of 1000 mg g-1 and R2 value of 0. 9999. The EDX analysis revealed that GALAC contained 82.81% by weight and 91.2% by atom of carbon contents which are requisites for high adsorption capacity. Adsorption kinetic data best fitted the PSO kinetic model. Thermodynamic parameters obtained for GALAC are (ΔGo ranged from -22.71 to -18.19 kJmol-1; ΔHo: 1.51 kJmol-1; and ΔSo: 0.39 kJmol-1 K-1respectively) indicating that the RhB dye removal from aqueous solutions by GALAC was spontaneous and endothermic in nature. The cost analysis established that GALAC is approximately eleven times cheaper than CAC thereby providing a saving of 351.41USD/kg. Chemically treated GAL was found to be an effective absorbent for the removal of RhB dye from aqueous solution.

Silver nanoparticle synthesis by Acalypha wilkesiana extract: phytochemical screening, characterization, influence of operational parameters, and preliminary antibacterial testing.

Single pot green synthesis of silver nanoparticles (AgNPs) was successfully carried out using medicinal plant extract of Acalypha wilkesiana via bottom-up approach. Five imperative operational parameters (pH, contact time, concentration, volume ratio and temperature) pivotal to the synthesis of silver nanoparticles were investigated. The study showed pH 9, 90 min contact time, 0.001 M Ag+ concentration, volume ratio 1:9 (extract: Ag+ solution), and temperature between 90 - 100 °C were important for the synthesis of Acalypha wilkesiana silver nanoparticles (AW-AgNPs). Phytochemical screening confirmed the presence of saponins, flavonoids, phenols and triterpenes for A. wilkesiana. These phytomolecules served as both capping and stabilizing agent in the green synthesis of silver nanoparticles. AW-AgNPs was characterized by UV-Vis Spectroscopy, Fourier Transform Infrared (FTIR) Spectroscopy and Scanning Electron Microscopy (SEM), Transmission Electron Microscopy (TEM) and Energy Dispersive X-ray (EDX). The surface Plasmon resonance (SPR) was observed at 450 nm which is a characteristic absorbance region of AW-AgNPs formation as a result of the collective oscillation of free electron of silver nanoparticles. FTIR Spectroscopy confirmed the presence of functional groups responsible for bioreduction of Ag+. SEM and TEM results confirmed a well dispersed AW-AgNPs of spherical shape. EDX shows the elemental distribution and confirmed AgNPs with a characteristic intense peak at 3.0 keV. AW-AgNPs showed significant inhibition against selected Gram negative and Gram positive prevailing bacteria. AW-AgNPs can therefore be recommended as potential antimicrobial and therapeutic agent against multidrug resistant pathogens.