-
Research Article
Fluoride Removal Efficiency of Calcium-spiked and Non-spiked Moringa Oleifera Seed Powder
Issue:
Volume 14, Issue 4, December 2025
Pages:
91-99
Received:
1 September 2025
Accepted:
15 September 2025
Published:
18 October 2025
Abstract: Fluoride contamination in drinking water remains a widespread public health concern, particularly in arid and semi-arid regions where groundwater is the primary source of potable water. Chronic exposure to elevated fluoride levels—commonly above the World Health Organization’s (WHO) recommended limit of 1.5 mg/L—can result in dental and skeletal fluorosis, affecting millions of people globally. Affordable and effective defluoridation technologies are urgently needed, especially in low-income rural settings. In this study, the fluoride removal efficiency of calcium-spiked and non-spiked Moringa oleifera seed powder was investigated through controlled laboratory batch adsorption experiments. Biosorbents were prepared by treating ground seed powder with 1% calcium chloride solution and characterised based on their performance across five fluoride concentrations (1-20 ppm). Key parameters such as removal efficiency, residual fluoride levels, and adsorption capacity (qe) were evaluated under consistent operating conditions (pH 7, 2 g/50 mL dose, mesh 40, 120 minutes). Results indicated that calcium-spiked Moringa oleifera powder significantly outperformed its non-spiked counterpart. At 1 ppm, the spiked adsorbent achieved 94.35 ± 1.15% removal efficiency, compared to 81.45 ± 1.35% for the non-spiked. At the highest tested concentration (20 ppm), the spiked biosorbent still removed 72.31 ± 1.80% of fluoride, while the non-spiked removed only 54.21 ± 1.95%. Linear regression models showed strong inverse correlations between fluoride concentration and removal efficiency (R2 > 0.99, p < 0.001). The spiked adsorbent also resulted in significantly lower residual fluoride concentrations, with final values closer to the WHO guideline. One-way ANOVA confirmed significant differences in adsorption capacity and efficiency between treatments (p < 0.001). These findings highlight the effectiveness of calcium modification in enhancing biosorption performance and suggest that calcium-spiked Moringa oleifera seed powder is a promising, low-cost, and environmentally friendly solution for mitigating fluoride contamination in drinking water.
Abstract: Fluoride contamination in drinking water remains a widespread public health concern, particularly in arid and semi-arid regions where groundwater is the primary source of potable water. Chronic exposure to elevated fluoride levels—commonly above the World Health Organization’s (WHO) recommended limit of 1.5 mg/L—can result in dental and skeletal fl...
Show More
-
Research Article
Enhanced Solubility of Herbicide Diuron in Aqueous Solution by Micellisation
Souleymane Sambou
,
Ibrahima Sarr,
Nehou Diouf,
Coumba Faye,
Abdou Khadre Cisse,
Boubacar Sidibe,
Aly Cisse,
Keba Diongue,
El Hadji Tombe Bodian*,
Diene Diegane Thiare,
Atanasse Coly
Issue:
Volume 14, Issue 4, December 2025
Pages:
100-109
Received:
17 October 2025
Accepted:
6 November 2025
Published:
17 December 2025
Abstract: Surfactants are substances widely used in agricultural sprays to improve the solubility and mobility of pesticides across crops. This study investigates the micellar properties of two ionic surfactants sodium dodecyl sulfate (SDS) and tetramethylammonium tetrafluoroborate (TMATFB) with respect to their ability to solubilize the herbicide diuron in aqueous solution. Conductometric measurements were performed in aqueous media over a temperature range of 298 to 331 K to analyze the micellization behavior and evaluate the efficiency of solubilization. From the conductivity data the critical micelle concentration (CMC), and degree of ionization were obtained at various temperatures. Concentration and temperature effect on the CMC have been studied and the different thermodynamic parameters were evaluated. The critical micellar concentration (CMC) values of surfactants decreased with increasing temperature, indicating enhanced micelle formation under thermal influence. Additionally, the solubility of diuron varied significantly across different surfactant micelles concentration, suggesting that specific interactions occur between the surfactant head groups and the pesticide. The standard Gibbs free energy (∆G°) for the diuron–surfactant mixtures was attained to be negative throughout the study suggesting spontaneous micellization process. The enthalpy (∆H°) and entropy (∆S°) were also evaluated, offering additional insight into the thermodynamic driving forces involved. The obtained thermodynamic parameters showed that |TΔS°| is greater than |ΔH°|, suggesting that the micellization process is controlled by entropy.
Abstract: Surfactants are substances widely used in agricultural sprays to improve the solubility and mobility of pesticides across crops. This study investigates the micellar properties of two ionic surfactants sodium dodecyl sulfate (SDS) and tetramethylammonium tetrafluoroborate (TMATFB) with respect to their ability to solubilize the herbicide diuron in ...
Show More
-
Research Article
Selective Removal of Methylene Blue Using Cellulose-Based Imprinted Polymers from Agro-Waste
Issue:
Volume 14, Issue 4, December 2025
Pages:
110-124
Received:
20 September 2025
Accepted:
4 October 2025
Published:
26 December 2025
DOI:
10.11648/j.ajpc.20251404.13
Downloads:
Views:
Abstract: Methylene blue (MB), a common cationic dye, poses environmental and health risks due to its persistence in industrial effluents. In this study, cellulose-based molecularly imprinted polymer (MIP) was synthesized from oil bean (Pentaclethra macrophylla) seed shell waste, using MB as a template. Non-imprinted polymer (NIP) was prepared as control. The materials were characterized by FTIR, SEM, and XRD, which confirmed successful polymerization and the presence of template-specific binding cavities in MIP. Batch adsorption experiments assessed the effects of pH, contact time, adsorbent dosage, initial dye concentration, and temperature. The adsorption kinetics followed a pseudo-second-order model, while equilibrium data were best fitted to the Freundlich isotherm, indicating heterogeneous surface binding. The maximum adsorption capacity of the MIP was 14.93 mg g-1, compared with 10.26 mg g-1 for the NIP. Thermodynamic analysis showed the process was spontaneous and exothermic. Selectivity studies demonstrated strong molecular recognition of MB, with an imprinting factor of 3.37 and selectivity factors of 3.25 (MB/indigo carmine) and 2.89 (MB/fuchsin basic). These findings highlight that agro-waste valorization into functional MIPs provides an efficient and low-cost adsorbent with enhanced affinity and selectivity for dye removal. The study contributes to sustainable wastewater management by combining molecular imprinting with biomass utilization, thereby supporting circular economy goals. Future work should investigate regeneration, scale-up, and application in continuous-flow systems for practical deployment.
Abstract: Methylene blue (MB), a common cationic dye, poses environmental and health risks due to its persistence in industrial effluents. In this study, cellulose-based molecularly imprinted polymer (MIP) was synthesized from oil bean (Pentaclethra macrophylla) seed shell waste, using MB as a template. Non-imprinted polymer (NIP) was prepared as control. Th...
Show More
-
Research Article
Prediction of Molecular Structures and Properties by Using Quantum Technology
Ravuri Hema Krishna*
Issue:
Volume 14, Issue 4, December 2025
Pages:
125-146
Received:
26 November 2025
Accepted:
20 December 2025
Published:
31 December 2025
DOI:
10.11648/j.ajpc.20251404.14
Downloads:
Views:
Abstract: Accurate prediction of molecular structures and properties is vital for chemistry; materials science, and drug discovery, yet classical electronic-structure methods often fail for strongly correlated systems, large basis sets, and complex potential-energy landscapes. Quantum technology encompassing quantum computing, quantum machine learning, and hybrid quantum classical strategies offers a fundamentally new paradigm by encoding many-electron wave functions directly on qubits and exploiting superposition and entanglement to explore exponentially large Hilbert spaces. This review synthesizes recent algorithmic and hardware advances relevant to molecular modelling, including the Variational Quantum Eigensolver (VQE), Quantum Phase Estimation (QPE), quantum unitary coupled-cluster (q-UCC) families, equation-of-motion and subspace methods for excited states, tensor-network hybrids, and quantum kernel and variational QML approaches. We examine noise-aware hybrid workflows, error-mitigation techniques, symmetry-preserving ansätze, and operator-factorization methods that reduce measurement and gate overhead. Representative applications are discussed: ground- and excited-state energy prediction, potential-energy surface mapping, geometry and transition-state optimization, spectroscopic property estimation (IR, UV–Vis, NMR, EPR), and reaction-dynamics scenarios where non-adiabatic effects and conical intersections dominate. Resource estimates and scaling analyses clarify current NISQ limitations qubit counts, circuit depth, shot complexity and delineate the roadmap to fault-tolerant QPE for chemical accuracy. We compare quantum approaches with classical baselines (DFT, CCSD (T), multireference methods), identifying domains where quantum methods already show promise (strong correlation, multi-reference dissociation, spin-state ordering) and where classical methods remain competitive. Finally, we highlight near-term industrial opportunities in drug design, catalysis, CO2 capture, and energy materials, and outline critical research directions: algorithmic reductions in measurement/precision cost, hardware improvements in fidelity and connectivity, scalable ansatz design, and integrated software stacks for reproducible hybrid simulations. Together, these developments indicate that while practical, large-scale quantum advantage for general chemistry remains future work, quantum technologies are rapidly maturing into powerful tools for targeted molecular problems that are intractable with existing classical techniques.
Abstract: Accurate prediction of molecular structures and properties is vital for chemistry; materials science, and drug discovery, yet classical electronic-structure methods often fail for strongly correlated systems, large basis sets, and complex potential-energy landscapes. Quantum technology encompassing quantum computing, quantum machine learning, and h...
Show More
