Sustainable removal of chromium (III) from water using highly efficient magnetic biochar derived from Sawdust

Ifeoma Juliet Opara — 2026-06-01

In this study, magnetic biochars (MgSB450 and MgSB500) were applied for the adsorption of Cr³ ions from aqueous solutions. FTIR analysis (PerkinElmer, USA) confirmed the presence of surface functional groups, including amine, hydroxyl (O-H), C=C, C-N, and C-H stretching of aliphatic groups. Adsorption experiments were conducted to evaluate the effects of contact time, pH, temperature, ionic strength, and initial metal ion concentration. Optimum adsorption was observed at pH 7, with removal efficiencies of 99.481 % and 99.404 % for MgSB450 and MgSB500, respectively. At an initial metal ion concentration of 80 mg/L, maximum adsorption of up to 99.98 % and 99.96 % for MgSB450 and MgSB500, respectively was obtained. It was noticed that as the temperature increases, the adsorption capacity decreases, and optimum adsorption (99.928 and 99.968 %) was observed at 30 °C for both MgSB450 and MgSB500. The results showed that as time increases, the removal efficiency of chromium ions increases for the first 30 min., and then gradually decrease with an increase in time for MgSB450. It reached a maximum adsorption of 99.848 %, while MgSB500 reached equilibrium at 50 mins., with an adsorption capacity of 98.208 %. From the results, it was observed that, the ionic strength increases, the adsorption capacity decreases, with maximum adsorption values of 95.772 % and 96.888 % for both adsorbents at a 0.4 % NaCl concentration. The sorption capacities of MgSB450 and MgSB500 were comparable, demonstrating strong potential for adsorbing chromium ions from aqueous solutions and their applicability in industrial wastewater treatment.

Artificial intelligence–based avoidance of hopf bifurcations in dynamic optimal control of fermentation systems

Lakshmi. N. Sridhar — 2026-06-05

In biochemical systems, nonlinear processes are often associated with the Hopf bifurcation, which can result in oscillations, instability, and reduced product concentration. While bifurcation analysis tools such as MATCONT, implemented in MATLAB, can efficiently determine Hopf bifurcation points and associated stability boundaries, the direct incorporation of these results into dynamic optimal control problems remains an area of research. This paper presents an artificial intelligence-based approach for the optimal control of nonlinear biochemical processes. The proposed approach first determines the Hopf bifurcation points using the bifurcation analysis tool MATCONT. A neural network is then developed to determine the dominant eigenvalue or its proximity as an artificial intelligence-based surrogate model. This surrogate model is then incorporated into the optimal control framework based on the Pyomo model. The results demonstrate the efficiency of the proposed approach in maximizing product concentration while ensuring process stability. The proposed approach achieves near-optimal product concentrations, with only a small reduction compared to the unconstrained case, while effectively avoiding Hopf bifurcation-induced oscillations. In addition, the resulting control profiles remain smooth and practically implementable, highlighting the robustness of the proposed framework.

American Journal of Chemistry

Sustainable removal of chromium (III) from water using highly efficient magnetic biochar derived from Sawdust

Artificial intelligence–based avoidance of hopf bifurcations in dynamic optimal control of fermentation systems