Jacques Romain Njimou

The performance of biomass briquettes produced from agricultural residues is governed by nonlinear and interacting thermochemical parameters, limiting the applicability of conventional deterministic models. This study proposes a probabilistic machine-learning framework to predict, interpret, and optimize the calorific performance of lignocellulosic biomass briquettes. An experimental dataset of 300 observations covering pyrolysis temperatures of 400–600 °C, moisture contents of 4–15%, binder proportions of 5–15%, fixed carbon contents of 45–78%, and ash contents of 3–18% was analysed. Under five-fold cross-validation, Random Forest achieved R² ≈ 0.97 and outperformed Extreme Gradient Boosting (XGBoost; R² ≈ 0.95). Shapley Additive Explanations (SHAP) and Sobol global sensitivity analysis identified fixed carbon and pyrolysis temperature as the dominant predictors. Bayesian optimization converged in approximately 35 iterations and identified a processing window of 548–562 °C, 9–11% binder, and moisture below 7%. The Non-dominated Sorting Genetic Algorithm II (NSGA-II) revealed a Pareto compromise near 10% binder. Random Forest ensemble dispersion produced approximate 95% uncertainty bands of ±120 kcal kg⁻¹; these bands are internal uncertainty estimates rather than externally calibrated prediction intervals. The framework combines nonlinear prediction, interpretation, sensitivity analysis, optimization, and uncertainty assessment, while its applicability remains restricted to the measured maize/cassava feedstocks, clay binder, and operating domain.

Al₂O₃ is an electrical insulator material with high thermal conductivity and low toxicity. In this study, we combined the properties of Al₂O₃ and orange peel (OP) to form a hydrothermally synthesized nanomaterial, resulting in an excellent nanocomposite (AlOP) with favorable electrochemical properties compared to those of their separate materials. AlOP exhibited a compact morphology with relatively high porosity and varying shapes, attributed to the blending of aluminum oxide nanoparticles in the OP matrix. The structural properties of this nanocomposite have facilitated the modification of the carbon paste electrode (CPE) for the detection of methyl orange, an anionic dye of environmental significance. This electrochemical sensor has demonstrated high sensitivity, selectivity, stability, rapid response, and remarkable reproducibility for the detection of methyl orange (MO) with detection limits of 3.23×10⁻⁸ and 1.26×10⁻⁷ mol. L⁻¹ in deionized and spring waters with molarities of 2 to 1.2 μM. Therefore, the developed CPE/AlOP sensor has the capacity for detecting anionic dye from multiple systems without affecting its efficiency.

Amongst the various water pollutants, heavy metal ions require special attention because of their toxic nature and effects on humans and the environment. Preserving natural resources will have positive impacts on living conditions by reducing diseases and water treatment by nanotechnology is effective in solving this problem owing to the properties of nanomaterials. In this study, a goethite nanoparticle was prepared by hydrothermal method, while ZnO/goethite nanocomposite by co-precipitation was developed. The nanoparticles were characterized using Scanning Electron Microscopy (SEM), X-ray Diffraction (XRD), Fourier Transform Infrared Spectroscopy (FTIR), Transform Electron Microscopy (TEM), Thermogravimetric Differential Thermal Analysis (TGA-DTA), Dynamic Light Scattering (DLS), and Breunner-Emmet-Teller (BET) surface area analysis. The adsorption of Cd(II)-Pb(II) and Cd(II)-Pb(II)-Ni(II) ions systems on ZnO/goethite nanocomposite was investigated in a batch mode. The findings of the study showed that nanoparticles ZnO/goethite composite were mixed of spherical and rod-like shapes. The BET results revealed average particle sizes of 41.11 nm for nanoparticles for ZnO/goethite while TGA/DTA confirmed the stability of the adsorbents. The optimum adsorption capacities of the nanocomposite for Pb(II), Cd(II), and Ni(II) ions from the Pb-Cd-Ni ternary system were 415.5, 195.3, and 87.13 mg g⁻¹, respectively. The adsorption isotherm data fitted well with the Langmuir isotherm model. The study concluded that the nanoparticle adsorbents are efficient for the remediation of toxic pollutants and are, therefore, recommended for wastewater treatment.

BACKGROUND: Water contaminated by heavy metals has many negative impacts on human health and the environment. According to the UN's sustainable development goals, preserving natural resources will have positive impacts on living conditions by reducing diseases. In this study, a novel adsorbent synthesized from phosphate‐based geopolymer cement composite material was developed and evaluated for lead removal from aqueous solutions. The developed adsorbent is made from natural resources using a facile protocol, and thus it is suitable for both developed and developing countries.RESULTS: Analyses of mineralogical composition, pore‐size distribution and surface of the synthesized phosphate‐based geopolymer cement composite were performed. A microporous structure was observed from the microstructural characterization. Geopolymer cement was immobilized with sodium alginate to fabricate alginate–geopolymer cement beads (Alg/GES). The parameters influencing the adsorption process were investigated in batch mode. The obtained results showed that the adsorption capacity of Pb(II) ions increased with time and equilibrium was reached in 90 min. The optimum adsorption pH was 4.17. The experimental results showed that the adsorption equilibrium of Pb(II) on Alg/GES was well described by the Freundlich and Langmuir models whereas the adsorption rate was well fitted by the pseudo‐second‐order kinetics model. The maximum adsorption capacity obtained from the Langmuir isotherm was q_max = 0.38 mmol g⁻¹. From the Dubinin–Radushkevitch isotherm model, the value of the free adsorption energy was 41 kJ mol⁻¹.CONCLUSIONS: Compared with other adsorbents, Alg/GES exhibited a greater adsorption capacity confirming that the phosphate‐based geopolymer cement can be suitable for removal of heavy metals from wastewaters. © 2021 Society of Chemical Industry

Olive oil extraction generates a large quantity of wastewater which is a strong pollutant due to its high organic load and phytotoxic. However, its content in antibacterial phenolic substances displays to be resistant to biological degradation. The discharge of olive mill wastewater (OMWW) is not allowed through the municipal sewage system and/or in a natural effluent. Unfortunately, the current technologies for the treatment of OMWW are expensive and complicated to be operated in a mill factory where the objective of this study. We have designed and implemented a process that permitted both the treatment of agro-food processing water and the recovering of compounds of market interest. The process was applied in the effluents of olive oil mill factories to recover polyphenols with a possible significant reduction of organic waste. The nanofiltration fraction obtained from a sequential treatment involved coagulation, photocatalysis, ultrafiltration and nanofiltration was performed to separate the most valuable compounds using column adsorption runs. Competitive adsorption and the selectivity were obtained for phenol and hydroxytyrosol onto macro-reticular aromatic polymer (FPX66) and macroporous polystyrene cross-linked with divinylbenzene (MN202), respectively. The investigations were followed by a single component of phenol or tyrosol, binary phenol and tyrosol and ternary components in NF concentrate of OMWW for valuable compounds recovery conducted in a fixed-bed adsorber of resins. During the intermediate stage of the column operation, adsorbed tyrosol molecules were replaced by the incoming phenol molecules due to the lower tyrosol affinity for FPX66 resin and the tyrosol concentration was higher than its feed concentration.

The biosorption characteristics of Cd (II) ions from synthetic wastewater using raw Ayous wood sawdust (Triplochiton scleroxylon), r-AS, immobilized by sodium alginate were investigated with respect to pH, biomass quantity, contact time, initial concentration of heavy metal, temperature and stirring rate. The experimental data fitted well with the Langmuir isotherm, suggesting that monolayer adsorption of the cadmium ions onto alginate–Ayous sawdust composite (a-ASC). The obtained monolayer adsorption capacity of a-ASC for Cd (II) was 6.21 mg/g. From the Dubinin–Radushkevich isotherm model, a 5.39 kJ/mol value for the mean free energy was calculated, indicating that Cd (II) biosorption could include an important physisorption stage. Thermodynamic calculations showed that the Cd (II) biosorption process was feasible, endothermic and spontaneous in nature under examined conditions. The results indicated that a-ASC could be an alternative material replacing more costly adsorbents used for the removal of heavy metals.