pH-dependent effect of Congo Red on the growth of Aspergillus nidulans and Aspergillus niger

How Metarhizium robertsii's mycelial consciousness gets its conidia Zen-ready for stress

This memoir takes a whimsical ride through my professional adventures, spotlighting my fungal stress research on the insect-pathogenic fungus Metarhizium robertsii, which transformed many of my wildest dreams into reality. Imagine the magic of fungi meeting science and me, a happy researcher, arriving at Utah State University ready to dive deep into studies with the legendary insect pathologist, my advisor Donald W. Roberts, and my co-advisor Anne J. Anderson. From my very first "Aha!" moment in the lab, I plunged into a vortex of discovery, turning out research like a mycelium on a mission. Who knew 18 h/day, seven days a week, could be so exhilarating? I was fueled by an insatiable curiosity, boundless creativity, and a perhaps slightly alarming level of motivation. Years later, I managed to bring my grandest vision to life: the International Symposium on Fungal Stress-ISFUS. This groundbreaking event has attracted 162 esteemed speakers from 29 countries to Brazil, proving that fungi can be both fun and globally fascinating. ISFUS is celebrating its fifth edition in 2024, a decade after its 2014 debut.

Sorption Behavior of Azo Dye Congo Red onto Activated Biochar from Haematoxylum campechianum Waste: Gradient Boosting Machine Learning-Assisted Bayesian Optimization for Improved Adsorption Process

This work aimed to describe the adsorption behavior of Congo red (CR) onto activated biochar material prepared from Haematoxylum campechianum waste (ABHC). The carbon precursor was soaked with phosphoric acid, followed by pyrolysis to convert the precursor into activated biochar. The surface morphology of the adsorbent (before and after dye adsorption) was characterized by scanning electron microscopy (SEM/EDS), BET method, X-ray powder diffraction (XRD), and Fourier-transform infrared spectroscopy (FTIR) and, lastly, pHpzc was also determined. Batch studies were carried out in the following intervals of pH = 4-10, temperature = 300.15-330.15 K, the dose of adsorbent = 1-10 g/L, and isotherms evaluated the adsorption process to determine the maximum adsorption capacity (Qmax, mg/g). Kinetic studies were performed starting from two different initial concentrations (25 and 50 mg/L) and at a maximum contact time of 48 h. The reusability potential of activated biochar was evaluated by adsorption-desorption cycles. The maximum adsorption capacity obtained with the Langmuir adsorption isotherm model was 114.8 mg/g at 300.15 K, pH = 5.4, and a dose of activated biochar of 1.0 g/L. This study also highlights the application of advanced machine learning techniques to optimize a chemical removal process. Leveraging a comprehensive dataset, a Gradient Boosting regression model was developed and fine-tuned using Bayesian optimization within a Python programming environment. The optimization algorithm efficiently navigated the input space to maximize the removal percentage, resulting in a predicted efficiency of approximately 90.47% under optimal conditions. These findings offer promising insights for enhancing efficiency in similar removal processes, showcasing the potential of machine learning in process optimization and environmental remediation.

Magnetically separable Co0.6Fe2.4O4/MIL-101-NH2 adsorbent for Congo red efficient removal

The development of effective and practical adsorbents for eliminating pollutants still remains a significant challenge. Herein, we synthesized a novel magnetically separable composite, Co0.6Fe2.4O4/MIL-101-NH2, through the in-situ growth of MIL-101-NH2 on magnetic nanoparticles, designed specifically for the removal of Congo red (CR) from aqueous solutions. MIL-101-NH2 possessed high BET surface area (240.485 m2•g-1) and facile magnetic separation function and can be swiftly separated (within 30 s) through an external magnetic field post-adsorption. The investigation systematically explored the influence of crucial parameters, including adsorbent dosage, pH, adsorption duration, temperature, and the presence of interfering ions, on CR adsorption performance. Findings indicate that CR adsorption adheres to the pseudo-second-order (PSO) kinetic model and the Langmuir isotherm model. Thermodynamic analysis reveals the spontaneity, endothermic nature, and orderly progression of the adsorption process. Remarkably, the adsorbent with 0.1 g•L-1 boasts an impressive maximum adsorption capacity of 1756.19 mg•g-1 for CR at 298.15 K, establishing its competitive advantage. The reuse of the adsorbent over 5 cycles remains 78% of the initial adsorption. The CR adsorption mechanisms were elucidated, emphasizing the roles of π-π interactions, electrostatic forces, hydrogen bonding, and metal coordination. Comparison with other dyes, such as methylene blue (MB) and methyl orange (MO), and exploration of adsorption performance in binary dye systems, demonstrates the superior capacity and selectivity of this adsorbent for CR. In conclusion, our magnetically separable metal-organic framework (MOF)based composite presents a versatile and effective solution for CR removal, with promising applications in water treatment and environmental remediation.