Elemi essential oil, extracted from the resin of the elemi tree (Canarium luzonicum), is highly valued for its distinctive aromatic and medicinal properties. Its complex composition includes various monoterpenes and sesquiterpenes such as α-phellandrene, limonene, and elemicin, which collectively contribute to its unique fragrance and therapeutic benefits. However, the oil’s susceptibility to environmental factors such as heat, light, and oxidation often leads to degradation and reduced efficacy. In this study, we investigated the encapsulation of elemi essential oil components within cyclodextrin metal-organic frameworks (CD-MOFs) using molecular docking and molecular dynamics (MD) simulations to assess adsorption behavior and complex stability. Significant variation in binding affinities was observed, with cis-sabinene exhibiting the strongest adsorption driven by favorable hydrophobic interactions within the CD-MOF cavity, while β-phellandrene demonstrated weaker binding attributed to less optimal molecular fit. MD simulations further confirmed the stable encapsulation of hydrophobic compounds, including d-limonene, α-elemol, α-phellandrene, and elemicin within the CD-MOF structure. Despite conformational adjustments during simulation, these complexes maintained high structural integrity, as evidenced by consistently low root-mean-square deviation (RMSD) and radius of gyration values. These results underscore the critical role of non-covalent interactions, particularly van der Waals forces, and reveal the inherent structural flexibility and robustness of CD-MOFs in accommodating diverse hydrophobic guest molecules. This work demonstrates the strong potential of CD-MOFs as versatile and effective carriers for the encapsulation and stabilization of hydrophobic essential oil components, paving the way for their application in advanced delivery systems across pharmaceutical, cosmetic, and food industries.

This study examines the adsorption behavior of textile dyes Crystal Violet (CV), Methylene Blue (MB), and Congo Red (CR) within cyclodextrin-based metal-organic frameworks (CD-MOFs) using simulated annealing and molecular dynamics simulations. The lowest-energy configurations revealed that CV is predominantly trapped within the central cavity of CD-MOF, stabilized by strong hydrogen bonding between cyclodextrin moieties and the amine group of CV. The adsorption energy of -74.84 kJ mol-1 suggests strong interaction, indicative of chemisorption-like behavior. MB and CR, in contrast, were primarily adsorbed within the side cavities of CD-MOF, exhibiting adsorption energies of -47.55 kJ mol-1 and -718.17 kJ mol-1, respectively. The stability of these dye-CD-MOF complexes was confirmed by molecular dynamics, with low root-mean-square deviations (RMSD) and consistent radii of gyration over 10 ns simulations. Electrostatic and van der Waals interactions played a critical role in maintaining dye entrapment, ensuring prolonged retention within the MOF structure. These results highlight the potential of CD-MOFs as effective adsorbents for dye removal in wastewater treatment, with strong and stable dye-MOF interactions preventing desorption and ensuring efficient pollutant capture.

Academic success in Physical Chemistry is influenced by personal, institutional, and social factors. Key predictors include prior academic performance, study habits, motivation, and time management. A strong foundation in prerequisite knowledge, effective learning strategies, and self-efficacy are crucial for overcoming challenges. Institutional factors, particularly instructional quality, academic policies, and resource accessibility, significantly impact outcomes, with structured pedagogy proving more influential than interactive learning environments. Peer interactions, including group cohesion and instructor engagement, emerged as the strongest social predictors of success. Students with clear grade expectations and strong self-efficacy exhibited higher persistence and achievement, while stress, physical health, and administrative support played indirect roles in overall well-being. Regression analysis confirmed the predictive strength of these factors. Student feedback highlighted the need for additional practice problems, tutoring, and online resources, while faculty emphasized challenges in conceptual understanding, mathematical skills, and workload management. Addressing these concerns through evidence-based teaching, flexible assessments, and targeted interventions can enhance student performance. Universities should integrate personalized learning, motivation-driven strategies, and institutional support to foster resilience and long-term academic success.

This study investigates the factors influencing student performance in Chemical Engineering Thermodynamics, focusing on personal, institutional, social, and external factors. We examine the role of teaching strategies, course design, and peer collaboration in enhancing student success. Key predictors of success include confidence in problem-solving, intrinsic motivation, and a strong foundation in prerequisite knowledge. Effective teaching strategies, such as well-structured course design, practical application of concepts, timely feedback, and engaging lectures, significantly enhance comprehension and academic performance. Peer collaboration, instructor accessibility, and a positive classroom environment further support student engagement and persistence. External challenges also impact outcomes and underscore the need for flexible academic policies and robust student support services. The study highlights the importance of a holistic and student-centered approach that integrates high-quality instruction, structured learning environments, and comprehensive support systems to foster resilience, deepen learning, and ensure long-term success.

This study explores the potential of chitosan (CS)/polyvinyl alcohol (PVA)/lemongrass hydrochar (LGHC) composite beads as efficient adsorbents for azo dye removal for the first time, demonstrating their high efficacy and sustainability. Unlike conventional adsorbents, these composite beads incorporate LGHC, a low-cost, renewable biomass-derived material, and sustainable polymers (CS and PVA), offering an eco-friendly and cost-effective alternative for industrial dye removal. The optimal composition of the composite beads was determined to be 2.00 wt% CS, 862.70 ppm LGHC, and 0.50 wt% PVA, achieving impressive sorption capacities of 22.30 mg/g for methyl orange, 57.73 mg/g for congo red, and 74.20 mg/g for methyl red. The composite beads featured a porous structure, and a composition enriched with carbon, oxygen, and nitrogen, facilitating dye removal through electrostatic interactions, hydrogen bonding, and π-π stacking. While their sorption capacities are comparable to conventional adsorbents, the incorporation of biomass-derived hydrochar and sustainable polymers enhances their environmental viability. This study underscores the potential of CS/PVA/LGHC composite beads as a scalable, eco-friendly solution for mitigating industrial dye pollution, contributing to cleaner water systems and greater environmental sustainability.

Graphitic carbon nitride (GCN) is a versatile photocatalytic material with applications in water treatment, hydrogen production, CO₂ reduction, and organic synthesis due to its 2D structure and semiconducting properties. Its experimental band gap of ∼2.7 eV makes it active under visible light, facilitating photocatalytic reactions such as pollutant degradation, water splitting, and CO₂ conversion. To enhance its utility, strategies to lower GCN's band gap through doping are being actively explored. Transition metal and non-metal doping have been investigated to improve GCN’s light absorption and electronic properties. Non-metal dopants, such as nitrogen, chalcogens, and halogens, offer high electronegativity and covalent bonding potential, leading to improved visible light activity. Despite these advances, detailed understanding of dopants’ atomic-level effects remains limited, making computational studies like density functional theory (DFT) essential. This study examines the effects of main-group element doping on corrugated heptazine-structured GCN. Group III dopants increase the band gap by introducing electron deficiencies, while Groups IV–VII dopants generally reduce the band gap due to larger atomic sizes and weaker electron binding. Unique behaviors, such as high band gaps from nitrogen and fluorine doping, are attributed to their strong electronegativity and small radii. The findings reveal periodic trends in dopant effects on GCN’s band structure, providing insights into rational dopant selection to optimize its electronic properties. These results highlight the potential of tailored doping strategies to enhance GCN’s performance in photocatalysis, energy conversion, and electronic applications.

The rational selection of dopants for graphitic carbon nitride (GCN) is essential for tailoring its electronic properties, enabling advancements in photocatalysis, energy conversion, and electronics. Modifying the band gap, valence band edge (VBE), and conduction band edge (CBE) of GCN can enhance its light absorption capabilities, with narrower gaps improving visible light absorption and wider gaps increasing stability while lowering electron-hole recombination rates. Transition metals serve as effective dopants due to their distinct electronic configurations, allowing precise tuning of GCN's electronic structure. Early transition metals like titanium and vanadium reduce the band gap, enhancing conductivity for catalytic applications. Mid-transition metals such as iron and cobalt maintain structural integrity while optimizing electron mobility, ideal for stable catalytic systems. Late transition metals, including palladium and silver, provide highly conductive pathways with significant band gap reduction, suitable for high-performance catalysis and electronics. Strategic dopant selection, considering both functionality and sustainability, is vital for achieving high-performing, economically viable materials. Overall, the findings pave the way for tailored materials that address challenges in energy storage and environmental sustainability, highlighting the potential of doped GCN as a versatile candidate for innovative electronic and catalytic systems.

Catalysis is a fundamental process in chemistry and industry, driving the transformation of reactants into valuable products while minimizing energy input and waste generation. The quest for efficient and selective catalysts has led to the emergence of Cyclodextrin Metal-Organic Frameworks (CD-MOFs), a unique class of porous materials combining the advantages of cyclodextrins and metal-organic frameworks. CD-MOFs are gaining recognition for their distinctive capabilities in catalysis, offering benefits in terms of catalytic activity, selectivity, and sustainability. This paper presents an overview of current research on CD-MOFs in catalysis, emphasizing their application as hosts for catalytic materials and as catalysts themselves. The exploration includes studies on the confinement of redox-active monomers within CD-MOFs, resulting in controlled polymerization and enhanced electrical conductivity. Additionally, the paper discusses the encapsulation of photocatalysts in CD-MOFs, leading to stable and active hybrid materials for selective reduction processes. Further investigations delve into the nanoconfined environment of CD-MOFs, showcasing their ability to influence the regio- and stereoselectivity of photodimerization reactions. The synthesis of bimetallic nanoparticles within CD-MOFs is also explored, highlighting their potential in catalytic applications with enhanced stability and recyclability. Despite significant progress, research gaps persist, urging a deeper understanding of the structure-function relationships within CD-MOFs. Mechanistic insights into catalytic processes, scalable synthesis methods, stability under catalytic conditions, recyclability, and diversification of catalytic functions are identified as critical areas for future exploration. The paper concludes by envisioning the future of CD-MOFs in catalysis, emphasizing tailored structures for specific reactions, multifunctionality, sustainability, industrial integration, and the exploration of novel catalytic frontiers in challenging environments. The catalytic prowess of CD-MOFs holds the promise of contributing to sustainable and efficient chemical processes, ushering in a new era of innovation at the intersection of materials science and catalysis

The pressing environmental and energy challenges of today are driven by the depletion of fossil fuels and a surge in greenhouse gas emissions, particularly carbon dioxide. This situation highlights the critical need for sustainable energy solutions. While carbon capture and storage (CCS) technologies offer hope, they face economic challenges at the scale needed to significantly reduce carbon dioxide emissions. Biogas, produced mainly through the anaerobic digestion of various biomass sources like agricultural waste, municipal solid waste, and wastewater, presents a renewable alternative. Composed largely of methane and carbon dioxide, biogas can be upgraded to bio-methane, serving as an eco-friendly replacement for natural gas. Technological advancements, particularly in mem-brane separation, have made biogas purification more efficient and cost-effective. Anaerobic digestion, a key process in biogas production, breaks down organic matter into simpler compounds, which are then transformed into gases like methane and carbon dioxide. The composition of biogas depends on the feedstock and digestion conditions, with methane being a valuable but challenging component to separate due to its greenhouse gas properties. Several purification technologies have been developed, including absorption, adsorption, cryogenic separation, and membrane separation, each with unique benefits and drawbacks. Membrane separation is particularly promising for its environmental benefits and scalability. However, the biogas industry faces challenges, especially in developing countries, due to high costs and limited research and development. Overcoming these obstacles requires collaboration among various stakeholders. Looking ahead, the future of biogas technology is bright, with advances in membrane materials and integrated refining processes. In-tegrating biogas into sectors like waste management and agriculture is crucial for its development and for meeting global renewable energy goals. Biogas technology not only reduces dependence on fossil fuels but also plays a vital role in the transition to sustainable energy.

The increasing global demand for lithium, driven by its critical role in battery technology and nu-clear applications, necessitates efficient and sustainable extraction methods. Lithium, primarily sourced from brine pools, igneous rocks, and low-grade ores, is extracted through various tech-niques including ion exchange, precipitation, electrolysis, and adsorption. This paper reviews the current state of lithium extraction, focusing on the diverse methodologies employed to meet the burgeoning demand. Extraction methods exploit the solubilities of salts in brine water, employing techniques like liquid–liquid extraction. Despite the effectiveness, challenges arise from the similar characteristics of lithium and other constituents. Adsorption methods utilize lithium-selective ad-sorbents, requiring stability and adaptability under varying conditions. Membrane processes, such as electrodialysis and nanofiltration, offer the potential for energy-efficient, continuous lithium recovery. Electrochemical processes facilitate lithium intercalation and deintercalation, emphasiz-ing the need for electrode optimization. The review further delves into emerging technologies, like electrosorption and ionic pumps, highlighting their roles in lithium recovery. Challenges such as temperature dependency, impurity influence, and initial concentration are discussed, underscoring their impact on lithium recovery efficiency. Finally, this paper identifies research gaps and future directions, emphasizing the need for cost-effective, high-performance electrode materials and sys-tems. It concludes that enhancing lithium recovery and separation techniques, particularly in electrochemical Li extraction, is crucial for sustainable lithium production in response to global demand.

Cyclodextrin metal-organic frameworks (CD-MOFs) exhibit permanent porosity, which makes them an ideal adsorbent material. However, the instability of CD-MOFs in water limits their applications. To overcome this limitation, we encapsulated CD-MOFs in polyacrylonitrile (PAN) and polyvinylpyrrolidone (PVP) polymeric support to produce PAN/PVP/CD-MOF composite beads. Batch adsorption studies were performed to remove methyl orange in water. The results showed that low CD-MOF and intermediate PAN and PVP loadings led to the highest dye sorption capacities. The optimized bead formulation of PAN = 4.10 wt.%, PVP = 3.07 wt.%, and CD-MOF = 2.00 wt.%, resulted in a sorption capacity of 6.56 ± 0.59 mg/g. Molecular modeling showed that the MO is adsorbed on the surface of the CD-MOF, with an adsorption energy of -292.55 kcal mol-1. Overall, this study demonstrated that PAN/PVP/CD-MOF composite beads could be an excellent adsorbent for textile dye removal in water.

Lost circulation during oil well drilling is a critical challenge, resulting in significant financial losses and environmental concerns. This study explores the utilization of corn husks as an eco-friendly alternative to traditional chemical additives in drilling fluids. Corn husks were converted into a lost-circulation material (LCM) in the form of corn husk powder (CHP). Various tests were conducted to assess the impact of CHP on the physical and rheological properties, filtration behavior, and lost circulation performance of a water-based mud system. The effect of different CHP concentrations on these properties was evaluated. The results revealed that CHP can act as a rheological modifier, enhancing the apparent viscosity, plastic viscosity, gel strength, and yield point of the drilling mud in a nearly proportional manner with increasing CHP loading. This modification can optimize the mud's ability to suspend cuttings and transport them to the surface. CHP also contributed to controlling fluid loss by forming a filter cake on the borehole wall, effectively preventing the loss of drilling mud into the formation. Additionally, CHP exhibited promise in influencing mud cake thickness and controlling lost circulation, making it a reliable LCM for water-based drilling muds. Optimization showed that a 2.10 wt. % CHP loading resulted in a drilling mud that met the API RP 13B-1 standard for rheological and fluid loss properties. This demonstrates the potential of CHP as an eco-friendly and effective additive for improving drilling mud performance, enhancing drilling efficiency, and mitigating environmental concerns. Overall, this study underscores the significance of CHP as a promising and environmentally responsible solution in the oil well drilling industry.

The rising levels of carbon dioxide (CO2) in the atmosphere pose a significant environmental concern due to their contribution to global warming and climate change. Post-combustion carbon capture (PCCC) and storage is one method to minimize CO2 emissions. Cyclodextrin-based metal-organic frameworks (CD-MOFs) are potential adsorbents for PCCC because of their high CO2 sorption capacity. Here, we used Grand Canonical Monte Carlo (GCMC) simulations to investigate the adsorption of CO2 on various CD-MOFs. Results showed that CD-MOFs are selective for water and CO2 molecules over nitrogen and oxygen molecules. The Rb-CD-MOF had the highest CO2 uptake, while K-CD-MOF exhibited the highest isosteric heat of adsorption. However, all CD-MOFs had much higher water sorption capacity than CO2, and Cs-CD-MOF had the highest water uptake. Moreover, our results showed that CD-MOFs had lower CO2 adsorption capacity when combined with other gases than under pure gas conditions. We also discovered that hypothetical transition metal – based CD-MOFs behave similarly with alkaline metal – based CD-MOFs during combined gas sorption studies, suggesting that enhancing the ligand-coordination bond may have only a minimal effect in the hydrophobicity of the CD-MOFs. Other strategies for endowing hydrophobicity to CD-MOFs must be sought if it were to be deployed as an adsorbent for post-combustion carbon capture. Overall, this study underscores the importance of considering other gases in the performance assessment of MOFs for CO2 capture.

Diesel oil contamination is a threat to environment and human health. Many technologies have been developed to address this issue; however, they are costly to be deployed in real-world oil remediation. Adsorption remains to be one of the most economical methods to remove oil from water. Here, we used banana peel biochar (BPBC) immobilized in teabags as an adsorbent for the removal of diesel oil in water. We investigated the adsorption behavior of BPBC under different conditions, examining the influence of adsorbent loading, pH, salinity, and contact time on its efficiency for removing diesel oil in water. Our results show that the sorption capacity of BPBC is significantly affected by the amount of adsorbent used. Lower biochar loadings enhance the sorption capacity due to greater surface area accessibility, while higher loadings lead to decreased efficiency due to pore blockage and reduced surface exposure. Interestingly, the pH of the solution was found to have minimal impact on the sorption process. This is attributed to diesel oil’s hydrophobic and non-polar nature, which leads to its interaction with BPBC being predominantly governed by hydrophobic forces instead of pH-sensitive electrostatic interactions. Salinity emerged as a crucial factor in the adsorption process. An increase in salinity enhances the sorption capacity, likely due to the “salting-out” effect, where higher salt concentrations decrease the solubility of diesel oil, promoting its adsorption onto the biochar surface. Furthermore, the study highlights the importance of contact time, with longer exposure resulting in increased sorption capacity. This trend is explained by the adsorption kinetics, initially characterized by rapid adsorption, followed by a slower, progressive occupation of the biochar’s adsorption sites. The kinetic analysis of the process suggests that the pseudo-second-order model is more suitable, indicating a chemisorption mechanism. The Harkins–Jura isotherm model was identified as the best fit for explaining the isotherm behavior, owing to its capacity to account for the heterogeneous nature of the biochar surface and the formation of multiple adsorbate layers. The optimum conditions for maximum diesel oil removal are as follows: BPBC loading of 0.50 g, a solution pH of 5.00, a salinity concentration of 12,656.57 mg/L, and a contact time of 240 min. Under these conditions, BPBC exhibited an adsorption capacity of 19.04 g/g. In summary, our research establishes BPBC, particularly when contained within teabags, as an efficient and practical adsorbent for diesel oil removal in water. Its effectiveness, superior to other biochar, is mainly due to its porosity and hydrophobic properties. These findings not only enhance our understanding of BPBC’s adsorption capabilities but also underscore its potential for environmental remediation.

Metal-Organic Frameworks (MOFs) have gained traction as an adsorbent due to their high surface area and porosity. MIL-101(Fe), a MOF that has been used for removing dyes in water by adsorption, faces the problem of being inseparable from water after use. To get around this difficulty, MIL-101(Fe) was incorporated into composite beads consisting of polymers Chitosan (CS), and Polyvinyl Alcohol (PVA) crosslinked with Glutaraldehyde (GLA) to remove Methyl Orange (MO) from water. The resulting CS/MIL-101(Fe)/PVA beads were optimized based on the right combination of synthesis parameters that gave the highest percent MO removal. It was found that the maximum MO removal can be achieved by beads made of 1500 ppm MIL-101(Fe), 2.0 % PVA, crosslinked in 2.5% GLA. Using FTIR analysis and SEM imaging, the beads exhibited favorable properties for adsorption, as shown by their coarse and porous structure. The beads proved viable for adsorption, exhibiting a percent MO removal of 69.62% upon validation.

Cyclodextrin metal-organic frameworks (CD-MOFs) are synthesized from green precursors, making them an ideal material for green adsorbents. However, CD-MOFs are unstable in water, thus limiting their applications. Here, we report encapsulating CD-MOFs in polyacrylonitrile (PAN) and polyvinylpyrrolidone (PVP) polymeric support to produce PAN/PVP/CD-MOF composite beads. Batch adsorption studies showed that high dye adsorption capacities could be obtained at intermediate PVP, high PAN, and low CD-MOF loadings. Maximum MB and CR sorption capacities under optimum bead formulation: PAN = 6.96 wt.%, PVP = 2.20 wt.%, and CD-MOF = 2.88 wt.%. The optimized composite beads have a sorption capacity of 37.40 mg/g for MB and 18.42 mg/g for CR. We showed that PAN/PVP/CD-MOF composite beads could be an excellent adsorbent for textile dye removal in water.

Detection of heavy metals in water has long been a key area of study due to the adverse health effects these substances may bring. Multiple methods of detecting heavy metals have already been established. Though these methods are highly selective and can detect heavy metals in trace amounts, they commonly require specialized equipment. Thus, producing an inexpensive, reliable, and convenient sensor that could be used for point-of-need applications is of great interest. This study focuses on fabricating paper-based silver nanoparticle (AgNP) sensors for the smartphone-based colorimetric detection of Cu2+ ions in water. Polymer-decorated AgNPs functionalized by chitosan, glutaraldehyde, and polyethyleneimine were used as the main sensing mechanism for the paper-based sensors. Various fabrication methods were tested, and the optimal fabrication method was through the rectangular soak method with a total of 5 coatings as it produced the most uniform sensors. The calibration curve was studied over concentrations from 0.5 mM to 50 mM of Cu2+ across multiple parameters. It was found that there was a linear correlation between the Euclidean distance measured in reference to the blank filter paper against the concentration of copper in the analyte. The calibration curve exhibited a dynamic linear range between 2 mM to 28 mM of Cu2+ with R2 = 0.99789. The LOD and LOQ were reported at 94.9438 ppm and 316.4793 ppm, respectively. Lastly, selectivity studies were also performed to determine the sensor’s response to other metal ions. It was found that the response of the sensor to Cu2+ was significantly different from those elicited by Ni2+, Cd+, Mn2+, Ca2+, Mg2+, Sn2+, K+, Cr3+, Al3+, Ba2+, Na+, Zn2+, Fe3+, and Fe2+. The study demonstrated its strong potential as rapid on-site detection method for Cu (II) in industrial wastewater.

Here, banana peel biochar (BPBC) generated from discarded saba banana peels powder (SBPP) was utilized as an adsorbent in this study to remove diesel oil from water. The BPBC was synthesized using a slow pyrolysis method and characterized using SEM, EDX, FTIR, DSC, TGA, BET, contact angle analyzer, and XRD. The results showed that BPBC exhibited high porosity, thermal stability, and hydrophobic character, making it a promising adsorbent for oil-water separation and environmental remediation. The adsorption capacity of BPBC for diesel oil removal was examined in terms of adsorbent dose, pH level, salinity, and contact time. Increasing the BPBC dosage, contact time, and salinity significantly enhanced the sorption capacity, however, pH variations had no significant effect on adsorption. Adsorption parameters were correlated using a reduced cubic model, and an adsorbent dose of 2.50 g, pH of 7.00, salinity of 44,999.95 mg/L, and contact duration of 240 minutes were found to be optimal, producing a sorption capacity of 5.3352 g diesel oil/g adsorbent. The adsorption process was characterized by the first-order kinetic model. The creation of multilayer adsorption on the BPBC surface was confirmed by the BET isotherm. Adsorption characterization revealed changes in the surface morphology, elemental analysis, and functional groups of BPBC after adsorption. SEM revealed occupied surface pores, and EDX analysis verified an increase in carbon content. The presence of adsorbed diesel oil molecules on the BPBC surface was detected by FTIR analysis, which exhibited changes in peak appearance and functional group shifts. Overall, this study presents an adsorbent derived from waste material for diesel oil adsorption, which is useful for remediating oil spills and for wastewater treatment.

Enhanced oil recovery (EOR) relies on the use of surfactant to flood the wellbore and thus extract the oil from the rocks. However, current surfactants used for EOR are non-biodegradable and are made from toxic chemicals. Here, we report the potential of soybean lecithin as a biobased surfactant for enhancing oil recovery by stabilizing oil-in-water (O/W) emulsions. Our findings show that pH has a significant impact on stability, with lower pH levels leading to improved stability. Salinity affects stability, but soybean lecithin shows minimal sensitivity to salt concentration. Surfactant loading also plays a crucial role, with higher concentrations causing instability. The optimized operating parameters for soybean lecithin are determined to be at pH = 4, salinity = 84,171.08 ppm, and surfactant loading = 4.48 wt.%. Comparative evaluation reveals that soybean lecithin performs competitively, outperforming certain commercial surfactants in terms of emulsion stability in oil phase. The solubilization ratio of oil (SRo) values are lecithin = 3.2219, CAPB = 0.7028, CTAC = 11.1044, NP10EO = 11.1570, and SLES = 11.7067. Utilizing soybean lecithin as a biobased surfactant in enhanced oil recovery offers a sustainable and environmentally friendly alternative with potential economic advantages. Further research can focus on optimizing formulation and exploring synergies with other additives.

There is a rising concern over the presence of heavy metals in water due to their toxicity. Although current methods of heavy metal detection are accurate, highly selective, and sensitive, they also require tedious preparation procedures, expensive equipment, and professional assistance. Hence, there is a need to develop a fast, portable, reliable, and inexpensive method that enables on-site detection of heavy metals. Herein, polymer-decorated AgNPs were used as an assay-based nanosensor for detecting copper ions in water. AgNPs were decorated with chitosan crosslinked with polyethyleneimine using glutaraldehyde to make them more stable. The composition of the PD-AgNPs was optimized by varying the CS, GLA, and PEI concentrations using a Box-Behnken design. Response surface analyses showed that a reduced cubic model is sufficient to model and predict the Φ and LOD of PD-AgNPs with 95 % confidence. Numerical optimization revealed that the optimum formulation comprises 1.1642 wt% CS, 0.8298 wt% GLA, and 1.3687 wt% PEI. The predicted Φ = 82.5559 and LOD = 2.1566 mg/L agree well with our validation experiments (actual Φ = 82.9540 and LOD = 2.2498 mg/L).

Recent advancements in particle dispersion modeling have significantly enhanced our understanding and capabilities in predicting and analyzing the behavior of particulate matter in various environments. However, this field still confronts several research gaps and challenges that span across scientific inquiry and technological applications. This paper reviews the current state of particle dispersion modeling, focusing on various models such as Lagrangian, Eulerian, Gaussian, and Box models, each with unique strengths and limitations. It highlights the importance of accurately simulating multi-phase interactions, addressing computational intensity for practical applications, and considering environmental and public health implications. Furthermore, the integration of emerging technologies like machine learning (ML) and artificial intelligence (AI) presents promising avenues for future advancements. These technologies could potentially enhance model accuracy, reduce computational demands, and enable handling complex, multi-variable scenarios. The paper also emphasizes the need for real-time monitoring and predictive capabilities in particle dispersion models, which are crucial for environmental monitoring, industrial safety, and public health preparedness.

Pneumatic conveying is a vital technology for delivering bulk solids, powders, and granular materials in various industries. Significant advances in pneumatic conveying technology have occurred in recent years, spurred by the demand for sustainable and energy-efficient industrial processes. This paper explores the current advances in pneumatic conveying technology and their implications for the industry. First, the principles of pneumatic conveying are discussed. Then, two significant advances in pneumatic conveying technology are highlighted. Schenck Process, for example, has created the Enhanced Dilute Phase Pneumatic Conveying (EDIP) system, the E-Finity continuous dense phase system, and high-pressure systems utilizing Lontra’s LP2 Compressor Blower. Second, Palamatic Process provides dense-phase vacuum conveying cyclones as well as powder pumps for nonabrasive dense-phase vacuum conveying. Several research gaps in pneumatic conveying technology are identified in the paper, including the integration of artificial intelligence and machine learning, the optimization of multiphase flow behavior, energy efficiency and sustainability, material degradation, and particle damage, handling of cohesive and difficult-to-convey materials, scale-up and design optimization, and real-time monitoring and control systems. The future outlook highlights the potential of sustainable practices to advance pneumatic conveying technology further. The integration of these technologies can lead to improved performance, energy efficiency, and sustainability in pneumatic conveying systems.

Using environmentally friendly solvents for liquid–liquid extraction offers a promising avenue for promoting sustainability in various industries. Green solvents, including ionic liquids, deep eutectic solvents, supercritical fluids, and bio-based solvents, offer several advantages compared to the traditional solvents of the present time. These solvents possess low toxicity, biodegradability, and reduced environmental impact, making them highly desirable for liquid–liquid extraction processes. Through careful adjustments in composition and physicochemical properties, these solvents can be customized to achieve efficient and selective extraction of desired compounds. Additionally, recent advances in green solvents often contribute to improved energy efficiency, reduced waste production, and the potential for developing novel products with unique characteristics. By embracing green solvents for liquid–liquid extraction, industries can actively contribute to sustainable development, minimize environmental harm, and support the transition towards an eco-friendlier future.

In recent years, metal–organic frameworks (MOFs) have gained a lot of attention from researchers because of their potential applications in gas separation, storage, catalysis, as well as sensing. In spite of this, further development for the actual utilization of this material is hindered mainly by its lack of ability to withstand harsh conditions. Advances over the past few years have made it possible to create MOFs with greater variability and structural properties that are more robust in nature. This paper focuses on the development of synthesis and design of MOFs so as to attain robust frameworks that are relevant for various applications. Finally, this paper also discusses the possible future directions of study for synthesizing highly durable MOFs.

SARS-CoV-2 caused the ongoing COVID-19 pandemic, and only a few treatment options are available to mitigate its impact on human health. Hence, there is a need to discover drugs that could be used to treat COVID-19. Several studies have already reported the repurposing of existing drugs to inhibit the receptor-binding domain of SARS-CoV-2. However, the emergence of COVID-19 variants may render current drug candidates ineffective. Here, we report the structure-based drug screening of the DrugBank database against the wild-type, B.1.1.7, B.1.351, and P.1 variants of SARS-CoV-2. Our study revealed that Salmeterol, Abediterol, and Lysophosphatidylglycerol are among the top candidates against all four variants. Furthermore, we showed that Salmeterol forms a stable complex with the receptor binding domain of SARS-CoV-2 variants. Further studies are needed to evaluate the clinical relevance of the drug candidates discovered. Nevertheless, this study provides insight into computational drug design that works against multiple variants of SARS-CoV-2.

Reactive distillation (RD) combines chemical reactions and separation in a single unit essential to equilibrium-limited reactions. This new technique encompasses multiple advantages over traditional processes, including lower operating costs, increased thermal energy efficiency, high product selectivity, high purity percentage, and lower environmental impact. This paper provided an overview of the features, industrial applications, and industrial perspective of advanced reactive distillation technologies (ARDTs). This study focused on five under-development ARDTs: reactive dividing wall column (R-DWC), reactive high-gravity distillation (R-HiGee), reactive heat-integrated distillation column (R-HIDiC), catalytic cyclic distillation (CCD), and membrane-assisted reactive distillation (MA-RD). The primary drivers for new RD applications are reduced number of vessels, reduced residence time and holdup volume, increased mass and heat transfer, overcoming azeotropes, and prefractionation or impurity removal. ARDT’s potential has yet to be studied, and research remains active to improve it further by investigating other RD technologies, simulation, and optimization techniques.

Particle characterization is critical in industries that are influenced by particle size distribution. Understanding particle behavior is crucial for product quality control and manufacturing process optimization. Particle characteristics significantly affect material performance and properties. This review paper examines the importance of particle characterization in many industries and focuses on particle size and shape measurement. This paper begins by delving into particle size and size distribution analysis, emphasizing the impact of particle size on material properties and the many methodologies used for particle size analysis. This paper then examines particle shape characterization and its impact on material characteristics. It gives an overview of particle characterization techniques and the criteria for selecting the best technique for a given sample. Particle characterization in ceramics, food, cosmetics, medicines, and metallurgy are also thoroughly discussed. Overall, this work emphasizes the importance of particle characterization in numerous industries and provides insights into particle size and shape measurement.

Metal–organic frameworks (MOFs) are a class of material made up of metal ions or clusters and organic linkers. Cyclodextrin-based MOFs (CD-MOFs) are gaining popularity among MOFs due to their unique features, such as high porosity, permanent porosity, and biocompatibility. This paper focuses on recent advances in synthesizing CD-MOFs and their water stability. We highlight the difficulties involved in CD-MOF synthesis and the strategies explored to increase water stability. The advances in CD-MOF synthesis and characterization open new avenues for tailoring crystal growth processes and properties, with potential applications spanning areas such as catalysis, drug delivery, and environmental remediation. The combination of innovative synthesis techniques, systematic parameter exploration, and functionalization strategies heralds a promising era for crystal growth research and applications. Finally, we discuss the current research gaps and the future outlook of CD-MOF research. Overcoming obstacles in the synthesis and water stability of CD-MOFs is crucial for their practical applications.

Carbon dioxide (CO2) capture and separation constitute an important field of research as we seek to reduce the effects of climate change. Because of their porosity, resilient crystallinity, high adsorption capacity, and affinity for CO2, cyclodextrin-based metal-organic frameworks (CD-MOFs) have emerged as attractive materials for carbon capture. This paper gives an overview of CD-MOFs and their applications in CO2 capture and separation. Several studies have been conducted to synthesize and characterize CD-MOFs for CO2 capture. The causes of the high binding affinity of CO2 in CD-MOFs were discovered through mechanistic studies on CO2 adsorption. Furthermore, CD-MOF modifications have been carried out to improve the sorption capacity and selectivity of CO2 adsorption. Meanwhile, several researchers have reported using CD-MOFs for gaseous CO2 membrane separation. This paper also highlights the current gaps in CD-MOF research and future outlooks in carbon capture and separation using CD-MOFs.

Recent advances in particle fluidization focus on improving the efficiency and control of various processes used in different industries. New technologies, such as spouted beds and circulating fluidized beds, have emerged to improve particle distribution. Additionally, the integration of computational fluid dynamics (CFD) simulations and other advanced technology leads to the effective observation of particle fluidization behavior and up-scaling of fluidized beds. In this paper, we aim to give a thorough analysis of studies from various research groups in the field of particle fluidization. The fundamentals of fluidization, recent advanced techniques, models and simulations, and application of the process will be emphasized. Moreover, it discusses various aspects regarding the challenges and opportunities of the fluidization process. Advances in particle fluidization hold great promise for improving industrial processes and enabling technologies in various industries.

Plastic waste has increased worldwide due to the steady rise in plastic consumption. Several strategies were developed to mitigate plastic waste. Among these methods, pyrolysis is a promising technology for converting plastic waste into valuable products. This paper discusses the latest advancements in the pyrolysis of three common types of plastic waste: polyvinyl chloride (PVC), polypropylene (PP), and polystyrene (PS). The challenges associated with the pyrolysis of these plastics are highlighted, and an outlook on the future of research on pyrolysis is given. Overall, this review provides valuable insights into the current state of research on the pyrolysis of PVC, PP, and PS. This has implications for advancing pyrolysis technology to contribute to a more sustainable and circular economy.

Distillation is widely recognized as the preferred method for separation due to its operational and control benefits. Traditional distillation processes, however, cannot successfully separate azeotropic mixtures with near boiling points. Numerous special distillation processes have been developed to address this limitation. Extractive distillation, in particular, has gained significant popularity in the chemical, petrochemical, pharmaceutical, and refining industries. This review examined the state-of-the-art advances in extractive distillation. The importance of the proper selection of a solvent was discussed. Several configurations of extractive distillation processes were presented. Additionally, alternative extractive distillation systems have been elaborated. However, significant research gaps remain, such as the need for an exhaustive investigation of various control variables, the impact of certain entrainers on distillation processes, and cost comparisons across specialized distillation systems. Furthermore, process intensification strategies require additional research to solve complexity and operability issues. The integration of energy-efficient technologies, developments in renewable energy consumption, and the development of cost-effective reactive or split distillation columns will shape the future of distillation operations. These advances will help the chemical process sector achieve improved energy efficiency, lower environmental impact, and increased sustainability.

Recent advances in nucleation and crystal growth have revolutionized our understanding and control of crystallization processes. This paper highlights key developments in this field and the processes and technologies involved in its continuous growth. Advanced computational models have allowed for precise prediction of nucleation rates and crystal morphologies, facilitating the rational design of materials with desired properties. Innovative strategies have also emerged, enabling enhanced control over crystal growth kinetics and crystallographic orientations. Process intensification strategies, including microreactors and membrane crystallization, enhance nucleation rates and crystal growth. Advances in the potential-driven growth of metal crystals from ionic liquids, including protic ionic liquids (PILs) and solvate ionic liquids (SILs), are discussed. Lastly, current research gaps and future prospects in the field of nucleation and crystal formation are highlighted. The integration of cutting-edge experimental techniques, computational modeling, and novel strategies will drive the understanding of nucleation and crystal growth processes, allowing for the development of materials with tailored properties and enhanced functionality across multiple disciplines.

Heavy metal contamination in groundwater has become more prevalent due to the leaching of toxic wastes from various anthropogenic sources. When ingested, this can cause serious ill effects detrimental to human health. Hence, there is a need to monitor the levels of heavy metals in various water sources to ensure that they are fit for human consumption. Standard detection methods such as AAS and ICP-MS are typically used for quantifying the concentration of heavy metals. However, these require expensive equipment, not to mention the need for a trained and highly-skilled technician to operate the equipment. Nanosensors offer a low-cost alternative to these methods. By utilizing the localized surface plasmon resonance (LSPR) and the properties of noble metal nanoparticles such as AgNPs, the colorimetric detection of heavy metals is made possible. Herein, we report the synthesis of humic-acid-functionalized silver nanoparticles (HA-AgNPs) using a borohydride reduction approach as a colorimetric nanosensor for Ni (II) detection in aqueous solutions. Humic acid acts as a capping agent that stabilizes the AgNPs in the colloidal mixture while providing functional groups for the detection of heavy metals. The synthesized HA-AgNPs had an average hydrodynamic diameter of 42.9 nm, a polydispersity index of 0.438, and an LSPR peak of 400.6 nm. The nanosensor could be used for the colorimetric detection of Ni (II) ions within the linear range of 0.15–0.40 mM Ni (II) with a limit of detection (LoD) of 2.35 mg L−1. The HA-AgNPs were shown to be selective when detecting Ni (II) ions; common metals in water such as Ca (II), Mg (II), Al (III), Zn (II), Na (I), and K (I) did not interfere with Ni (II) detection. As such, HA-AgNPs can be used as reliable and environmentally friendly colorimetric nanosensors for the rapid and point-of-need detection of Ni (II) ions in aqueous solutions.

Cyclodextrin metal–organic frameworks (CD-MOFs) have a high surface area and unique coordination chemistry that enable them to be used as a carrier material for various materials. However, it is unstable in water, limiting its application in aqueous solutions. Here, we report the application of CD-MOFs in treating cationic and anionic dyes in water for the first time by forming a composite with polyacrylonitrile (PAN) and polyvinylpyrrolidone (PVP) to form composite beads. The composition of the composite beads was optimized through a Box-Behnken design of experiments. The optimum composition of PAN = 5.91 wt%, PVP = 1.89 wt%, and CD-MOF = 2.68 wt% yielded a CV and BB sorption capacities of 50.8109 ± 0.0634 mg/g and 28.5583 ± 0.1296 mg/g, respectively. The composite beads were characterized using SEM, EDX, and FTIR. We showed that CD-MOFs could be used as an adsorbent for wastewater treatment.

Detecting heavy metals in water is necessary to ensure its safety. However, current detection methods require costly equipment, making heavy metal monitoring challenging. Colorimetric detection of heavy metals using silver nanoparticles (AgNPs) relies on the optical spectra changes when it detects an analyte. We have previously shown that a colorimetric assay comprised of humic acid - functionalized AgNPs (HA-AgNPs) can selectively detect copper ions in water. Here, we investigated the effect of humic acid concentration on the stability of HA-AgNPs and their ability to detect copper. HA acts as a capping agent around the AgNPs, making them stable even for up to 48 days of storage in both ambient and cold storage environments. At critical HA concentrations of 5 mg L-1 and beyond, the changes in the optical properties of the HA-AgNPs are linearly dependent on Cu (II) concentration. Below this critical HA concentration, Cu (II) sensing is futile. The most stable HA-AgNPs is at HA = 25 mg L-1 based on zeta potential measurements, while the best assay for colorimetric copper (II) detection is at HA = 50 mg L-1, giving the lowest detection limit of 4.35 mg L-1 and R2 = 0.999 within a dynamic linear range of 0.00 to 1.25 mM Cu (II). We have shown that the ligand concentration is critical for achieving stable AgNP assays for heavy metal detection.

Most plastics on the market are based on petroleum. Because of their chemical inertness and durability, plastics are essentially non-biodegradable. Previously, plastic waste management typically focused on reusing and recycling it into valuable products. However, virgin plastic resins and their chemical processing to produce new plastic products are more economical than recycling. As such, most plastic waste ends up in dumpsites and sanitary landfills. Waste-to-energy conversion is a viable solution to the alarming rise of plastic proliferation in the Anthropocene age. The conversion of plastic wastes into valuable products such as liquid oils, fuel gas, and solid chars through a high-temperature pyrolytic process could lead to a source of alternative fuels. In this paper, the application of the pyrolysis process to polyethylene is discussed. Several process parameters were seen to influence the characteristics of the final pyrolysis products, such as the operating temperature, type of catalyst, and presence of agitation. Optimizing these key parameters is essential for the industrial adoption of the pyrolysis of plastics.

This paper investigates the general trends in the structural, electronic, and optical properties of anatase TiO2 photocatalysts co-doped with transition metals and sulfur. We attempt to rationalize co-dopant selection by employing molecular dynamics and density functional theory calculations. The structural properties of the first-row transition metal co-dopants were determined. TM-TiO2 and TM/S-TiO2 were structurally stable, with minimal changes in their lattice parameters, cell volume, density, and XRD profiles relative to pristine TiO2. However, only Fe and Mn among the first-row transition metals are thermodynamically favorable, i.e., their substitutional energies are lower relative to pristine TiO2. Intermediate energy levels (IELs) are formed during the co-doping of transition metals and sulfur on TiO2. In particular, Fe and Co form two IELs between the VBM and CBM, resulting in improved optical properties, especially in the visible-light region, which are mainly attributed to the unsaturated nonbonding transition metal d orbitals and the half-filled Ti–O bonding orbitals. On the other hand, Cu and Ni form three IELs close to each other due to the M–O anti-bond orbitals, half-filled p orbitals of S, and the Ti–S anti-bonding orbitals. These IELs in co-doped systems can serve as “stepping stones” for photogenerated electrons, facilitating easier charge mobility. Among the investigated co-doped systems, Fe/S-TiO2 was shown to be the most promising for photocatalytic applications.

Titanium dioxide has long been investigated for its excellent photocatalytic activity under UV illumination. However, its sluggish activity under visible-light illumination remains a challenge. Doping titanium dioxide with transition metals and non-metals was done in the past to improve its catalytic properties, yet the expensive synthesis protocols involved in doping titanium dioxide limit its applications. Herein, a one-pot approach to doping titanium dioxide nanotubes was used. In particular, the Cu/S-TiNTs electrode was synthesized by electrochemical anodization using an electrolyte solution spiked with CuSO4. The resulting nanostructured Cu/S-TiNTs electrode was used as a photoanode for the photoelectrocatalytic degradation of synthetic dye solution (50 ppm C.I. Basic Blue 9 in deionized water) in a 125-mL reactor. The Cu/S-TiNTs were shown to be catalytically active under both ultraviolet and visible light. Co-doping pristine TiNTs with copper and sulfur significantly enhanced the photoelectrocatalytic degradation rates of BB 9. Cu/S-TiNTs achieved a 67% faster degradation rate (k1 = 1.5054 ± 0.0193 × 10−2 min−1) compared to pristine TiNTs (k1 = 8.9106 ± 0.0647 × 10−3 min−1) under visible light illumination. At the end of 60 min, the Cu/S-TiNTs were able to degrade 59.69% of the initial dye concentration under visible light, compared to 45.43% degradation using pristine TiNTs. The synthesized photoanodes demonstrated good reusability and stability after several cycles of use, even at a low dopant loading. These findings bring us closer to the possibility of large-scale adaptation of advanced oxidation processes, such as photoelectrocatalysis, for environmental remediation of recalcitrant organic compounds in wastewater.

Farmers widely use malathion, even in households, and significant amounts seep through groundwater and effluent wastewater. It is toxic to animal and human life. Hence, its removal from wastewater is necessary. Here, we report the applicability of hydroxyapatite as a catalyst in the UV-light-assisted degradation of malathion. The hydroxyapatite was synthesized via calcination from milkfish (MF1000) and cream dory (CD1000) bones. FTIR and PXRD results proved the successful synthesis of hydroxyapatite from the fish bones. SEM images revealed that the synthesized hydroxyapatite varies in size from 19 to 52 nm with a pseudo-spherical morphology. Degradation efficiency increases when catalyst dosage or irradiation time are increased. Degradation efficiencies range from 8.18% to 67.80% using MF1000 and from 20.50% to 67.90% using CD1000. Malathion obeys first-order kinetics with a kinetic constant up to 7.0289 × 10−3 min−1 for 0.6 g catalyst loading. Meanwhile, malathion obeys second-order kinetics with a kinetic constant up to 1.1946 × 10−3 L min−1 mg−1 for 0.6 g loading. Across all catalyst loadings, CD1000 has faster degradation kinetics compared to MF1000. The results of this study validate that the calcined fish bones are effective in removing malathion in an aqueous solution, which significantly lessens the detrimental effects of pesticides in groundwater and wastewater.

Metal-organic frameworks (MOFs) are an evolving class of crystalline porous materials made of organic linkers and metallic nodes. The rich chemistry of MOFs allows them to have an almost infinite number of possible structures. Consequently, they have been of great interest because of their highly tunable properties and unique features, such as their high porosity, high surface area, structural stability, structural diversity, and tailorability. These enable MOFs to be a flexible catalytic platform for photocatalytic applications. Thus, this paper discusses the opportunities of MOFs for use in catalysis. In particular, the use of metal-organic frameworks as a photocatalyst is briefly discussed. Specifically, MOFs can be used as a photocatalyst for carbon dioxide reduction (CO2RR), nitrogen reduction reactions (NRRs), and water-splitting reactions (HERs and ORRs). However, using MOFs as catalytic platforms has some challenges that must be addressed to achieve commercialization. Therefore, this paper also discusses some prospects of designing MOFs for their specific catalytic applications to improve their catalytic properties and enhance selectivity. More importantly, an outlook is also provided on how MOF catalysts can further be developed to enable other catalytic reactions. Overall, MOFs have great potential as a photocatalytic material, provided they are uniquely designed to suit their intended applications.

The enormous environmental impact of the excessive use of the fossil fuels has prompted researchers to search for an environmentally friendly energy source. In this study, buri palm leaves was utilized to produce biochar and bio-oil using slow pyrolysis. The effects of temperature (T), of (300, 500 and 700 °C) and residence time (RS) of (30, 60 and 90 mins) to pyrolysis products were investigated using a self-design fixed bed reactor. Particularly, the effects of these parameters on the proximate analysis, ultimate analysis, and calculated heating value of biochar were conducted. The results showed that the highest yield in biochar of 68% (T = 300 °C, RT = 90 min) while the bio-oil yield of 46% (T = 500 °C, RS = 90 min) was obtained. It was observed that biochar products increased with residence time but decreasing with the temperature while the bio-oil recovery is as both parameters increase. In addition, fixed carbon, volatile matter, ash, carbon, hydrogen and the higher heating value of biochar were significantly affected by the residence time. The calculated lowest and highest higher heating values of biochar were 16.93 MJ/kg at 300 °C for 30 mins and 28 MJ/kg at 700 °C for 30 mins respectively. Finally, this study presented the viability of buri palm leaves as potential option for sustainable alternative energy sources.

In this study, novel potential inhibitors of SARS-CoV-2 variants were designed de novo using generative neural networks. The top-performing ligand based on docking performance and ADMET profiles was CID #526. It forms several hydrogen bonds with wild-type SARS-CoV-2, indicating its potential as an inhibitor of the receptor-binding domain. Mutated variants of the RBD also showed good interactions with CID #526, implying the inhibitory properties of our top-performing compound against various variants. Molecular dynamics analysis showed a stable ligand–RBD complex. CID #526 can easily be synthesized using low-cost starting molecules. Overall, the generated ligands merit further investigation to determine their efficacy and safety as a treatment for COVID-19.

Here, potential inhibitors of the SARS-CoV-2 papain-like protease (PLpro) are reported. A drug molecule (PLpro-50), designed de novo using generative neural networks, interacts with PLpro via hydrogen bonding, forming a salt bridge, and π–π stacking, making it a promising drug against PLpro. PLpro-50 has an excellent ADMET profile with good absorbability, high clearance, and low toxicity. Molecular dynamics analysis revealed the stability of the receptor–ligand complex of PLpro-50 and PLpro. An organic retrosynthesis study showed the feasibility of PLpro-50 to be synthesized using low-cost starting materials. Further studies should be performed to determine whether the determined drug candidates are efficacious in treating COVID-19 infections.

Emerging pollutants such as diclofenac (DFC) are a cause of concern worldwide due to their persistence in the environment. Advanced oxidation processes (AOPs), such as Fenton-like processes, are among the emerging technologies for wastewater treatment due to their capability to completely degrade even recalcitrant pollutants. However, previously-investigated catalysts are expensive. Here, we report the performance of the synthesized iron-impregnated biochar derived from mussel shells (Fe@MSBC) as a catalyst for DFC degradation in water using sodium percarbonate (SPC) as an oxidant. SEM, EDX, FTIR, DSC, and TGA confirmed the successful synthesis of Fe@MSBC. A Box-Behnken design of experiments was used to investigate the effects of Fe@MSBC catalyst loading, initial DFC concentration, and SPC concentration on the removal of DFC. Here, we found that a reduced cubic model can adequately model these effects. Lower Fe@MSBC catalyst loadings, higher initial DFC concentrations, and SPC concentrations near 1.5 mmol L-1 SPC yielded higher DFC degradation. Maximum DFC removal can be achieved at 15.1831 mg L-1 Fe@MSBC catalyst loading, 60 mg L-1 initial DFC concentration, and 1.5228 mmol L-1 SPC concentration. 98.2872 % ± 0.0278 % DFC can be degraded under these conditions. These results show the exceptional degradation efficiency of Fe@MSBC in degrading DFC. These findings could help our search for novel materials to degrade emerging pollutants in wastewater, leading to a safer wastewater effluent to be released into the environment.

In this study, the effectiveness of novel nanocomposite-coated filters consisting of biochar (BC) functionalized with sodium alginate (SA) and poly (vinyl alcohol) (PVA) was investigated for methylene (MB) blue removal. The filters were fabricated via a dip-coating method and SEM and FTIR spectroscopy confirmed the successful coating of the filters. The impact of the nanocomposite formulation and the operating parameters (initial pH and MB concentration) on the performance of the coated filters were studied. A nanocomposite composition consisting of 1.0 wt.% SA, 2.0 wt.% PVA, and 1000 ppm BC were found to be optimum, reaching as high as 96.51% MB removal. The fabricated filters were determined to be robust over a wide range of pH and initial MB concentrations. The Sips isotherm model proved to be the best-fit model for MB adsorption, where chemisorption dominates at low MB concentrations, while physisorption dominates at high MB concentrations. The filters have a maximum sorption capacity of 54.5198 mg g-1 and showed good reusability. Overall, our synthesized SA/PVA/BC-coated filters can be used to effectively remove dyes in wastewater over a wide range of operating conditions.

Photoelectrocatalysis has emerged as a promising technology to degrade recalcitrant pollutants such as textile dyes in wastewater completely. Titanium dioxide is typically used as a photocatalyst, but its wide bandgap constrains its use to the use of ultraviolet light. To extend its use to the visible-light region, we doped titanium dioxide nanotubes with iron and sulfur. We used them as a photoelectrode for the photoelectrocatalytic degradation of a model pollutant – phenol red. Response surface methodology using a Box-Behnken design of experiments was used to investigate the effects of initial dye concentration, applied potential, and dopant loading on phenol red degradation kinetics. Statistical analysis showed that our reduced cubic model adequately correlates these parameters. The fastest dye degradation rate was achieved at the optimized conditions: initial phenol red concentration = 5.0326 mg L-1, applied voltage = 29.9686 V, and dopant loading = 1.2244 wt.%. Complete degradation of phenol red may be achieved after 11.77 hours of treatment under the optimized conditions in a batch reactor. Our model's robustness enables it to be used for process modeling and a basis for designing scaled-up photoelectrocatalytic reactors.

Photoelectrocatalysis is a rapidly developing technology for degrading recalcitrant organic compounds in wastewater due to its ability to overcome electron-hole recombination. Herein, we synthesized Fe/S co-doped TiO2 nanotubes through an in-situ anodization technique. We developed a simple reduced quadratic model based on response surface modeling which can be used to adequately correlate the operating parameters with the photoelectrocatalytic performance of Fe/S-TiNTs in degrading phenol red. Predicted maximum dye degradation of 54.78% was achieved by the generated model using the optimized parameters: initial phenol red concentration = 5.22 mg L-1, applied voltage = 27.4 V, and dopant loading = 2.97 wt.%. Upon validation, experimental maximum phenol degradation of 53.24% was obtained, which agrees well with the predicted value within statistical significance. Overall, our model can be potentially used for process optimization within the design space studied.

Humic acid - functionalized silver nanoparticles (HA-AgNPs) were successfully synthesized and used to detect Cu (II) ions in aqueous solutions. The HA-AgNPs was shown to have an average hydrodynamic diameter of 101.4 nm and a polydispersity index of 0.447. The absorbance spectra of HA-AgNPs showed the characteristic local surface plasmon resonance (LSPR) peak of AgNPs at 408.3 nm. Addition of Cu (II) in the HA-AgNPs led to their agglomeration as evidenced by the change in their surface morphology and their corresponding optical absorbance spectra. The synthesized HA-AgNPs showed a strong linear response for Cu (II) concentrations in the range of 0.00 – 1.25 mM with a limit of detection (LoD) of 4.4428 ± 0.1091 mg L-1, a limit of quantification (LoQ) of 14.8094 ± 0.3636 mg L-1, and a limit of blank (LoB) of 0.1214 ± 0.0065 mg L-1. Statistical analysis showed that this calibration curve could be used to quantify Cu (II) concentrations within a 95% confidence level. Furthermore, HA-AgNPs was found to be selective for Cu (II) detection based on the selectivity study against common metal ions found in drinking water. This shows that the synthesized HA-AgNPs can be used as an environment-friendly colorimetric nanosensor for rapid and point-of-need quantification of Cu (II) ions in aqueous media.

Titanium dioxide is a widely-investigated semiconductor photocatalyst due to its wide availability and low cost. Although it has been successfully used in the photocatalytic treatment of various organics in wastewater, it remains a challenge to modify its structure to achieve enhanced catalytic properties at a wider light spectrum. Doping with transition metals was seen to narrow its optical band gap yet synthesis routes have been largely limited to the use of high-end equipment. Herein we demonstrate the use of a simpler one-pot approach to synthesize nanoporous arrays of silver-doped titanium dioxide nanotubes (Ag-TiNTs) by double anodization of titanium sheets. The synthesized Ag-TiNTs have an average inner diameter of 58.68 nm and a wall thickness of 16.46 nm. ATR-FTIR spectroscopy revealed its characteristic peaks attributed to O-Ti-O bonds. Silver doping increased the lattice volume and crystallite size of anatase with a corresponding decrease in the degree of crystallinity due to the introduction of impurity Ag atoms in its tetragonal structure. Silver was homogeneously distributed across the nanotube surface at an average loading of 1.41 at. %. The synthesized Ag-TiNTs were shown to have a superior photoelectrocatalytic activity in degrading C.I. Basic Blue 9 under UV illumination with a pseudo-first-order kinetic rate of 1.0253 x 10-2 min-1. Most importantly, the Ag-TiNTs are photoelectrocatalytically-active even at a low Ag loading.

Highly-organized one-dimensional arrays of copper-doped titanium dioxide nanotubes (Cu-TiNTs) were synthesized in a one-pot approach by double anodization of titanium sheets. Field-emission scanning electron microscopy showed that Cu-TiNTs have an average inner diameter of 52.13 nm, a wall thickness of 14.28 nm, and a tube length of 0.6401 μm. Fourier-transform infrared spectroscopy confirmed the presence of characteristic O-Ti-O bond of TiO2. X-ray fluorescence spectroscopy confirmed copper-doping with an average dopant loading of 0.0248%. Even at this low dopant loading, Cu-TiNTs were shown to be photo-active in degrading Acid Orange 52 (AO 52) under UV light illumination. The kinetic profiles of AO 52 photoelectrochemical degradation were best described by the pseudo-first-order kinetic model (R2 ≥ 0.991) with kinetic constants 9.42 x 10-3 min-1 for Cu-TiNTs as compared to 6.04 x 10-3 min-1 for pristine TiNTs. Overall, doping pristine TiNTs with Cu was shown to enhance its photoelectrocatalytic properties in degrading textile dyes such as AO 52.

Silver-doped TiO2 nanotubes (Ag-TiNTs) were synthesized in a top-down approach by single-step anodization of titanium sheets. The highly-ordered array of Ag-TiNTs was confirmed by scanning electron microscopy with an average inner diameter of 41.28 nm and a wall thickness of 35.38 nm. Infrared spectroscopy confirmed the presence of O-Ti-O bonds. Analysis of the X-ray powder diffraction profiles showed the characteristic peaks for anatase and titanium for both pristine TiNTs and Ag-TiNTs. Ag-doping caused no observed changes in the crystalline structure of pristine TiNTs. High-definition X-ray fluorescence spectroscopy revealed that the synthesized Ag-TiNTs have 0.05 wt% Ag-loading. Even at low Ag-loading, the Ag-TiNTs were shown to be photo-active, achieving 10.13% degradation of Acid Orange 52 under UV illumination after 120 min.