Determination Of Activation Energy Research Articles

Determination of the kinetic parameters of complex condensed phase reactions using a nonlinear model

This research introduces a novel nonlinear model that can be used in the modified Friedman method to determine activation energy via linear regression with a trial-and-error approach. Its application in a simulated reaction enhanced precision in activation energy determination and accurately captured the trend in activation energy variation with temperature compared to quadratic regression. The nonlinear model can also predict nonlinearity in compensation effect relationships, aiding in the assessment of pre-exponential factor, rate constant, and conversion function in complex reactions, ensuring more precise results compared to linear model. By incorporating random noise into the simulated reaction’s isoconversional kinetic data, which follows a normal distribution, we observed that both nonlinear and quadratic regressions produce comparable activation energy values. However, the nonlinear compensation effect approach yields more precise results for the pre-exponential factor, rate constant, and conversion function compared to the linear model in the presence of random errors. The novel approach based on the nonlinear model was applied, in conjunction with the linear and quadratic Friedman methods featuring linear compensation effect, to compute the kinetic parameters of a polymer coating on a commercial optical fiber as well as a polyethylene. Gnu Octave/MATLAB codes were also made available for estimating the kinetic parameters of complex reactions exhibiting a single peak in reaction rate curves using the linear, quadratic, and nonlinear Friedman methods, along with the application of linear and nonlinear compensation effects. These codes can be customized by users to estimate the kinetic parameters of their own kinetic data.

Machine learning based prediction and iso-conversional assessment of oxidatively torrefied spent coffee grounds pyrolysis

This research focused on developing a predictive model for mass loss during the pyrolysis of oxidatively torrefied spent coffee grounds (SCG) using machine learning techniques. Four algorithms were employed: artificial neural networks (ANN), k-nearest neighbors (k-NN), random forest (RF), and decision tree (DT), with the RF model demonstrating superior performance (R2 > 0.9981, RMSE <1.346) for both training and testing sets. The pyrolysis behavior, kinetics, and thermodynamics of SCG were also investigated using thermogravimetric analysis (TGA) under an inert atmosphere at different heating rates. Higher heating rates in TGA cause Tpeak values to shift to higher temperatures with increased DTGpeak values, while also resulting in lower Tonset and higher Toffset. Kinetic analysis, using the Flynn-Wall-Ozawa (FWO) method, was identified as the most suitable approach for determining activation energy (Ea), with values ranging from 192.66 to 288.13 kJ mol−1, indicating differences in energy requirements for pyrolysis across samples. Thermodynamic analysis further revealed that both raw SCG and oxidatively torrefied SCG pyrolysis were endothermic reactions. These findings contribute valuable insights into the optimization of biomass conversion technologies, highlighting the potential of machine learning in improving predictive accuracy and efficiency in thermal behavior modeling. This research advances sustainable bioenergy production by promoting the use of SCG, an abundant waste material, as a renewable feedstock in pyrolysis-based processes.

A new method for determining activation energy in spark plasma sintering

In general, the power-law creep is used to calculate the activation energy in hot press powder sintering. However, associated difficulty is caused by its large amount of exploratory experiments and multiple creep mechanisms of metal powder with holding time at specific temperatures and macroscopic pressures. In the present study, we propose a new method combining the stress-temperature map of metals and the power-law creep equations, that allows for a faster determination of the creep temperature interval of metals, and finally an accurate determination of the creep mechanism in powder sintering. We verified the viability of this method by varying the pulse current frequency during spark plasma sintering of pure titanium powder. It is also concluded that the higher pulse current frequency is able to reduce the activation energy of pure titanium powder. Accordingly, the results obtained provides a labor-saving method to determine the activation energy of metals in powder sintering.

Behaviour and mechanics of phenolic sorption by novel bio-based graphene derivatives as adsorbents

Phenolic compounds, notorious for their environmental and health hazards, demand efficient removal from wastewater. Our research leads in synthesizing bio-based graphene derivatives from biomass-derived lignin, such as graphene oxide (bGO) and reduced graphene oxide (brGO), and these materials show promise in effectively removing hydrophobic pollutants like phenol and tannic acid. Hence, this study investigated the mechanical and dynamical aspects of their sorptions by bGO and brGO. Both adsorbents demonstrated a comparable adsorption pattern, with enhanced efficiency observed at higher adsorbent dosage, prolonged contact time, neutralized pH solutions, and elevated temperatures. Of note, phenol is removed at a much greater rate (>94%) than tannic acid (>84%) by both adsorbents at a dosage of 180 mg L−1, pH 6.5, 900 min, and 25 °C. The Freundlich model provided the best fit for the isotherm data of both phenol (R2 = 0.99) and tannic acid (R2 = 0.98), while the pseudo-second-order model effectively described the adsorption kinetics of phenol (R2 = 0.99) and tannic acid (R2 = 0.99). The determined activation energy exceeds 5.88 kJ mol−1, affirming the prevalence of physisorption as the dominant mechanism in the adsorption process. Thermodynamic analysis confirmed that the adsorption process is endothermic (ΔH) and occurs spontaneously (ΔG), indicating a random (ΔS) nature. However, the percentage removal plunged considerably after five consecutive adsorption-desorption cycles, attributed to the alterations of active sites on bGO and brGO.

Fabrication of Gold and Silver Nanoparticles Supported on Zinc Imidazolate Metal-Organic Frameworks as Active Catalysts for Hydrogen Release from Ammonia Borane.

Well-dispersed Au and Ag nanoparticles (NPs) have been immobilized on a zinc imidazolate metal-organic framework, Zn(mim), using the "one-pot" method and tested as catalysts in ammonia borane hydrolysis. The AuNPs@Zn(mim) and AgNPs@Zn(mim) materials were characterized by FTIR, XRD, ICP-OES, TGA, BET, SEM, and TEM. The AgNPs@Zn(mim) catalyst showed a high yield (98.5%) and high hydrogen generation rate (3352.71 mL min-1 gAg -1) in NH3BH3 dehydrogenation. The determined activation energies (19.6 kJ mol-1 for AuNPs@Zn(mim) and 38.13 kJ mol-1 for AgNPs@Zn(mim)) are lower than those for most reported catalysts containing Au/Ag-MOF used in the hydrolysis of NH3BH3. Moreover, the catalysts tested here revealed good stability and reusability, preserving 71.42% (AuNPs@Zn(mim)) and 88.23% (AgNPs@Zn(mim)) of their initial catalytic activities after five consecutive cycles. In the case of AgNPs@Zn(mim), the combination of the simple and green synthesis method, low active metal content, relatively low cost, and moderate dehydrogenation conditions makes the material an excellent candidate to produce hydrogen from ammonia borane.

Thermoluminescence (TL) properties of Eu3+ incorporated with CaB4O7 phosphors prepared by solution-combustion process

The solution-combustion approach was used to create CaB4O7:Eu3+phosphors using Ba (NO3)2, Eu (NO3)3·5H2O, H3BO3, NH3(ON)H2, and NH4NO3 as source materials. We investigated the thermoluminescence (TL) characteristics of beta (β)-irradiated CaB4O7:Eu3+. When the TL intensity was evaluated at different dosages of β, it rose with the dose. Changes in peak temperature were observed because of the investigation of the effects of varying heating rates on TL glow curves. Moreover, the positions of the peak temperature and the TL intensity did not change when the same sample was measured again, suggesting that the sample was stable. Additionally, the study calculated several kinetic parameters, including activation energy (E), frequency factor (s), and geometrical factor (μg), for distinct TL glow curves. Through geometric analysis of TL glow peaks, the study determined activation energies and kinetic orders, enabling the calculation of the frequency factor. The findings highlight the suitability of the prepared phosphor for dosimetry and provide insights into trap characteristics crucial for continuous illumination at room temperature. The study also emphasises the importance of optimising trap depth for prolonged afterglow, shedding light on the interplay between trap energies and luminescence characteristics. These findings deepen our comprehension of phosphor behavior and open the door to better dosimetry applications.

Molecular dynamics simulation of the diffusion behaviour in Ti–Ag using diffusion couple method

The diffusion behaviour of the Ti–Ag system was investigated using classical molecular dynamics by simulating a diffusion couple at various temperatures. One bulk of the diffusion couple consisted of titanium atoms arranged in a hexagonal close-packed (hcp) structure, i.e., α-Ti, and the other consisted of silver atoms arranged in a face-centred cubic (fcc) structure. The modern second nearest-neighbour modified embedded-atom method (2NN-MEAM) interatomic potential was used. The mean square displacement (MSD) of Ti atoms diffusing into Ag and Ag atoms into α-Ti was recorded during the simulation. Diffusion coefficients were determined from the slopes of lines fit to linear regions of MSD dependence on time. The Arrhenius relation was used to determine the activation energy and the frequency of attempts. The activation energy of Ti was 0.61eV and frequency of attempts 1.90⋅10−8m2s−1. The determined activation energy of Ag and frequency of attempts were not considered reliable because the Ag diffusion coefficient did not grow exponentially with temperature. Ti atoms penetrated deeper and greater amounts into Ag than Ag into α-Ti and also had a greater diffusion coefficient at all temperatures. The results were compared with the available experimental data, and for these purposes, self-diffusion in α-Ti and Ag was further investigated. Finally, it was determined that Ag diffuses in α-Ti by hopping over interstitial positions and Ti in Ag via vacancies.

Smelting Reduction of HIsarna Slag with Methane

To study the smelting reduction behavior of methane in the HIsarna process, the isothermal reduction experiments of HIsarna slag with 6 wt% of FeO were conducted at the temperatures of 1450, 1475, and 1550 °C, using 5 vol% CH4‐Ar. The effect of the gas injection flow rate on the overall reduction rate was investigated in the range of 0.5–1.5 L min−1. The results confirm that the decomposed carbon black acts as the dominant reductant in the reduction process compared to hydrogen. Increased gas flow rate increases the reaction rate, while temperature shows no significant effect. The reduction process could be described by the JMAEK model: by fixing the gas flow rate at 1.0 L min−1 with different temperatures, the exponent n value is around 1.5, indicating FeO mass transfer is the limiting step since there are sufficient carbon blacks as nucleation sites. The reduction process follows the first‐order model controlled by the reactant concentration with the gas flow rate being at 0.5 L min−1 and in the second reaction stage of the gas flow rate at 1.5 L min−1. The determined activation energy for the methane reduction is 59.8 kJ mol−1.

Temperature Dependence of the Defect States in LWIR (100) and (111)B HgCdTe Epilayers for IR HOT Detectors

HgCdTe epilayers grown by chemical vapor deposition (MOCVD) on GaAs substrates operating in the long-wave infrared range were characterized by the photoluminescence (PL) method. Photodiode and photoconductor designs, both (100) and (111)B crystallographic, were analyzed. Spectral current responsivity (RI) and a PL signal approximated by a theoretical expression being the product of the density of states and the Fermi–Dirac distribution were used to determine the fundamental transition (energy gap, Eg). For all the samples, an additional deep-level-related transition associated with mercury vacancies (VHg) were observed. The energy distance of about 80 meV above the valence band edge was observed for all the samples. Moreover, measurements at low temperature showed shallow acceptor-level (AsTe and VHg as acceptors) transitions. In HgCdTe(100), due to the higher arsenic activation, AsTe was the dominant acceptor dopant, while, in HgCdTe(111)B, the main acceptor level was formed by the neutral VHg. The determined activation energies for AsTe and VHg dopants were of about 5 meV and 10 meV, respectively.

Impact on activation energy with elevating calcination temperature of barium bismuth ferrite nanocomposite

Barium Bismuth Ferrite nanoparticles having the general formula Ba1-xBixFeO3 were successfully made by the sol-gel system, using nitrates as the fundamental material. Tartaric acid and polyvinyl alcohol were used as chelating agents. The synthesized nanoparticle powder was sintered at 650 ̊C and 750 ̊C for 3 h. Filtering with dilute nitric acid and distilled water is used to remove the impurities. The structural, optical, and dielectric properties were determined at room temperature. Using X-ray diffraction (XRD) analysis, structure, lattice parameter, microstrain, and dislocation density were calculated. Using the Scherrer equation, the peak's crystalline size was ascertained. In FTIR, the vibrational modes of the octahedral and tetrahedral metal complexes in the sample have been studied using the wavenumber in this range. The synthesized nanocomposite contains morphological features, such as interconnecting agglomerates with spherical, irregular, or non-uniform elongated shapes, as demonstrated by SEM images. The activation energy for relaxation and activation energy for conduction was measured from the Cole-Cole plot and the AC conductivity versus frequency plot respectively. The determined activation energies from the two investigations were relatively close to one another. The Barium Bismuth Ferrite nanoparticles samples at room temperature indicate that the samples have implicit candidates for information storage devices for spintronic devices. In the high frequency range, all samples depending upon the temperature demonstrate excellent dielectric behaviour and small dielectric loss, and with stable dielectric constant, these samples make their prospective for the practical application in spintronic devices the main goal of this work.

Impact of natural antioxidant (silybin) on the thermal stability of ultra high molecular weight polyethylene: a thermogravimetric study

The natural antioxidant (Silybin), with different concentrations, is introduced in Ultra High Molecular Weight Polyethylene (UHMWPE) and impact on thermal stability is observed. For this, thermograms are recorded at 5 ℃/min heating rate in temperature region 50–600 ℃ through Thermogravimetric Analysis (TGA) technique. The model fitting (Coats and Redfern) kinetic approach is adopted to determine activation energy of each recorded thermograms to identify optimum silybin concentration. UHMWPE, with optimum silybin concentration, are further subjected to three other heating rates (10, 15 and 20 ℃) in the same temperature region. By employing deconvolution (bi-Gaussian asymmetric function) approach, two iso-conversional kinetic models (Starink (SR) and Friedman (FR)) are utilized to obtain activation energies of the deconvoluted peaks. Further, the reaction mechanism involved in thermal decomposition, change in entropy ΔS#\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\left({\\Delta \ ext{S}}^{\\#}\\right)$$\\end{document}, change in enthalpy ΔH#\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\left({\\Delta \ ext{H}}^{\\#}\\right)$$\\end{document} and change in Gibbs free energy ΔG#\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\left(\\Delta {\ ext{G}}^{\\#}\\right)$$\\end{document} are determined.

Quantifying reaction rates in methane oxidation: atomistic simulations at high temperature

This study presents a comprehensive analysis of methane oxidation at high temperatures (2500 K–3500 K)—a critical process in atmospheric chemistry and energy production. Employing reactive molecular dynamics simulations, the research bridges the knowledge gap in understanding the complex reaction networks at these elevated temperatures. Key features include the identification of intermediate species and the simplification of the reaction networks through advanced simulation and post-processing techniques. Another focus of the study is on employing the Arrhenius equation for nonlinear curve fitting to determine activation energy and pre-exponential factors for various reactions. The analysis reveals that, despite temperature variations, there are 121 common reactions among the reduced reaction systems. This discovery revealed the underlying consistency in methane oxidation pathways across a range of high temperatures. The results of this research are vital for enhancing current models of methane oxidation, particularly in the context of improving combustion processes and deepening our understanding of atmospheric dynamics involving methane.

A Study toward the Model Independence of Various Heating Rates Method in Thermoluminescence Glow Curve Analysis

This study analyzes thermoluminescence (TL) glow curves simulated in general order kinetics (GOK), one trap one recombination center (OTOR), and non‐interactive multi‐trap system (NMTS) models using various heating rates (VHR) method in linear heating scheme to extract the activation energy. A theoretical analysis to determine activation energy from TL curves using OTOR and NMTS models in an iterative manner, where the TL intensity is determined by using the Lambert‐W function, is proposed with its limitations. It is established that the activation energies in OTOR and NMTS models consist of the relevant GOK term and a respective correction term. Systematic analysis is carried out to study the improvement of the accuracy of activation energy derived from OTOR and NMTS model TL curves over the GOK model calculation. A quantitative analysis of the quasi‐equilibrium (QE) approximations is carried out for choosing appropriate system parameters. The validity of QE conditions are determined by studying variations of full width at half maximum as well as area under the curve as a function of heating rate. The present method is applied on some experimental data to estimate activation energies. This investigation reveals that the activation energy derived in VHR method has negligible dependence on the underlying theoretical models, i.e., the activation energy derived from GOK model calculation is significantly accurate for experimental scenario.

Eco-innovation in energy: Solid degradation kinetics of rejected red macroalgae (Kappaphycopsis cottonii) for bio-oil and biochar production

In the pursuit of renewable energy sources, biomass conversion into biofuels has garnered attention as a sustainable alternative to fossil fuels. This research focuses on the pyrolytic conversion of red macroalgae, specifically rejected Kappaphycus cottonii, an underutilized biomass in Indonesia, into valuable bio-energy carriers, while analyzing the solid degradation kinetics involved. The dried K. cottonii underwent slow pyrolysis at varying temperatures (400–600 °C) and time intervals (10–50 min). The impact of these variables on the yield of bio-oil and biochar, alongside the thermogravimetric profiles indicating mass loss, was thoroughly assessed. The study also explores the chemical kinetics of the decomposition process, utilizing the first-order reaction model to analyze the solid biomass conversion rate, activation energy, and frequency factor. Key findings demonstrate that the optimal pyrolysis temperature for maximizing bio-oil yield was precisely 500 °C, beyond which thermal cracking led to yield reductions. Reaction times also greatly affect yield, highlighting the importance of optimized pyrolysis conditions. The determined activation energy and frequency factor, based on the Arrhenius equation, highlighted K. cottonii's lower decomposition energy barrier relative to terrestrial biomass. This distinction is largely ascribed to its unique chemical makeup, notably a lower lignin content, positioning K. cottonii as an advantageous feedstock for biofuel production through pyrolysis.

Deep‐bed drying kinetics and thermodynamic parameters of high‐moisture parboiled paddy (ASD‐16) in a reversible airflow fixed bed dryer

AbstractReversible airflow fixed bed dryer (RAFBD) is an energy‐efficient, cost‐effective, and dependable dryer for using renewable energy sources in parboiling mills. In this study, a medium‐sized and high‐moisture parboiled paddy, ASD‐16, was dried in the RAFBD to determine its deep drying characteristics and thermodynamic properties. The chosen paddy variety is a commonly cultivated paddy in the southern region of Tamil Nadu, India. The RAFBD experimental setup was designed to dry 30 kg of parboiled paddy. For the statistical analysis, the experimental data for the deep‐bed drying at hot air temperatures 50–80°C and velocities of 0.1 and 0.15 m/s were used at constant specific humidity. To predict drying characteristics, 12 drying models were compared. Based on their statistical parameters, the Midilli et al. model was selected. For the tested conditions, the coefficients for effective moisture diffusion, heat transfer, and mass transfer were between 9.82 × 10−8 and 2.13 × 10−7 m2/s, 0.3802 and 1.325 W/m2 K, and 0.375 × 10−4 and 1.26 × 10−4 m/s, respectively. Furthermore, the determined activation energy ranged from 20.4964 to 20.4390 kJ/mol.Practical ApplicationsASD‐16 is one of the popular paddy varieties cultivated and used in parboiling mills in the study region. The outcome of this research can contribute to the application of a cost‐effective dryer for drying high‐moisture paddy. Furthermore, the drying time and bed height proposed in this work can reduce the drying time in the mills and improve energy efficiency. The drying kinetics and suitability of the models found in this study will contribute to the design and development of low‐cost dryers for the local parboiling industries. As rice husk, which is a waste from paddy processing, is used for the heating process, industries can reduce the cost of energy for closed‐roof drying. This study provides a clear insight to the researchers and designers in standardizing the capacity of the dryer, drying temperature, and airflow rate for any similar kind of paddy variety.

Synergistic effects of the mixing factor on the kinetics and products obtained by co-pyrolysis of Rosa rubiginosa rosehip seed and husk wastes

The aim of this work was to study the potential synergistic effects of the mixing factor on the kinetics parameters and products obtained through co-pyrolysis of two wastes from Rosa rubiginosa rosehip, and further co-gasification with CO2 of the remaining biochar. Thermogravimetric analysis showed that 6 different processes occur by slow pyrolysis (heating rates of 5, 10, and 20 °C/min), associated with the decomposition of hemicelluloses, cellulose, lignin, and CaCO3 from the ashes. Isoconversional methods determined activation energies of 84.68–223.42, 230.11–270.85, 187.58–303.37, and 400.11–421.71 kJ/mol for hemicellulose, cellulose, lignin, and CaCO3 decomposition, respectively. In most cases, the activation energy from co-pyrolysis was higher for the blends than for the pure wastes, which means that the blends are less reactive to pyrolysis. Gas and tar analyses showed that the blend with 75 % husk waste and 25 % seed waste produced the most hydrogen (5.639 mmol/g biomass), while the blend with 25 % husk waste and 75 % seed waste produced the most carbon monoxide (3.642 mmol/g biomass). The biochar produced by the blends and pure wastes were thermally treated with CO2 to compare reactivity to gasification. It was concluded that the addition of husk waste to the blend increases the reactivity of the biochar obtained, mainly due to its higher ash content.

Thermal investigation of NbSe2 nanoparticles synthesized through a temperature-dependent sonochemical method.

Due to their unique size-dependent properties, transition metal di-chalcogenide nanoparticles are trending in research for their potential to revolutionize next-generation electronics, energy storage, and catalytic processes. This study addresses the effect of temperature when synthesizing NbSe2 nanoparticles via the sonochemical method at three different temperatures, room temperature (R.T.), 70 °C, and 100 °C. Energy Dispersive X-ray Analysis (EDAX) confirmed the high purity of NbSe2, with the sample synthesized at 70 °C, displaying the accurate stoichiometric ratio. X-ray diffraction (XRD) analysis revealed that all samples maintained the hexagonal phase of NbSe2, with 70 °C exhibiting superior crystallinity due to their crystallite size, lowest dislocation density, and minimal internal strain. Thermogravimetric analysis (TGA) and differential thermogravimetric (DTG) analyses, demonstrated that the sample synthesized at 70 °C had the highest thermal stability, with the lowest total weight loss and most consistent mass loss behavior. Kinetic parameters were evaluated using the Kissinger-Akahira-Sunose (KAS) and Flynn-Wall-Ozawa (FWO) methods, determining activation energy (E a), pre-exponential factor (A), change in activation enthalpy (ΔH*), change in activation entropy (ΔS*), and Gibbs free energy change (ΔG*). Also, the sample synthesized at 70 °C exhibited the highest E a, indicating superior thermal stability and favorable reaction kinetics. The findings underscore the significant impact of synthesis temperature on the structural and thermal properties of NbSe2 nanoparticles, with the sample synthesized at 70 °C demonstrating optimal characteristics. This study provides valuable insights into temperature-dependent synthesis and the thermal behavior of NbSe2 nanoparticles, highlighting their potential in various technological applications.

Tailored synthesis and optimization of nickel-molybdenum carbide-graphite nanofiber composite for enhanced ethanol electrooxidation.

A novel nickel-molybdenum carbide-graphite nanofiber composite is introduced as an electrocatalyst for ethanol electrooxidation. The proposed nanofibers have been prepared by calcinating electrospun nanofibers composed of nickel acetate tetrahydrate, molybdenum chloride, and polyvinyl alcohol. The calcination process was conducted at different temperatures (700, 850, and 1000°C) under a nitrogen gas atmosphere with a heating rate of 2.5 deg/min and a holding time of 5 h. Physicochemical characterizations have indicated that nickel acetate is entirely reduced to nickel metal during the sintering process, and molybdenum has bonded with carbon to produce molybdenum carbide. At the same time, the used polymer has been pyrolyzed to produce a carbon nanofiber matrix embedding formed inorganic nanoparticles. Electrochemical measurements concluded that molybdenum content and calcination temperature should be controlled to maximize the electrocatalytic activity of the proposed catalyst. Typically, the oxidation peak current density was 28.5, 28.8, 51.5, 128.3, 25.6, and 3 mA/cm2 for nanofibers prepared from an electrospun solution containing 0, 5, 10, 15, 25, and 35 wt% molybdenum carbide, respectively. Moreover, it was observed that increasing the calcination temperature distinctly improves the electrocatalytic activity. Kinetic studies have indicated that the reaction order is close to zero with a reaction temperature-dependent value. Moreover, it was detected that the electrooxidation reaction of ethanol over the proposed nanofiber composite follows the Arrhenius equation. The determined activation energy is 33 kJ/mol, which indicates good catalytic activity for the introduced nanofibers. Through the application of a set of visualization-based tools and the general linear model (GLM), the optimal conditions that generate the highest current density were identified. The computations unveiled that the optimal parameter settings are as follows: Mo content at 15 wt.%, methanol concentration of 1.55 M, and reaction temperature of 59°C.

Efficient hydrogen evolution from NaBH4 using bimetallic nanoparticles (Ni–Co) supported on recycled Zn–C battery electrolyte paste

Electrolytic paste (EP) from used batteries was innovatively utilized as a support for Ni–Co nanoparticles (Ni–Co NPs) to catalyze hydrogen evolution from NaBH4. The materials exhibited a porous and heterogeneous morphology, characterized by a ZnMn2O4 interplanar distance of 0.34 nm, as confirmed by SAED analysis. Elemental analysis identified carbon, nitrogen, hydrogen, and sulfur, while ICP-MS quantified zinc, manganese, and iron. XRD unveiled an amorphous broad peak at 2θ = 13.3–39.8°, with additional phases identified as ZnO, graphite, simonkolleite, manganese oxides, and hetaerolite. Raman spectroscopy showcased characteristic bands typical of carbonaceous materials. FTIR detected functional groups alongside Ni–O, Co–O, and Zn–O bonds. Various Ni/Co ratios were assessed, and the 25:75 and 20:80 (w/w) ratios showed optimal performance, yielding hydrogen at rates of 238.1 and 278.0 mL H2 gcatalyst−1 min−1, respectively. The determined activation energy was 32.76 kJ mol−1. The turnover frequency reached 1823.93 mL H2 gcatalyst−1 min−1 (328.15 K), and the catalyst exhibited satisfactory performance over 16 reuse cycles.

Machine learning-based modeling of malachite green adsorption on hydrochar derived from hydrothermal fulvification of wheat straw

This study investigated the efficiency of hydrochar derived from hydrothermal fulvification of wheat straw in adsorbing malachite green (MG) dye. The characterizations of the hydrochar samples were determined using various analytical techniques like SEM, EDX, FTIR, X-ray spectroscopy, BET surface area analysis, ICP-OES for the determination of inorganic elements, elemental analysis through ultimate analysis, and HPLC for the content of sugars, organic acids, and aromatics. Adsorption experiments demonstrated that hydrochar exhibited superior removal efficiency compared to feedstock. The removal efficiency of 91 % was obtained when a hydrochar dosage of 2 g L−1 was used for 20 mg L−1 of dye concentration in a period of 90 min. The results showed that the study data followed the Freundlich isotherms as well as the pseudo-second order kinetic model. Moreover, the determined activation energy of 7.9 kJ mol−1 indicated that the MG adsorption was a physical and endothermic process that increased at elevated temperatures. The study also employed an artificial neural network (ANN), a machine learning approach that achieved remarkable R2 (0.98 and 0.99) for training and validation dataset, indicating high accuracy in simulating MG adsorption by hydrochar. The model's sensitivity analysis demonstrated that the adsorbent dosage exerted the most substantial influence on the adsorption process, with MG concentration, pH, and time following in decreasing order of impact.