Catalytic Surface Research Articles

Synergetic Effect of Ni‐CeO₂ Bimetallic Catalyst for an Effective Decomposition of Methane to Hydrogen and Filamentous Nanocarbons

AbstractThe work attempts to synthesis nickel‐ceria bimetallic catalysts supported on porous carbon template, thermally stable at 850 °C, for dehydrogenation of methane to hydrogen and carbon nanostructures. A series of bimetallic Ni catalysts were synthesized by varying the % ceria content (30Ni‐5CeO2/AC, 30Ni‐10CeO2/AC, and 30Ni‐15CeO2/AC) using the incipient wetness impregnation approach. Among the set of bimetallic catalysts, the 30Ni‐5CeO2/AC catalyst was found to offer highest methane conversion and stability. A maximum conversion of 90 % was achieved with 40 % methane feed concentration along with good catalyst stability. The promoter ceria at low concentration enhanced the dispersion of metal over the catalytic surface, resulting in adequate metal‐support interaction. The ability of the carbon support along with promoter ceria enhanced the thermal stability of the Ni catalyst up to 850 °C, offering high conversion and catalyst stability has been the highlight of the work. Advanced analytical techniques were used to characterize the catalyst's structural, textural, and morphological properties both before and after the reaction. The morphological study of the best‐performing catalyst demonstrated the formation of dense carbon nanotubes through tip‐growth mechanism exhibiting a high aspect ratio.

Nano‐Multiactive Sites Pd/PdO/CuO/PdCu3 Formed In Situ on the Surface Hetero‐Organometallic Pd(II)/Cu(II) Nanosheet: Investigation on the Formation of Active Sites, Synergistic, and Catalytic Activity

ABSTRACTExploring the relationship between the structure of active site and the activity in molecular level and investigating the reason for deactivation are extremely important in designing the highly active catalyst. In this paper, new self‐assembly Schiff‐base Pd/Cu nanosheets supported on the surface of graphene oxide (GO) (called as GO@Hpmaba‐Pd/Cu) were fabricated and characterized. Among them, GO@Hpmaba‐Pd0.2/Cu0.8 exhibited a high activity with a TOF value of up to 95,357 h−1 and substrate suitability in Suzuki cross‐coupling reaction. GO@Hpmaba‐Pd0.2/Cu0.8 could be reused at least 13 times. GO@Hpmaba‐Pd0.2/Cu0.8 was a heterogeneous catalyst and the catalysis occurred on the surface. The truly active sites included Pd/PdO/CuO/PdCu3 formed in situ on the surface of the hetero‐organometallic Pd/Cu nanosheet during catalysis. The synergistic effects among these active sites could be described as that the electrons transferred from GO to CuO (PdO) or to Pd via ligand (Hpmaba) and subsequently electrons transferred from CuO (PdO) to Pd. These made more electron negative palladium, enhancing the oxidation addition between palladium and aryl halide and prompting the activity. The deactivation of catalyst was mainly caused by some destroyed organometallic in the nanosheet, residues adsorbed on catalytic surface, loss of active Pd due to the leaching with increase of recycling, and the aggregation of active metals.

Structure, Properties, and Applications of Silica Nanoparticles: Recent Theoretical Modeling Advances, Challenges, and Future Directions.

Silica nanoparticles (SNPs), one of the most widely researched materials in modern science, are now commonly exploited in surface coatings, biomedicine, catalysis, and engineering of novel self-assembling materials. Theoretical approaches are invaluable to enhancing fundamental understanding of SNP properties and behavior. Tremendous research attention is dedicated to modeling silica structure, the silica-water interface, and functionalization of silica surfaces for tailored applications. In this review, the range of theoretical methodologies are discussed that have been employed to model bare silica and functionalized silica. The evolution of silica modeling approaches is detailed, including classical, quantum mechanical, and hybrid methods and highlight in particular the last decade of theoretical simulation advances. It is started with discussing investigations of bare silica systems, focusing on the fundamental interactions at the silica-water interface, following with a comprehensively review of the modeling studies that examine the interaction of silica with functional ligands, peptides, ions, surfactants, polymers, and carbonaceous species. The review is concluded with the perspective on existing challenges in the field and promising future directions that will further enhance the utility and importance of the theoretical approaches in guiding the rational design of SNPs for applications in engineering and biomedicine.

Substrate and potential-driven surface morphology of bifunctional Ni-Fe electrode for efficient alkaline water electrolysis

Nickel-iron (Ni-Fe) alloy electrodes are synthesized using chronoamperometry. The influence of substrate type (copper, stainless steel, and nickel) and deposition potential on the structural, morphological, and electrocatalytic characteristics are systematically investigated. X-ray diffraction (XRD) analysis revealed the formation of a face-centered cubic (FCC) Ni-Fe alloy. Electrodeposition at higher potential (−1.45 V) forms well-defined nanoflakes, whereas electrodeposition at lower potential (−1.00 V) results aggregated Ni-Fe particles. The Ni-Fe alloy electrodes having well-defined nanoflakes demonstrated superior electrocatalytic performance, exhibiting a overpotential of −168 mV vs. RHE for the hydrogen evolution reaction (HER) and 236 mV vs. RHE for the oxygen evolution reaction (OER), at current density of 10 mA/cm2. The enhanced electrocatalytic activity of the nanoflakes based Ni-Fe alloy is attributed due to their larger catalytic surface area, porous morphology and higher Fe concentration. The Ni-Fe alloy electrodes displayed bifunctional electrocatalytic behavior, making them highly suitable for both HER and OER processes.

A platinum-coated staggered reactor to intensify lean hydrogen/air combustion: A large eddy simulation study

Catalytic-aided combustion has been proven effective for premixed hydrogen/air mixtures, particularly under lean to ultra-lean conditions. However, minimising the required catalyst sets a significant challenge because noble metals with high catalytic activity are rare and expensive. Therefore, this study aims to intensify the catalytic combustion process by investigating a non-planar reactor comprising an array of platinum-coated half- and full-cylinders through large eddy simulation. A premixed mixture with a fuel-lean equivalence ratio of 0.15 and an incoming Reynolds number of 3500 based on hydraulic diameter is used. For comparison, a planar reactor without cylinders is also studied under the same operating conditions and with the same amount of platinum-coated surface area. The simulation employs the turbulent kinetic energy sub-grid model and the eddy dissipation concept to model the turbulent catalytic reacting flow. The discrete ordinate model is used to account for radiation heat transfer in the catalytic process. Numerical simulations are validated against experimental results prior to analysis. The findings indicate that the placement of cylinders along the reactor length enhances convective mass transfer and intensifies catalytic combustion, resulting in effective combustion over a smaller catalytic surface. Compared to planar models, non-planar reactors demonstrate a much better H2 conversion efficiency throughout the reactor length, saving nearly 62.5 % of the catalyst.

Bringing Molecules Together: Synergistic Coadsorption at Dopant Sites of Single Atom Alloys.

Bringing molecules together on a catalytic surface is a prerequisite for bimolecular and recombination reactions. However, in the absence of attractive interactions between reactants, such as hydrogen bonds, this poses a challenge. In contrast, based on density functional theory, we show that coadsorption at active sites of single-atom alloys (SAAs) is favored and that coadsorption is a general phenomenon observed for catalytically relevant adsorbates on a broad range of SAAs under temperature and pressure conditions commonly employed for catalysis. Dopants located in both terrace sites and in step edge defects exhibit a preference for coadsorption, displaying similar periodic trends. Using kinetic Monte Carlo simulations, we compare the reactivity of a model reaction on both a pure metal and an SAA and show that the preference for coadsorption significantly alters the overall reaction energy profile, even when the barriers for the rate-determining elementary step are identical. In our models, the coadsorption preference enhances the catalytic activity of the SAA surface by several orders of magnitude compared to the pure metal. We also report infrared (IR) spectroscopic signatures of coadsorption, which facilitate experimental detection. Analysis reveals that in these systems repulsive lateral interactions between nearby molecules are more than compensated for by the enhanced binding at dopant sites. Among the broad range of systems considered, SAAs containing early transition metals (TMs) exhibit the strongest coadsorption preference, which can be rationalized by assuming the existence of an optimal number of electrons involved in binding. The strong coadsorption preference, together with facile product desorption from early TMs, renders these systems attractive candidates for catalysis. Moreover, these SAAs could open new routes for reduction reactions because coadsorption with hydrogen is favored.

Electronic modulation towards MOFs as template derived CoP via engineered heteroatom defect for a highly efficient overall water splitting

The reasonable design of material morphology and eco-friendly electrocatalysts are essential to highly efficient water splitting. It is proposed that a promising strategy effectively regulates the electronic structure of the d‐orbitals of CoP using cerium doping in this paper, thus significantly improving the intrinsic property and conductivity of CoP for water splitting. As a result, the as-synthesize porous Ce-doped CoP micro-polyhedron composite derived from Ce-ZIF-67 as bifunctional electrocatalytic materials exhibits excellent electrocatalytic performance in both the oxygen evolution reaction (OER) and the hydrogen evolution reaction (HER), overpotentials of about 152 mV for HER at 10 mA cm−2 and about 352 mV for OER at 50 mA cm−2, and especially it shows outstanding long-term stability. Besides, an alkaline electrolyzer, using Ce0.04Co0.96P electrocatalyst as both the anode and cathode, delivers a cell voltage value of 1.55 V at the current density of 10 mA cm−2. The calculation results of the density functional theory (DFT) demonstrate that the introduction of an appropriate amount of Ce into CoP can enhance the conductivity, and can induce the electronic modulation to regulate the selective adsorption of reaction intermediates on catalytic surface and the formation of O* intermediates (CoOOH), which exhibits an excellent electrocatalytic performance. This study provides novel insights into the design of an extraordinary performance water-splitting of the multicomponent electrocatalysts.

Alloying effects on the reactivity of Pd are ensemble dominated

In this paper the geometric (“ensemble”) and electronic (“ligand”) effects of alloying on surface reactivity and catalysis are considered. The effect of alloying on the behaviour of Pd, both in single crystal form, and as a nanoparticulate catalyst is discussed. The first case concerns Pd alloyed with Cu, and here the reactivity with formic acid and ethanol is modified by the presence of Cu. However, both Cu and Pd maintain their elemental integrity for the reactions, and it is shown that the main alloying effect is one of dilution of Pd atoms, rather than by global electronic factors such as d-band shifting and filling. Similarly, when Pd is alloyed with Au, then the adsorption characteristics (sticking probability and uptake) for CO, O2, ethene and acetaldehyde are dominated by changes in the surface arrangement of the two atoms. Au mainly acts as an adsorption blocker, but to different degrees depending upon the nature of the adsorbing molecule and its demand for particular ensemble sizes. Finally, nanoparticulate Pd is considered, and the effect of alloying on high pressure methanol synthesis from CO2 and H2 is outlined. Pd on its own is not very selective, instead it mainly produces CO and methane. However, by supporting on oxides such as ZnO, Ga2O3 and In2O3 and by reducing in hydrogen, the Pd forms alloys, which then results in high selectivity to methanol. Again, this is ascribed to the dilution of the Pd ensembles at the surface, which are the cause of methane production.

Regeneration of methane splitting catalysts by interfacial hydrogenation

Methane splitting, also known as decomposition or pyrolysis, has a unique potential to accelerate the transition from the current carbon-based economy towards the foreseen hydrogen economy. Low-temperature catalytic methane splitting systems are unavailable due to fast catalyst deactivation, caused by solid carbon that encapsulates the catalyst. Catalyst regeneration must be performed to reactivate the catalyst and achieve a long-term operational lifetime. This can be accomplished by cyclically refeeding a portion of the produced hydrogen back to the catalyst, which promotes the hydrogenation of carbon atoms, preferentially at the interface between carbon deposits and catalytic nanoparticles. Interfacial hydrogenation ideally breaks the bonds that connect carbon allotrope products to the metal catalyst, causing the former to detach, and freeing the catalytic metal surface for further reaction. In this work, a proof-of-concept of this technology is provided, showing the full regeneration of a bulk-type Ni catalyst during 22 cycles of methane splitting, at 550 °C and 1 bar. Furthermore, a commercial SiO2-Al2O3-supported Ni catalyst has been used to study the regenerability of a highly active nanostructured material by interfacial hydrogenation, using different reactor designs. It has been demonstrated that regeneration is beneficial to improve the stability of Ni-based systems, at the applied working conditions. Nevertheless, tip-grown carbon nanotubes were considered as a cause of permanent deactivation, which could not be solved by refeeding hydrogen into the system.

Improving heat transfer prediction across catalytic SiC interface through a multiscale framework leveraging machine learning and data fusion techniques

Accurate aerothermal prediction under hypersonic flow conditions is crucial for any thermal protection materials design and engineering. The surface catalytic effect, where dissociated atoms recombine into their molecular forms at the air-solid interface, is an exothermic reaction and plays an important role in high-enthalpy aerodynamic environment prediction. Taking SiC, a widely recognized high-temperature thermal protection material as an example, a multiscale fusion approach for aerothermal prediction is proposed. The approach utilizes reactive molecular dynamics method to construct an interface catalysis model, and the Bayesian maximum entropy to integrate experimental and simulational data into an optimized database. Subsequently, using the radial basis function neural network algorithm, a machine learning-based reaction kinetics model with precise analysis of surface catalysis is trained. The obtained catalytic recombination efficiency is used as a boundary input for computational fluid dynamics simulation, enabling rapid and accurate prediction of hypersonic thermal environment. The result shows that the predicted surface heat flux by this novel approach is consistent with the benchmark studies, but comes with significantly reduced computation time. The stagantion heat flux predictions based on the assumptions of full catalytic wall, finite rate catalytic wall (from the proposed multiscale fusion method), and non-catalytic wall are determined to be 8.65×106 W/m2, 7.51×106 W/m2, and 4.02×106 W/m2, respectively. Comparing these with the wind tunnel benchmark value of 7.48×106 W/m2, the error from the proposed multiscale fusion method is 0.30 %, indicating significant enhancement in prediction accuracy through the proposed upscaling method. The new approach could not only reveal complex exothermic reaction processes at the interface, but also enhance the prediction accuracy at much higher computational efficiency, providing an alternative for multiscale modeling of complex flow and heat transfer at the interface.

Electric field components within a micro-scaled DBD measured by Stark shifting and splitting of helium lines

Abstract Atmospheric pressure dielectric barrier discharges (DBDs), such as the micro cavity plasma array (MCPA), have emerged as promising technologies for the conversion of volatile gases. These conversion processes’ effectiveness can be enhanced by integrating catalytically active surfaces. To deepen the understanding of the plasma-catalyst interaction, it is crucial to study the transport dynamics of charged species to the catalytic surface, which, due to collisions with neutrals, also directly affects the transport of reactive species to the catalyst. Thereby the transport of the charged species is in particular influenced by the electric field perpendicular to the catalytic surface. However, experimental data on the component-wise electric field strength within SDBDs are rare. To address this issue, we performed polarized optical emission spectroscopy on the shifting and splitting of the allowed 492.19 nm (1D → 1P0) and forbidden 492.06 nm (1F0 → 1P0) helium line pair. This diagnostic approach requires a non-radially symmetric geometry, which leads to an adapted reactor design of the MCPA allowing the side-on observation of the discharge. The discharge operates in pure helium at atmospheric pressure, utilizing a triangular excitation voltage with a frequency of 15 kHz and an amplitude of 600 V. We performed phase-resolved measurements of the electric field components with a temporal resolution of 1 µs. Our results revealed an electric field strength of approximately 22 kV cm−1 for the component perpendicular to the dielectric surface, while the component parallel to the dielectric surface is about 5 kV cm−1 larger during the decreasing potential phase of the applied voltage.

Industrial-grade electrocatalytic synthesis of glycine from oxalic acid and nitrate using a porous PbSnBi catalyst

Electrochemical transformation of oxalic acid and nitrate into glycine is an appealing way for valuable chemical synthesis and waste nitrate treatment. Currently, strategies to electrosynthesis of amino acid through catalyst design have been successfully developed, but it is still of huge challenge to realize industrial grade electrocatalytic synthesis of amino acid. Here, we develope an innovative electrochemical method to synthesize glycine from harnessing nitrate (NO3-) and oxalic acid in an aqueous electrolyte with a porous PbSnBi alloy catalyst. By means of construction the multiple catalytic sites and regulation electrode surface microenvironment, this strategy produces glycine with high Faraday efficiencies of 57.2 %, high yield rates of 1.125 mmol h−1 cm−2cat, and average current density up to 1 A cm−2 at −1.5 V vs. SCE potential after 2 h electrolysis. The recycled electrolysis experiment confirms its good stability and practical potential.

A Molecular View of Methane Activation on Ni(111) through Enhanced Sampling and Machine Learning.

A combination of machine learned interatomic potentials (MLIPs) and enhanced sampling simulations is used to investigate the activation of methane on a Ni(111) surface. The work entails the development and iterative refinement of MLIPs, initially trained on a data set constructed via ab initio molecular dynamics simulations, supplemented by adaptive biasing forces, to enrich the sampling of catalytically relevant configurations. Our results reveal that upon incorporation of collective variables that capture the behavior of the reactant molecule, as well as additional frames that describe the dynamic response of the catalytic surface, it is possible to enhance considerably the accuracy of predicted energies and forces. By employing enhanced sampling schemes in the refinement of the MLIP, we systematically explore the potential energy surface, leading to a refined MLIP capable of predicting density functional theory-level energies and forces and replicating key geometric characteristics of the catalytic system. The resulting free energy landscapes at several temperatures provide a detailed view of the thermodynamics and dynamics of methane activation. Specifically, as methane approaches and dissociates on the catalytic surface, the process involves the dynamic interplay of CH4 and the Ni catalyst that includes both enthalpic and entropic contributions. The progression toward the transition state involves a CH4 moiety that is increasingly restrained in its ability to rotate or translate, while the stage following the transition state is characterized by a notable rise of the Ni atom that interacts with the cleaved C-H bond. This leads to an increase in the mobility of the adsorbed species, a feature that becomes more pronounced at higher temperatures.

Recent Advances in Ammonia Synthesis Modeling and Experiments on Metal Nitrides and Other Catalytic Surfaces

In this review, we explore the recent progress in catalytic materials for the ammonia syntheses that are based on metal nitrides and other catalytic surfaces. It comprises a detailed overlook of the various techniques used in ammonia synthesis research and the state-of-the-art modeling techniques employed to investigate new reaction mechanisms and more efficient processes for sustainable ammonia synthesis production. The review is discussed in the context of the reaction mechanisms developed and the recent progress that has been made with respect to thermal, electrochemical, and photocatalytic ammonia synthesis.

Synergistic Pd‐Au Catalyst for Selective Electrosynthesis of Dimethyl Carbonate in Conjunction with High‐Rate Redox System

AbstractThis study reports ambient electrosynthesis of dimethyl carbonate with a palladium–gold catalyst. Material screening identifies a region of intermediate‐catalyst binding energy that facilitates interfacial electron and proton transfers for selective carbonylation, achieving a distinct maximum of 92% faradaic efficiency to dimethyl carbonate. Structural and electrochemical analyses suggest that the alloying of palladium and gold effectively modulates the CO* binding energy to the catalytic surface, in accord with subsequent computational studies. With an extended heterogeneous–homogeneous catalytic environment with a halide redox mediator, a remarkable partial current density of 52 mA cm−2 is observed for dimethyl carbonate for 100 h of continuous operation.

Computer-aided nanodrug discovery: recent progress and future prospects.

Nanodrugs, which utilise nanomaterials in disease prevention and therapy, have attracted considerable interest since their initial conceptualisation in the 1990s. Substantial efforts have been made to develop nanodrugs for overcoming the limitations of conventional drugs, such as low targeting efficacy, high dosage and toxicity, and potential drug resistance. Despite the significant progress that has been made in nanodrug discovery, the precise design or screening of nanomaterials with desired biomedical functions prior to experimentation remains a significant challenge. This is particularly the case with regard to personalised precision nanodrugs, which require the simultaneous optimisation of the structures, compositions, and surface functionalities of nanodrugs. The development of powerful computer clusters and algorithms has made it possible to overcome this challenge through in silico methods, which provide a comprehensive understanding of the medical functions of nanodrugs in relation to their physicochemical properties. In addition, machine learning techniques have been widely employed in nanodrug research, significantly accelerating the understanding of bio-nano interactions and the development of nanodrugs. This review will present a summary of the computational advances in nanodrug discovery, focusing on the understanding of how the key interfacial interactions, namely, surface adsorption, supramolecular recognition, surface catalysis, and chemical conversion, affect the therapeutic efficacy of nanodrugs. Furthermore, this review will discuss the challenges and opportunities in computer-aided nanodrug discovery, with particular emphasis on the integrated "computation + machine learning + experimentation" strategy that can potentially accelerate the discovery of precision nanodrugs.

In-situ polarization modulation IRRAS investigation of ammonia electrooxidation on Pt-Ir and Pt-Ru nanoparticles prepared on engineered catalyst supports

The catalytic activity and surface reactivity of monometallic Pt and bimetallic Pt-Ir and Pt-Ru nanoparticles, supported on two distinct Engineered Catalyst Supports (ECSs), were investigated for the Ammonia Electrooxidation Reaction (AmER) in alkaline media. XRD measurements confirmed alloy formation between Pt-Ir and Pt-Ru nanoparticles, as indicated by the shift of the (111) reflection to higher 2θ values. Cyclic voltammetry, linear sweep voltammetry, and chronoamperometry experiments were conducted to assess the catalytic activity of the Pt, Pt-Ir, and Pt-Ru electrocatalysts. All bimetallic catalysts exhibited lower onset potentials compared to Pt. The differing Tafel slopes between Pt (74 mV dec⁻¹), Pt-Ir (152 mV dec⁻¹), and Pt-Ru (118–197 mV dec⁻¹) suggest that alloying Pt with Ir or Ru alters the reaction mechanisms. Furthermore, the bimetallic Pt-Ir and Pt-Ru catalysts demonstrated greater tolerance for concentrated ammonia solutions relative to Pt.In-situ Polarization Modulation Infrared Reflection Absorption Spectroscopy (PM-IRRAS) provided insights into the formation of N-H species, azide anions (N₃⁻), and N-O compounds. For the Pt-Ru catalyst, an additional peak around ∼3600 cm⁻¹ was observed, corresponding to OH⁻ species. The PM-IRRAS results align with the Gerischer–Mauerer mechanism, indicating that partially dehydrogenated ammonia adsorbates act as active intermediates in the oxidation of ammonia over Pt-Ir and Pt-Ru catalysts.

Rationalizing the catalytic surface area of oxygen vacancy‐enriched layered perovskite LaSrCrO4 nanowires on oxygen electrocatalyst for enhanced performance of Li–O2 batteries

AbstractEfficient electrocatalysis at the cathode is crucial to addressing the limited stability and low rate capability of Li−O2 batteries. This study examines the kinetic behavior of Li−O2 batteries utilizing layered perovskite LaSrCrO4 nanowires (NWs) composed of lower oxidation states. Layered perovskite LaSrCrO4 NWs exhibited improved rate capability over a wide range of current densities and longer cycle life in Li−O2 batteries than V‐based layered perovskite (LaSrVO4) and simple perovskite (La0.8Sr0.2CrO3) NWs. X‐ray photoelectron spectroscopy and electrochemical surface area analyses showed that the observed performance variations primarily stemmed from active sites such as oxygen vacancies. In situ Raman analysis showed that these active sites significantly modulate the kinetics of oxygen reduction and evolution, which are related to LiO2 intermediate adsorption. Electrochemical impedance spectroscopy showed that the active sites in layered perovskite LaSrCrO4 NWs contributed to their high charge transfer capability and reduced polarization. This study presents an appealing method for the precise fabrication and analysis of Cr‐based layered perovskites, aimed at achieving highly efficient and stable bifunctional oxygen electrocatalysis.

Heterogeneous Photo-Fenton Degradation of Azo Dyes over a Magnetite-Based Catalyst: Kinetic and Thermodynamic Studies

Textile wastewater containing dyes poses significant environmental hazards. Advanced oxidative processes, especially the heterogeneous photo-Fenton process, are effective in degrading a wide range of contaminants due to high conversion rates and ease of catalyst recovery. This study evaluates the heterogeneous photodegradation of the azo dyes Acid Red 18 (AR18), Acid Red 66 (AR66), and Orange 2 (OR2) using magnetite as a catalyst. The magnetic catalyst was synthesized via a hydrothermal process at 150 °C. Experiments were conducted at room temperature, investigating the effect of catalyst dosage, pH, and initial concentrations of H2O2 and AR18 dye. Kinetic and thermodynamic studies were performed at 25, 40, and 60 °C for the three azo dyes (AR18, AR66, and OR2) and the effect of the dye structures on the degradation efficiency was investigated. At 25 °C for 0.33 mmolL−1 of dye at pH 3.0, using 1.4 gL−1 of the catalyst and 60 mgL−1 of H2O2 under UV radiation of 16.7 mWcm−2, the catalyst showed 62.3% degradation for AR18, 79.6% for AR66, and 83.8% for OR2 in 180 min of reaction. The oxidation of azo dyes under these conditions is spontaneous and endothermic. The pseudo-first-order kinetic constants indicated a strong temperature dependence with an order of reactivity of the type OR2 > AR66 > AR18, which is associated with the molecular size, steric hindrance, aromatic conjugation, electrostatic repulsion, and nature of the acid–base interactions on the catalytic surface.

The catalytic decomposition of aqueous Rhodamine B using porous carbons and persulfate: Influence of catalytic surface oxidation with ozone

The catalytic decomposition of aqueous Rhodamine B using porous carbons and persulfate: Influence of catalytic surface oxidation with ozone