Second-order Model Research Articles

Removal of Malachite Green Dye from Aqueous Solution by a Novel Activated Carbon Prepared from Baobab Seeds Using Chemical Activation Method.

Two activated carbons were synthesized from baobab seeds (BSs) using two activators, sulfuric acid (BS-AAC) and sodium hydroxide (BS-BAC), for dye removal from aqueous solutions. Malachite green (MG) was used as a model dye. SEM, FTIR, TGA, and surface area were used to characterize the feedstock and synthesis activated carbons. According to the SEM results, the surface morphology differed significantly from that of the raw material due to the many pores created by activating agents during carbonization. Various surface groups existed on the activated carbon surface as shown by FTIR analysis. An oxidation process utilizing hydrogen peroxide (H2O2) was investigated for MG. Various reaction parameters such as pH value, H2O2 concentration, and activated carbon dosage were investigated for the oxidative degradation of MG. By using BS-AAC and BS-BAC, 97.9% and 78% dye degradation efficiency in aqueous solutions, respectively, was achieved under optimal conditions. This study reveals that MG dye degradation increases with solution pH, making BS-AAC and BS-BAC ineffective at low pH values. However, degradation declines above pH 6. Based on the BS-AAC data, MG removal kinetics were fitted with a first-order kinetic model, while BS-BAC data were fitted with a second-order kinetic model. It was demonstrated that activating baobab with sulfuric acid can form a novel activated carbon that can quickly remove MG from aqueous solutions. The results showed that the removal of malachite green was over 89% for AC-AAC and 77% for AC-BAC, even after four regeneration cycles.

Synergistic fermentation of vitamin B2 (riboflavin) bio-enriched soy milk: optimization and techno-functional characterization of next generation functional vegan foods

Vitamin B2 (riboflavin) is essential for cellular growth, energy production, and redox potential. Certain lactic acid bacteria (LAB) can synthesize B2 in low levels in fermented products, however it is mostly retained inside the cell. This study aimed to develop B2-enriched soymilk by fermenting with B2-producing probiotic Lactiplantibacillus plantarum strains and traditional starter culture Lactobacillus acidophilus NCIM2902. Using the central composite design approach, processing parameters were optimized for enhanced B2 content and probiotic count. Six independent variables were assessed: temperature (A: 35–45 °C), pH (B: 4–6), time (C: 3–18 h), and inoculum size for strains L. plantarum MTCC 25432 (D: 1–2%), L. plantarum MTCC 25433 (E: 1–2%), and L. acidophilus NCIM 2902 (F: 1–2%). The second-order model effectively predicted responses, identifying optimal fermentation conditions for developing vitamin B2-enriched soymilk: temperature (A) 36 °C, pH (B) 5.5, fermentation time (C): 11 h, inoculum size for L. plantarum MTCC 25432 (D): 2%, MTCC 25433 (E): 2%, and L acidophilus NCIM (F): 0.43%. These conditions resulted in a threefold increase in B2 concentration (481 µg/L) while maintaining a probiotic count of 9 logs CFU/mL. Additionally, techno-functional characterization, including rheology and texture profile analysis, showed that enhanced protease activity of co-cultured LAB improved protein hydrolysis (6259 nm), positively impacting the water holding capacity (WHC) and overall acceptability of the fermented soymilk. This optimized fermentation process represents a novel approach to developing nutritionally enhanced dairy-free soy products with high riboflavin content, utilizing the synergistic benefits of co-fermentation by two riboflavin-producing L. plantarum strains and traditional starter culture of L. acidophilus. This advancement is particularly significant for lactose-intolerant and vegan consumers who may lack sufficient dietary sources of Vitamin B2.

Kinetics of lead sorption by farm yard manure

Aim: Removal of lead through adsorption and immobilization using processed or composted farm wastes is one of the effective methods to reclaim contaminated waste water. This study deals with the lead removal potential of farm yard manure (FYM) from contaminated waste water. Methodology: A batch incubation experiment was conducted to study the effect of sorbent dosage, initial lead concentration, and incubation intervals on lead adsorption and desorption and the data was fitted to various kinetic models. Results: The rate of lead adsorption increased with increasing sorbent dosage and time with a mean adsorption rate of 78.1%. Fitting the adsorption data to various kinetic models revealed that, pseudo second-order kinetic model described the adsorption process better than other models and chemisorption was the dominant mechanism of lead removal. The lead desorption rate also decreased with sorbent dosage and lead concentration at successive time intervals with a mean of 0.37%, which further confirmed its efficiency in lead removal. Interpretation: Farm yard manure could be utilised as an effective biosorbent for removing lead from wastewaters. Key words: Adsorption, Farm yard manure, Kinetic models, Lead

Cell Morphology, Material Property and Ni(II) Adsorption of Microcellular Injection-Molded Polystyrene Reinforced with Graphene Nanoparticles.

Graphene's incorporation into polymers has enabled the development of advanced polymer/graphene nanocomposites with superior properties. This study focuses on the use of a microcellular foamed polystyrene (PS)/graphene (GP) nanocomposite (3 wt%) for nickel (II) ion removal from aqueous solutions. Adsorption behavior was evaluated through FTIR, TEM, SEM, TGA, and XRD analyses. Key factors, including initial ion concentration, pH, temperature, and sorbent dosage, were examined. Results showed optimal nickel removal at specific pH levels with removal efficiency decreasing from 91 to 80% as Ni (II) concentrations increased from 10 to 100 mg/L. The adsorption capacity improved from 11 to 130 mg/g. Equilibrium data aligned with Langmuir and Freundlich isotherm models, while adsorption kinetics followed a second-order kinetic model. These findings highlight the potential of PS/GP nanocomposites for nickel ion removal, offering a promising solution for small-scale industrial applications.

Viscoelastic wetting transition: beyond lubrication theory

Abstract The dip-coating geometry, where a solid plate is withdrawn from or plunged into a liquid pool, offers a prototypical example of wetting flows involving contact-line motion. Such flows are commonly studied using the lubrication approximation approach which is intrinsically limited to small interface slopes and thus small contact angles. Flows for arbitrary contact angles, however, can be studied using a generalized lubrication theory that builds upon viscous corner flow solutions. Here we derive this generalized lubrication theory for viscoelastic liquids that exhibit normal stress effects and are modelled using the second-order fluid model. We apply our theory to advancing and receding contact lines in the dip-coating geometry, highlighting the influence of viscoelastic normal stresses for contact line motion at arbitrary contact angle.

Psychometric study of the Maslach Burnout Inventory-Student Survey on Thai university students

The Maslach Burnout Inventory-Student Survey (MBI-SS) is a widely used instrument to assess burnout levels, which provides valuable insight into their psychological well-being. Accurate measurement of burnout is crucial for developing interventions aimed at reducing stress and promoting mental health among students. This study aims to validate the MBI-SS when applied among Thai university students and to examine whether the psychometric properties of the scale are consistent with the original conceptual framework. A total of 413 undergraduate students from Thailand participated in the study, with 57.63% females and 42.37% males, and a mean age 21.75 years (SD = 2.40). The MBI-SS was translated into Thai by following rigorous procedures to maintain accuracy and cultural relevance. The factorial structure of the MBI-SS Thai version was evaluated using confirmatory factor analysis (CFA) for both a three-factor model and second-order factor model. The Thai version of the MBI-SS demonstrated a three-dimensional structure consistent with the original inventory, with excellent model fit indices. All item factor loadings exceeded the recommended threshold, and the instrument showed high internal consistency, establishing it a valuable tool for future research and practical application in educational settings aimed at addressing and reducing student burnout.

Sustainable Removal of Phenol from Aqueous Media by Activated Carbon Valorized from Polyethyleneterephthalate (PET) Plastic Waste

PET, one of the most commonly used plastics, presents significant environmental challenges due to its non-biodegradable nature. To address this, we developed a sustainable method to convert PET waste into high-performance activated carbon via chemical activation with phosphoric acid (H3PO4). The produced activated carbon was analyzed utilizing X-ray diffraction (XRD), Fourier-transform infrared spectroscopy (FT-IR), scanning electron microscopy (SEM), nitrogen adsorption/desorption (BET), energy-dispersive X-ray (EDX), and Raman spectroscopy. The activated carbon produced had a macroporous architecture with a substantial surface area, pore diameter, and pore volume of 655.59 m2/g, 3.389 nm, and 0.120 cm3/g, respectively. The adsorption isotherm of activated carbon for phenol conformed to the Langmuir model, signifying single-layer adsorption with a maximal capacity of 114.94 mg/g, while the kinetic adsorption adhered to the second-order model at an optimal pH of 7. The study highlights the sustainable benefits of mitigating plastic waste pollution while producing a cost-effective and eco-friendly adsorbent for water treatment applications. This research underscores the potential for recycling PET waste into valuable materials for environmental remediation.

Kinetic study on the extraction of ethanimidic acid from hibiscus flowers using microwave assisted hydrodistillation

Microwave extraction of active compounds from plants offers an efficient alternative to traditional methods, highlighting the need to investigate its modeling and kinetic mechanisms for comprehensive understanding. This study evaluated kinetic models for the microwave-assisted hydrodistillation (MAHD) of ethanimidic acid from hibiscus flowers. Experimental data, including ethanimidic acid concentration as a function of time, power, and solid-to-liquid ratio, were analyzed using three-parameter empirical models. The second-order model demonstrated superior accuracy (R² = 0.954), outperforming the first-order model, and effectively described the two-stage extraction process: washing and diffusion. The second-order kinetic model ensures precise control of ethanimidic acid extraction, enabling efficient scalability for industrial production and consistent quality for pharmacological applications, emphasizing sustainable and cost-effective manufacturing practices. This model provides a robust framework for advancing MAHD applications in the industrial production of bioactive compounds, promoting innovation in sustainable technologies, and enhancing the economic feasibility of bioactive compound recovery.

Optimizing COD reduction in dairy wastewater treatment using magnetic coagulant derived from Moringa oleifera

In wastewater treatment scenarios, traditional coagulants are becoming increasingly complex and raising environmental concerns. This has led to the exploration of magnetized plant-derived coagulant as an alternative. In this paper, coagulation parameters such as coagulant dosage and pH were optimized through response surface methodology (RSM) based on a central composite design (CCD) employing a magnetic coagulant derived from Moringa oleifera seeds (M. oleifera–CoFe2O4). The optimized response variable during the treatment of dairy wastewater was the chemical oxygen demand (COD) reduction. The response surface methodology revealed a statistically significant second-order polynomial model (R2 99.24%) for maximizing COD reduction. The maximum COD reduction achieved was 76.13% under optimal conditions with coagulant dosage of 14.24 g/L and pH of 9.38. The results indicated that magnetic coagulant derived from M. oleifera seeds demonstrated significant potential and can be used in an efficient and eco-friendly process for dairy wastewater treatment. Keywords: coagulation, dairy wastewater, flocculation, magnetic coagulant, Moringa Oleifera.

Predicting Soil Salinity Based on Soil/Water Extracts in a Semi-Arid Region of Morocco

Soil salinity is a major constraint to soil health and crop productivity, especially in arid and semi-arid regions. The most accurate measurement of soil salinity is considered to be the electrical conductivity of saturated soil extracts (ECe). Because this method is labor-intensive, it is unsuitable for routine analysis in large soil sampling campaigns. This study aimed to identify the best models to estimate soil salinity based on ECe in relation to a rapid electrical conductivity (EC) measurement in soil/water (referred to as S:W henceforward) extracts. We evaluated the relationship between ECe and the ECS:W extract ratios (1:1, 1:2, and 1:5) in salt-affected soils from the semi-arid Sehb El Masjoune region of Morocco. The soil salinity in this region is 0.5 to 235 dS/m, as determined by the ECe method. A total of 125 soil samples, from topsoil (0–15 cm) and subsoil (15–30 cm) with mainly fine to medium textures, were analyzed using linear, logarithmic, and second-order polynomial regression models. The models included all samples or grouped samples according to soil texture (fine, medium) or specific textural classes. The mean ECe values were 2.6, 3.1, and 7.9 times greater than the EC of 1:1, 1:2, and 1:5 S:W extracts, respectively. Polynomial regression models had the best predictive accuracy, R2 = 0.98, and the lowest root mean square error of 10.6 to 10.7 dS/m for the ECS:W extract ratios of 1:5 and 1:2. The polynomial models could represent the non-linear relationships between ECe and salinity indicators, especially in the 80–170 dS/m salinity range, where other models typically underestimate the salinity. These results confirm that advanced regression techniques are suitable for predicting soil salinity in a salt-affected semi-arid region. The site-specific models outperformed previously published models, because they consider the spatial variability and heterogeneity of the salinity in the study area explicitly. This confirms the importance of calibrating soil salinity models according to the local soil and environmental conditions. Consequently, we can undertake soil salinity assessments in hundreds of samples by using the simple, rapid ECS:W extraction method as a direct indicator of EC and extrapolate to ECe with a polynomial regression model. Our approach enables the widespread soil salinity assessments that are needed for land-use planning, irrigation management, and crop selection in salt-affected landscapes.

Waste PET bottle-derived carbon for defluorination of fluoride-polluted water

ABSTRACT This study synthesises expanded graphite (EG) from graphitised carbon from waste polyethylene terephthalate (PET) bottles. The adsorbent material was characterised using FTIR, XRF, XRD, SEM, Raman Spectroscopy, and BET surface area analysis. The synthesised EG defluorinated wastewater, utilising response surface methodology (RSM) for experimental design and optimisation. XRD patterns confirmed the successful synthesis of graphite and EG, demonstrating structural modifications. Raman spectra indicated higher crystalline order in EG, with D and G band shifts and an increased ID/IG intensity ratio from 0.89–1.04. BET analysis revealed a specific surface area of 247.1 m²/g. . FTIR analysis showed abundant functional groups, particularly hydroxyl (-OH) and alkene (C = C). Batch adsorption experiments revealed that fluoride adsorption onto EG depended on pH, time, and initial fluoride concentration. Optimal conditions for fluoride removal, determined using RSM with central composite design (CCD), demonstrated a maximum fluoride removal rate of 97%. Isotherm data fitted both Langmuir and Freundlich model, and kinetics data aligned well with the pseudo-first-order model. ANOVA showed significant effects of contact time, pH, adsorbent dose, and initial fluoride concentration on removal efficiency. The model's R² value of 0.98 and lack of fit value of 0.1554 confirmed the quality of the second-order polynomial model. Optimal conditions for maximum fluoride removal efficiency of 97% were validated at 5 mg/L fluoride concentration, pH 4, adsorbent dose of 5 g/L, and a contact time of 30 min. Therefore, the present study demonstrated efficient fluoride-polluted water treatment using waste-derived EG.

Classification of Buried Objects From Ground Penetrating Radar Images by Using Second-Order Deep Learning Models

Classification of Buried Objects From Ground Penetrating Radar Images by Using Second-Order Deep Learning Models

A "cyclodextrin-salicylic acid-chitosan" bifunctional monomer magnetic hydrophilic imprinted sandwich gel for targeted adsorption and slow release of ginkgolic acid.

This study aims to address the challenge of detoxifying ginkgolic acid and transform it from waste into a valuable resource. By using pseudo-template molecular imprinting technology to chemically modify polysaccharide materials, we developed a polysaccharide-based molecular imprinted material (MMCC-CD/CS-MIP) for the targeted separation and controlled release of ginkgolic acid. Under optimal conditions, MMCC-CD/CS-MIP demonstrated excellent adsorption performance (Qmax=47.786mgg-1) and desorption performance (QD=42.33mgg-1), with a desorption rate of 88.58%. In addition, the material exhibited outstanding selectivity, stability, recyclability, antibacterial activity, and sustained-release properties, with a cumulative release rate of 95.57% over 72h. The release data followed the Korsmeyer-Peppas model, while the adsorption behavior fit a multi-layer heterogeneous adsorption model (Freundlich model) and conformed to a second-order kinetic model. Thermodynamic analysis confirmed that the adsorption of ginkgolic acid by MMCC-CD/CS-MIP is both feasible and spontaneous. MMCC-CD/CS-MIP provides a promising solution for the detoxification of medicinal components.

A potential eco-friendly degradation of methyl orange by water-ball (sodium polyacrylate) stabilized zero valent iron nanoparticles.

This study presents the synthesis and application of water-ball (sodium polyacrylate) stabilized zero-valent iron nanoparticles (wb@Fe0) for the eco-friendly degradation of Methyl Orange (MO). The nanoparticles were prepared using a chemical reduction method using NaBH4. Characterization techniques including Field Emission Scanning Electron Microscopy (FESEM), Energy Dispersive X-ray Spectroscopy (EDS), Fourier Transform Infrared Spectroscopy (FTIR), X-ray Photoelectron Spectroscopy (XPS), and X-ray Diffraction (XRD) were employed to analyze the morphology, elemental composition, valent state and crystallinity of the nanoparticles. The catalytic performance was evaluated under standard conditions, with a maximum degradation efficiency of 94% achieved for a 0.05mM MO solution using 10mg of the catalyst, 0.1mM NaBH4, at neutral pH and room temperature within 10min. Optimal degradation occurred at 40°C and pH 6. The catalyst demonstrated excellent recyclability, maintaining activity over ten reuse cycles. Kinetic studies revealed that the degradation followed first-order kinetics with an R2 value of 0.8907 and a rate constant of 0.3708. Though with a lower R2 value (0.6884), the second-order kinetics model indicated the highest rate constant of 2.6522. Regression and ANOVA analysis confirmed the accuracy of the reaction protocol. This study highlights the potential of water-ball stabilized zero-valent iron nanoparticles for effective dye pollutant removal and degradation, offering a promising approach for environmental remediation.

Synchronization of two coupled massive oscillators in the time-delayed Kuramoto model.

We examine the impact of the time delay on two coupled massive oscillators within the second-order Kuramoto model, which is relevant to the operations of real-world networks that rely on signal transmission speed constraints. Our analytical and numerical exploration shows that time delay can cause multi-stability within phase-locked solutions, and the stability of these solutions decreases as the inertia increases. In addition to phase-locked solutions, we discovered non-phase-locked solutions that exhibit periodic and chaotic behaviors, depending on the amount of inertia and time delay.

Foam investigation and optimization by Response Surface Methodology of electrocoagulation process for textile wastewater decolorization in single-channel reactor

This research investigates foam formation during decolorization of synthetic textile effluent by the electrocoagulation process in a single-channel reactor. This study aims to optimize the process by examining multiple responses, including the foam layer thickness, under different operating conditions such as current intensity (0.5-2.5A), recirculation flowrate (40-100L.h−1), electrolysis time (10-40min), and active electrode area (69-621cm2).The active electrode area and the recirculation flowrate impact foam distribution, with thicker foam layers observed in compartments housing active electrodes, influenced by the reactor's geometry. Current intensity and electrolysis time are key factors affecting foam shape and volume. A higher recirculation flowrate (100L.h−1) reduces foam volume in active compartments due to increased mixing, which hinders effective liquid-solid separation. The foam thickness in the last active compartment increased 6.5 times as electrolysis time extended from 10 to 60minutes at 1.5A when 5 pairs of electrodes are active.Response Surface Methodology was employed to optimize the electrocoagulation process using Central Composite Design as a second-order mathematical model. Optimal conditions were identified at a current intensity of 1A, electrolysis time of 32.5min, recirculation flowrate of 65.5L.h−1, and 9 pairs of electrodes (621cm2). These conditions yielded a predicted decolorization efficiency of 42.72%, energy consumption of 26Wh.m−3, total foam layer volume of 166.92cm3, and last active compartment foam volume of 5.24cm3.

Plasma effects on bacterial time-kill dynamics; insights from a PKPD modelling analysis.

In vitro time-kill curve (TKC) experiments are an important part of the pharmacokinetic- pharmacodynamic (PKPD) characterisation of antibiotics. Traditional TKCs use Mueller-Hinton broth (MHB), which lacks specific plasma components that could potentially influence the bacterial growth and killing dynamics, and affect translation to in vivo. This study aimed to evaluate the impact of plasma on the PKPD characterisation of two antibiotics; cefazolin and clindamycin. TKC experiments were conducted in pure MHB, and MHB spiked with 20% and 70% human plasma. Plasma protein binding (PPB) data were available, and a linear model described cefazolin's PPB, while clindamycin's PPB was best described by a second-order polynomial model. PKPD models were developed based on pure MHB and described drug effects using an Emax model, with consideration of adaptive resistance for cefazolin. The observed bacterial growth and killing in the plasma-spiked MHB TKC data was insufficiently described when applying the developed PPB and PKPD models. In plasma spiked MHB, a growth delay was observed, estimated to 0.25 h (20% plasma), or 2.90 h (70% plasma) for cefazolin, and 0.64 h (20% plasma), or 1.40 h (70% plasma) for clindamycin. Furthermore, the drug effect was higher than expected in plasma-spiked MHB, with bacterial stasis and/or killing at unbound concentrations below MIC, necessitating drug effect parameter scaling (C50 for cefazolin, Hill coefficient for clindamycin). The findings highlight significant differences in bacterial growth and killing dynamics between pure MHB and plasma-spiked MHB and exemplify how PKPD modelling may be used to improve the translation of in vitro results.

Study of microwave-assisted extraction of polyphenol from Phyllanthus urinaria

ABSTRACTBackground: Phyllanthus urinaria, found extensively in tropical Asian countries, possesses numerous biological activities attributed to its polyphenol compounds.Objective: This study aims to optimize polyphenol extraction from Phyllanthus urinaria using microwave assistance.Materials and Methods: First, the effects of parameters including ethanol concentration (used as the solvent) (40–80% v/v), material-to-solvent ratio (1:10–1:50 w/v), extraction time (30–150 minutes), and extraction temperature (30–70°C) on conventional extraction were investigated. Subsequently, the effects of microwave pretreatment prior to extraction during the microwave-assisted extraction (MAE) process, including microwave power (100–700 W) and irradiation time (1–9 minutes), were evaluated. Optimal extraction conditions were determined based on total flavonoid content (TFC), total phenolic content (TPC), and antioxidant activity (DPPH scavenging assay) of the extract. The second-order kinetic model was also used to compare the efficiency of extraction methods.Results: Results indicated that a microwave power of 250 W and irradiation time of 3 minutes were optimal for material pretreatment prior to extraction. Subsequent extraction parameters included ethanol concentration of 60% (v/v), solvent-to-material ratio of 1:40 (w/v), extraction temperature of 50°C, and extraction time of 60 minutes. Under these conditions, the extract exhibited maximum levels of TPC (277.99 ± 5.47 mgGAE/gDW), TFC (38.90 ± 0.58 gQE/gDW), and TEAC (280.08 ± 0.75 µmolTE/gDW), which were 22.5%, 36.1%, and 29.4% higher, respectively, compared to the control without microwave treatment.Conclusion: Furthermore, the second-order kinetic model demonstrated higher initial extraction rate (h), extraction rate constant (k), and extraction capacity (Ce) for MAE compared to conventional extraction.Keywords: Antioxidant capacity; kinetic model; microwave-assisted extractio; phyllanthus urinaria; polyphenol

Psychological Distress and Online Academic Difficulties: Development and Validation of Scale to Measure Students' Mental Health Problems in Online Learning.

In the present study, a short instrument (eight-item self-report, five-point Likert scales) was developed and validated to assess self-perceived mental health problems in online learning. The participants were 398 Romanian university students from nine different faculties. The factor structure of the scale was assessed using Exploratory Factor Analysis (Principal Axis Factoring extraction method) and Confirmatory Factor Analysis. The high goodness-of-fit indices validated a second-order factor model of mental health problems, with two distinct but correlated sub-constructs, psychological distress, and online academic difficulties, integrated under a single higher-level factor. Psychological distress comprises indicators such as anxiety and stress, while online academic difficulties contain, for instance, indicators such as decreased performance, fatigue or lack of motivation. The results of applying multiple assessment criteria showed good reliability (e.g., McDonald's omega), as well as convergent validity (e.g., Average Variance Extracted) and discriminant validity (e.g., the heterotrait-monotrait ratio of correlations) of the scale. Also, correlations analysis between mental health problems occurred in online learning context and other measures indicated a strong negative relation with online course satisfaction and weak negative relations with subjective academic performance, perceived social competence, and perceived digital competence. In conclusion, the scale appears to be a valid instrument for measuring some negative mental health outcomes in online learning, perceived by university students. The implications of the results and limitations of this study are also discussed. In conclusion, the scale has multiple possible applications, the most important being (1) the assessment of mental health problems both in ordinary online learning situations and in emergency ones, which would allow the early detection of these issues, (2) the possibility of assessing relations between the sub-constructs of the scale and other psychological constructs of interest in scientific research, and (3) the feedback for teaching staff involved in the online learning system.

New Insights on Iron-Trimesate MOFs for Inorganic As(III) and As(V) Adsorption from Aqueous Media.

Arsenic contamination of water endangers the health of millions of people worldwide, affecting certain countries and regions with especial severity. Interest in the use of Fe-based metal organic frameworks (MOFs) to remove inorganic arsenic species has increased due to their stability and adsorptive properties. In this study, the performance of a synthesized Nano-{Fe-BTC} MOF, containing iron oxide octahedral chains connected by trimesic acid linkers, in adsorbing As(III) and As(V) species was investigated and compared with commercial Basolite®F300 MOF. Despite their similarities in composition, they exhibit distinct structural characteristics in their porosity, pore size, and surface areas, which affected the adsorption processes. The kinetic data of the adsorption of As(III) and As(V) by both Fe-MOFs fitted the pseudo second-order model well, with the kinetic constant being higher for Basolite®F300 given its higher porosity. Intraparticle diffusion was, in both cases, the rate controlling step with the contribution of film diffusion in the adsorption processes, which achieved equilibrium after 1 h. The maximum adsorption capacity for As(V), 41.66 mg g-1, was obtained with Basolite®F300 at the 6.5-10 pH range, whereas Nano-{Fe-BTC} showed a different behaviour as maximum adsorption (14.99 mg g-1) was obtained at pH 2. However, both adsorbents exhibited the same performance for As(III) adsorption, which is not adsorbed at pH < 9. The Langmuir adsorption isotherm model fitted well for As(III) and As(V) adsorption by Nano-{Fe-BTC} and As(III) by Basolite®F300, whereas the Freundlich model fitted best for As(V) given its superior structural properties.