Theory Modeling Research Articles

Development and validation of an instrument for assessing secondary students’ transdisciplinary STEM practices

BackgroundGiven that limited well-developed instruments are available to assess students’ transdisciplinary STEM practices (T-STEMP), this study aims to develop and validate an instrument for examining secondary students’ T-STEMP competence. According to the T-STEMP assessment framework proposed in our previous study, we developed items and validated the items using Bayesian structural equation modeling (BSEM) and item response theory (IRT).ResultsFirst, the structure of T-STEMP has been justified, that the four design phases are related to a common third-order factor: knowledge-based reasoning and each design phase is composed of three key design challenges. The goodness of fit indices indicated that a two-parameter logistic (2PL) graded response model could fit the data well. The discrimination parameters indicated that most of the items for different grades performed well in distinguishing between students with various ability levels. The Cronbach’s alpha also indicated that the instrument had good reliability in terms of internal consistency.ConclusionsThe model of one third-order factor with four second-order factors and 12 first-order factors was justified as the fitted model representing the structure of the T-STEMP instrument. It means that the four design phases are related to knowledge-based reasoning and each design phase is composed of three key design challenges. The IRT findings show that Taiwanese students may have basic T-STEMP competence, but the breadth and depth of their responses to the key design challenges need to be advanced. Implications for further studies and suggestions for STEM teaching are also provided.

Modelling and controlling outputs of nonlinear systems using feedback

This study aimed to analyze methods for modeling and controlling the output of nonlinear systems using feedback, analytical methods, mathematical modeling, and differential equation theory. Key findings include the mathematical characterization of equations and the analysis of system stability and asymptotic behavior. The study explored various methods for addressing problems in nonlinear systems, emphasizing the importance of identifying effective solutions. The research highlights the significance of developing effective approaches to solving complex problems involving nonlinear systems. Feedback is essential for controlling and correcting dynamic processes in systems with nonlinearities. The study’s key finding is the mathematical characterization of equations describing nonlinear systems, providing insight into system structure and behavior under different parameters. Analyzing stability and asymptotic behavior allows for assessing system reliability and predicting long-term stability. This study contributes to the scientific understanding and development of methods for modeling and controlling nonlinear systems using feedback.

A Review on High-speed Electric Spindle Dynamics Modeling and Vibration Response Research

Background: One of the main directions of modern technology in the field of precision machining is high-speed operation. The spindle system is commonly utilized in this kind of operation, and the electric spindle is the main preference among high-speed machine tool spindles. Objective: High-speed electric spindle vibration characteristics affect the machining accuracy of the machine tool and the quality of the workpiece, so the research on high-speed electric spindle vibration characteristics has important engineering practical significance. Methods: The research status of high-speed electrospindle at home and abroad has been summarized in this paper. Combined with the patents related to the dynamics modelling of electrospindle, the research on the dynamics modelling of high-speed electrospindle is analyzed. On this basis, the computational and analytical methods for the vibration modelling of the electrospindle, including the transfer matrix method and the finite element method, are investigated, the theoretical foundations of these methods are discussed in depth, and the advantages and disadvantages of the methods are evaluated. The applicability and limitations of the two methods are also compared. Results: The analysis has shown that the current research on the vibration characteristics of highspeed electrospindle is mainly based on mechanical modal analysis and electromagnetic analysis. At present, the dynamic modeling of the electrospindle mainly includes bearing modeling, shaft bearing modeling, spindle-case modeling, electrospindle electromechanical coupling modeling, electrospindle thermal coupling modeling, etc. The correctness of the modelling theory is verified through experimental and simulation results. Although these models tend to be perfected, they are still insufficient in the case of multiple influencing factors coupling and need further development. Conclusion: Finally, through the analysis of the patent and dynamic characteristics related to the high-speed electric spindle, thermal deformation, magnetic tension, material, and other factors should be considered comprehensively, and these factors should be coupled to establish an overall dynamics model for the vibration characteristics analysis. The dynamic modelling, vibration modelling method, and vibration characteristics of the high-speed electric spindle have been summarized in this study, and the outlook is presented.

Automated System for Evaluating Alternatives for Developing Innovative IT Projects

Software engineering occupies a prominent place in the theory and practice of simulation modeling, which necessitates scientific research in the field of methodological principles for forming software product quality. The problem of determining the optimal option for software development is one of the key ones in the field of information technology because it determines the quality of the final product and the efficiency of project management. The article considers the concept of developing an automated system, the basis of which is the software for assessing alternatives in the process of creating innovative IT projects. The main goal of the study is to model alternatives and select the optimal option for the process of creating an IT project using modern methodological approaches. For this purpose, the methods of ontological analysis, expert evaluation, multi-criteria optimization, pairwise comparisons and multi-factor selection of alternatives are applied. In the course of the research, a subset of Pareto factors is singled out and alternative development options are formed based on the method of linear convolution of criteria. The proposed methodology allows for assessing the importance of key factors and selecting the optimal option for the software development process. As a result, the developed approach contributes to strategic planning and increases the transparency of the decision-making process. The key result of the research is the created software product that allows one to automate the procedure for selecting the optimal solution for the IT project development process, providing reliable support for simulation modeling and increasing the efficiency of project management. The proposed methodology creates a new paradigm for making informed decisions regarding systems for creating complex software complexes.

Validation of a Single Item Measure for Financial Toxicity Screening in Patients With Breast Cancer.

Financial toxicity (FT) has been linked to higher symptom burden and poorer clinical outcomes for patients with cancer. Despite the availability of validated tools to measure FT, a simple screen remains an unmet need. We evaluated item 12 ("My illness has been a financial hardship to my family and me") of the COmprehensive Score for Financial Toxicity (COST) measure as a single-item FT screening measure. In this secondary analysis, 711 patients with cancer (690 with breast cancer) were recruited via a web-based survey from a philanthropic organization. COST items 1-11 were scored according to Functional Assessment of Chronic Illness Therapy scoring guidelines, with lower scores indicating worse FT. Analyses focused on establishing a correlation, examining item properties, and sensitivity/specificity of item 12 relative to the total COST score. Item 12 had a correlation of r = 0.53 with the COST-11 score, and an increase of one point on item 12 is associated with a decrease of approximately three total points on the full scale (b, 3.35; P < .001; adjusted R2, 0.28). Item analysis with the graded-response item in response theory modeling showed very good discrimination (a, 2.096) for item 12, indicating that it can reliably distinguish between low and high FT in patients. Sensitivity ranged between 75.6% and 95.7% on all item 12 thresholds to screen positive for FT using two COST cutoffs as criteria. Maximizing both sensitivity and specificity was to be found for higher item 12 scores. To our knowledge, this is the first validation of a single-item screening measure for FT. Overall, these results illustrate that item 12 from the COST measure is a good candidate for a single-item screener. Clinicians can choose among item 12 screening thresholds depending on their tolerance for low specificity.

Depth of focus as a function of spherical aberration using adaptive optics in pseudophakic subjects.

To measure visual acuity at three different defocus planes in pseudophakic subjects with varying levels of spherical aberration induced by an adaptive optics visual simulator. The study aimed to simulate Extended Depth of Focus (EDOF) intraocular lenses (IOLs). Private hospital (IMO, Barcelona, Spain). Observational case series; modelling theory. Through-focus visual acuity was measured in 26 pseudophakic subjects (age 63 ± 10 years old) with an adaptive optics visual simulator optimized for clinical use (VAO, Voptica SL, Murcia, Spain). Measurements were made under five different conditions of induced negative spherical aberration: 0, -0.07, -0.15, -0.23 and -0.30 μm (pupil diameter: 4.5 mm). Results were also modelled using ray tracing simulations. On average, depth of focus was extended when spherical aberration increased from -0.07 to -0.15 μm (4.5 mm pupil diameter). Some indivisuals (27%) experienced improved depth of focus with higher magnitudes of spherical aberration, while others (23%) exhibited no benefit from increased (negative) SA, as visual acuity dropped below acceptable levels. Depth of focus calculations based on ray tracing showed general agreement with the measurements. The visual conditions of EDOF IOLs were artificially recreated in a population of pseudophakic patients implanted with a monofocal IOL. The variability seen across subjects in visual acuity at different defocus planes suggests that visual simulators might be capable of screening subjects for suitability and tolerability of these advanced technology lenses.

Bourdieu’s theory of economic practice and organisational modelling

Bourdieu’s theory of economic practice and organisational modelling

Latent motor growth trajectories of term and preterm infants based on caregiver report

ABSTRACT Early motor development is a key predictor of development in other skill domains and specific neurodevelopmental disorders, but it is typically measured as achievement of milestones rather than rate of development. To explore the value of the latter approach, this study utilized a novel caregiver report method to examine differences in the developmental trajectory of motor development in term-born compared to preterm-born infants. Caregiver-infant dyads (331 term, 240 preterm) were followed from birth through 12 months (48% female; 6.4% Hispanic; 34.1% Black; 10.3% Mixed or Biracial; and 48.3% White). Longitudinal Item Response Theory (IRT) modeling was used to compare growth trajectories of motor skills between term and preterm infants. The moderating effects of biological sex on group differences also were examined. The main effect for term status was significant. Preterm infants exhibited slower rates of growth in motor ability over the first 12 months compared with term infants. Differences in rate of growth were significant by 6 months of age. In the term group only, females exhibited more rapid growth than males in motor ability. Findings indicate that caregiver report yields reliable estimates of growth in the latent trait of motor ability, with slower rate of growth in infants born preterm. Estimates of latent growth in motor ability may provide more sensitive measures of neurodevelopmental risk and a method to examine response to treatment.

A Density Functional Theory (DFT) Modeling Study of NO Reduction by CO over Graphene-Supported Single-Atom Ni Catalysts in the Presence of CO2, SO2, O2, and H2O.

The mechanisms of NO reduction by CO over nitrogen-doped graphene (N-graphene)-supported single-atom Ni catalysts in the presence of O2, H2O, CO2, and SO2 have been studied via density functional theory (DFT) modeling. The catalyst is represented by a single Ni atom bonded to four N atoms on N-graphene. Several alternative reaction pathways, including adsorption of NO on the Ni site, direct reduction of NO by CO, decomposition of NO to N2O followed by reduction of N2O to N2, formation of active oxygen radical O*, and reduction of O* by CO, were hypothesized and the energy barrier corresponding to each of the reaction steps was calculated using DFT. The most probable pathway was found to be that NO adsorbed on the Ni site decomposes via the Langmuir-Hinshelwood mechanism to form N2O and subsequently N2, leaving an active oxygen radical (O*) on the surface, which is then reduced by CO. The large adsorption energy of NO on the Ni site results in strong resistance to CO2, SO2, O2, and water vapor. The activation energy of N2O reduction to N2 was found to be larger than those of NO decomposition to N2O and active oxygen radical reduction by CO, illustrating that the step of N2O reduced to N2 is the rate-controlling step.

Mining exceptional Rasch models

Abstract The detection of differential item function (DIF) is a crucial task in item response theory modeling. In recent years, machine learning (ML) techniques are increasingly used for this task, for example, using model-based recursive partitioning (MOB) techniques. For example, Rasch trees are a combination of MOB and Rasch models. In this paper, we propose an alternative ML technique for DIF detection in Rasch models, called exceptional model mining in Rasch models (RaschEMM). While Rasch trees and RaschEMM share an algorithmic base and the goal to identify covariate-based subgroups, they have different goals. Rasch trees aim at identifying a “global model of the data”, whereas RaschEMM aims at identifying exceptional subgroups. After a general and comprehensive presentation of RaschEMM, we present the results from two simulation studies and provide an applied example.

The Temperature-Dependent Tight Binding Theory Modelling of Strain and Composition Effects on the Electronic Structure of CdSe- and ZnSe-Based Core/Shell Quantum Dots.

We propose a temperature-dependent optimization procedure for the second-nearest neighbor (2NN) sp3s* tight-binding (TB) theory parameters to calculate the effects of strain, structure dimensions, and alloy composition on the band structure of heterostructure spherical core/shell quantum dots (QDs). We integrate the thermoelastic theory of solids with the 2NN sp3s* TB theory to calculate the strain, core and shell dimensions, and composition effects on the band structure of binary/ternary CdSe/Cd(Zn)S and ZnSe/Zn(Cd)S QDs at any temperature. We show that the 2NN sp3s* TB theory with optimized parameters greatly improves the prediction of the energy dispersion curve at and in the vicinity of L and X symmetry points. We further used the optimized 2NN sp3s* TB parameters to calculate the strain, core and shell dimensions, and composition effects on the nanocrystal bandgaps of binary/ternary CdSe/Cd(Zn)S and ZnSe/Zn(Cd)S core/shell QDs. We conclude that the 2NN sp3s* TB theory provides remarkable agreement with the measured nanocrystal bandgaps of CdSe/Cd(Zn)S and ZnSe/Zn(Cd)S QDs and accurately reproduces the energy dispersion curves of the electronic band structure at any temperature. We believe that the proposed optimization procedure makes the 2NN sp3s* TB theory reliable and accurate in the modeling of core/shell QDs for nanoscale devices.

A response time-based mixture item response theory model for dynamic item-response strategies.

Educational researchers have a long-lasting interest in the strategies examinees employ when responding to items in an assessment. Mixture item response theory (IRT) modeling is a popular class of approaches to studying examinees' item-response strategies. In the present study, we introduce a response time (RT)-based mixture IRT model for flexible modeling of examinee-and-item-specific item-response strategies. We posit that examinees may alternate between ability-based and non-ability-based strategies across different test items. Our proposed model identifies such within-examinee strategy switches without the need to predefine the non-ability-based strategies. Instead, our proposed approach allows for inferring the nature of these strategies from model parameter estimates. We illustrated the proposed approach using empirical data from PISA 2018 Science test and evaluated it through simulation studies. We concluded the article with discussions of limitations and future research directions.

A Novel Mechanism-Equivalence-Based Tweedie Exponential Dispersion Process for Adaptive Degradation Modeling and Life Prediction.

Accurately predicting the remaining useful life (RUL) of critical mechanical components is a central challenge in reliability engineering. Stochastic processes, which are capable of modeling uncertainties, are widely used in RUL prediction. However, conventional stochastic process models face two major limitations: (1) the reliance on strict assumptions during model formulation, restricting their applicability to a narrow range of degradation processes, and (2) the inability to account for potential variations in the degradation mechanism during modeling and prediction. To address these issues, we propose a novel mechanism-equivalence-based Tweedie exponential dispersion process (ME-based TEDP) for adaptive degradation modeling and RUL prediction of mechanical components. The proposed model enhances the original Tweedie exponential dispersion process (TEDP) by incorporating degradation mechanism equivalence, effectively capturing the correlation between model parameters. Furthermore, it improves prediction accuracy and interpretability by employing a dynamic testing-modeling-predicting strategy. Application of the ME-based TEDP model to high-speed rail bogie systems demonstrates its effectiveness and superiority over existing approaches. This study advances the theory of degradation modeling and significantly improves the precision of RUL predictions.

Modulation of PI3K/AKT signaling and DFT modeling via selected pharmaceutical compounds attenuates carrageenan-induced inflammation and oxidative stress in rats.

The main goal of the current study is to estimate the in vivo anti-inflammatory/antioxidant ability of four selected pharmaceutical compounds: bisoprolol (Biso), piracetam (Pirc), clopidogrel (Clop), and cinnarizine (Cinna). Indomethacin (Indo) was used as areference drug to perform a realistic comparison between the four compounds and the Indo in vivo through tracking PI3K/AKT signaling and computational chemistry via density functional theory (DFT) modeling to analyze the electrostatic potential across the molecule and provide insight into the regions for receptor binding of the studied compounds. To achieve the safe dose of these compounds, cytotoxicity was performed against isolated adipose tissue-derived mesenchymal stem cells (ADMSCs) using MTT assay. In vivo determination of anti-inflammatory/antioxidant biochemical and genetic parameters of the tested compounds against rats' paw carrageenan (Carg)-induced inflammation was assessed. The data showed that there was no significant different in cell viability of ADMSCs until dose 10 µg/ml, so we used this concentration for in vivo experiments. Carg high significantly increased the volume of the paw edema at 120 min and 180 min compared to the control group (p < 0.01). Cinna (10 mg/kg), relatively similar to Indo, was the most anti-inflammatory compound among others, followed by Clop and Pirc, where they decreased the volume of the paw edema significantly (p < 0.01) at 120 min and 180 min compared to the Carg-group. Microscopic examination confirmed the above results indicating that paw tissue of Carg-group shows edema formation and massive inflammation compared with control. In comparison to the control group, Carg high significantly increased the malondialdehyde (MDA) levels (p < 0.01), whereas, at the concentration 10 mg/kg of the tested compounds, the MDA concentrations significantly reduced, especially the Clop, Cinna, and Indo-treated groups. On the contrary, total antioxidant capacity (TAC) and 5-lipoxygenase (5-LOP) concentrations were significantly decreased in Carg-group (p < 0.01) compared with control. Cyclooxygenase-2 (COX-2), phosphoinositide 3-kinase (PI3k), and protein kinase B (AKT) gene expressions were high and significantly upregulated in Carg-group compared to control,whilethe tested compounds downregulated theirexpressions compared to the Carg-group. Moreover, COX-2, interleukins (IL-10/IL-6/IL-4), PI3k, and AKT protein concentrations were high and significantly increased in Carg-group compared to control, however thetestedcompounds were high and significantly decreased their concentrations compared to the Carg-group. DFT modeling aligned with the biochemical data and indicated that Cinna emerges as the most reactive drug with high polarizability (302.741 a.u.), a relative small FMOs energy gap (ΔE 5.002 eV), relative low molecular hardness (2.501 eV), relative high softness (0.400 eV-1), and distinct nucleophilic/electrophilic interaction sites, indicating strong specific interactions with biological receptor. In conclusion, this study revealed the ability of Cinna to potentially suppress inflammation in in vivo Carg-induced rat paw inflammation model through inhibition of PI3K/AKT signaling and DFT modeling mediated by oxidative stress and inflammatory mediators.

New Hydrazone Derivatives Based on Pyrazolopyridothiazine Core as Cytotoxic Agents to Colon Cancers: Design, Synthesis, Biological Evaluation, and Molecular Modeling.

In this research, a series of novel hydrazone derivatives based on pyrazolopyridothiazinylacetohydrazide were designed, synthesized, and evaluated for their in vitro cytotoxic potency on several human colon cancer cells (HTC116, HT-29, and LoVo). After MTT and SRB assays four of the most active derivatives: hydrazide GH and hydrazones GH7, GH8, and GH11, were chosen for further investigation. Hydrazone GH11 had the highest cytotoxic activity (IC50 values of c.a. 0.5 μM). Additionally, the impact of novel derivatives on the oxidative stress level, apoptosis induction, and modulation of inflammation in colon cancer cells was examined. In all studies, the activity of the derivatives increased in order GH < GH7 < GH8 < GH11. At the same time, most of the research was conducted on compounds combined with apple pectin (PC). The most interesting observation was that all the studied derivatives applied together with PC showed significantly higher activity than observed in the case of using PC, hydrazide, or hydrazones separately. Finally, computational chemistry methods (molecular modeling and Density Functional Theory - DFT) were used to complement the experimental studies.

Statistical-mathematical analysis of childhood caries in children between the ages of one and thirteen years as a function of diet and oral hygiene

Objective. Determine was statistical mathematically the percentage (%) of prevalence of childhood caries in children between the ages of one and thirteen years as a function of diet and oral hygiene wearing the Empirical Modeling Theory of Bronstein &amp; Semendiaev. Design. Correlational, predictive and transversal study. Participants. Patients from one year to thirteen years old were considered and distributed in four groups from one to four years old; from five to seven years old, from eight to ten years old and from eleven to thirteen years old; respectively. Twelve children have been considered in each group and we have worked with the average percentage of prevalence of each group; in which each average percentage of prevalence was contrasted with age during eight consecutive years. Main measurement. Each dispersogram showed that the first and third groups have similar behavior (sigmoidal or logistic) and groups two and four showed different behavior to groups one and three, but similar behavior between them (quadratic). Results. The statistical-mathematical analysis for groups one and three turned out tobe good, with coefficients of determination of r2=0,9752 and r2=0,9347respectively, and the relationship between time t(years) and the percentage (%) of prevalence of childhood caries (P), for children between 1 and 4 years old and 8 to 10 years old is real, there is a non-significant difference, the predictive models have high estimation, there is a "very strong correlation" between the elapsed time (t) and the percentage (%) of prevalence of childhood caries (P).Conclusions. The statistical-mathematical analysis for groups two and four proved to be good, with coefficients of determination of r2=0,9595 and r2=0,8562. respectively, and the relationship between time, t(years) and the percentage (%) of prevalence of childhood caries (P), for children between five and seven years and eleven to thirteen years, is real, there is a non-significant difference, the predictive models have high estimation, there is a "very strong correlation" between the elapsed time (t) and the percentage (%) prevalence of childhood caries (P).

In Search of an Integrative Method to Study Unconscious Processing: An Application of Bayesian and General Recognition Theory Models to the Processing of Hierarchical Patterns in the Absence of Awareness.

The dissociation between conscious and unconscious perception is one of the most relevant issues in the study of human cognition. While there is evidence suggesting that some stimuli might be unconsciously processed up to its meaning (e.g., high-level stimulus processing), some authors claim that most results on the processing of subliminal stimuli can be explained by a mixture of methodological artefacts and questionable assumptions about what can be considered non-conscious. Particularly, one of the most controversial topics involves the method by which the awareness of the stimuli is assessed. To address this question, we introduced an integrative approach to assess the extent to which masked hierarchical stimuli (i.e., global shapes composed of local elements) can be processed in the absence of awareness. We combined a priming task where participants had to report global or local shapes, with the use of subjective and objective awareness measures collected either in a separate block (offline), or trial-by-trial during the main task (online). The unconscious processing of the masked primes was then evaluated through two different novel model-based methods: a Bayesian and a General Recognition Theory modeling approach. Despite the high correlation between awareness measures, our results show that the use of alternative approaches based on different theoretical assumptions leads to diverging conclusions about the extent of the unconscious processing of the masked primes.

Associations among externalizing psychopathology, personality, and behavioral traits: Models of an externalizing spectrum in youth.

Consistent evidence has documented the cross-sectional and longitudinal associations of externalizing psychopathology with personality and behavioral traits, suggesting the presence of a broad, underlying liability to externalizing. In one of the first studies of its kind, we use a large, representative sample of youth (N = 2,245 twins and their siblings) to evaluate the evidence of an externalizing spectrum model, which includes psychopathology, personality, and behavioral traits and spans normal and pathological variation. We examine evidence for the inclusion of 15 candidate traits, from the domains of general and pathological personality, temperament, and aggression, in a model that includes dimensions of common childhood externalizing psychopathology. Using a combination of structural equation modeling and item response theory analyses, we found strong to moderate evidence for including the narcissism and impulsivity dimensions of psychopathic traits; reactive, proactive, and relational aggression; and agreeableness and conscientiousness from the five-factor model of personality. These traits were reliable indicators of the externalizing spectrum, as evidenced by their shared variance with externalizing symptoms, strong factor loadings, and high information. In addition, these traits indexed the externalizing spectrum at higher and lower levels of the latent trait relative to the symptoms alone, highlighting the value of including them. Many of our findings replicate and extend work conducted in adult samples, suggesting developmental continuity of externalizing. Broadly speaking, these findings have important implications for the conceptualization, measurement, and treatment of externalizing in youth. (PsycInfo Database Record (c) 2025 APA, all rights reserved).

Enhancement of Solubility and Bioactivity of Zonisamide Through Supramolecular Inclusion With β‐Cyclodextrin: A Comprehensive Analytical and Computational Study

AbstractThis study delved into the interaction between the neurological drug zonisamide (ZNS) and β‐cyclodextrin (β‐CD) using an innovative coprecipitation technique, leading to the formation of a stable 1:1 supramolecular inclusion complex (IC). Analytical tools, including 1H NMR, FTIR spectroscopy, ESIMS, UV–vis spectroscopy, and SEM, revealed the structural details of this assembly. Job's plot confirmed the stoichiometric ratio, whereas binding constants were determined through UV–vis spectroscopic titrations using the Benesi–Hildebrand method. ESIMS data corroborated these findings. Molecular modeling and density functional theory (DFT) calculations provided additional evidence of complexation, demonstrating the stability of the IC through adsorption energy analysis. Biological evaluations showed enhanced antioxidant and antimicrobial activities of the ZNS+β‐CD complex compared to pure ZNS, reflecting its improved properties. Encapsulation within β‐CD significantly increased the solubility of ZNS in aqueous media, enabling lower effective dosages and reducing potential side effects. The study's experimental and computational findings aligned seamlessly, affirming the encapsulation of ZNS within β‐CD and advancing our understanding of supramolecular chemistry. This work highlights the potential of β‐CD to optimize drug solubility and therapeutic efficiency, offering a promising approach for improved drug delivery systems.

Mechanistic study of the adsorption capabilities of heavy metals on the surface of ferrihydrite: batch sorption, modeling, and density functional theory.

Ferrihydrite (Fh), a widely distributed mineral in the environment, plays a crucial role in the geochemical cycling of elements. This study used experimental and computational approaches to investigate the adsorption behavior of seven heavy metal ions on Fh. The pH edge analysis revealed that the adsorption capacity followed the order: Pb2+ > Cu2+ > Zn2+ > Cd2+ > Ni2+ > Co2+ > Mn2+, with Pb2+ showed the highest adsorption. Competitive adsorption was observed in multi-metal systems, and adsorption isotherms confirmed that Pb2+ and Cu2+ exhibited significantly higher equilibrium adsorption capacities than the other ions. Diffuse Layer Model (DLM) analysis indicated that for most heavy metals (HMs), [triple bond, length as m-dash]FesOM and [triple bond, length as m-dash]FewOM were the predominant adsorption species, while for Pb2+, [triple bond, length as m-dash]FesOPb dominated. Density Functional Theory (DFT) calculations were employed further to investigate the molecular interactions between HMs and Fh. The DFT results revealed that the distribution of surface iron sites on Fh strongly influences the adsorption process. Larger metal ions, such as Pb2+, form stronger coordination bonds with hydroxyl groups on the Fh surface, leading to distinct adsorption mechanisms compared to smaller ions. These findings, combining experimental and computational data, emphasize the critical role of surface iron site distribution and ion size in governing the adsorption behavior of HMs on Fh.