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Catalyzing the Hydrogenation of Nitro Group to Amino Group                                                           From Agent-Based Models to Takagi–Sugeno Linear Differential
               using Greenly Synthesized Fe₃O₄ Nanoparticles for Water                                                           Equations (TS-LDEs):  A Fuzzy-Logic Bridge Between Discrete and

                                                   Purification                                                                                                   Continuous Dynamics





                                                       Author(s):                                                                                                             Author(s):


        Ahmad, Z. (University of Swabi), Rauf, A. (University of Swabi), Ajaj, R. (Abu Dhabi University), Zhang, H. (Changchun   Bouhanch, Z. (Sidi Mohamed Ben Abdellah University), El Moutaouakil, K. (Sidi Mohamed Ben Abdellah University), Tridane,
        Institute of qApplied Chemistry, Chinese Academy of Sciences), Bahattab, O. S. (University of Tabuk), Al-Awthan, Y. S.      A. (United Arab Emirates University), Laatabi, A. (Moulay Ismail University), Benrhmach, G. (Abu Dhabi University)
                                    (University of Tabuk), Hemeg, H. A. (Taibah University)
                                                                                                                                                                             Index Terms:
                                                     Index Terms:
                                                                                                                               Autonomous agents; Computational methods; Continuous time systems; Differential equations; Dynamics; Fuzzy inference;
        Catalyst activity; Efficiency; Iron oxides; Kinetic theory; Kinetics; Nanoparticles; Plant extracts; Purification; Rate constants;   Fuzzy rules; Large scale systems; Water resources; Agent-based model; Continuous dynamics; Discrete dynamics; Fuzzy-
        Remediation; Synthesis (chemical); % reductions; 4-Nitrophenol; Amino group; Catalyse; Euphorbium milli; Functional    Logic; Gray-box models; Grey-box models; Interpretability; Linear differential equation; Takagi-sugeno; Takagi–sugenu
        group transformations; Kinetic study; NaBH 4; Nitro group; Synthesised; Catalysis; Sodium Borohydride; 4 nitrophenol;                                           model; Sensitivity analysis
        Euphorbia milii extract; iron oxide nanoparticle; nitric oxide; plant extract; unclassified drug; catalysis; concentration
        (composition); nanoparticle; organic pollutant; phenol; reaction kinetics; water treatment; Article; enzyme activity;                                                  Abstract:
        Euphorbia; Euphorbia milii; Fourier transform infrared spectroscopy; hydrogenation; nonhuman; oxidative stress;
        pH; scanning electron microscopy; temperature; transmission electron microscopy; ultraviolet spectroscopy; water       This paper introduces the Takagi–Sugeno Latent Differential Equation (TS-LDE) framework as a gray-box modeling
                                               management; X ray diffraction                                                   paradigm that bridges the gap between the microscopic interpretability of agent-based models (ABM) and the analytical
                                                                                                                               tractability of continuous-time dynamical systems. Unlike traditional black-box simulations, TS-LDE explicitly captures

                                                        Abstract:                                                              latent system dynamics while preserving transparency in the rule-based structure, enabling both explanatory insight and
                                                                                                                               predictive capability. To demonstrate the applicability of the proposed framework, we present four illustrative domains,

        This study investigates the synthesis, characterization, and catalytic application of Fe3O4 nanoparticles (NPs) derived from   climate  dynamics  (CO–temperature  interaction),  epidemic  spreading  (SIR),  financial  contagion,  and  water/agricultural
        the Euphorbia milii leaf extract. The nanoparticles were synthesized by reducing iron salts (FeSO₄ and FeCl₃) in the presence   resource management, as pedagogical demonstrations of the TS-LDE identification pipeline. Each case study serves as a
        of the plant extract, with the formation of Fe3O4 confirmed through UV–visible, FTIR, and SEM analyses. The catalytic activity   step-by-step illustration of the modeling process: from ABM-inspired data generation, local parameter identification, and
        of Fe3O4 NPs was evaluated through the reduction of 4-nitrophenol (4NP) to amino phenol in the presence of sodium      fuzzy rule construction, to TS-LDE simulation and sensitivity analysis. Our results show that the TS-LDE models reproduce
        borohydride (NaBH4). The reaction exhibited a high reduction in efficiency, achieving 82.63% conversion at 20 min at a 0.1   the essential dynamics observed in their ABM counterparts while offering enhanced stability, smoother trajectories, and
        mM 4NP concentration. The reduction reached 80.36% at 0.2 mM 4NP after 24 min, highlighting the influence of substrate   greater interpretability. This gray-box approach thus provides a structured and computationally efficient alternative to
        concentration on the reaction rate. Optimization of reaction conditions revealed that a 2.0 mM NaBH4 concentration     purely agent-based simulations, serving as a unifying surrogate framework for the analysis of complex systems across
        achieved the highest reduction, with a 90.68% conversion within 14 min. Kinetic studies indicated that the reduction   domains. The proposed methodology highlights how data-driven yet interpretable dynamical modeling can support
        followed pseudo-first-order kinetics with an apparent rate constant (kapp) of 0.0962 min⁻1 and an R2 value of 0.9424. The   deeper understanding, policy assessment, and pedagogical exploration of interconnected socio-environmental and
        recyclability of the catalyst was also evaluated, showing that Fe3O4 NPs maintained 82.63% reduction efficiency in the first                                        financial  systems.
        cycle, which decreased to 71.09% in the third cycle. These findings highlights the potential of Fe3O4 NPs for environmental
                        and industrial applications, particularly in catalytic remediation of organic pollutants.                                                          Read the paper


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