Search Results (242)

This study presents a hybrid sensor placement methodology that combines criterion-based candidate selection with advanced optimization algorithms. Four established selection criteria—modal kinetic energy (MKE), modal strain energy (MSE), modal assurance criterion (MAC) sensitivity, and mutual information (MI)—are used to evaluate DOF sensitivity and generate candidate pools. These are followed by one of four optimization algorithms—greedy, genetic algorithm (GA), particle swarm optimization (PSO), or simulated annealing (SA)—to identify the optimal subset of sensor locations. A key feature of the proposed approach is the incorporation of constraint dynamics using the Udwadia–Kalaba (U–K) generalized inverse formulation, which enables the accurate expansion of structural responses from sparse sensor data. The framework assumes a noise-free environment during the initial sensor design phase, but robustness is verified through extensive Monte Carlo simulations under multiple noise levels in a numerical experiment. This combined methodology offers an effective and flexible solution for data-driven sensor deployment in structural health monitoring. To clarify the rationale for using the Udwadia–Kalaba (U–K) generalized inverse, we note that unlike conventional pseudo-inverses, the U–K method incorporates physical constraints derived from partial mode shapes. This allows a more accurate and physically consistent reconstruction of unmeasured responses, particularly under sparse sensing. To clarify the benefit of using the U–K generalized inverse over conventional pseudo-inverses, we emphasize that the U–K method allows the incorporation of physical constraints derived from partial mode shapes directly into the reconstruction process. This leads to a constrained dynamic solution that not only reflects the known structural behavior but also improves numerical conditioning, particularly in underdetermined or ill-posed cases. Unlike conventional Moore–Penrose pseudo-inverses, which yield purely algebraic solutions without physical insight, the U–K formulation ensures that reconstructed responses adhere to dynamic compatibility, thereby reducing artifacts caused by sparse measurements or noise. Compared to unconstrained least-squares solutions, the U–K approach improves stability and interpretability in practical SHM scenarios. Full article

In this work, HNTs@ZIF-67 composites were synthesized using the in situ growth method and incorporated into 6FDA-TFMB to prepare mixed-matrix membranes (MMMs). Scanning electron microscope (SEM) and transmission electron microscope (TEM) proved that the HNTs@ZIF-67 composite not only retained the hollow structure of HNTs, but also formed a continuous ZIF-67 transport layer on the surface of HNTs. The results of gas permeability experiments showed that with the increase in HNTs@ZIF-67 incorporation, the He permeability and He/CH₄ selectivity of MMMs showed a trend of increasing first and then decreasing. When the loading is 5 wt%, the He permeability and He/CH₄ selectivity of MMMs reach 116 Barrer and 305, which are 22.11% and 79.41% higher than the pure 6FDA-TFMB membrane. The results of density functional theory (DFT) and Monte Carlo (MC) calculations reveal that He diffuses more easily inside ZIF-67, HNTs and 6FDA-TFMB than CH₄, and ZIF-67 shows larger adsorption energy with He than HNTs and 6FDA-TFMB, indicating that He is easily adsorbed by ZIF-67 in MMMs. Based on experimental and molecular simulation results, the mechanism of HNTs@ZIF-67 improving the He/CH₄ separation performance of MMMs was summarized. With the advantage of a smaller molecular kinetic diameter, He can diffuse through ZIF-67 on the tube orifice of HNTs@ZIF-67 and enter the HNTs’ hollow tube for rapid transmission. At the same time, He can also be rapidly transferred in the continuous ZIF-67 transport channel layer, which improves the He permeability and the He/CH₄ selectivity of MMMs. Full article

Chemiresistive gas sensors have gained significant attention and have been widely applied in various fields. However, the gap between experimental observations and fundamental sensing mechanisms hinders systematic optimization. Despite the critical role of modeling in explaining atomic-scale interactions and offering predictive insights beyond experiments, existing reviews on chemiresistive gas sensors remain predominantly experimental-centric, with a limited systematic exploration of the modeling approaches. Herein, we present a comprehensive overview of the modeling approaches for chemiresistive gas sensors, focusing on two critical processes: the reception and transduction stages. For the reception process, density functional theory (DFT), molecular dynamics (MD), ab initio molecular dynamics (AIMD), and Monte Carlo (MC) methods were analyzed. DFT quantifies atomic-scale charge transfer, and orbital hybridization, MD/AIMD captures dynamic adsorption kinetics, and MC simulates equilibrium/non-equilibrium behaviors based on statistical mechanics principles. For the transduction process, band-bending-based theoretical models and power-law models elucidate the resistance modulation mechanisms, although their generalizability remains limited. Notably, the finite element method (FEM) has emerged as a powerful tool for full-process modeling by integrating gas diffusion, adsorption, and electronic responses into a unified framework. Future directions highlight the use of multiscale models to bridge microscopic interactions with macroscopic behaviors and the integration of machine learning, accelerating the iterative design of next-generation sensors with superior performance. Full article

In the present work, we address the theory of the lattice-gas model to the study of intercalation materials by using a novel kinetic Monte Carlo (kMC) algorithm for the simulation of an electrochemical method of everyday use in R&D laboratories: constant-current chrono-potentiometric measurements. The main aim of the present approach is to show how to use these atomistic simulations to study intercalation materials used as electrodes in alkali-ion batteries under galvanostatic conditions. The framework can be applied to related areas. To accomplish this, we explain the electrochemical background, linking the continuum scale with the microscopic events of discrete simulations. A comprehensive theoretical approach developed in a previous work is used as a reference for this aim. The galvanostatic kMC algorithm proposed is explained in detail and is subject to validation tests. The present work may serve as a basis for future implementations of kMC under galvanostatic conditions to study phenomena beyond the applicability of simulations on the continuum scale. Full article

The objective of this study is to develop a kinetic model that incorporates time-delay mechanisms to describe the gradual release behavior of pectin. Three models were used: modified Peleg, logistic, and second-order linear with time delay (SOPDT), to represent the extraction kinetics of grapefruit peels at 60, 70, and 90 °C. Model fitting was performed using a hybrid methodology combining Monte Carlo simulations with genetic algorithms. The SOPDT model provided the best fit, with the lowest squared error values (J = 7.06 at 60 °C, 5.63 at 70 °C, and 8.71 at 90 °C), requiring only two parameters to represent the entire process. In contrast, the other models required six. The maximum pectin yield reached over 120% at 90 °C, compared to <80% at lower temperatures. These results demonstrate the potential of the SOPDT model for efficient process description and control. Full article

This study aims to mitigate slope-collapse hazards that threaten life and property at the Lujiawan resettlement site in Wanbi Town, Dayao County, Yunnan Province, within the Guanyinyan hydropower reservoir. It integrates centimeter-level point-cloud data collected by a DJI Matrice 350 RTK equipped with a Zenmuse L2 airborne LiDAR (Light Detection And Ranging) sensor with detailed structural-joint survey data. First, qualitative structural interpretation is conducted with stereographic projection. Next, safety factors are quantified using the limit-equilibrium method, establishing a dual qualitative–quantitative diagnostic framework. This framework delineates six hazardous rock zones (WY1–WY6), dominated by toppling and free-fall failure modes, and evaluates their stability under combined rainfall infiltration, seismic loading, and ambient conditions. Subsequently, six-degree-of-freedom Monte Carlo simulations incorporating realistic three-dimensional terrain and block geometry are performed in RAMMS::ROCKFALL (Rapid Mass Movements Simulation—Rockfall). The resulting spatial patterns of rockfall velocity, kinetic energy, and rebound height elucidate their evolution coupled with slope height, surface morphology, and block shape. Results show peak velocities ranging from 20 to 42 m s⁻¹ and maximum kinetic energies between 0.16 and 1.4 MJ. Most rockfall trajectories terminate within 0–80 m of the cliff base. All six identified hazardous rock masses pose varying levels of threat to residential structures at the slope foot, highlighting substantial spatial variability in hazard distribution. Drawing on the preceding diagnostic results and dynamic simulations, we recommend a three-tier “zonal defense with in situ energy dissipation” scheme: (i) install 500–2000 kJ flexible barriers along the crest and upper slope to rapidly attenuate rockfall energy; (ii) place guiding or deflection structures at mid-slope to steer blocks and dissipate momentum; and (iii) deploy high-capacity flexible nets combined with a catchment basin at the slope foot to intercept residual blocks. This staged arrangement maximizes energy attenuation and overall risk reduction. This study shows that integrating high-resolution 3D point clouds with rigid-body contact dynamics overcomes the spatial discontinuities of conventional surveys. The approach substantially improves the accuracy and efficiency of hazardous rock stability assessments and rockfall trajectory predictions, offering a quantifiable, reproducible mitigation framework for long slopes, large rock volumes, and densely fractured cliff faces. Full article

The spontaneous deposition of platinum ($Pt$) atoms on $Au\left(111\right)$ surfaces is systematically investigated through kinetic Monte Carlo simulations within the Embedded Atom Model framework. The kinetic model aims to capture both stoichiometric, atomic-scale interactions and the more relevant processes that describe the kinetics of a physical problem. Various deposition rates are examined, encompassing a thorough exploration of $Pt$ adsorption up to a coverage degree of $\theta =0.25$. The resulting 2D islands exhibit a ramified structure, mirroring the experimental methodologies. For the first time, this study extensively analyzes the dependence of both the mean island size and island density on spontaneous deposition, thereby offering valuable insights into the intricate dynamics of the system. Full article

In chemical vapor deposition (CVD)-mediated graphene growth, copper foil serves as both a catalyst for methane decomposition and as a substrate for graphene nucleation and growth. Due to the low solubility of carbon in copper and the ease of transferring graphene from its surface, copper—particularly the Cu(111) facet—is widely favored for high-quality, monolayer graphene synthesis. In this article, the thermodynamic processes involved in methane dissociation and graphene nucleation on the Cu(111) surface were investigated using density functional theory (DFT). Molecular dynamics simulations were performed for structural optimization and to evaluate the reaction energies. Additionally, the average adsorption energies (ΔEad) of carbon clusters with varying atomic numbers on the Cu(111) surface were calculated. The graphene growth process was further modeled using the kinetic Monte Carlo (KMC) method to simulate carbon atom migration and nucleation dynamics. Thermodynamic analysis based on equilibrium component data was conducted to examine the influence of key operational parameters—temperature, pressure, and the CH₄/H₂ partial pressure ratio—on the graphene deposition rate. Full article

The present study aims to prepare a composite via pyrolysis, based on sodium alginate (SA) and a natural clay collected from the eastern region of Morocco, specifically the OUJDA area (C.O.R), for use in the disposal process of emerging pharmaceuticals. The strategy of rapid microwave heating followed by nitrogen calcination at 500 °C was successfully applied to produce the pyrolyzed carbonaceous materials. The removal of paracetamol (PCT) by adsorption on the carbonaceous clay (ca-C.O.R) composite was investigated to determine the effect of operating parameters (initial contaminant concentration, contact time, pH, and temperature) on the efficiency of PCT removal. The nanocomposite was analyzed using various techniques, including the nitrogen gas adsorption–desorption isothermal curve, X-ray diffraction, scanning electron microscopy, and Fourier transform infrared spectroscopy. Three models were used to describe the kinetic adsorption, and it was found that the experimental kinetic data fit well with a pseudo-second-order kinetic model with a coefficient of determination R² close to one, a nonlinear chi-square value close to zero, and a reduced root mean square error RMSE (R² → 1, X² → 0 and lower RMSE). The adsorption was best described by the Sips isotherm. The ca-C.O.R composite achieved a PCT removal efficiency of 91% and a maximum adsorption capacity of 122 mg·g⁻¹ improving on the performance of previous work. Furthermore, the variation in enthalpy (∆H°), Gibbs free energy (∆G°), and entropy (∆S°) indicated that the adsorption is exothermic in nature. The composite has shown promising efficiency for the adsorption of PCT as a model of emergent pollutant from aqueous solutions, making it a viable option for industrial wastewater treatment. Using Density Functional Theory (DFT) along with the 6-31G (d) basis set, the geometric structure of the molecule was determined, and the properties were estimated by analyzing its boundary molecular orbitals. The adsorption energy of PCT on MMT and ca-C.O.R studied using the Monte Carlo (MC) simulation method was −120.3 and −292.5 (kcal·mol⁻¹), respectively, which shows the potential of the two adsorbents for the emerging product. Full article

In the present paper, we discuss the thermodynamic and dynamic phase transition properties of the kinetic Blume–Capel model with spin-1, defined on non-regular lattices, namely decorated simple cubic, decorated triangular, and decorated square (Lieb) lattice geometries. Benefiting from the recent results obtained for the thermodynamic phase transitions of the aforementioned lattice topologies [Azhari, M. and Yu, U., J. Stat. Mech. (2022) 033204], we explore the variation of the dynamic order parameter, dynamic scaling variance, and dynamic magnetic susceptibility as functions of the amplitude, bias, and period of the oscillating field sequence. According to the simulations, a second-order dynamic phase transition takes place at a critical field period for the systems with zero bias. A particular emphasis has also been devoted to metamagnetic anomalies emerging in the dynamic paramagnetic phase. In this regard, the generic two-peak symmetric behavior of the dynamic response functions has been found in the slow critical dynamics (i.e. dynamic paramagnetic) regime. Our results yield that the characteristics of the dynamic phase transitions observed in the kinetic Ising model on regular lattices can be extended to such non-regular lattices with a larger spin value. Full article

Background/Objectives: Levofloxacin dosing guidelines recommend adjustments only when the creatinine clearance (CrCl) is <50 mL/min. We hypothesized that further dose stratification based on CrCl could improve therapeutic outcomes, even when the CrCl ≥ 50 mL/min. This study aimed to develop a population pharmacokinetic (PK) model of levofloxacin in healthy adults and identify optimal dosing regimens. Methods: In this prospective, open-label study, 12 healthy adults received a single dose of levofloxacin. Plasma concentrations were measured using liquid chromatography–tandem mass spectrometry. A population PK model was developed with nonlinear mixed-effects modeling, and Monte Carlo simulations were performed to identify optimal dosing regimens. Results: A two-compartment model with first-order kinetics best described the levofloxacin PK profiles. The CrCl was associated with a variation in clearance and lean body mass, with a variation in peripheral volume of distribution. Simulations identified optimal regimens, defined as those achieving a probability of target attainment of at least 90% for the target unbound 24-hour area under the curve at steady state to minimum inhibitory concentration ratio (fAUC/MIC), which differed by pathogen (≥30 for Gram-positive bacteria; ≥100 for Gram-negative bacteria). For the ratio fAUC/MIC ≥ 30 and an MIC of 0.5 mg/L, 500 mg daily was optimal for patients with a CrCl of 50–89 mL/min. For the ratio fAUC/MIC ≥ 100, 1000 mg daily was required in the same CrCl range and MIC value. Conclusions: The population PK model incorporating CrCl and lean body mass improved the prediction of levofloxacin PKs. Refining current dosing recommendations by incorporating stratified CrCl and MIC values could optimize therapeutic outcomes, particularly for patients with a CrCl ≥ 50 mL/min. Full article

The presence of abundant water vapor in industrial organic waste gases greatly reduces the selective adsorption of volatile organic pollutants (VOCs). The polarity of the adsorbent and VOC molecules plays an important role in the adsorption process, especially in the presence of water vapor. In this paper, commercial coconut shell activated carbon (CSC) was modified by a thermal reduction treatment to obtain heat-treated coconut shell activated carbon (HCSC). CSC and HCSC exhibited similar pore structure characteristics but differed significantly in surface oxygen content (10.97% and 7.55%, respectively). Dynamic adsorption breakthrough experiments were conducted to determine the dynamic adsorption capacities of toluene on both adsorbents under varying relative humidity levels. HCSC demonstrated superior toluene/water vapor adsorption selectivity. Further analyses of toluene adsorption kinetics, activation energy, and water vapor adsorption isotherms revealed that the lower surface oxygen functional group content of HCSC resulted in a weaker surface polarity, facilitating the adsorption of weakly polar toluene. This was attributed to stronger toluene–HCSC interactions and weaker water–HCSC interactions. The dynamic adsorption capacities of three VOCs with varying polarities were also tested on HCSC. The observed VOC/water vapor adsorption selectivity had the following order: toluene > n-heptane > 1,2-dichloroethane. Grand Canonical Monte Carlo (GCMC) simulations were employed to quantify the relationship between the adsorption selectivity of eight VOCs with varying polarities and their molecular polarity. The results indicated a decrease in adsorption selectivity with increasing VOC polarity. A mechanistic analysis suggests that more polar VOCs prefer to adsorb polar oxygen-containing functional groups, competing with water molecules for adsorption sites. Under high humidity, hydrogen bonding leads to the formation of water clusters, exacerbating this competition. This research holds significant implications for the efficient selective adsorption of VOCs with varying polarities in humid industrial conditions. Full article

In this work, the simulation of deoxidation–oxidation of oxygen vacancies (V_Os) in an oxide matrix with embedded conductive nanocrystals (c-NCs) is carried out for the development of bipolar resistive switching memories (BRSMs). We have employed the three-dimensional kinetic Monte Carlo (3D-kMC) method to simulate the RS behavior of BRSMs. The c-NC is modeled as fixed oxygen vacancy (f-V_O) clusters, defined as sites with zero recombination probability. The three-dimensional oxygen vacancy configuration (3D-V_OC) obtained for each voltage step of the simulation is used to calculate the resistive state and the electrical current. It was found that the c-NC reduces the voltage required to switch the memory state from a high to a low resistive state due to the increase in a nonhomogeneous electrical field between electrodes. Full article

The nucleation and growth of surface islands in the pre-coalescence stage has previously been studied by different methods, including the rate equation approach and kinetic Monte Carlo simulations. However, full understanding of island growth kinetics and the scaling properties of their size distributions is still lacking. Here, we investigate rate equations for the irreversible homogeneous growth of islands in the continuum limit, and derive a general island-size distribution whose shape is fully determined by the dynamics of the monomer concentration at a given size dependence of the capture coefficients. We show that the island-size distribution acquires the Family–Viscek scaling shape in the large time limit if the capture coefficients are linear in size for large enough islands. We obtain analytic solutions for the time-dependent monomer concentration, island density, average size and island-size distribution, which are valid for all times, and the analytic scaling function in the large time limit. These results can be used for modeling growth kinetics in a wide range of systems and shed more light on the general properties of the size distributions of different nano-objects. Full article

This study investigates the functionalization of a poplar biochar (PB), obtained by high-temperature pyrolysis, under oxidative conditions typically used in organic synthesis. In particular, concentrated nitric acid, a sulfonitric mixture and a piranha mixture were applied as oxidants at different temperatures and reaction times. In order to assess the outcome of the reaction conditions on the characteristics of the resultant products, these were characterized by a combination of imaging (SEM), spectroscopic (ATR-FTIR, RAMAN) and FFC-NMR relaxometric techniques. The latter techniques, rationalized in terms of the Kohlrausch-type stretched exponential kinetic model, were analyzed using a recently developed heuristic Monte Carlo method, providing insights into the water dynamics within material pore networks. Additionally, the water-holding capacity of the modified biochars and their abilities to adsorb some model dyes were evaluated. The results clarify the relationship between oxidative treatment conditions and biochar properties, highlighting their impact on both structural modifications and water dynamics within the porous network, and enabling us to identify the best reaction conditions for optimizing the features of the oxidized product. Full article