Experimental Simulation Research Articles

Astaxanthin-mediated Nrf2 activation ameliorates glucocorticoid-induced oxidative stress and mitochondrial dysfunction and impaired bone formation of glucocorticoid-induced osteonecrosis of the femoral head in rats

BackgroundOsteonecrosis of the femoral head caused by glucocorticoids (GIONFH) is a significant issue resulting from prolonged or excessive clinical glucocorticoid use. Astaxanthin, an orange-red carotenoid present in marine organisms, has been the focus of this study to explore its impact and mechanism on osteoblast apoptosis induced by dexamethasone (Dex) and GIONFH.MethodsIn this experiment, bioinformatic prediction, molecular docking and dynamics simulation, cytotoxicity assay, osteogenic differentiation, qRT-PCR analysis, terminal uridine nickend labeling (TUNEL) assay, determination of intracellular ROS, mitochondrial function assay, immunofluorescence, GIONFH rat model construction, micro-computed tomography (micro-CT) scans were performed.ResultsOur research demonstrated that a low dose of astaxanthin was non-toxic to healthy osteoblasts and restored the osteogenic function of Dex-treated osteoblasts by reducing oxidative stress, mitochondrial dysfunction, and apoptosis. Furthermore, astaxanthin rescued the dysfunction in poor bone quality, bone metabolism and angiogenesis of GIONFH rats. The mechanism behind this involves astaxanthin counteracting Dex-induced osteogenic damage by activating the Nrf2 pathway.ConclusionAstaxanthin shields osteoblasts from glucocorticoid-induced oxidative stress and mitochondrial dysfunction via Nrf2 pathway activation, making it a potential therapeutic agent for GIONFH treatment.

Development of a ReaxFF reactive force field for ternary phosphate-based bioactive glasses.

Phosphate-based glasses (PBGs) in the CaO-Na2O-P2O5 system have diverse applications as biomaterials due to their unique dissolution properties. A reactive force field (ReaxFF) has been developed to simulate these materials at the atomic level. The ReaxFF parameters of PBGs, including the interaction between phosphorus and calcium atoms, have been developed using a published code based on genetic algorithms. The training data, including the atomic charges, atomic forces, bond and angle parameters, and different differential energies, are chosen and measured from static quantum-mechanical calculations and abinitio molecular dynamics of PBGs. We did different short- and medium-range structural analyses on the bulk simulated PBGs with different compositions to validate the developed potential. Radial and angular distribution functions and coordination numbers of network formers and modifiers, as well as the network connectivity of the glass, are in agreement with experimental and previous simulations using both shell-model classical force fields and abinitio simulated data; for example, the coordination number of phosphorus is 4.0. This successful development of ReaxFF parameters being able to describe the bulk PBGs enables us to work on the dissolution behavior of the glasses, including the interaction of water molecules with PBGs, in future works.

Anisotropic Fourier Heat Conduction and phonon Boltzmann transport equation based simulation of time domain thermo-reflectance experiments

The anisotropic Fourier Heat Conduction Equation (FHCE) and the multidimensional phonon Boltzmann Transport Equation (BTE) were solved numerically in cylindrical coordinates and in time domain to simulate a Time Domain Thermo-Reflectance (TDTR) experimental silicon/aluminum substrate/transducer setup. The out-of-phase response of the probe laser was predicted at various beam offset distances for a pump laser pulse frequency of 80 MHz and modulation frequency of 10 MHz and compared against experimental measurements for a silicon substrate. The isotropic FHCE was also solved for comparison. Results show that the isotropic FHCE with bulk thermal conductivity of 145 W/m/K significantly underpredicts the out-of-phase temperature difference, particularly at smaller beam offsets. With an isotropic thermal conductivity of 105 W/m/K, the computed results match experimental data at smaller beam offsets well, but overpredicts the experimental data at larger beam offsets. An almost-perfect match is obtained by using an anisotropic thermal conductivity wherein the radial (in-plane) thermal conductivity is set to 85 W/m/K and the axial (through-plane) conductivity is set to 130 W/m/K. The multidimensional frequency and polarization dependent phonon BTE is next solved. The BTE results for the out-of-phase temperature difference match experimental observations well at small and intermediate beam offsets, but overpredicts the experimental data at larger beam offsets. FHCE results are fitted to the BTE predictions, and the extracted (best fit) thermal conductivity is found to be 110 W/m/K.

Hydrogel Nanoparticles Enable Nucleation Barrier Regulation and Ion Anchoring as an Alternative Pathway for Monosodium Urate Monohydrate Crystallization Control.

Gout flare-up, commonly resulting from monosodium urate monohydrate (MSUM) crystallization, has led to painful inflammatory arthritis among hundreds of millions of people. Herein, a kind of hydrogel nanoparticles (HNPs) with specific properties was developed, aimed at providing a promising pathway for MSUM crystallization control. The experimental and molecular dynamics simulation results synchronously indicate that the fabricated HNPs achieve efficient inhibition of MSUM crystallization governed by the mechanism of "host-guest interaction" even under very low-dose administration. HNPs as the host dispersed in the hyperuricemic model effectively lift the relative heterogeneous nucleation barrier of the MSUM crystal and hinder solute aggregation with strong electronegativity and hydrophobicity. The initial appearance of MSUM crystals was then delayed from 94 to 334 h. HNPs as the guest on the surface of the formed crystal can decelerate the growth rate by anchoring ions and occupying the active sites on the surface, and the terminal yield of the MSUM crystal declined to less than 1% of the control group. The good biocompatibility of HNPs (cell viability > 94%) renders it possible for future clinical applications. This study can guide the rational design of inhibitory nanomaterials and the development of their application in the control of relevant pathological crystallization.

Dynamic Nuclear Polarization Using Electron Spin Cluster.

Dynamic nuclear polarization (DNP) utilizing narrow-line electron spin clusters (ESCs) to achieve nuclear spin resonance matching (ESC-DNP) by microwave irradiation is a promising way to achieve NMR signal enhancements with a wide design scope requiring low microwave power at high magnetic field. Here we present the design for a trityl-based tetra-radical (TetraTrityl) to achieve DNP for 1H NMR at 7 T, supported by experimental data and quantum mechanical simulations. A slow-relaxing (T1e ≈ 1 ms) 4-ESC is found to require at least two electron spin pairs at <8 Å e-e spin distance to yield 1H ESC-DNP enhancement, while squeezing the rest of the e-e spin distances to <12 Å results in optimal 1H ESC-DNP enhancements. Fast-relaxing ESCs (T1e ≈ 10 μs) are found to require a weakly coupled narrow-line radical (sensitizer) to extract polarization from the ESC. These results provide design principles for achieving a power-efficient DNP at high field via ESC-DNP.

Cyclic Air Braking Strategy for Heavy Haul Trains on Long Downhill Sections Based on Q-Learning Algorithm

Cyclic air braking is a key factor affecting the safe operation of trains on long downhill sections. However, a train’s cycle braking strategy is constrained by multiple factors such as driving environment, speed, and air-refilling time. A Q-learning algorithm-based cyclic braking strategy for a heavy haul train on long downhill sections is proposed to address this challenge. First, the operating environment of a heavy haul train on long downhill sections is designed, considering various constraint parameters, such as the characteristics of special operating routes, allowable operating speeds, and train tube air-refilling time. Second, the operating status and braking operation of a heavy haul train on long downhill sections are discretized in order to establish a Q-table based on state–action pairs. The training of algorithm performance is achieved by continuously updating Q-tables. Finally, taking the heavy haul train formation as the study object, actual line data from the Shuozhou–Huanghua Railway are used for experimental simulation, and different hyperparameters and entry speed conditions are considered. The results show that the safe and stable cyclic braking of a heavy haul train on long downhill sections is achieved. The effectiveness of the Q-learning control strategy is verified.

Investigation into the Hot-Forming Limit for 22MnB5 Hot-Forming Steel under a Stamping Process

Hot-forming technology for 22MnB5 hot-forming steel (22MnB5 HF steel) plates has been widely used in the automobile manufacturing industry in recent years. Physical simulation and numerical modeling were carried out in order to determine the forming limit of a 22MnB5 steel plate for the stamping process. The deformation experiments were performed in a temperature range of 600~900 °C and a strain rate range of 0.1~10 s−1. In the uniaxial tensile tests, it was found that at the forming temperature of 600 °C, the condition of dynamic recrystallization was not fully reached, and thus the corresponding tensile strength was much larger than that at other deformation temperatures. In the numerical simulation of bulging experiments, it was found that 22MnB5 steel had good formability when the initial deformation temperature was high and the forming speed was low by using the instability criterion, combining the maximum punch force and strain path transition. The forming limit diagram of 22MnB5 steel at a temperature of 700 °C and tool speed of 25 mm/s was obtained by means of simulation and a hot stamping experiment. The establishment of the forming limit of the 22MnB5 steel plate can provide theoretical and technical guidance for the hot-forming process.

Development and Calibration of a Phenomenological Material Model for Steel-Fiber-Reinforced High-Performance Concrete Based on Unit Cell Calculations

A phenomenological material model has been developed to facilitate the efficient numerical analysis of fiber-reinforced high-performance concrete (HPC). The formulation integrates an elasto-plastic phase-field model for simulating fractures within the HPC matrix, along with a superimposed one-dimensional elasto-plasticity model that represents the behavior of the embedded fibers. The Drucker–Prager plasticity and one-dimensional von-Mises plasticity formulations are incorporated to describe the nonlinear material behavior of both the HPC matrix and the fibers, respectively. Specific steps are undertaken during the development and calibration of the phenomenological material model. In the initial step, an experimental and numerical analysis of the pullout test of steel fibers embedded in an HPC matrix is conducted. This process is used to calibrate the micro-mechanical model based on the elasto-plastic phase-field formulation for fracture. In the subsequent step, virtual experiments based on an ellipsoidal unit cell, also with the resolution of fibers (used as a representative volume element, RVE), are simulated to analyze the impact of fiber–matrix interactions and their physical properties on the effective material behavior of fiber-reinforced HPC. In the final step, macroscopic boundary value problems (BVPs) based on a cuboid are simulated on a single scale using the developed phenomenological material model. The resulting macroscopic stress–strain characteristics obtained from both types of simulations, namely simulations of virtual experiments and macroscopic BVPs, are compared. This comparison is utilized for the calibration of material parameters to obtain a regularized solution and to assess the effectiveness of the presented phenomenological material model.

Revealing the Roles of Guanidine Hydrochloride Ionic Liquid in Ion Inhibition and Defects Passivation for Efficient and Stable P erovskites Solar Cells.

As a result of full-scale ongoing global efforts, the power conversion efficiency (PCE) of the organic-inorganic metal halide perovskite has skyrocketed. Unfortunately, the long-term operational stability for commercialization standards is still lagging owing to intrinsic defects such as ion migration-induced degradation, undercoordinated Pb2+, and shallow defects initiated by disordered crystal growth. Herein, we employed multifunctional, non-volatile tetra-methyl guanidine hydrochloride [TMGHCL] ionic liquid (IL) as an additive to elucidate defects' passivation effects on organic-inorganic metal halide perovskite. More specifically, the formation of hydrogen bonds between H+ in GA+ and I- and coordinate bonding between Cl- and undercoordinated PbI2+could significantly passivate these defects. The hypothesis was confirmed by both experimental and DFT simulations displaying that the optimized ratio of IL integration restrains ion migration, improving grains' size, and significantly elongating the carrier lifetime. Remarkably, the modified cell achieved a peak efficiency of 22.00% with negligible hysteresis, compared to the control device's PCE of 20.12%. In addition, the TMGHCL-based device retains its 93.29% efficiency after 16 days of continuous exposure to air. This efficient approach of adding IL to perovskites absorber can produce high PCE and has strong commercialization potential.

Efficient and secure privacy protection scheme and consensus mechanism in MEC enabled e-commerce consortium blockchain

The application of blockchain technology to the field of e-commerce has solved many dilemmas, such as low transparency of transactions, hidden risks of data security and high payment costs. Mobile edge computing(MEC) can provide computational power for blockchain, and can meet the demand for high real-time and low latency in e-commerce transaction systems. However, there are still some constraints in the MEC enabled e-commerce consortium blockchain, such as the leakage of user privacy information, low security of consensus algorithm and other security issues. In this paper, we propose a secure transaction model suitable for MEC enabled e-commerce consortium blockchain, aiming to ensure the efficiency of system transaction processing while improving the security of users’ privacy information and transaction data. The model adopts the lightweight Paillier encryption algorithm to protect the security of user privacy information and transaction data to prevent the leakage of user privacy information, and optimizes the security of leader election phase of Raft consensus algorithm by introducing the shamir secret sharing protocol to improve the anti-Byzantine failure capabilities of Raft consensus algorithm. The effectiveness of the scheme proposed in this paper is demonstrated by experimental simulations.

Bridging theory and practice: CFD simulation and interactive VR for conduction heat transfer learning

AbstractSoftware simulation programs and virtual reality (VR) have become powerful tools for several educational purposes, and recently, they were used in a wide range of applications. In cases of inaccessibility to labs, workshops, or industries, as happened before in the coronavirus disease 2019 pandemic, these tools could be effectively integrated with practical lab experiments. In this study, a computational fluid dynamics (CFD) simulation and a VR module were utilized to simulate heat transfer by conduction through various experimental cases. The CFD simulation results were obtained using ANSYS/FLUENT software. Meantime, the experimental data were obtained by carrying out three experiments of heat conduction with different heat transfer rates through simple, composite, and different cross‐sectional area bars. At last, the experimental procedure and devices used were virtually constructed using SolidWorks software as three‐dimensional models, which were then extruded into VR and augmented reality models. It was found that the simulation results closely align with the experimental ones, and the temperature profile in both cases has the same behavior with small differences, which indicates the validity of the developed module to be used as a simulation of the actual experiments. In addition to improving knowledge of heat transfer principles, this combination of simulation and VR technology advances many Sustainable Development Goals (SDGs), including advancing quality education (SDG 4) and innovation in higher education (SDG 9). Additionally, this method assists in achieving the course learning objectives by mimicking real‐world lab experiments, guaranteeing that students graduate from the course with the required information and abilities.

Experimental measurement and molecular dynamics simulation analysis of thermal aging performance in composite solid propellants

As a complex mixed system, the aging mechanism of high-energy composite materials involves the aging of each component itself, interactions between components, and transformation of microstructural and thermodynamic properties. The study of a single component or performance parameter has great limitations for elaborating the cognitive complexity of aging processes, making it difficult to reveal the underlying principles of physicochemical property transformation. Thus, it can only be applied as an empirical summary. In view of this, this study comprehensively utilized numerical analysis and experimental detection to explore the evolution of micromolecular conformation and changes in macro aging performance from four aspects of composite systems, including binder aging, plasticizer migration, bond interface debonding, and mechanical property transformation. There was good consistency observed between molecular simulation and thermal aging experiments, indicating that there was basically no post curing process for HTPB propellants using TDI as the curing agent. In the early stage of aging, scission chain was the main process and, in the later stage of aging, oxidation crosslinking the main process. Oxidative crosslinking increased the mean square radius of gyration and glass transition temperature of the binder system, reduced the peak value of radial distribution function, and revealed the reason for the change of propellant hardness and CC and CO double bond content. However, chain degradation increased the number of polar groups, enhanced intermolecular polarity, reduced the solubility parameter, and increased the free volume fraction of the mixed system and the dioctyl sebacate diffusion coefficient. This resulted in an increase in the tangent value of the HTPB propellant loss angle from 0.43 to 0.44° and a decrease in the glass transition temperature from 203.3 to 202.0 K. The binding energy at the interfaces of AP/HTPB and Al/HTPB increased first and then decreased, which was consistent with SEM images of bonding interfaces. The joint effect of binding energy and mechanical properties of the binder system promoted the transformation of the stress-strain curve of aging propellant.

Real and In Silico Microgels Show Comparable Bulk Moduli Below and Above the Volume Phase Transition.

The compressibility of soft colloids influences their phase behavior and flow properties, especially in concentrated suspensions. Particle compressibility, which is proportional to the reciprocal of the bulk modulus K, is a key parameter for soft polymer-based particles that can be compressed in crowded environments. Here, microgels with different degrees of cross-linking, i.e.,softness, are investigated below and above their volume phase transition temperature (VPTT). By combining molecular dynamics simulations with small-angle neutron scattering with contrast variation, a change in the particle bulk moduli of two orders of magnitude is observed. The degree of cross-linking has a significant impact on the bulk modulus of the swollen microgel, while above the VPTT the values of K are almost independent of the cross-linking density. The excellent agreement between experimental results and simulations also highlight that the model microgels from computer simulationspossess both the internal architecture and the elastic properties of real polymeric networks. This paves the way to a systematic use of simulations to investigate the behavior of dense microgelsuspensions below and above their VPTT.

Experimental and Thermal Stress Field Numerical Simulation Study on Laser Metal Deposition of Ti-48Al-2Cr-2Nb Alloy

The experimental and numerical simulation analysis of a TiAl alloy by laser metal deposition technology is presented in this paper. The research examines the macroscopic morphology, microstructure, and mechanical properties of samples as laser power varies. It also delves into how the temperature field and residual stress evolve under different laser powers. The results reveal that the microstructure of samples is mainly composed of α2-Ti3Al phase and a γ-TiAl phase and that the details of the microstructure are significantly affected by laser power. As laser power increases, coarse lamellar structure content increases, corresponding to a decrease in α2 phase content. The deposited layer hardness ranges from 550 HV to 600 HV, and the average deposition layer hardness decreases with increased laser power. Simulation results predict the molten pool’s size, temperature, and residual stresses. A significant increase in the molten pool size is observed when the laser power exceeds 1000 W, and the measured molten pool depths correspond closely to simulation predictions. However, significant tensile stresses are generated in the deposition layer due to high cooling rates, mainly in the x direction. Cracks are observed on the surface of the deposition layer at all laser powers.

Frequency and amplitude of flashing-induced instability in an open natural circulation loop

Several nuclear reactor designs rely on passive containment cooling systems. The so-called containment wall condenser relies on natural circulation loops to extract heat from high-temperature steam in the containment to a water tank at ambient pressure. In such passive systems, phase changes can happen and cause flow instabilities in the cooling loop. The flashing-induced instability occurs when the heated fluid in the riser suddenly vaporizes due to a hydrostatic pressure decrease. This instability causes periodic flow peaks, which are of major concern but whose characteristics have not been studied quantitatively.This paper presents two analytical models that predict the flashing frequency and a maximum flow amplitude from geometry and basic operating parameters such as power level and reservoir temperature. The expressions are derived from a physical analysis and do not involve any calibration constants. The flashing frequency appears to be driven by the power level, the inlet temperature and the riser pipe geometry. For the amplitude, the maximum flow rate can be expressed in a Froude number that depends only on the total pressure losses. These models are validated against PASI experiments and system-scale simulations with the CATHARE 3 code, both performed as part of the European Commission funded PASTELS project. Additional data from numerous experimental studies in the literature are used to extend the validity range of the frequency model.Successfully validated against experimental data and additional simulations, these models provide an explicit relationship between oscillations characteristics and design parameters, making them valuable tools for nuclear engineers.

Texture and Twinning Evolution of Cold-Rolled Industrial Pure Zirconium

Industrial pure zirconium plays an essential role as a structural material in the nuclear energy sector. Understanding the deformation mechanisms is crucial for effectively managing the plasticity and texture evolution of industrial pure zirconium. In the present study, the texture and microstructure evolution of industrial pure zirconium during the cold-rolling process have been characterized by XRD, EBSD, and TEM. The influences of various twins on texture evolution have also been simulated by the reaction stress model. The effects of slip and twinning on the deformation behavior and texture evolution have been discussed based on crystallographic and experimental considerations. Cold rolling yields a typical bimodal texture, resulting in the preferential &lt;21-1-0&gt;//RD orientation. The activation of the deformation mechanisms during cold rolling follows the sequential trend of slip, twinning, local slip. Experimental characterization and reaction stress simulation illustrate that T1 twins dominate in the early stage, whereas C2 twins develop at the later stage of the cold-rolling process. Twinning, especially the T1 twin, contributes to the formation of the {0001}&lt;101-0&gt; orientation.

Porous Aromatic Frameworks Enabling Polyiodide Confinement toward High Capacity and Long Lifespan Zinc-Iodine Batteries.

Aqueous zinc-iodine batteries (AZIBs) are attracting increasing attention because of their high safety and abundance of resources. However, the performance of AZIBs is compromised by inadequate confinement of soluble polyiodides, the undesired shuttle effect, and slow reaction kinetics. In this study, a porous aromatic framework (PAF) with abundant benzene motifs and a well-organized pore structure is adopted as the iodine host, which exhibits high iodine adsorption capacity and robust polyiodide confinement. Both experimental characterizations and theoretical simulations indicate that the interactions between iodine species and the PAF-1 facilitate the redox reaction by coupling the electronic structures of the active species in the framework. A comparison of PAF-1, PAF-5, and PAF-11 also emphasizes the structural advantages of the high surface area and interconnected three-dimensional channels of PAF-1. Consequently, the I2@PAF-1 cathode can deliver a high capacity of 328 mAh g-1 at 0.5 C, outstanding rate performance (86% retention at 10 C), and a stable cycling life of 20000 cycles. The robust polyiodide confinement and superb electrochemical performance of Zn-I2@PAF-1 provide insights into the practical application of PAFs as excellent electrode materials for AZIBs. This article is protected by copyright. All rights reserved.

Lattice Boltzmann Simulation of Breaking Waves

Abstract Water wave breaking at the ocean's surface is a turbulent phenomenon and encompasses a wide range of physical processes such as generation of bubbles/drops with different spatio-temporal scales. In the present study, breaking of periodic waves in deep water regime has been simulated using phase-field Lattice Boltzmann Method (LBM). Compared to direct Navier-Stokes equation based numerical models, the present LB model is Poisson-free and explicit in time integration. Both the flow field and interface are solved using LBM with two sets of distribution functions. The normalized pressure-velocity formulation is used for the flow field, whereas the conservative Allen-Cahn equation is used to capture the interface. An impulsively started wave approach with Stokes third order wave profile has been used to initiate the breaking process. Through systematic &amp;#xD;variation of Weber number and initial steepness, the effect of surface tension on the kinematic, geometric, and energy dissipation characteristics has been studied for three breaker types, viz., spilling, weak plunging, and plunging breakers. The results are in good agreement with the past experimental observations and direct numerical simulation. In particular, the obtained breaking strength for different Weber numbers agrees well with the semi-empirical relation used in a wind-wave forecasting models.&amp;#xD;

The development of thermodynamically consistent and physics-informed equation-of-state model through machine learning

Ab initio molecular dynamics (AIMD) simulations have become an important tool used in the construction of equations of state (EOS) tables for warm dense matter. Due to computational costs, only a limited number of system state conditions can be simulated, and the remaining EOS surface must be interpolated for use in radiation-hydrodynamic simulations of experiments. In this work, we develop a thermodynamically consistent EOS model that utilizes a physics-informed machine learning approach to implicitly learn the underlying Helmholtz free-energy from AIMD generated energies and pressures. The model, referred to as PIML-EOS, was trained and tested on warm dense polystyrene producing a fit within a 1% relative error for both energy and pressure and is shown to satisfy both the Maxwell and Gibbs–Duhem relations. In addition, we provide a path toward obtaining thermodynamic quantities, such as the total entropy and chemical potential (containing both ionic and electronic contributions), which are not available from current AIMD simulations.

Energy absorption in expanding metallic wire mesh tubes

The deformation process and energy absorption of metal wire mesh tubes under quasi-static expanding by a hemispherical-cylindrical indenter were investigated by experimental tests, finite element (FE) simulations and analytical modelling. Stainless steel and aluminum alloy tubes were tested on an MTS universal testing machine at a speed of 10 mm/min. The effects of mesh cell size and friction coefficient on the quasi-static force and specific energy absorption (SEA) were examined by FE analysis and analytical modelling. The analysis reveals that a combination of the mesh cell size and cross section dimension of the wire governs the energy absorption of tubes of equal overall dimension (diameter and length) and masses. In general, a decrease of the size of cells with constant height-to-width ratios leads to an increase of the specific energy absorption mainly due to the increased number of cells within the deformed region. An increase of the specific energy absorption is also achieved when the cell size is reduced by only decreasing the cell height. The maximum indenter force predicted by the proposed analytical model of the expanded tube deformation agrees well with the experimental results and FE simulations.