Microscopic Model Research Articles

Recent developments on multiscale simulations for rheology and complex flow of polymers

AbstractThis review summarized the multiscale simulation (MSS) methods for polymeric liquids. Since polymeric liquids have multiscale characteristics of monomeric, mesoscopic, and macroscopic flow scales, MSSs that relate different hierarchical levels are adequate to reproduce flow properties accurately. Our review includes pioneering studies to the most advanced MSS studies on rheology predictions and flow simulations of polymeric liquids. We discuss two major types of MSS methods: the bottom-up and model-embedded MSS methods. The former method mainly connects all-atom molecular dynamics models and mesoscopic models to predict rheological properties. In contrast, the latter method, where a microscopic or mesoscopic model is embedded in a macroscopic computational domain, is designed to predict macroscopic flow properties. Finally, we also discuss MSS methods using machine learning techniques. Graphical abstract

Investigating the impact of three levels of representation-based visual media on students’ mental models

Abstract This study examines the effect of visual media on students’ mental models regarding battery functions and electrical resistance concepts. The study presents a novel visual media approach consisting of phenomena videos, dynamic analogies, and microscopic models. The development of the visual media followed the ADDIE model. The research subjects were 25 12th-grade students from a private senior high school in Bandung, West Java. Students’ mental models were assessed using open-ended test that examined four concepts: (1) electromotive force (EMF) in batteries; (2) electrical resistance; (3) resistors in series; and (4) resistors in parallel. The test were administered as both pre-tests and post-tests.The pre-test results revealed that the majority of students had initial mental models regarding battery functions and electrical resistance concepts. By the end of the study, most students had developed synthetic mental models. However, the majority successfully achieved scientific mental models concerning electrical resistance concepts. In other concepts, only a few students achieved scientific mental models. Overall, the visual media had a significant positive effect on students’ mental models, with corrections observed in 92% of students for EMF in batteries, 96% for electrical resistance, 80% for resistors in series, and 84% for resistors in parallel.These findings encourage physics teachers and researchers to develop innovative visual media focused on correcting students’ mental models in scientific concept learning.

Pair-Density-Wave Superconductivity: A Microscopic Model on the 2D Honeycomb Lattice.

Pair-density wave (PDW) is a long-sought exotic state with oscillating superconducting order without external magnetic field. So far it has been rare in establishing a 2D microscopic model with PDW long-range order in its ground state. Here, we propose to study PDW superconductivity in a minimal model of spinless fermions (or spin-polarized electrons) on the honeycomb lattice with nearest-neighbor and next-nearest-neighbor interaction V_{1} and V_{2}, respectively. By performing a state-of-the-art density-matrix renormalization group study of this t-V_{1}-V_{2} model at finite doping on six-leg and eight-leg honeycomb cylinders, we show that the ground state exhibits PDW ordering (namely quasi-long-range order with a divergent PDW susceptibility). Remarkably this PDW state persists on the wider cylinder with 2D-like Fermi surfaces. To the best of our knowledge, this is probably the first controlled numerical evidence of PDW in systems with 2D-like Fermi surfaces.

Analytic continuation in the coupling constant for resonances in ${}^9_{\Lambda}$Be

Abstract The application scope of the analytic continuation in the coupling constant (ACCC) can be extended to the exchange parameters of the effective nucleon-nucleon interaction in microscopic cluster model. Based on such exchange parameter dependent ACCC (abbreviated as EPD-ACCC), we study the ${}_{\Lambda}^9$Be system in the framework of $\alpha+\alpha+\Lambda$ microscopic cluster model. The resonant states of $\alpha+\alpha+\Lambda$ are obtained through EPD-ACCC. Meanwhile, the complex scaling method (CSM) is applied as a comparison. A good agreement between these two theoretical approaches is obtained. This work demonstrate a reliable method EPD-ACCC for estimating the multi-cluster resonances in light hypernuclei.

Buckling analysis and parametric optimization of the metal-composite shell with voids under hydraulic pressure combined with sensitivity analysis

Structural design parameters always impact the buckling properties of the composite shells due to the differences in the anisotropy of the materials and the varying enhancement capabilities of each component. This paper aims to analyze the parametric effect on the buckling load and optimize the design parameters of metal-composite shells with voids under hydraulic pressure. Firstly, the theoretical model of buckling load is established based on the microscopic model of hybrid materials and the Galerkin method. Then, four design parameters including fiber volume content, winding angles, and CNTs volume content are selected to discuss the parametric effect on the critical buckling load. Further, the global sensitivity analysis is conducted to determine the influence rank, and the GA-PSO algorithm is used to confirm the optimal parametric combination. The results imply that the fiber volume content and internal and external helical symmetrical angles significantly affect the buckling load. Besides, The winding layers of internal and external helical symmetrical angles enhance the hydraulic resistance of the anti-symmetric structure. The middle helical layer can be influenced by the outer layer, leading to directional changes in the critical buckling load at an angle of around 50°.

Towards complexity in de Sitter space from the doubled-scaled Sachdev-Ye-Kitaev model

How can we define complexity in dS space from microscopic principles? Based on recent developments pointing towards a correspondence between a pair of double-scaled Sachdev-Ye-Kitaev (DSSYK) models/ 2D Liouville-de Sitter (LdS2) field theory/ 3D Schwarzschild de Sitter (SdS3) space in [1–3], we study concrete complexity proposals in the microscopic models and their dual descriptions. First, we examine the spread complexity of the maximal entropy state of the doubled DSSYK model. We show that it counts the number of entangled chord states in its doubled Hilbert space. We interpret spread complexity in terms of a time difference between antipodal observers in SdS3 space, and a boundary time difference of the dual LdS2 CFTs. This provides a new connection between entanglement and geometry in dS space. Second, Krylov complexity, which describes operator growth, is computed for physical operators on all sides of the correspondence. Their late time evolution behaves as expected for chaotic systems. Later, we define the query complexity in the LdS2 model as the number of steps in an algorithm computing n-point correlation functions of boundary operators of the corresponding antipodal points in SdS3 space. We interpret query complexity as the number of matter operator chord insertions in a cylinder amplitude in the DSSYK, and the number of junctions of Wilson lines between antipodal static patch observers in SdS3 space. Finally, we evaluate a specific proposal of Nielsen complexity for the DSSYK model and comment on its possible dual manifestations.

Study on corrosion behavior and first-principle analysis of M50 steel in lubricating oil contaminated by salt water

The corrosive wear of M50 steel in lubricating oil contaminated with saline is a form of wear that often occurs within the main shaft bearings of aviation engines carried by aircraft working at sea. In the present paper, the corrosion behavior of M50 steel in lubricating oil contaminated with saline was studied. The open-circuit potential, polarization curve and impedance spectrum were analyzed by rotating electrochemical corrosion wear test. A three-layer interface microscopic molecular model was established with Materials Studio to simulate the dynamic corrosion evolution process of M50 steel self-matching pairs and the adsorption energy was calculated. The results show that the corrosion type is pitting corrosion. With the increase of saline concentration, the corrosion area becomes wider and shallower, and the size of the pitting core gradually decreases. The weight loss of M50 steel increases over time, but the trend slows down, which is also shown in the MS simulation results. Electrochemical tests show that the tribocorrosion of M50 steel is related to load, speed. As the load increases, the corrosion rate decreases. And, as the speed increases, the corrosion rate increases. This has practical significance for extending the understanding of tribocorrosion of M50 steel in marine atmospheric environments.

Sustainable Nanofluids Constructed from Size-Controlled Lignin Nanoparticles: Application Prospects in Enhanced Oil Recovery.

Lignin, a widely available, cost-effective, and structurally stable natural polymer, has recently attracted significant attention due to its diverse potential applications. A promising approach is to prepare lignin nanoparticles (LNPs) as a substitute for conventional nanoparticles to fulfill a variety of functions. In this study, LNPs with controlled size, regular morphology, and excellent dispersibility were synthesized by using industrial alkali lignin. The antisolvent method was employed, utilizing an aqueous solution of the anionic surfactant sodium apolyolefin sulfonate (AOS) as the antisolvent. Subsequently, the prepared LNPs were used to formulate nanofluids in combination with AOS and nonionic surfactant coconut diethanolamide (CDEA). The incorporation of LNPs has significantly enhanced the interfacial activity of the resulting nanofluids, thereby improving their emulsion stabilization, spreading on quartz surfaces, and oil droplet removal capabilities, which establish a strong foundation for the AOS/CDEA/LNPs nanofluid to achieve high performance in enhanced oil recovery (EOR), which was validated through microscopic visual physical model experiments. The quartz crystal microbalance with the dissipation monitoring (QCM-D) technique was employed to investigate the adsorption of surfactants onto quartz surfaces. It was found that the incorporation of LNPs significantly reduces the adsorption loss of surfactants, presenting a potential solution to overcome the challenges associated with surfactant adsorption in chemically enhanced oil recovery (EOR) processes, such as high cost and unreliable efficiency. This study reveals the good performance of LNPs/surfactant nanofluids and provides a potential approach to the advancement of green, sustainable, and intelligent EOR technologies.

Deuteration removes quantum dipolar defects from KDP crystals

Dielectric properties of the hydrogen-bonded ferroelectric crystal KH2PO4 (KDP) differ significantly from those of KD2PO4 (DKDP). It is well established that deuteration affects the interplay of hydrogen-bond switches and heavy ion displacements that underlie the emergence of macroscopic polarization, but a detailed microscopic model is missing. We show that all-atom path integral molecular dynamics simulations can predict the isotope effects, revealing the microscopic mechanism that differentiates KDP and DKDP. Proton tunneling generates phosphate configurations that do not contribute to the polarization. At low temperatures, these quantum dipolar defects are substantial in KDP but negligible in DKDP. These intrinsic defects explain why KDP has lower spontaneous polarization and transition entropy than DKDP. The prominent role of quantum fluctuations in KDP is related to the unusual strength of the hydrogen bonds and should be equally important in other crystals of the KDP family, which exhibit similar isotope effects.

A Microscopic On-Ramp Model Based on Macroscopic Network Flows

While macroscopic traffic flow models adopt a fluid dynamic description of traffic, microscopic traffic flow models describe the dynamics of individual vehicles. Capturing macroscopic traffic phenomena accurately remains a challenge for microscopic models, especially in complex road sections. Based on a macroscopic network flow model calibrated to real traffic data and new rules for the acceleration and merging behavior on the on-ramp, we propose a microscopic model for on-ramps. To evaluate the performance of the new flow-based model, we conduct traffic simulations assessing speeds, accelerations, lane change positions, and risky behavior. Our results show that, although the proposed model exhibits some limitations, its performance is superior to the Intelligent Driver Model in the evaluated aspects. While the Intelligent Driver Model simulations are almost free of conflicts, the proposed model evokes a realistic amount and severity of conflicts and therefore can be considered for safety analysis.

Research on microscopic structure–activity relationship of AP particle–matrix interface in HTPB propellant

Abstract The matrix and particle interface of hydroxyl-terminated polybutadiene (HTPB) propellant is the weakest part of its mechanical properties, making it prone to dewetting damage and destroying the structural integrity of the propellant. This article uses nano-indentation, gas cluster ion beam etching, and X-ray photoelectron spectroscopy experimental analyses to study the physicochemical properties of the interface and subsequently construct a microscopic model for the HTPB matrix and ammonium perchlorate particle interface. The model fully considers the existing forms of curing agent toluene diisocyanate, bonding agent Tris (2-methyl-aziridine) phosphine oxide (MAPO), and the aging products of the propellant in the interface structure. Meanwhile, the physicochemical properties, mechanical properties, and adhesive properties of the interface under different tensile loading conditions were analyzed. The results indicate that the bonding agent MAPO significantly enhances the mechanical and adhesive properties of the interface. The interface is sensitive to changes in temperature and tensile rate, and the aged interface is more fragile.

Theoretical Study of the Co‐doping Effects at Sr and Fe Sites on the Magnetic and Optical Properties of SrFe12O19

For the first time, the magnetic and optical (bandgap) properties of co‐doped Mg/Dy, Al/Dy, and Mn/Nd (SFO) at Sr and Fe sites are investigated using a microscopic model and the Green's function theory. It is shown that the co‐doping at both Sr and Fe sites can change the behavior of the magnetization which decreases by transition metal or nonmagnetic ion doping at the Fe site (with doping ions larger than the host Fe ions), but by additive co‐doping at the Sr site with rare‐earth ion (which ionic radius is smaller than that of Sr) the magnetization increases with increasing the co‐doping concentration. The bandgap energy decreases in the co‐doped SFO. The mechanism of this co‐doping effect is explained on microscopic level. It is due to the changes of the spin‐exchange interaction constants at the doped sites caused by the appearance of different strain by the doping with two ions. The theoretical results are compared with the existing experimental data and are in good qualitative agreement.

A cluster-based incremental potential approach for reduced order homogenization of bones.

We develop a cluster-based model order reduction (called C-pRBMOR) approach for efficient homogenization of bones, compatible with a large variety of generalized standard material (GSM) models. To this end, the pRBMOR approach based on a mixed incremental potential formulation is extended to a clustered version for a significantly improved computational efficiency. The microscopic modeling of bones falls into a mixed incremental class of the GSM framework, originating from two potentials. An offline phase of the C-pRBMOR approach includes both a clustering analysis spatially decomposing the micro-domain within an RVE and a space-time decomposition of the microscopic plastic strain fields. A comparative study on two different clustering approaches and two algorithms for mode identification is additionally conducted. For an online analysis, a cluster-enhanced version of evolution equations for the reduced variables is derived from an effective incremental variational formulation, rendering a very small set of nonlinear equations to be numerically solved. Several numerical examples show the effectiveness of the C-pRBMOR approach. A striking acceleration rate beyond 104 against conventional FE computations and that beyond 103 against the original pRBMOR approach are observed.

Enhancing horticultural harvest efficiency: The role of moisture content in ultrasonic cutting of tomato stems

Ultrasonic vibration has notable benefits in the harvesting and processing of tomato stems, particularly in reducing cutting force and minimizing moisture loss. Given the anisotropic nature of biological materials, the moisture content of tomato stems significantly impacts their physical properties. This study investigates the influence of varying moisture content on temperature and cutting force during the ultrasonic cutting of tomato stems. Initially, the moisture content of tomato stems at different maturity stages was measured using a water activity meter. Mechanical properties were characterized using a universal testing machine, and thermal properties were analyzed with a differential scanning calorimeter (DSC). Regression models were established to correlate moisture content with these material properties. Additionally, a three-dimensional microscopic model of stem skeletons, interfaces, and fiber bundles was created to simulate the fracture mechanisms during ultrasonic cutting under different moisture levels. Single-factor and response surface optimization experiments were conducted using a custom experimental setup under varying maturity stages, excitation frequencies, and voltage variations. Results showed that after 24 h, the peak temperatures for tomato stems at different maturity stages were 97.84 °C, 80.59 °C, and 74.15 °C, with corresponding cutting forces of 0.492 N, 0.544 N, and 0.998 N, respectively. The discrepancy between experimental results and simulation data was within 10 %. Higher moisture content was found to enhance the thermal conductivity of fiber materials, aiding in the fracture of fiber bundles, thus reducing cutting time and force. This study provides a theoretical foundation for the application of ultrasonic technology in the efficient harvesting and processing of industrial crops, with significant implications for horticultural crop treatment and processing.

The problem of obtaining vehicles speed input for road traffic noise microscopic models: a comparison between field measurements and a stochastic approach

Mitigating environmental noise harmful effects is a relevant goal in the EU "Zero Pollution Action Plan", which targets a 30% reduction in chronic annoyance from transportation noise by 2030. Since road traffic is a major noise source in urban and non-urban settings, much effort has been invested in analyzing and modeling it. To assess noise levels, numerous Road Traffic Noise Models (RTNMs) exist, each requiring multiple inputs like vehicle flows, percentage of heavy vehicles, and average speed. Specifically, when dealing with microscopic models, the single vehicle speeds are needed. To obtain them, on-site measurements offer accurate data but are time consuming and expensive. This paper explores two approaches: an alternative measurement approach, based on video processing and object detection tools, and a stochastic approach, which randomly assigns a speed to each vehicle from a distribution curve, depending on traffic conditions and vehicle category. These methodologies are used to provide input data to a road traffic noise microscopic model, whose results are compared with field measured data. This comparison will allow to get useful insights on the performances of the proposed techniques in providing reliable inputs and their potential applications in different scenarios where single vehicle measured speeds are not available.

Second harmonic scattering reveals different orientational orders inside the hydrophobic cavity of hybrid nanotubes.

Second Harmonic Scattering (SHS) is a suitable technique to investigate the orientational correlations between molecules. This article explores the organization of different dye molecules adsorbed within the hydrophobic porosity of a hybrid organic-inorganic nanotube. Experimental polarization resolved SHS measurements highlight different orientational orders ranking from highly ordered and rigid organizations to disordered assemblies. Microscopic models of assemblies inside the pores are presented and discussed in the context of orientational correlation between the dye molecules. This work shows that the degree of order in the nanotube cavity follows the molecule's affinity within the porosity.

Study on mixed traffic characteristics around highway on-ramp bottleneck using a microscopic simulation model

In the early mixed traffic environment, connected and automated vehicles (CAVs) tend to follow simple control rules for the sake of traffic safety and stability. Comprehensive analysis of overall mixed traffic performance and vehicle to vehicle interactions around highway on-ramp bottleneck is a basis for further traffic management and control. And yet CAVs in existing researches are mainly in the form of cooperative vehicular platoon, and mixed traffic scenarios within simulation software are not applicable for in-depth investigation. The purpose of this paper is to develop a microscopic simulation model to study in detail lane-based mixed traffic performance around the highway on-ramp. This model firstly considers vehicle characteristics of individual human vehicles (HVs) and CAVs by combining different microscopic traffic models. After the hypothetical on-ramp bottleneck structure is constructed, various simulation scenarios are developed under varying traffic volumes and changing market penetration rates (MPRs) of CAVs. Simulation results show that mixed traffic flow is improved in terms of congestion patterns and traffic capacity. For oscillating and nearly homogeneous congested traffic, congestion degrees are greatly reduced when CAV MPR above 30 % and 50 % respectively. Mixed traffic capacity is increased by 19.3 % when a smaller desired time gap set for CAVs, while it shows no significant change in a larger value. In the HV-HV interactions, traffic conflicts are slightly influenced by CAVs. Comparatively, conflict situations in HV-CAV interactions get worse, the proportion of time to collision (TTC) greater than 2 s monotonically declining with the rise in CAV MPR. It is concluded that traffic characteristics overall show a good momentum when MPR of CAV and the desired time gap of CAVs in mixed traffic are appropriate.

Diffracting crystals of an intrinsically disordered protein (IDP) AtPP16-1 grown in 1.3 V cm−1 DC field

DC electric field as weak as ∼1.3 V cm−1 induces crystal nucleation in very dilute protein solutions lacking precipitant. The basis of such growth is the microscopic model of interaction of protein dipoles with the Stark field, leading to glass-like amorphous aggregation and reconfiguration of the aggregates for crystal nucleation. This modest approach is very different from an earlier and rather ‘aggressive’ one in which electric field of ∼1 kV or orders of magnitude in excess is used to influence charge migration in a highly concentrated protein solution having precipitant confined to the crystallization drop. As an application of the precipitant-lacking ultralow protein method, the present work seeks the assistance of internally supplied 1.3 V cm−1 DC field to crystallize an intrinsically disordered protein (IDP) called AtPP16-1 in a 0.017 mg mL−1 solution. Crystallization is allowed in cuvette cells of spectrometers with online electric field, enabling measurement of real time changes in spectral features. The average crystal size increases with the time of passage of the electric field, from ∼0.042 at 10 min to 0.165 µm at the end of 300 min. The cubic crystals diffract electron and X-ray. Electron diffraction spot indexing yields lattice spacing dhkl ∼ 2.85 Å, consistent with 2.88 Å found from powder X-ray diffraction analysis. This level of lattice spacing will correspond to moderately resolved crystal structure of the IDP.

A frequency-independent bound on trigonometric polynomials of Gaussians and applications

We prove a frequency-independent bound on trigonometric functions of a class of singular Gaussian random fields, which arise naturally from weak universality problems for singular stochastic PDEs. This enables us to reduce the regularity assumption on the nonlinearity of the microscopic models (for pathwise convergence) in KPZ and dynamical Φ34 in the previous works of Hairer-Xu and Furlan-Gubinelli to heuristically optimal thresholds required by PDE structures.

Why do things expand on heating? A discussion on the need for asymmetric potentials to understand thermal expansion

Abstract Understanding thermal expansion is pivotal in various contexts such as comprehending sea level rise due to climate change. Considering the importance of these topics for physics education, this article aims to clarify the characteristics of the models used to represent and explain thermal expansion. Limitations of the linear expansion equation commonly found in textbooks are shown, emphasising the importance of conceptual discussion about thermal expansion. Microscopic models are also explored, demonstrating the inadequacy of the harmonic oscillator model in explaining thermal expansion and introducing the necessity of employing asymmetric potentials. Through the graphic of the Lennard-Jones potential and an algebraic deduction akin to Enrico Fermi’s approach, the thermal expansion of solids and its relation with asymmetric interactions is explored.