Multiscale Simulation Strategy Research Articles

(Invited) The Electrochemical-Mechanical Coupled Interface Contacts during Lithium Plating and Stripping

The current density during battery operation is often assumed uniform across the entire electrode surface. This may be valid for conformal solid/liquid interfaces; however, solid/solid interfaces generally have imperfect contacts. By introducing the contact area ratio, γ, to the electrochemical model, it can be demonstrated clearly that the effective current density scales linearly with the 1/γ and the overpotential scales exponentially with contact area loss, 1-γ.The calculation of surface contact area must consider the multi-length-scale nature of surface roughness. Assuming surface roughness is self-affine, Bo Persson’s multiscale contact mechanics model for elastic materials can be used for the cathode/solid electrolyte interface to predict the necessary pressure to maintain the original contact area. [1]However, the most challenging process is Li-stripping, as the vacancy generated by each Li atom removed from the interfaces can accumulate and generate voids, reducing the contact area. However, under an applied stack pressure, the self-affine property will reach a steady state interface contact ratio (γo.) in different length scales. Thus, we proposed a coupled atomistic-and-continuum model, which will capture Li striping and vacancy hopping and accumulation near the Li/SE interface with Density Functional Theory (DFT) informed Kinetic Monte Carlo (KMC) simulations and predict the macroscopic contact area evolution according to the macroscopic creep law with finite element simulations (FEM). The creep rate will be mapped to preferred forward hopping rates for all the Li atoms at the atomic scale. Solving these models iteratively leads to a steady contact area ratio (γo.). Generally, lithiophilic interface requires less stack pressure to maintain a flat surface while a higher stack pressure is needed at lithiophobic interfaces to accelerate Li vacancy diffusion into the bulk and maintain a flat surface. This critical stack pressure needs to be high enough to alter the Li forward-and-backward hopping barriers at the interface. This predictive multiscale simulation scheme was able to combine multiple chemical-mechanical effects during Li stripping morphology evolution. [2,3] [1] Hong-Kang Tian and Yue Qi, Electrochem. Soc. 2017, 164, E3512[2] T. Yang and Y. Qi, Chem. Mat. 2021, 33, 2814-2823[3] Feng, C.T. Yang, and Y. Qi, J. Electrochem. Soc. 2022, 169, 090526

Multiscale simulation scheme by using a finite-difference derivative framework for lubrication surface

To exactly describe lubrication problems modelling micro-scale influence in rough lubricated contact is unavoidable. In this study a novel computational scheme for lubricated problem is presented based on two-scale homogenization method, which facilitates solving the two-scale problem. Homogenization model of mass fluxes is implemented at the micro-scale domain, and represents the influence of surface topography. A linearization method is developed to derive finite derivatives of mass fluxes at the micro-scale domain defined by scale separation. The key strength of the proposed procedure is the finite difference derivative coupling which represents the lubricated problem inclusive of the effect of surface topography. The effectiveness of the proposed multiscale scheme is validated by comparing with the deterministic method. The numerical results show that increasing topography amplitude can improve the performance of journal bearing in terms of load carrying capacity and friction coefficient.

Multiscale simulation of hygrothermal stress and mechanical properties degradation of carbon fiber reinforced polymers laminates

AbstractA mesoscopic representative volume element (RVE) model of carbon fiber reinforced polymers (CFRP) laminate with 15 plies was established based on the principle of fiber random disturbance. The RVE model was validated by comparing the elastic parameters calculated by the RVE model, Chamis model, and Bridge model. Wet stress and thermal stress were coupled using a sequential method. Macroscopic and microscopic subroutines were developed to calculate the stress–strain field of CFRP laminate and RVE model. A multiscale numerical simulation of three‐point bending of moisture‐saturated CFRP laminate was conducted. Failure process and failure modes of CFRP laminate were discussed based on the multiscale simulation and SEM observations. The results show that the RVE model and the multiscale simulation strategy presented in this work can predict the coupled hygrothermal stress and the strength degradation due to moisture absorption very well. The maximum error between the simulated and experimental averaged force of the moisture‐saturated CFRP laminate subjected to three‐point bending is about 3.4%. Multiscale simulation demonstrated that uneven distribution of fibers can result in the fiber/matrix interfaces bearing a larger transverse stress in the fiber's dense distribution area. It is the main reason that results in fiber/matrix interface failure of CFRP laminates working in hygrothermal environments.Highlights A RVE model of CFRP laminate was presented using fibers random disturbance. Coupled hygrothermal stress of single fiber and surrounded matrix was obtained. A multiscale simulation of the strength change of the CFRP plate due to wet‐thermal stress was conducted. Failure modes of CFRP laminate are discussed based on the multiscale simulation.

Numerical investigation into vibration damping in woven composite structures

This study numerically investigates the mechanism of vibration damping in woven composite structures using a decoupled multi-scale simulation scheme that considers the macroscopic woven structure consisting of bundles and resin-rich regions, as well as the microscopic structure in the bundles made of fiber and resin. For efficient macroscopic modeling of complicated woven structures, the embedded element technique is introduced to utilize separate meshes for bundles and resin regions. A special treatment is introduced for volumetric integration in the mesh overlapped between bundle and resin regions, which is required to calculate the strain energy and modal damping ratio of the entire woven structure. Using the developed scheme, the natural frequencies and damping ratios of braided and laminated composite cylinders are investigated. By comparing the vibration properties of two braided composites with different braided angles and two unidirectional laminates with different fiber volume fractions, the effects of the fiber volume fraction, braided angle, and out-of-plane waviness on vibration properties are discussed. Based on the mode shape and resultant energy dissipation within each bundle and resin-rich region, the braided composite with a large braided angle exhibited the best damping properties, mainly owing to the in-plane shear deformation in the crimped braided bundles.

Damage preserving transformation for materials with microstructure

The failure of heterogeneous materials with microstructures is a complex process of damage nucleation, growth and localisation. This process spans multiple length scales and is challenging to simulate numerically due to its high computational cost. One option is to use domain decomposed multi-scale methods with dynamical refinement. If needed, these methods refine coarse regions into a fine-scale representation to explicitly model the damage in the microstructure. However, damage evolution is commonly restricted to fine-scale regions only. Thus, they are unable to capture the full complexity and breath of the degradation process in the material. In this contribution, a generic procedure that allows to account for damage in all representations is proposed. The approach combines a specially designed orthotropic damage law, with a scheme to generate pre-damaged fine-scale microstructures. Results indicate that the damage approximation for the coarse representation works well. Furthermore, the generated fine-scale damage patterns are overall consistent with explicitly simulated damage patterns. Minor discrepancies occur in the generation but subsequently vanish when explicit damage evolution continuous; for instance under increased load. The presented approach provides a methodological basis for adaptive multi-scale simulation schemes with consistent damage evolution.

Supported Pt Nanoclusters on Single-Layer MoS2 for the Detection of Cortisol: From Atomistic Scale to Device Modeling

The development of nonenzymatic sensors is a challenge which requires, on the one hand, careful design of the sensing materials with respect to the chosen analyte, and on the other hand, suitable device architectures. In this work, we propose single-layer molybdenum disulfide (MoS2) decorated with subnanometer Pt clusters as the sensing platform for the detection of cortisol. The aim is to assess the suitability of such a sensing platform for the development of wearable and portable cortisol sensors. For this study, we performed multiscale computer simulations at the materials level up to device scale. First, ab initio simulations within the framework of density functional theory (DFT) allowed us to gain insights into the interaction, at the atomic level, between the analyte (cortisol) and the sensing platform (MoS2/Pt). Then, by carrying out technology computer-aided design (TCAD) simulations, we were able to consider a device architecture and investigate its performance as cortisol sensor. Following our multiscale simulation strategy, we were able to assess the proposed field-effect transistor (FET) sensor, whose channel is made of Pt-decorated MoS2. The sensing mechanism relies on the chemiresistive response of the device to the adsorption of cortisol on the channel, which leads to a sizable charge transfer from the analyte to the substrate and, consequently, to the measurable shift in the gate voltage threshold of the FET. Our findings suggest that both the choice of the sensing materials and the proposed FET architecture are suitable for detecting cortisol by non-enzymatic means. In the best case scenario, we predict theoretical gate voltage shifts between 76 and 780 mV with respect to the cluster concentration and between 27 and 780 mV when varying the cluster occupancy by cortisol. We may expect our results to provide the necessary basis to develop highly sensitive nonenzymatic cortisol sensors based on 2D materials decorated with Pt nanoclusters.

A Generic Framework for Multiscale Simulation of High and Low Enthalpy Fractured Geothermal Reservoirs under Varying Thermodynamic Conditions

We develop a multiscale simulation strategy, namely, algebraic dynamic multilevel (ADM) method, for simulation of fluid flow and heat transfer in fractured geothermal reservoirs under varying thermodynamic conditions. Fractures with varying conductivities are modeled using the projection-based embedded discrete fracture model (pEDFM) in an explicit manner. The developed ADM method allows the fine-scale system to be mapped to a discrete domain with an adaptive grid resolution via the use of the restriction and prolongation operators. The developed framework is used (a) to investigate the impacts of formulations with different primary variables on the simulation results, and (b) to assess the performance of ADM in a high-enthalpy reservoir by comparing the simulation results against those obtained from fine-scale grids. Results show that the two formulations produce similar results in the case of single-phase flow, which indicates that the molar formulation is a favorable option that can be applied to varying thermodynamic conditions. Moreover, the ADM can provide accurate solutions with only a fraction of fine-scale grids, e.g., for the studied case, the maximum error is by average 1.3 with only 42% of active cells, thereby improving the computational efficiency. This is promising for applying the developed method to field-scale geothermal systems.

Ribonucleic Acid Folding Prediction Based on Iterative Multiscale Simulation

RNA folding prediction is a challenge. Currently, many RNA folding models are coarse-grained (CG) with the potential derived from the known RNA structures. However, this potential is not suitable for modified and entirely new RNA. It is also not suitable for the folding simulation of RNA in the real cellular environment, including many kinds of molecular interactions. In contrast, our proposed model has the potential to address these issues, which is a multiscale simulation scheme based on all-atom (AA) force fields. We fit the CG force field using the trajectories generated by the AA force field and then iteratively perform molecular dynamics (MD) simulations of the two scales. The all-atom molecular dynamics (AAMD) simulation is mainly responsible for the correction of RNA structure, and the CGMD simulation is mainly responsible for efficient conformational sampling. On the basis of this scheme, we can successfully fold three RNAs belonging to a hairpin, a pseudoknot, and a four-way junction.

The Critical Stack Pressure to Alter Void Generation at Li/Solid-Electrolyte Interfaces during Stripping

The lithium stripping process generates vacancies, which may accumulate as voids and lead to uneven current distribution and dendrite growth in the following plating cycles. A stack pressure is typically required during stripping, but how to optimize the stack pressure is not clear. In this work, extremely lithiophilic Li/Li2O and lithiophobic Li/LiF interfaces were used to reveal the combining effect of interface interaction and stack pressure induced lithium creep on the stripping critical current density (CCD). A multiscale simulation scheme with Density Functional Theory (DFT), kinetic Monte Carlo (KMC) simulations, and an analytical model was developed. The analytical model predicted lithiophobic interfaces require a higher stack pressure than lithiophilic interfaces to reach the same CCD. The KMC simulations also showed higher stack pressure is needed at lithiophobic interfaces to accelerate Li vacancy diffusion into the bulk and maintain a flat surface. This stack pressure needs to be high enough to alter the Li forward-and-backward hopping barriers at the interface. This multiscale simulation scheme illustrates the importance to include the chemical-mechanical effects during Li stripping morphology evolution. It can be used to design ideal interlayer coating materials to maintain a flat Li surface during cycling.

Derivation of Liouville-like equations for the n-state probability density of an open system with thermalized particle reservoirs and its link to molecular simulation

A physico-mathematical model of open systems proposed in a previous paper (Delle Site and Klein 2020 J. Math. Phys. 61 083102) can represent a guiding reference in designing an accurate simulation scheme for an open molecular system embedded in a reservoir of energy and particles. The derived equations and the corresponding boundary conditions are obtained without assuming the action of an external source of heat that assures thermodynamic consistency of the open system with respect to a state of reference. However, in numerical schemes the temperature in the reservoir must be controlled by an external heat bath otherwise thermodynamic consistency cannot be achieved. In this perspective, the question to address is whether the explicit addition of an external heat bath in the theoretical model modifies the equations of the open system and its boundary conditions. In this work we consider this aspect and explicitly describe the evolution of the reservoir employing the Bergmann–Lebowitz statistical model of thermostat. It is shown that the resulting equations for the open system itself are not affected by this change and an example of numerical application is reviewed where the current result shows its conceptual relevance. Finally, a list of pending mathematical and modelling problems is discussed the solution of which would strengthen the mathematical rigour of the model and offer new perspectives for the further development of a new multiscale simulation scheme.

A novel ANN-Based boundary strategy for modeling micro/nanopatterns on airfoil with improved aerodynamic performances

In this paper, in order to overcome computational challenge in numerical simulations of airfoil covered with micro/nanopatterns for aerodynamic drag-reduction design, an ANN-Based boundary strategy is proposed to balance the accuracy and efficiency. Lattice Boltzmann Method (LBM) is utilized to extract the micro/nanoflow characteristics in the near-wall region considering the rarefied effect and the available microscopic data is used to train the surrogate boundary model by Generalized Regression Neural Network (GRNN). The modified boundary conditions obtained by ANN-Based model replacing the real complex and fine micro/nano structure are applied on the smooth configuration to perform macroscopic simulations. Rectangular riblets as micro/nano pattern are discussed for our study. Various arrangement strategies of rectangular riblets over airfoil are adopted by adjusting the width, height, and coverage area to investigate their effects on aerodynamic performances. The results indicate that for the riblet airfoil, the skin friction reduces and the transition position moves backward compared with those of the smooth airfoil. Furthermore, the lift-to-drag ratio also significantly increases and the rate of improvement is up to 13.8% at the Angle of Attack (AOA) of 1°. This paper shows a perspective in aerodynamic design with micro/nano pattern for drag reduction by providing an innovative multi-scale simplified simulation strategy.

3D Multilevel Modeling of Surface Roughness Influences on Hole Expansion Ratios

The steel grade DP1000 is widely used in various industrial application fields. Its mechanical properties satisfy basic requirements in terms of strength and global formability due to the tailored microstructure composed of ductile ferrite and hard martensite. Nevertheless, the edge crack sensitivity of dual‐phase steels is still of interest. For its evaluation, hole expansion tests have become a standard experimental approach. Finite element simulation is a tool that further supports the assessment of edge crack resistance by providing insights into local stress and strain fields at the formed edges during hole expansion tests. However, there are still discrepancies between the experiments and simulations in terms of force–displacement curves and hole expansion ratios due to several factors including the hole edge surface condition. To overcome these discrepancies, this work proposes a 3D multiscale simulation strategy to quantify this factor under a complex loading case and to include it into the simulation approaches. The workflow is sufficiently general to handle arbitrary load cases. Compared with state‐of‐the‐art ductile damage mechanics simulations, the accuracy of the simulations is significantly improved.

Ultrathin 2D Titanium Carbide MXene (Ti3 C2 Tx ) Nanoflakes Activate WNT/HIF-1α-Mediated Metabolism Reprogramming for Periodontal Regeneration.

Periodontal defect regeneration in severe periodontitis relies on the differentiation and proliferation of periodontal ligament cells (PDLCs). Recently, an emerging 2D nanomaterial, MXene (Ti3 C2 Tx ), has gained more and more attention due to the extensive antibacterial and anticancer activity, while its potential biomedical application on tissue regeneration remains unclear. Through a combination of experimental and multiscale simulation schemes, Ti3 C2 Tx has exhibited satisfactory biocompatibility and induced distinguish osteogenic differentiation of human PDLCs (hPDLCs), with upregulated osteogenesis-related genes. Ti3 C2 Tx manages to activate the Wnt/β-catenin signaling pathway by enhancing the Wnt-Frizzled complex binding, thus stabilizing HIF-1α and altering metabolic reprogramming into glycolysis. In vivo, hPDLCs pretreated by Ti3 C2 Tx display excellent performance in new bone formation and osteoclast inhibition with enhanced RUNX2, HIF-1α, and β-catenin in an experimental rat model of periodontal fenestration defects, indicating that this material has high efficiency of periodontal regeneration promotion. It is demonstrated in this work that Ti3 C2 Tx has highly efficient therapeutic effects in osteogenic differentiation and periodontal defect repairment.

Applying multi-scale simulations to materials research of nuclear fuels: A review

Computational simulation is an important technical means in research of nuclear fuel materials. Since nuclear fuel issues are inherently multi-scopic, it is imperative to study them with multi-scale simulation scheme. At present, the development of multi-scale simulation for nuclear fuel materials calls for a more systematic approach, in which lies the main purpose of this article. The most important thing in multi-scale simulation is to accurately formulate the goals to be achieved and the types of methods to be used. In this regard, we first summarize the basic principles and applicability of the simulation methods which are commonly used in nuclear fuel research and are based on different scales ranging from micro to macro, i.e. First-Principles (FP), Molecular Dynamics (MD), Kinetic Monte Carlo (KMC), Phase Field (PF), Rate Theory (RT), and Finite Element Method (FEM). And then we discuss the major material issues in this field, also ranging from micro-scale to macro-scale and covering both pellets and claddings, with emphasis on what simulation method would be most suitable for solving each of the issues. Finally, we give our prospective analysis and understanding about the feasible ways of multi-scale integration and relevant handicaps and challenges.

A multiscale volume of fluid method with self-consistent boundary conditions derived from molecular dynamics

Molecular dynamics (MD) and volume of fluid (VOF) are powerful methods for the simulation of dynamic wetting at the nanoscale and macroscale, respectively, but the massive computational cost of MD and the sensitivity and uncertainty of boundary conditions in VOF limit their applications to other scales. In this work, we propose a multiscale simulation strategy by enhancing VOF simulations using self-consistent boundary conditions derived from MD. Specifically, the boundary conditions include a particular slip model based on the molecular kinetic theory for the three-phase contact line to account for the interfacial molecular physics, the classical Navier slip model for the remaining part of the liquid–solid interface, and a new source term supplemented to the momentum equation in VOF to replace the convectional dynamic contact angle model. Each slip model has been calibrated by the MD simulations. The simulation results demonstrate that with these new boundary conditions, the enhanced VOF simulations can provide consistent predictions with full MD simulations for the dynamic wetting of nanodroplets on both smooth and pillared surfaces, and its performance is better than those with other VOF models, especially for the pinning–depinning phenomenon. This multiscale simulation strategy is also proved to be capable of simulating dynamic wetting above the nanoscale, where the pure MD simulations are inaccessible due to the computational cost.

A new all-inorganic vacancy-ordered double perovskite Cs2CrI6 for high-performance photovoltaic cells and alpha-particle detection in space environment

Although MAPbI3 photovoltaics have gained increasing interest for space application, its low stability and radiation resistance is insurmountable. Here, we unexpectedly find a new vacancy-ordered double perovskite Cs2CrI6 to realize high-performance space solar cells and α-particle detectors through an innovative multi-scale simulation strategy based on the first-principle calculations coupling with drift-diffusion model and Monte Carlo method. Compared to the MAPbI3, Cs2CrI6 possesses more excellent stability and optical absorption, suitable band gap (1.08 eV), higher mobility (∼103 cm2/V) and lower capture cross-section. These lead to the ultra-high power conversion efficiency (PCE) for single-junction solar cells (22.4%) and monolithic all-perovskite tandem solar cells (26.6%), and excellent α-particle detectors with ultra-high charge collection efficiency (CCE = 99.3%) and mobility-lifetime product (μτh = 4.99 × 10−3 cm2V−1), which are superior to those of corresponding MAPbI3 devices. Meanwhile, the 90% of initial PCE can be remained even under the 5 × 1013 p. cm−2 fluence proton beam and several orders higher than traditional space solar cell. Moreover, the proton irradiation resistance of Cs2CrI6 α-particle detection can reach up to 1016 p. cm−2. The excellent device performance and irradiation resistance of Cs2CrI6 devices indicate the great potential application in photovoltaic cells, α-particle detectors and even their space applications.

Network structure and properties of crosslinked bio-based epoxy resin composite: An in-silico multiscale strategy with dynamic curing reaction process

A multiscale simulation strategy was proposed to study the curing reaction on the network formation and corresponding mechanical properties of a bio-based epoxy resin composite. The crosslinking process of the system to form an epoxy network structure was reproduced on the mesoscopic scale by the dissipative particle dynamics simulation coupled with a curing reaction model. The density functional theory (DFT)-based method, IRC and relaxed potential energy surface scanning calculations were combined with the reverse mapping operations in order to improve the overall quality the reverse mapped structures. Finally, molecular dynamics simulations were performed on the atomistic level to analyze the mechanical properties, the volume shrinkage and the glass transition of the bio-based epoxy resin system, etc. This multiscale simulation strategy can provide as a possible investigation scheme for the subsequent improvement and design of bio-based epoxy resin composite materials.

Adaptively Iterative Multiscale Switching Simulation Strategy and Applications to Protein Folding and Structure Prediction.

Structure prediction is an important means to quickly understand new protein functions. However, the prediction of effects of proteins that have no detectable templates is still to be improved. Molecular dynamics simulation is supposed to be the primary research tool for structure predictions, but it still has limitations of huge computational cost in all-atom (AA) models and rough accuracy in coarse-grained (CG) models. We propose a universal multiscale simulation strategy named AIMS in which simulations can iteratively switch among multiple resolutions in order to adaptively trade off AA accuracy and CG high-efficiency. AIMS follows the idea of CG-guided enhanced sampling so that final results always keep AA accuracy. We successfully achieve four ab initio and four data-assisted protein structure predictions using AIMS. The prediction result is an ensemble rather than a structure and provides special insights on folding metastable states. AIMS is estimated to achieve a computational speed about 40 times faster than that of conventional AA simulations.

Validation of a multi-scale simulation strategy based on the Pointwise Strain Superposition Method

This paper details the experimental validation of a multi-scale simulation strategy that we developed for predicting the stresses and distortions induced by Powder Bed Fusion processes. The strategy comprises a meso-scale model, a macro-scale model, and a scaling method named Pointwise Strain Superposition. The first model evaluates the temperature, stress, and strain fields produced by a single scan line. The scaling method transfers the meso-scale results to the macro-scale model, which is then able to simulate the entire manufacturing process with a reasonable computational cost. The simulation strategy was validated by comparing its results with the stresses and distortions measured on several specimens made of selective laser melted Inconel 718. Stresses were measured through the blind hole drilling method on a cylindrical specimen printed with two different scanning strategies, while distortions were measured on a hollow cylinder and on a cantilever-shaped specimen after removing its supports. In both cases the simulation showed first- or higher-order accuracy despite the significant uncertainties regarding the input parameters and material properties. This robustness, coupled with its computational efficiency, leads us to believe that our simulation strategy could enhance the process optimization and provide a better understanding of the underlying physical phenomena along with their effects on the manufactured parts.

Molecular Details of Protein Condensates Probed by Microsecond Long Atomistic Simulations.

The formation of membraneless organelles in cells commonly occurs via liquid-liquid phase separation (LLPS) and is in many cases driven by multivalent interactions between intrinsically disordered proteins (IDPs). Investigating the nature of these interactions, and their effect on dynamics within the condensed phase, is therefore of critical importance but very challenging for either simulation or experiment. Here, we study these interactions and their dynamics by pairing a novel multiscale simulation strategy with microsecond all-atom MD simulations of a condensed, IDP-rich phase. We simulate two IDPs this way, the low complexity domain of FUS and the N-terminal disordered domain of LAF-1, and find good agreement with experimental information about average density, water content, and residue-residue contacts. We go significantly beyond what is known from experiments by showing that ion partitioning within the condensed phase is largely driven by the charge distribution of the proteins and-in the cases considered-shows little evidence of preferential interactions of the ions with the proteins. Furthermore, we can probe the microscopic diffusive dynamics within the condensed phase, showing that water and ions are in dynamic equilibrium between dense and dilute phases, and their diffusion is reduced in the dense phase. Despite their high concentration in the condensate, the protein molecules also remain mobile, explaining the observed liquid-like properties of this phase. We finally show that IDP self-association is driven by a combination of nonspecific hydrophobic interactions as well as hydrogen bonds, salt bridges, and π-π and cation-π interactions. The simulation approach presented here allows the structural and dynamical properties of biomolecular condensates to be studied in microscopic detail and is generally applicable to single- and multicomponent systems of proteins and nucleic acids involved in LLPS.