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As the properties of sintered products are considerably affected by the microstructures formed during sintering, numerical simulation is essential for predicting and controlling microstructures with high accuracy. Although the phase-field method can reproduce sintered microstructures with the highest accuracy, its high computational cost has limited the scale of computation. In this study, we develop a multi-phase-field (MPF) sintering model with a double-obstacle potential that is effective for large-scale simulations. We also establish an efficient algorithm on graphics processing unit (GPU) to accelerate the computations of rigid-body motions of particles, which cause densification, and implement it on multiple GPUs in parallel. The simulation method enables three-dimensional large-scale MPF sintering simulations of approximately 160,000 Al2O3 particles on 1,2803 grid points, which is sufficiently large to reproduce a bulk sintering behavior. For the large-scale simulation results, the difference between near-surface and bulk sintering behaviors is discussed. The large-scale MPF sintering simulation method developed in this study is expected to contribute to the accurate prediction and control of sintered microstructures significantly.

Morphological diversity in directionally-solidified microstructures of fcc-based binary alloys was investigated using quantitative phase-field simulation. The growth morphology for each set of anisotropy parameters was identified from the degree of undercooling of the dendrite tip and a morphology map was constructed. We investigated the effects of solidification conditions and alloy systems on growth morphology and found that the pulling speed has a significant effect, while temperature gradient and partition coefficient have only small effects on the morphology selection. Furthermore, we examined the emergence of doublon and triplet dendrites under conditions of weak interfacial anisotropy.

Permeability for interdendritic flow plays a crucial role in accurately simulating macrosegregation. The dimensionless permeability of normal flow for columnar structures growing along a temperature gradient is conventionally represented by using the Kozeny–Carman (KC) equation with a KC coefficient kc= 9. In this study, we used high-performance computing to predict permeability for columnar dendrites tilted from the temperature gradient direction in both single crystals and polycrystals with phase-field and lattice Boltzmann methods. In single crystals, to cover all solid fractions, permeability was predicted for periodic hexagonal arrays as well as multiple dendrites. We found that the complexity of dendrite morphology and the directional dependency of interdendritic flow increased considerably with increasingly tilted angles for single crystals. The dimensionless permeability remained in good agreement with the KC equation for angles below 20° and deviated from the KC equation with kc= 9 for tilted angles above 30°. For polycrystals, we predicted permeability for systems sufficiently large to be independent of the flow direction. The complexity of dendrite morphology decreased with growth owing to the overgrowth of grains with a large tilt angle by smaller grains. Consequently, the predicted dimensionless permeability deviated from the KC equation with kc= 9.

Abstract In the phase-field simulation of dendrite growth during the solidification of an alloy, the computational cost becomes extremely high when the diffusion length is significantly larger than the curvature radius of a dendrite tip. In such cases, the adaptive mesh refinement (AMR) method is effective for improving the computational performance. In this study, we perform a three-dimensional dendrite growth phase-field simulation in which AMR is implemented via parallel computing using multiple graphics processing units (GPUs), which provide high parallel computation performance. In the parallel GPU computation, we apply dynamic load balancing to parallel computing to equalize the computational cost per GPU. The accuracy of an AMR refinement condition is confirmed through the single-GPU computations of columnar dendrite growth during the directional solidification of a binary alloy. Next, we evaluate the efficiency of dynamic load balancing by performing multiple-GPU parallel computations for three different directional solidification simulations using a moving frame algorithm. Finally, weak scaling tests are performed to confirm the parallel efficiency of the developed code.

Utilizing the data assimilation and multi-phase-field grain growth model, this study proposes a novel framework of measuring anisotropic (nonuniform) grain boundary energy and mobility. The framework can evaluate a large number of boundary properties from typical observations of grain growth without requiring specifically designed experiments or calculations. In this method, by optimizing the multi-phase-field model parameters such that the simulation results are in good agreement with the observation data, the energies and mobilities of multiple individual boundaries are directly and simultaneously estimated. To validate the method, numerical tests on boundary property estimation were performed using synthetic microstructure dataset generated from grain growth simulations with a priori assumed property values. Systematic tests on simple tricrystal systems confirmed that the proposed method accurately estimates each boundary energy and mobility within an error of only several % of their assumed true values even for conditions with strong property anisotropy and grain rotation. Further numerical tests were conducted on a more general multi-grain system, showing that our method can be successfully applied to complicated polycrystalline grain growth. The obtained results demonstrate the potential of the proposed method in extracting a large dataset of grain boundary properties for arbitrary boundaries from actual grain growth observations.

Temperature dependence of solid–liquid interfacial properties during crystal growth in nickel was investigated by ensemble Kalman filter (EnKF)-based data assimilation, in which the phase-field simulation was combined with atomic configurations of molecular dynamics (MD) simulation. Negative temperature dependence was found in the solid–liquid interfacial energy, the kinetic coefficient, and their anisotropy parameters from simultaneous estimation of four parameters. On the other hand, it is difficult to obtain a concrete value for the anisotropy parameter of solid–liquid interfacial energy since this factor is less influential for the MD simulation of crystal growth at high undercooling temperatures. The present study is significant in shedding light on the high potential of Bayesian data assimilation as a novel methodology of parameter estimation of practical materials an out of equilibrium condition.

Grain growth: Simulations elucidate statistical behavior Grain growth under ideal conditions is simulated by phase-field simulations in ultra-large time and space scales to elucidate the statistical behaviors. A team led by Tomohiro Takaki at Kyoto Institute of Technology in Japan performed large scale phase-field simulations to study ideal grain growth behavior. The time and space scales used in the simulations are more than ten times larger than those in previous reports, enabling them to reach a true steady-state with a statistically significant number of grains. A comprehensive theoretical description was derived to understand the ideal grain growth behavior based on the simulations. The knowledge provided by these findings may offer a model to understand the effects of complicated factors present in real materials and thus establish a platform to study more realistic grain growth phenomena in the future.

Nucleation is a fundamental physical process, however it is a long-standing issue whether completely homogeneous nucleation can occur. Here the authors reveal, via a billion-atom molecular dynamics simulation, that local heterogeneity exists during homogeneous nucleation in an undercooled iron melt.

Galling and wear have been a tribology problem in sheet metal forming of stainless steel. Although lubrication oil with chlorinated extreme pressure (EP) additives have been used, environmental and safety issues have demanded not to use chlorinated EP additives. For developing chloride-free oil for cold ironing of stainless steels, some commercial sulfur-based EP additives were evaluated by a cup internal ironing test. Moreover, the superior sulfur-based EP additive was combined with calcium- and zinc-base type additives in order to improve anti-galling performance. The mixture oil, as shown the high performance in the cup internal ironing test, successively passed a 10,000 shots practical process with severe ironing of stainless steel. After the 10,000 shots, it was found that no galling was observed on these 10,000 products. Based on the X-ray photoelectron spectroscopy (XPS) results, sulfide and calcium carbonate were formed on the surface of the products. This lubricating film seems to prevent galling in the practical process. The developed oil is an example of a chloride-free oil to replace the conventional chloride-containing oil.

The conventional phase-field topology optimization (PFTO) models minimize not only the objective function but also the interface energy. In the present study, a new PFTO model, which minimizes only the objective function, is developed by removing the curvature effect from the conventional PFTO model. Simulations of elastic strain energy minimization under a constant-volume constraint condition of a cantilever are performed using the developed and conventional PFTO models. From the simulation results, we confirm that the developed PFTO model that removes the curvature effects can efficiently optimize only the objective function.

In this study, we applied a modified Kobayashi-Warren-Carter (KWC) phase-field model to the neurite growth process. To confirm the applicability of this model, we observed axonal extension of PC-12D cells cultured with nerve growth factor (NGF). Based on our observations, we defined three stages of nerve cell axonal extension: neurite generation, neurite contraction, and axon extension. We further determined the parameters in the phase-field equations to express the three extension stages. Finally, our results show that the modified KWC phase-field model reasonably expresses the morphologies of nerve cells and predicts the three stages of nerve cell axonal extension. Although, we employed the binary alloy solidification model as a sample model in the present phase-field simulations, this work will be extensible to relatively more realistic models for nerve cell growth.

The authors analyzed the structures of sulfurized olefins using NMR spectroscopy and studied the effects of sulfur chain length and alkyl structure on the ironing performance. They found that branched chain olefins, which contain branched alkyl groups, show superior ironing performance to straight chain olefins, provided that their carbon numbers are relatively low. When the sulfurized olefins were used in combination with overbased detergents (calcium sulfonate or salicylate), they showed a higher performance in ironing than with sulfurized olefins alone. It was also found that lubricating films consisting of both iron sulfide and calcium carbonate seem to improve ironing performance.