Search results

It is proposed a parallel Monte Carlo algorithm to simulate templated grain growth in sintering ceramics materials.
The algorithm applies the general Potts model to treat the matrix as the discrete lattices for simulating the grain growth and there will be a number of lattices to be computed synchronously.
Introduction Grain growth of ceramic crystalline materials sintering has been studied for many years.
It is called an attempt to change the orientation value, and the attempt will be repeated N times while N is the total number of lattices.
Experimental Firstly it is shown the results of the former serial simulations for the templated grain growth.

It is established that the grain boundaries in coarse-grain copper have significantly lower relative energy in contrast to the grain boundaries of ECAP-treated copper.
Additionally, the curves obtained using the proposed model are shown, highlighting the individual groups of grain boundaries that represent the overall distribution, numbered 1 to 5 The application of the proposed model, shown in Fig. 1, made it possible to approximate the experimental distributions with sufficient accuracy.
It was found that grain boundaries in coarse-grained copper have significantly lower relative energy as compared to grain boundaries in ECAP treated copper.
Acknowledgments The research was carried out within the State Assignment (theme “Function”, State registration number AAAA-A19-119012990095-0).
Rabkin, Relative grain boundary energies in ultrafine grain Ni obtained by high pressure torsion, Scr.

It was found that the microstructures of Cu samples with a small number of ECAP passes (4-8) were not inhomogeneous and the fraction of high-angle grain boundary (HAGB) was low (25~43%).
While for the samples with many number of ECAP passes (12-24), the grains became more equiaxed-like and the GB misorientations exhibited double-peak distribution with high fraction (51~64%) of HAGB.
Fig.3 Average grain size and the fraction of HAGB vs.
By contrast, the numbers are increased up to 57.9% and 62.4% when the number of ECAP passes is 16 and 24, respectively.
The increase in the fraction of HAGB in the many-pass samples and the decrease in the average grain size imply that more cells have transformed into real grains after many passes.

Each point is called "lattice point" and is assigned a random number Si between 1 and Q, where Q is the total number of grain orientations at initial state.
Here the number of Q is chosen as two due to the bicrystals.
It is observed that the upper grain A obviously has less deformation than the lower grain B.
These observations show the grain migration from the lower grain B into the upper grain B after 2 hours at 450°C as shown in Fig. 2(b) and (c).
In section III, however, grain A moved toward grain B, and the mobility was small that the grain boundary hardly move after annealing 3 hours at 450°C in Fig.2.

It is observed that grains with more sides than a critical number (equal to six in two dimensions) grow while those below the critical number shrink.
(1) In two dimensions, the rate of change of grain area (A) with time can be related to the number of grain edges (n) (Eq. 2).
Grains having edges greater than six grow and grains having edges lesser than six shrink [12,13]
In the present model, a two-dimensional square lattice with size either 256x256, or 512x512 is populated with a specific number of grains (1000 and 2000 grains respectively) by using a Voronoi tessellation routine, which produces an initial microstructure with near-random distribution of boundary inclinations.
(5) Only those neighbors contribute to the Hamiltonian which are of unlike spin number [1].

A Brief History of the Grain Refinement of Cast Light Alloys D.H.
Today we understand the main factors that lead to good refinement for all alloys systems: growth restricting solute [5,6] and potent particles of optimum particle number density and size distribution [7].
Prior to the 1990s a number of theories were developed [1] to explain grain refinement observations (Table 1).
Reports of good grain refinement.
Prediction capability needs further refinement to quantitatively take into account the simultaneous increase in solute Zr and Zr particle number density.

The crack lies at the interface of two adjacent NC grains with the crack tip intersecting at the grain boundary of the coarse grain.
Let us calculate N--the number of dislocations emitted from a crack tip and retarded at the opposite grain boundaries of the coarse grain.
Fig.5 The maximum number N of edge dislocations that can be emitted from the crack tip along one slip plane as a function of coarse grain size D in NC copper.
It is because that the number of emitted dislocations N increases with increasing the coarse grain size D which can prove more shielding effect on crack.
The dependence of both the maximum number of dislocations, emitted from a crack, and the critical stress intensity factor on grain size d of the NC matrix (ranging from 20 to 100 nm) as well as to the coarse grain size D (ranging from 1 to 10 μm) for Cu were calculated.

The grain boundary fracture toughness (KICgb) was estimated from a percentage of the intergranular fracture as a grain boundary property for each specimen.
The number of sliding pass is one.
After the sliding test, the surface of the sample was observed by scanning electron microscopy (SEM), and the number of grain boundary microcracks as mechanical damage was countered on 50 SEM images of each sample.
The relationship of the amount of silicon debris and the number of microcracks showed qualitatively inverse proportion, namely, the amount of silicon debris increased with decreasing the number of microcracks.
Arrows indicate grain boundary microcracks.

It can be caused by the fact that a standard grit number is defined in terms of grain sizes corresponding to five sieves [3].
The grain distribution standard allows a wide variation of the number of grains of various size fractions in the grain distribution of the same grit number.
So, the actual grain size distribution of close grit numbers can be almost identical.
As it is established by our experiments, the number of such cutting edges on the working surface of an abrasive tool depends on the material type.
The values of the BP and NP parameters depend on the grit number (grain size), the sieve-shaking procedure of abrasive grains and research depth. 2.

So far we have established that the rate of grain growth follows the usual L ~ t1/2 scaling law when the grain boundary energy is independent of the misorientation angle between neighboring grains.
In the standard phase field model the number of different grain types decide the dimensionality of the orientation field vector.
Where as here, irrespective of the number of grain types, we time evolve a 4 dimensional vector only.
Once grains are formed further evolution is driven by the interfacial energy between grains i.e., grains grow in size via coarsening (Fig.1) and average grain size follows the usual t1/2 law (Fig.2).
During coarsening, a quaternion at the interface between two grains is forced by noise to lift off from the minima of one grain and fall into the minima of a neighboring grain; thus the neighboring grain gets bigger at the cost of another grain.