Self-assembly process under a solid-state reaction of β-Si₃N₄/austenitic stainless-steel composites: stirring conditions and material texture

Abstract

In the self-assembly process of β-Si3N4 (SN)/316L stainless-steel (SUS316L) composite materials tailored via sintering of powder mixtures, the formation of a SN agglomerate resulting from condensation–dispersion reactions during the stirring of SN/SUS316L was found to play an important role in improving the thermal conductivity. Moreover, the obtained SN secondary particle groups connected to form a network through diffusion-limited aggregation. In particular, it was shown that the sample prepared at the milling speed of 150 r/min has a similar particle group area (about 1.38 μm2) to that at 120 r/min, but a higher κ (increased from 9.5 W m−1 K−1 to 11.5 W m−1 K−1). To quantitatively evaluate the microstructural morphology of the texture of the self-assembled composite material, global parameters τ( q) and D q and local parameters α( q) and f( α) were determined via multifractal analysis. These characteristics of the anisotropy, dispersion, and cohesiveness of the particle network in the material texture could be analyzed together with the capacity dimension D0, information dimension D1 (configuration entropy), correlation dimension D2, and α( q) (related to internal energy). The results suggest that α( q) reflects the differences in the cohesion of the additive particle agglomeration that constitutes the self-assembly process under the solid-state reaction.

Thermal conductivities and complex network properties of fractal self-assembled/self-organized texture in binary composite materials

“…This is thought to be due to the longer sintering time required for PLS than for SPS, which reflects the influence of grain growth in the base material. This result also corresponds to the results of a previously reported multifractal analysis [6,7]. The crossover from the power-law profile to the exponential function of such networks has already been reported as a local world property [21,22].…”

“…This is similar to the agglomeration/aggregation and growth of fillers in a matrix. As previously reported for fractal material texture organization, [6][7][8][9][10][11][12][13][14][15] the construction of this self-assembly/self-organization consists of the following two processes:…”

“…This is because when estimating the interaction energy (E int. ) between particle groups using multifractal analysis, [7,10,26,27] E int. between the SN particle groups [10] tends to increase with the addition amount; however, E int.…”

“…In particular, the interaction of the filler particles in the matrix and the resulting network formation are important for expressing specific functionality. In fact, in β-Si 3 N 4 (SN)/austenitic stainless steel (SUS) [6,7] and BaTiO 3 (BT)/piezoelectric polyvinylidene fluoride (PVDF) [8][9][10][11][12][13][14][15] systems, the characteristics of the material structure constructed by the process of self-assembly or self-organization have been mapped to material performance such as dielectric properties and thermal conductivity.…”

“…On the other hand, multifractal analysis [1-5], which is widely used in physics, chemistry, medicine, and engineering involving morphology and shape, is being applied to the field of materials science. Recently, this analysis has been used to reveal the particle morphology, arrangement, dispersion, and statistical thermodynamic properties during chemical reaction processes, and has been shown to be effective in clarifying the dissipation state of particles due to self-organized or self-assembled processes in real binary systems (metal/ceramics and polymer/ceramics) [6][7][8][9][10]. In particular, the general dimension D q (multiple fractal dimension for q-th order moment) and scaling exponent τ q obtained from the microstructural morphologies of self-organized or self-assembled materials serve as material design indices for designing composite materials with Fumio Munakata…”