Читать книгу Encyclopedia of Glass Science, Technology, History, and Culture - Группа авторов - Страница 244

Two conceptual models have proved very influential over the years in picturing the overarching aperiodic structure of glass. Zachariasen's continuous random network (CRN), devised for oxide glasses, dates from 1932 [13]. In 1960 Bernal introduced the dense random packing of hard spheres (DRPHS) to describe the structure of liquid metals [25], which has been applied widely to glassy metals once these had been discovered. Both constructs of glass structure, for insulators and metals, respectively, came in advance of experimental techniques that have since illuminated their strengths as well as their shortcomings. The two models are illustrated in Figure 7, reduced to 2‐D arrangements. Presented in this way, they reveal a common basis for constructing aperiodic arrays from contiguous spheres. They markedly differ, however, because each sphere touches just three neighbors in the CRN, resulting in a more open network structure than with the DRPHS where the number of neighboring spheres lies between five and seven. Taken together, though, both the CRN and DRPHS noncrystalline schemes yield a lower density than for their crystalline counterparts, and voids are seen to align mimicking the quasiperiodicity attributed to the FSDP (dashed curves in Figure 7). The increased free volume derives from variations in packing. As such, both CRN and DRPHS offer respective snapshots of the glassy state without informing on the quenching process during which the configurational entropy is generated. With the CRN each sphere embodies the SRO surrounding individual atoms: MO₃ units, for example, mimic SiO₄ tetrahedra in silica glass or BO₃ and BO₄ polyhedra in borate glasses (Figure 7).

The SRO units are interconnected to create corner‐sharing networks of directionally bonded atoms perpetuating indefinitely, which in addition provides a conceptual representation of the extended structures of network glass formers. Although amorphous semiconductors were not yet discovered in 1932, the CRN is equally applicable to chalcogenide glasses like As₂S₃ and also to elemental semiconductors like amorphous As and Ge [7]. In all cases fixed CNs and bond lengths are prescribed by the tenets of the CRN. Usually these parameters are informed from crystalline structures even though space group symmetry is broken by variations in bond angles. Distortions between SRO units lead to rings of atoms of different sizes (Figure 7), including odd‐membered rings seldom found in the crystalline state. Because of the bond angle flexibility of the CRN, point defects, like vacancies and interstitials, can formally be avoided, which is consistent with the observation that optical‐quality glass is almost free of point defects.

By contrast Bernal's DRPHS structure is the geometric outcome of the random packing of spheres, originally ball bearings in a can [25], each representing a metal atom (Figure 7). Designed to model elemental liquid metals, the DRPHS became an approximate structure for glassy metallic alloys where components have similar atomic radii, such as Pd₈₀Si₂₀. Nearest‐neighbor distances in densely packed structures scale with metallic radii, but the packing scheme in three dimensions incorporates icosahedral units avoiding dense‐packed crystalline arrangements. By analogy with the CRN, Bernal's model is free from dislocations that render crystalline metals prone to mechanical damage, which qualitatively explains the exceptional toughness of metallic glasses. Moreover, as the main contribution to metallic electrical resistivity at ambient temperature is governed by the scattering of electrons by irregularities in the positions of core ions, the DRPHS supports the greater electrical resistivity of glassy metals compared to than crystalline metals, enabling the low‐loss of metglas magnetic transformer cores.

The major success of the Zachariasen and Bernal models has been in reconciling SRO with the extended structure of the glassy state. These model structures are isotropic and homogeneous by definition, however, and as such they fail to account for DFs observed almost universally in network as well as in metallic glasses. The solution to this drawback can only be solved through the computer modeling of large 3‐D melt‐quenched structures.