
doi: 10.1007/bf02646981
This paper considers the problem of impurity segregation in metals and the effect of these impurities on grain boundary cohesion. The primary goal of this paper is to provide a physical model that will allow us to think about these two processes. We describe both of them in chemical terms. Segregation is treated as a distribution of a solute between two phases. In this way, it is a typical example of heterogeneous equilibrium. We also consider the various driving forces for solute segregation and find that the correlation between decreased solubility and increased segregation, first proposed by Hondros and Seah,[9] is still an adequate one. We introduce the discussion of grain boundary fracture by pointing out that as the impurity enters the boundary, it establishes chemical bonds with the structural units of the boundary. The segregated boundary can then be thought of as a string of molecular units with bonds of different types. Some of these bonds will be weaker than others, and they will be the ones that eventually fracture when a stress is applied. We consider the cause of these weak bonds and suggest that the primary reason for them is the transfer of electronic charge from the metal atoms to the impurity, as proposed in previous work.[3] However, some of the ideas in the earlier models should be amended based on new results obtained from the quantum mechanical analysis of bonding in metals presented by McAdon and Goddard.[10,11] We also suggest that intergranular brittleness of intermetallic compounds such as Ni3Al, which occurs in the absence of impurity segregation, can be explained by the charge distribution present at the grain boundary. Finally, we provide a critique of other models that have been used to describe grain boundary fracture and segregation.
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 74 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Top 10% | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Top 10% | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Top 10% |
