The orientation
relationships (ORs) between precipitates and a matrix are closely related to the
precipitate morphology. A deep understanding of morphological crystallography forms
the basis for controlling precipitate shapes and provides scientific guidance
for improving the strength and plasticity of materials. The coexistence of
multiple ORs has been observed in several precipitation systems, providing
opportunities to manipulate precipitate morphology. The Mg–Sn-based alloy is a
typical example of such a system. Previous studies have reported 13 ORs between
Mg2Sn and the matrix in this system. These studies explained and
predicted these ORs using the preferential matching principle for primary
planes. However, this traditional approach alone cannot fully explain why the number
of observed ORs is considerably lower than the predicted number. This study
systematically analyzes the previous experimental data to further explore the
natural preference rules governing the primary planes. By applying lattice
matching criteria that considers smaller mismatches and shorter matching
vectors, several well-matched vector pairs are identified. However, no vector
pair simultaneously exhibits the shortest length and minimal misfit. It is proposed
that the presence of multiple well-matched vector pairs contributes to the
coexistence of multiple ORs. A systematic analysis of the previous experimental
results also reveals that preventing dislocations with long Burgers vectors is
an important factor that further constrains the primary facets. A new
analytical method focusing on the primary matching column—shared by primary and
secondary facets—is introduced. The primary matching column must be parallel to
the short Burgers vector of dislocations, unless it is aligned parallel to an
invariant or near-invariant line. Based on the characteristics of the primary
matching column, the observed ORs are classified, improving our understanding
of ORs and explaining why most precipitates lie on the (0001)α plane. These new findings provide insights into the
coexistence of multiple ORs in other systems and contribute to a knowledge base
for optimizing precipitate morphologies.