  Bulk metallic glasses (BMGs) are amorphous alloys with desirable mechanical
properties and processing capabilities. To date, the design of new BMGs has
largely employed empirical rules and trial-and-error experimental approaches.
Ab initio computational methods are currently prohibitively slow to be
practically used in searching the vast space of possible atomic combinations
for bulk glass formers. Here, we perform molecular dynamics simulations of a
coarse-grained, anisotropic potential, which mimics interatomic covalent
bonding, to measure the critical cooling rates for metal-metalloid alloys as a
function of the atomic size ratio $\sigma_S/\sigma_L$ and number fraction $x_S$
of the metalloid species. We show that the regime in the space of
$\sigma_S/\sigma_L$ and $x_S$ where well-mixed, optimal glass formers occur for
patchy and LJ particle mixtures coincides with that for experimentally observed
metal-metalloid glass formers. Our simple computational model provides the
capability to perform combinatorial searches to identify novel glass-forming
alloys.
