  Self-assembly of complex and functional materials remains a grand challenge
in soft material science. Efficient assembly depends on a delicate balance
between thermodynamic and kinetic effects, requiring fine-tuning affinities and
concentrations of subunits. By contrast, we introduce an assembly paradigm that
allows large error-tolerance in the subunit affinity and helps avoid kinetic
traps. Our combined experimental and computational approach uses a model system
of triangular subunits programmed to assemble into T=3 icosahedral capsids
comprising 60 units. The experimental platform uses DNA origami to create
monodisperse colloids whose 3D geometry is controlled to nanometer precision,
with two distinct bonds whose affinities are controlled to kBT precision,
quantified in situ by static light scattering. The computational model uses a
coarse-grained representation of subunits, short-ranged potentials, and
Langevin dynamics. Experimental observations and modeling reveal that when the
bond affinities are unequal, two distinct hierarchical assembly pathways occur,
in which the subunits first form dimers in one case, and pentamers in another.
These hierarchical pathways produce complete capsids faster and are more robust
against affinity variation than egalitarian pathways, in which all binding
sites have equal strengths. This finding suggests that hierarchical assembly
may be a general engineering principle for optimizing self-assembly of complex
target structures.
