Fig. 5.

JIS scenario. (A) In the JIS scenario, the different species are added sequentially; here, for illustration, they are in a linear sequence ($T_1<T_2<T_3<\dots$). Along the regular assembly paths, $A_{1\text{D}}$ (1D) or $A_{2\text{D}}$ (2D), additional dimers B can form, competing for resources with the regular structures and thereby disrupting their growth. While for one-dimensional structures a disruption event prevents a structure $A_{1\text{D}}$ from further growth, in higher dimensions both defective structures $A_{2\text{D}}$ and B continue to grow, thereby increasing competition for resources. (B) Competition for resources can be alleviated by enhancing the amount of resources with each assembly step (nonstoichiometric concentrations; SI Appendix, section 1). For example, providing the first species in concentration $0.9N$ and increasing linearly up to $1.1N$ for the last species strongly enhances assembly efficiency (D) and robustness (E). (C) Parallel supply protocol illustrated for a 2D structure of size S = 25 causing the structures to grow radially in an “onion-skin”–like fashion. Roman numbers indicate the order in which species are supplied. Species with identical numbers (“onion skins”) are supplied simultaneously in “batches.” (D) When using nonstoichiometric concentrations, high yield can be achieved with a shorter time span $\mathrm{\Delta }T$ between subsequent batches, exhibiting a smaller control parameter exponent (Inset) compared to the case of stoichiometric concentrations. Simulations were performed for 3D structures with $N={10}^4$ to 10⁵. (E) External noise in the concentrations jeopardizes the yield when stoichiometric concentrations are used, whereas nonstoichiometric concentrations are much more robust. Here, for each species we assumed a coefficient of variation $\text{CV}=0.1\%$ with average particle numbers as in D.