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Many functional properties of particle system rely on collective behaviour and the type of superstructures formedwhen thousands of particles come together. Self-assembly, agglomeration and aggregation depend sensitively on the size and shape of particles present, as well as the size distribution and themixtures of shapeswithin a given sample, whichmakes simulation of these superstructures and their properties challenging.Here we present a new, flexible, software package for the simulations of ordered and disorder aggregates of faceted polyhedral particle from the nanoscale to themicronscale, which is capable of including size distributions andmixtures ofmultiple particle shapes defined by theUser, subject to additional User-defined interactions. Following relaxation usingmolecular dynamics a number of characterisation tools are provided, including interfacial probabilities and distribution functions. The software is applicable to a range of problems fromnanoparticle assembly to additivemanufacturing. Aggregates of nanoparticles can provide a range of unique properties that are different from isolated, individual entities. Depending on the particle size(s) and shape(s), the overall porosity, strength and complexity of the aggregates the reactivity, transport and efficiency of entire samples can be controlled [1–7]. Examples include the tribological properties of powders [8], the toxicological properties of colloids [9], themechanical properties of composites [10], the collective electromagnetic properties exhibited in surface plasmon resonances and nanoporousmaterials formed via aggregation or self-assembly [11]. Characterising the superstructure of aggregates ismuchmore difficult than ordered self-assemblies of nanoparticles, due to the variations in particles sizes, shapes, interaction points, types of interactions and the inherent randomness. Probingwith experimentalmethods can be challenging due to interference from the probe and the collection of either averaged results that represent entire samples, or local results (limited by the probe size) thatmay not be representative at all. Both local interactions and long-ranged statistics can be obtained from computationalmethods, but these have their challenges too. Simulationswithout periodic boundary conditions (PBCs) lack the ability to control the number density, while simulationswith PBCs impose an unnatural translational symmetry and necessitates larger systems or repetition to develop the right statistics. The use of classical atomistic simulationsmethods limits the number of nanoparticles that can be practically handled, while the use of electronic structuremethods limits the size and number of nanoparticles that can be handled, leading to an artificial bias towardminority features such as edges and corners. The aggregation ofmost realistic systems are driven by formation of either facet–facet interfaces (depending on the size and type of the facets) and the formation of voids. This cannot be achieved if we are limited to a small number of nanoparticles, regardless of how accurately the interfaces or free surfaces can be described. Recognising that the aggregation is a surface-driven process provides uswith opportunities to address this computational intractability. The bulk atoms beneath the surface of nanoparticles serve only to support the position, energetic stability and reactive properties of the surface shell. If we preserve these surface properties the OPEN ACCESS

Simulated nanoparticle assembly using protoparticles (SNAP)