Lattice induced crystallization of nanodroplets: the role of finite-size effects and substrate properties in controlling polymorphism

Abstract

Targeting specific technological applications requires the control of nanoparticle properties, especially the crystalline polymorph. Freezing a nanodroplet deposited on a solid substrate leads to the formation of crystalline structures. We study the inherent mechanisms underlying this general phenomenon by means of molecular dynamics simulations. Our work shows that different crystal structures can be selected by finely tuning the solid substrate lattice parameter. Indeed, while for our system, face-centered cubic is usually the most preponderant structure, the growth of two distinct polymorphs, hexagonal centered packing and body-centered cubic, was also observed even when the solid substrate was face-centered cubic. Finally, we also demonstrated that the growth of hexagonal centered packing is conditioned by the appearance of large enough body-centered cubic clusters thus suggesting the presence of a cross-nucleation pathway. Our results provide insights into the impact of nanoscale effects and solid substrate properties towards the growth of polymorphic nanomaterials.

Explicitly stable fundamental-measure-theory models for classical density functional theory

“…In summary, the class of "explicitly" stable functionals consistent with dimensional crossover and involving only measures up to the second-order tensor are F ex [ρ] = F (1) ex [ρ] + F (2) ex [ρ] + F (3) ex [ρ] with the third contribution having the form…”

“…Classical density functional theory (cDFT) has become an important tool for studying nanoscale phenomena such as the solvation energy of large ions [1], crystallization [2], confinement-induced polymorphism [3], and wetting [4], to name a few. Key to this utility is the ability of cDFT to accurately describe molecular-scale correlations ultimately arising from excluded volume effects.…”

“…The issue is not just philosophical: the local minima can be explored in, e.g., perfect crystals due to the high symmetry, but in more general applications such as those in Refs. [2,3] cited above, a complete lack of symmetry leaves the calculations vulnerable to such unphysical global minima resulting in numerical calculations that blow up. Another conceptual drawback is that to achieve a good quantitative description of dense liquids, the functionals that come out of the dimensional-crossover path are heuristically modified in a way that invalidates the recovery of the low-dimensional results that were their motivation in the first place.…”

How crystals form: A theory of nucleation pathways

“…Liquid-liquid phase separation is now recognized as “underlying the formation of several membraneless compartments in living cells, including, for example, stress granules, the nucleolus, and P bodies in the cytoplasm” ( 2 ). Crystallization plays a role in several pathologies such as malaria ( 3 ) and amyloid aggregation leading to Alzheimer’s disease ( 4 , 5 ), while the control of polymorphism in industrial processes, such as the production of pharmaceuticals ( 6 ), and at the nanoscale, where surface effects enhance polymorphism ( 7 , 8 ), is a subject of intense practical interest.…”

Non-classical nucleation of zinc oxide from a physically-motivated machine-learning approach

“…Better understanding crystallization would allow for a rational control of material engineering and possibly the development of novel functional materials and technological applications. From the fundamental point of view, numerous works have been dedicated to elucidating the emergence of the nucleation core [1][2][3][4][5] and its role in controlling the final crystal structure [6][7][8][9][10][11][12]. For instance, it is now possible to observe the crystal birth with electron microscopy [6,7,[13][14][15], and colloidal science has also provided numerous experimental results on nucleation [16][17][18][19].…”