Issue 5, 2022

Selective desolvation in two-step nucleation mechanism steers crystal structure formation

Abstract

The two-step nucleation (TSN) theory and crystal structure prediction (CSP) techniques are two disjointed yet popular methods to predict nucleation rate and crystal structure, respectively. The TSN theory is a well-established mechanism to describe the nucleation of a wide range of crystalline materials in different solvents. However, it has never been expanded to predict the crystal structure or polymorphism. On the contrary, the existing CSP techniques only empirically account for the solvent effects. As a result, the TSN theory and CSP techniques continue to evolve as separate methods to predict two essential attributes of nucleation – rate and structure. Here we bridge this gap and show for the first time how a crystal structure is formed within the framework of TSN theory. A sequential desolvation mechanism is proposed in TSN, where the first step involves partial desolvation to form dense clusters followed by selective desolvation of functional groups directing the formation of crystal structure. We investigate the effect of the specific interaction on the degree of solvation around different functional groups of glutamic acid molecules using molecular simulations. The simulated energy landscape and activation barriers at increasing supersaturations suggest sequential and selective desolvation. We validate computationally and experimentally that the crystal structure formation and polymorph selection are due to a previously unrecognized consequence of supersaturation-driven asymmetric desolvation of molecules.

Graphical abstract: Selective desolvation in two-step nucleation mechanism steers crystal structure formation

Supplementary files

Article information

Article type
Paper
Submitted
27 Sep 2021
Accepted
17 Dec 2021
First published
12 Jan 2022

Nanoscale, 2022,14, 1723-1732

Author version available

Selective desolvation in two-step nucleation mechanism steers crystal structure formation

A. V. Dighe, P. Coliaie, P. K. R. Podupu and M. R. Singh, Nanoscale, 2022, 14, 1723 DOI: 10.1039/D1NR06346D

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