Reversible Tuning of Ca Nanoparticles Embedded in a Superionic CaF2 Matrix

Controlling the size and shape of metallic colloids is crucial for a number of nanotechnological applications ranging from medical diagnosis to electronics. Yet, achieving tunability of morphological changes at the nanoscale is technically difficult and the structural modifications made on nanoparticles generally are irreversible. Here, we present a simple nonchemical method for controlling the size of metallic colloids in a reversible manner. Our strategy consists of applying hydrostatic pressure on a Ca cationic sublattice embedded in the irradiated matrix of CaF2 containing a large concentration of defects. Application of our method to CaF2 along with in situ optical absorption of the Ca plasmon shows that the radii of the Ca nanoparticles can be reduced with an almost constant rate of −1.2 nm/GPa up to a threshold pressure of ∼9.4 GPa. We demonstrate recovery of the original nanoparticles upon decompression of the irradiated matrix. The mechanisms for reversible nanocolloid-size variation are analyzed with first-principles simulations. We show that a pressure-driven increase in the binding energy between fluorine centers is responsible for the observed nanoparticle shrinkage. We argue that the same method can be used to generate other metallic colloids (Li, K, Sr, and Cs) with tailored dimensions by simply selecting an appropriate matrix.
J.R.-F. and V.M. acknowledge the Spanish Ministry of Science, Innovation and Universities for the Juan de la Cierva program IJCI-2014-20513 and FJCI-2016-27921, respectively. C.C. acknowledges support from the Australian Research Council under the Future Fellowship funding scheme (No. FT140100135). Computational resources and technical assistance were provided by the Australian Government and the Government of Western Australia through the National Computational Infrastructure (NCI) and Magnus under the National Computational Merit Allocation Scheme and The Pawsey Supercomputing Centre. This project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement no. 829161.