Surface-directed and bulk spinodal decomposition compete to decide the morphology of bimetallic nanoparticles

TL;DR

This paper develops a thermodynamic and phase-field simulation framework to predict and control the morphology of bimetallic nanoparticles by analyzing the competition between surface and bulk spinodal decomposition processes influenced by temperature and capillarity.

Contribution

It introduces a combined thermodynamic and phase-field approach to predict nanoparticle morphologies based on temperature-dependent surface energies and bulk driving forces.

Findings

Morphologies cluster into distinct regions in the $\Delta ilde{f}$-$ heta$ space.

Temperature influences the balance of surface and bulk effects, leading to different nanoparticle structures.

The framework enables prediction of morphological transitions in BNPs as a function of processing temperature.

Abstract

An embedded-domain phase-field formalism is used for studying phase transformation pathways in bimetallic nanoparticles (BNPs). Competition of bulk and surface-directed spinodal decomposition processes and their interplay with capillarity are identified as the main determinants of BNP morphology. The former is characterized by an effective bulk driving force $\Delta\tilde{f}$ which increases with decreasing temperature, while the latter manifests itself through a balance of interfacial energies captured by the contact angle $\theta$. The simulated morphologies, namely, core-shell, Janus and inverse core-shell, cluster into distinct regions of the $\Delta\tilde{f}$-$\theta$ space. Variation of $\theta$ with $\Delta\tilde{f}$ in the Ag-Cu alloy system is computed as a function of temperature using a CALPHAD approach in which surface energies are estimated from a modified Butler equation. This $\theta-\Delta\tilde{f}$ trajectory for Ag-Cu, when superimposed on the morphology map, enables the prediction of different morphological transitions as a function of temperature. Therefore, the study establishes a unique thermodynamic framework coupled with phase-field simulations for predicting and tailoring nanoparticle morphology through a variation of processing temperature.