Kevin Rossi

Metallic nanoparticles meet metadynamics

Metadynamics coupled with classical molecular dynamics has been successfully applied to sample the configuration space of metallic and bimetallic nanoclusters. We implement a new set of collective variables related to the pair distance distribution function of the nanoparticle to achieve an exhaustive isomer sampling. As paradigmatic examples, we apply our methodology to Ag147, Pt147, and their alloy Ag(shell)Pt(core) at 2:1 and 1:1 chemical compositions. The proposed scheme is able to reproduce the known solid-solid structural transformation pathways, based on the Lipscombs diamond-square-diamond mechanisms, both in mono and bimetallic nanoparticles. A discussion of the free energy barriers involved in these processes is provided.

Building machine learning force fields for nanoclusters

We assess Gaussian process (GP) regression as a technique to model interatomic forces in metal nanoclusters by analyzing the performance of 2-body, 3-body, and many-body kernel functions on a set of 19-atom Ni cluster structures. We find that 2-body GP kernels fail to provide faithful force estimates, despite succeeding in bulk Ni systems. However, both 3- and many-body kernels predict forces within an ∼0.1 eV/Å average error even for small training datasets and achieve high accuracy even on out-of-sample, high temperature structures. While training and testing on the same structure always provide satisfactory accuracy, cross-testing on dissimilar structures leads to higher prediction errors, posing an extrapolation problem. This can be cured using heterogeneous training on databases that contain more than one structure, which results in a good trade-off between versatility and overall accuracy. Starting from a 3-body kernel trained this way, we build an efficient non-parametric 3-body force field that allows accurate prediction of structural properties at finite temperatures, following a newly developed scheme [A. Glielmo et al., Phys. Rev. B 95, 214302 (2017)]. We use this to assess the thermal stability of Ni19 nanoclusters at a fractional cost of full ab initio calculations.

Mapping the conformational free energy of aspartic acid in the gas phase and in aqueous solution

The conformational free energy landscape of aspartic acid, a proteogenic amino acid involved in a wide variety of biological functions, was investigated as an example of the complexity that multiple rotatable bonds produce even in relatively simple molecules. To efficiently explore such a landscape, this molecule was studied in the neutral and zwitterionic forms, in the gas phase and in water solution, by means of molecular dynamics and the enhanced sampling method metadynamics with classical force-fields. Multi-dimensional free energy landscapes were reduced to bi-dimensional maps through the non-linear dimensionality reduction algorithm sketch-map to identify the energetically stable conformers and their interconnection paths. Quantum chemical calculations were then performed on the minimum free energy structures. Our procedure returned the low energy conformations observed experimentally in the gas phase with rotational spectroscopy [M. E. Sanz et al., Phys. Chem. Chem. Phys. 12, 3573 (2010)]. Moreover, it provided information on higher energy conformers not accessible to experiments and on the conformers in water. The comparison between different force-fields and quantum chemical data highlighted the importance of the underlying potential energy surface to accurately capture energy rankings. The combination of force-field based metadynamics, sketch-map analysis, and quantum chemical calculations was able to produce an exhaustive conformational exploration in a range of significant free energies that complements the experimental data. Similar protocols can be applied to larger peptides with complex conformational landscapes and would greatly benefit from the next generation of accurate force-fields.

Thermodynamics of CuPt nanoalloys

The control of structural and chemical transitions in bimetallic nanoalloys at finite temperatures is one of the challenges for their use in advanced applications. Comparing Nested Sampling and Molecular Dynamics simulations, we investigate the phase changes of CuPt nanoalloys with the aim to elucidate the role of kinetic effects during their solidification and melting processes. We find that the quasi-thermodynamic limit for the nucleation of (CuPt)309 is 965 ± 10 K, but its prediction is increasingly underestimated when the system is cooled faster than 109 K/s. The solidified nanoparticles, classified following a novel tool based on Steinhardt parameters and the relative orientation of characteristic atomic environments, are then heated back to their liquid phase. We demonstrate the kinetic origin of the hysteresis in the caloric curve as (i) it closes for rates slower than 108 K/s, with a phase change temperature of 970 K ± 25 K, in very good agreement with its quasi-thermodynamic limit; (ii) the process happens simultaneously in the inner and outer layers; (iii) an onion-shell chemical order - Cu-rich surface, Pt-rich sub-surface, and mixed core - is always preserved.

Author Correction: Thermodynamics of CuPt nanoalloys

A correction to this article has been published and is linked from the HTML and PDF versions of this paper. The error has been fixed in the paper.