RAFFLE – predicting interface structure

We have recently been working on a method for predicting the atomic structure of interfaces. This approach uses random structure search methods informed by genetic algorithms to reduce the intense computational cost typically associated with such methods. This method is called RAFFLE (pseudoRandom Approach For Finding Local Energetic minima)

Article: https://doi.org/10.1103/PhysRevLett.132.066201

Within the article, we showcase the capabilities of the RAFFLE method by applying it to predicting the phase of thin layers of magnesium oxide (MgO) when encapsulated between two layers of graphene. The results show that the rocksalt phase of MgO is heavily stabilised by encapsulation as compared to its other potential phases.

The RAFFLE methodology generates interface structures by taking a host structure and inserting new atoms based on three placement methods (where the specific method used for each atom is randomly selected, with weighting to specific methods pre-defined); these methods are 1) global minima identifier, 2) pseudorandom walk, and 3) void identifier. The particulars of methods 1 and 2 depend on utilising distribution functions that relate particular features in n-body distributions of existing known structures (with the same chemical composition) to energetic favourability (i.e. the distribution functions of each known structure are combined with weightings applied to each based on the structure’s formation energy).

Global minima identifier
This method involves discretising the unit cell into a grid and evaluating the energetic favourability of each point based on the existing distribution functions. The point with the lowest energy (i.e. most favourable) is selected for the next atom placement. This captures global energetic information of the system.

Pseudorandom walk
This method involves selecting a random point in the cell and then evaluating points within a certain radius of the point for more energetically favourable sites. If one is found, the same evaluation is then performed on that point. This process is repeated until no points within a defined radius are found to be more favourable. That final point is selected for the next atom placement. This captures atoms getting caught in local energetic minima within the system.

Void identifier
This method involves identifying the point in the unit cell with the lowest atomic density. This point is then selected for the next atom placement. This method captures grain seed sites and increasing entropy of a system, i.e. homogeneity.

The Hepplestone Research Group is currently working on a follow-up paper and the associated RAFFLE code. The authors hope to have the code open-source and publicly available within the coming months.