Researchers at the Japan Advanced Institute of Science and Technology (JAIST) have successfully predicted the most stable boron nitrate structure with the utilisation of a cutting-edge quantum simulation method.
Boron nitrate is an incredibly flexible material with applications in a wide range of scientific and engineering fields. The core reason for this is because of a fascinating property of boron nitrate known as polymorphism, which is exemplified by its ability to crystallise into multiple types of structures.
This phenomenon usually occurs in response to changes in pressure or temperature. As well as this, the different structures, known as polymorphs, massively vary in their physical properties despite having an identical chemical formula. Due to this, polymorphs have a significant role to play in material design and an understanding of how to select the formation of the desired polymorph is imperative.
Overcoming challenges of boron nitrate polymorphs
However, boron nitrate polymorphs cause a particular challenge. Despite scientists undertaking multiple experiments to measure the relative stabilities of boron nitrate polymorphs, an agreement in the scientific community has not come to light.
While computational techniques are frequently the approach taken to overcome these challenges, boron nitrate polymorphs have presented significant barriers to standard computation methods because of the weak van der Waals (vdW) interactions between their layers, which is not taken into consideration in these computations.
Furthermore, the four stable boron nitrate polymorphs – rhombohedral (rBN), hexagonal (hBN), wurtzite (wBN), and zinc-blende (cBN) – exhibit a narrow energy range, meaning that the capture of small energy differences together with vdW interactions is even more daunting.
Now, an international group of researchers led by Assistant Professor Kousuke Nakano from JAIST has offered evidence that will shed light on this debate.
Their findings have been published in the journal Physical Chemistry C.
Applying fixed-node diffusion Monte Carlo simulations
As part of their research, they responded to this challenge with an advanced first principles calculations framework, namely fixed-node diffusion Monte Carlo (FNDMC) simulations. FNDMC signifies a step in the popular quantum Monte Carlo simulations technique, in which a parametrised many-body quantum ‘wavefunction’ is enhanced to accomplish the ground state and then supplied to the FNDMC.
On top of this, the group computed the Gibbs energy (the useful work attainable from a system at constant pressure and temperature) of boron nitrate polymorphs for various temperatures and pressures by utilising density functional theory (DFT) and phonon calculations.
Analysing the results
The FNDMC results indicated that the most stable structure was hBN, followed by rBN, cBN, and wBN. These findings were reliable at both 0 K and 300 K (room temperature). Nevertheless, the DFT assessments produced contradictory conclusions for two different approximations. Dr Nakano explains these inconsistent discoveries: “Our results reveal that the estimation of relative stabilities is greatly influenced by the exchange correlational functional, or the approximation used in the DFT calculation. As a result, a quantitative conclusion cannot be reached using DFT findings, and a more accurate approach, such as FNDMC, is required.”
Remarkably, the FNDMC results were in line with findings produced by other refined computation methods, such as ‘coupled cluster,’ indicating that FNDMC is an efficient method for dealing with polymorphs, particularly those regulated by vdW forces.
The research team also highlighted that this method could offer other vital information, including dependable reference energies, in the event that experimental data is unavailable.
Nakano is enthusiastic about the possibilities of the technique in the field of materials science. He concluded: “Our study demonstrates the ability ofFNDMCto detect tiny energy changes involving vdW forces, which will stimulate the use of this method for other van der Waals materials,” he says. “Moreover, molecular simulations based on this accurate and reliable method could empower material designs, enabling the development of medicines and catalysts.”
