Litcius/Paper detail

Structure of disordered <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"><mml:msub><mml:mi>TiO</mml:mi><mml:mn>2</mml:mn></mml:msub></mml:math> phases from <i>ab initio</i> based deep neural network simulations

Marcos F. Calegari Andrade, Annabella Selloni

2020Physical Review Materials23 citationsDOIOpen Access PDF

Abstract

Amorphous ${\mathrm{TiO}}_{2}$ (a-${\mathrm{TiO}}_{2}$) is widely used in many fields, ranging from photoelectrochemistry to bioengineering, hence detailed knowledge of its atomic structure is of scientific and technological interest. Here we use an ab initio-based deep neural network potential (DP) to simulate large scale atomic models of crystalline and disordered ${\mathrm{TiO}}_{2}$ with molecular dynamics. Our DP reproduces the structural properties of all 11 ${\mathrm{TiO}}_{2}$ crystalline phases, predicts the densities and structure factors of molten and amorphous ${\mathrm{TiO}}_{2}$ with only a few percent deviation from experiments, and describes the pressure dependence of the amorphous structure in agreement with recent observations. It can be extended to model additional structures and compositions, and can be thus of great value in the study of ${\mathrm{TiO}}_{2}$-based nanomaterials.

Topics & Concepts

Amorphous solidMaterials scienceAb initioMachine learningCrystallographyPhysicsComputer scienceChemistryQuantum mechanicsMachine Learning in Materials ScienceElectronic and Structural Properties of OxidesX-ray Diffraction in Crystallography