Evolutionary search for novel superhard materials: Methodology and applications to forms of carbon and TiO2
arXiv:1105.1729 · doi:10.1103/PhysRevB.84.092103
Abstract
We have developed a method for prediction of the hardest crystal structures in a given chemical system. It is based on the evolutionary algorithm USPEX (Universal Structure Prediction: Evolutionary Xtallography) and electronegativity-based hardness model that we have augmented with bond-valence model and graph theory. These extensions enable correct description of the hardness of layered, molecular, and low-symmetry crystal structures. Applying this method to C and TiO2, we have (i) obtained a number of low-energy carbon structures with hardness slightly lower than diamond and (ii) proved that TiO2 in any of its possible polymorphs cannot be the hardest oxide, its hardness being below 17 GPa.
Submitted in November 2010; revised in March 2011; resubmitted 24 June 2011; published 12 September 2011. 8 pages, 2 tables, 3 figures
References in corpus (2)
Cited by in corpus (33)
- Simple and accurate model of fracture toughness of solids
- Low-energy silicon allotropes with strong absorption in the visible for photovoltaic applications
- Constrained crystals deep convolutional generative adversarial network for the inverse design of crystal structures
- Evolutionary Method for Predicting Surface Reconstructions with Variable Stoichiometry
- Low-energy tetrahedral polymorphs of carbon, silicon, and germanium
- The Phase Diagram and Hardness of Carbon Nitrides
- Superhard sp3 carbon allotropes with odd and even ring topologies
- Systematic search for low-enthalpy sp3 carbon using evolutionary metadynamics
- Understanding the nature of "superhard graphite"
- High Energy Density Mixed Polymeric Phase From Carbon Monoxide and Nitrogen
- Machine Learning and Evolutionary Prediction of Superhard B-C-N Compounds
- Computational Search for Novel Hard Chromium-Based Materials
- Evolutionary Metadynamics: a Novel Method to Predict Crystal Structures
- ADAIS: Automatic Derivation of Anisotropic Ideal Strength via high-throughput first-principles computations
- Predicting Polymeric Crystal Structures by Evolutionary Algorithms
- The high-pressure phase of boron, γ-B28: disputes and conclusions of 5 years after discovery
- Coevolutionary search for optimal materials in the space of all possible compounds
- Structural Diversity in Lithium Carbides
- Nonempirical definition of the Mendeleev numbers: Organizing the chemical space
- Crystal chemistry and ab initio prediction of ultra-hard rhombohedral B2N2 and BC2N
- Accelerating inverse crystal structure prediction by machine learning: a case study of carbon allotropes
- Polycrystalline γ-boron: As hard as polycrystalline cubic boron nitride
- Predicting kinetics of polymorphic transformations from structure mapping and coordination analysis
- Silicon clathrates for photovoltaics predicted by a two-step crystal structure search
- XtalOpt Version 13: Multi-Objective Evolutionary Search for Novel Functional Materials
- Novel phase of beryllium fluoride at high pressure
- Tricarbon: two novel ultra-hard metallic carbon allotropes from first-principle calculations
- Structurally Constrained Evolutionary Algorithm for the Discovery and Design of Metastable Phases
- Generative Adversarial Networks for Crystal Structure Prediction
- Fused borophenes: a new family of superhard materials
- Low compressible BPN
- Synthesis of ultra-incompressible sp3-hybridized carbon nitride
- Prediction of a new ground state of superhard compound B6O at ambient conditions