High-Throughput Computation of New Carbon Allotropes with Diverse Hybridization and Ultrahigh Hardness

Abstract

The discovery of new carbon allotropes with different building blocks and crystal symmetries has long been of great interest to broad materials science fields. Herein, we report several hundred new carbon allotropes predicted by the state-of-the-art RG2 code and first-principles calculations. The types of new carbon allotropes that were identified in this work span pure sp2, hybrid sp2/sp3, and pure sp3 C–C bonding. All structures were globally optimized at the first-principles level. The thermodynamic stability of some selected carbon allotropes was further validated by computing their phonon dispersions. The predicted carbon allotropes possess a broad range of Vickers’ hardness. This wide range of Vickers’ hardness is explained in detail in terms of both atomic descriptors such as density, volume per atom, packing fraction, and local potential energy throughout the unit cell, and global descriptors such as elastic modulus, shear modulus, and bulk modulus, universal anisotropy, Pugh’s ratio, and Poisson’s ratio. For the first time, we found strong correlation between Vickers’ hardness and average local potentials in the unit cell. This work provides deep insight into the identification of novel carbon materials with high Vickers’ hardness for modern applications in which ultrahigh hardness is desired. Moreover, the local potential averaged over the entire unit cell of an atomic structure, an easy-to-evaluate atomic descriptor, could serve as a new atomic descriptor for efficient screening of the mechanical properties of unexplored structures in future high-throughput computing and artificial-intelligence-accelerated materials discovery methods.

Tuning band gap and enhancing optical functions of AGeF3 (A = K, Rb) under pressure for improved optoelectronic applications

“…The Voigt and Reuss coefficients describe the upper and lower bounds of the effective modulus, respectively. For cubic lattices, the Voigt bulk modulus ( B V ) and Voigt shear modulus ( G V ) as well as the Reuss bulk modulus ( B R ) and Reuss shear modulus ( G R ) are described by the well-known expressions 57 , 58 . According to Hill’s theory 59 , the B and G are the arithmetic mean of Voigt and Reuss expressions.…”

High-throughput computational discovery of 3218 ultralow thermal conductivity and dynamically stable materials by dual machine learning models

“…In order to gain deep insight into the structure-property relationship, Fig. 7 shows the t-distributed stochastic neighbor embedding (t-SNE) 74 plot for exploring and visualizing high dimensional data in a 2D plot. The t-SNE plot provides a deep understanding of the correlation between LTC and atomic and structural properties.…”

Density Function Theory Predicted Carbon Allotropes: Recent Developments

“…[8,9] Machine learning can explore the relationship between geometric parameters and the band gap of carbon allotropes. [10] The predicted resulting carbon allotropes can possess a wide range of hybridizations, including pure sp 2 , hybrid sp 2 /sp 3 , and pure sp 3 [11] and be in the range 0-3D, as, for example, hopfene -3D carbon allotrope. [12] Before 2019, more than 500 carbon allotropes (might be more) have been predicted by the DFT method; some representative of them were described in our recent book.…”