Related papers: Metric-driven search for structurally stable inorg…
Detailed understanding of the structural and photophysical properties of polymeric carbon nitride (PCN) materials is of critical importance to derive future material optimization strategies towards more desirable optical properties and more…
Exploratory synthesis in novel chemical spaces is the essence of solid-state chemistry. However, uncharted chemical spaces can be difficult to navigate, especially when materials synthesis is challenging. Nitrides represent one such space,…
Crystal structure prediction with theoretical methods is particularly challenging when unit cells with many atoms need to be considered. Here we employ a symmetry-driven structure search (SYDSS) method and combine it with density functional…
The vastness of the space of possible multicomponent metal alloys is hoped to provide improved structural materials but also challenges traditional, low-throughput materials design efforts. Computational screening could narrow this search…
The ability to reliably predict the structures and stabilities of a molecular crystal and its polymorphs without any prior experimental information would be an invaluable tool for a number of fields, with specific and immediate applications…
We present a detailed quantum mechanical non empirical DFT investigation of the energy-optimized geometries, phase stabilities and electronic properties of bulk Pt3N, PtN and PtN2 in a set of twenty different crystal structures. Structural…
A periodic structure sandwiched between two homogeneous media can support bound states in the continuum (BICs) that are valuable for many applications. It is known that generic BICs in periodic structures with an up-down mirror symmetry and…
For Y$_2$C$_3$ with a superconducting critical temperature (T$_c$) $\sim$18 K, zone-center imaginary optical phonon modes have been found for the high-symmetry $I$-$43d$ structure due to C dimer wobbling motion and electronic instability…
We report a detailed theoretical study of the structural, vibrational, and optical properties of solid nitromethane using first principles density functional calculations. The ground state properties were calculated using a plane wave…
Metastable materials are abundant in nature and technology, showcasing remarkable properties that inspire innovative materials design. However, traditional crystal structure prediction methods, which rely solely on energetic factors to…
Using density functional theory calculations, many researchers have predicted that various tungsten-nitride compounds WN$_x$ ($x$ > 1) will be "ultra-compressible" or "superhard", $i.e.$ as hard as or harder than diamond. These compounds…
We present a combined experimental and computational methodology for the discovery of new materials. Density functional theory (DFT) formation energy calculations allow us to predict the stability of various hypothetical structures. We…
Accelerated materials discovery is an urgent demand to drive advancements in fields such as energy conversion, storage, and catalysis. Property-directed generative design has emerged as a transformative approach for rapidly discovering new…
Nitriding introduces nitrides into the surface of steels, significantly enhancing the surface me-chanical properties. By combining the variable composition evolutionary algorithm and first-principles calculations based on density functional…
The discovery of new multicomponent inorganic compounds can provide direct solutions to many scientific and engineering challenges, yet the vast size of the uncharted material space dwarfs current synthesis throughput. While the…
Machine learning has emerged as a novel tool for the efficient prediction of materials properties, and claims have been made that machine-learned models for the formation energy of compounds can approach the accuracy of Density Functional…
By combining neutron inelastic scattering (NIS) and first-principles calculations, we have investigated the lattice dynamics of MOF5. The structural stability of MOF5 was evaluated by calculating the three cubic elastic constants. We find…
Generative design marks a significant data-driven advancement in the exploration of novel inorganic materials, which entails learning the symmetry equivalent to the crystal structure prediction (CSP) task and subsequent learning of their…
Carbon nanomembranes (CNMs) are nanometer-thin disordered carbon materials that are suitable for a range of applications, from energy generation and storage, through to water filtration. The structure-property relationships of these…
Structures and properties of many inorganic compounds have been collected historically. However, it only covers a very small portion of possible inorganic crystals, which implies the presence of numerous currently unknown compounds. A…