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A two dimensional (2D) Group-VI Te monolayer, tellurene, is predicted by using the first-principles calculations, which consists of planner four-membered and chair-like six-membered rings arranged alternately in a 2D lattice. The phonon…
Nanoscale polar structures are significant for understanding polarization processes in low-dimensional systems and hold potential for developing high-performance electronics. Here, we demonstrate a polar vortex superstructure arising from…
A real-space method using generating integers is used to classify the possible moire patterns for two equal hexagonal lattices. The result is that the rotations that take (n,m) to (m,n) with n,m relatively prime form the fundamental moire…
We construct families of one-dimensional (1D) stable solitons in two-component $\mathcal{PT}$-symmetric systems with spin-orbit coupling (SOC) and quintic nonlinearity, which plays the critical role in 1D setups. The system models light…
In heterostructures consisting of atomically thin crystals layered on top of one another, lattice mismatch or rotation between the layers results in long-wavelength moir\'e superlattices. These moir\'e patterns can drive significant band…
We present a universal method for the large-scale prediction of the atomic structure of clusters. Our algorithm performs the joint evolutionary search for all clusters in a given area of the compositional space and takes advantage of…
RNA design aims to find a sequence that folds with highest probability into a designated target structure. However, certain structures are undesignable, meaning no sequence can fold into the target structure under the default (Turner) RNA…
A novel crystalline structure of hybrid monolayer hexagonal boron nitride (BN) and graphene is predicted by means of the first-principles calculations. This material can be derived via boron or nitrogen atoms substituted by carbon atoms…
RNA pseudoknots are a kind of minimal RNA tertiary structural motifs, and their three-dimensional (3D) structures and stability play essential roles in a variety of biological functions. Therefore, to predict 3D structures and stability of…
We report the first principle theory-based study of stability, electronic structure and optical properties of cluster assembled materials in various 1D, 2D and 3D nanostructures using a cage-like Cd9Te9 cluster as the super-atom. The bulk…
Principles of design to create dynamically stable transition metal, lanthanide, and actinide based low-dimensional borides are presented. A charge transfer analysis of donor metal atoms to electron deficient honeycombed B lattices allows to…
Pt deposited on a Ge(001) surface spontaneously forms nanowire arrays. These nanowires are thermodynamically stable and can be hundreds of atoms long. The nanowires only occur on a reconstructed Pt-Ge-surface where they fill the troughs…
The enchanting Dirac fermions in graphene stimulated us to seek for other two-dimensional (2D) Dirac materials, and boron monolayers may be a good candidate. So far, a number of monolayer boron sheets have been theoretically predicted, and…
Hexagonal boron nitride (h-BN) is a prominent member in the growing family of two-dimensional materials with potential applications ranging from being an atomically smooth support for other 2D materials to templating growth of molecular…
Each human genome is a 3 billion base pair set of encoding instructions. Decoding the genome using deep learning fundamentally differs from most tasks, as we do not know the full structure of the data and therefore cannot design…
We have developed a software MagGene to predict magnetic structures by using genetic algorithm. Starting from an atom structure, MagGene repeatedly generates new magnetic structures and calls first-principles calculation engine to get the…
The present study applies a novel two-dimensional learning framework (2D-UPSO) based on particle swarms for structure selection of polynomial nonlinear auto-regressive with exogenous inputs (NARX) models. This learning approach explicitly…
We present a method for reliably determining the lowest energy structure of an atomic cluster in an arbitrary model potential. The method is based on a genetic algorithm, which operates on a population of candidate structures to produce new…
We use parametrized linear combination of atomic orbitals calculations to determine the stability, optimum geometry and electronic properties of nanometer-sized capped graphitic cones, called ``nano-horns''. Different nano-horn morphologies…
The spatial positioning of chromosomes relative to functional nuclear bodies is intertwined with genome functions such as transcription. However, the sequence patterns and epigenomic features that collectively influence chromatin spatial…