Qunchao Tong

National University of Defense Technology | NUDT · Department of Physics

Ab initio structure prediction methods have been nowadays widely used as powerful tools for structure searches and material discovery. However, they are generally restricted to small systems owing to the heavy computational cost of underlying density functional theory (DFT) calculations. In this work, by combining state-of-art machine learning (ML)...

Theoretical structure prediction method via quantum mechanical atomistic simulations such as density functional theory (DFT), solely based on chemical composition, already becomes a routine tool to determine the structures of physical and chemical systems, e.g. solids and clusters. However, the application of DFT to more realistic simulations, to a...

Boron is an intriguing element due to its electron deficiency and the ability to form multicenter bonds in allotropes and borides, exhibiting diversified structures, unique chemical bonds, and interesting properties. Using swarm-intelligence structural prediction driven by a machine learning potential, we identified a boron phase with a 24-atom cub...

Simulating reconstructive phase transition requires an accurate description of potential energy surface (PES). Density-functional-theory (DFT) based molecular dynamics can achieve the desired accuracy but it is computationally unfeasible for large systems and/or long simulation times. Here we introduce an approach that combines the metadynamics sim...

X-ray diffraction (XRD) is an important technique for structure determination. However, in traditional methods, estimated structural information (e.g., unit cell parameters and space group) is required to determine the precise structure from XRD data. We propose a versatile global search method for determining crystal structures from experimental p...

The immiscibility of hydrogen-helium mixture under the temperature and pressure conditions of planetary interiors is crucial for understanding the structures of gas giant planets (e.g., Jupiter and Saturn). While the experimental probe at such extreme conditions is challenging, theoretical simulation is heavily relied in an effort to unravel the mi...

Controllable phase modulation and electronic structure are essential factors in the study of two-dimensional transition metal dichalcogenides due to their impact on intriguing physical properties and versatile optoelectronic applications. Here, we report the phase-controlled growth of ternary monolayer MoSe2xTe2(1−x) (0 ≤ x ≤ 1) alloys induced thro...

Metallic uranium-based alloys, with d-transition metals such as Nb, Mo, and Zr, are promising candidates for actinide fuel. For this purpose, their behaviors under changing physical stimuli need to be understood. Here, we systematically investigate U–Nb intermetallic compounds and predict new compound formations under different pressures using the...

Metallic uranium-based alloys, with d-transition metals like Nb, Mo, and Zr, are promising candidates for actinide fuel. For this purpose, their behaviors under changing physical stimuli need to be understood. Here we systematically investigate U-Nb intermetallic compounds and predict new compound formations under different pressures using first-pr...

Structure prediction methods have been widely used as a state-of-the-art tool for structure searches and materials discovery, leading to many theory-driven breakthroughs on discoveries of new materials. These methods generally involve the exploration of the potential energy surfaces of materials through various structure sampling techniques and opt...