Accuracy of ab initio methods in predicting the crystal structures of metals: review of 80 binary alloys

We present our findings of a large-scale screening for new synthesizable materials in five M-Sn binaries, M = Na, Ca, Cu, Pd, and Ag. The focus on these systems was motivated by the known richness of M-Sn properties with potential applications in energy storage, electronics packaging, and superconductivity. For the systematic exploration of the large configuration space, we relied on our recently developed MAISE-NET framework that constructs accurate neural network interatomi...

The structural electronic and optical properties of intermetallic compound MgRh were investigated by using the ab-initio technique from CASTEP code. In this study we have carried out the pseudo-potential plane-wave (PP-PW) method based on the density functional theory (DFT), within the generalized gradient approximation (GGA). Our calculated structural parameters and corresponding graphical values fit with other previous available experimental data and other theoretical obser...

Reducing the number of candidate structures is crucial to improve the efficiency of global optimization. Herein, we demonstrate that the generalized Hamiltonian can be described by the atom classification model (ACM) based on symmetry, generating competent candidates for the first-principles calculations to determine ground states of alloy directly. The candidates can be obtained in advance through solving the convex hull step by step, because the correlation functions of ACM...

Machine-learned potentials (MLPs) trained against quantum-mechanical reference data have demonstrated remarkable accuracy, surpassing empirical potentials. However, the absence of readily available general-purpose MLPs encompassing a broad spectrum of elements and their alloys hampers the applications of MLPs in materials science. In this study, we present a feasible approach for constructing a unified general-purpose MLP for numerous elements and showcase its capability by d...

Structure is the most basic and important property of crystalline solids; it determines directly or indirectly most materials characteristics. However, predicting crystal structure of solids remains a formidable and not fully solved problem. Standard theoretical tools for this task are computationally expensive and at times inaccurate. Here we present an alternative approach utilizing machine learning for crystal structure prediction. We developed a tool called Crystal Struct...

We present an algorithm for generating all derivative superstructures--for arbitrary parent structures and for any number of atom types. This algorithm enumerates superlattices and atomic configurations in a geometry-independent way. The key concept is to use the quotient group associated with each superlattice to determine all unique atomic configurations. The run time of the algorithm scales linearly with the number of unique structures found. We show several applications d...

We report a new family of ternary 111 hexagonal LnAuSb (Ln = La-Nd, Sm) compounds that, with a 19 valence electron count, has one extra electron compared to all other known LnAuZ compound. The "19th" electron is accommodated by Au-Au bonding between the layers; this Au-Au interaction drives the phases to crystallize in the YPtAs-type structure rather than the more common LiGaGe-type. This is critical, as the YPtAs structure type has the symmetry-allowed band crossing necessar...

The structural, electronic, mechanical and thermal properties of Ir$_{1-x}$Rh$_{x}$ alloys were studied systematically using ab initio density functional theory at different concentrations (x = 0.00, 0.25, 0.50, 0.75, 1.00). A Special Quasirandom Structure method was used to make alloys having FCC structure with four atoms per unit cell. The ground state properties such as lattice constant and bulk modulus were calculated to find the equilibrium atomic position for stable all...

The high strength of structural aluminium alloys depends strongly on the controlled precipitation of specific intermetallic phases, whose identity and crystal structure can be difficult to predict. Here, we investigate the Al-Pt system, which shows some similarity to the Al-Cu system as one of their main intermetallic phases, $Al_2Pt$, is nearly isostructural with $\theta^{\prime} (Al_2Cu)$, the metastable phase responsible for the high-strength of Al-Cu alloys. However, phas...

Fast and accurate crystal structure prediction (CSP) algorithms and web servers are highly desirable for exploring and discovering new materials out of the infinite design space. However, currently, the computationally expensive first principle calculation based crystal structure prediction algorithms are applicable to relatively small systems and are out of reach of most materials researchers due to the requirement of high computing resources or the software cost related to ...