skip to main content


This content will become publicly available on December 1, 2024

Title: Million-scale data integrated deep neural network for phonon properties of heuslers spanning the periodic table
Abstract Existing machine learning potentials for predicting phonon properties of crystals are typically limited on a material-to-material basis, primarily due to the exponential scaling of model complexity with the number of atomic species. We address this bottleneck with the developed Elemental Spatial Density Neural Network Force Field, namely Elemental-SDNNFF. The effectiveness and precision of our Elemental-SDNNFF approach are demonstrated on 11,866 full, half, and quaternary Heusler structures spanning 55 elements in the periodic table by prediction of complete phonon properties. Self-improvement schemes including active learning and data augmentation techniques provide an abundant 9.4 million atomic data for training. Deep insight into predicted ultralow lattice thermal conductivity (<1 Wm −1  K −1 ) of 774 Heusler structures is gained by p–d orbital hybridization analysis. Additionally, a class of two-band charge-2 Weyl points, referred to as “double Weyl points”, are found in 68% and 87% of 1662 half and 1550 quaternary Heuslers, respectively.  more » « less
Award ID(s):
2110033 2030128 1905775
NSF-PAR ID:
10427719
Author(s) / Creator(s):
; ; ; ; ; ; ; ; ; ;
Date Published:
Journal Name:
npj Computational Materials
Volume:
9
Issue:
1
ISSN:
2057-3960
Format(s):
Medium: X
Sponsoring Org:
National Science Foundation
More Like this
  1. Abstract Although first principles based anharmonic lattice dynamics is one of the most common methods to obtain phonon properties, such method is impractical for high-throughput search of target thermal materials. We develop an elemental spatial density neural network force field as a bottom-up approach to accurately predict atomic forces of ~80,000 cubic crystals spanning 63 elements. The primary advantage of our indirect machine learning model is the accessibility of phonon transport physics at the same level as first principles, allowing simultaneous prediction of comprehensive phonon properties from a single model. Training on 3182 first principles data and screening 77,091 unexplored structures, we identify 13,461 dynamically stable cubic structures with ultralow lattice thermal conductivity below 1 Wm −1 K −1 , among which 36 structures are validated by first principles calculations. We propose mean square displacement and bonding-antibonding as two low-cost descriptors to ease the demand of expensive first principles calculations for fast screening ultralow thermal conductivity. Our model also quantitatively reveals the correlation between off-diagonal coherence and diagonal populations and identifies the distinct crossover from particle-like to wave-like heat conduction. Our algorithm is promising for accelerating discovery of novel phononic crystals for emerging applications, such as thermoelectrics, superconductivity, and topological phonons for quantum information technology. 
    more » « less
  2. Abstract

    Proposed mechanisms for large intrinsic anomalous Hall effect (AHE) in magnetic topological semimetals include diverging Berry curvatures of Weyl nodes, anticrossing nodal rings or points of non-trivial bands. Here we demonstrate that a half-topological semimetal (HTS) state near a topological critical point can provide an alternative mechanism for a large AHE via systematic studies on an antiferromagnetic (AFM) half-Heusler compound TbPdBi. We not only observe a large AHE with tanΘH≈ 2 in its field-driven ferromagnetic (FM) phase, but also find a distinct Hall resistivity peak in its canted AFM phase. Moreover, we observe a large negative magnetoresistance with a value of ~98%. Our in-depth theoretical modelling indicates that these exotic transport properties originate from the HTS state which exhibits Berry curvature cancellation between the trivial spin-up and nontrivial spin-down bands. Our study offers alternative strategies for improved materials design for spintronics and other applications.

     
    more » « less
  3. Half-Heusler materials are strong candidates for thermoelectric applications due to their high weighted mobilities and power factors, which is known to be correlated to valley degeneracy in the electronic band structure. However, there are over 50 known semiconducting half-Heusler phases, and it is not clear how the chemical composition affects the electronic structure. While all the n-type electronic structures have their conduction band minimum at either the Γ - or X -point, there is more diversity in the p-type electronic structures, and the valence band maximum can be at either the Γ -, L -, or W -point. Here, we use high throughput computation and machine learning to compare the valence bands of known half-Heusler compounds and discover new chemical guidelines for promoting the highly degenerate W -point to the valence band maximum. We do this by constructing an “orbital phase diagram” to cluster the variety of electronic structures expressed by these phases into groups, based on the atomic orbitals that contribute most to their valence bands. Then, with the aid of machine learning, we develop new chemical rules that predict the location of the valence band maximum in each of the phases. These rules can be used to engineer band structures with band convergence and high valley degeneracy. 
    more » « less
  4. Among the diversity of new materials, two-dimensional crystal structures have been attracting significant attention from the broad scientific community due to their promising applications in nanoscience. In this study we predict a novel two-dimensional ferromagnetic boron material, which has been exhaustively studied with DFT methods. The relaxed structure of the 2D-B 6 monolayer consists of slightly flattened octahedral units connected with 2c-2e B–B σ-bonds. The calculated phonon spectrum and ab initio molecular dynamics simulations reveal the thermal and dynamical stability of the designed material. The calculation of the mechanical properties indicate a relatively high Young's modulus of 149 N m −1 . Moreover, the electronic structure indicates the metallic nature of the 2D-B 6 sheets, whereas the magnetic moment per unit cell is found to be 1.59 μ B . The magnetism in the 2D-B 6 monolayer can be described by the presence of two unpaired delocalized bonding elements inside every distorted octahedron. Interestingly, the nature of the magnetism does not lie in the presence of half-occupied atomic orbitals, as was shown for previously studied magnetic materials based on boron. We hope that our predictions will provide promising new ideas for the further fabrication of boron-based two-dimensional magnetic materials. 
    more » « less
  5. Abstract

    The prediction of non-trivial topological electronic states in half-Heusler compounds makes these materials good candidates for discovering new physics and devices as half-Heusler phases harbour a variety of electronic ground states, including superconductivity, antiferromagnetism, and heavy-fermion behaviour. Here, we report a systematic studies of electronic properties of a superconducting half-Heusler compound YPtBi, in its normal state, investigated using angle-resolved photoemission spectroscopy. Our data reveal the presence of a Dirac state at the$$\Gamma$$Γpoint of the Brillouin zone at 500 meV below the Fermi level. We observe the presence of multiple Fermi surface pockets, including two concentric hexagonal and six half-oval shaped pockets at the$$\Gamma$$Γand K points of the Brillouin zone, respectively. Furthermore, our measurements show Rashba-split bands and multiple surface states crossing the Fermi level, this is also supported by the first-principles calculations. Our findings of a Dirac state in YPtBi contribute to the establishing of half-Heusler compounds as a potential platform for novel topological phases.

     
    more » « less