Giant magnetic anisotropy of adatoms on the graphane surface.

Remarkable magnetic anisotropy provides more possibilities in electronic devices such as quantum information storage and processing. Here, based on first-principles calculations, we identified a series of magnetic adatoms including 12 d-type and 8 p-type members with estimated high structural stability and large magnetic anisotropy energy (MAE). Among the p-type systems, a giant MAE up to 157 meV was predicted for the Pb adatom with out-of-plane magnetization and up to 313 meV for Bi with in-plane magnetization. By analyzing the density of states and the p-orbital-resolved MAE, the large MAEs are found to mainly derive from the orbital hybridization of degenerated px/y near the Fermi levels, which is induced by the synergistic effect of the ligand field and significant spin-orbit coupling interaction. In addition, by comparing various magnetic configurations of Pb/Bi atomic kagome/hexagonal/triangular magnetic lattices, we found that their magnetization keeps the same direction as that of the single Pb/Bi adatom, which further confirms the robust magnetic anisotropy of the individual Pb/Bi adatom on the graphane surface. Our findings provide a promising platform for the realization of atomic scale memory.

Controllable spin splitting in 2D ferroelectric few-layerγ-GeSe.

γ-GeSe is a new type of layered bulk material that was recently successfully synthesized. By means of density functional theory first-principles calculations, we systematically studied the physical properties of two-dimensional (2D) few-layerγ-GeSe. It is found that few-layerγ-GeSe are semiconductors with band gaps decreasing with increasing layer number; and 2Dγ-GeSe with layer numbern⩾ 2 are ferroelectric with rather low transition barriers, consistent with the sliding ferroelectric mechanism. Particularly, spin-orbit coupling induced spin splitting is observed at the top of valence band, which can be switched by the ferroelectric reversal; furthermore, their negative piezoelectricity also enables the regulation of spin splitting by strain. Finally, excellent optical absorption was also revealed. These intriguing properties make 2D few-layerγ-GeSe promising in spintronic and optoelectric applications.

Unexpected spontaneous symmetry breaking and diverse ferroicity in two-dimensional mono-metal phosphorus chalcogenides.

Mono-metal phosphorus trichalcogenides (MPX3) have attracted intensive interest due to their intriguing magnetic properties and potential applications. Generally, single-layer two-dimensional (2D) MPX3 are believed to be centrosymmetric. However, we discovered that unexpected spontaneous symmetry breaking may occur in some 2D MPX3, i.e., vertical P-P dimers move out of the plane and become tilted, leading to the structural stability being enhanced, the inversion symmetry being simultaneously broken, and ferroelectricity or ferroelasticity emerging. By systematically investigating the family (176) of 2D MPX3, we found that 34 members undergo such symmetry breaking during geometric optimization, in which ten are identified to be dynamically stable. We show that the mismatch between the triangular sublattice of P-P dimers and the hexagonal sublattice of M atoms and the variable accommodation of P lone-pair electrons in different valence states of M atoms play dominant roles in the inversion symmetry breaking and the emergence of ferroicity. We obtained a ferroic atlas of the whole 2D MPX3 family, which also includes many stable antiferromagnetic and non-ferroic members that have never been reported. Our work not only presents ferroelectricity in the 2D MPX3 family but also reveals how diverse ferroicity emerges with various spontaneous symmetry breakings, which will be helpful for further exploration of 2D ferroic materials.

Ferroelectric and Room-Temperature Ferromagnetic Semiconductors in the 2D MIMIIGe2X6 Family: First-Principles and Machine Learning Investigations.

Inspired by experimentally discovering ferromagnetism and ferroelectricity in two-dimensional (2D) CrGeTe3 and CuInP2S6 with similar geometric structures, respectively, we systematically investigated ferroic properties in a large family of 2D MIMIIGe2X6 (MI and MII = metal elements, X = S/Se/Te) by combining high-throughput first-principles calculations and the machine learning method. We identified 12 stable 2D multiferroics containing simultaneously ferromagnetic (FM) and ferroelectric (FE) properties and 35 2D ferromagnets without FE polarization. Particularly, the predicted FM Curie temperatures (TC) of eight 2D FM+FE semiconductors are close to or above room temperature. The ferroelectricity originates from the spontaneous geometric symmetry breaking induced by the unexpected shift of Ge-Ge atomic pairs and the emergence of Ge lone pair electrons, which also strengthens the p-d orbital hybridization between X atoms and metal atoms, leading to enhanced super-super-exchange interactions and raising the FM TC. Our findings not only enrich the family of 2D ferroic materials and present room-temperature FM semiconductors but also disclose the mechanism of the emerging ferroelectricity and enhanced ferromagnetism, which sheds light on the realization of high temperature multiferroics as well as FM semiconductors.

High-efficient ab initio Bayesian active learning method and applications in prediction of two-dimensional functional materials.

Beyond the conventional trial-and-error method, machine learning offers a great opportunity to accelerate the discovery of functional materials, but still often suffers from difficulties such as limited materials data and the unbalanced distribution of target properties. Here, we propose the ab initio Bayesian active learning method that combines active learning and high-throughput ab initio calculations to accelerate the prediction of desired functional materials with ultrahigh efficiency and accuracy. We apply it as an instance to a large family (3119) of two-dimensional hexagonal binary compounds with unbalanced materials properties, and accurately screen out the materials with maximal electric polarization and proper photovoltaic band gaps, respectively, whereas the computational costs are significantly reduced by only calculating a few tenths of the possible candidates in comparison with a random search. This approach shows the enormous advantages for the cases with unbalanced distribution of target properties. It can be readily applied to seek a broad range of advanced materials.

Voting Data-Driven Regression Learning for Accelerating Discovery of Advanced Functional Materials and Applications to Two-Dimensional Ferroelectric Materials.

Regression machine learning is widely applied to predict various materials. However, insufficient materials data usually leads to poor performance. Here, we develop a new voting data-driven method that could generally improve the performance of the regression learning model for accurately predicting properties of materials. We apply it to investigate a large family (2135) of two-dimensional hexagonal binary compounds focusing on ferroelectric properties and find that the performance of the model for electric polarization is indeed greatly improved, where 38 stable ferroelectrics with out-of-plane polarization including 31 metals and 7 semiconductors are screened out. By unsupervised learning, actionable information such as how the number and orbital radius of valence electrons, ionic polarizability, and electronegativity of constituent atoms affect polarization was extracted. Our voting data-driven method not only reduces the size of materials data for constructing a reliable learning model but also enables one to make precise predictions for targeted functional materials.

Large family of two-dimensional ferroelectric metals discovered via machine learning.

Ferroelectricity and metallicity are usually believed not to coexist because conducting electrons would screen out static internal electric fields. In 1965, Anderson and Blount proposed the concept of "ferroelectric metal", however, it is only until recently that very rare ferroelectric metals were reported. Here, by combining high-throughput ab initio calculations and data-driven machine learning method with new electronic orbital based descriptors, we systematically investigated a large family (2964) of two-dimensional (2D) bimetal phosphates, and discovered 60 stable ferroelectrics with out-of-plane polarization, including 16 ferroelectric metals and 44 ferroelectric semiconductors that contain seven multiferroics. The ferroelectricity origins from spontaneous symmetry breaking induced by the opposite displacements of bimetal atoms, and the full-d-orbital coinage metal elements cause larger displacements and polarization than other elements. For 2D ferroelectric metals, the odd electrons per unit cell without spin polarization may lead to a half-filled energy band around Fermi level and is responsible for the metallicity. It is revealed that the conducting electrons mainly move on a single-side surface of the 2D layer, while both the ionic and electric contributions to polarization come from the other side and are vertical to the above layer, thereby causing the coexistence of metallicity and ferroelectricity. Van der Waals heterostructures based on ferroelectric metals may enable the change of Schottky barrier height or the Schottky-Ohmic contact type and induce a dramatic change of their vertical transport properties. Our work greatly expands the family of 2D ferroelectric metals and will spur further exploration of 2D ferroelectric metals.

Boron based layered electrode materials for metal-ion batteries.

Graphite is the most commonly used electrode material, which is mainly due to two key advantages, i.e., its layered structure acts a perfect framework for the accommodation and migration of ions, and the light atomic mass of carbon is conducive to obtaining a high specific capacity. As a neighbor of carbon in the periodic table, boron is even lighter than carbon, and it can also form various layered structures. Here, we systematically investigate boron-based layered compounds to explore their potential applications as electrode materials by means of first-principle calculations. Among various types of boron compounds, MXB4 (M = Li, Na, Mg; X = Al, Ga) with the YCrB4-type structure are found to be potentially excellent electrode materials for metal-ion batteries. The adsorption and migration of Li/Na/Mg in MXB4 have been presented, and migration barriers comparable with conventional electrode materials are observed. In particular, Li2AlB4 and Li2GaB4 are found to exhibit quite high specific capacities of 754 mA h g-1 and 470 mA h g-1 compared to the theoretical value of graphite (372 mA h g-1) as well as low average voltages of 0.71 V and 0.79 V, respectively, revealing that they may be good anode materials for Lithium ion batteries.

Exploring T-carbon for energy applications.

Seeking for next-generation energy sources that are economic, sustainable (renewable), clean (environment-friendly), and earth-abundant, is crucial when facing the challenges of the energy crisis. There have been numerous studies exploring the possibility of carbon-based materials to be utilized in future energy applications. In this paper, we introduce T-carbon, which is a theoretically predicted but also a recently experimentally synthesized carbon allotrope, as a promising material for next-generation energy applications. It is shown that T-carbon can be potentially used in thermoelectrics, hydrogen storage, lithium ion batteries, etc. The challenges, opportunities, and possible directions for future studies of energy applications of T-carbon are also addressed. With the development of more environment-friendly technologies, the promising applications of T-carbon in energy fields would not only produce scientifically significant impact in related fields, but also lead to a number of industrial and technical applications.

Lithium adsorption and migration in group IV-VI compounds and GeS/graphene heterostructures: a comparative study.

By means of first-principles calculations, the adsorption and transport properties of lithium (Li) in orthorhombic group IV-VI compounds MX (M = Ge, Sn; X = S, Se) and GeS/graphene heterostructures have been systematically investigated. Strong interactions and distinct charge transfer between Li and compounds MX are observed. The Li diffusion barriers along the zigzag direction are found to be much lower than that along the armchair direction in monolayer and bulk MX, showing distinct anisotropic diffusion features. In particular, monolayer GeS has a lowest barrier of 0.173 eV (zigzag) among them and it will transit from a semiconductor to a metallic state after Li intercalation, indicating fast Li and electron transport properties. As a comparison, the addition of graphene in a GeS/graphene heterostructure could enhance its binding with Li, decrease the Li diffusion barrier and inhibit the volume expansion dramatically, suggesting a potential performance improvement. Our study not only reveals the directional transport properties of Li in MX, but also improves the understanding of the role of graphene in the MX/graphene heterostructure, and shows great potential application in the field of electrode materials.