A simple and efficient criterion for ready screening of potential topological insulators

Screening potential topological insulators in half-Heusler compounds via compressed-sensing

Ternary half-Heusler compounds with widely tunable electronic structures, present a new platform to discover topological insulators (TIs). Due to time-consuming computations and synthesis procedures, the identification of new TIs is however a rough task. Here, we adopt a compressed-sensing approach to rapidly screen potential TIs in half-Heusler family, which is realized via a two-dimensional descriptor that only depends on the fundamental properties of the constituent atoms. Beyond the finite training data, the proposed descriptor is employed to screen many new half-Heusler compounds, including those with integer and fractional stoichiometry, and a larger number of possible TIs are predicted.

Data-Driven Materials Science: Status, Challenges, and Perspectives

Data-driven science is heralded as a new paradigm in materials science. In this field, data is the new resource, and knowledge is extracted from materials datasets that are too big or complex for traditional human reasoning-typically with the intent to discover new or improved materials or materials phenomena. Multiple factors, including the open science movement, national funding, and progress in information technology, have fueled its development. Such related tools as materials databases, machine learning, and high-throughput methods are now established as parts of the materials research toolset. However, there are a variety of challenges that impede progress in data-driven materials science: data veracity, integration of experimental and computational data, data longevity, standardization, and the gap between industrial interests and academic efforts. In this perspective article, the historical development and current state of data-driven materials science, building from the early evolution of open science to the rapid expansion of materials data infrastructures are discussed. Key successes and challenges so far are also reviewed, providing a perspective on the future development of the field.

Dynamically reconfigurable topological edge state in phase change photonic crystals

The observation of topological edge states (TESs) revolutionized our understanding of scattering and propagation of electromagnetic (EM) waves. Supported by topological robustness, the TES at the interface between trivial and non-trivial insulators was not reflected from the structural disorders and imperfections. Recently topological photonic crystals (PhCs) were demonstrated to obtain remarkable one-way propagation of the TES, having the advantages of lossless propagation, dense integration, and high fabrication tolerance over conventional PhCs. Nevertheless, the lack of reversible switching of TES possesses significant limitations in helicity/spin filtering and tunable photonic devices. We proposed a topological PhC based on a prototypical phase-change material, Ge₂Sb₂Te₅ (GST225) to solve the problem. We find that at a particular frequency, the TES within the structure can be reversibly switched between "on" and "off" by transiting the GST225 structural state between amorphous and crystalline. Moreover, the topology of the PhC was maintained since the tuning of TES was achieved by varying the refractive index of GST225 instead of the structural geometry. This provides a continuous change of the spectral position of the photonic bandgap and TES by gradually crystallising the GST225. We show that the phase change of GST225 from amorphous to crystalline and vice versa can be engineered in nanoseconds. Our proof of concept may offer a platform for dynamically tuning the TESs that might otherwise be challenging to attain in photonic systems. We expect it to have potential applications for photonic devices in topological optical circuits and scatter-free one-way light propagation.

Prediction of intrinsic two dimensional ferromagnetism realized quantum anomalous Hall effect

The monolayer of FeX₃ (X = Cl, Br, I) possesses a quantum anomalous Hall insulating phase generated by the honeycomb lattice of iron atoms.

High-Throughput Screening and Automated Processing toward Novel Topological Insulators

The bottleneck of current studies on topological insulators is to identify better materials that can be fabricated into devices more feasibly. To search for novel topological materials, we developed a high-throughput framework that can be utilized to screen for candidates with known crystal structures and further showcase topological properties based on automated construction of Wannier functions. We have applied our methods to ternary compounds of Bi, Sb, and nitrides as a representative sample. The topological properties are characterized by the surface states, verified by auxiliary evaluation of the Z₂ topological invariant. We successfully identified seven topological insulators. Our work paves the way to design novel topological materials.