Spontaneous generation and active manipulation of real-space optical vortex

Optical vortices host the orbital nature of photons, which offers an extra degree of freedom in photonic applications. Unlike vortices in other physical entities, optical vortices require structural singularities, which restrict their abilities in terms of dynamic and interactive characteristics. In this study, we present the spontaneous generation and external magnetic field-induced manipulation of an optical vortex and antivortex. A gradient-thickness optical cavity (GTOC) consisting of an Al/SiO2/Ni/SiO2 multilayer structure realised the distinct transition between the trivial and non-trivial topological phases, depending on the magneto-optic effects of the Ni layer. In the non-trivial topological phase, the mathematical singularities generating the optical vortex and antivortex pair in the reflected light existed in the generalised parameter space of the thicknesses of the top and bottom SiO2 layers, which is bijective to the real space of the GTOC. Coupled with the magnetisation, the optical vortex and antivortex in the GTOC experienced an effective spin-orbit interaction and showed topology-dependent dynamics under external magnetic fields. We expect that field-induced engineering of optical vortices will pave the way for the study of topological photonic interactions and their applications.Comment: 22 pages, 4 figure

Reducing time to discovery : materials and molecular modeling, imaging, informatics, and integration

This work was supported by the KAIST-funded Global Singularity Research Program for 2019 and 2020. J.C.A. acknowledges support from the National Science Foundation under Grant TRIPODS + X:RES-1839234 and the Nano/Human Interfaces Presidential Initiative. S.V.K.’s effort was supported by the U.S. Department of Energy (DOE), Office of Science, Basic Energy Sciences (BES), Materials Sciences and Engineering Division and was performed at the Oak Ridge National Laboratory’s Center for Nanophase Materials Sciences (CNMS), a U.S. Department of Energy, Office of Science User Facility.Multiscale and multimodal imaging of material structures and properties provides solid ground on which materials theory and design can flourish. Recently, KAIST announced 10 flagship research fields, which include KAIST Materials Revolution: Materials and Molecular Modeling, Imaging, Informatics and Integration (M3I3). The M3I3 initiative aims to reduce the time for the discovery, design and development of materials based on elucidating multiscale processing-structure-property relationship and materials hierarchy, which are to be quantified and understood through a combination of machine learning and scientific insights. In this review, we begin by introducing recent progress on related initiatives around the globe, such as the Materials Genome Initiative (U.S.), Materials Informatics (U.S.), the Materials Project (U.S.), the Open Quantum Materials Database (U.S.), Materials Research by Information Integration Initiative (Japan), Novel Materials Discovery (E.U.), the NOMAD repository (E.U.), Materials Scientific Data Sharing Network (China), Vom Materials Zur Innovation (Germany), and Creative Materials Discovery (Korea), and discuss the role of multiscale materials and molecular imaging combined with machine learning in realizing the vision of M3I3. Specifically, microscopies using photons, electrons, and physical probes will be revisited with a focus on the multiscale structural hierarchy, as well as structure-property relationships. Additionally, data mining from the literature combined with machine learning will be shown to be more efficient in finding the future direction of materials structures with improved properties than the classical approach. Examples of materials for applications in energy and information will be reviewed and discussed. A case study on the development of a Ni-Co-Mn cathode materials illustrates M3I3's approach to creating libraries of multiscale structure-property-processing relationships. We end with a future outlook toward recent developments in the field of M3I3.Peer reviewe

Customizing Radiative Decay Dynamics of Two-Dimensional Excitons via Position- and Polarization-Dependent Vacuum-Field Interference

Embodying bosonic and interactive characteristics in two-dimensional space, excitons in transition metal dichalcogenides (TMDCs) have garnered considerable attention. The utilization of the strong-correlation effects, long-range transport, and valley-dependent properties requires customizing exciton decay dynamics. Vacuum-field manipulation allows radiative decay engineering without disturbing intrinsic material properties. However, conventional flat mirrors cannot customize the radiative decay landscape in TMDC’s plane or support vacuum-field interference with desired spectrum and polarization properties. Here, we present a meta-mirror platform resolving the issues with more optical degrees of freedom. For neutral excitons of the monolayer MoSe2, the optical layout formed by meta-mirrors manipulated the radiative decay rate in space by 2 orders of magnitude and revealed the statistical correlation between emission intensity and spectral line width. Moreover, the anisotropic meta-mirror demonstrated polarization-dependent radiative decay control. Our platform would be promising to tailor two-dimensional distributions of lifetime, density, diffusion, and polarization of TMDC excitons in advanced opto-excitonic applications.11Nsciescopu

Reducing time to discovery:materials and molecular modeling, imaging, informatics, and integration

Multiscale and multimodal imaging of material structures and properties provides solid ground on which materials theory and design can flourish. Recently, KAIST announced 10 flagship research fields, which include KAIST Materials Revolution: Materials and Molecular Modeling, Imaging, Informatics and Integration (M3I3). The M3I3 initiative aims to reduce the time for the discovery, design and development of materials based on elucidating multiscale processing-structure-property relationship and materials hierarchy, which are to be quantified and understood through a combination of machine learning and scientific insights. In this review, we begin by introducing recent progress on related initiatives around the globe, such as the Materials Genome Initiative (U.S.), Materials Informatics (U.S.), the Materials Project (U.S.), the Open Quantum Materials Database (U.S.), Materials Research by Information Integration Initiative (Japan), Novel Materials Discovery (E.U.), the NOMAD repository (E.U.), Materials Scientific Data Sharing Network (China), Vom Materials Zur Innovation (Germany), and Creative Materials Discovery (Korea), and discuss the role of multiscale materials and molecular imaging combined with machine learning in realizing the vision of M3I3. Specifically, microscopies using photons, electrons, and physical probes will be revisited with a focus on the multiscale structural hierarchy, as well as structure-property relationships. Additionally, data mining from the literature combined with machine learning will be shown to be more efficient in finding the future direction of materials structures with improved properties than the classical approach. Examples of materials for applications in energy and information will be reviewed and discussed. A case study on the development of a Ni-Co-Mn cathode materials illustrates M3I3's approach to creating libraries of multiscale structure-property-processing relationships. We end with a future outlook toward recent developments in the field of M3I3.</p