Hybrid Functional Study Rationalizes the Simple Cubic Phase of Calcium at High Pressures

Simple cubic (SC) phase has been long experimentally determined as the high-pressure phase III of elemental calcium (Ca) since 1984. However, recent density functional calculations within semi-local approximation showed that this SC phase is structurally unstable by exhibiting severely imaginary phonons, and is energetically unstable with respect to a theoretical body-centered tetragonal I41/amd structure over the pressure range of phase III. These calculations generated extensive debates on the validity of SC phase. Here we have re-examined the SC structure by performing more precise density functional calculations within hybrid functionals of Heyd-Scuseria-Erhzerhof (HSE) and PBE0. Our calculations were able to rationalize fundamentally the phase stability of SC structure over all other known phases by evidence of its actual energetic stability above 33 GPa and its intrinsically dynamical stability without showing any imaginary phonons in the entire pressure range studied. We further established that the long-thought theoretical I41/amd structure remains stable in a narrow pressure range before entering SC phase and is actually the structure of experimental Ca-III' synthesized recently at low temperature 14 K as supported by the excellent agreement between our simulated X-ray diffraction patterns and the experimental data. Our results shed strong light on the crucial role played by the precise electron exchange energy in a proper description of the potential energy of Ca.Comment: submitted to Physical Review

Robust Multi-sensor Data Fusion for Practical Unmanned Surface Vehicles (USVs) Navigation

The development of practical Unmanned Surface Vehicles (USVs) are attracting increasing attention driven by their assorted military and commercial application potential. However, addressing the uncertainties presented in practical navigational sensor measurements of an USV in maritime environment remain the main challenge of the development. This research aims to develop a multi-sensor data fusion system to autonomously provide an USV reliable navigational information on its own positions and headings as well as to detect dynamic target ships in the surrounding environment in a holistic fashion. A multi-sensor data fusion algorithm based on Unscented Kalman Filter (UKF) has been developed to generate more accurate estimations of USV’s navigational data considering practical environmental disturbances. A novel covariance matching adaptive estimation algorithm has been proposed to deal with the issues caused by unknown and varying sensor noise in practice to improve system robustness. Certain measures have been designed to determine the system reliability numerically, to recover USV trajectory during short term sensor signal loss, and to autonomously detect and discard permanently malfunctioned sensors, and thereby enabling potential sensor faults tolerance. The performance of the algorithms have been assessed by carrying out theoretical simulations as well as using experimental data collected from a real-world USV projected collaborated with Plymouth University. To increase the degree of autonomy of USVs in perceiving surrounding environments, target detection and prediction algorithms using an Automatic Identification System (AIS) in conjunction with a marine radar have been proposed to provide full detections of multiple dynamic targets in a wider coverage range, remedying the narrow detection range and sensor uncertainties of the AIS. The detection algorithms have been validated in simulations using practical environments with water current effects. The performance of developed multi-senor data fusion system in providing reliable navigational data and perceiving surrounding environment for USV navigation have been comprehensively demonstrated

Ecology of giant virus in deep ocean

令和4年度 京都大学化学研究所 スーパーコンピュータシステム 利用報告