Effizienter als in zweidimensionalen Einheiten ist die Energieumwandlung in dreidimensionalen farbstoffsensibilisierten Solarzellen (DSSCs) in einer Hybridstruktur aus optischen Fasern und Nanodrähten. Axiale Bestrahlung von innen erhöht die Energieumwandlungseffizienz einer Hybridstruktur mit der Form einer rechteckigen Faser (siehe Bild) bis zum Sechsfachen gegenüber der Bestrahlung von außen senkrecht zur Faserachse. Detailed facts of importance to specialist readers are published as "Supporting Information". Such documents are peer-reviewed, but not copy-edited or typeset. They are made available as submitted by the authors. Please note: The publisher is not responsible for the content or functionality of any supporting information supplied by the authors. Any queries (other than missing content) should be directed to the corresponding author for the article.
Vapor-liquid-solid (VLS) is a well-established process in catalyst-guided growth of nanowires. The catalyst particle is generally believed to be in liquid state during growth, and it is the site for adsorbing incoming molecules; the crystalline structure of the catalyst may not have any influence on the structure of the grown one-dimensional nanostructures. In this paper, using tin particle guided growth of ZnO nanostructures as a model system, we show that the interfacial region of the tin particle with the ZnO nanowire/nanobelt could be ordered (or partially crystalline) during the VLS growth, although the local growth temperature is much higher than the melting point of tin, and the crystallographic lattice structure at the interface is important in defining the structural characteristics of the grown nanowires and nanobelts. The interface prefers to take the least lattice mismatch; thus, the crystalline orientation of the tin particle may determine the growth direction and the side surfaces of the nanowires and nanobelts. This result may have important impact on the understanding of the physical chemical process in the VLS growth.
Due to limitations in operational scope and efficiency, a single Autonomous Underwater Vehicle (AUV) falls short of meeting the demands of the contemporary marine working environment. Consequently, there is a growing interest in the coordination of multiple AUVs. To address the requirements of coordinated missions, this paper proposes a comprehensive solution for the coordinated development of multi-AUV formations, encompassing long-range ferrying, coordinated detection, and surrounding attack. In the initial phase, detection devices are deactivated, employing a path planning method based on the Rapidly Exploring Random Tree (RRT) algorithm to ensure collision-free AUV movement. During the coordinated detection phase, an artificial potential field method is applied to maintain AUV formation integrity and avoid obstacles, dynamically updating environmental probability based on formation movement. In the coordinated surroundings attack stage, predictive capabilities are enhanced using Long Short-Term Memory (LSTM) networks and reinforcement learning. Specifically, LSTM forecasts the target’s position, while the Deep Deterministic Policy Gradient (DDPG) method controls AUV formation. The effectiveness of this coordinated solution is validated through an integrated simulation trajectory.
