For spintronic devices excited by a sudden magnetic or optical perturbation, the torque acting on the magnetization plays a key role in its precession and damping. However, the torque itself can be a dynamical quantity via the time-dependent anisotropies of the system. A challenging problem for applications is then to disentangle the relative importance of various sources of anisotropies in the dynamical torque, such as the dipolar field, the crystal structure or the shape of the particular interacting magnetic nanostructures. Here, we take advantage of a range of colloidal cobalt ferrite nanocubes assembled in 2D thin films under controlled magnetic fields to demonstrate that the phase, ϕPrec, of the precession carries a strong signature of the dynamical anisotropies. Performing femtosecond magneto-optics, we show that ϕPrec displays a π-shift for a particular angle θH of an external static magnetic field, H. θH is controlled with the cobalt concentration, the laser intensity, as well as the interparticle interactions. Importantly, it is shown that the shape anisotropy, which strongly departs from those of equivalent bulk thin films or individual noninteracting nanoparticles, reveals the essential role played by the interparticle collective effects. This work shows the reliability of a noninvasive optical approach to characterize the dynamical torque in high density magnetic recording media made of organized and interacting nanoparticles.
Download full-text PDF |
Source |
---|---|
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4981894 | PMC |
http://dx.doi.org/10.1021/acs.nanolett.6b02618 | DOI Listing |
Sci Rep
December 2024
School of Civil Engineering and Architecture, East China Jiaotong University, Nanchang, 330013, Jiangxi, People's Republic of China.
Compared with simple formations, EPB (earth pressure balance) shield tunnelling in composite formations encounters severe problems with muck conditioning and require improved muck conditioning technology to fulfil expectations for continuous and efficient excavation. In the Nanchang Metro Line 4 Project, a water-rich sand-argillaceous siltstone composite formation is encountered. With a high moisture content and complex composite formation ratio, it is quite difficult to determine the optimum muck conditioning scheme, and thus, muck spewing accidents frequently occur during the tunnelling process.
View Article and Find Full Text PDFSci Rep
December 2024
School of Vehicle and Energy, Yanshan University, 438 West Hebei Avenue, Qinhuangdao, 066004, People's Republic of China.
This study presents a strategy for an intelligent vehicle trajectory tracking system that employs an adaptive robust non-singular fast terminal sliding mode control (ARNFTSMC) approach to address the challenges of uncertain nonlinear dynamics. Initially, a path tracking error system based on mapping error is established, along with a speed tracking error system. Subsequently, a novel ARNFTSMC strategy is introduced to tackle the uncertainties and external perturbations encountered during actual vehicle operation.
View Article and Find Full Text PDFSci Data
December 2024
The University of North Carolina at Chapel Hill and North Carolina State University, Joint Department of Biomedical Engineering, Raleigh, 27695, USA.
The role of the human ankle joint in activities of daily living, including walking, maintaining balance, and participating in sports, is of paramount importance. Ankle joint dorsiflexion and plantarflexion functionalities mainly account for ground clearance and propulsion power generation during locomotion tasks, where those functionalities are driven by the contraction of ankle joint skeleton muscles. Studies of corresponding muscle contractility during ankle dynamic functions will facilitate us to better understand the joint torque/power generation mechanism, better diagnose potential muscular disorders on the ankle joint, or better develop wearable assistive/rehabilitative robotic devices that assist in community ambulation.
View Article and Find Full Text PDFBiomimetics (Basel)
December 2024
School of Computer Science and Technology, Dongguan University of Technology, Dongguan 523808, China.
In this paper, a deep reinforcement learning (DRL) approach based on generative adversarial imitation learning (GAIL) and long short-term memory (LSTM) is proposed to resolve tracking control problems for robotic manipulators with saturation constraints and random disturbances, without learning the dynamic and kinematic model of the manipulator. Specifically, it limits the torque and joint angle to a certain range. Firstly, in order to cope with the instability problem during training and obtain a stability policy, soft actor-critic (SAC) and LSTM are combined.
View Article and Find Full Text PDFMethods Mol Biol
December 2024
Structure and Dynamics of Molecular Machines, Max Planck Institute of Biochemistry, Martinsried, Germany.
Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!