Angle-dependent magnetoresistance as a sensitive probe of the charge density wave in quasi-one-dimensional semimetal Ta2_2NiSe7_7

The behavior of charge density wave (CDW) in an external magnetic field is dictated by both orbital and Pauli (Zeeman) effects. A quasi-one-dimensional (Q1D) system features Q1D Fermi surfaces that allow these effects to be distinguished, which in turn can provide sensitive probe to the underlying electronic states. Here we studied the field dependence of an incommensurate CDW in a transition-metal chalcogenide Ta2NiSe7 with a Q1D chain structure. The angle-dependent magnetoresistance (MR) is found to be very sensitive to the relative orientation between the magnetic field and the chain direction. With an applied current fixed along the b axis (the chain direction), the angle-dependent MR shows a striking change of the symmetry below T_CDW only for a rotating magnetic field in the ac plane. In contrast, the symmetry axis remains unchanged for other configurations (H in ab and bc plane). The orbital effect conforms to the lattice symmetry, while Pauli effect in the form of {\mu}B B / v_F can be responsible for such symmetry change, provided that the Fermi velocity v_F is significantly anisotropic and the nesting vector changes in a magnetic field, which is corroborated by our first-principles calculations. Our results show that the angle-dependent MR is a sensitive transport probe of CDW and can be useful for the study of low-dimensional systems in general

Band dependence of charge density wave in quasi-one-dimensional Ta2NiSe7 probed by orbital magnetoresistance

Ta2NiSe7 is a quasi-one-dimensional (quasi-1D) transition-metal chalcogenide with Ta and Ni chain structure. An incommensurate charge-density wave (CDW) in this quasi-1D structure was well studied previously using tunnelling spectrum, X-ray and electron diffraction, whereas its transport property and the relation to the underlying electronic states remain to be explored. Here we report our results of magnetoresistance (MR) on Ta2NiSe7. A breakdown of the Kohler's rule is found upon entering the CDW state. Concomitantly, a clear change of curvature in the field dependence of MR is observed. We show that the curvature change is well described by two-band orbital MR, with the hole density being strongly suppressed in the CDW state, indicating that the $p$ orbitals from Se atoms dominate the change in transport through the CDW transition

MULTI-SCALE ANALYSIS OF THE STRUCTURE-MECHANICS RELATIONSHIP OF MYCELIUM-BASED BIO-COMPOSITES

The construction industry faces significant challenges due to the environmental impact of traditional materials like steel and concrete, whose production is energy-intensive and contributes to environmental pollution. This issue is exacerbated by the growing global demand for construction materials, driven by an increasing population. Concurrently, the agricultural and wood industrial sectors produce vast byproducts, such as straw, husk, coir, sawdust, and wood chips. They are often considered as wastes and disposed of through methods like burning. Such a reckless treatment releases greenhouse gases that further lead to environmental degradation. Mycelium, the vegetative part of fungi, presents a natural, promising solution to treat these wastes due to its energy-efficient growth, minimal byproduct generation, and broad application range. Integrating mycelium with organic substrates such as agricultural waste makes it possible to create lightweight and biodegradable materials. These mycelium-based composites offer numerous advantages, including sustainability, non-toxicity, and the ability to be composted at the end of their lifecycle, thus contributing to a circular economy. This dissertation explores the potential of mycelium-based bio-composite materials for future development into a class of promising insulation materials. Central to the dissertation is integrating mycelium with organic substrates, such as agricultural waste, to create bio-composites with multifunctional features (e.g., mechanical solidity and thermal insulation) obtained through lab treatments after growth. This approach presents a method to repurpose agrarian byproducts and reduce waste. The study meticulously examines the applicability of these bio-composites in the inner layer of the structure (insulation layer), assessing their potential use in various contexts. The dissertation is structured to methodically address these research goals, starting with a comprehensive literature review of mycelium and its potential applications. Subsequent chapters detail experimental investigations into mycelium-based materials\u27 physical and mechanical properties, exploring species selection, substrate composition, and environmental conditions that influence mycelium growth and material performance. The study emphasizes the importance of continued research and development in this area while acknowledging the current limitations in strength, stiffness, hardness, flexibility, toughness, and durability compared to conventional construction materials. This dissertation contributes to the field of insulation materials by studying mycelium-based bio-composites. It highlights the potential of these materials to address some environmental challenges and offer a viable path toward more sustainable practices in the long term. The findings underscore the need for ongoing exploration and innovation in material science to meet the demands of a growing population while preserving environmental integrity

Research on Surface Mounting Technology of Micromechanical Silicon Resonant Accelerometer

Surface mounting technology is a key process in MEMS packaging. The finite element model of package structures was established in this paper according to the designed micromechanical silicon resonant accelerometer. The effects of package substrate materials, adhesive material characteristics, uneven adhesive thickness, and adhesive defects on the micromechanical silicon resonant accelerometer were analyzed with ANSYS software. Results showed that the package substrate material strongly affected the resonance frequency of the resonator after the application of surface mounting technology. The Young’s modulus and thermal expansion coefficient of adhesives were found to be important factors that affect chip thermal stress and warpage. Uneven adhesive thickness and adhesive defects also affect the resonance frequency of the resonator. DOI: http://dx.doi.org/10.11591/telkomnika.v11i5.247

Numerical Simulations of Spread Characteristics of Toxic Cyanide in the Danjiangkou Reservoir in China under the Effects of Dam Cooperation

Many accidents of releasing toxic pollutants into surface water happen each year in the world. It is believed that dam cooperation can affect flow field in reservoir and then can be applied to avoiding and reducing spread speed of toxic pollutants to drinking water intake mouth. However, few studies investigated the effects of dam cooperation on the spread characteristics of toxic pollutants in reservoir, especially the source reservoir for water diversion with more than one dam. The Danjiangkou Reservoir is the source reservoir of the China’ South-to-North Water Diversion Middle Route Project. The human activities are active within this reservoir basin and cyanide-releasing accident once happened in upstream inflow. In order to simulate the spread characteristics of cyanide in the reservoir in the condition of dam cooperation, a three-dimensional water quality model based on the Environmental Fluid Dynamics Code (EFDC) has been built and put into practice. The results indicated that cooperation of two dams of the Danjiangkou Reservoir could be applied to avoiding and reducing the spread speed of toxic cyanide in the reservoir directing to the water intake mouth for water diversions

Learning to Use Chopsticks in Diverse Gripping Styles

Learning dexterous manipulation skills is a long-standing challenge in computer graphics and robotics, especially when the task involves complex and delicate interactions between the hands, tools and objects. In this paper, we focus on chopsticks-based object relocation tasks, which are common yet demanding. The key to successful chopsticks skills is steady gripping of the sticks that also supports delicate maneuvers. We automatically discover physically valid chopsticks holding poses by Bayesian Optimization (BO) and Deep Reinforcement Learning (DRL), which works for multiple gripping styles and hand morphologies without the need of example data. Given as input the discovered gripping poses and desired objects to be moved, we build physics-based hand controllers to accomplish relocation tasks in two stages. First, kinematic trajectories are synthesized for the chopsticks and hand in a motion planning stage. The key components of our motion planner include a grasping model to select suitable chopsticks configurations for grasping the object, and a trajectory optimization module to generate collision-free chopsticks trajectories. Then we train physics-based hand controllers through DRL again to track the desired kinematic trajectories produced by the motion planner. We demonstrate the capabilities of our framework by relocating objects of various shapes and sizes, in diverse gripping styles and holding positions for multiple hand morphologies. Our system achieves faster learning speed and better control robustness, when compared to vanilla systems that attempt to learn chopstick-based skills without a gripping pose optimization module and/or without a kinematic motion planner

Intelligent high-altitude power inspection vision module based on KendryteK210 microcontroller

Now our country has a huge electric power system, it needs a complex electric power transmission network to support its normal operation. With the development of unmanned aerial vehicle platform and microprocessor technology in recent years, the unmanned aerial vehicle inspection platform based on microprocessor is an important development direction of power transmission network maintenance. Based on this background, this paper designs an intelligent high-altitude line inspection vision module based on KendryteK210 microcontroller. The module can be used as a UAV load to carry out efficient power line patrol work, and wireless communication is carried out by ESP8285Wi-Fi. First of all, the inspection vision module uses OV2640 visible light camera to complete the target image data acquisition. Then, in the process of data processing, the least square method and Theil-Sen regression algorithm are combined to get the target line object, so as to get the slope and length of the line object and other parameters. Finally, the target in the image was identifi ed based on the yolov2 neural network model, and then the fl ight path instruction was provided for the UAV platform