Discontinuous fibre composites represent a class of materials that are strong, lightweight and have remarkable fracture toughness. These advantages partially explain the abundance and variety of discontinuous fibre composites that have evolved in the natural world. Many natural structures out-perform the conventional synthetic counterparts due, in part, to the more elaborate reinforcement architectures that occur in natural composites. Here we present an additive manufacturing approach that combines real-time colloidal assembly with existing additive manufacturing technologies to create highly programmable discontinuous fibre composites. This technology, termed as ‘3D magnetic printing', has enabled us to recreate complex bioinspired reinforcement architectures that deliver enhanced material performance compared with monolithic structures. Further, we demonstrate that we can now design and evolve elaborate reinforcement architectures that are not found in nature, demonstrating a high level of possible customization in discontinuous fibre composites with arbitrary geometries.
Here, recent significant developments are reviewed in manipulating soft matter systems through the use of magnetic torque. Magnetic torque enables the orientation, assembly, and manipulation of thermally fluctuating systems in broad material fields including biomaterials, ceramic and composite precursor suspensions, polymer solutions, fluids, foams, and gels. Magnetism offers an effective, safe, and massively parallel manufacturing approach. By exploiting magnetic torque, leading soft matter researchers have demonstrated new technologies in rheology, life sciences, optics, and structural materials. Specifically, magnetic torque has been used to assemble particle suspensions, to fabricate and actuate composite materials, and to control and manipulate biological materials. In each of these applications, there are energetic limitations to magnetic torque that need to be understood and characterized. However, magnetic torque offers a promising remote‐controlled approach to creating and enabling new soft matter technologies.
Abstract. The CopterSonde is an unmanned aircraft system (UAS) developed in house by a team of engineers and meteorologists at the University of Oklahoma. The CopterSonde is an ambitious attempt by the Center for Autonomous Sensing and Sampling to address the challenge of filling the observational gap present in the lower atmosphere among the currently used meteorological instruments such as towers and radiosondes. The CopterSonde is a unique and highly flexible platform for in situ atmospheric boundary layer measurements with high spatial and temporal resolution, suitable for meteorological applications and research. Custom autopilot algorithms and hardware features were developed as solutions to problems identified throughout several field experiments carried out since 2017. In these field experiments, the CopterSonde has been proven capable of safely operating at wind speeds up to 22 m s−1, flying at 3050 m above mean sea level, and operating in extreme temperatures: nearly −20 ∘C in Finland and 40 ∘C in Oklahoma, United States. Leveraging the open-source ArduPilot autopilot code has allowed for seamless integration of custom functions and protocols for the acquisition, storage, and distribution of atmospheric data alongside the flight control data. This led to the development of features such as the “wind vane mode” algorithm, which commands the CopterSonde to always face into the wind. It also inspired the design of an asymmetric airframe for the CopterSonde, which is shown to provide more suitable locations for weather sensor placement, in addition to allowing for improvements in the overall aerodynamic characteristics of the CopterSonde. Moreover, it has also allowed the team to design and create a modular shell where the sensor package is attached and which can run independently of the CopterSonde's main body. The CopterSonde is on the trend towards becoming a smart UAS tool with a wide possibility of creating new adaptive and optimized atmospheric sampling strategies.
Fiber alignment is the defining architectural characteristic of discontinuous fiber composites and is dictated by shear-dominated processing techniques including flow-injection molding, tape-casting, and mold-casting. However, recent colloidal assembly techniques have started to employ additional forces in fiber suspensions that have the potential to change the energy landscape of the shear-dominated alignment in conditions of flow. In this paper, we develop an energetics model to characterize the shear-alignment of rigid fibers under different flow conditions in the presence of magnetic colloidal alignment forces. We find that these colloidal forces can be sufficient to manipulate the energetic landscape and obtain tunable fiber alignment during flow within even small geometries, such as capillary flow. In most conditions, these colloidal forces work to freeze the fiber orientation during flow and prevent the structure disrupting phenomenon of Jeffrey's orbits that has been accepted to rule fiber suspensions under simple shear flow.
The deployment of small unmanned aircraft systems (UAS) to collect routine in situ vertical profiles of the thermodynamic and kinematic state of the atmosphere in conjunction with other weather observations could significantly improve weather forecasting skill and resolution. High-resolution vertical measurements of pressure, temperature, humidity, wind speed and wind direction are critical to the understanding of atmospheric boundary layer processes integral to air–surface (land, ocean and sea ice) exchanges of energy, momentum, and moisture; how these are affected by climate variability; and how they impact weather forecasts and air quality simulations. We explore the potential value of collecting coordinated atmospheric profiles at fixed surface observing sites at designated times using instrumented UAS. We refer to such a network of autonomous weather UAS designed for atmospheric profiling and capable of operating in most weather conditions as a 3D Mesonet. We outline some of the fundamental and high-impact science questions and sampling needs driving the development of the 3D Mesonet and offer an overview of the general concept of operations. Preliminary measurements from profiling UAS are presented and we discuss how measurements from an operational network could be realized to better characterize the atmospheric boundary layer, improve weather forecasts, and help to identify threats of severe weather.
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