Search for: All records

Structures with specific graded geometries or properties can cause spatial separation and local field enhancement of wave energy. This phenomenon is called rainbow trapping, which manifests itself as stopping the propagation of waves at different locations according to their frequencies. In acoustics, most research on rainbow trapping has focused on wave propagation in one dimension. This research examined the elastic wave trapping performance of a two-dimensional (2D) axisymmetric grooved phononic crystal plate structure. The performance of the proposed structure is validated using numerical simulations based on finite element analysis and experimental measurements using a laser Doppler vibrometer. It is found that rainbow trapping within the frequency range of 165–205 kHz is achieved, where elastic waves are trapped at different radial distances in the plate. The results demonstrate that the proposed design is capable of effectively capturing elastic waves across a broad frequency range of interest. This concept could be useful in applications such as filtering and energy harvesting by concentrating wave energy at different locations in the structure.

 

The generation of acoustic vortex beams has attracted an increasing amount of research attention in recent years, offering a range of functions, including acoustic communication, particle manipulation, and biomedical ultrasound. However, incorporating more vortices and broadening the capacity of these beams and associated devices in three dimensions pose challenges. Traditional methods often necessitate complex transducer arrays and are constrained by conditions such as system complexity and the medium in which they operate. In this paper, a 3D printed acoustic lens capable of generating a double vortex pattern with an optional focusing profile in water was demonstrated. The performance of the proposed lens was evaluated through computational simulations using finite element analysis and experimental tests based on underwater measurements. The results indicate that by altering the positioning of the vortices’ axes, it is possible to control both the intensity and the location of the pressurized zone. The proposed approach shows promise for enhancing the effectiveness and versatility of various applications by generating a larger number of vortices and freely tailoring the focal profile with a single lens, thereby expanding the practical uses of acoustic vortex technology.

 

Abstract Although first principles based anharmonic lattice dynamics is one of the most common methods to obtain phonon properties, such method is impractical for high-throughput search of target thermal materials. We develop an elemental spatial density neural network force field as a bottom-up approach to accurately predict atomic forces of ~80,000 cubic crystals spanning 63 elements. The primary advantage of our indirect machine learning model is the accessibility of phonon transport physics at the same level as first principles, allowing simultaneous prediction of comprehensive phonon properties from a single model. Training on 3182 first principles data and screening 77,091 unexplored structures, we identify 13,461 dynamically stable cubic structures with ultralow lattice thermal conductivity below 1 Wm −1 K −1 , among which 36 structures are validated by first principles calculations. We propose mean square displacement and bonding-antibonding as two low-cost descriptors to ease the demand of expensive first principles calculations for fast screening ultralow thermal conductivity. Our model also quantitatively reveals the correlation between off-diagonal coherence and diagonal populations and identifies the distinct crossover from particle-like to wave-like heat conduction. Our algorithm is promising for accelerating discovery of novel phononic crystals for emerging applications, such as thermoelectrics, superconductivity, and topological phonons for quantum information technology. 

Abstract Existing machine learning potentials for predicting phonon properties of crystals are typically limited on a material-to-material basis, primarily due to the exponential scaling of model complexity with the number of atomic species. We address this bottleneck with the developed Elemental Spatial Density Neural Network Force Field, namely Elemental-SDNNFF. The effectiveness and precision of our Elemental-SDNNFF approach are demonstrated on 11,866 full, half, and quaternary Heusler structures spanning 55 elements in the periodic table by prediction of complete phonon properties. Self-improvement schemes including active learning and data augmentation techniques provide an abundant 9.4 million atomic data for training. Deep insight into predicted ultralow lattice thermal conductivity (<1 Wm −1  K −1 ) of 774 Heusler structures is gained by p–d orbital hybridization analysis. Additionally, a class of two-band charge-2 Weyl points, referred to as “double Weyl points”, are found in 68% and 87% of 1662 half and 1550 quaternary Heuslers, respectively. 

Acoustic resonances in open systems, which are usually associated with resonant modes characterized by complex eigenfrequencies, play a fundamental role in manipulating acoustic wave radiation and propagation. Notably, they are accompanied by considerable field enhancement, boosting interactions between waves and matter, and leading to various exciting applications. In the past two decades, acoustic metamaterials have enabled a high degree of control over tailoring acoustic resonances over a range of frequencies. Here, we provide an overview of recent advances in the area of acoustic resonances in non-Hermitian open systems, including Helmholtz resonators, metamaterials and metasurfaces, and discuss their applications in various acoustic devices, including sound absorbers, acoustic sources, vortex beam generation and imaging. We also discuss bound states in the continuum and their applications in boosting acoustic wave–matter interactions, active phononics and non-Hermitian acoustic resonances, including phononic topological insulators and the acoustic skin effect. 

The advent of acoustic metasurfaces (AMs), which are the two-dimensional equivalents of metamaterials, has opened up new possibilities in wave manipulation using acoustically thin structures. Through the interaction between the acoustic waves and the subwavelength scattering, AMs exhibit versatile capabilities to control acoustic wave propagation such as by steering, focusing, and absorption. In recent years, this vibrant field has expanded to include tunable, reconfigurable, and programmable control to further expand the capacity of AMs. This paper reviews recent developments in AMs and summarizes the fundamental approaches for achieving tunable control, namely, by mechanical tuning, active control, and the use of field-responsive materials. An overview of basic concepts in each category is first presented, followed by a discussion of their applications and details about their performance. The review concludes with the outlook for future directions in this exciting field. 

Metasurfaces exhibiting spatially asymmetric inner structures have been shown to host unidirectional scattering effects, benefiting areas where directional control of waves is desired. In this work, we propose a non-Hermitian planar elastic metasurface to achieve unidirectional focusing of flexural waves. The unit cells are constructed by piezoelectric disks and metallic blocks that are asymmetrically loaded. A tunable material loss is then introduced by negative capacitance shunting. By suitably engineering the induced loss profile, a series of unit cells are designed, which can individually access the exceptional points manifested by unidirectional zero reflection. We then construct a planar metasurface by tuning the reflected phase to ensure constructive interference at one side of the metasurface. Unidirectional focusing of the incident waves is demonstrated, where the reflected wave energy is focused from one direction, and zero reflection is observed in the other direction. The proposed metasurface enriches the flexibility in asymmetric elastic wave manipulation as the loss and the reflected phase can be tailored independently in each unit cell. 

The construction industry has traditionally been a labor-intensive industry. Typically, labor cost takes a significant portion of the total project cost. In spite of the good pay, there was a big gap recently between demand and supply in construction trades position. A survey shows that more than 80% of construction companies in the Midwest of US are facing workforce shortage and suffering in finding enough skilled trades people to hire. This workforce shortage is also nationwide or even worldwide in many places. Construction automation provides a potential solution to mitigate this problem by seeking to replace some of the demanding, repetitive, and/or dangerous construction operations with robotic automation. Currently, robots have been used in bricklaying or heavy-lifting operations in the industry, and other uses remain to be explored. In this paper, the authors proposed a feasibility breakdown structure (FBS)-based robotic system method that can be used to test the feasibility of performing target construction operations with specific robotic systems, including a top-down work breakdown structure and a bottom-up set of feasibility analysis components based on literature search and/or simulation. The proposed method was demonstrated in testing the use of a KUKA robot and a Fetch robot to perform rebar mesh construction. Results showed that the overall workflow is feasible, whereas certain limitations presented in path planning. In addition, a smooth and timely information flow from the Fetch robot sensor and computer vision-based control to the two robots for a coordinated path planning and cooperation is critical for such constructability.