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We report on a total of 310 samples from marine sediments drilled in the Indian Ocean that were analyzed for glass shard compositions. Samples are mainly from International Ocean Discovery Program Expeditions 353 and 362 but are complemented by samples from Expedition 354; Ocean Drilling Program Legs 183, 121, 120, 119, 116, and 115; and Deep Sea Drilling Project Leg 22. We performed 4327 successful single glass shard analyses with the electron microprobe for major element compositions and conducted 937 successful single analyses with laser ablation-inductively coupled plasma-mass spectrometry (LA-ICP-MS) for trace element compositions on individual glass shards previously measured with the electron microprobe. In total, we were able to measure glass compositions for 254 samples. Of all the samples, 235 can be classified as tephra layers containing pyroclasts as the predominant component in their clast inventory between the 63 and 125 µm grain size fraction, often exceeding 90 vol%. The compositions of the Indian Ocean marine tephras range from basalt to rhyolite and from basaltic trachyandesite to trachyte and fall into the calc-alkaline, K-rich calc-alkaline, and shoshonitic magmatic series. 

The evolutionary sequence for high-mass star formation starts with massive starless clumps that go on to form protostellar, young stellar objects and then compact H ii regions. While there are many examples of the three later stages, the very early stages have proved to be elusive. We follow-up a sample of 110 mid-infrared dark clumps selected from the ATLASGAL catalogue with the IRAM telescope in an effort to identify a robust sample of massive starless clumps. We have used the HCO+ and HNC (1-0) transitions to identify clumps associated with infall motion and the SiO (2-1) transition to identity outflow candidates. We have found blue asymmetric line profile in 65 per cent of the sample, and have measured the infall velocities and mass infall rates (0.6–36 × 10−3 M⊙ yr−1) for 33 of these clumps. We find a trend for the mass infall rate decreasing with an increase of bolometric luminosity to clump mass, i.e. star formation within the clumps evolves. Using the SiO 2-1 line, we have identified good outflow candidates. Combining the infall and outflow tracers reveals that 67 per cent of quiescent clumps are already undergoing gravitational collapse or are associated with star formation; these clumps provide us with our best opportunity to determine the initial conditions and study the earliest stages of massive star formation. Finally, we provide an overview of a systematic high-resolution ALMA study of quiescent clumps selected that allows us to develop a detailed understanding of earliest stages and their subsequent evolution.

 

We propose a nonlinear acoustic metasurface concept by exploiting the nonlinearity of locally resonant unit cells formed by curved beams. The analytical model is established to explore the nonlinear phenomenon, specifically the second-harmonic generation (SHG) of the nonlinear unit cell, and validated through numerical and experimental studies. By tailoring the phase gradient of the unit cells, nonlinear acoustic metasurfaces are developed to demultiplex different frequency components and achieve anomalous wavefront control of SHG in the transmitted region. To this end, we numerically demonstrate wave steering, wave focusing, and self-bending propagation. Our results show that the proposed nonlinear metasurface provides an effective and efficient platform to achieve significant SHG and separate different harmonic components for wavefront control of individual harmonics. Overall, this study offers an outlook to harness nonlinear effects for acoustic wavefront tailoring and develops potential toward advanced technologies to manipulate acoustic waves.

 

Abstract Origami has great potential for creating deployable structures, however, most studies have focused on their static or kinematic features, while the complex and yet important dynamic behaviors of the origami deployment process have remained largely unexplored. In this research, we construct a dynamic model of a Miura origami sheet that captures the combined panel inertial and flexibility effects, which are otherwise ignored in rigid folding kinematic models but are critical in describing the dynamics of origami deployment. Results show that by considering these effects, the dynamic deployment behavior would substantially deviate from a nominal kinematic unfolding path. Additionally, the pattern geometries influence the effective structural stiffness, and it is shown that subtle changes can result in qualitatively different dynamic deployment behaviors. These differences are due to the multistability of the Miura origami sheet, where the structure may snap between its stable equilibria during the transient deployment process. Lastly, we show that varying the deployment rate can affect the dynamic deployment configuration. These observations are original and these phenomena have not and cannot be derived using traditional approaches. The tools and outcomes developed from this research enable a deeper understanding of the physics behind origami deployment that will pave the way for better designs of origami-based deployable structures, as well as extend our fundamental knowledge and expand our comfort zone beyond current practice. 

Mg-Sn and Mg-Zn alloys exhibit a strong age-hardening effect and have become promising bases for high-strength and low-cost Mg alloys. However, the atomic structures and phase stabilities of various precipitates and intermetallic compounds during the heat treatment in these systems remain unclear. Here we use a combined approach of first-principles calculations and cluster expansion (CE) to investigate the atomic structures and thermodynamic stabilities of the experimentally reported precipitates as well as orderings on the FCC and HCP lattices in Mg-Sn and Mg-Zn alloys. From the low energy structures searched by CE, potential Guinier–Preston (GP) zones are identified from preferred HCP orderings. The slow convergence for CE of HCP Mg-Zn, compared with that of Mg-Sn system, is attributed to the long-ranged interactions resulting from the larger lattice mismatch. This study could help design better age-hardened Mg alloys. 

Tensegrity robots, composed of rigid rods and flexible cables, are difficult to accurately model and control given the presence of complex dynamics and high number of DoFs. Differentiable physics engines have been recently proposed as a data-driven approach for model identification of such complex robotic systems. These engines are often executed at a high-frequency to achieve accurate simulation. Ground truth trajectories for training differentiable engines, however, are not typically available at such high frequencies due to limitations of real-world sensors. The present work focuses on this frequency mismatch, which impacts the modeling accuracy. We proposed a recurrent structure for a differentiable physics engine of tensegrity robots, which can be trained effectively even with low-frequency trajectories. To train this new recurrent engine in a robust way, this work introduces relative to prior work: (i) a new implicit integration scheme, (ii) a progressive training pipeline, and (iii) a differentiable collision checker. A model of NASA's icosahedron SUPERballBot on MuJoCo is used as the ground truth system to collect training data. Simulated experiments show that once the recurrent differentiable engine has been trained given the low-frequency trajectories from MuJoCo, it is able to match the behavior of MuJoCo's system. The criterion for success is whether a locomotion strategy learned using the differentiable engine can be transferred back to the ground-truth system and result in a similar motion. Notably, the amount of ground truth data needed to train the differentiable engine, such that the policy is transferable to the ground truth system, is 1% of the data needed to train the policy directly on the ground-truth system. 

Tensegrity robots, which are composed of compressive elements (rods) and flexible tensile elements (e.g., cables), have a variety of advantages, including flexibility, low weight, and resistance to mechanical impact. Nevertheless, the hybrid soft-rigid nature of these robots also complicates the ability to localize and track their state. This work aims to address what has been recognized as a grand challenge in this domain, i.e., the state estimation of tensegrity robots through a markerless, vision-based method, as well as novel, onboard sensors that can measure the length of the robot's cables. In particular, an iterative optimization process is proposed to track the 6-DoF pose of each rigid element of a tensegrity robot from an RGB-D video as well as endcap distance measurements from the cable sensors. To ensure that the pose estimates of rigid elements are physically feasible, i.e., they are not resulting in collisions between rods or with the environment, physical constraints are introduced during the optimization. Real-world experiments are performed with a 3-bar tensegrity robot, which performs locomotion gaits. Given ground truth data from a motion capture system, the proposed method achieves less than 1~cm translation error and 3 degrees rotation error, which significantly outperforms alternatives. At the same time, the approach can provide accurate pose estimation throughout the robot's motion, while motion capture often fails due to occlusions. 

Many engineering applications leverage metamaterials to achieve elastic wave control. To enhance the performance and expand the functionalities of elastic waveguides, the concepts of electronic transport in topological insulators have been applied to elastic metamaterials. Initial studies showed that topologically protected elastic wave transmission in mechanical metamaterials could be realized that is immune to backscattering and undesired localization in the presence of defects or disorder. Recent studies have developed tunable topological elastic metamaterials to maximize performance in the presence of varying external conditions, adapt to changing operating requirements, and enable new functionalities such as a programmable wave path. However, a challenge remains to achieve a tunable topological metamaterial that is comprehensively adaptable in both the frequency and spatial domains and is effective over a broad frequency bandwidth that includes a subwavelength regime. To advance the state of the art, this research presents a piezoelectric metamaterial with the capability to concurrently tailor the frequency, path, and mode shape of topological waves using resonant circuitry. In the research presented in this manuscript, the plane wave expansion method is used to detect a frequency tunable subwavelength Dirac point in the band structure of the periodic unit cell and discover an operating region over which topological wave propagation can exist. Dispersion analyses for a finite strip illuminate how circuit parameters can be utilized to adjust mode shapes corresponding to topological edge states. A further evaluation provides insight into how increased electromechanical coupling and lattice reconfiguration can be exploited to enhance the frequency range for topological wave propagation, increase achievable mode localization, and attain additional edge states. Topological guided wave propagation that is subwavelength in nature and adaptive in path, localization, and frequency is illustrated in numerical simulations of thin plate structures. Outcomes from the presented work indicate that the easily integrable and comprehensively tunable proposed metamaterial could be employed in applications requiring a multitude of functions over a broad frequency bandwidth.