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Human–machine interfaces (HMI) are currently a trendy and rapidly expanding area of research. Interestingly, the human user does not readily observe the interface between humans and machines. Instead, interactions between the machine and electrical signals from the user's body are obscured by complex control algorithms. The result is effectively a one-way street, wherein data is only transmitted from human to machine. Thus, a gap remains in the literature: how can information be effectively conveyed to the user to enable mutual understanding between humans and machines? Here, this paper reviews recent advancements in biosignal-integrated wearable robotics, with a particular emphasis on “visualization”—the presentation of relevant data, statistics, and visual feedback to the user. This review article covers various signals of interest, such as electroencephalograms and electromyograms, and explores novel sensor architectures and key materials. Recent developments in wearable robotics are examined from control and mechanical design perspectives. Additionally, we discuss current visualization methods and outline the field's future direction. While much of the HMI field focuses on biomedical and healthcare applications, such as rehabilitation of spinal cord injury and stroke patients, this paper also covers less common applications in manufacturing, defense, and other domains. 

Nanocrystalline silicon can have unique thermal transport and mechanical properties governed by its constituent grain microstructure. Here, we use phonon ray-tracing and molecular dynamics simulations to demonstrate the largely tunable thermomechanical behaviors with varying grain sizes (a0) and aspect ratios (ξ). Our work shows that, by selectively increasing the grain size along the heat transfer direction while keeping the grain area constant, the in-plane lattice thermal conductivity (kx) increases more significantly than the cross-plane lattice thermal conductivity (ky) due to anisotropic phonon–grain boundary scattering. While kx generally increases with increasing ξ, a critical value exists for ξ at which kx reaches its maximum. Beyond this transition point, further increases in ξ result in a decrease in kx due to substantial scattering of low-frequency phonons with anisotropic grain boundaries. Moreover, we observe reductions in the elastic and shear modulus with decreasing grain size, and this lattice softening leads to significant reductions in phonon group velocity and thermal conductivity. By considering both thermal and mechanical size effects, we identify two distinct regimes of thermal transport, in which anisotropic phonon–grain boundary scattering becomes more appreciable at low temperatures and lattice softening becomes more pronounced at high temperatures. Through phonon spectral analysis, we attribute the significant thermal conductivity anisotropy in nanograined silicon to grain boundary scattering of low-frequency phonons and the softening-driven thermal conductivity reduction to Umklapp scattering of high-frequency phonons. These findings offer insights into the manipulation of thermomechanical properties of nanocrystalline silicon via microstructure engineering, carrying profound implications for the development of future nanomaterials. 

Abstract Heterogeneous and complex electronic packages may require unique thermomechanical structures to provide optimal heat guiding. In particular, when a heat source and a heat sink are not aligned and do not allow a direct path, conventional thermal management methods providing uniform heat dissipation may not be appropriate. Here we present a topology optimization method to find thermally conductive and mechanically stable structures for optimal heat guiding under various heat source-sink arrangements. To exploit the capabilities, we consider complex heat guiding scenarios and three-dimensional (3D) serpentine structures to carry the heat with corner angles ranging from 30 deg to 90 deg. While the thermal objective function is defined to minimize the temperature gradient, the mechanical objective function is defined to maximize the stiffness with a volume constraint. Our simulations show that the optimized structures can have a thermal resistance of less than 32% and stiffness greater than 43% compared to reference structures with no topology optimization at an identical volume fraction. The significant difference in thermal resistance is attributed to a thermally dead volume near the sharp corners. As a proof-of-concept experiment, we have created 3D heat guiding structures using a selective laser melting technique and characterized their thermal properties using an infrared thermography technique. The experiment shows the thermal resistance of the thermally optimized structure is 29% less than that of the reference structure. These results present the unique capabilities of topology optimization and 3D manufacturing in enabling optimal heat guiding for heterogeneous systems and advancing the state-of-the-art in electronics packaging. 

Abstract This study uncovers a correlation between the mid-infrared emissivity of butterfly wings and the average air temperature of their habitats across the world. Butterflies from cooler climates have a lower mid-infrared emissivity, which limits heat losses to surroundings, and butterflies from warmer climates have a higher mid-infrared emissivity, which enhances radiative cooling. The mid-infrared emissivity showed no correlation with other investigated climatic factors. Phylogenetic independent contrasts analysis indicates the microstructures of butterfly wings may have evolved in part to regulate mid-infrared emissivity as an adaptation to climate, rather than as phylogenetic inertia. Our findings offer new insights into the role of microstructures in thermoregulation and suggest both evolutionary and physical constraints to butterflies’ abilities to adapt to climate change. 

Shape memory polymers are gaining significant interest as one of the major constituent materials for the emerging field of 4D printing. While 3D-printed metamaterials with shape memory polymers show unique thermomechanical behaviors, their thermal transport properties have received relatively little attention. Here, we show that thermal transport in 3D-printed shape memory polymers strongly depends on the shape, solid volume fraction, and temperature and that thermal radiation plays a critical role. Our infrared thermography measurements reveal thermal transport mechanisms of shape memory polymers in varying shapes from bulk to octet-truss and Kelvin-foam microlattices with volume fractions of 4%–7% and over a temperature range of 30–130 °C. The thermal conductivity of bulk shape memory polymers increases from 0.24 to 0.31 W m−1 K−1 around the glass transition temperature, in which the primary mechanism is the phase-dependent change in thermal conduction. On the contrary, thermal radiation dominates heat transfer in microlattices and its contribution to the Kelvin-foam structure ranges from 68% to 83% and to the octet-truss structure ranges from 59% to 76% over the same temperature range. We attribute this significant role of thermal radiation to the unique combination of a high infrared emissivity and a high surface-to-volume ratio in the shape memory polymer microlattices. Our work also presents an effective medium approach to explain the experimental results and model thermal transport properties with varying shapes, volume fractions, and temperatures. These findings provide new insights into understanding thermal transport mechanisms in 4D-printed shape memory polymers and exploring the design space of thermomechanical metamaterials.