Ambient Humidity-Induced Phase Separation for Fiber Morphology Engineering toward Piezoelectric Self-Powered Sensing.

Electrospun polymeric piezoelectric fibers have a considerable potential for shape-adaptive mechanical energy harvesting and self-powered sensing in biomedical, wearable, and industrial applications. However, their unsatisfactory piezoelectric performance remains an issue to be overcome. While strategies for increasing the crystallinity of electroactive ß phases have thus far been the major focus in realizing enhanced piezoelectric performance, tailoring the fiber morphology can also be a promising alternative. Herein, a design strategy that combines the nonsolvent-induced phase separation of a polymer/solvent/water ternary system and electrospinning for fabricating piezoelectric poly(vinylidene fluoride-trifluoroethylene) (P(VDF-TrFE) fibers with surface porosity under ambient humidity is presented. Notably, electrospun P(VDF-TrFE) fibers with higher surface porosity outperform their smooth-surfaced counterparts with a higher ß phase content in terms of output voltage and power generation. Theoretical and numerical studies also underpin the contribution of the structural porosity to the harvesting performance, which is attributable to local stress concentration and reduced dielectric constant due to the air in the pores. This porous fiber design can broaden the application prospects of shape-adaptive energy harvesting and self-powered sensing based on piezoelectric polymer fibers with enhanced voltage and power performance, as successfully demonstrated in this work by developing a communication system based on self-powered motion sensing.

Stress-Induced Structural Transformations in Au Nanocrystals.

Nanocrystals can exist in multiply twinned structures like icosahedron or single crystalline structures like cuboctahedron. Transformations between these structures can proceed through diffusion or displacive motion. Experimental studies on nanocrystal structural transformations have focused on high-temperature diffusion-mediated processes. Limited experimental evidence of displacive motion exists. We report structural transformation of 6 nm Au nanocrystals under nonhydrostatic pressure of 7.7 GPa in a diamond anvil cell that is driven by displacive motion. X-ray diffraction and transmission electron microscopy were used to detect the structural transformation from multiply twinned to single crystalline. Single crystalline nanocrystals were recovered after unloading, then quickly reverted to the multiply twinned state after dispersion in toluene. The dynamics of recovery was captured using TEM which showed surface recrystallization and rapid twin boundary motion. Molecular dynamics simulations showed that twin boundaries are unstable due to defects nucleated from the interior of the nanocrystal.

Nucleation of Dislocations in 3.9 nm Nanocrystals at High Pressure.

As circuitry approaches single nanometer length scales, it has become important to predict the stability of single nanometer-sized metals. The behavior of metals at larger scales can be predicted based on the behavior of dislocations, but it is unclear if dislocations can form and be sustained at single nanometer dimensions. Here, we report the formation of dislocations within individual 3.9 nm Au nanocrystals under nonhydrostatic pressure in a diamond anvil cell. We used a combination of x-ray diffraction, optical absorbance spectroscopy, and molecular dynamics simulation to characterize the defects that are formed, which were found to be surface-nucleated partial dislocations. These results indicate that dislocations are still active at single nanometer length scales and can lead to permanent plasticity.

Mechanical metamaterials as broadband electromagnetic wave absorbers: investigating relationships between geometrical parameters and electromagnetic response.

The utilization of low-density and robust mechanical metamaterials rises as a promising solution for multifunctional electromagnetic wave absorbers due to their structured porous structures, which facilitates impedance matching and structural absorption. However, the various geometrical parameters involved in constructing these metamaterials affect their electromagnetic response, necessitating a comprehensive understanding of underlying absorbing mechanisms. Through experimentally validated numerical analysis, this study delves into the influence of geometrical factors on the electromagnetic response of representative low-density, high strength mechanical metamaterials, namely octet-truss and octet-foam. By juxtaposing electromagnetic response under varying volume fractions, cell lengths, and multilayer configurations of octet-truss and octet-foam, distinct absorption mechanisms emerge as geometrical parameters evolve. These mechanisms encompass diminished reflection owing to porous structures, effective medium approximations within subwavelength limits, and transmission-driven or reflection-driven phenomena originating from the interplay of open- and closed-cell structures. Through analyses on these mechanical metamaterials, we demonstrate the viability of employing them as tunable yet scalable structures that are lightweight, robust, and broadband electromagnetic wave absorption.

Deep Learning Accelerated Design of Mechanically Efficient Architected Materials.

Lattice structures are known to have high performance-to-weight ratios because of their highly efficient material distribution in a given volume. However, their inherently large void fraction leads to low mechanical properties compared to the base material, high anisotropy, and brittleness. Most works to date have focused on modifying the spatial arrangement of beam elements to overcome these limitations, but only simple beam geometries are adopted due to the infinitely large design space associated with probing and varying beam shapes. Herein, we present an approach to enhance the elastic modulus, strength, and toughness of lattice structures with minimal tradeoffs by optimizing the shape of beam elements for a suite of lattice structures. A generative deep learning-based approach is employed, which leverages the fast inference of neural networks to accelerate the optimization process. Our optimized lattice structures possess superior stiffness (+59%), strength (+49%), toughness (+106%), and isotropy (+645%) compared to benchmark lattices consisting of cylindrical beams. We fabricate our lattice designs using additive manufacturing to validate the optimization approach; experimental and simulation results show good agreement. Remarkable improvement in mechanical properties is shown to be the effect of distributed stress fields and deformation modes subject to beam shape and lattice type.

Generative machine learning algorithm for lattice structures with superior mechanical properties.

Lattice structures are typically made up of a crisscross pattern of beam elements, allowing engineers to distribute material in a more structurally effective way. However, a main challenge in the design of lattice structures is a trade-off between the density and mechanical properties. Current studies have often assumed the cross-sectional area of the beam elements to be uniform for reducing the design complexity. This simplified approach limits the possibility of finding superior designs with optimized weight-to-performance ratios. Here, the optimized shape of the beam elements is investigated using a deep learning approach with high-order Bézier curves to explore the augmented design space. This is then combined with a hybrid neural network and genetic optimization (NN-GO) adaptive method for the generation of superior lattice structures. In our optimized design, the distribution of material is smartly shifted more towards the joint region, the weakest location of lattice structures, to achieve the highest modulus and strength. This design strikes to balance between two modes of deformation: axial and bending. Thus, the optimized design is efficient for load bearing and energy absorption. To validate our simulations, the optimized design is then fabricated by additive manufacturing and its mechanical properties are evaluated through compression testing. A good correlation between experiments and simulations is observed and the optimized design has outperformed benchmark ones in terms of modulus and strength. We show that the extra design flexibility from high-order Bézier curves allows for a smoother transition between the beam elements which reduces the overall stress concentration profile.

Extreme-Pressure Imprint Lithography for Heat and Ultraviolet-Free Direct Patterning of Rigid Nanoscale Features.

Nanoimprint lithography (NIL) is typically performed by filling up of molds by heated polymers or UV-curable liquid resists, inevitably requiring subsequent pattern-transfer processes. Although direct NIL techniques have been suggested alternatively, they usually require precursors or ink-type resists containing undesired organic components. Here, we demonstrate extreme-pressure imprint lithography (EPIL) that effectively produces well-defined multiscale structures with a wide range from 10 nm to 10 mm on diverse surfaces even including pure or alloy metals without using any precursors, heating, UV exposure, or pattern transfer. In particular, EPIL is accomplished through precise control of room-temperature plastic deformation in nanoscale volumes, which is elucidated by finite element analyses and molecular dynamics simulations. In addition to scalability to macroscopic areas, we confirm the outstanding versatility of EPIL via its successful applications to Ni, Cu, steel, and organics. We expect that the state-of-the-art EPIL process combined with other emerging nanopatterning technologies will be extendable to the future large-area nanofabrication of various devices.

Author Correction: A micromechanics-based analytical solution for the effective thermal conductivity of composites with orthotropic matrices and interfacial thermal resistance.

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A micromechanics-based analytical solution for the effective thermal conductivity of composites with orthotropic matrices and interfacial thermal resistance.

We obtained an analytical solution for the effective thermal conductivity of composites composed of orthotropic matrices and spherical inhomogeneities with interfacial thermal resistance using a micromechanics-based homogenization. We derived the closed form of a modified Eshelby tensor as a function of the interfacial thermal resistance. We then predicted the heat flux of a single inhomogeneity in the infinite media based on the modified Eshelby tensor, which was validated against the numerical results obtained from the finite element analysis. Based on the modified Eshelby tensor and the localization tensor accounting for the interfacial resistance, we derived an analytical expression for the effective thermal conductivity tensor for the composites by a mean-field approach called the Mori-Tanaka method. Our analytical prediction matched very well with the effective thermal conductivity obtained from finite element analysis with up to 10% inhomogeneity volume fraction.

Ubiquitous Graphene Electronics on Scotch Tape.

We report a novel concept of graphene transistors on Scotch tape for use in ubiquitous electronic systems. Unlike common plastic substrates such as polyimide and polyethylene terephthalate, the Scotch tape substrate is easily attached onto various objects such as banknotes, curved surfaces, and human skin, which implies potential applications wherein electronics can be placed in any desired position. Furthermore, the soft Scotch tape serves as an attractive substrate for flexible/foldable electronics that can be significantly bent, or even crumpled. We found that the adhesive layer of the tape with a relatively low shear modulus relaxes the strain when subjected to bending. The capacitance of the gate dielectric made of oxidized aluminum oxide was 1.5 µF cm(-2), so that a supply voltage of only 2.5 V was sufficient to operate the devices. As-fabricated graphene transistors on Scotch tape exhibited high electron mobility of 1326 (±155) cm(2) V(-1) s(-1); the transistors still showed high mobility of 1254 (±478) cm(2) V(-1) s(-1) even after they were crumpled.