Table of contents

Miniature robots and actuators with micrometer or millimeter scale size can be driven by diverse power sources, e.g. chemical fuels, light, magnetic, and acoustic fields. These machines have the potential to access complex narrow spaces, execute medical tasks, perform environmental monitoring, and manipulate micro-objects. Recent advancements in 3D printing techniques have demonstrated great benefits in manufacturing small-scale structures such as customized design with programmable physical properties. Combining 3D printing methods, functional polymers, and active control strategies enables these miniature machines with diverse functionalities to broaden their potentials in medical applications. Herein, this review provides an overview of 3D printing techniques applicable for the fabrication of small-scale machines and printable functional materials, including shape-morphing materials, biomaterials, composite polymers, and self-healing polymers. Functions and applications of tiny robots and actuators fabricated by 3D printing and future perspectives toward small-scale intelligent machines are discussed.

Platinum-binding (Pt-binding) peptides have been used for fabrication of complex platinum nanomaterials such as catalysts, metallopharmaceuticals, and electrodes. In this review, we present an understanding of the mechanisms behind Pt-binding peptides and their applications as multifunctional biomaterials. We discuss how the surface recognition, roles of individual amino acids, and arrangement of amino acid sequences interplay. Our summary on the current state of understanding of Pt-binding peptides highlights opportunities for interdisciplinary research which will expand the applicability of these multifunctional peptides.

Graphene quantum dots (GQDs) exhibit abundant magnetic edge states with promising applications in spintronics. Hexagonal zigzag GQDs possess a ground state with an antiferromagnetic (AFM) inter-edge coupling, followed by a metastable state with ferromagnetic (FM) inter-edge coupling. By analyzing the Hubbard model and performing large-scale spin-polarized density functional theory calculations containing thousands of atoms, we predict a series of new mixed magnetic edge states of GQDs arising from the size effect, namely mix-n, where n is the number of spin arrangement parts at each edge, with parallel spin in the same part and anti-parallel spin between adjacent parts. In particular, we demonstrate that the mix-2 state of bare GQDs (C$_{6N^{\,2}}$) appears when $N \geqslant 4$ and the mix-3 state appears when $N \geqslant 6$, where N is the number of six-membered-ring at each edge, while the mix-2 and mix-3 magnetic states appear in the hydrogenated GQDs with N = 13 and N = 15, respectively.

The emerging research field of structural batteries aims to combine the functions of load bearing and energy storage to improve system-level energy storage in battery-powered vehicles and consumer products. Structural batteries, when implemented in electric vehicles, will be exposed to greater temperature fluctuations than conventional batteries in electric vehicles. However, there is a lack of knowledge in public domains and scientific literature regarding how these thermal boundary conditions impact power capabilities of the structural batteries. To fill this gap, the present work simulates the transient temperature-dependent specific power capabilities of a high aspect ratio structural battery composite by solving the one-dimensional heat transfer equation with heat source terms and convective boundary conditions. Equivalent circuit modeling of resistivity-induced losses is used with a second-order finite difference method to examine battery performance. More than 60 different run configurations are evaluated in this work, examining how thermal boundary conditions and internal heat generation influence power capabilities and multifunctional efficiency of the structural battery. The simulated structural battery composite is shown to have good specific Young's modulus (79.5%–80.3% of aluminum), a specific energy of 158 Wh kg⁻¹, and specific power of 41.2–55.2 W kg⁻¹, providing a multifunctional efficiency of 1.15–1.17 depending on configuration and thermal loading conditions and demonstrating the potential of load-bearing structural batteries to achieve mass savings. This work emphasizes the dependency of power efficiency on cell design and external environmental conditions. Insulating material is shown to improve multifunctional efficiency, particularly for low ambient temperatures. It is demonstrated that as cell temperature increases due to high ambient temperature or heat generation in the battery, the specific power efficiency increases exponentially due to a favorable nonlinear relation between ionic conductivity and cell temperature. The simulations also demonstrate a thermal feedback loop where resistivity-induced power losses can lead to self-regulation of cell temperature. This effect reduces run-averaged losses, particularly at low ambient temperatures.

This paper presents an analytic model of one dimensional magnetostriction. We show how specific assumptions regarding the symmetry of key micromagnetic energies (magnetocrystalline, magnetoelastic, and Zeeman) reduce a general three-dimensional statistical mechanics model to a one-dimensional form with an exact solution. We additionally provide a useful form of the analytic equations to help ensure numerical accuracy. Numerical results show that the model maintains accuracy over a large range of applied magnetic fields and stress conditions extending well outside those produced in standard laboratory conditions. A comparison to experimental data is performed for several magnetostrictive materials. The model is shown to accurately predict the behavior of Terfenol-D, while two compositions of Galfenol are modeled with varying accuracy. To conclude we discuss what conditions facilitate the description of materials with cubic crystalline anisotropy as transversely isotropic, to achieve peak model performance.

The goal of this research is to establish a highly compact on-demand release platform for functional materials where porous nanofibers serve as the host, heat-based release trigger and temperature controller for regulated release. The ability to store functional materials in fibers and release them on demand via external signals may open up new frontiers in areas such as smart textiles and autonomous composites. The host material was porous carbon nanofibers (CNFs), which encapsulated functional materials, protected by a thin polymeric coating to thermally regulate the release. This platform was used to store Gentian violet (GV), an antibacterial material, and release it with highly controllable rates in aqueous environment. The high porosity of the CNF yarns, both inter- and intra-fiber porosity, resulted in a mass loading of as high as ∼50 wt%. The active release was triggered via passing electrical signals through CNF yarn backbone, thereby heating the coating. The rate of release as a function of temperature was measured. It was concluded that the release mechanism is via thermally augmented and reversible diffusion rates of GV and water through the coating. By applying electric current, the diffusion coefficient of the coating was increased, and the release rate dramatically increased in a reversible fashion by as much as 39×.