Recent work in structure–processing relationships of polymer semiconductors have demonstrated the versatility and control of thin-film microstructure offered by meniscus-guided coating (MGC) techniques. Here, we analyze the qualitative and quantitative aspects of solution shearing, a model MGC method, using coating blades augmented with arrays of pillars. The pillars induce local regions of high strain rates—both shear and extensional—not otherwise possible with unmodified blades, and we use fluid mechanical simulations to model and study a variety of pillar spacings and densities. We then perform a statistical analysis of 130 simulation variables to find correlations with three dependent variables of interest: thin-film degree of crystallinity and transistor field-effect mobilities for charge-transport parallel (μpara) and perpendicular (μperp) to the coating direction. Our study suggests that simple fluid mechanical models can reproduce substantive correlations between the induced fluid flow and important performance metrics, providing a methodology for optimizing blade design.

When I began writing this article, it was just the beginning of COVID-19, when we were not yet social distancing. Everything has changed since then, but not a conviction I have disseminated for more than 25 years. More than ever, I maintain that formally addressing the critical visual component of research should be part of every researcher's education. How you visually represent your work not only communicates to others in your discipline. Crafting your visual presentations helps clarify your own thinking and, just as important, is a means of engaging the public. In these challenging times, when society is bombarded with complex information, it is more essential than ever to develop a more accessible and honest visual “language” for the public to understand and gather that information. Formal programs in teaching visual communication will help show the world, outside the research community, how to look at science, understand it, question it, and, hopefully, make smart decisions.

The orientation between twin boundary (TB) and loading direction may play an intriguing role in the deformation behaviors of twinned metallic materials. In this aspect, its essential effect on the high-entropy alloy (HEA) nanocrystals is elusive. Attention herein is focused on the atomic-scaled deformation mechanisms and fracture behaviors of HEA nanocrystals containing twins of even smaller spacings via a combined approach of in situ tensile tests inside a high-resolution transmission electron microscope and molecular dynamics simulations. The results indicate that the deformation mechanisms (especially dislocation activities) of HEA nanocrystals depend on the load orientation with respect to TBs. Because of the low activation energy and uneven local composition of HEA, the surface acts as an effective dislocation source and, together with Schmid factor, dominate the activated dislocation slip system. The load orientation-dependent TB-dislocation interactions may transform the type of fracture from semi-brittle to ductile. Our results indicate that the deformation mechanisms and the types of fracture in HEA nanocrystals can be controlled by changing the orientation.

Structural phase transitions in semiconductors have been utilized for driving technological advancements in switchable electronics and phase-change memory devices. There have been numerous reports on high susceptibility of halide perovskites to phase transitions because of their soft lattice; however, the factors affecting the underlying process are still poorly understood. Insights into the phase transition dynamics of halide perovskites are desirable for precise control of optoelectronic properties and for unlocking their use in novel solid-state applications.

Triiodide perovskites CsPbI3, CsSnI3, and FAPbI3 (where FA is formamidinium) are highly promising materials for a range of optoelectronic applications in energy conversion. However, they are thermodynamically unstable at room temperature, preferring to form low-temperature (low-T) non-perovskite phases with one-dimensional anisotropic crystal structures. While such thermodynamic behavior represents a major obstacle toward realizing high-performance devices based on their high-temperature (high-T) perovskite phases, the underlying phase transition dynamics are still not well understood. Here we use in situ optical micro-spectroscopy to quantitatively study the transition from the low-T to high-T phases in individual CsSnI3 and FAPbI3 nanowires. We reveal a large blueshift in the photoluminescence (PL) peak (~38 meV) at the low-T/high-T two-phase interface of partially transitioned FAPbI3 wire, which may result from the lattice distortion at the phase boundary. Compared to the experimentally derived activation energy of CsSnI3 (~1.93 eV), the activation energy of FAPbI3 is relatively small (~0.84 eV), indicating a lower kinetic energy barrier when transitioning from a face-sharing octahedral configuration to a corner-sharing one. Further, the phase propagation rate in CsSnI3 is observed to be relatively high, which may be attributed to a high concentration of Sn vacancies. Our results could not only facilitate a deeper understanding of phase transition dynamics in halide perovskites with anisotropic crystal structures, but also enable controllable manipulation of optoelectronic properties via local phase engineering.

Vibration-based methods can be used effectively to characterize the physical properties of biological materials, with an increasing interest focused on the mechanics of individual, living cells. Real-time measurements of cell properties, such as mass and Young's modulus, can yield important insights into many aspects of cell growth and metabolism as well as the interaction of cells with external stimuli (e.g., drugs). Vibrational test structures designed for the study of such cell properties often use fixed configurations and operational modes, with associated limitations in determining multiple characteristics of the cell, simultaneously. Recent development of mechanics-guided techniques for deterministic assembly of three-dimensional (3D) microstructures provides a route to vibrational frameworks that offer tunable configurations, vibration modes, and resonant frequencies. Here we propose a method that exploits such tunable vibrational structures to simultaneously determine the mass and modulus of a single adherent cell, or of other biological materials or small-scale living systems (e.g., organoids), through theoretical modeling and finite element analysis. The idea involves a 3D architecture that supports two different vibrational structures and can be converted from one to the other through application of strain to an elastomeric substrate. Specifically, tailored designs for serpentine ribbons in these systems enable a decoupling of the dependence of the resonant frequencies of the two structures to the cell mass and modulus, with an associated ability to measure these two properties accurately and independently. These same concepts can be scaled to apply to various types of cells, as well as to organoids (3D clusters of cells) and other biological materials with small geometries, across a range of values of mass and modulus. This method could serve as the foundation for microelectromechanical systems capable of monitoring mass and modulus in real time for use in research in biomechanics and dynamic biological processes.

The inverse elasticity problem of identifying elastic modulus distribution based on measured displacement/strain fields plays a key role in various non-destructive evaluation (NDE) techniques used in geological exploration, quality control, and medical diagnosis (e.g., elastography). Conventional methods in this field are often computationally costly and cannot meet the increasing demand for real-time and high-throughput solutions for advanced manufacturing and clinical practices. Here, we propose a deep learning (DL) approach to address this challenge. By constructing representative sampling spaces of shear modulus distribution and adopting a conditional generative adversarial net, we demonstrate that the DL model can learn high-dimensional mapping between strain and modulus via training over a limited portion of the sampling space. The proposed DL approach bypasses the costly iterative solver in conventional methods and can be rapidly deployed with high accuracy, making it particularly suitable for applications such as real-time elastography and high-throughput NDE techniques.

When I began writing this article, it was just the beginning of COVID-19, when we were not yet social distancing. Everything has changed since then, but not a conviction I have disseminated for more than 25 years. More than ever, I maintain that formally addressing the critical visual component of research should be part of every researcher's education. How you visually represent your work not only communicates to others in your discipline. Crafting your visual presentations helps clarify your own thinking and, just as important, is a means of engaging the public. In these challenging times, when society is bombarded with complex information, it is more essential than ever to develop a more accessible and honest visual “language” for the public to understand and gather that information. Formal programs in teaching visual communication will help show the world, outside the research community, how to look at science, understand it, question it, and, hopefully, make smart decisions.

Development of high energy density solid-state batteries with Li metal anodes has been limited by uncontrollable growth of Li dendrites in liquid and solid electrolytes (SEs). This, in part, may be caused by a dearth of information about mechanical properties of Li, especially at the nano- and microlength scales and microstructures relevant to Li batteries. We investigate Li electrodeposited in a commercial LiCoO2/LiPON/Cu solid-state thin-film cell, grown in situ in a scanning electron microscope equipped with nanomechanical capabilities. Experiments demonstrate that Li was preferentially deposited at the LiPON/Cu interface along the valleys that mimic the domain boundaries of underlying LiCoO2 (cathode). Cryogenic electron microscopy analysis of electrodeposited Li revealed a single-crystalline microstructure, and in situ nanocompression experiments on nano-pillars with 360–759 nm diameters revealed their average Young's modulus to be 6.76 ± 2.88 GPa with an average yield stress of 16.0 ± 6.82 MPa, ~24x higher than what has been reported for bulk polycrystalline Li. We discuss mechanical deformation mechanisms, stiffness, and strength of nano-sized electrodeposited Li in the framework of its microstructure and dislocation-governed nanoscale plasticity of crystals, and place it in the parameter space of existing knowledge on small-scale Li mechanics. The enhanced strength of Li at small scales may explain why it can penetrate and fracture through much stiffer and harder SEs than theoretically predicted.

Lithium-ion batteries have enabled the widespread use of portable electronic devices and are propelling the growing electric vehicle market, but new battery technologies with improved performance are necessary for emerging applications such as electric aircraft. The solid-state battery is one such technology that could exhibit enhanced safety and higher energy density compared to conventional lithium-ion batteries. The use of a pure lithium metal anode within solid-state batteries is key for higher energy density (Figure 1a), and it is thought that using solid-state electrolytes instead of conventional liquids could increase the chemical and structural stability of lithium metal.1 Despite continued progress in the development of new inorganic solid-state electrolyte materials; however, a persistent problem has emerged: lithium metal tends to grow as filaments during charging instead of as a flat film, and these filaments can penetrate and fracture the stiff solid-state electrolyte to short circuit the cell (Figure 1b).2–4 To prevent this chemo-mechanical degradation process and enable filament-free charging, it is critical to understand the mechanical properties of lithium metal, which have been elusive because of the highly reactive nature of lithium.