Field responsive mechanical metamaterials.

Typically, mechanical metamaterial properties are programmed and set when the architecture is designed and constructed, and do not change in response to shifting environmental conditions or application requirements. We present a new class of architected materials called field responsive mechanical metamaterials (FRMMs) that exhibit dynamic control and on-the-fly tunability enabled by careful design and selection of both material composition and architecture. To demonstrate the FRMM concept, we print complex structures composed of polymeric tubes infilled with magnetorheological fluid suspensions. Modulating remotely applied magnetic fields results in rapid, reversible, and sizable changes of the effective stiffness of our metamaterial motifs

Nanocone‐Modified Surface Facilitates Gas Bubble Detachment for High‐Rate Alkaline Water Splitting

Abstract: The significant amount of gas bubbles generated during high‐rate alkaline water splitting (AWS) can be detrimental to the process. The accumulation of bubbles will block the active catalytic sites and hinder the ion and electrolyte diffusion, limiting the maximum current density. Furthermore, the detachment of large bubbles can also damage the electrode's surface layer. Here, a general strategy for facilitating bubble detachment is demonstrated by modifying the nickel electrode surface with nickel nanocone nanostructures, which turns the surface into underwater superaerophobic. Simulation and experimental data show that bubbles take a considerably shorter time to detach from the nanocone‐modified nickel foil than the unmodified foil. As a result, these bubbles also have a smaller detachment size and less chance for bubble coalescence. The nanocone‐modified electrodes, including nickel foil, nickel foam, and 3D‐printed nickel lattice, all show substantially reduced overpotentials at 1000 mA cm−2 compared to their pristine counterpart. The electrolyzer assembled with two nanocone‐modified nickel lattice electrodes retains >95% of the performance after testing at ≈900 mA cm−2 for 100 h. The surface NC structure is also well preserved. The findings offer an exciting and simple strategy for enhancing the bubble detachment and, thus, the electrode activity for high‐rate AWS

Planar and Three-Dimensional Printing of Conductive Inks

Printed electronics rely on low-cost, large-area fabrication routes to create flexible or multidimensional electronic, optoelectronic, and biomedical devices1-3. In this paper, we focus on one- (1D), two- (2D), and three-dimensional (3D) printing of conductive metallic inks in the form of flexible, stretchable, and spanning microelectrodes

Train Small, Model Big: Scalable Physics Simulators via Reduced Order Modeling and Domain Decomposition

Numerous cutting-edge scientific technologies originate at the laboratory scale, but transitioning them to practical industry applications is a formidable challenge. Traditional pilot projects at intermediate scales are costly and time-consuming. An alternative, the E-pilot, relies on high-fidelity numerical simulations, but even these simulations can be computationally prohibitive at larger scales. To overcome these limitations, we propose a scalable, physics-constrained reduced order model (ROM) method. ROM identifies critical physics modes from small-scale unit components, projecting governing equations onto these modes to create a reduced model that retains essential physics details. We also employ Discontinuous Galerkin Domain Decomposition (DG-DD) to apply ROM to unit components and interfaces, enabling the construction of large-scale global systems without data at such large scales. This method is demonstrated on the Poisson and Stokes flow equations, showing that it can solve equations about $15 - 40$ times faster with only $\sim$ $1\%$ relative error. Furthermore, ROM takes one order of magnitude less memory than the full order model, enabling larger scale predictions at a given memory limitation.Comment: 40 pages, 12 figures. Submitted to Computer Methods in Applied Mechanics and Engineerin

Optimization of Porosity Distribution in Gas Diffusion Electrodes for CO2 Electrolysis

The criteria dictating the performance of gas diffusion electrodes (GDEs) for CO2 electrolysis are not well understood, due to the complex and highly coupled relationships of the underlying physical and chemical phenomena. In addition, a number of key performance indicators (KPIs) have been identified (e.g., Faradaic efficiency, reaction selectivity, single-pass conversion, and productivity), and optimizing for any single metric often leads to inherent tradeoffs. Consequently, much recent work has focused on understanding how operational and architectural parameters control GDE performance. The porous catalyst supports and diffusion media in these devices are critical components as they mediate the transport and reactive processes. The microstructure of these components influences the balance between the electrochemical surface area, which dictates CO2 consumption, and mass transfer of the aqueous and gaseous species. Traditional porous media is often spatially homogeneous and provides limited opportunity to tailor this balance. In contrast, novel advanced manufacturing methods have now enabled researchers to create electrodes with variable porosity that can be tuned for optimal performance. To explore the impact of locally altering the porous media structure, we leverage previous modeling work by Weng et al. to allow for spatially varying porosity. Further, we couple the forward simulation to adjoint based optimization algorithms to determine optimal porosity distribution in the diffusion media and catalyst layer of a GDE. The cost functions for the optimization are derived from the previously mentioned KPIs. Finally, the performance of the resultant spatially varying porosity GDEs is compared to the performance of homogenous porosity GDEs, and we identify key features of the porosity distribution leading to improved performance. Weng, Lien-Chun, Alexis T. Bell, and Adam Z. Weber. "Modeling gas-diffusion electrodes for CO2 reduction." Physical Chemistry Chemical Physics 20.25 (2018): 16973-16984. This work was performed under the auspices of the U.S. Department of Energy by Lawrence Livermore National Laboratory under Contract DE-AC52-07NA27344. LLNL-ABS-83008

Tuning Material Properties of Alkaline Anion Exchange Membranes Through Crosslinking: A Review of Synthetic Strategies and Property Relationships

Alkaline anion exchange membranes (AAEMs) are an enabling component for next generation electrochemical applications, including alkaline fuel cells, alkaline water electrolyzers, CO2 electrochemical reduction, and flow batteries. While commercial systems, notably fuel cells, have traditionally relied on proton-exchange membranes (PEMs), hydroxide-ion conducting AAEMs hold promise as a way to reduce cost-per-device by enabling the use of less expensive non-platinum group electrodes and cheaper cell components. AAEMs have undergone significant material development over the past two decades resulting in substantial improvements in hydroxide conductivity, alkaline stability, and dimensional stability. Despite these advances, challenges still remain in the areas of durability, water management, high temperature performance, and selectivity. In this review we discuss crosslinking as a synthesis tool for tuning various AAEM material properties, such as water uptake, conductivity, alkaline stability, and selectivity, and we describe synthetic strategies for incorporating crosslinks during membrane fabrication