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Abstract Recent advances in 3D printing have enabled the manufacture of porous electrodes which cannot be machined using traditional methods. With micron-scale precision, the pore structure of an electrode can now be designed for optimal energy efficiency, and a 3D printed electrode is not limited to a single uniform porosity. As these electrodes scale in size, however, the total number of possible pore designs can be intractable; choosing an appropriate pore distribution manually can be a complex task. To address this challenge, we adopt an inverse design approach. Using physics-based models, the electrode structure is optimized to minimize power losses in a flow reactor. The computer-generated structure is then printed and benchmarked against homogeneous porosity electrodes. We show how an optimized electrode decreases the power requirements by 16% compared to the best-case homogeneous porosity. Future work could apply this approach to flow batteries, electrolyzers, and fuel cells to accelerate their design and implementation.

Abstract Lattices remain an attractive class of structures due to their design versatility; however, rapidly designing lattice structures with tailored or optimal mechanical properties remains a significant challenge. With each added design variable, the design space quickly becomes intractable. To address this challenge, research efforts have sought to combine computational approaches with machine learning (ML)-based approaches to reduce the computational cost of the design process and accelerate mechanical design. While these efforts have made substantial progress, significant challenges remain in (1) building and interpreting the ML-based surrogate models and (2) iteratively and efficiently curating training datasets for optimization tasks. Here, we address the first challenge by combining ML-based surrogate modeling and Shapley additive explanation (SHAP) analysis to interpret the impact of each design variable. We find that our ML-based surrogate models achieve excellent prediction capabilities (R 2 > 0.95) and SHAP values aid in uncovering design variables influencing performance. We address the second challenge by utilizing active learning-based methods, such as Bayesian optimization, to explore the design space and report a 5 × reduction in simulations relative to grid-based search. Collectively, these results underscore the value of building intelligent design systems that leverage ML-based methods for uncovering key design variables and accelerating design.

The relationship between structure and performance in alkaline Zn batteries is undeniable, where anode utilization, dendrite formation, shape change, and passivation issues are all addressable through anode morphology. While tailoring 3D hosts can improve the electrode performance, these practices are inherently limited by scaffolds that increase the mass or volume. Herein, a direct write strategy for producing template‐free metallic 3D Zn electrode architectures is discussed. Concentrated inks are customized to build designs with low electrical resistivity (5 × 10−4 Ω cm), submillimeter sizes (200 μm filaments), and high mechanical stability (Young's modulus of 0.1–0.5 GPa at relative densities of 0.28–0.46). A printed Zn lattice anode versus NiOOH cathode with an alkaline polymer gel electrolyte is then demonstrated. This Zn||NiOOH cell operates for over 650 cycles at high rates of 25 mA cm−2 with an average areal capacity of 11.89 mAh cm−2, a cumulative capacity of 7.8 Ah cm−2, and a volumetric capacity of 23.78 mAh cm−3. A thicker Zn anode achieves an ultrahigh areal capacity of 85.45 mAh cm−2 and a volumetric capacity of 81.45 mAh cm−3 without significant microstructural changes after 50 cycles.

Alkaline anion exchange membranes (AAEMs) are an enabling component for next-generation electrochemical devices, including alkaline fuel cells, water and CO2 electrolyzers, and flow batteries. While commercial systems, notably fuel cells, have traditionally relied on proton-exchange membranes, hydroxide-ion conducting AAEMs hold promise as a method to reduce cost-per-device by enabling the use of non-platinum group electrodes and cell components. AAEMs have undergone significant material development over the past two decades; however, challenges remain in the areas of durability, water management, high temperature performance, and selectivity. In this review, we survey crosslinking as a tool capable of tuning AAEM properties. While crosslinking implementations vary, they generally result in reduced water uptake and increased transport selectivity and alkaline stability. We survey synthetic methodologies for incorporating crosslinks during AAEM fabrication and highlight necessary precautions for each approach.

In comparison with conventional methods, electrochemical CO2 reduction (CO2RR) represents a promising and environmentally friendly method to generate value‐added products and mitigate anthropogenic climate change. Herein, the recently reported CO2RR catalysts that show high selectivity and activity toward alcohol production are highlighted. The current understanding of reaction pathways on different catalyst surfaces for alcohol production is highlighted and strategies to enhance CO2RR catalytic performance are discussed. Finally, the views on the challenges and possible future paths for the field are shared.

Porous ceramic materials have a wide range of potential applications for which controlling the structure across multiple length scales is desirable. Additive manufacturing (AM) of porous ceramics is therefore of interest for design flexibility. Here, a ceramic ink compatible with 2 AM techniques, projection microstereolithography (PμSL) and direct ink write (DIW), was formulated and demonstrated printed parts with a range of controllable feature sizes as well as nanoporosity resulting from partial sintering. A diacrylate polymer was mixed with 3% yttria partially stabilized zirconia (3YZ) ceramic nanoparticles having different sizes and solids loadings to find formulations that meet the printing requirements of both AM techniques. Detailed rheological studies were used to determine optimal ink formulations to use for either printing method. The resulting 3YZ structures printed with DIW and PμSL have engineered macro cavities with span lengths greater than several millimeters, wall thicknesses of 200 to 540 μm, and porosity within the wall structure on the order of 100 nm. This study revealed that through facile composition changes to the 3YZ ink, it was feasible to use the same ink base for multiple AM techniques without the need for separate cumbersome ink development processes.

Recent advances in additive manufacturing, specifically direct ink writing (DIW) and ink-jetting, have enabled the production of elastomeric silicone parts with deterministic control over the structure, shape, and mechanical properties. These new technologies offer rapid prototyping advantages and find applications in various fields, including biomedical devices, prosthetics, metamaterials, and soft robotics. Stereolithography (SLA) is a complementary approach with the ability to print with finer features and potentially higher throughput. However, all high-performance silicone elastomers are composites of polysiloxane networks reinforced with particulate filler, and consequently, silicone resins tend to have high viscosities (gel- or paste-like), which complicates or completely inhibits the layer-by-layer recoating process central to most SLA technologies. Herein, the design and build of a digital light projection SLA printer suitable for handling high-viscosity resins is demonstrated. Further, a series of UV-curable silicone resins with thiol-ene crosslinking and reinforced by a combination of fumed silica and MQ resins are also described. The resulting silicone elastomers are shown to have tunable mechanical properties, with 100–350% elongation and ultimate tensile strength from 1 to 2.5 MPa. Three-dimensional printed features of 0.4 mm were achieved, and complexity is demonstrated by octet-truss lattices that display negative stiffness.

Abstract Direct ink writing enables the layer-by-layer manufacture of ordered, porous structures whose mechanical behavior is driven by architecture and material properties. Here, we incorporate two different gas filled microsphere pore formers to evaluate the effect of shell stiffness and Tg on compressive behavior and compression set in siloxane matrix printed structures. The lower Tg microsphere structures exhibit substantial compression set when heated near and above Tg, with full structural recovery upon reheating without constraint. By contrast, the higher Tg microsphere structures exhibit reduced compression set with no recovery upon reheating. Aside from their role in tuning the mechanical behavior of direct ink write structures, polymer microspheres are good candidates for shape memory elastomers requiring structural complexity, with potential applications toward tandem shape memory polymers.

Abstract Multiphysics modeling enables probing of conditions inside a CO2 electrolyzer that are difficult to measure, such as local concentrations and pH, as well as rapid testing of possible design changes. A one‐dimensional model for a zero‐gap membrane electrode assembly (MEA) CO2 electrolyzer was developed with the assumption that catalyst layers interact with the membrane ionomer such that the ionomer affects the underlying kinetics. The kinetics for bicarbonate reacting to form hydrogen are fit using a planar electrode model for silver with an ionomer coating. The MEA model results are validated against experimental studies for current density and product selectivity. Flooding of the cathode is modeled using saturation curves, and results show that blocked pores in the microporous layer play a significant role in limiting the mass transport at high potentials (>2.8 V). Sensitivity studies showed that CO Faradaic efficiency can be increased by decreasing catalyst layer thickness and porosity, and decreasing KHCO3 concentration.

Abstract Invited for this issue's Front Cover are researchers from the Carbon Initiative at Lawrence Livermore National Laboratory and the SUNCAT Center at Stanford University. The front cover shows a cross‐section of the cathode of a membrane electrode assembly for CO2 electrolysis looking down the feed channel. CO2 molecules flow down the channel and diffuse up through the gas diffusion layer to the silver catalyst, where CO2 reacts to form CO, while also competing against hydrogen reduction from water. Some of the CO2 molecules react to form bicarbonate and carbonate ions, which can diffuse across the membrane, where they react at the anode to form CO2 again. The top of the image shows CO2 that has crossed over through the membrane into the anolyte. Cover design by Brendan Thompson. Read the full text of the Research Article at 10.1002/celc.202300566.