Accelerating the design of lattice structures using machine learning.

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 (R2 > 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.

Toward Multiscale, Multimaterial 3D Printing.

Biological materials and organisms possess the fundamental ability to self-organize, through which different components are assembled from the molecular level up to hierarchical structures with superior mechanical properties and multifunctionalities. These complex composites inspire material scientists to design new engineered materials by integrating multiple ingredients and structures over a wide range. Additive manufacturing, also known as 3D printing, has advantages with respect to fabricating multiscale and multi-material structures. The need for multifunctional materials is driving 3D printing techniques toward arbitrary 3D architectures with the next level of complexity. In this paper, the aim is to highlight key features of those 3D printing techniques that can produce either multiscale or multimaterial structures, including innovations in printing methods, materials processing approaches, and hardware improvements. Several issues and challenges related to current methods are discussed. Ultimately, the authors also provide their perspective on how to realize the combination of multiscale and multimaterial capabilities in 3D printing processes and future directions based on emerging research.

Tuning 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 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.

Designing a Zn-Ag Catalyst Matrix and Electrolyzer System for CO2 Conversion to CO and Beyond.

CO2 emissions can be transformed into high-added-value commodities through CO2 electrocatalysis; however, efficient low-cost electrocatalysts are needed for global scale-up. Inspired by other emerging technologies, the authors report the development of a gas diffusion electrode containing highly dispersed Ag sites in a low-cost Zn matrix. This catalyst shows unprecedented Ag mass activity for CO production: -614 mA cm-2 at 0.17 mg of Ag. Subsequent electrolyte engineering demonstrates that halide anions can further improve stability and activity of the Zn-Ag catalyst, outperforming pure Ag and Au. Membrane electrode assemblies are constructed and coupled to a microbial process that converts the CO to acetate and ethanol. Combined, these concepts present pathways to design catalysts and systems for CO2 conversion toward sought-after products.

Performance of three-dimensional printed nasopharyngeal swabs for COVID-19 testing.

ABSTRACT: At the start of the COVID-19 pandemic, the US faced nationwide shortages of nasopharyngeal swabs due to both overwhelmed supply chains and an increase in demand. To address this shortfall, multiple 3D printed swabs were ultimately produced and sold for COVID-19 testing. In this work, we present a framework for mechanical and functional bench-testing of nasopharyngeal swabs using standard and widely available material testing equipment. Using this framework, we offer a comprehensive, quantitative comparison of the 3D printed swabs to benchmark their performance against traditional flocked swabs. The test protocols were designed to emulate the clinical use of the nasopharyngeal swabs and to evaluate potential failure modes. Overall, the 3D printed swabs performed comparably to, or outperformed, the traditional swabs in all mechanical tests. While traditional swabs outperformed some of the new 3D printed swabs in terms of sample uptake and retention, similar amounts of RNA were recovered from both 3D printed and traditional swabs.

Chemical Modifications of Ag Catalyst Surfaces with Imidazolium Ionomers Modulate H2 Evolution Rates during Electrochemical CO2 Reduction.

Bridging polymer design with catalyst surface science is a promising direction for tuning and optimizing electrochemical reactors that could impact long-term goals in energy and sustainability. Particularly, the interaction between inorganic catalyst surfaces and organic-based ionomers provides an avenue to both steer reaction selectivity and promote activity. Here, we studied the role of imidazolium-based ionomers for electrocatalytic CO2 reduction to CO (CO2R) on Ag surfaces and found that they produce no effect on CO2R activity yet strongly promote the competing hydrogen evolution reaction (HER). By examining the dependence of HER and CO2R rates on concentrations of CO2 and HCO3-, we developed a kinetic model that attributes HER promotion to intrinsic promotion of HCO3- reduction by imidazolium ionomers. We also show that varying the ionomer structure by changing substituents on the imidazolium ring modulates the HER promotion. This ionomer-structure dependence was analyzed via Taft steric parameters and density functional theory calculations, which suggest that steric bulk from functionalities on the imidazolium ring reduces access of the ionomer to both HCO3- and the Ag surface, thus limiting the promotional effect. Our results help develop design rules for ionomer-catalyst interactions in CO2R and motivate further work into precisely uncovering the interplay between primary and secondary coordination in determining electrocatalytic behavior.

Inertially enhanced mass transport using 3D-printed porous flow-through electrodes with periodic lattice structures.

Electrochemical reactors utilizing flow-through electrodes (FTEs) provide an attractive path toward the efficient utilization of electrical energy, but their commercial viability and ultimate adoption hinge on attaining high currents to drive productivity and cost competitiveness. Conventional FTEs composed of random, porous media provide limited opportunity for architectural control and engineering of microscale transport. Alternatively, the design freedom engendered by additively manufacturing FTEs yields additional opportunities to further drive performance via flow engineering. Through experiment and validated continuum computation we analyze the mass transfer in three-dimensional (3D)-printed porous FTEs with periodic lattice structures and show that, in contrast to conventional electrodes, the mesoscopic length scales in 3D-printed electrodes lead to an increase in the mass correlation exponent as inertial flow effects dominate. The inertially enhanced mass transport yields mass transfer coefficients that exceed previously reported 3D-printed FTEs by 10 to 100 times, bringing 3D-printed FTE performance on par with conventional materials.

Cellular fluidics.

The natural world provides many examples of multiphase transport and reaction processes that have been optimized by evolution. These phenomena take place at multiple length and time scales and typically include gas-liquid-solid interfaces and capillary phenomena in porous media1,2. Many biological and living systems have evolved to optimize fluidic transport. However, living things are exceptionally complex and very difficult to replicate3-5, and human-made microfluidic devices (which are typically planar and enclosed) are highly limited for multiphase process engineering6-8. Here we introduce the concept of cellular fluidics: a platform of unit-cell-based, three-dimensional structures-enabled by emerging 3D printing methods9,10-for the deterministic control of multiphase flow, transport and reaction processes. We show that flow in these structures can be 'programmed' through architected design of cell type, size and relative density. We demonstrate gas-liquid transport processes such as transpiration and absorption, using evaporative cooling and CO2 capture as examples. We design and demonstrate preferential liquid and gas transport pathways in three-dimensional cellular fluidic devices with capillary-driven and actively pumped liquid flow, and present examples of selective metallization of pre-programmed patterns. Our results show that the design and fabrication of architected cellular materials, coupled with analytical and numerical predictions of steady-state and dynamic behaviour of multiphase interfaces, provide deterministic control of fluidic transport in three dimensions. Cellular fluidics may transform the design space for spatial and temporal control of multiphase transport and reaction processes.

3D Printing of High Viscosity Reinforced Silicone Elastomers.

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.

3D Printed Nickel-Molybdenum-Based Electrocatalysts for Hydrogen Evolution at Low Overpotentials in a Flow-Through Configuration.

Three-dimensional (3D) printed, hierarchically porous nickel molybdenum (NiMo) electrocatalysts were synthesized and evaluated in a flow-through configuration for the hydrogen evolution reaction (HER) in 1.0 M KOH(aq) in a simple electrochemical H-cell. 3D NiMo electrodes possess hierarchically porous structures because of the resol-based aerogel precursor, which generates superporous carbon aerogel as a catalyst support. Relative to a traditional planar electrode configuration, the flow-through configuration allowed efficient removal of the hydrogen bubbles from the catalyst surface, especially at high operating current densities, and significantly decreased the overpotentials required for HER. An analytical model that accounted for the electrokinetics of HER as well as the mass transport with or without the flow-through configuration was developed to quantitatively evaluate voltage losses associated with kinetic overpotentials and ohmic resistance due to bubble formation in the porous electrodes. The chemical composition, electrochemical surface area (ECSA), and roughness factor (RF) were also systematically studied to assess the electrocatalytic performance of the 3D printed, hierarchically porous NiMo electrodes. An ECSA of 25163 cm2 was obtained with the highly porous structures, and an average overpotential of 45 mV at 10 mA cm-2 was achieved over 24 h by using the flow-through configuration. The flow-through configuration evaluated in the simple H-cell achieved high electrochemical accessible surface areas for electrochemical reactions and provided useful information for adaption of the porous electrodes in flow cells.

3D-Printable Fluoropolymer Gas Diffusion Layers for CO2 Electroreduction.

The electrosynthesis of value-added multicarbon products from CO2 is a promising strategy to shift chemical production away from fossil fuels. Particularly important is the rational design of gas diffusion electrode (GDE) assemblies to react selectively, at scale, and at high rates. However, the understanding of the gas diffusion layer (GDL) in these assemblies is limited for the CO2 reduction reaction (CO2 RR): particularly important, but incompletely understood, is how the GDL modulates product distributions of catalysts operating in high current density regimes > 300 mA cm-2 . Here, 3D-printable fluoropolymer GDLs with tunable microporosity and structure are reported and probe the effects of permeance, microstructural porosity, macrostructure, and surface morphology. Under a given choice of applied electrochemical potential and electrolyte, a 100× increase in the C2 H4 :CO ratio due to GDL surface morphology design over a homogeneously porous equivalent and a 1.8× increase in the C2 H4 partial current density due to a pyramidal macrostructure are observed. These findings offer routes to improve CO2 RR GDEs as a platform for 3D catalyst design.

Toward Engineering of Solution Microenvironments for the CO2 Reduction Reaction: Unraveling pH and Voltage Effects from a Combined Density-Functional-Continuum Theory.

Engineering the electrolyte microenvironment represents an attractive route to tuning the selectivity of electrocatalytic reactions beyond catalyst composition and morphology. However, harnessing the full potential of this approach requires understanding the interplay between voltage, electrolyte composition, and adsorbate binding within the electrical double layer, which is absent from the usual theoretical approaches. In this work, we apply a recently developed density functional theory (DFT)-continuum approach based on the effective screening medium method and reference interaction site model (ESM-RISM) to explore electrolyte effects with an enhanced description of the electrochemical interface. Applying this method to the binding of CO adsorbates in potassium-containing electrolytes on copper, a problem of direct relevance to CO2 electroreduction to value-added products, we show that the interdependence of voltage and pH leads to an unexpected change in adsorption site preference on Cu(001) terraces. Our findings highlight the often-overlooked importance of the electrical double-layer structure for predicting catalyst operation.

3D-Printed Structure Boosts the Kinetics and Intrinsic Capacitance of Pseudocapacitive Graphene Aerogels.

The performance of pseudocapacitive electrodes at fast charging rates are typically limited by the slow kinetics of Faradaic reactions and sluggish ion diffusion in the bulk structure. This is particularly problematic for thick electrodes and electrodes highly loaded with active materials. Here, a surface-functionalized 3D-printed graphene aerogel (SF-3D GA) is presented that achieves not only a benchmark areal capacitance of 2195 mF cm-2 at a high current density of 100 mA cm-2 but also an ultrahigh intrinsic capacitance of 309.1 µF cm-2 even at a high mass loading of 12.8 mg cm-2 . Importantly, the kinetic analysis reveals that the capacitance of SF-3D GA electrode is primarily (93.3%) contributed from fast kinetic processes. This is because the 3D-printed electrode has an open structure that ensures excellent coverage of functional groups on carbon surface and facilitates the ion accessibility of these surface functional groups even at high current densities and large mass loading/electrode thickness. An asymmetric device assembled with SF-3D GA as anode and 3D-printed GA decorated with MnO2 as cathode achieves a remarkable energy density of 0.65 mWh cm-2 at an ultrahigh power density of 164.5 mW cm-2 , outperforming carbon-based supercapacitors operated at the same power density.

Colloidal Materials for 3D Printing.

In recent years, 3D printing has led to a disruptive manufacturing revolution that allows complex architected materials and structures to be created by directly joining sequential layers into designed 3D components. However, customized feedstocks for specific 3D printing techniques and applications are limited or nonexistent, which greatly impedes the production of desired structural or functional materials. Colloids, with their stable biphasic nature, have tremendous potential to satisfy the requirements of various 3D printing methods owing to their tunable electrical, optical, mechanical, and rheological properties. This enables materials delivery and assembly across the multiple length scales required for multifunctionality. Here, a state-of-the-art review on advanced colloidal processing strategies for 3D printing of organic, ceramic, metallic, and carbonaceous materials is provided. It is believed that the concomitant innovations in colloid design and 3D printing will provide numerous possibilities for the fabrication of new constructs unobtainable using traditional methods, which will significantly broaden their applications.

Automated detection and sorting of microencapsulation via machine learning.

Microfluidic-based microencapsulation requires significant oversight to prevent material and quality loss due to sporadic disruptions in fluid flow that routinely arise. State-of-the-art microcapsule production is laborious and relies on experts to monitor the process, e.g. through a microscope. Unnoticed defects diminish the quality of collected material and/or may cause irreversible clogging. To address these issues, we developed an automated monitoring and sorting system that operates on consumer-grade hardware in real-time. Using human-labeled microscope images acquired during typical operation, we train a convolutional neural network that assesses microencapsulation. Based on output from the machine learning algorithm, an integrated valving system collects desirable microcapsules or diverts waste material accordingly. Although the system notifies operators to make necessary adjustments to restore microencapsulation, we can extend the system to automate corrections. Since microfluidic-based production platforms customarily collect image and sensor data, machine learning can help to scale up and improve microfluidic techniques beyond microencapsulation.

Direct Writing of Tunable Living Inks for Bioprocess Intensification.

Critical to the success of three-dimensional (3D) printing of living materials with high performance is the development of new ink materials and 3D geometries that favor long-term cell functionality. Here we report the use of freeze-dried live cells as the solid filler to enable a new living material system for direct ink writing of catalytically active microorganisms with tunable densities and various self-supporting porous 3D geometries. Baker's yeast was used as an exemplary live whole-cell biocatalyst, and the printed structures displayed high resolution, large scale, high catalytic activity and long-term viability. An unprecedented high cell loading was achieved, and cell inks showed unique thixotropic behavior. In the presence of glucose, printed bioscaffolds exhibited increased ethanol production compared to bulk counterparts due largely to improved mass transfer through engineered porous structures. The new living materials developed in this work could serve as a versatile platform for process intensification of an array of bioconversion processes utilizing diverse microbial biocatalysts for production of high-value products or bioremediation applications.

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.

Toward digitally controlled catalyst architectures: Hierarchical nanoporous gold via 3D printing.

Monolithic nanoporous metals, derived from dealloying, have a unique bicontinuous solid/void structure that provides both large surface area and high electrical conductivity, making them ideal candidates for various energy applications. However, many of these applications would greatly benefit from the integration of an engineered hierarchical macroporous network structure that increases and directs mass transport. We report on 3D (three-dimensional)-printed hierarchical nanoporous gold (3DP-hnp-Au) with engineered nonrandom macroarchitectures by combining 3D printing and dealloying. The material exhibits three distinct structural length scales ranging from the digitally controlled macroporous network structure (10 to 1000 µm) to the nanoscale pore/ligament morphology (30 to 500 nm) controlled by dealloying. Supercapacitance, pressure drop, and catalysis measurements reveal that the 3D hierarchical nature of our printed nanoporous metals markedly improves mass transport and reaction rates for both liquids and gases. Our approach can be applied to a variety of alloy systems and has the potential to revolutionize the design of (electro-)chemical plants by changing the scaling relations between volume and catalyst surface area.

Custom 3D Printable Silicones with Tunable Stiffness.

Silicone elastomers have broad versatility within a variety of potential advanced materials applications, such as soft robotics, biomedical devices, and metamaterials. A series of custom 3D printable silicone inks with tunable stiffness is developed, formulated, and characterized. The silicone inks exhibit excellent rheological behavior for 3D printing, as observed from the printing of porous structures with controlled architectures. Herein, the capability to tune the stiffness of printable silicone materials via careful control over the chemistry, network formation, and crosslink density of the ink formulations in order to overcome the challenging interplay between ink development, post-processing, material properties, and performance is demonstrated.

Ultralight Conductive Silver Nanowire Aerogels.

Low-density metal foams have many potential applications in electronics, energy storage, catalytic supports, fuel cells, sensors, and medical devices. Here, we report a new method for fabricating ultralight, conductive silver aerogel monoliths with predictable densities using silver nanowires. Silver nanowire building blocks were prepared by polyol synthesis and purified by selective precipitation. Silver aerogels were produced by freeze-casting nanowire aqueous suspensions followed by thermal sintering to weld the nanowire junctions. As-prepared silver aerogels have unique anisotropic microporous structures, with density precisely controlled by the nanowire concentration, down to 4.8 mg/cm3 and an electrical conductivity up to 51 000 S/m. Mechanical studies show that silver nanowire aerogels exhibit "elastic stiffening" behavior with a Young's modulus up to 16 800 Pa.