3D Electrode Research Articles

High performance Mg–Li dual metal-ion batteries based on highly pseudocapacitive hierarchical TiO2-B nanosheet assembled spheres cathodes

Although Mg-Li dual metal-ion batteries are proposed as a superior system that unite safety of Mg-batteries and performance of Li-ion based systems, its practical implantation is limited due to the lack of reliable high-performance cathodes. Herein, we report a high-performance Mg-Li dual metal-ion battery system based on highly pseudocapacitive hierarchical TiO2-B nanosheet assembled spheres (NS) cathode. This 2D cathode displayed exceptional pseudocapacitance (a maximum of 93%) specific capacity (303 mAh g-1at 25 mA g-1), rate performance (210 mAh g-1at 1 A g-1), consistent cycling (retain ∼100% capacity for 3000 cycles at 1 A g-1), Coulombic efficiency (nearly 100%) and fast-charging (∼12.1 min). These properties are remarkably dominant to the existing Mg-Li dual metal-ion battery cathodes. Spectroscopic and microscopic mechanistic studies confirmed negligible structural changes during charge-discharge cycles of the TiO2-B nanosheet assembled spheres electrodes. Exceptional electrochemical properties of the 2D electrode is ascribed to remarkable pseudocapacitive Mg-Li dual metal-ion diffusion via the numerous nanointerfaces of TiO2-B caused by its hierarchical microstrucrure. Large surface area, nanosheet morphology, mesoporous structure and ultrathin nature also acted as secondary factors facilitating improved electrode-electrolyte contact. Demonstrated approach of pseudocapacitive type Mg-Li dual metal-ion intercalation through hierarchical nanointerfaces may be further utilized for the designing of numerous top-notch electrode materials for futuristic Mg-Li dual metal-ion batteries.

High-Energy Aqueous Sodium-Ion Batteries Using Water-in-Salt Electrolytes and 3D Structured Electrodes.

Aqueous sodium-ion batteries (SIBs) are gradually being recognized as viable solutions for large-scale energy storage because of their inherent safety as well as low cost. However, despite recent advancements in water-in-salt electrolyte technologies, the challenge of identifying anode materials with sufficient specific capacity persists, complicating the wider adoption of these batteries. This study introduces an innovative and straightforward approach for synthesizing vanadium oxide laser-scribed graphene (VOx-LSG) composites, which function as effective anode materials in aqueous sodium-ion batteries. By combining a rapid laser-scribing technique with precise thermal control, the method not only allows for changing the morphology of the vanadium oxide, but also tuning its oxidation state. This is achieved while embedding these electrochemically active particles within a highly conductive graphene scaffold. When paired with a Prussian blue-based cathode (Na1.88Mn[Fe(CN)6]0.97) in a concentrated NaClO4-based aqueous electrolyte, the battery's charge storage mechanism is found to be largely surface-controlled, leading to exceptional rate performance. The full cell demonstrates specific capacities of 128 mA h/g@0.05 A/g and 65.6 mA h/g@1 A/g, with an energy density of 47.7 W h/kg, outperforming many existing aqueous sodium-ion batteries. This strategy offers a promising path forward for integrating efficient, eco-friendly, and low-cost anode materials into large energy storage devices and systems.

Self-Potential Inversion for Regularly Polarized Ore Deposits Anomalies in Different Models Based on Quantum Genetic Algorithm

The self-potential (SP) method is widely used in mineral exploration for its simplicity and cost-effectiveness. Traditional inversion approaches often face challenges with local optima and computational inefficiency in complex models. A quantum genetic algorithm (QGA) for SP data inversion is introduced, combining quantum computation principles with genetic algorithms. Modal analysis and parameters analysis of inversion in different physical models are conducted to determine parameter sensitivity and the optimal parameter range. The proposed optimizer is applied on synthetic data generated from diverse geological models. Gaussian noise is added to test robustness. Indoor experiments, using a controlled environment with a 2D electrode grid, validate QGA's effectiveness in layered models. The impact of data density on the algorithm's performance is evaluated by reducing the number of measurement points. Different field cases from Turkey, Germany and USA further confirmed QGA's practical applicability, with inversion results closely matching drilling data or research published before. Uncertainty appraisal analyses show the validity of the model parameter estimations. In summary, QGA significantly improves SP data inversion, offering better accuracy, efficiency, and robustness, making it a promising tool for complex geological conditions.

Enhanced treatment of multiphase extraction wastewater from contaminated sites with Cu-Ce modified GAC three-dimensional electrodes.

A three-dimensional (3D) electrode system is widely recognized as an effective technology for enhancing electrocatalytic effect. In this study, Cu-Ce modified granular activated carbon (GAC) particle electrodes were prepared using the impregnation method and applied to handle multiphase extraction wastewater. Structural and electrochemical characterization revealed that while the specific surface area of Cu-Ce/GAC decreased by 13.94%, the active area was 2.6 times greater than that of GAC. In addition, the influences of distinct impregnation concentrations, calcination temperatures, and calcination times on the performance of Cu-Ce/GAC electrodes were investigated. The results suggested the optimal preparation conditions of 15mmol/L, 500°C and 2h. Under these conditions, the Cu-Ce/GAC electrode achieved a 92.39% removal of chemical oxygen demand (COD) from a multi-extract of groundwater, with an energy consumption of 13.44 kWh/(kg∙COD). The degradation efficiency improved by 62% compared to the conventional 2D system, while energy consumption decreased by 60%. The main organic pollutants in the multiple extracts, including benzene, toluene, dichloromethane, trichloromethane, were removed at rates exceeding 90% after 60min treatment. This study yields a methodological and engineering approach for treating multiple extracts wastewater from contaminated groundwater.

Electrochemical reduction for chlorinated hydrocarbons contaminated groundwater remediation: Mechanisms, challenges, and perspectives.

Electrochemical reduction technology is a promising method for addressing the persistent contamination of groundwater by chlorinated hydrocarbons. Current research shows that electrochemical reductive dechlorination primarily relies on direct electron transfer (DET) and active hydrogen (H⁎) mediated indirect electron transfer processes, thereby achieving efficient dechlorination and detoxification. This paper explores the influence of the molecular charge structure of chlorinated hydrocarbons, including chlorolefin, chloroalkanes, chlorinated aromatic hydrocarbons, and chloro-carboxylic acid, on reductive dechlorination from the perspective of molecular electrostatic potential and local electron affinity. It reveals the affinity characteristics of chlorinated hydrocarbon pollutants, the active dechlorination sites, and the roles of substituent groups. It also comprehensively discusses the current progress on electrochemical reductive dechlorination using metal, carbon-based, and 3D electrode catalysts, with an emphasis on the design and optimization of electrode materials and the impact of catalyst microstructure regulation on dechlorination performance. It delves into the current application status of coupling electrochemical reduction technology with biodegradation and electrochemical circulating well technology for the remediation of groundwater contaminated by chlorinated hydrocarbons. The paper discusses practical application challenges such as electron transfer, electrode corrosion, water chemistry environment, and aquifer heterogeneity. Finally, considerations are presented from the perspectives of environmental impact and sustainable application, along with a summary and analysis of potential future research directions and technological prospects.

Novel 3D composite for efficient photocatalysis in environmental remediation

AbstractHighly porous, self-supported 3D interconnected network-based nanomaterials hold immense promise in revolutionizing the field of catalysis. These materials combine two critical features; a large accessible surface and an overall active surface that leads to substantial catalytic effects. In this study, we developed a novel class of 3D composite material composed of zinc oxide tetrapods (ZOT) and polyethylene glycol (PEG) polymer, specifically designed for photocatalysis. A polymer composite of ZOT with PEG has been synthesized with 2.5 wt.% ZOT powder mixed with a PEG solution forming a 3D electrode. A consistent composite solution was obtained using probe-sonication and its thick layers were deposited on various substrates using the spin coating technique which were subsequently characterized for optical, morphological, and structural properties. The catalytic response of the fabricated 3D composite was evaluated both in solution and thin film forms under UV exposure. The surface-engineered ZOT-PEG composites showed an excellent capability to degrade the methylene blue (MB) dye in different forms under UV and normal light, opening their potential scopes in environmental remediation.

3D Printing of Graphene Aerogel Microspheres to Architect High-Performance Electrodes for Hydrogen Evolution Reaction.

The hydrogen evolution reaction (HER) efficiency is highly dependent on the electrocatalysts microstructure and the macrostructure of the electrodes. Herein, the graphene aerogel microspheres loaded with well-dispersed ultrafine Ni/Co nanoparticles catalyst is prepared through electro-spraying, in-situ crosslinking, freeze-drying, and pyrolysis, and then is utilized to print the HER electrode via direct ink writing (DIW). The obtained graphene-based aerogel microspheres possess peculiar cabbage-like mesoporous structures which allow ready access of reaction species to active sites, optimal mass transfer, and proton diffusion within the microspheres. DIW 3D printing achieves the ordered control on the periodic lattice macro-geometry and thus facilitates the fast gas bubble evolution and release from the electrode surface. The as-fabricated 3D electrode possesses a low overpotential of 341 mV at 10 mA cm-2, a decrease by 31.5% compared to 3D printed electrode directly from 2D graphene, and a low Tafel slope of 119.1 mV dec-1, 40% lower than that of the electrodes fabricated via directly casting the aerogel microspheres. Furthermore, the 3D-printed electrode of aerogel microspheres displays good HER stability. This work provides a good approach for constructing high-performance HER electrodes through 3D printing of graphene aerogel microspheres.

Tailoring Porous N-Doped Carbon Nanospheres for 3D Bottom-Up Electrode Design: A Versatile Synthesis Toolbox for Particle Size Independent Pore Size Control.

The rational design of carbon-based electrode materials plays an important role in improving the electrochemical properties of both, energy storage and energy conversion electrodes and devices. For most applications, well-defined and easily processable porous carbon-based electrode materials with controlled particle morphology (ideally spherical), particle size, and intraparticle pore size are desired. Here, a hard-templating synthesis toolbox is reported for highly-monodisperse meso- and macroporous N-doped carbon nanospheres (MPNCs) as a versatile material platform for the 3D bottom-up design of porous electrodes. With this approach, it is possible to change the MPNC pore size without affecting the particle size. By changing the template size, the pore size is adjusted between 15 and 99nm while maintaining a particle size ≈300nm. MPNCs are further used in electrochemical double-layer capacitors (EDLCs) as model application to demonstrate pore size effects on the performance independently from particle size effects, resulting in increasing specific capacitances for decreasing pores sizes, which correlates well with the surface area of the MPNCs and mass transport phenomena in the electrode. In conclusion, the toolbox allows to control intraparticulate porosities while keeping interparticulate properties constant, essential parameters to enable a true bottom-up 3D electrode design.

Printed for Performance: Harnessing the Electrochemical Potential of Prussian White Thick Electrodes v ia 3D Printing

The development of Prussian White (PW, Na1.92Fe[Fe(CN)6]) for water-based inks for thick, structured electrodes will be presented. PW is a derivative of Prussian blue analogues (PBA) and has the structural formula of AxM2[M1(CN)6]1-y, where A an alkaline metal such as Na or K, and M is usually a transitional metal such as Fe or Mn. Here, our PW is a strong Na-ion contender to replace Li-ion usage due to their low cost, efficient synthesis methods and comparable capacity to that Lithium iron phosphate of around 160 mAh/g. However, to match the performance of LFP, thick PW electrodes will need to be fabricated and here the mass transport of the electrode can be limiting. Thus, it is imperative to develop a Na-ion battery (NIB), that can exhibit both high energy and high power density, whilst maintaining cost and sustainability. To overcome this limitation of PW, the manufacturing of electrodes through careful battery design can be studied further to achieve a high performing cell.Thicker electrodes (>100 µm) have the potential to have both high power and higher energy, however there is a trade-off between both. When increasing the thickness of a standard two-dimensional (2D) electrode this lengthens the ionic pathways, limiting ionic transport across these thick electrodes. To overcome these restraints, we can introduce a 3D architecture within the electrode microstructure to maintain favourable, short ionic pathways hence, reducing the tortuosity within the electrode microstructure. This overcomes the mass transport limiting effects and now only the electron kinetic mechanism will be restrictive. One electrode deposition method that is used to create structured electrodes is by using a 3D printer (i.e., direct ink writing). Where electrode ink is loaded into a syringe and pressure is applied to extrude the ink through a nozzle.Prussian White is investigated here to see whether it has potential to be 3D printed via extrusion to create our desired thick and structured electrodes. 3D structured electrodes are achieved through tuning the ink rheology, these are compared against our standard 2D electrodes and with hopes to overcome the ionic and mass transport limits of 2D thick electrodes.Here, the overpotentials, impedance measurements and operando XRD from a synchrotron source will be evaluated, to understand how PW will transform under various electrochemical techniques. Further, there will be a direct electrochemical performance comparison between our 3D printed and 2D electrodes, through rate testing and Galvanostatic Intermittent Titration Technique (GITT). Here, we have seen the mass transport improve in our thick 2.8 mAh/cm2 3D printed electrodes, compared against our standard 2D electrode due to differences in the overpotentials. Thus, demonstrating our 3D printed electrodes can surpass the constraints linked to mass transport in thick electrodes, as we have now changed the kinetics at the electrode surface. Overall, we have achieved a multi-disciplinary project as we are discovering new electrode manufacturing processes, whilst using a Na-ion material to create the next-generation of batteries. Figure 1

Time-Dependent Deep Learning Manufacturing Process Model for Battery Electrode Microstructure Prediction

Manufacturing process of Lithium-ion battery electrode has a direct impact on the resulting practical properties of the cell such as durability, safety and overall performance. In this scenario, together with experimental efforts to understand the correlation between manufacturing process parameters and final overall electrode performance, computational tools have shown the potential to produce insights on the manufacturing properties interdependencies. The ARTISTIC initiative [1] pioneered the development of a series of computational 3D-resolved physics-based models describing each step of the manufacturing process following a sequential pattern, going from the slurry phase, through the drying phase, to produce a calendered electrode. Such physics-based models have the capability to predict how manufacturing parameters impact the electrode microstructure. At the end of each phase the output microstructure is carefully validated with experimental data, assuring that the model is in good agreement with real properties. For the calendering phase, the Discrete Element Method (DEM) is used for the model simulation.One of the main limitations of the DEM simulations is their high computational cost, preventing their direct application in electrode optimization loops. In this matter, and given the great amount of already validated data that was produced in our previous works by using the ARTISTIC model, we take one step forward in the development of a new generation model employing machine learning (ML) techniques to accelerate the physics-based simulations but keeping their accuracy. In this presentation we report a novel time-dependent deep learning (DL) model of the battery electrodes manufacturing process. The DL model is demonstrated for calendering of nickel manganese cobalt (NMC111) electrodes, and trained with time-series data arising from physics-based DEM simulations coming from the ARTISTIC physics-based modeling pipeline [2]. The innovative DL model presented in this work can predict an electrode microstructure evolution over time at a given compression degree during calendering and provide the associated final relaxed electrode microstructure. Here we used the formulation of 96% AM and 4% CBD as a proof of concept.The DL model predictions are validated by comparing data evaluation metrics (e.g., mean square error (MSE) and R2 score) and electrode functional metrics (contact surface area, porosity, diffusivity, and tortuosity factor), showing very good accuracy with respect to the DEM simulations (all the properties are above 90% accurate when compared to target data). Regarding transport properties and given the high accuracy of the DL model to predict tortuosity factor and porosity values we can conclude that the model correctly predicts the effect of the calendering on the transport properties since tortuosity factor and porosity has a high impact on the effective transport properties of Li-ions in the electrolyte. The DL model can remarkably capture the elastic recovery of the electrode upon compression (spring-back phenomenon) and the main 3D electrode microstructure features without using the functional descriptors during its training. In terms of computational cost, the DL model performs a timestep in 15 seconds (wall time) while the DEM model performs an equivalent time step in ∼47 minutes (wall time). Given the DL model significant lower computational cost than the DEM simulations, it paves the way toward quasi-real-time optimization loops of the 3D electrode architecture predicting the calendering conditions to adopt in order to obtain the desired electrode performance. Moreover, we consider that our model has tremendous potential to grow in several aspects such as accuracy and predictability. Therefore, our incoming efforts will be focused on continuing the development of the model and testing it for other formulations and in other manufacturing stages.[1] ARTISTIC Project website. https://www.erc-artistic.eu.[2] D. E. Galvez-Aranda, T. L. Dinh, U. Vijay, F. M. Zanotto, A. A. Franco, Time-Dependent Deep Learning Manufacturing Process Model for Battery Electrode Microstructure Prediction. Adv. Energy Mater. 2024, 2400376. https://doi.org/10.1002/aenm.202400376 Figure 1

Optimization of 3D Battery Geometries Using a Combination of Accurate Energy Prediction Models and Automatic Geometry Generator

In order to enlarge the IoT ecosystem, there is a growing need for microbatteries with high areal energy density. A promising approach to improve areal energy density includes using three-dimensional (3D) electrodes, which allow for the holding of more active materials without increasing the internal resistance. Nonetheless, pinpointing the optimal 3D geometry is a challenging task, reliant on the printable materials, the resolution of the production machinery, and the usage of the battery. This constitutes a multiobjective optimization problem, introducing substantial difficulties even when computer simulations are employed because of their high computational cost.To overcome this challenge, we propose a novel approach for the automated identification of optimal 3D battery geometries, which combines quick and accurate energy prediction models with an automatic geometry generator (AGG). [1-4] The energy prediction models employ simple principal component regression, which results in a significantly reduced computational cost. [2] AGG constructs a 3D geometry by filling the empty cell space with cuboid-shaped electrodes (electrode elements). The placement of each electrode element is determined automatically through the Monte Carlo tree search (MCTS) algorithm, leading to the designation of this method as AGG-MCTS. Given that the dimensions of the electrode elements are determined following the resolution of using fabrication equipment, such as 3D printers, our method ensures the generation of only manufacturable geometries. The combination of the energy prediction models and AGG-MCTS enables the rapid identification of optimal 3D battery geometries, without using human intuition and experience.In this study, we demonstrate the efficacy of our approach through its application to two standard electrode pairs: LiFePO4/Li4Ti5O12 (LFP/LTO) and LiNi0.5Mn0.3Co0.2O2/graphite (NMC/Graphite). Despite the distinct discharging behaviors of these systems, our regression models accurately predict the discharge-current-dependent energies of both systems.[4] By integrating these models with the AGG-MCTS, we successfully identify frontier solutions and obtain optimal geometries that display 30% - 40% greater energy than the current state of the art. Notably, optimal geometries vary in response to the discharge current and the specific electrode combination. Our approach uniquely facilitates the discovery of material- and discharge-current-dependent optimal geometries for the first time. This advancement underscores the significance of custom-designed batteries for a variety of IoT applications and highlights our method’s potential to enable such designs.[1] Miyamoto, et al., iScience, 23, 101317 (2020).[2] Miyamoto, et al., Cell. Rep. Phys. Sci., 2, 100504 (2021).[3] Miyamoto, et al., J. Power. Sources, 536, 231473 (2022).[4] Miyamoto, in preparation (2024).

Upscaling Salinity Gradient CRED Cell for Blue Energy Harvesting

CRED (Capacitive reverse electrodialysis) cells are a hybrid technology that were originally introduced by David A. Vermaas to extract electrical energy from salinity gradient [1]. They use selective IME (ion membranes exchange) just like RED (Reverse Electrodialysis) systems but borrow long-lasting, non-faradaic and inexpensive capacitive electrodes from Capmix (Capacitive Mixing) systems achieving power densities around 0.9 W/m² of IME - 5 times higher than Capmix systems [2] but 2 times lower than RED systems [3].Since then, we reviewed this CRED cell in the MIE lab in order to simplify and optimize it. The current system designed by Youcef BRAHMI [4] only uses one IME and carbon felts as capacitive electrodes (Figure 1). The whole cell is equivalent to an ideal generator Ecell, an internal resistance Rcell and an internal capacitor C in series (Figure 2b). Due to the charge of the internal capacitor, the cell must be used in an alternative regime by switching the concentrated and diluted solutions of sodium chloride over a half-period T (Figure 2a). The uptake of these 3D electrodes increases drastically the capacitance allowing us to achieve around 2.3 W/m² by stabilizing the potential (Middle of Figure 5); which can even reach 3.3 W/m² by choosing an appropriate half-period and reducing the internal resistance by employing thinner membranes and higher concentrations (Figure 2e) [5]. Yet, this still represents about 2/3 of the maximum theoretical power obtained for a square potential generator like in RED systems. The maximal power is obtained for loading resistances Rload slightly higher than Rcell (Figure 2d).Very recently, Nan Wu proposed a very surprising technique to recover around 90% of the theoretical power density [5]. She used an additional power supply in phase with the fluid switching (Figure 3). For a given half-period, using this boosting technique ads 60% of the power compared to the non-boosting functioning after retrieving the power contribution of the external source (Figure 4). The boosting acts formally like an additional resistance that increases the characteristic time of the RC circuit stabilizing the whole cell potential at its highest value. It also allows to work with higher external resistances (up to 10 times).Currently, our techno-economic analysis estimates that our cell can produce energy at a cost of 200 €/MWh in the best conditions [6]. Given the decrease of the cost of the IME, these systems could become quite soon a profitable renewable energy. This motivates us in building a cell capable of producing 50 W. For that, we will upscale our CRED cell. The first approach is to increase the surface of a single membrane. We will focus on the effect of the extension of the length - along the flow - and the width – perpendicular to it. The extension of the length highlights the problem of the filling time that has to be as short as possible in order to reach the maximal potential as quick as possible and approach a square signal while not spending too much energy fighting viscous dissipations. Extending the length also amplifies the non-ideal selectivity of the membrane requiring an adjustment of the relative volume flows of the saline solutions. Preliminary results showed that during a switch, the potential of the cell is mostly given by the Donnan potential and its spatial mean considering a plug flow (Figure 5). Regarding the width, the mechanism is different. As the system displays an invariance regarding the flow, the main goal is to improve the transmission line along the current collectors that sets a limit width due to the linear resistance of the collectors. Increasing the surface of one membrane helps reducing the total inner resistance of the cell resulting in a higher current. We will then associate in series the CRED cells to obtain cumulative potential and power while preserving power density on small cells (Figure 6) [7].[1] D. A. Vermaas et al., Energy & Environmental Science, 2013[2] F. Liu et al., Energy & Environmental Science, 2012[3] D. A. Vermaas et al., Environmental Science & Technology, 2011[4] Y. Brahmi et al., Energy Conversion and Management, 2022[5] N. Wu et al., Environmental Science & Technology, 2023[6] N. Wu et al., Scientific Reports, 2024 (Under Review)[7] Z. MAN, PhD Student, 2023 - Now Figure 1

Unravelling the Relationship between Crystallographic Structure and Oxygen Evolution Reaction Activity of Nickel Cobalt Oxide Thin Films

The development of a sustainable energy system relies on the production of green hydrogen. One of the major challenges for water splitting is the synthesis of platinum group metal-free oxygen evolution reaction (OER) electrocatalysts. Spinel nickel cobalt oxides (NCOs) have attracted particular interest due to their stable electrocatalytic performance. The less researched rock-salt NCOs, however, are also promising due to their ability to convert to the OER-active hydroxide phase1. Further development of NCO electrocatalysts requires fundamental understanding of their crystallographic structure-OER performance relationship. This work addresses ~20 nm atomic layer deposited (ALD) NCO thin film systems with a broad composition range to unravel the above-mentioned relationship.Our previously developed ALD supercycle process2 based on Ni(MeCp)2, CoCp2 and O2 plasma is employed to generate a full range of chemical compositions, such that the phase transition from Ni-rich rock-salt films to Co-rich films at ~55 at.% Co can be observed. Extensive material characterisation reveals that the phase transition is accompanied by an increase in the +3/+2 ratio of the oxidation state of both Ni and Co. Electrochemical analysis in 1M KOH shows an optimal performance for the 30 at.% Co rock-salt film after 500 CV cycles and a synergistic effect between cobalt and nickel such that NCO films are more OER active than Co3O4 and NiO. The films show a composition-dependent activation during CV cycling, where a decrease in activation is observed for increasing Co at.%. No activation is observed for the spinel films. The activation is driven by bulk transformation to the active (oxy)hydroxide phase and is accompanied by an increase in electrochemical surface area (ECSA) up to a factor 8 for rock-salt films. The overpotential after cycling is corrected for the increase in ECSA using an original method, which reveals that Ni-rich spinel structure films are intrinsically more active3.The use of model systems in combination with extensive material characterisation and prolonged electrochemical testing allows us to distinguish two classes of NCO catalysts, the instantly active and highly stable Co-rich spinel films and the high surface area Ni-rich rock-salt phase which develops upon extensive activation . Placing these results in perspective, we conclude that application of these catalysts on high surface area 3D electrodes would benefit from the more intrinsically active spinel NCO films, whilst activated rock-salt films would be the preferred choice for thin film electrocatalysis studies. These results also show that rock-salt NCO films (<40 at.% Co) could be a more sustainable alternative to the more commonly used spinel NCO films. 1Gebreslase et al. J. Energy Chem. 2022, 67, 101-137 2van Limpt et al. JVSTA, 2023, 41, 032407 3van Limpt et al. Adv. Energy Mat. under review Figure 1

3D-Printed High Surface Area Electrodes and Advanced Flow Reactors for Bio-Compatible Electrochemical Reactions

With the urgent need for emissions-free economies, bio-catalytic electrochemical processes such as electro-bio-methanation enable coupling of renewable energy harvesting with chemical energy storage and/or chemical synthesis. Electro-bioreactors offer high product selectivity and efficiency, eliminating the need for energy intensive separations. However, the electrochemical reaction rates of bio-catalytic processes are fundamentally constrained due to poor fluid distribution and ion transport near the electrode surface. Mass transport limitations in bioreactors alter the reactive surface environments and cause bio-catalytic stability issues. To address these challenges and achieve high volumetric productivities under bio-compatible conditions, we introduced additively manufactured, high surface area 3D electrodes and engineered flow cells. We characterized the effects of electrode geometry and structural parameters on electrochemical performance in abiotic media to develop structure property relationships. Using the hydrogen evolution reaction as a model system, we identified several high surface area structures that improve the fluid distribution within the reactor. Triply periodic minimal surface structures, like gyroids, enable higher volumetric productivities compared to conventional planar electrodes. These findings can be used to understand the role of electrode structure on electrochemical performance and the scaling behavior or bio-reactor flow cells utilizing 3D electrodes.This work was performed under the auspices of the U.S. Department of Energy by Lawrence Livermore National Laboratory under Contract DE-AC52-07NA27344

Robust 3D Lithium Cell Architecture - Inherently Boosted Safety

The HE3DA concept of up to several millimeters thick electrodes (3D) gives lithium battery incomparable safety and brings a number of new technical attributes, which are not achievable by the existing thin film technology (2D).3D architecture allows construction of very large cells and provides inherent safety required for large energy storage. Ceramic composite separator, together with the advanced 3D electrode design give the cell robust and stable performance, extend the temperature range, eliminate common ageing mechanisms such as active layer delamination, plastic separator shrinkage on overheating, gas bubbles or step increase of internal resistance during cycling.Performance of 1KWh 3D cells at different load and conditions will be demonstrated. Figure 1

High-Fidelity Transfer of 2D Semiconductors and Electrodes for van der Waals Devices.

As traditional silicon-based materials almost reach their limits in the post-Moore era, two-dimensional (2D) transition metal dichalcogenides (TMDCs) have been regarded as next-generation semiconductors for high-performance electrical and optical devices. Chemical vapor deposition (CVD) is a widely used technique for preparing large-area and high-quality TMDCs. Yet, it suffers from the challenge of transfer due to the strong interaction between 2D materials and substrates. The traditional PMMA-assisted wet etching method tends to induce damage, wrinkles, and inevitable polymer residues. In this work, we propose an etch-free and clean transfer method via a water intercalation strategy for TMDCs, ensuring a high-fidelity, wrinkle-free, and crack-free transfer with negligible residues. Furthermore, metal electrodes can also be transferred via this method and back-gate field-effect transistors (FETs) based on CVD-grown monolayer WSe2 with van der Waals (vdW) metal/semiconductor contacts are fabricated. Compared to the PMMA-assisted transfer method (∼1.2 cm2 V-1 s-1 hole mobility with ∼2 × 106 ON/OFF ratio), our high-fidelity transfer method significantly enhances the electrical performance of WSe2 FET over one order of magnitude, achieving a hole mobility of ∼43 cm2 V-1 s-1 and a high ON/OFF ratio of ∼5 × 107 in air at room temperature.

Spatially Localized Visual Perception Estimation by Means of Prosthetic Vision Simulation.

Retinal prosthetic devices aim to repair some vision in visually impaired patients by electrically stimulating neural cells in the visual system. Although there have been several notable advancements in the creation of electrically stimulated small dot-like perceptions, a deeper comprehension of the physical properties of phosphenes is still necessary. This study analyzes the influence of two independent electrode array topologies to achieve single-localized stimulation while the retina is electrically stimulated: a two-dimensional (2D) hexagon-shaped array reported in clinical studies and a patented three-dimensional (3D) linear electrode carrier. For both, cell stimulation is verified in COMSOL Multiphysics by developing a lifelike 3D computational model that includes the relevant retinal interface elements and dynamics of the voltage-gated ionic channels. The evoked percepts previously described in clinical studies using the 2D array are strongly associated with our simulation-based findings, allowing for the development of analytical models of the evoked percepts. Moreover, our findings identify differences between visual sensations induced by the arrays. The 2D array showed drawbacks during stimulation; similarly, the state-of-the-art 2D visual prostheses provide only dot-like visual sensations in close proximity to the electrode. The 3D design could offer a technique for improving cell selectivity because it requires low-intensity threshold activation which results in volumes of stimulation similar to the volume surrounded by a solitary RGC. Our research establishes a proof-of-concept technique for determining the utility of the 3D electrode array for selectively activating individual RGCs at the highest density via small-sized electrodes while maintaining electrochemical safety.

Single-Entity Electrochemistry of N-Doped Graphene Oxide Nanostructures for Improved Kinetics of Vanadyl Oxidation.

N-doped graphene oxides (GO) are nanomaterials of interest as building blocks for 3D electrode architectures for vanadium redox flow battery applications. N- and O-functionalities have been reported to increase charge transfer rates for vanadium redox couples. However, GO synthesis typically yields heterogeneous nanomaterials, making it challenging to understand whether the electrochemical activity of conventional GO electrodes results from a sub-population of GO entities or sub-domains. Herein, single-entity voltammetry studies of vanadyl oxidation at N-doped GO using scanning electrochemical cell microscopy (SECCM) are reported. The electrochemical response is mapped at sub-domains within isolated flakes and found to display significant heterogeneity: small active sites are interspersed between relatively large inert sub-domains. Correlative Raman-SECCM analysis suggests that defect densities are not useful predictors of activity, while the specific chemical nature of defects might be a more important factor for understanding oxidation rates. Finite element simulations of the electrochemical response suggest that active sub-domains/sites are smaller than the mean inter-defect distance estimated from Raman spectra but can display very fast heterogeneous rate constants >1cms-1. These results indicate that N-doped GO electrodes can deliver on intrinsic activity requirements set out for the viable performance of vanadium redox flow battery devices.

Scalable balloon catheter assisted contact enhancement of 3D electrode array for colon electrophysiological recording

The clinical diagnosis of functional gastrointestinal disorders primarily relies on symptom assessment and physical examination, methods that are inherently limited due to undetermined specific biomarkers and susceptibility to subjective judgment. Electrophysiological techniques offer a clinically practical approach by precisely recording the electrical activities of the intestines, providing deeper biophysical insights. However, in vivo electrophysiological investigation of the intestines remains challenging, such as the stability of the electrode-tissue interface, high-frequency signal transmission, motion artifact, and signal interpretation. This study developed an endoscopic-based high spatiotemporal electrophysiological recording device, by integrating balloon catheters and flexible three-dimensional electrode arrays with a mapping function. We integrated the 3D electrode array on a scalable balloon catheter and deployed this device in rabbits, achieving a stable collection of multiphasic electrophysiological signals from the intestinal mucosa. In vivo electrophysiological recordings identified observable spike bursts associated with intestinal motility, as well as coordinated periodic pulses potentially related to intestinal pacemaker activities, revealing their activation modulation patterns. Further, longer-duration non-periodic spike bursts were also observed to link to spontaneous non-periodic peristaltic contractions. This technique realized through minimally invasive procedures, achieves a high spatiotemporal resolution in electrophysiological recording, providing a powerful tool for the diagnosis and research of functional bowel diseases.

A metallic lithium anode for solid-state batteries with low volume change by utilizing a modified porous carbon host

Lithium metal is a promising negative electrode material for solid-state batteries (SSBs). However, uncontrolled lithium deposition and stripping cause several issues during cycling. Herein, the microporous carbon YP-50F and its modifications obtained by thermal ethene-based chemical vapor deposition (CVD) are investigated as 3D host to accommodate and control the deposition of metallic lithium. In half-cells vs. lithium, the CVD-YP composite electrode with Li6PS5Cl electrolyte shows significantly higher initial coulombic efficiency (79.5 %) than the pristine carbon (55.3 %) due to the reduction of side reactions. The metallic character of the deposited lithium is evidenced by 7Li Nuclear Magnetic Resonance spectroscopy. However, full cells with nickel-rich NCM (LiNi0.9Co0.05Mn0.05O2) positive electrode and CVD-YP composite negative electrode show reasonable performance over 50 cycles without occurrence of (micro-) short-circuits (in contrast to 2D reference electrodes). In addition, small prototype pouch cells are investigated and the thickness change during (dis)charging is less than one third compared to a bare lithium metal electrode. This demonstrates low breathing behavior of the CVD-YP electrode and confirms the reversible storage of metallic lithium within the 3D carbon-based composite electrode.