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At least 1,135 records · Page 63

Engineering Catalyst–Electrolyte Microenvironments to Optimize the Activity and Selectivity for the Electrochemical Reduction of CO 2 on Cu and Ag

We report the electrochemical reduction of carbon dioxide (CO 2 R) driven by renewably generated electricity (e.g., solar and wind) offers a promising means for reusing the CO 2 released during the production of cement, steel, and aluminum as well as the production of ammonia and methanol. If CO 2 could be removed from the atmosphere at acceptable costs (i.e., <$100/t of CO 2 ), then CO 2 R could be used to produce carbon-containing chemicals and fuels in a fully sustainable manner. Economic considerations dictate that CO 2 R current densities must be in the range of 0.1 to 1 A/cm 2 and selectivity toward the targeted product must be high in order to minimize separation costs. Industrially relevant operating conditions can be achieved by using gas diffusion electrodes (GDEs) to maximize the transport of species to and from the cathode and combining such electrodes with a solid-electrolyte membrane by eliminating the ohmic losses associated with liquid electrolytes. Additionally, high product selectivity can be attained by careful tuning of the microenvironment near the catalyst surface (e.g., the pH, the concentrations of CO 2 and H 2 O, and the identities of the cations in the double layer adjacent to the catalyst surface).

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Cooling Mixed A-Site Halide Perovskites: Impact of Temperature on Optical and Structural Properties

The widespread utilization of perovskite-based photovoltaics requires probing both the structural and optical properties under extreme operating conditions to gain a holistic understanding of the material behavior under stressors. Here, in this study, we investigate the temperature-dependent behavior of mixed A-site cation lead triiodide perovskite thin films (85% methylammonium and 15% formamidinium) in the range from 300 to 20 K. Through a combination of optical and structural techniques, we find that the tetragonal-to-orthorhombic phase transition occurs at similar to 110 K for this perovskite composition, as indicated by the change in the diffraction pattern. With decreasing temperature, the quantum yield increases with a concurrent elongation of the carrier lifetimes, indicating suppression of nonradiative recombination pathways. Interestingly, in contrast to single A-site cation perovskites, an additional optical transition appears in the absorption spectrum when the phase transition is approached, which is also reflected in the emission spectrum. We propose that the splitting of the optical absorption and emission is due to local segregation of the mixed cation perovskite during the phase transition.

36 MATERIALS SCIENCE↗

Quasi-In-Situ Analysis of Electrode Top Atomic Layers via High-Sensitivity Low-Energy Ion Scattering and Potential-Controlled Sample Transfer

Electrocatalytic reactions involve interfacial interactions between the surfaces of electrodes and reactive species at an electrolyte interface. There are presently no universal or unambiguous methods to directly assay the active top atomic layer composition that influences the reactivity of these electrodes under relevant operating conditions. Low-energy ion scattering (LEIS) spectroscopy is a surface characterization technique that yields compositional analysis of the outermost atomic layer of a material, but it must be performed in ultrahigh vacuum (UHV). Application of LEIS measurements to electrochemical materials that are removed from ambient liquid-phase environments thus leaves an open question as to whether the surface that is transferred to UHV is truly the surface that manifested during the electrochemical reaction. Toward the goal of preserving the active surface state, we developed a sample transfer workflow for LEIS enabling air-free removal and drying of an electrode from an electrochemical cell while maintaining control of the potential using an auxiliary electrode. The potential-controlled emersion method was demonstrated to give distinct potential-dependent surface compositions for a Cu−Pd alloy relative to removal after uncontrolled return to open-circuit potential. A Cu-enriched surface was found at anodic potential and a Pd-enriched surface at cathodic potential, suggesting that the approach can be used to retain representative atomic configurations during transfer. Since adsorbates will often persist from the reaction environment, conventional sample pretreatment methods for removal, including atomic O and atomic H exposure, were also contrasted. Both methods were found to differ with results from incidental low-dose depth profiling by the LEIS primary ion source, which removes adventitious species and surface atoms during the course of repeated measurements. These depth profiles were found to be sensitive to sample history and thus qualitatively informative, despite the possible changes induced by ion damage. The results exhibit (i) the need for complete control over the polarization state of the sample at all times (no excursions to open circuit during transfer) and (ii) the utility of low-dose depth profiling to capture changes in the near-surface composition.

Alloys↗

Carbon Dioxide Conversion to Nanomaterials: Methods, Applications, and Challenges

Anthropogenic carbon dioxide (CO 2 ) emission is one of the biggest global threats that we are confronted with in the 21st century. A lack of prompt action to mitigate the atmospheric CO 2 level could lead to global catastrophic events. As a result of the significance of the aforementioned threat, multiple nations have agreed to enact carbon capture, storage, utilization, and sequestration (CCUS) technologies at academic and industrial scales with the aim of lowering the atmospheric CO 2 level. Although there are many reviews on CCUS technologies, there is a lack of comprehensive review on CO 2 conversion to more economically valuable products, such as nanomaterials. Carbon dioxide capture and conversion into nanomaterials is an interesting research topic in many ways because it contributes to our fundamental knowledge of material conversion, provides alternative ways to reduce atmospheric pollution, and yields lucrative products, which has not been explored broadly. Aside from the positive outcomes, we have a moral obligation to rectify a global threat caused by anthropogenic emission. Herein, we present current methods of converting CO 2 into organic and inorganic nanomaterials with a focus on operating conditions and challenges as well as the potential of nanomaterials in specifically biomedical applications as opposed to extensively reviewed energy-related uses. Furthermore, our review emphasizes the toxicity issues related to using such nanomaterials in biological settings based on literature and other comparable studies.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Perspectives on Polyolefin Catalysis in Microfluidics for High-Throughput Screening: A Minireview

Polyolefins are the largest produced plastics in the world which traditionally employ continuous stirred tank reactors and fluidized bed reactors for commercial production. The operating condition, reaction kinetics, and molecular interactions inside the reactor strongly affect the polyolefin properties, which require stringent process control in conventional procedures. Understanding the catalytic pathway, behavior of polymer particles and effect of reactor conditions are essential for designing specific polymer properties, namely the molecular weight, chain length, polydispersity, etc. Microfluidics can play a significant role in designing polymers tailored to the user needs. Smaller channel dimensions help obtain uniform reaction conditions over the length of the microfluidic reactor in a controlled environment. With real-time monitoring techniques in microfluidics, even single particle growth of polymer can be studied to understand the parameters affecting the polymer properties. High throughput microfluidics can help catalyst screening in a short duration with less consumption of reagents generating less waste. When supplemented with efficient machine learning algorithms, automated high throughput microfluidics has the potential to rapidly optimize the process and develop new knowledge even with a limited data set. When trained on data sets generated using microfluidic experiments that are designed efficiently with working knowledge of the process, machine learning algorithms can provide the relationship between the multivariable parameters space and polymer properties, which is not possible with the traditional statistical methods and interpolation techniques. Here, the rise in the utilization of microfluidics, with the advancement of machine learning algorithms, for polyolefin catalysis, highlights the importance of microfluidics for catalyst discovery, parameter optimization, and understanding reaction pathway for producing polymers with specific properties for specialized applications.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

X-ray Transient Absorption Spectroscopy Reveals Light Responses of Cobalt Centers in Co-Pi OER Catalytical Devices under Electrochemical Biases

Here, operando X-ray transient absorption measurements were successfully performed for the first time on the Co-Pi catalyst, confirming a photoreduction in Co-Pi under 400 nm blue light excitation. This provides key insights into spectroelectrochemical mechanistic studies of relevant oxygen evolution catalysts and guidance for photocatalysis using these metal oxides. Limiting blue-light exposure of these films should allow for better self-healing and higher turnover in photon-driven water oxidation. These results also demonstrate the importance of performing XTA measurements under operating conditions. Further development of this technique will allow for analysis of complex materials such as tethered molecules on surfaces and in complex device architectures to yield beneficial data for applied materials.

electrochemical cells↗

Unlocking Dysprosium Constraints for China’s 1.5 °C Climate Target

Some key low-carbon technologies, ranging from wind turbines to electric vehicles, are underpinned by the strong rare-earth-based permanent magnets of the Nd, Pr (Dy)–Fe–Nb type (NdFeB). These NdFeB magnets, which are sensitive to demagnetization with temperature elevation (the Curie point), require the addition of variable amounts of dysprosium (Dy), where an elevation of the Curie point is needed to meet operational conditions. Given that China is the world’s largest REE supplier with abundant REE reserves, the impact of an ambitious 1.5 °C climate target on China’s Dy supply chain has sparked widespread concern. Here, we explore future trends and innovation strategies associated with the linkage between Dy and NdFeBs under various climate scenarios in China. We find China alone is expected to exhaust the global present Dy reserve within the next 2–3 decades to facilitate the 1.5 °C climate target. By implementing global available innovation strategies, such as material substitution, reduction, and recycling, it is possible to avoid 48%–68% of China’s cumulative demand for Dy. Nevertheless, ongoing efforts in REE exploration and production are still required to meet China’s growing Dy demand, which will face competition from the United States, European Union, and other countries with ambitious climate targets. Here our analysis urges China and those nations to form wider cooperation in REE supply chains as well as in NdFeB innovation for the realization of a global climate-safe future.

54 ENVIRONMENTAL SCIENCES↗

Influence of Transition Metal Ion Contaminants on the Performance of Amine-Based Solid Sorbents in Direct Air Capture

Amine-functionalized solid sorbents are a class of sorbent materials proposed for direct air capture (DAC) of CO 2 , yet their long-term performance is susceptible to degradation under realistic operating conditions. Many amines are not thermodynamically stable in air, and amine sorbents oxidize while in use during DAC temperature swing adsorption processes. In this study, we investigate the role of transition metal ion contaminants, specifically Cu 2+ , Fe 2+ , and Ni 2+ , on the oxidative degradation of poly(ethylenimine) (PEI)-impregnated SBA-15 sorbents. By introducing metal ions via different modes mimicking both synthesis-related impurities and impurities derived from environmental exposure, we systematically evaluate sorbent stability after exposure to dry air at an elevated temperature. Thermogravimetric CO 2 uptake measurements reveal that even trace levels of Cu and Fe (as low as ∼4 ppm) can lead to measurable sorbent deactivation after oxidative aging, despite negligible loss in the performance of the control samples. In situ infrared, UV–vis, and X-ray photoelectron spectroscopies indicate that these metals catalyze radical-driven oxidation pathways, altering the chemical structure of the sorbent and accelerating degradation. Our findings underscore the need to account for trace metal contamination during DAC sorbent synthesis and deployment and highlight the importance of environmental contamination pathways.

CO2 capture↗

Reconstruction and Dissolution of Copper Catalysts during Electrocatalytic Nitrate Reduction

Copper-based electrocatalysts are widely explored for electrochemical nitrate remediation, yet their stability under operating conditions remains poorly understood. While nanoscale and subnanoscale Cu motifs are known to restructure during the nitrate reduction reaction (NO 3 RR), how these transformations translate into irreversible material loss remains unclear. Here, we quantify Cu dissolution during NO 3 RR as a function of catalyst architecture and electrolyte chemistry using two model systems: single-atom Cu (Cu 1 ) and Cu nanoparticles (Cu NP ). Time-resolved leaching measurements, integrated with in situ X-ray absorption spectroscopy (XAS), reveal measurable Cu loss for both catalysts during NO 3 RR. Dissolution is concentrated at the initiation of electrolysis, coinciding with rapid restructuring, and depends strongly on morphology, with Cu NP consistently exhibiting greater Cu loss than Cu 1 . In situ XAS reveals that Cu 1 forms transient metallic clusters under reduction that largely redisperse upon returning to open-circuit voltage, whereas Cu NP undergoes reduction of an oxidized surface layer accompanied by sustained Cu loss during electrolysis. Notably, the presence of nitrate significantly intensifies restructuring and Cu loss, highlighting the critical role of electrolyte composition. Furthermore, these findings establish a direct link between electrochemical restructuring and Cu dissolution, unveiling electrolyte-dependent interactions as key determinants of catalyst durability in electrochemical nitrate conversion.

36 MATERIALS SCIENCE↗

Temperature Homogeneity under Selective and Localized Microwave Heating in Structured Flow Reactors

Selective heating of different phases of multiphase systems via microwaves can result in energy savings and suppression of side reactions. However, materials properties and operating conditions that maximize temperature gradients are poorly understood. Here we utilize computational fluid dynamics (CFD) computations and temperature measurements in structured flow reactors (monoliths) in a monomodal microwave cavity to assess the temperature difference between the walls and the fluid and develop a simple lumped model to estimate when temperature gradients exist. We also explore the material’s thermal and electrical properties of structured reactors for isothermal catalyst conditions. We propose that CFD simulations can be used as a nonintrusive, predictive tool of temperature homogeneity. Importantly, we demonstrate that localized heating in the bed under several conditions rather than selective heating is responsible for the selectivity enhancement. Furthermore, our results indicate that structured beds made of high thermal conductivity materials avoid arcing and enable temperature homogeneity and low electrical conductivity materials allow microwaves to penetrate the domain.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

PemNet: A Transfer Learning-Based Modeling Approach of High-Temperature Polymer Electrolyte Membrane Electrochemical Systems

Widespread adoption of high-temperature electrochemical systems such as polymer electrolyte membrane fuel cells (HT-PEMFCs) requires models and computational tools for accurate optimization and guiding new materials for enhancing fuel cell performance and durability. Furthermore, while robust and better suited for extrapolation, knowledge-based modeling has limitations as it is time-consuming and requires information about the system that is not always available (e.g., material properties and interfacial behavior between different materials). Data-driven modeling, on the other hand, is easier to implement but often necessitates large datasets that could be difficult to obtain. In this contribution, knowledge-based modeling and data-driven modeling are combined by implementing a few-shot learning (FSL) approach. A knowledge-based model originally developed for a HT-PEMFCs was used to generate simulated data (887,735 points) and used to pretrain a neural network source model tuned via a genetic algorithm-based AutoML. Then, experimental datasets from HT-PEMFCs with different materials and operating conditions (~50 points each) were used to train six target models via FSL. Models for the unseen data reached high accuracies in all cases (rRMSE < 10%).

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Mechanistic Interpretations and Insights for the Oxidative Dehydrogenation of Propane via CO 2 over Cr 2 O 3 /Al 2 O 3 Catalysts

Oxidative dehydrogenation (ODH) of alkanes using carbon dioxide as a soft oxidant has recently emerged as a potentially attractive alternative to steam cracking for the production of light olefins. To elucidate reaction pathways and their dependence on the operating conditions, CO 2 -assisted propane dehydrogenation over a redox-active Cr 2 O 3 /Al 2 O 3 catalyst was examined in a packed bed reactor as a function of temperature, Cr 2 O 3 /CO 2 feed ratio, and residence time. Previous ODH studies have largely focused on CO 2 -rich conditions with the aim of preventing coke formation. However, at T = 600 °C the present study finds that the use of propane-rich conditions (1 ≤ C 3 H 8 /CO 2 ≤ 2.5) maximizes propylene production and selectivity while maintaining catalyst stability. In this work, it is postulated that the selective Mars van Krevelen dehydrogenation process is optimized at these ratios. Excess CO 2 apparently promotes nonselective dehydrogenation and dry reforming pathways that generate additional CO, adversely impacting catalyst stability via the Bouduard reaction. This hypothesis is supported by complementary investigations of the reverse water gas shift reaction and thermodynamic analysis. The findings and methodology presented here are likely applicable to related ODH processes with other alkanes and redox-active catalysts.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Stability Analysis of Substituted Cobaltocenium [Bis(cyclopentadienyl)cobalt(III)] Employing Chemistry-Informed Neural Networks

Cobaltocenium derivatives are promising components of the anion exchange membranes due to their excellent thermal and alkaline stability under the operating conditions of a fuel cell. Here we present an efficient modeling approach of assessing the chemical stability of substituted cobaltocenium CoCp 2 + based on the computed electronic structure enhanced by machine learning techniques. Within the aqueous environment, the positive charge of the metal cation is balanced by the hydroxide anion through formation of the CoCp 2 + OH¯ complexes, whose dissociation is studied within the implicit solvent employing density functional theory. The data set of about 118 species based on 42 substituent groups characterized by a range of electron- donating (ED) and electron-withdrawing (EW) properties is constructed and analyzed. Given 12 carefully chosen chemistry-informed descriptors of the complexes and relevant fragments, the stability of the complexes is found to strongly correlate with the energies of the highest occupied and lowest unoccupied molecular orbitals, modulated by a switching function of the Hirshfeld charge. The latter is used as a measure of the electron withdrawing-donating character of the substituents. Based on this observation from the conventional regression analysis, two fully connected, feed-forward neural network (FNN) models with different unit structures, called the chemistry-informed (CINN) and the quadratic (QNN) neural networks, are developed. Both models predict the bond dissociation energies of the cobaltocenium complexes with mean relative errors less than 5.40% and average absolute errors less than 0.94 kcal/mol. The results show the potential of QNN to efficiently capture more complex relationships. Here, the concept of incorporating the domain (chemical) knowledge/insight into the neural network structure paves the way to applications of machine learning techniques with small data sets, ultimately leading to better predictive models compared to the conventional regression analysis.

36 MATERIALS SCIENCE↗

Energetics of Base–Acid Pairs for the Design of High-Temperature Fuel Cell Polymer Electrolytes

The interaction energy of base–acid plays a key role in acid retention of phosphoric acid (PA)-doped polymer electrolytes under fuel cell operating conditions. Here, we investigate the energetics of proton-accepting and hydroxide-donating organic bases using density functional theory calculations. Because of their weak basicity, proton-accepting organic bases such as benzimidazole have relatively low interaction energy with the acid in the absence of water (15.3–28.0 kcal mol –1 ). Energetics of the proton-accepting base–PA complex increases by adding water, indicating that the interactions in the base–acid complex strengthen in the presence of water. On the other hand, hydroxide-donating organic bases, such as tetramethylammonium hydroxide, have high interaction energy with PA (~110 kcal mol –1 ), which remains high in the presence of water. The chemical shifts of 31P NMR support the energetics of the base–acid complexes. Overall, this study further discusses the benefit of incorporating hydroxide-donating organic bases into the polymeric structure over proton-accepting bases as a way to increase acid retention.

25 ENERGY STORAGE↗

Temperature-Dependent Constrained Diffusion of Micro-Confined Alkylimidazolium Chloride Ionic Liquids

Alkylimidazolium chloride ionic liquids (ILs) have many uses in a variety of separation systems, including micro-confined separation systems. To understand the separation mechanism in these systems, the diffusion properties of analytes in ILs under relevant operating conditions, including micro-confinement dimension and temperature, should be known. For example, separation efficiencies for various IL-based microextraction techniques are dependent on the sample volume and temperature. Temperature-dependent (20–100 °C) fluorescence recovery after photobleaching (FRAP) was utilized to determine the diffusion properties of a zwitterionic, hydrophilic dye, ATTO 647, in alkylimidazolium chloride ILs in micro-confined geometries. These micro-confined geometries were generated by sandwiching the IL between glass substrates that were separated by ~1 to 100 μm. From the measured temperature-dependent FRAP data, we note alkyl chain length-, thickness-, and temperature-dependent diffusion coefficients, with values ranging from 0.021 to 46 μm 2 /s. Deviations from Brownian diffusion are observed at lower temperatures and increasingly less so at elevated temperatures; the differences are attributed to alterations in intermolecular interactions that reduce temperature-dependent nanoscale structural heterogeneities. Furthermore, the temperature- and thickness-dependent data provide a useful foundation for efficient design of micro-confined IL separation systems.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Modeling Hydrogen Evolution Reaction Kinetics through Explicit Water–Metal Interfaces

Despite the apparent simplicity of the hydrogen evolution reaction (HER) and the decades of research into it, controversy remains in the literature regarding the identity of the active site and the competition between the Heyrovsky and Tafel steps. In this work, we use charge-extrapolated ab initio simulations with explicit water in conjunction with mean-field microkinetic modeling to explore the mechanism for HER on both close-packed (111) and stepped (211) transition metals. First, we show that atop H*, beyond a monolayer of hollow H*, is unlikely to play a role in the HER mechanism, given its very positive adsorption energies. The energetics suggests the Volmer–Heyrovsky mechanism to predominate on fcc transition metals under typical operating conditions. Here, we evaluate our theoretical results vs several experimental observations. We show that the Volmer–Heyrovsky mechanism predicts an activity volcano with its peak at a H* binding ΔG H* ≈ 0 eV, consistent with experiment. In contrast, the Volmer–Tafel volcano shows a broad rate plateau between ΔG H* ≈ 0 eV and ΔG H* ≈ – 0.4 eV. We find our theoretical Tafel slopes to be consistent with experimental ones on a range of transition metals. We show that, in line with experimental observations, the introduction of a CO(g) atmosphere shifts the strong binding metals toward the weak binding leg. Our study suggests that the simple thermodynamic approach to HER activity still holds, even when a detailed kinetic picture is considered.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Suppressing Auger Recombination in Multiply Excited Colloidal Silicon Nanocrystals with Ligand-Induced Hole Traps

Nonradiative Auger recombination in multiply excited nanocrystals is a dominant efficiency loss pathway for nanocrystal-containing optoelectronic devices that rely on high-rate emission and absorption operating conditions. Overcoming Auger recombination in these quantum-confined systems is therefore a longstanding challenge to the synthetic nanocrystal as well as device manufacturing communities. Several successful strategies have been realized to reduce Auger recombination, but they rely on complex and time-consuming nanocrystal core/shell synthesis. Alternatively, controlling Auger rates by varying the nanocrystal–ligand-binding chemistry is a promising route to obtain functional tunability, which reduces the barrier to large-scale manufacturing. The covalent surface chemistry and the extremely long-lived photoexcited lifetimes of silicon nanocrystals (Si NCs) make them a unique system among colloidal semiconductor NCs to study the intersection between surface chemistry and photoexcited carrier dynamics. Here, we show that changing the functional group that binds a saturated dodecyl ligand to the surface of nonthermal plasma-synthesized Si NCs from alkyl to thiolate slows Auger recombination rates within multiply excited Si NCs. This reduction in Auger rate persists across Si NC sizes ranging from 3.5 to 8 nm in diameter, but the expected linear dependence of Auger rates on the NC volume is retained for both alkyl and alkylthiolate surface terminations. To understand the origin behind this elongation, we carry out steady-state and time-resolved photoluminescence measurements as well as time-resolved terahertz spectroscopy measurements. These measurements reveal that thiolate groups introduce mid-gap surface states, which, we argue, reduces the photoexcited electron–hole overlap and elongates Auger recombination times. These results highlight how a typically detrimental chemical species—mid-band gap NC surface states—can be beneficial under high-rate absorption/emission conditions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Nafion Inhibits Polysulfide Crossover in Hybrid Nonaqueous Redox Flow Batteries

Here, we report on the effectiveness of sodium-exchanged Nafion membranes for inhibiting polysulfide crossover during redox flow battery operation. The solubility of polysulfides allows them to be used as a high-capacity catholyte for nonaqueous redox flow batteries (NARFB). The NARFB cathode capacity is controlled by the total tank catholyte volume and polysulfide concentration and, as such, is independent of polysulfide adsorption sites on carbon fibers or nanotubes as found within traditional Na or Li–S batteries. However, one of the major barriers to the realization of polysulfide NARFBs is associated with developing a robust membrane that has minimal polysulfide crossover under the operating conditions. We found that sodium-exchanged Nafion membrane separators effectively inhibit polysulfide crossover within a Na–sulfur NARFB. These membranes significantly improve both capacity retention (70%) and Coulombic efficiencies (99%) after 50 cycles. Commercial porous membranes showed a large crossover as detected by UV–vis spectroscopy and resulted in low capacity retention (20%) and Coulombic efficiency (74%) after 45 cycles. Electrochemical impedance spectroscopy (EIS) measurements highlighted the trade-off between innate reactivity and ionic conduction of the membranes. The results show that dense, single ion conducting Nafion enables a long cycle life; however, it reacts with Na metal to form a resistive passivation layer and increases the cell resistance. On the contrary, the open pore structure of Celgard allows for higher current charge/discharge, and its chemical nature is compatible with Na; however, it has a high degree of polysulfide crossover.

25 ENERGY STORAGE↗