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At least 883 records · Page 49

Finite-size effects in periodic coupled cluster calculations

Here, we provide the first rigorous study of the finite-size error in the simplest and representative coupled cluster theory, namely the coupled cluster doubles (CCD) theory, for gapped periodic systems. Given exact Hartree-Fock orbitals and their corresponding orbital energies, we demonstrate that the correlation energy obtained from the approximate CCD method, after a finite number of fixed-point iterations over the amplitude equation, exhibits a finite-size error scaling as $\mathcal{O}(N^{-\frac{1}{3}}_k)$. Here $N_k$ is the number of discretization points in the Brillouin zone and characterizes the system size. Under additional assumptions ensuring the convergence of the fixed-point iterations, we demonstrate that the CCD correlation energy also exhibits a finite-size error scaling as $\mathcal{O}(N^{-\frac{1}{3}}_k)$. Our analysis shows that the dominant error lies in the coupled cluster amplitude calculation, and the convergence of the finite-size error in energy calculation can be boosted to $\mathcal{O}(N^{-1}_k)$ with accurate amplitudes. This also provides the first proof of the scaling of the finite-size error in the third order Møller-Plesset perturbation theory (MP3) for periodic systems.

97 MATHEMATICS AND COMPUTING↗

Investigation of MO x (M = Cr, Mn, Re, and Mo) coated stainless-steel electrodes for oxygen evolution reaction in natural seawater electrolysis

Seawater electrolysis is considered a potential strategy for large-scale of affordable H 2 production. However, poor durability of the anode for oxygen evolution reaction (OER) in natural seawater is a remaining concern due to chloride-induced reaction. Herein, the effect of various MO x (M = Mn, Cr, Re, and Mo) coated stainless steel (SS) electrodes on OER in direct natural seawater electrolysis was comprehensively studied. It is found that the Mo-coated SS electrode is superior to all others in terms of durability, followed by Re-coated SS, while the Cr and Mn-coated SS electrodes show the poorest durability. Additionally, the durability and activity of the Mo/SS electrode can be boosted remarkably in 1 M KOH/seawater compared to the natural seawater, resulting in an overpotential at 10 mA cm −2 decrease from 830 to 399 mV. Meanwhile, no degradation is observed at 1000 mA cm −2 for 100 h in 1 M KOH seawater, which is among the best stability, based on the literature review. Moreover, the improved durability and activity with Mo coating were extended to the Inconel 718 substrate, and around 40 % improvement in durability and 25 mV overpotential decrease at 10 mA cm −2 are observed, which indicates that Mo coating can be considered as a universal approach to improve the anode durability and activity. The improved performance with Mo coating may be attributed to the continuous Mo oxide layer formation or in situ generated MoO 4 2− in the OER process. In conclusion, this work provides a holistic strategy to enhance the anode durability and activity under harsh conditions, offering valuable insights for designing corrosion-resistant electrodes in direct seawater electrolysis.

Direct seawater electrolysis↗

Confined Ni-In intermetallic alloy nanocatalyst with excellent coking resistance for methane dry reforming

Carbon dioxide and methane are two main greenhouse gases which are contributed to serious global warming. Fortunately, dry reforming of methane (DRM), a very important reaction developed decades ago, can convert these two major greenhouse gases into value-added syngas or hydrogen. The main problem retarding its industrialization is the seriously coking formation upon the nickel-based catalysts. Herein, a series of confined indium-nickel (In-Ni) intermetallic alloy nanocatalysts (In x Ni@SiO 2 ) have been prepared and displayed superior coking resistance for DRM reaction. The sample containing 0.5 wt.% of In loading (In 0.5 Ni@SiO 2 ) shows the best balance of carbon deposition resistance and DRM reactivity even after 430 h long term stability test. The boosted carbon resistance can be ascribed to the confinement of core–shell structure and to the transfer of electrons from Indium to Nickel in In-Ni intermetallic alloys due to the smaller electronegativity of In. Additionally, both the silica shell and the increase of electron cloud density on metallic Ni can weaken the ability of Ni to activate C–H bond and decrease the deep cracking process of methane. The reaction over the confined InNi intermetallic alloy nanocatalyst was conformed to the Langmuir-Hinshelwood (L-H) mechanism revealed by in situ diffuse reflectance infrared Fourier transform spectroscopy (in-situ DRIFTS). This work provides a guidance to design high performance coking resistance catalysts for methane dry reforming to efficiently utilize these two main greenhouse gases.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

High-performance LiNi 0.8 Mn 0.1 Co 0.1 O 2 cathode by nanoscale lithium sulfide coating via atomic layer deposition

The commercialization of nickel-rich LiNi 0.8 Mn 0.1 Co 0.1 O 2 (NMC811) has been hindered by its continuous loss of practical capacity and reduction in average working voltage. To address these issues, surface modification has been well-recognized as an effective strategy. Different from the coatings reported in literature to date, in this work, we for the first time report a sulfide coating, amorphous Li 2 S via atomic layer deposition (ALD). Here, our study revealed that the conformal nano-Li 2 S coating shows exceptional protection over the NMC811 cathodes, accounting for the dramatically boosted capacity retention from ~11.6% to ~71% and the evidently mitigated voltage reduction from 0.39 to 0.18 V after 500 charge–discharge cycles. In addition, the Li 2 S coating remarkably improved the rate capability of the NMC811 cathode. Our investigation further revealed that all these beneficial effects of the ALD-deposited nano-Li 2 S coating lie in the following aspects: (i) maintain the mechanical integrity of the NMC811 electrode; (ii) stabilize the NMC electrode/electrolyte interface; and (iii) suppress the irreversible phase transition of NMC structure. Particularly, this study also has revealed that the nano-Li 2 S coating has played some unique role not associated with traditional non-sulfide coatings such as oxides. In this regard, we disclosed that the Li 2 S layer has reacted with the released O 2 from the NMC lattices, and thereby has dramatically mitigated electrolyte oxidation and electrode corrosion. Thus, this study is significant and has demonstrated that sulfides may be an important class of coating materials to tackle the issues of NMCs and other layered cathodes in lithium batteries.

36 MATERIALS SCIENCE↗

An epitaxial surface heterostructure anchoring approach for high-performance Ni-rich layered cathodes

Nickel-rich (Ni≥90%) layered oxides materials have emerged as a promising candidate for next-generation high-energy-density lithium-ion batteries (LIBs). However, their widespread application is hindered by structural fatigue and lattice oxygen loss. In this work, an epitaxial surface rock-salt nanolayer is successfully developed on the LiNi 0.9 Co 0.1 O 2 sub-surface via heteroatom anchoring utilizing high-valence element molybdenum modification. This in-situ formed conformal buffer phase with a thickness of 1.2nm effectively suppresses the continuous interphase side-reactions, and thus maintains the excellent structure integrity at high voltage. Furthermore, theoretical calculations indicate that the lattice oxygen reversibility in the anion framework of the optimized sample is obviously enhanced due to the higher content of O 2p states near the Fermi level than that of the pristine one. Meanwhile, the stronger Mo–O bond further reduces cell volume alteration, which improves the bulk structure stability of modified materials. Besides, the detailed charge compensation mechanism suggests that the average oxidation state of Ni is reduced, which induces more active Li + participating in the redox reactions, boosting the cell energy density. As a result, the uniquely designed cathode materials exhibit an extraordinary discharge capacity of 245.4 mAh g −1 at 0.1 C, remarkable rate performance of 169.3 mAh g −1 at 10 C at 4.5V, and a high capacity retention of 70.5% after 1000 cycles in full cells at a high cut-off voltage of 4.4V. Further, this strategy provides an valuable insight into constructing distinctive heterostructure on high-performance Ni-rich layered cathodes for LIBs.

25 ENERGY STORAGE↗

Ru-CoO heterostructured nanoparticles supported on nitrogen and sulfur codoped graphene nanosheets as effective electrocatalysts for hydrogen evolution reaction in alkaline media

Production of clean hydrogen energy from water splitting is vital for the future fuel industry, and nanocomposites have emerged as effective catalysts for the hydrogen evolution reaction (HER). In this study, Ru-CoO@SNG nanocomposites are prepared by controlled pyrolysis where Ru-CoO heterostructured nanoparticles are supported on nitrogen and sulfur codoped graphene oxide nanosheets. With a large surface area, the obtained composites exhibit a remarkable electrocatalytic activity toward HER in 1.0M KOH with an overpotential of only -90mV to reach the current density of 10 mA cm -2 , in comparison to -60mV for commercial Pt/C benchmark, along with high stability. Mechanistically, codoping of sulfur and nitrogen facilitates the dispersion of the nanoparticles, and the formation of Ru-CoO heterostructures increases the active site density, reduces the electron-transfer kinetics and boosts the catalytic performance. Further, results from this study highlight the unique potential of structural engineering in enhancing the electrocatalytic performance of heterostructured nanocomposites.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Projected network performance for next generation aerosol monitoring systems

Aerosol monitoring for radioactivity is a mature and proven technology. However, by improving key specifications of aerosol monitoring equipment, more samples per day can be collected and analyzed with the same minimum detectable concentrations as current systems. This work models hypothetical releases of 140 Ba and 131 I over a range of magnitudes corresponding to the inventory produced from the fission of about 100 g to 1 kiloton TNT-equivalent of 235 U. The releases occur over an entire year to incorporate the natural variability in atmospheric transport. Sampling equipment located at the 79 locations for radionuclide stations identified in the Comprehensive Nuclear-Test-Ban Treaty (CTBT) for the International Monitoring System are used to determine the detections of the individual releases. Alternative collection schemes in next generation equipment that collect 2, 3, or 4 samples per day, rather than the current 1 sample per day, would result in detections in many more samples at more stations with detections for a given release level. The authors posit that next generation equipment will result in increased network resilience to outages and improved source-location capability for lower yield source releases. The application of dual-detector and coincidence measurements to these systems would significantly boost sensitivity for some isotopes and would further enhance the monitoring capability.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

A large-scale comparison of Artificial Intelligence and Data Mining (AI&DM) techniques in simulating reservoir releases over the Upper Colorado Region

In recent years, the Artificial Intelligence and Data Mining (AI&DM) models have become popular tools in assisting various aspects of reservoir operation. However, the practical uses are still rarely reported. Comparison experiment of many AI&DM models over a large number of reservoir cases is particularly valuable to help reservoir operators first examine the usefulness and transferability of different AI&DM models, and then identify the most stable and reliable AI&DM model in assist of various decision-making processes. In this study, a total of 12 AI&DM models with different parameterizations and simulation scenarios are comprehensively tested out and compared in simulating the controlled reservoir outflows of 33 reservoir cases over the Upper Colorado Region, United States. Results show that the Random Forecast and the Long-Short-Term-Memory model could consistently derive the best statistical performance than other models under the baseline simulation scenario. The employed AI&DM models could obtain satisfactory statistical interquartile ranges (25–75%) between [0.6–0.9], [0.3–0.8], and [0.2–0.8], for CORR, NSE, and KGE measurements, respectively, and [1.5–6.5], [–15 to 20], and [0.5–8.5] for the normalized RMSE, PBIAS and RSR measurements, respectively. Results also show Multi-Layer Perceptron model and Extreme Gradient Boosting Tree Algorithm produced more stable and superior performance than other models under more complex input scenarios. We also found that the performance of different AI&DM models are closely relevant to the reservoir elevations, sizes, and functionalities. Discussions were made about the sensitivity of AI&DM models’ parameterizations and the key advantages of AI&DM models over the rule-based reservoir models. We further identify that the main advantage of AI&DM models is the flexibility in designing input structures, whereas the rule-based simulation model is rather limited. Future studies were suggested regarding the best way reservoir operators and researchers could use, select, and apply different AI&DM models in simulating reservoir releases under different natural and modeling environments. Finally, this comparison study also serves as a reference and a piece of groundwork for further promoting the practical uses of AI&DM models in assisting reservoir operation.

54 ENVIRONMENTAL SCIENCES↗

The Global LAnd Surface Satellite (GLASS) evapotranspiration product Version 5.0: Algorithm development and preliminary validation

An accurate estimation of spatially and temporally continuous global terrestrial evapotranspiration (ET) is essential in the assessment of surface energy, water and carbon cycles. The Global LAnd Surface Satellite (GLASS) ET product Version 4.0 (v4.0) based on the Bayesian model averaging (BMA) method was generated to estimate global terrestrial ET. However, certain uncertainty for the GLASS ET product v4.0 limits its application. In this study, we introduced the deep neural networks (DNN) merging framework to improve terrestrial ET estimation for GLASS ET product Version 5.0 (v5.0) generation by integrating five satellite-derived ET products [Moderate Resolution Imaging Spectroradiometer (MODIS) ET product (MOD16), Shuttleworth–Wallace dual-source ET product (SW), Priestley–Taylor-based ET product (PT-JPL), modified satellite-based Priestley–Taylor ET product (MS-PT) and simple hybrid ET product (SIM)]. We compared the performance of DNN method against other merging methods, including GLASS ET algorithm v4.0 (BMA), the gradient boosting regression tree (GBRT) method and the random forest (RF) method, based on 195 global eddy covariance (EC) flux towers covering observations from 2000 through 2015. Validations indicated that the DNN had the highest accuracy among four merging methods across different land cover types, yielding the highest average determination coefficients (R 2 , 0.62), root-mean-squared-error (RMSE, 24.1 W/m 2 ) and Kling–Gupta efficiency (KGE, 0.77) with a of 99% confidence interval. Compared with GLASS ET algorithm v4.0, the DNN improved on the R 2 by approximately 7% (p < 0.01) and the KGE by 10%. Based on the DNN, we then generated 8-day GLASS ET product v5.0 globally with a 1 km spatial resolution from 2001 to 2015 driven by GLASS vegetation and surface net radiation (R n ) datasets and Modern-Era Retrospective Analysis for Research and Applications, Version 2 (MERRA2) datasets. Finally, this global terrestrial ET product provides a valuable dataset for monitoring regional and global water resources and environmental changes.

54 ENVIRONMENTAL SCIENCES↗

Invariant surface elastic properties in FCC metals and their correlation to bulk properties revealed by machine learning methods

In this work, we present a combination of machine-learned models that predicts the surface elastic properties of general free surfaces in face-centered cubic (FCC) metals. These models are built by combining a semi-analytical method based on atomistic simulations to calculate surface properties with the artificial neural network (ANN) method or the boosted regression tree (BRT) method. The latter is also used to link bulk properties and surface orientation to surface properties. The surface elastic properties are represented by their invariants considering plane elasticity within a polar method. The resulting models are shown to accurately predict the surface elastic properties of seven pure FCC metals (Cu, Ni, Ag, Au, Al, Pd, Pt). The BRT model reveals the correlations between bulk and corresponding surface properties in terms of invariants, which can be used to guide the design of complex nano-sized particles, wires and films. Finally, by expressing the surface excess energy density as a function of surface elastic invariants, fast predictions of surface energy as a function of in-plane deformations can be made from these model constructs.

36 MATERIALS SCIENCE↗

Atomic-scale tuned interface of nickel-rich cathode for enhanced electrochemical performance in lithium-ion batteries

The Ni-rich layered LiNi 0.6 Mn 0.2 Co 0.2 O 2 (NMC6 22 ) is one promising cathode for lithium-ion batteries (LIBs), but suffers from poor cycling stability under high cutoff potentials. The performance degradation was reflected as capacity fading and voltage drop, having their roots in instable interface of NMC622. Aimed at improving interfacial stability, in this study, we deposited nanoscale ZrO 2 coatings conformally over NMC622 cathodes using atomic layer deposition (ALD). We found that, under a high cutoff voltage (4.5 V), the ALD ZrO 2 coatings evidently improved the performance of NMC622 cathode, showing better cyclability and higher sustainable capacity. In addition, the ALD coatings dramatically boosted the rate capability of NMC622. All these compelling performance results are ascribed to the atomic-scale tunable ZrO 2 coatings via ALD, which create stable interface and thereby inhibit unfavorable evolutions. In the study, we utilize a suite of characterization tools and various analyses to clarify the effects of ALD ZrO 2 coatings. This study will be helpful for improving the performance of nickel-rich cathodes via interfacial engineering using ALD.

25 ENERGY STORAGE↗

Hybrid data-driven and model-informed online tool wear detection in milling machines

Precision machining tool wear is responsible for low product throughput and quality. Monitoring the tool wear online is vital to prevent degradation in machining quality. However, direct real-time tool wear measurement is not practical. This paper presents residual-based anomaly detection models, combining a hybrid model comprised of a physics-based model and a data-driven model (a decision tree or a neural network) to predict signals of interest (e.g., power or forces) under nominal conditions, followed by Page’s cumulative sum test for detecting tool wear on-line using the computer numerical control machine measurements. The most informative features are ranked using dynamic programming and its approximation variants from real-time measurements and machine settings, such as the width of cut, depth of cut, feed rate and spindle speed, that serve as inputs to the predictive models. The baseline nominal model is incrementally updated with experimental data via a gradient boosted adaptation model to generate the residuals that account for discrepancies between the actual machine data under normal conditions and the baseline nominal model predictions. The hybrid model is validated against 20 Mazak milling machine experimental tests and one Haas run-to-failure experiment. The proposed anomaly detector is applied to synthetic data from simulations of the physics-based model at different operating conditions, measurement noise levels, and tool wear levels, and the methods were able to achieve an overall 92% accuracy in data with 1% noise. The anomaly detection methods based on hybrid model reduced the false alarms of either the data-driven or physical-based models alone, and are found to be capable of good online detection of tool wear.

42 ENGINEERING↗

Leakoff assessment of nanoparticle-stabilized CO 2 foams for fracturing applications

The leakoff of multiphase systems through porous media is a complicated process. In this study, we have designed an experimental setup that is used to assess the leakoff of the liquid and gas phase under pressurized conditions. The novelty of this study is that while most previous studies utilized fluid/gas in the aqueous phase, nanoparticles are introduced in this study, which formed a solid/fluid/gas multiphase system to boost foam performance and reduce leakoff. In the parametric experimental analysis, the effects of foam quality, core permeability, surfactant concentration, and polymer concentration on the dynamic and static leakoff rates of liquid and gas are evaluated. It was found that core permeability affects the leakoff of foam the most with a leakoff coefficient of up to 1.37015 $ft/\sqrt{min}$ for gas and up to 0.1056 $ft/\sqrt{min}$ for liquid under the experiment settings herein. The leakoff rate of gas is generally several magnitudes higher than that of the liquid. When CO 2 gas is present in the foam, the leakoff coefficient falls in the range between 0 and 1.37015 $ft/\sqrt{min}$ for gas, and between 0.0005 and 0.1056 $ft/\sqrt{min}$ for liquid. Finally, the methodology and results of this study shed light on the mechanistic understanding of the leakoff properties of multiphase systems and could be used to assist the design of foam fracturing for reservoir stimulation.

03 NATURAL GAS↗

α-U and ω-UZr 2 in neutron irradiated U-10Zr annular metallic fuel

Here, to develop metallic fuel with ultra-high burnup of 30%-40%, an annular U-10Zr fuel with 55% smear density was fabricated through a casting route and irradiated at the Advanced Test Reactor at Idaho National Laboratory. The annular fuel design also serves as a demonstration of the feasibility to replace sodium bond with a helium bond to benefit the geological disposal of irradiated fuel, cut the cost of fuel fabrication, and boost the overall metallic fuel economy. This paper reports the results from transmission electron microscopy (TEM) based post-irradiation examination of this fuel type irradiated to a burnup of 3.3% fissions per initial heave metal atoms for initial screening purpose. After irradiation, the initial U-10Zr separated into an a-U annular region and an UZr 2+x center region with nanoscale spinodal decomposed microstructure. Because of the provided large amount of coherent interface areas, the fission gas atoms and vacancies generated in UZr 2+x phase are possibly pinned at the interface areas, leading to 20 times smaller fission gas bubbles than those in the neighboring a-U. The large bubbles in a-U become connected and merged into large pores that provide fast release paths for fission gas which prevents further fuel swelling. The fuel center still has open space to accommodate further fuel swelling from solid fission products at higher burnup. Other neutron irradiation induced phase and microstructure change are also characterized and compared with traditional solid fuel designs.

36 MATERIALS SCIENCE↗

Highly efficient bifacial single-junction perovskite solar cells

Bifacial photovoltaics (PV) harvest solar irradiance from both their front and rear surfaces, boosting energy conversion efficiency to maximize their electrical power production. For single-junction perovskite solar cells (PSCs), the performance of bifacial configurations is still far behind that of their state-of-the-art monofacial counterparts. Here, in this paper, we report on highly efficient, bifacial, single-junction PSCs based on the p-i-n (or inverted) architecture. We used optical and electrical modeling to design a transparent conducting rear electrode for bifacial PSCs to enable optimized efficiency under a variety of albedo illumination conditions. The bifaciality of the PSCs was about 91%–93%. Under concurrent bifacial measurement conditions, we obtained equivalent, stabilized bifacial power output densities of 26.9, 28.5, and 30.1 mW/cm 2 under albedos of 0.2, 0.3, and 0.5, respectively. We further showed that bifacial perovskite PV technology has the potential to outperform its monofacial counterparts with higher energy yields and lower levelized cost of energy (LCOE).

14 SOLAR ENERGY↗

Insights into the rapid two-phase transport dynamics in different structured porous transport layers of water electrolyzers through high-speed visualization

In proton exchange membrane electrolyzer cells (PEMECs), maintaining efficient two-phase transport is one of the most important functions of porous transport layers (PTLs). To enhance the two-phase transport in PTLs, thin/titanium liquid/gas diffusion layers (TT-LGDLs) are introduced in PEMECs, and their difference from the conventional Ti felt PTLs are analyzed in-situ through high-speed and microscale visualization and electrochemical characterizations. The visualization results show that unfavorable large slugs can be greatly reduced in the PEMEC with a TT-LGDL compared to the PEMEC with a Ti felt PTL. More importantly, the recovery capability of water starvation with different PTLs is studied. After water starvation, the PEMEC with the TT-LGDL can recover the water starvation much more rapidly than the Ti felt cell, benefiting from its short and straight-through flow paths. Furthermore, the TT-LGDL tends to generate oxygen bubbles that are almost six times smaller and 236 times more frequently than the Ti felt PTL, indicating significantly boosted removal efficiency of produced oxygen and PEMEC performance. Finally, this study offers new insights into the dynamic processes of two-phase transport and the recovery capability of water starvation for different PTLs, which will provide valuable guidance for further optimization of PTLs and performance enhancement of PEMECs.

08 HYDROGEN↗

Infiltrated electrodes for metal supported solid oxide electrolysis cells

Metal-supported solid oxide cells (MSOCs) are an alternative to conventional solid oxide cells (SOCs) based on ceramic cermets, offering lower material costs and higher operational flexibility. In this study symmetric MSOCs with infiltrated electrodes are explored for steam electrolysis operation to understand the underlying operation and degradation principles and suggest a direction for future MSOCs development. Two different fuel electrode backbones are used: an electronically-conductive lanthanum strontium co-doped iron nickel titanate (LSFNT) infiltrated with cerium-gadolinium oxide (CGO), or an ionic conductive zirconia based backbone (10ScYSZ) infiltrated with Ni:CGO. At the oxygen side, the backbone is 10ScYSZ, which is infiltrated with lanthanum-strontium co-doped cobalt oxide (LSC), or praseodymium oxide as cobalt-free alternative for comparison. This study suggests that the backbone electronic conductivity is key for good electrochemical performance as well as for boosting cell durability. Highly electronically conductive nanoparticles, especially nickel, were observed to irreversibly agglomerate driven by thermal conditions, whereas CGO proved to be a very stable electrocatalyst. At the fuel side, CGO (LSFNT) electrode showed lower ASR and degradation rate than Ni:CGO(ScYSZ) configuration with measured values of 0.50 Ω cm2 and 11 %/1000 h (at 0.60 A/cm2), and 0.70 Ω cm2 and 26 %/1000 h (at 0.50 A/cm2) at 1.30 V, respectively (700 °C, 50 % steam in hydrogen at the fuel side and air at the oxygen electrode side, LSC(ScYSZ) oxygen electrode).

25 ENERGY STORAGE↗

Deconvoluting the impact of current collector structure and electrolyte selection on Coulombic efficiency of lithium metal anodes

Lithium metal batteries are regarded as a promising avenue for significantly boosting the gravimetric energy density of batteries, particularly for electric vehicles. However, the instability of the lithium metal anode continues to hinder performance. While 3D structured current collectors for lithium metal anodes have been frequently proposed as a solution, few studies explore the impact of these structures when combined with various electrolytes and the inclusion of a lithium reservoir within the structure. This study pairs four commercially available copper current collectors with four different electrolytes to assess how these factors influence cycling performance with a 4 mAh/cm2 lithium reservoir. Coulombic efficiency (CE) measurements revealed no statistically significant difference in CE across different current collectors within the same electrolyte. However, significant variations were noted when the current collector remained intact, and the electrolyte was changed. Although polarization, electrochemical impedance, and lithium morphology varied between structures and electrolytes, no consistent patterns emerged to suggest superior performance by any specific current collector structure. Therefore, the choice of structure appears inconsequential when a lithium reservoir is present, and efforts should focus on selecting and designing the electrolyte.

White, Julia↗