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NASA NTRS2010

Digital Microfluidics Sample Analyzer

Three innovations address the needs of the medical world with regard to microfluidic manipulation and testing of physiological samples in ways that can benefit point-of-care needs for patients such as premature infants, for which drawing of blood for continuous tests can be life-threatening in their own right, and for expedited results. A chip with sample injection elements, reservoirs (and waste), droplet formation structures, fluidic pathways, mixing areas, and optical detection sites, was fabricated to test the various components of the microfluidic platform, both individually and in integrated fashion. The droplet control system permits a user to control droplet microactuator system functions, such as droplet operations and detector operations. Also, the programming system allows a user to develop software routines for controlling droplet microactuator system functions, such as droplet operations and detector operations. A chip is incorporated into the system with a controller, a detector, input and output devices, and software. A novel filler fluid formulation is used for the transport of droplets with high protein concentrations. Novel assemblies for detection of photons from an on-chip droplet are present, as well as novel systems for conducting various assays, such as immunoassays and PCR (polymerase chain reaction). The lab-on-a-chip (a.k.a., lab-on-a-printed-circuit board) processes physiological samples and comprises a system for automated, multi-analyte measurements using sub-microliter samples of human serum. The invention also relates to a diagnostic chip and system including the chip that performs many of the routine operations of a central labbased chemistry analyzer, integrating, for example, colorimetric assays (e.g., for proteins), chemiluminescence/fluorescence assays (e.g., for enzymes, electrolytes, and gases), and/or conductometric assays (e.g., for hematocrit on plasma and whole blood) on a single chip platform.

Pollack, Michael G.↗

DOE OSTI2021

Stepwise Dynamic Calibration of a Hydromechanical Simulation Using Time-Lapse Vertical Seismic Profile

This study aims to develop a methodology for calibrating subsurface stress changes through time-lapse Vertical Seismic Profiling (VSP) integration. The selected study site is the 13-10A injector well within the ongoing CO2-EOR operation of the Farnsworth Field Unit. The Time-lapse VSP dataset carries the combined effects of fluid substitution and mean effective stress changes, thereby providing a dataset amenable for the calibration of production and injection-induced stress changes. The concept is similar to calibrating a reservoir simulation model in that the process honor real field data to set up an inverse problem. The solution optimizes the independent and impactful geomechanical parameters that replicate the observed time-lapse seismic velocity changes. This stress calibration is enabled by 4D geomechanical modeling and the VSP Integration workflow. This calibration benefits from extensive geological, geophysical and geomechanical characterization through 3D seismic data, geophysical well logs, and core assessed as part of the 1D MEM conducted on the 13-10A subject well. These data are used to develop a site-specific rock physics model. The Biot Gassmann workflow combines rock physics and reservoir simulation outputs to determine the fluid substitution contribution to seismic velocity change. Additionally, modeled seismic velocity attributed to mean effective stress are determined from the geomechanical simulation outputs, and the stress-velocity relationship developed from the ultrasonic seismic velocity measurements on the extracted Morrow B core. A penalty function is then formed between the modeled seismic velocities and the observed time-lapse VSP dataset. Four independent and impactful geomechanical parameters have been determined. These are the bulk modulus and shear modulus for zero porosity and the shear and compressional seismic velocity to mean effective stress derivatives. The dataset of numerous coupled hydromechanical- geomechanical simulation realizations is built by combining variations of the four stated geomechanical parameters. A machine learning-assisted workflow comprised of an artificial neural network and a particle swarm optimizer are used to converge on the optimal geomechanical parameters. The successful execution of this workflow has affirmed the suitability of acoustic time-lapse measurements for 4D-VSP geomechanical stress calibration pending measurable stress sensitivities within the anticipated effective stress changes and the availability of suitable and reliable datasets for petroelastic modeling.

02 PETROLEUM↗

DOE OSTI2023

Review and Summary of Oxide Thickness Data for Aluminum-Clad Spent Nuclear Fuel

The U.S. Department of Energy (DOE) owns a large inventory of aluminum-clad spent nuclear fuel (ASNF) in interim storage pending ultimate disposition, with more being generated by currently operating research reactors. Dry storage in sealed DOE Standard Canisters is being investigated as an approach for long-term interim storage and/or disposition in a repository for ASNF. A primary challenge for ASNF storage is the presence of aluminum (oxy)hydroxide layers formed on the cladding surfaces during water exposure in the reactor and in wet storage, which forms a reservoir of chemisorbed water not readily removed at low (<100°C) drying temperatures. Free, physisorbed, and chemisorbed water are all susceptible to radiolytic breakdown under irradiation and can release hydrogen gas. Identifying the likely range of (oxy)hydroxide loadings on ASNF that may be placed in dry storage will help to ensure that the impact of the (oxy)hydroxide is adequately accounted for while avoiding over conservatism and enable mitigation strategies to be implemented where needed. The current report summarizes information on (oxy)hydroxide thicknesses and characteristics from the literature and from recent measurements taken in the present research campaign. In general, corrosion studies have indicated that the corrosion and oxide buildup on aluminum are affected by numerous conditions, including pH, temperature and heat flux, coolant flowrates, irradiation (in-reactor vs. unirradiated tests), duration of water exposure, and the amount of oxide already on the surface. Some of these factors are interrelated (e.g., the local temperature, heat flux, and coolant flowrate). Observations of the impact of irradiation (in-reactor versus ex-reactor measurements) on corrosion and oxide thickness are mixed, but multiple studies indicate that there is a significant difference between in-reactor and ex-reactor corrosion kinetics, even when other operating conditions such as pH, flowrate, heat flux, etc., simulate those in a reactor.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

NASA NTRS2017

The Iodine Satellite (iSat) Propellant Feed System - Design and Demonstration

CUBESATS are relatively new spacecraft platforms that are typically deployed from a launch vehicle as a secondary payload, providing low-cost access to space for a wide range of end-users. These satellites are comprised of building blocks having dimensions of 10x10x10 cm3 and a mass of 1.33 kg (a 1-U size). While providing low-cost access to space, a major operational limitation is the lack of a propulsion system that can fit within a CubeSat and is capable of executing high Delta V maneuvers. This makes it difficult to use CubeSats on missions requiring certain types of maneuvers (i.e. formation flying, spacecraft rendezvous). Work has been performed investigating the use of iodine as a propellant for Hall-effect thrusters (HETs) that could subsequently be used to provide a high specific impulse path to CubeSat propulsion. One of the systems under development to support such a technology is the propellant feed system, which must be capable of storing solid iodine propellant, applying heat to sublime the stored solid into the vapor phase, and then control the flow of low-pressure gaseous iodine to both the thruster and cathode. In a test conducted in 2016, a first-generation iodine propellant feed system was integrated with a cathode and Hall thruster. While this test had to be terminated, the feed system in this first test was able to support both cathode and integrated cathode and thruster operation prior to the termination of the test. In the present paper, we describe work performed since that initial integrated test. The effort uses lessons learned from the previous integrated test, retiring risk associated with the iodine propellant feed system, answering open design-space questions, and demonstrating iodine flow control in an integrated system. The work is undertaken at both the component level and then at the integrated subsystem level to systematically improve the feed system design, improving the hardware fidelity so the appearance and operation of the system are as flight-like as possible. At the component level, the work focuses on the propellant tank, the feed system tubing, the valves used to control the flow to the cathode and thruster, and the heaters that maintain the temperature of the flowpaths and keep iodine from redepositing and clogging the system. Work on the propellant reservoir focuses on fabricating a tank that matches the geometry of the flight design, which allows for the identification of flight tank fabrication issues that may arise and permits thermal testing of a tank possessing the same size and thermal mass as the flight design, which can be used to anchor thermal modeling of the component. This is critical for finalizing the tank heater power requirements that feed into the heater design. All metallic materials in the feed system are hastelloy or Inconel, as these materials are resistant to chemical attack by the highly-reactive iodine vapor. The tubing in the iodine feed system must possess ports to permit a neutral gas purge of the system that clear impurities after iodine is loaded into the propellant tank. A procedure is discussed whereby these ports are crimped and sealed after the purge process is completed so as to not re-expose the iodine system to air. The valves are a critical component for control of the flow to the thruster and the cathode. Significant effort has gone into upgrading the materials of the valves to make them more resistant to chemical attack and into developing an understanding of the use of these valves during the startup and operation of the cathode and thruster. The heaters that line the entire feed system are designed to draw minimal power from the power processing unit (PPU) while still having the capacity to maintain all the feed system components at the temperatures required to discourage iodine deposition inside components downstream of the propellant tank exit. The heaters possess two separate resistive traces, giving the design redundancy should a failure occur in the primary heater circuit of one of the heater zones. The task of operating a feed system in conjunction with a thruster and cathode is undertaken in a series of sub-steps. The system is first assembled and operated on xenon gas, using the valves for cathode startup and thruster control based on measurement of the discharge current. After startup and control on xenon are demonstrated, the thruster will be transitioned to iodine operation, demonstrating thruster startup and feed system control while using a xenon-fed cathode. Finally, the last step is to integrate an iodine-compatible cathode with the system, demonstrate autonomous cathode start-up with open-loop control and thruster start-up with closed-loop control for multiple cycles.

Polzin, Kurt A.↗

DOE OSTI2024

Enhancing Fluid Flow Pressure and Saturation Prediction Accuracy and Reducing Uncertainty with Committee Machine – Illinois Basin Decatur Project (IBDP) as a Case Study

Presentation at the 17th International Conference on Greenhouse Gas Control Technologies GHGT-17 held in Calgary, Canada, October 20-24, 2024. Carbon capture and storage (CCS) is a way to play a critical role in the global transition to a low-emission economy. Current progress is hampered by a number of factors, among which the lack of risk-informed design tools and decision support frameworks is seen as a major roadblock. Significant interest exists in using artificial intelligence to accelerate CCS site feasibility studies, as well as to facilitate the permit application process. Existing works commonly train a single deep learning model. This work investigates the feasibility of using a conventional ensemble learning (committee machine) technique to further improve prediction accuracy. Ensemble-based algorithms generally improve over individual base learners in terms of robustness and accuracy. Deep ensembles, however, are time-consuming to create and train. A pragmatic question is whether small-sized ensembles may lead to prediction improvement. Here we evaluated the efficacy of an ensemble learning technique using the latent spectral model (LSM), an efficient deep neural operator algorithm, as base learners. Preliminary results, obtained using the Illinois Basin-Decatur Project (IBDP) carbon sequestration data/model, show that small-sized ensembles can improve prediction over the base learners, achieving prediction accuracy of ~1.6 psi root mean square error (RMSE) on pressure (relative the average reservoir pressure of 3150 psi), and less than 1.3% for saturation.

Sun, Alexander↗

DOE OSTI2025

RectifHydPlus: Forty Year Hydropower Generation Reanalysis for Conterminous United States, Version 1.1.

This dataset contains monthly hydropower net-generation totals for 590 plants (each >10 MW) across the conterminous United States (CONUS) from 1980 to 2019. RectifHydPlus v1.1 includes one harmonized table of historical monthly generation—backfilled with observed monthly values where available—and two companion tables: (i) an estimates-only version with no backfill and (ii) a hydrological-control version that removes the effects of capacity and operational change. Each table comprises 23,600 records (590 plants × 40 years). The dataset was developed to address temporal gaps and inconsistencies in publicly available hydropower generation data as available through EIA-923 survey reports. Each record includes a quality label denoting the underlying proxy—from best (direct reservoir releases) to weakest (pattern copied from similar years). By combining the agency-reported survey records with observed and simulated hydrologic releases, RectifHydPlus offers complete, quality-labeled monthly estimates suitable for trend analysis and generation of hydropower generation inputs for energy-water modeling.

Turner, Sean [Oak Ridge National Laboratory (ORNL)↗

NASA NTRS1976

Space electric power design study

The conversion of laser energy to electrical energy is discussed. Heat engines in which the laser heats the gas inside the engine through a window as well as heat engines in which the gas is heated by a thermal energy storage reservoir which has been heated by laser radiation are both evaluated, as well as the necessary energy storage, transmission and conversion components needed for a full system. Preliminary system concepts are presented and a recommended development program is outlined. It appears possible that a free displacer Stirling engine operating directly a linear electric generator can convert 65% of the incident laser energy into electricity.

Martini, W. R.↗

NASA NTRS1984

Growth of crystals from solutions in low gravity (A0139A)

The objective of the low gravity crystal growth experiments is to develop a novel solute diffusion method for growing single crystals. The experiments will utilize specially designed reactors with three or more compartments separated by valves to keep the reactant solutions and solvent separated until the apparatus reaches low gravity. There will be a mechanism for opening the valves automatically to initiate the diffusion and growth processes. The reactant reservoirs will be large enough to take advantage of the time provided by the Long Duration Exposure Facility (LDEF) flight. An array of several reactors will be mounted in a 12-in.-deep end center tray located on the Earth-facing end of the LDEF. Several reactors operating simultaneously will allow experimentation with more than one crystal growth system and/or variations of conditions for each. The reactors will be enclosed in a vacuum tight container and will be surrounded by thermal insulation. The temperature (approximately 35 deg C) will be regulated and any departures from the desired temperature will be recorded. Power requirements will be provided by LiSO2 batteries.

Lind, M. D.↗

NASA NTRS1983

Thermal modeling of the Shuttle Infrared Telescope Facility

The Shuttle Infrared Telescope Facility (SIRTF) is a cryogenically cooled telescope in the one-meter aperture class designed for sensing in the infrared from 2-200 microns. This facility is currently planned for multiple missions onboard the Space Shuttle with varying instrument complements. All components of the SIRTF within the field of view of the optics are cryogenically cooled. The baseline primary coolant is supercritical helium which is stored in an external tank and routed through the telescope-cooling the instruments, the optical components and the baffles. For detector cooling below 6 K, small reservoirs of superfluid helium (HeII) are provided. The SIRTF was thermally modeled on the SINDA computer program both for steady state and transient solutions. The analysis shows that the baseline configuration has a large capacity for growth in cryogen requirements. A proportional controller model was developed for transient operations. The control system maintained the optics within all prescribed temperature limits except for certain combinations of transients involving a large step change in the power dissipation in the secondary mirror assembly and/or when the primary mirror was assumed to be constructed of quartz. The baseline SIRTF will perform the mission for which it was designed.

Gier, H. L.↗

DOE OSTI2024

Enhancing Fluid Flow Pressure and Saturation Prediction Accuracy and Reducing Uncertainty with Committee Machine – Illinois Basin Decatur Project (IBDP) as a Case Study

This is the conference paper accompanying an oral presentation at the 17th International Conference on Greenhouse Gas Control Technologies GHGT-17 held in Calgary, Canada, October 20-24, 2024. Carbon capture and storage (CCS) is a way to play a critical role in the global transition to a low-emission economy. Current progress is hampered by a number of factors, among which the lack of risk-informed design tools and decision support frameworks is seen as a major roadblock. Significant interest exists in using artificial intelligence to accelerate CCS site feasibility studies, as well as to facilitate the permit application process. Existing works commonly train a single deep learning model. This work investigates the feasibility of using a conventional ensemble learning (committee machine) technique to further improve prediction accuracy. Ensemble-based algorithms generally improve over individual base learners in terms of robustness and accuracy. Deep ensembles, however, are time-consuming to create and train. A pragmatic question is whether small-sized ensembles may lead to prediction improvement. Here we evaluated the efficacy of an ensemble learning technique using the latent spectral model (LSM), an efficient deep neural operator algorithm, as base learners. Preliminary results, obtained using the Illinois Basin-Decatur Project (IBDP) carbon sequestration data/model, show that small-sized ensembles can improve prediction over the base learners, achieving prediction accuracy of ~1.6 psi root mean square error (RMSE) on pressure (relative the average reservoir pressure of 3150 psi), and less than 1.3% for saturation.

Sun, Alexander↗

DOE OSTI2023

Field Laboratory for Emerging Stacked Unconventional Plays in Central Appalachia

The goal of the Field Laboratory for Emerging Stacked Unconventional Plays (ESUP) in Central Appalachia project was to investigate and characterize the resource potential for multi-play production of emerging unconventional reservoirs in Central Appalachia. Project activities included drilling, logging and coring of a vertical characterization well drilled to basement to approximately 15,000 feet in depth. The data from drilling and well logs as well recovered core samples were used by the research team to support characterization of the geology and potential pay zones within the Nora Gas Field of southwestern Virginia and the greater Central Appalachian Basin. This project was led by Dr. Nino Ripepi of the Virginia Center for Coal and Energy Research (VCCER) in close collaboration with EnerVest Operating LLC (EnerVest). VCCER is housed in the Department of Mining and Minerals Engineering at Virginia Tech and was created by an Act of the Virginia General Assembly on March 30, 1977, as an interdisciplinary study, research, information, and resource facility for the Commonwealth of Virginia. EnerVest is a top tier, low-cost oil and natural gas company with a long history of traditional operating relationships with institutional investors as well as public and private companies. This report summarizes two major research activities: 1) Log and Core Analysis and 2) Numerical Modeling. Core analysis comprises the characterization efforts of the ESUP Field Laboratory and includes a discussion of the well logs run in the deep characterization wells, an initial analysis of those, the number, size and location of cores recovered, core testing and analysis done to date as well as plans for future analysis. Numerical modeling is comprised of seven major modeling efforts, including (1) Multiphysics shale transport modeling work, (2) the developed in-house compositional simulator studies, (3) reservoir modeling studies using GEM software, (4) fracture modeling work using EFRAC3D software and (5) numerical modeling efforts with ABAQUS software, (6) Numerical modeling efforts using FLAC3D and PFC3D, and (7) Automatic Machine Learning (AutoML) Studies.

02 PETROLEUM↗

DOE OSTI2024

CO 2 storage site characterization using ensemble-based approaches with deep generative models

Estimating spatially distributed properties such as permeability from available sparse measurements is a great challenge in efficient subsurface CO 2 storage operations. In this paper, a deep generative model that can accurately capture complex subsurface structure is tested with an ensemble-based inversion method for accurate and accelerated characterization of CO 2 storage sites. We chose Wasserstein Generative Adversarial Network with Gradient Penalty (WGAN-GP) for its realistic reservoir property representation and Ensemble Smoother with Multiple Data Assimilation (ES-MDA) for its robust data fitting and uncertainty quantification capability. WGAN-GP are trained to generate high-dimensional permeability fields from a low-dimensional latent space and ES-MDA then updates the latent variables by assimilating available measurements. Several subsurface site characterization examples including Gaussian, channelized, and fractured reservoirs are used to evaluate the accuracy and computational efficiency of the proposed method and the main features of the unknown permeability fields are characterized accurately with reliable uncertainty quantification. Furthermore, the estimation performance is compared with a widely-used variational, i.e., optimization-based, inversion approach, and the proposed approach outperforms the variational inversion method in several benchmark cases. We explain such superior performance by visualizing the objective function in the latent space: because of nonlinear and aggressive dimension reduction via generative modeling, the objective function surface becomes extremely complex while the ensemble approximation can smooth out the multi-modal surface during the minimization. This suggests that the ensemble-based approach works well over the variational approach when combined with deep generative models at the cost of forward model runs unless convergence-ensuring modifications are implemented in the variational inversion.

42 ENGINEERING↗

DOE OSTI2023

Coupled Investigation of Fracture Permeability Impact on Reservoir Stress and Seismic Slip Behavior

Our goal is to develop, apply and validate a holistic thermal, hydrologic, mechanical, and chemical (THMC) workflow that includes evaluation of induced seismic slip in EGS reservoirs. We will integrate experimental and modeling approaches to reduce parameter uncertainty and better predict/mitigate seismic hazard at EGS sites. Our novel approach couples 3D physics-based earthquake simulations with THMC models (THMc+E). This capability will enable improve engineering decisions at Utah-FORGE and move EGS operations toward repeatable, robust, economically viable, and socially accepted development. For example, our THMC+E models will predict circulation scenarios and related seismic hazard for a suite of flow rates and under uncertainty, thus enabling evaluation of optimal circulation strategy. Laboratory experiments will be performed to constrain key model parameters and Bayesian techniques will provide a probabilistic evaluation of parameters used in models. THMC+E simulations will enable exploration various circumstances that may hinder EGS success and develop mitigation strategies.

58 GEOSCIENCES↗

DOE OSTI2024

5-2428: Fracture Permeability Impact on Seismic Slip Behavior

58 GEOSCIENCES↗

NASA NTRS2000

Facility Designed and Built to Investigate the Combined Effects of Contaminant and Atomic Oxygen on a Light-Transmitting Surface

A need exists to investigate changes in the transparency of a light-transmitting surface during simultaneous exposure to a contaminant and an atomic oxygen (AO) flux. This mechanism may be responsible for the degradation of the light-transmitting surfaces of both photovoltaic cells and photodiodes currently in use on many low-Earth-orbit spacecraft. To address this need, researchers from the Electro-Physics Branch of the NASA Glenn Research Center at Lewis Field built such a test system within their AO beam facility. This facility produces an effective AO flux of 1.4 10(exp 16) atoms/sq cm/sec and contains a three-axis positioning system that provides the motion capability necessary for test operations. During testing, a target surface is held directly within the AO beam and close to two contaminant effusion cells. The effusion cells are shielded from the AO beam, and the outgassing contaminant is constrained to move across the target surface when heat is applied to either of the reservoirs. A light source is periodically moved over the target surface, and the transmitted light intensity is checked with a photodiode located below the target. This light source is also periodically checked with a separate photodiode, which is protected from contamination and AO exposure, to allow adjustments necessary to maintain a consistent light intensity.

Sechkar, Edward A.↗

DOE OSTI2025

Hydroboost

HydroBoost is the most realistic revenue optimization tool for the hybridization of hydropower and battery energy storage systems to date. The innovative representation of how operators actually schedule hydropower in practice results in more realistic predictions of revenue and operations. Unlike other optimization tools, HydroBoost generates forecast energy prices with uncertainty to use in the optimization. This allows HydroBoost to give users a range of potential revenue with an upper bound using the perfect foresight pricing and a lower bound using a naive persistence forecast model. Additional forecast can be generated and used in the optimization, such as additive models, random forest, and neural networks to give further insight into potential revenue. HydroBoost has been designed to be applicable for both run-of-river and reservoir storage sites. The primary focus is on the day-ahead market and requires year-long data with an hour time-step. All time-series input and constraints are contained in an Excel worksheet for convince. The user will run the forecasting generation first with a Python script to give the optimization model the necessary requirements. Next the optimization is ran using Julia and results are generated and stored into a directory as csv files. HydroBoost includes an additional module to generate figures based on the results of the optimization simulation. The results help analyze the results and users to draw insights into how the hydro and battery systems are operated and the revenue each is producing. Additionally, the difference between the perfect foresight model and models that include forecast can easily be inspected.

Phillips, TylerB. [Idaho National Laboratory (INL)↗

DOE OSTI2024

Simulation of Multiphase Flow and Poromechanical Effects Around Injection Wells in CO 2 Storage Sites

In geological CO 2 storage operations, wellbore deformations and leakage pathways formations can occur around injection and abandoned wells subjected to high rates and long-term CO 2 injection. To guide engineering design and prevent CO 2 leakage risks, a full understanding of the underlying physics and robust numerical models is necessary to evaluate the response of underground formations in the near wellbore region and in the reservoir. In this study, a multi-scale and multi-physics open-source simulator (GEOS) is used to simulate multiphase flow and poromechanical deformations over time in three dimensions. The governing equations for mechanical deformations of the rock body and multiphase compositional fluid flow within the rock matrix are solved with a fully coupled finite element and finite volume approach. The Drucker–Prager model with friction hardening is applied to simulate elastoplastic deformation and a multiphase fluid model with power-law correlations for relative permeability is used to model the migration of CO 2 plume, which are coupled with numerical implicit scheme. Simulation results are verified against multiple analytical solutions for multiphase flow and wellbore problems, thus demonstrating the accuracy of this advanced simulator. In two engineering applications, here we highlight the impact of elastoplastic deformation and coupled modeling for assessing induced displacements and stress perturbations, which are more pronounced in the near wellbore regions. This work focuses on short-term processes in the vicinity of injection wells where stress evolutions, rock deformations and multiphase compositional flow and transport are simulated jointly to ensure wellbore stability and prevent damage. This fully coupled geomechanical model can simulate multiphase flow and any associated poromechanical effects within the CO 2 storage site and in the surrounding formations. Such a large-scale, long-term, multi-physics simulation model is useful in many ways: it can guide operational decisions for CO 2 injection, assess the containment potential and risks of a site, and analyze the wellbore stability and integrity during and after CO 2 injection.

58 GEOSCIENCES↗

DOE OSTI2026

Cathode-Confined Polysulfide Retention-Release Reprograms Li 2 S Deposition in High-Loading Li–S Batteries

High-loading lithium-sulfur (Li-S) cells operated with lean electrolyte are limited by polysulfide crossover to Li metal and by transport-limited liquid-solid conversion that forms passivating Li 2 S films. Here, we show that a cathode-facing separator coating of carboxylated multiwalled carbon nanotubes acts as a cathode-confined polysulfide reservoir with intermediate binding. Early in discharge it captures newly generated polysulfides at the separator interface, suppressing shuttle reactions. As polysulfides are consumed, the reservoir buffers concentration gradients and feeds reactants back to the cathode, shifting Li 2 S deposition from burst-like film growth to progressive, three-dimensional, porous formation. Synchrotron XRD and S K-edge XANES, together with Scharifker–Hills nucleation analysis and depth-of-discharge EIS/DRT, substantiate this coupled transport–reaction control. With 4.3 mg S cm -2 and E/S = 5, cells reach 4.2 mAh cm -2 and retain 90% capacity over 100 cycles at 20 °C.

25 ENERGY STORAGE↗