Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “Reaction Rates”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 469 records · Page 26

Simulation of hardened cement degradation and estimation of uncertainty in predicted failure times with peridynamics

Modeling the degradation of cement-based infrastructure due to aqueous environmental conditions continues to be a challenge. In order to develop a capability to predict concrete infrastructure failure due to chemical degradation, here we created a chemomechanical model of the effects of long-term water exposure on cement paste. The model couples the mechanical static equilibrium balance with reactive–diffusive transport and incorporates fracture and failure via peridynamics (a meshless simulation method). The model includes fundamental aspects of degradation of ordinary Portland cement (OPC) paste, including the observed softening, reduced toughness, and shrinkage of the cement paste, and increased reactivity and transport with water induced degradation. This version of the model focuses on the first stage of cement paste decalcification, the dissolution of portlandite. Given unknowns in the cement paste degradation process and the cost of uncertainty quantification (UQ), we adopt a minimally complex model in two dimensions (2D) in order to perform sensitivity analysis and UQ. We calibrate the model to existing experimental data using simulations of common tests such as flexure, compression and diffusion. Then we calculate the global sensitivity and uncertainty of predicted failure times based on variation of eleven unique and fundamental material properties. We observed particularly strong sensitivities to the diffusion coefficient, the reaction rate, and the shrinkage with degradation. Also, the predicted time of first fracture is highly correlated with the time to total failure in compression, which implies fracture can indicate impending degradation induced failure; however, the distributions of the two events overlap so the lead time may be minimal. Extension of the model to include the multiple reactions that describe complete degradation, viscous relaxation, post-peak load mechanisms, and to three dimensions to explore the interactions of complex fracture patterns evoked by more realistic geometry is straightforward and ongoing.

36 MATERIALS SCIENCE↗

Kinetics and Mechanism of Tetravalent Cerium Extraction by Di-2-Ethylhexyl Isobutyramide (DEHiBA)

DEHiBA is a fully-incinerable, CHON extractant with a high selectivity for hexavalent actinides. However, as a recently-developed ligand, much remains unknown about its physical and chemical properties, including its extraction and phase disengagement rates. Here, we present data on the phase transfer kinetics of Ce(IV) extraction and stripping by both DEHiBA and TBP collected using microfluidic devices. Ce(IV) was selected as a surrogate for Pu(IV) and Np(IV) in the initial tests of the microfluidics system prior to testing with the actinides. Pseudo first-order reaction rate constants are determined for both systems, and the corresponding Damköhler numbers (Da) are calculated to establish whether the extraction and stripping processes are kinetically or diffusion controlled. The stoichiometry of the extracted Ce(IV)-DEHiBA complex is determined, and the phase disengagement properties under extraction conditions are assessed using the dimensionless dispersion number. A possible explanation for the favorable extraction of Ce(IV) by DEHiBA, which is known to poorly extract many tetravalent cations, is presented.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Predicted Reaction Mechanisms, Product Speciation, Kinetics, and Detonation Properties of the Insensitive Explosive 2,6-Diamino-3,5-dinitropyrazine-1-oxide (LLM-105)

2,6-Diamino-3,5-dinitropyrazine-1-oxide (LLM-105) is a relatively new and promising insensitive high-explosive (IHE) material that remains only partially characterized. IHEs are of interest for a range of applications and from a fundamental science standpoint, as the root causes behind insensitivity are poorly understood. In this work, we adopt a multitheory approach based on reactive molecular dynamic simulations performed with density functional theory, density functional tight-binding, and reactive force fields to characterize the reaction pathways, product speciation, reaction kinetics, and detonation performance of LLM-105. We compare and contrast these predictions to 1,3,5-triamino-2,4,6-trinitrobenzene (TATB), a prototypical IHE, and 1,3,5,7-tetranitro-1,3,5,7-tetrazoctane (HMX), a more sensitive and higher performance material. The combination of different predictive models allows access to processes operative on progressively longer timescales while providing benchmarks for assessing uncertainties in the predictions. We find that the early reaction pathways of LLM-105 decomposition are extremely similar to TATB; they involve intra- and intermolecular hydrogen transfer. Additionally, the detonation performance of LLM-105 falls between that of TATB and HMX. We find agreement between predictive models for first-step reaction pathways but significant differences in final product formations. Predictions of detonation performance result in a wide range of values, and one-step kinetic parameters show the similar reaction rates at high temperatures for three out of four models considered.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

( 6 Li, d) and ( 6 Li, t) reactions on 22 Ne and implications for s-process nucleosynthesis

We studied α cluster states in 26 Mg via the 22 Ne( 6 Li,dγ) 26 Mg reaction in inverse kinematics at an energy of 7 MeV/nucleon. States between E x = 4–14 MeV in 26 Mg were populated and relative α spectroscopic factors were determined. Some of these states correspond to resonances in the Gamow window of the 22 Ne(α,n) 25 Mg reaction, which is one of the main neutron sources in the astrophysical s-process. Using our new 22 Ne(α,n) 25 Mg and 22Ne(α,γ) 26 Mg reaction rates, we performed new s-process calculations for massive stars and asymptotic giant branch stars and compared the resulting abundances with the abundances obtained using other 22 Ne+α rates from the literature. We observe an impact on the s-process abundances up to a factor of three for intermediate-mass AGB stars and up to a factor of ten for massive stars. Additionally, states in 25 Mg at E x < 7.5 MeV are identified via the 22 Ne( 6 Li,t) 25 Mg reaction for the first time. We present the ( 6 Li, t) spectroscopic factors of these states and note similarities to the (d,p) reaction in terms of reaction selectivity.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Modeling Combustion Reaction ODEs with Neural Networks

The chemistry of combustion reactions is complex as it involves many species and reactions. In practice, such a system is often modeled computationally using an empirically derived chemical mechanism. Given the large range of reaction rates, the system is then time evolved using a stiff ODE solver. However, even when reduced chemical mechanisms are employed, the system can become computationally expensive for two-dimensional or three-dimensional systems. Such systems can also face problems with instability. As such, it is desirable to find a cheaper, stable alternative to solving the reaction system. Neural networks offer the potential to learn these reaction ODEs and time evolve a combustion reaction in a more cost-efficient manner than stiff ODE solvers. In this study, a variety of neural networks are trained on zero-dimensional Cantera simulations of methane combustion with varying initial conditions. Several predictive approaches as well as several neural network architectures (artificial neural network with dropout, ResNet, and Neural ODE) are compared in their ability to predict combustion trajectories. Promising models are then identified.

combustion kinetics↗

Plastic-waste hydrogenolysis over two-dimensional MXene-supported ruthenium catalysts with tunable interlayer spacing

The hydrogenolysis of plastics is limited by active-site inaccessibility and inefficient mass transport of bulky polymer chains. To overcome these challenges, this work developed two-dimensional MXene-supported Ru (Ru@MXene) catalysts. Lyophilization of a solution containing dispersed MXene sheets and Ru precursors enabled the confinement of Ru species within the MXene interlayers, which act as pillars to expand the interlayer spacing. Building on this, a silica-pillared MXene-supported Ru (Ru@P-MXene) with even larger interlayer spacing exhibited a reaction rate of 914.9 g C5–C35 g Ru –1 h –1 for the hydrogenolysis of low-density polyethylene (LDPE) into valuable liquid chemicals (e.g., C 5 –C 35 ). A comparison of product yields between Ru@P-MXene and Ru@MXene suggests that elongated Ru particles confined within the MXene support expose their side facets for the reaction. In conclusion, this work demonstrates a new application of MXene in thermochemical catalysis, offering a solution to the challenges of active-site accessibility, mass transport, and reaction confinement in chemical plastic upcycling.

2D materials↗

The γ -process nucleosynthesis in core-collapse supernovae

The γ-process nucleosynthesis in core-collapse supernovae is generally accepted as a feasible process for the synthesis of neutron-deficient isotopes beyond iron. However, crucial discrepancies between theory and observations still exist: the average yields of γ-process nucleosynthesis from massive stars are still insufficient to reproduce the solar distribution in galactic chemical evolution calculations, and the yields of the Mo and Ru isotopes are a factor of ten lower than the yields of the other γ-process nuclei. We investigate the γ-process in five sets of core-collapse supernova models published in the literature with initial masses of 15, 20, and 25 M ⊙ at solar metallicity. We compared the γ-process overproduction factors from the different models. To highlight the possible effect of nuclear physics input, we also considered 23 ratios of two isotopes close to each other in mass relative to their solar values. Further, we investigated the contribution of C–O shell mergers in the supernova progenitors as an additional site of the γ-process. Our analysis shows that a large scatter among the different models exists for both the γ-process integrated yields and the isotopic ratios. We find only ten ratios that agree with their solar values, all the others differ by at least a factor of three from the solar values in all the considered sets of models. The γ-process within C–O shell mergers mostly influences the isotopic ratios that involve intermediate and heavy proton-rich isotopes with A > 100. We conclude that there are large discrepancies both among the different data sets and between the model predictions and the solar abundance distribution. More calculations are needed; particularly updating the nuclear network, because the majority of the models considered in this work do not use the latest reaction rates for the γ-process nucleosynthesis. Moreover, the role of C–O shell mergers requires further investigation.

79 ASTRONOMY AND ASTROPHYSICS↗

Development of Scalable Reactive Transport Framework for PFAS

Research on PFAS chemicals is extensive and covers all aspects, including analytical quantification, determination of properties, toxicology, ex situ treatment, and in situ remediation. PFAS chemicals are very stable and thus persistent/recalcitrant in the environment. Although there are many unknowns about PFAS chemicals, degradation pathways, reaction rates, etc., many different sorption, oxidation, reduction, biological, and innovative treatment approaches are being developed. Sorption with activated carbon is currently the only fully available in situ treatment technology for PFAS-impacted groundwater. Given the wide array of PFAS chemicals and transformation products, remediation may need multi-step treatment trains to fully address the PFAS contamination. The work here provides kinetic reaction modules that represent an initial cut at functionality representing PFAS migration and reaction in groundwater aquifer flow and transport models. One reaction kinetics module provides a method to model kinetically limited adsorption using a mass transfer model. The second reaction module represents biological transformation of 8:2 FTOH and daughter species, illustrating how a complex reaction pathway network can be represented. Both reaction modules allow for spatially variable parameter values so that a variety of remediation approaches (e.g., a PRB or volumetric treatment or variations in geochemical conditions) can be simulated. The intent with these PFAS reaction modules is to provide tools for practitioners to aid in the selection, design, and assessment of potential in situ PFAS remediation strategies. It is anticipated that, as PFAS remediation technologies and scientific understanding advances, these modules would be refined or replaced to match new knowledge.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Developing the Science Basis for Understanding Polymer Encapsulant Degradation Mechanisms: DuraMAT 2.0 Final Project Report

Polymeric encapsulants are essential materials in photovoltaic modules, protecting sensitive electronics from the environment while providing mechanical integrity to the multilayered assembly. However, these polymeric materials are susceptible to degradation processes driven by the ingress of environmental species, ultraviolet radiation, thermal stresses, and mechanical loading. In this study, we employ a combined atomistic simulation and accelerated aging experimental approach to study the molecular-scale mechanisms of encapsulant degradation. Classical molecular dynamics simulations quantify the diffusion of environmental and degradation species through the polymer matrix, producing composition-specific diffusion coefficients. Reactive simulations characterize activation energy barriers and reaction rate constants for key chemical pathways. In parallel, thermal-desorption analyses coupled with mass spectrometry monitor the emergence and concentration profiles of degradation products under controlled stressor conditions. By integrating simulation and experiment, we establish quantitative correlations between polymer composition, species diffusivity, and chemical reactivity. We anticipate that these relations and quantitative values could serve as high-fidelity inputs to reaction-diffusion models, enabling physics-informed lifetime predictions and guiding the design of more durable encapsulant materials for solar energy applications.

36 MATERIALS SCIENCE↗

Isolated Metal Sites in Cu–Zn–Y/Beta for Direct and Selective Butene-Rich C 3+ Olefin Formation from Ethanol

Direct and selective production of C 3+ olefins from bioethanol remains a critical challenge and important for the production of renewable transportation fuels such as aviation biofuels. In this study, we report a Cu–Zn–Y/Beta catalyst for selective ethanol conversion to butene-rich C 3+ olefins (88% selectivity at 100% ethanol conversion, 623 K), where the Cu, Zn, and Y sites are all highly dispersed. The ethanol-to-butene reaction network includes ethanol dehydrogenation, aldol condensation to crotonaldehyde, and hydrogenation to butyraldehyde, followed by further hydrogenation and dehydration reactions to form butenes. Cu sites play a critical role in promoting hydrogenation of the crotonaldehyde C═C bond to form butyraldehyde in the presence of hydrogen, making this a distinctive pathway from crotyl alcohol-based ethanol-to-butadiene reaction. Reaction rate measurements in the presence of ethanol and acetaldehyde (543 K, 12 kPa ethanol, 1.2 kPa acetaldehyde, 101.9 kPa H 2 ) over monometallic Zn/Beta and Y/Beta catalysts indicate that Y sites have higher C–C coupling rates than over Zn sites (initial C–C coupling rate, 6.1 × 10 –3 mol mol Y –1 s –1 vs 1.2 × 10 –3 mol mol Zn –1 s –1 ). Further, Lewis-acidic Y-site densities over Cu–Zn–Y/Beta with varied Y loadings are linearly correlated with the initial C–C coupling rates, suggesting that Lewis-acidic Y sites are the predominant sites that catalyze C–C coupling in Cu–Zn–Y/Beta catalysts. Control experiments show that the dealuminated Beta support is important to form higher density of Lewis-acidic Y sites in comparison with other supports such as silica, or deboronated MWW despite similar atomic dispersion of Y sites and Y–O coordination numbers over these supports, leading to more than 9 times higher C–C coupling rate per mole Y over dealuminated Beta relative to other supports. This study highlights the significance of unique combination of metal sites in contributing to the selective valorization of ethanol to C 3+ olefins, motivating for exploring multifunctional zeolite catalysts, where the presence of multiple sites with varying reactivities and functions allows for controlling the predominant molecular fluxes toward the desired products in complex reactions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Polaritonic Bright and Dark States Collectively Affect the Reactivity of a Hydrolysis Reaction

Vibrational strong coupling (VSC) has emerged as a means for modifying chemical reactivity. Despite the intriguing discoveries and progresses in the field, the precise mechanisms that govern polaritonic chemistry still deserve further interrogation. Herein, we use the hydrolysis of ammonia borane in D 2 O as an exemplary reaction and systematically investigate the influence of VSC on its reactivity. Experimental evidence of the coexistence of a resonant effect and reaction acceleration is observed in this system. In particular, we find that when the O-D stretching mode of D 2 O is strongly coupled to a cavity mode, reaction acceleration is observed. The reaction rate acceleration factor, mu, is consistently observed to be dependent on the coupling conditions between the vibrational and cavity modes, and reaches a minimum at zero mode detuning, suggesting that a resonant effect is likely in play. In addition, we find that mu decreases with an increasing Rabi splitting. Based on these experimental findings, we propose that the overall influence of VSC on this reaction is likely determined collectively by the polaritonic bright and dark states. In conclusion, these findings could help shed new light on the intricate effects of VSC on ground-state reaction landscapes.

Rabi splitting↗

New measurement of the E c.m . = 323 keV resonance in the 19 F(p,γ) 20 Ne reaction

At temperatures below 0.1 GK, the 19 F(p, γ) 20 Ne reaction is the only breakout path out of the CNO cycle. Experimental studies of this reaction are challenging from a technical perspective due to copious γ -ray background from the far stronger 19 F(p, α) 16 O reaction channel. Here, we present the first inverse kinematics study of the 19 F(p, γ) 20 Ne reaction, in which we measure the strength of the 323-keV resonance. We find a strength value of ωγ = $3.3$$^{+1.1}_{–0.9}$ meV, which is a factor of two larger than the most recent previous study. Here, the discrepancy is likely the result of a direct to ground state transition which previous studies were not sensitive to. We also observe the transition to the first 2 – state, which has not been observed for this resonance in previous studies. A new thermonuclear reaction rate is calculated and compared with the literature.

20 ≤ A ≤ 38↗

Measurement of the Ne 18 ( α , p ) Na 21 reaction with the ANASEN active-target detector system at E c . m . = 2.5 – 4 MeV

The 18 Ne(α,p) 21 Na reaction plays a significant role in Type-I X-ray bursts. It is a major path in the breakout from the hot-CNO cycles to the synthesis of heavier elements in the αp- and rp-processes. An experiment to determine the cross section of this reaction was performed with the ANASEN active-target detector system, determining the cross section at energies between 2.5 and 4 MeV in the center-of-mass frame. The measured cross sections for reactions populating the ground state in 21 Na are consistent with results obtained from the time-inverse reaction, but significantly lower than the previously published experimental data of direct measurements. The total cross sections are also compared with those derived from indirect methods and statistical-model calculations. Furthermore, this experiment establishes a new experimental data set on the excitation function of the 18 Ne(α,p) 21 Na reaction, revealing the significance of the excited states' contributions to the total reaction cross section and allowing us to separate the contribution of the (α,2p) reaction. The impact of the measured cross section on thermal reaction rates is discussed.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Catalight─An Open-Source Automated Photocatalytic Reactor Package Illustrated through Plasmonic Acetylene Hydrogenation

An open-source and modular Python package, Catalight, is developed and demonstrated to automate (photo)catalysis measurements. (Photo)catalysis experiments require studying several parameters to evaluate performance, including the temperature, gas flow rate and composition, illumination power, and spectral profile. Catalight orchestrates measurements over this complicated parameter space and systematically stores, analyzes, and visualizes the results. To showcase the capabilities of Catalight, we perform an automated apparent activation barrier measurement of acetylene hydrogenation over a plasmonic AuPd catalyst on an Al 2 O 3 support, simultaneously varying laser power, wavelength, and temperature in a multiday experiment controlled by a simple Python script. Our chemical results unexpectedly show an increased activation barrier upon light excitation, contrary to previous findings for other plasmonic reactions and catalysts. We show that the reaction rate order with respect to both acetylene and hydrogen remains unchanged upon illumination, suggesting that molecular surface coverage is not changed by light. By analyzing the inhomogeneity of the laser-induced heating, we attribute these results to a partial photothermal effect combined with a photochemical/hot electron-driven mechanism. In conclusion, our findings highlight the capabilities of a new experiment automation tool; explore the photocatalytic mechanism for an industrially relevant reaction; and identify systematic sources of error in canonical photocatalysis experimental procedures.

Catalysts↗

Elucidation of the Roles of Water on the Reactivity of Surface Intermediates in Carboxylic Acid Ketonization on TiO 2

The effects of water on the carboxylic acid ketonization reaction over solid Lewis-acid catalysts were examined by nuclear magnetic resonance (NMR) spectroscopy, diffuse reflectance infrared Fourier transform spectroscopy (DRIFTS), temperature-programmed desorption (TPD), and kinetic measurements. Acetic acid and propanoic acid were used as model compounds, and P25 TiO 2 was used as a model catalyst to represent the anatase TiO 2 since the rutile phase only contributes to <2.5% of the overall ketonization activity of P25 TiO 2 . The kinetic measurement showed that introducing H 2 O vapor in gaseous feed decreases the ketonization reaction rate by increasing the intrinsic activation barrier of gas-phase acetic acid on anatase TiO 2 . Quantitative TPD of acetic acid indicated that H 2 O does not compete with acetic acid for Lewis sites. Instead, as indicated by combined approaches of NMR and DRIFTS, H 2 O associates with the adsorbed acetate or acetic acid intermediates on the catalyst surface and alters their reactivities for the ketonization reaction. There are multiple species present on the anatase TiO 2 surface upon carboxylic acid adsorption, including molecular carboxylic acid, monodentate carboxylate, and chelating/bridging bidentate carboxylates. The presence of H 2 O vapor increases the coverage of the less reactive bridging bidentate carboxylate associated with adsorbed H 2 O, leading to lower ketonization activity on hydrated anatase TiO 2 . In conclusion, surface hydroxyl groups, which are consumed by interaction with carboxylic acid upon the formation of surface acetate species, do not impact the ketonization reaction.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Evaluating large scale aqueous organic redox flow battery performance with a hybrid numerical and machine learning framework

Aqueous organic redox flow battery (AORFB) is a promising cost-competitive technology for large-scale energy storage. Among existing work, the dihydroxyphenazine (DHP)-based AORFB has demonstrated high energy density and low-capacity degradation in 10 cm$^2$ cells during lab tests. However, its commercial-scale performance in more complex environments remains unknown, posing a barrier to commercialization. To address this gap, this work presents a comprehensive performance evaluation of a 780 cm$^2$ DHP-based AORFB by combining a physics-based numerical model, machine learning (ML)-based surrogate models, and ML-derived sensitivity quantification. Specifically, we first select 12 key battery parameters that include 10 physicochemical and 2 operation quantities, then select 6 performance metrics that include energy efficiency (EE), discharging capacity, charging energy, and power losses due to concentration, activation, and ohmic over-potentials. With such selection, 12800 combinations of the 12 parameters are subsequently generated using the Latin Hypercube Sampling method. Such combinations, together with 38 pre-defined State of Charge, are then integrated to a validated AORFB model developed in COMSOL to compute the performance metrics. With both input parameters and performance metrics, 60 deep neural network (DNN) surrogate models are then trained to approximate the relationship between the 10 physicochemical quantities and 6 performance metrics at each flow rate and current density. Sensitivity scores are then calculated based on the DNN models. Two additional sensitivity analysis tools, i.e., MARS, and SHAP, are also used to cross-validate the sensitivity scores from the DNN. The results demonstrate that 1) the standard potential ranks first in controlling EE and charging energy, 2) the membrane conductivity is most critical for power loss and EE, and 3) specific area and reaction rate control activation power loss.

25 ENERGY STORAGE↗

A hybrid numerical and machine learning framework for evaluating the performance of a 780 cm 2 aqueous organic redox flow battery

Aqueous organic redox flow battery (AORFB) is a promising cost-competitive technology for large-scale energy storage. Among existing work, the dihydroxyphenazine (DHP)-based AORFB has demonstrated high energy density and low capacity degradation in 10 cm2 cells during lab tests. However, its commercial-scale performance in more complex environments remains unknown, posing a barrier for commercialization. To address this gap, this work presents a comprehensive performance evaluation of a 780 cm 2 DHP-based AORFB by combining physics-based numerical model, machine learning (ML)-based surrogate models, and ML-derived sensitivity quantification. Specifically, we first select 12 key battery parameters that include 10 physicochemical quantities and 2 operation quantities, then select 6 performance metrics that include energy efficiency (EE), discharging capacity, charging energy, and power losses due to concentration, activation, and ohmic over-potentials. With such selection, 12800 combinations of the 12 parameters are subsequently generated using the Latin Hypercube Sampling method. These combinations, together with 38 pre-defined State of Charge, are then integrated to a validated AORFB model developed in COMSOL to compute the performance metrics. With both input parameters and performance metrics, 60 deep neural network (DNN) surrogate models are then trained to approximate the relationship between the 10 physicochemical quantities and 6 performance metrics at each flow rate and current density. Sensitivity scores are then calculated based on the DNN models. Two additional sensitivity analysis tools, i.e., MARS, and SHAP, are also used to cross-validate the sensitivity scores from the DNN. The results demonstrate that 1) the standard potential ranks the first in controlling EE and charging energy, 2) the membrane conductivity is most critical for power loss and EE, and 3) specific area and reaction rate control activation power loss.

25 ENERGY STORAGE↗

Identification and Catalysis of the Potential-Limiting Step in Lithium-Sulfur Batteries

The Li-S chemistry is thermodynamically promising for high-density energy storage but kinetically challenging. Over the past few years, many catalyst materials have been developed to improve the performance of Li-S batteries and their catalytic role has been increasingly accepted. However, the classic catalytic behavior, i.e., reduction of reaction barrier, has not been clearly observed. Crucial mechanistic questions, including what specific step is limiting the reaction rate, whether/how it can be catalyzed, and how the catalysis is sustained after the catalyst surface is covered by solid products, remain unanswered. Herein, we report the first identification of the potential-limiting step of Li-S batteries operating under lean electrolyte conditions and its catalysis that conforms to classic catalysis principles, where the catalyst lowers the kinetic barrier of the potential-limiting step and accelerates the reaction without affecting the product composition. After carefully examining the electrochemistry under lean electrolyte conditions, we update the pathway of the Li-S battery reaction: S 8 solid is first reduced to Li 2 S 8 and Li 2 S 4 molecular species sequentially; the following reduction of Li 2 S 4 to a Li 2 S 2 -Li 2 S solid with an almost constant ratio of 1:4 is the potential-limiting step; the previously believed Li 2 S 2 -to-Li 2 S solid-solid conversion does not occur; the recharging reaction is relatively fast. We further demonstrate that supported cobalt phthalocyanine molecules can effectively catalyze the potential-limiting step. After Li 2 S 2 /Li 2 S buries the active sites, it can self-catalyze the reaction and continue driving the discharging process.

25 ENERGY STORAGE↗