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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.
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IR spectroscopy of a carbon–deuterium vibrational probe reveals that binding of the redox partner induces significant strengthening of the Cu-Cys89 bond in plastocyanin.
An ultra-stable reference electrode with novel design has been developed for scaled all-vanadium redox flow batteries, which demonstrates high accuracy and long-term stability over 500 charge–discharge cycles.
This report describes the first gram-scale synthesis of a nanocage that can host fullerenes (C 60 and C 70 ). The redox properties of the fullerenes are preserved in this host, enabling characterization of complexes with fulleride anions and dianions.
The use of sulfone-based redox mediators in electrocatalytic CO 2 reduction by Cr-centered complexes enhances the turnover frequencies at lower overpotentials via inner-sphere electron transfer and pancake bonding.
We highlight the status of, and propose future approaches for, rheological, electrochemical, and spectroscopic characterization of concentrated redoxmer electrolytes for energy storage, with an emphasis on nonaqueous redox flow batteries.
A novel simplicity-biased molecular structure generation method and Bayesian optimization based active learning have been used to discover a new class of heterocyclic molecules for organic non-aqueous redox flow batteries.
Metal atom lability from a well-defined bimetallic cluster was canvassed as a function of ligand substitution, redox chemistry, and group transfer processes.
QSPR analyses can be used to identify useful descriptors leading to statistical models for membrane crossover. This data-driven approach can be used to evaluate ROMs for asymmetric non-aqueous redox flow batteries.
An in-depth study of “Li 4 Mn 2 O 5 ”, a nanocomposite of Li 2 O and Li 4-x Mn 2 O 5 with a disordered rock salt structure (LMO), was conducted to determine the origins of the observed anomalously high charge and discharge capacity in lithium cells, which can exceed 350 mA h g -1 . Using soft and hard X-ray absorption spectroscopy (XAS), mapping of resonant inelastic X-ray scattering (mRIXS), and X-ray Raman spectroscopy (XRS), it was determined that electrochemical decomposition of Li 2 O upon charge and reduction of Mn to below 3+ during discharge is responsible for the capacities that are observed, with no evidence of contributions from reversible oxygen redox. Here, the over-reduction is exacerbated when charging limits of 4.5–4.8 V are used due to side reactions between electrolytic solution and the highly oxidized active material. These side reactions result in dissolution of Mn at room temperature and release of oxygen and other gases during initial cycles, which, in turn, cause rapid capacity fading. This is accompanied by evolution of the voltage profile upon cycling towards one that resembles that of manganese oxide spinels. The cycling behavior can be improved somewhat by reducing the upper voltage limit, although this results in a diminishment of the discharge capacities below 200 mA h g -1 . By adding various amounts of spinel LiMn 2 O 4 during synthesis, it was possible to produce LMOs with rock salt structures having significantly improved cycling behavior but still having capacities in excess of 250 mA h g -1 . An optimized modified material also exhibits better rate capability and much less gas evolution during initial cycles than the unmodified LMO. Interestingly, as-made modified materials generally exhibited lower than expected average Mn oxidation states attributable to oxygen loss during the synthesis process, as well as higher capacities than expected based on their manganese contents. The oxygen loss during processing may reduce the activity of the remaining oxygen and account for the lower reactivity of the spinel-modified material.
Solid-state sodium-metal batteries assembled with a composite solid-electrolyte separator and Na 0.72 Li 0.24 Mn 0.75 Si 0.01 O 2 cathode, utilizing reversible cationic (Mn) and anionic (O) redox, achieve high initial specific capacity of 180 mA h g −1 .
The activity of co-electrocatalytic CO 2 reduction can be optimized when the redox mediator and metal complex are modified to minimize the difference in their reduction potentials.
A new family of Isothermal, redox-activated CO 2 sorbents were successfully developed using a high-throughput combinatorial approach to facilitate the generation of green hydrogen from biogenic carbonaceous feedstocks.
This study systematically investigates the impact of increased upper limit voltage in the reliability and degradation of a scaled vanadium redox flow battery over long-term testing (500 cycles).
Redox-electrodes are designed to selectively bind platinum group metals by auto-oxidation, and release them electrochemically. The platform can efficiently recover PGMs from catalytic converter leachates, and contribute to energy-efficient technologies for materials recycling.
Fe was substituted into the anionic redox-active layered transition metal oxide (TMO) Na 2 Mn 3 O 7 lattice, which contains ordered TM vacancies in the TMO layer, improving the electrochemical performance. Excavator icon by FAAZT Creative/Adobe Stock.
This research aims to advance the field of vanadium redox flow batteries (VRFBs) by introducing a pioneering approach to optimize the microstructural characteristics of carbon cloth electrodes.
Volumetrically unbalanced compositionally symmetric cell cycling with potentiostatic (CV) or galvanostatic-with-potential-hold (CCCV) protocols is a rigorous technique for evaluating the calendar lifetime of reactants for redox flow batteries. Here, we evaluate the influence of reactant crossover through the membrane on symmetric cell cycling behavior. We tested symmetric cells of anthraquinone disulfonic acid (AQDS) with Nafion membranes of varied thickness and manufacture (NR211, NR212, N115, and N117, ranging 25–183 μm). Membranes were tested both as-received and pretreated with a common procedure of soaking in water at elevated temperature and then in dilute hydrogen peroxide. We found no significant difference in capacity fade rates of symmetric cells with any of the membranes as-received, indicating a negligible influence of crossover. However, we observed increased capacity fade with increased permeability through pretreated membranes. Supported by zero-dimensional modeling and operando UV-vis spectrophotometry, we propose a mechanism for net crossover in AQDS symmetric cells based on a higher time-averaged concentration of quinhydrone dimers in the non-capacity limiting side (NCLS) compared to the capacity limiting side (CLS), driving net crossover of AQDS reactants out of the CLS. Further, we illustrate other hypothetical scenarios of net crossover using the zero-dimensional model. Overall, many membrane–electrolyte systems used in symmetric cell studies have sufficiently low crossover flux as to avoid the influence of crossover on capacity fade, but under conditions of higher crossover flux, complex interactions of crossover and chemical reactions may result in diverse capacity fade trajectories, the mechanisms of which may be untangled with operando characterization and modeling.
Traditional trial-and-error methods for materials discovery are inefficient to meet the urgent demands posed by the rapid progression of climate change. This urgency has driven the increasing interest in integrating robotics and machine learning into materials research to accelerate experimental learning. However, idealized decision-making frameworks to achieve maximum sampling efficiency are not always compatible with high-throughput experimental workflows inside a laboratory. For multi-step chemical processes, differences in hardware capacities can complicate the digital framework by introducing constraints on the maximum number of samples in each step of the experiment, hence causing varying batch sizes in variable selection within the same batch. Therefore, designing flexible sampling algorithms is necessary to accommodate the multi-step synthesis with practical constraints unique to each high-throughput workflow. In this work, we designed and employed three strategies on a high-throughput robotic platform to optimize the sulfonation reaction of redox-active molecules used in flow batteries. Our strategies adapt to the multi-step experimental workflow, where their formulation and heating steps are separate, causing varying batch size requirements. By strategically sampling using clustering and mixed-variable batch Bayesian optimization, we were able to iteratively identify optimal conditions that maximize the yields. Our work presents a flexible approach that allows tailoring the machine learning decision-making to suit the practical constraints in individual high-throughput experimental platforms, followed by performing resource-efficient yield optimization using available open-source Python libraries.