Li 3 VP 3 O 9 N as a Multielectron Redox Cathode for Li-Ion Battery
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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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Thermochemical storage materials having the general formula AxA′1-xByB′1-yO3-δ, where A=La, Sr, K, Ca, Ba, Y and B=Mn, Fe, Co, Ti, Ni, Cu, Zr, Al, Y, Cr, V, Nb, Mo, are disclosed. These materials have improved thermal storage energy density and reaction kinetics compared to previous materials. Concentrating solar power thermochemical systems and methods capable of storing heat energy by using these thermochemical storage materials are also disclosed.
The present invention relates to a class of polymer ion imbibed membranes for electrolyte flow batteries. The membranes are a conducting aromatic polyether type copolymer bearing nitrogen heterocycles groups, especially pyridine type. While the membranes can be used in acid, basic, and neutral electrolytes, the nitrogen heterocycles in the membrane interact with acid in the electrolyte to form a proton transport network, so as to keep the proton transport performance of the membrane. The membrane has excellent mechanical stability and thermostability as well as tunable porosity.
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Devices, systems, and compositions of matter involving enzyme-mediated bioelectrocatalysis are disclosed and described. An enzyme electrode can include an electrode, a bioelectric material coupled to the electrode, the bioelectric material further including a water-permeable polymer matrix, a planar linker covalently coupled to the water-permeable polymer matrix and noncovalently coupled to the electrode, and electrochemically active oxidoreductase enzyme molecules functionally embedded in the water-permeable polymer matrix.
The invention provides flow batteries including an anthraquinone and methods of discharging the batteries that reduce loss of capacity. The loss of capacity of anthraquinones may be mitigated by controlling the state of charge and/or oxidizing the negolyte.
Abstract not provided.
Abstract not provided.
Concluding Russell L. Heath Distinguished Postdoctoral Fellowship presentation to DOE leadership.
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final report
The Temporal Analysis of Products (TAP) pulse response methodology is a transient technique that provides the time resolution needed to deconvolve reaction steps from the complex networks typical in industrial catalytic processes. Traditionally, TAP measurements observe gas phase dynamics at the reactor exit but lack direct measurements of changes in the catalyst itself. Recently, a new operando technique was developed that couples gas phase transients to dynamic changes in metal centers with the precise TAP methodology for nanomole titration. Using an industrial CrOx/Al2O3 catalyst used for propane dehydrogenation, we demonstrate the capabilities of this unique device to reveal key catalytic processes: 1) total propane oxidation not associated with chromia centers, 2) reduction of Cr6+ to Cr3+ correlated with selective product formation, and 3) subsequent carbon accumulation. By utilizing incremental pulsing in a diffusion-only transport regime, the spectrokinetic device allows us to resolve detailed changes in catalyst structure, composition, and kinetic function that are otherwise indistinguishable in conventional operando devices. The unification of the TAP methodology with time-resolved spectroscopic measurements offers new and unique insights into the complex kinetic phenomena regulated by solid catalyst surfaces.
LDRD project concluding poster for the LDRD poster presentation.
The redox reaction pathway is crucial to the sustainable production of the fuels and chemicals required for a carbon-neutral society. Our society is becoming increasingly dependent on devices using batteries and electrolyzers, all of which rely on a series of redox reactions. The overall properties of oxide materials make them very well suited for such electrochemical and catalytic applications due to their associated cationic redox properties and the static site-adsorbate interactions. As these technologies have matured, it has become apparent that defect-driven redox reactions, defect-coupled diffusion, and structural transformations that are both time- and rate-dependent are also critical materials processes. This change in focus, considering not only redox properties but also more complex, dynamic behaviors, represents a new research frontier in the molecular sciences as they are strongly linked to device operation and degradation and lie at the heart of various phenomena that take place at electrochemical interfaces. Fundamental studies of the structural, electronic, and chemical transformation mechanisms are key to the advancement of materials and technological innovations that could be implemented in various electrochemical systems. In this Account, we focus on recent studies and advances in characterizing and understanding the dynamic redox evolution and structural transformations that take place in model perovskites and layered oxides under reactive conditions and correlate them with degradation mechanisms and operations in electrolyzers and batteries. We show that the dynamic evolution of oxygen vacancies and cationic migration in the surface or bulk occurs at the solid-liquid interface, using a combination of different synchrotron-based Xray spectroscopies and scattering probes. Detailed redox-structure-reactivity correlation studies show how defects and diffusion processes can be tailored to drive various physical and chemical transformations in electrolyzers and batteries. We also highlight a strong correlation between oxygen redox reactivity and structural reorganization in both model thin films and particles, helping to bridge the gap between fundamental studies of the reaction mechanism and device applications. Finally, on the basis of these findings, we discuss strategies to probe and tune the redox reactivity and structural stability of the redox-active oxide interphase toward devising efficient pathways for energy and chemical harvesting.
Irreparable chemical damage to redox-active monomers, oligomers, and polymers (i.e. redoxmers) limits the lifetime of energy storage devices (e.g. redox flow batteries) by causing electrode and membrane fouling, as well as irreversible capacity loss. To predictably restore device and materials performance, it is desirable to add programmed destruction capabilities into these damage-prone materials. Here, we report the use of triggerable retrograde reactions to achieve programmable end-of-life function in redoxmers. Retrograde reactions are intended to break up damaged redoxmer materials into more soluble small-molecule constituents to prevent irreparably fouling battery interfaces. We investigated the redox-triggered mesolytic cleavage of homobenzylic ethers (HBEs) for this purpose. Combining experimental methods with simulations, we probed the influence of ring substituents on the programmable bond-scission behavior of HBEs. Variation of para-substituents on the HBEs allowed us to modify the oxidation potential, degradation pathway, and electrochemical mechanisms of the generated products. Given its ideal oxidation potential, we selected the para-methoxy-based HBE as the cleavage scaffold and integrated it with dialkoxybenzene, TEMPO, viologen, and para-nitrobenzene redox centers for compatibility, bulk deconstruction, and electrode defouling tests. Upon applying a high oxidation potential, the redox-active pendant is cleaved from the backbone via HBE bonds; of the four redox centers tested, three of them remained fully redox active. Viologen-appended redox active polymers with HBE linkers were cleaved to fully separate the redox centers from the backbone. Polymer-filmed electrodes were partially restored following HBE oxidation defouling. Here these studies highlight the co-design of new materials functions for developing sustainable energy storage materials.
Solubility prediction plays a crucial role in energy storage applications, such as redox flow batteries, because it directly affects the efficiency and reliability. Researchers have developed various methods that utilize quantum calculations and descriptors to predict the aqueous solubilities of organic molecules. Notably, machine learning models based on descriptors have shown promise for solubility prediction. As deep learning tools, graph neural networks (GNNs) have emerged to capture complex structure–property relationships for material property prediction. Specifically, MolGAT, a type of GNN model, was designed to incorporate n-dimensional edge attributes, enabling the modeling of intricacies in molecular graphs and enhancing the prediction capabilities. In a previous study, MolGAT successfully screened 23 467 promising redox-active molecules from a database of over 500 000 compounds, based on redox potential predictions. This study focused on applying the MolGAT model to predict the aqueous solubility (log S) of a broad range of organic compounds, including those previously screened for redox activity. The model was trained on a diverse sample of 8494 organic molecules from AqSolDB and benchmarked against literature data, demonstrating superior accuracy compared with other state of the art graph-based and descriptor-based models. Subsequently, the trained MolGAT model was employed to screen redox-active organic compounds identified in the first phase of high-throughput virtual screening, targeting favorable solubility in energy storage applications. The second round of screening, which considered solubility, yielded 12 332 promising redox-active and soluble organic molecules suitable for use in aqueous redox flow batteries. Thus, the two-phase high-throughput virtual screening approach utilizing MolGAT, specifically trained for redox potential and solubility, is an effective strategy for selecting suitable intrinsically soluble redox-active molecules from extensive databases, potentially advancing energy storage through reliable material development. This indicates that the model is reliable for predicting the solubility of various molecules and provides valuable insights for energy storage, pharmaceutical, environmental, and chemical applications.
In cyanobacteria, the redox-sensitive protein OpcA acts as a metabolic switch for G6PDH, enabling rapid adjustment of reducing power generation from glycogen catabolism and thereby precisely regulating carbon flux between anabolic and catabolic pathways. Although redox-sensitive cysteines in OpcA are known to regulate G6PDH, the mechanisms by which redox post-translational modifications (PTMs) on OpcA control G6PDH structure and activity remain unclear. Here, we combine computational modeling with experimental redox proteomics in Synechococcus elongatus PCC 7942 to dissect this mechanism. Experimentally, redox proteome analysis revealed differential redox PTM patterns, particularly on cysteines within the G6PDH-binding site of OpcA. These environmentally sensitive PTM changes at the interface suggest that thiol modifications in this region form a key regulatory node. More broadly, redox proteomics identified site-specific cysteine modifications under light/dark transitions and circadian cycling, linking distinct redox regimes to discrete PTM states. We employed PTM-Psi simulations to show that thiol PTMs near the OpcA–G6PDH interface are critical for allosteric regulation of G6PDH. The thiol PTMs on OpcA affect a putative gate region in G6PDH for substrate ingress and product egress as well as key hydrogen-bond networks within the active site. We infer that PTMs on OpcA tune the conformational landscapes of individual G6PDH subunits toward functionally relevant configurations according to environmental gradients, biasing the enzyme toward catalytically favorable states. Together, our results reveal a molecular mechanism in which thiol PTMs on OpcA modulate G6PDH structure and function through PTM-induced reorganization of conformational dynamics and allosteric communication. These findings demonstrate that PTM-level regulation provides a critical control layer from genotypes to phenotypes that enables cyanobacteria to rapidly adapt to environmental fluctuations through precise metabolic fine-tuning.