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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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At least 217 records · Page 12

Edge-Propagation Discharge Mechanism in CFx Batteries—A First-Principles and Experimental Study

Graphite fluoride (CF x ) cathodes coupled with lithium anodes yield one of the highest theoretical specific capacities (>860 mAh/g) among primary batteries. In practice, the observed discharge voltage (~2.5 V) is significantly lower than thermodynamic limits (>4.5 V), the discharge rate is low, and so far Li/CF x has only been used in primary batteries. Understanding the discharge mechanism at atomic length scales will improve practical CFx energy density, rate capability, and rechargeability. So far, purely experimental techniques have not identified the correct discharge mechanism or explained the discharge voltage. In this work, we apply density functional theory calculations to demonstrate that a CF x -edge propagation discharge mechanism based on lithium insertion at the CF/C boundary in partially discharged CF x exhibits a voltage range of 2.5 to 2.9 V—depending on whether solvent molecules are involved. The voltages and solvent dependence agree with our discharge and galvanostatic intermittent titration technique measurements. The predicted discharge kinetics are consistent with CF x operations. Finally, we predict some Li/CF x rechargeability under the application of high potentials, along a charging pathway different from that of discharge. Our work represents a general, quasi-kinetic framework to understand the discharge of conversion cathodes, circumventing the widely used phase diagram approach which most likely does not apply to Li/CF x because equilibrium conditions are not attained in this system.

25 ENERGY STORAGE↗

Solution-Phase Synthesis of Platinum-Decorated Hydrogen Tungsten Bronzes for Hydrogen Atom Transfer from Oxides to Molecules

Hydrogen bronzes can be used as hydrogen donors for the broad class of reactions involving proton-coupled electron transfer (PCET). Here, in this work, we describe a method to prepare platinum-decorated hydrogen tungsten bronzes, Pt@H x WO 3 · n H 2 O with n = 0, 1, and 2, by reacting the pristine oxides at modest temperatures with a mild reducing agent, H 3 PO 2 , and H 2 PtCl 6 in an aqueous solution. We explored the tunability and kinetics of this reaction and compared it with that of archetypal gas–solid hydrogen spillover. We demonstrate that the identity of the noble metal affects the extent of bronze reduction. This suggests that the mechanism proceeds via the adsorption of a hydrogen-atom species on the noble metal. Finally, we explored the ability of the Pt-decorated hydrogen tungsten bronzes to hydrogenate a model H + /e – acceptor, 2,2,6,6-tetramethyl-1-piperidinyloxyl (TEMPO). The bronze phases return to their fully oxidized states along with the subsequent reduction of TEMPO to TEMPOH. Overall, this work demonstrates a solution-phase method to obtain hydrogen bronzes, which can then be used to perform hydrogen transfer reactions, providing a pathway for the use of extended transition metal oxides as stoichiometric reagents for broad classes of hydrogenation reactions.

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Annealing-Driven Phase Control Enables Plasmonic Tunability in Alloy Nanoparticles

A critical aspect of designing and realizing useful solid state materials is controlling phase and structure to tailor physical properties. While common for semiconductor and quantum materials, plasmonic materials have inhabited a narrow phase space typically comprising one or two elements, e.g., face-centered cubic metals. While this simplicity has enabled robust use and understanding of Au and Ag nanoparticles, it has also limited the design and manipulation of solid state properties. Here, we show that by tuning the phase and elemental composition of binary Au−Sn nanoparticles, the steady-state absorbance and ultrafast thermalization properties of plasmonic nanoparticles can be controlled. Solid state characterization suggests this is due to the dealloying of Sn and destabilization of the AuSn phase, leading to higher quality Au 5 Sn intermetallic phases alongside Au. Consequently, this work shows that phase control can profoundly influence the properties of plasmonic nanoparticles, providing important tunability for applications in catalysis, photothermal heating, and sensing.

Gold↗

Efficient Step-Merged Quantum Imaginary Time Evolution Algorithm for Quantum Chemistry

In this work, we develop a resource-efficient step-merged quantum imaginary time evolution approach (smQITE) to solve for the ground state of a Hamiltonian on quantum computers. This heuristic method features a fixed shallow quantum circuit depth along the state evolution path. We use this algorithm to determine the binding energy curves of a set of molecules, including H 2 , H 4 , H 6 , LiH, HF, H 2 O, and BeH 2 , and find highly accurate results. The required quantum resources of smQITE calculations can be further reduced by adopting the circuit form of the variational quantum eigensolver (VQE) technique, such as the unitary coupled cluster ansatz. We demonstrate that smQITE achieves a similar computational accuracy as VQE at the same fixed-circuit ansatz, without requiring a generally complicated high-dimensional nonconvex optimization. Finally, smQITE calculations are carried out on Rigetti quantum processing units, demonstrating that the approach is readily applicable on current noisy intermediate-scale quantum devices.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Force-Free Identification of Minimum-Energy Pathways and Transition States for Stochastic Electronic Structure Theories

Here, the accurate mapping of potential energy surfaces (PESs) is crucial to our understanding of the numerous physical and chemical processes mediated by atomic rearrangements, such as conformational changes and chemical reactions, and the thermodynamic and kinetic feasibility of these processes. Stochastic electronic structure theories, e.g., Quantum Monte Carlo (QMC) methods, enable highly accurate total energy calculations that in principle can be used to construct the PES. However, their stochastic nature poses a challenge to the computation and use of forces and Hessians, which are typically required in algorithms for minimum-energy pathway (MEP) and transition state (TS) identification, such as the nudged elastic band (NEB) algorithm and its climbing image formulation. Here, we present strategies that utilize the surrogate Hessian line-search method, previously developed for QMC structural optimization, to efficiently identify MEP and TS structures without requiring force calculations at the level of the stochastic electronic structure theory. By modifying the surrogate Hessian algorithm to operate in path-orthogonal subspaces and at saddle points, we show that it is possible to identify MEPs and TSs by using a force-free QMC approach. We demonstrate these strategies via two examples, the inversion of the ammonia (NH 3 ) molecule and the nucleophilic substitution (S N 2) reaction F – + CH 3 F → FCH 3 + F – . We validate our results using Density Functional Theory (DFT)- and Coupled Cluster (CCSD, CCSD(T))-based NEB calculations. We then introduce a hybrid DFT-QMC approach to compute thermodynamic and kinetic quantities, free energy differences, rate constants, and equilibrium constants that incorporates stochastically optimized structures and their energies, and show that this scheme improves upon DFT accuracy. Our methods generalize straightforwardly to other systems and other high-accuracy theories that similarly face challenges computing energy gradients, paving the way for highly accurate PES mapping, transition state determination, and thermodynamic and kinetic calculations at significantly reduced computational expense.

Iyer, Gopal R.↗

Coupling of Charge Regulation and Geometry in Soft Ionizable Molecular Assemblies

The size, shape, and charge of structures, such as proteins and amphiphile assemblies, respond in an interconnected manner to solution ionic conditions. Here, we analyze assemblies of an amphiphile (C 16 K 2 ), with two ionizable amino acids [lysine (K)] coupled to a 16-carbon alkyl tail, via small-angle X-ray scattering (SAXS), nonlinear Poisson–Boltzmann theory (nl-PB), and hybrid Monte Carlo-molecular dynamics (MC-MD) simulations. SAXS revealed structural transitions from spherical micelles to cylindrical micelles to bilayers with increasing pH. By combining SAXS-determined structural information and nl-PB, we derived the molecular degree of ionization as a function of pH. The back-calculated titration curves matched the experimental data over an extended pH range, without adjustable parameters. Similarly, the SAXS data on the evolution of spherical micelle structure with ionic strength were combined with nl-PB and MC-MD to derive the bare and effective charges. MC-MD, which considered finite ion sizes, showed that bare and effective charges saturate quickly with increasing salt concentration. Furthermore, the calculated effective charges closely matched results from Zeta-potential measurements. The presented approach has advantages over customary methods for charge regulation, such as the Henderson–Hasselbalch (HH) or Hill models, where molecular ionization/deionization in assemblies is described by effective pKs that are distinct from the pK for isolated molecules. However, these models lack a physical explanation for these pK shifts. By contrast, our approach of combining structural details with an electrostatic model and simulations provides a more intuitive understanding of structure-charge coupling and a framework for understanding charge regulation in many synthetic and biological systems.

ionization↗

NMR-Guided High-Temperature Electrolyte Design Using a Novel PF 5 Marker

The thermal degradation of electrolytes containing lithium hexafluorophosphate (LiPF 6 ) is a well-studied subject. However, practical application of the knowledge is difficult since the effects of the degradation process on battery performance are not well known. In this work, we propose a novel NMR experimental setup allowing direct observation of the effects of various perturbations on the electrolyte thermal degradation process, which guides the design and synthesis of new additives that improve lithium-ion battery performance at elevated temperatures.

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Insights from Computational Studies on the Anisotropic Volume Change of Li x NiO 2 at High States of Charge (x < 0.25)

The need for high-capacity Li-ion battery cathodes has favored the increase of Ni content in commercial battery cells. However, at high states of charge (SOCs), Ni-rich materials undergo a phase transition and volume collapse with deleterious effects on battery performance. It is uncertain whether this drastic volume change is caused by the phase transition or not. To provide more insight into the volume-phase transition relationship in the high Ni cathode LixNiO 2 , we performed density functional theory calculations, along with molecular dynamics simulations using machine learning potentials to calculate the temperature- and composition-dependent free energy differences between the suspected phases at high SOCs (x < 0.25). Herein, we find that the calculated free energy difference between the suspected phases containing different oxygen stacking sequences is small at room temperature. Furthermore, we find that the collapse of the layered LiNiO 2 c-lattice parameter at high SOCs is mainly due to the electronic depletion of the oxygen sublattice and the lack of screening from positive Li ions. The interactions between adjacent oxygen ions across an empty Li layer (NiO 2 ) are largely controlled by van der Waals interactions and are in fact similar regardless of the oxygen stacking, which explains the negligible free energy differences between O1 and O3 stacking in NiO 2 .

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SPE-CZE-MS Quantifies Zeptomole Amounts of Phosphorylated Peptides

Capillary zone electrophoresis (CZE) is gaining attention in the field of single-cell proteomics for its ultralow-flow and high-resolution separation abilities. Even more sample-limited yet rich in biological information are phosphoproteomics experiments, as the phosphoproteome composes only a fraction of the whole cellular proteome. Rapid analysis, high sensitivity, and maximization of sample utilization are paramount for single-cell analysis. Some challenges of coupling CZE analysis with mass spectrometry analysis (MS) of complex mixtures include 1. sensitivity due to volume loading limitations of CZE and 2. incompatibility of MS duty cycles with electropherographic time scales. Here, we address these two challenges as applied to singlecell- equivalent phosphoproteomics experiments by interfacing a microchip-based CZE device integrated with a solid-phaseextraction (SPE) bed with the Orbitrap Astral mass spectrometer. Using 225 phosphorylated peptide standards and phosphorylated peptide-enriched mouse brain tissue, we investigate microchip-based SPE-CZE functionality, quantitative performance, and complementarity to nano-LC-MS (nLC-MS) analysis. We highlight unique SPE-CZE separation mechanisms that can empower fitfor- purpose applications in single-cell-equivalent phosphoproteomics.

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