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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 73 records · Page 4

Probing the Electronic Structure of a Thorium Nitride Complex by Solid-State 15N NMR Spectroscopy

The solid-state 15N NMR powder spectra of the thorium nitride complex, [K(18-crown-6)(THF)2][(R2N)3Th(m-15N)(Th(NR2)3] ([K][1-15N], R = SiMe3), and the thorium amide complex, [Th(NR2)3(15NH2)] (2-15N) were recorded. The spectrum for [K][1-15N] represents the first reported solid-state 15N NMR data for an actinide nitride complex. The experimentally measured tensor spans are 847 ppm for [K][1-15N] and 237 ppm for 2-15N. Both shielding tensors exhibit a near-zero asymmetry parameter, which for [K][1-15N] is consistent with a local rotational symmetry of its 15N-labelled nitride ligand. For 2-15N, the lack of asymmetry can be rationalized by a quasi-free Th-NH2 bond rotation in the solid-state. DFT calculations overestimate the tensor span somewhat for [K][1-15N], but provide isotropic shifts in good agreement with both the solid-state and solution values for both complexes. Natural localized molecular orbital (NLMO) analyses of the nuclear shielding reveal that the larger tensor span in [K][1-15N] vs. 2-15N is primarily a consequence of more pronounced covalency of the N-Th bonds, and large spin-orbit coupling due to significant Th 5f orbital contribution to those bonds, impacting the principal components of the shielding tensor perpendicular to the Th-N-Th axis. Overall, our analysis confirms the involvement of the 5f orbitals in Th-N multiple bonds, and further demonstrates the value of solid-state NMR spectroscopy for interrogating actinide-ligand bonding.

actinides, covalent bonding, Nuclear Magnetic Reso↗

Molecular Simulations Probing the Adsorption and Diffusion of Ammonia, Nitrogen, Hydrogen, and Their Mixtures in Bulk MFI Zeolite and MFI Nanosheets at High Temperature and Pressure

Recent advances in the synthesis of MFI zeolite nanosheets have led to highly selective membranes that are promising candidates for small-scale ammonia separation from ammonia/nitrogen/hydrogen mixtures in distributed green ammonia production plants. Using force-field-based molecular simulations, we evaluate the performance of bulk all-silica MFI zeolite and a 3 nm thick all-silica MFI nanosheet for ammonia/nitrogen/hydrogen separations at moderate temperature and pressure conditions (T = 373 K, p = 5 bar) as well as conditions relevant for a membrane-based reactor–separator process (T = 523 or 623 K, p = 80 bar). Isobaric–isothermal Gibbs ensemble Monte Carlo (GEMC) simulations were carried out to understand the selective adsorption behavior for these mixtures. Molecular dynamics simulations in the canonical ensemble were performed to examine the transport behavior of ammonia in a mixture with nitrogen or hydrogen at loadings obtained from the GEMC simulations. Our results show that both bulk MFI and the nanosheet with explicit surface silanols are highly selective toward ammonia adsorption, but the adsorption selectivity decreases by factors of 4 and 10 for ammonia/nitrogen and ammonia/hydrogen mixtures as the temperature is increased from 373 to 623 K. Conversely, the diffusion selectivities toward ammonia are more favorable at process-relevant temperatures and for the MFI nanosheet. Here, at T = 523 K and p = 80 bar, our simulations predict overall separation factors of 3.8 ± 0.2 and 4.5 ± 0.3 for ammonia/nitrogen and ammonia/hydrogen mixtures, respectively, in the bulk MFI zeolite, and separation factors of 8.6 ± 0.4 and 12.5 ± 0.8, respectively, for the MFI nanosheet.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Probing Accuracy-Speedup Tradeoff in Machine Learning Surrogates for Molecular Dynamics Simulations

The performance promise of machine learning surrogates of molecular dynamics simulations of soft materials is significant but generally comes at the cost of acquiring large training datasets to learn the complex relationships between input soft material attributes and output properties. Under the constraint of limited high-performance computing resources, optimizing the size of the training datasets becomes paramount. Using an artificial neural network based surrogate for molecular dynamics simulations of confined electrolytes, we explore the tradeoff between surrogate accuracy and computational gains. Accuracy is assessed by computing the root-mean-square errors between the surrogate predictions and the ground truth results obtained via molecular dynamics simulations. The computational performance is judged by evaluating the speedup which incorporates the training dataset creation time. Improvement in accuracy occurs with a loss of speedup, which scales as the inverse of the training dataset size. Furthermore, the link between surrogate generalizability and the accuracy-speedup tradeoff is assessed by examining the errors incurred in surrogate predictions on unseen, interpolated input variables and developing a net speedup metric to capture the associated gains.

Anions↗

Probing the Formation of Cathode-Electrolyte Interphase on Lithium Iron Phosphate Cathodes via Operando Mechanical Measurements

Interfacial instabilities in electrodes control the performance and lifetime of Li-ion batteries. While the formation of solid-electrolyte interface (SEI) on anodes has received much attention, there is still lack of understanding about the formation of cathode-electrolyte interface (CEI) on the cathodes. To fill this gap, we report on dynamic deformations on lithium iron phosphate, LiFePO 4 cathodes during charge / discharge by utilizing in-operando digital image correlation, impedance spectroscopy and Cryo X-ray photoelectron spectroscopy. LiFePO4 cathodes were cycled in either LiPF 6 , LiClO 4 or LiTFSI- containing organic liquid electrolytes. Beyond the first cycle, Li-ion intercalation results in a nearly linear correlation between electrochemical strains and the state of (dis)-charge, regardless of the electrolyte chemistry. However, during the first charge in LiPF 6 - containing electrolyte, there is a distinct irreversible positive strain evolution at the onset of anodic current rise as well as current decay at around 4.0V. Impedance studies show the increase in surface resistance in the same potential window, suggesting the formation of CEI layers on the cathode. The chemistry of the CEI layer was characterized by X-ray photoelectron spectroscopy. LiF is detected in CEI layer starting as early as 3.4 V and Li $x$ PO $y$ F $z$ appeared at voltages higher than 4.0 V during the first charge. In conclusion, our approach offers new insights into the formation mechanism of CEI layers on the cathode electrodes, which is crucial for the development of robust cathode and electrolyte chemistries for higher performance batteries.

25 ENERGY STORAGE↗

Probing Active-Site Relocation in Cu/SSZ-13 SCR Catalysts during Hydrothermal Aging by in situ EPR Spectroscopy, Kinetic Studies, and DFT Calculations

Cu/SSZ-13 selective catalytic reduction catalysts display activity loss after mild hydrothermal aging without support degradation or loss of isolated Cu ion content. By applying electron paramagnetic resonance spectroscopy to compare hydrated, dehydrated and NH3-saturated catalysts before and after hydrothermal aging, as well as density functional theory calculations, it is found that hydrothermal aging induces Cu relocation, leading to stronger Cu-support interactions. This is particularly evidenced by ZCuOH conversion to Z2Cu, which leads to the generation of a unique structure with two Cu(II) ions positioned in a double 6-membered ring prism. The Cu(II) ions that do not undergo such dramatic changes also appear to stay closer to framework windows as evidenced by the overall increased anisotropy during EPR measurements. In situ EPR measurements under SCR conditions demonstrate that, in comparison to the fresh catalyst, higher percentages of Cu species stay as Cu(II) in the aged catalyst. This suggests that the reduction half-cycle of the SCR redox, i.e., Cu(II) ? Cu(I), becomes slower for the hydrothermally aged catalyst.

42 ENGINEERING↗

Ce x Zr 1– x O 2 -Supported CrO x Catalysts for CO 2 -Assisted Oxidative Dehydrogenation of Propane–Probing the Active Sites and Strategies for Enhanced Stability

CO 2 -assisted oxidative dehydrogenation of propane (CO 2 -ODH) represents an attractive approach for propylene production and CO 2 utilization. As a soft oxidant, CO 2 can minimize overoxidation of the hydrocarbons to enhance the propylene selectivity while increasing the equilibrium yield. However, a major challenge of CO 2 -ODH is the rapid deactivation of the catalysts. The current study focuses on designing Ce x Zr 1–x O 2 -mixed oxide-supported CrO x catalysts for CO 2 -ODH with enhanced product selectivity and catalyst stability. By doping 0–30% Ce in the Ce x Zr 1–x O 2 mixed oxide support, propane conversion of 53–79% was achieved at 600 °C, with propylene selectivity up to 82%. Compared to the pure ZrO 2 -supported catalyst (i.e., 5 wt %Cr/ZrO 2 ), 20–30 %Ce doped catalysts (i.e., 5 wt %Cr/Ce 0.2 Zr 0.8 O 2 and 5 wt %Cr/Ce 0.3 Zr 0.7 O 2 ) inhibited the formation of CH 4 and ethylene and improved propylene selectivity from 57 to 77–82%. Detailed characterizations of the 5%Cr/Ce 0.2 Zr 0.8 O 2 catalyst and density functional theory (DFT) calculations indicated that Cr 3+ is the active species during the CO 2 -ODH reaction, and the reaction follows a non-redox dehydrogenation pathway. Coke formation was determined to be the primary reason for catalyst deactivation, and the addition of Ce to the ZrO 2 support greatly enhanced the coke resistance, leading to superior stability. Furthermore, coke removal by oxidizing the catalyst in air is effective in restoring its activity.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗