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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 397 records · Page 22
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Effects of Extended Aqueous Processing on Structure, Chemistry, and Performance of Polycrystalline LiNi x Mn y Co z O 2 Cathode Powders

The prospect of aqueous processing of LiNi x Mn y Co z O 2 (NMC) cathodes has significant appeal to battery manufacturers for the reduction in materials cost, toxicological risk, and environmental impact compared to conventional N -methyl-2-pyrrolidone (NMP)-based processing. However, the effects of aqueous processing of NMC powders at industrial timescales are not well studied, with prior studies mostly focusing on relatively brief water washing processes. Here, we investigate the bulk and surface impacts of extended aqueous processing of polycrystalline NMC powders with different compositions. We demonstrate that at timescales of several hours, polycrystalline NMC is susceptible to intergranular fracture, with the severity of fracture scaling with the NMC nickel content. While bulk crystallinity and composition are unchanged, surface sensitive techniques such as X-ray photoelectron spectroscopy (XPS) and transmission electron microscopy (TEM) indicate that the exposure of water leads to a level of delithiation, nickel reduction, and reconstruction from the layered to rock-salt structure at the surface of individual grains. Dynamic single NMC microparticle compression testing suggests that the resulting mechanical stresses weaken the integrity of the polycrystalline particle and increases susceptibility of intergranular fracture. The initially degraded surfaces along with the increased surface area lead to faster capacity fade and impedance growth during electrochemical cycling. From this work, it is demonstrated that NMC powders require surface or grain boundary modifications to make industrial-scale aqueous cathode processing viable, especially for next-generation nickel-rich NMC chemistries.

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DOE OSTI2023

Mechanism of Nitrogen-Carbon Bond Formation from Iron(IV) Disilylhydrazido Intermediates during N 2 Reduction

We recently reported a reaction sequence that activates C–H bonds in simple arenes as well as the N–N triple bond in N 2 , delivering the aryl group to N 2 to form a new N–C bond ( Nature 2020 , 584, 221). This enables the transformation of abundant feedstocks (arenes and N 2 ) into N-containing organic compounds. The key N–C bond forming step occurs upon partial silylation of N 2 . However, the pathway through which reduction, silylation, and migration occurred was unknown. Here, in this work, we describe synthetic, structural, magnetic, spectroscopic, kinetic, and computational studies that elucidate the steps of this transformation. N 2 must be silylated twice at the distal N atom before aryl migration can occur, and sequential silyl radical and silyl cation addition is a kinetically competent pathway to a formally iron(IV)–NN(SiMe 3 ) 2 intermediate that can be isolated at low temperature. Kinetic studies show its first-order conversion to the migrated product, and DFT calculations indicate a concerted transition state for migration. The electronic structure of the formally iron(IV) intermediate is examined using DFT and CASSCF calculations, which reveal contributions from iron(II) and iron(III) resonance forms with oxidized NNSi 2 ligands. The depletion of electron density from the Fe-coordinated N atom makes it electrophilic enough to accept the incoming aryl group. This new pathway for the N–C bond formation offers a method for functionalizing N 2 using organometallic chemistry.

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DOE OSTI2022

New Approaches to Improved PEM Fuel Cell Catalyst Layers

Polymer-electrolyte membrane (PEM) fuel-cells are one of the most promising energy conversion technologies for renewable clean energy applications. A major challenge preventing the widespread use and commercialization of PEM fuel cells is achieving high performance with low-loadings of platinum group metal (PGM) catalysts. One of the factors driving performance limitations in the cell is the mass transport losses within the cathode catalyst layers (CCL) due to sluggish oxygen-reduction reactions occurring at the platinum-ionomer interface. Any resistance to transport of these ionic and gaseous species within the CCL results in mass-transport limitations and performance losses, especially at high current densities. It is known that mass-transport losses increase with reduced platinum loading, thereby creating a performance-cost tradeoff for fuel cells. A viable solution to reduce the transport resistances in the catalyst layers is to create new ionomers that can provide good ion and oxygen transport needed to accomplish high-performing fuel cell catalysts. Using this approach Tetramer Technologies and LBNL propose improved fuel-cell catalyst ionomers based on Tetramers proprietary polymer chemistry.

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DOE OSTI2022

Review of recent developments in iodine wasteform production

Radioiodine capture and immobilization is not only important to consider during the operation of reactors (i.e., I-131), during nuclear accidents (i.e., I-131 and I-129) or nuclear fuel reprocessing (i.e., I-131 and I-129), but also during disposal of nuclear wastes (i.e., I-129). Most disposal plans for I-129-containing waste forms (including spent nuclear fuel) propose to store them in underground repositories. Here, iodine can be highly mobile and, given its radiotoxicity, needs to be carefully managed to minimize long-term environmental impacts arising from disposal. Typically, any process that has been used to capture iodine from reprocessing or in a reactor is not suitable for direct disposal, rather conversion into a wasteform for disposal is required. The objectives of these materials are to use either chemical immobilization or physical encapsulation to reduce the leaching of iodine by groundwaters. Some of the more recent ideas have been to design capture materials that better align with disposal concepts, making the industrial processing requirements easier. Research on iodine capture materials and wasteforms has been extensive. This review will act as both an update on the state of the research since the last time it was comprehensively summarized, and an evaluation of the industrial techniques required to create the proposed iodine wasteforms in terms of resulting material chemistry and applicability.

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DOE OSTI2021

Maintaining a Flat Li Surface during the Li Stripping Process via Interface Design

Electroplating has been the main focus in mitigating the dendrite growth on the Li-metal electrode; however, the stripping process is equally critical, since the nonsmooth Li surface during stripping will lead to nonuniform local current density, planting the seeds for dendrite growth. In this paper, density functional theory (DFT) and kinetic Monte Carlo (KMC) techniques were combined to investigate the vacancy evolution in Li interfaced with different solid–electrolyte interphase (SEI) materials. It was found that the lithiophilic interface, such as Li/Li 2 O, repels vacancies into the bulk Li, so Li atoms can quickly fill the Li vacancies near the Li/Li 2 O interface and maintain a smooth Li surface. In contrast, the lithiophobic interface, such as Li/LiF, traps Li vacancies toward the interface, and the accumulated Li vacancies form voids and roughen the surface. The predicted critical stripping current density, below which a smooth Li surface will be maintained, is therefore much faster at the lithiophilic interface than that at the lithiophobic interface. It was further revealed that the lithiophilicity at different SEI or coating materials can be ranked as Li/Li 2 O > Li/LiPON > Li/Li 2 CO 3 > Li/LiF based on the calculated interfacial adhesion and accumulation of electron density at the interface. Furthermore, this suggests that interface and coating design at nanoscale can be effective for maintaining a smooth Li surface during the stripping process, solving another challenge to achieving a dendrite-free Li-metal electrode in both liquid and solid electrolytes.

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DOE OSTI2021

From Three-Dimensional Clathrates to Two-Dimensional Zintl Phases AMSb 2 (A = Rb, Cs; M = Ga, In) Composed of Pentagonal M–Sb Rings

Three new antimonide Zintl phases, RbGaSb 2 , CsGaSb 2 , and CsInSb 2 , were discovered during exploration of corresponding A–M–Sb (A = Rb, Cs; M = Ga, In) ternary systems while searching for new clathrates. The AGaSb 2 phases crystallize in the tetragonal space group P4 2 /nmc (No. 137) in the LiBS 2 structure type, while CsInSb 2 crystallizes in lower symmetry in the orthorhombic space group Cmce (No. 64) in the KGaSb 2 structure type with additional disorder of one of the Cs sites. The crystal structures of all three reported AMSb 2 compounds are composed of two-dimensional [MSb 2 ] – tetrahedral layers separated by Rb + or Cs + cations. [MSb 2 ] – layers are built from fused M–Sb pentagons and hexagons, which are also the main structural units for A 8 M 27 Sb 19 clathrate cages. The semiconductor nature of AMSb 2 was suggested by band structure calculations and confirmed by transport property characterization. CsGaSb 2 is a rare example of an n-type pnictide Zintl phase. Finally, all reported compounds exhibit low thermal conductivity typical for complex antimonides of heavy elements.

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DOE OSTI2022

Bubble Point Measurements of Three Binary Mixtures of Refrigerants: R-32/1234yf, R-32/1234ze(E), and R-1132a/1234yf

In this article, bubble point pressures of three binary mixtures at two compositions each have been measured utilizing a static method. The mixtures studied were difluoromethane + 2,3,3,3-tetrafluoroprop-1-ene (R-32/1234yf), difluoromethane + (E)-1,3,3,3-tetrafluoroprop-1-ene (R-32/1234ze(E)), and 1,1-difluoroethene + 2,3,3,3-tetrafluoroprop-1-ene (R-1132a/1234yf). For all of the mixtures, the minimum temperature measured was 270 K. The maximum temperatures measured for the R-32/1234ze(E), R-32/1234yf, and R-1132a/1234yf mixtures were 360, 345, and 325 K, respectively. A total of 100 bubble point pressures are reported and compared to available literature data relative to the REFPROP database. Lemmon, E. W. [ NIST Standard Reference Database 23: Reference Fluid Thermodynamic and Transport Properties-REFPROP, 10.0; National Institute of Standards and Technology, Standard Reference Data Program: Gaithersburg, 2018]. Additionally, the bubble point pressures obtained in this study are modeled using the perturbed-chain statistical associating fluid theory (PC-SAFT) equation of state. The PC-SAFT model parameters, as well as deviations of this work and literature data from the model, are reported.

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DOE OSTI2023

Vapor and Liquid ( p –ρ– T–x ) Measurements of Binary Refrigerant Blends Containing R-32, R-152a, R-227ea, R-1234yf, and R-1234ze(E)

In this article, The pressure–density–temperature–composition (p–ρ–T–x) data of binary refrigerant mixtures containing R-32 (difluoromethane), R-152a (1,1,-difluoroethane), R-227ea (1,1,1,2,3,3,3-heptafluoropropane), R-1234yf (2,3,3,3-tetrafluoropropene), and R-1234ze(E) (trans-1,3,3,3-tetrafluoropropene) were measured in both the vapor and liquid phases using a two-sinker, magnetic suspension densimeter. The specific samples in this study comprised two compositions of approximately (0.3/0.7) and (0.7/0.3) mole fraction for each of the following four binary refrigerant blends: R-32 + R-1234yf, R-32 + R-1234ze(E), R-1234yf + R-152a, and R-1234ze(E) + R-227ea. Single-phase vapor densities were measured over a temperature range of approximately 253 to 293 K and pressures from 0.05 to 0.98 MPa. Single-phase liquid and supercritical densities were measured over a temperature range of approximately 230 to 400 K and pressures up to 22 MPa; for refrigerant blends containing R-1234yf, the maximum pressure was limited to 14 MPa. Overall relative combined, expanded (k = 2) uncertainties in density ranged from 0.025 to 0.191%, with an average uncertainty of approximately 0.05%. Here, we present measurement results, along with comparisons to available literature data and to default equations of state and mixture models included in REFPROP.

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DOE OSTI2020

Ab Initio Study of Vibronic and Magnetic 5f-to-5f and Dipole-Allowed 5f-to-6d and Charge-Transfer Transitions in [UX 6 ] n – (X = Cl, Br; n = 1, 2)

The absorption spectra of the octahedral [UX 6 ] n– (X = Cl, Br; n = 1, 2) complexes in the near-infrared (NIR) and UV–vis spectral regions were studied theoretically, using a relativistic restricted active space second-order perturbation theory (RASPT2) wavefunction framework, with the spin–orbit (SO) coupling treated by state interaction, in conjunction with Kohn–Sham density functional theory calculations for determining the vibrational normal modes. The electric-dipole-allowed ligand-to-metal charge-transfer (LMCT) and 5f-to-6d transitions, and the electric-dipole-forbidden 5f-to-5f ligand field (LF) transitions, are thereby obtained within the same theoretical framework. For the 5f-to-5f LF transitions, the observed absorption intensity is mostly due to vibronic coupling with low-energy electric-dipole-allowed transitions, but in some cases, the magnetic dipole intensity of the purely electronic transition has comparable intensity to the vibronic transitions. Here, experimental LF spectra of 5f 2 open-shell systems have been reported decades back, but ab initio calculations of their vibronic intensity have not yet been reported in the literature. Although the LF spectra for the 5f 2 systems can be assigned in detail, based on the calculations, the spectra are very complex and the underlying electronic states are strongly multiconfigurational. Therefore, the usefulness of the LF spectra beyond serving as a “fingerprint” of the LF and the metal oxidation state appears to be limited.

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DOE OSTI2020

Modeling Nonperturbative Field-Driven Vibronic Dynamics: Selective State Preparation and Nonlinear Spectroscopy

The partially linearized density matrix formalism for nonadiabatic dynamics is adapted to incorporate a classical external electromagentic field into the system Hamiltonian. This advancement encompasses the possibility of describing field-driven dynamics and computing a variety of linear and nonlinear spectroscopic signals beyond the perturbative limit. Here, the capabilities of the developed approach are demonstrated on a simple two-state vibronic model coupled to a bath, for which we (a) perform an exhaustive search in the field parameter space for optimal state preparation and (b) compute time-resolved transient absorption spectroscopy to monitor the effect of different pulse shapes on measurable experimental signals. While no restrictions on the form of the field have to be assumed, we focus here on Gaussian shaped (linearly) chirped pulses.

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DOE OSTI2023

A Practical Approach to Wave Function Propagation, Hopping Probabilities, and Time Steps in Surface Hopping Calculations

We compare several established approaches for propagating wave functions and calculating hopping probabilities within the fewest switches surface hopping (FSSH) algorithm for difficult cases with many electronic states and many trivial crossings. If only a single time step (Δt c ) is employed, we find that no published approach can accurately capture the dynamics correctly unless Δt c → 0 (which is not computationally feasible). If multiple time steps are employed, for a fixed classical time step (Δt c ), a robust scheme can be found for dynamically choosing quantum time steps (δt q1 and δt q2 ) and calculating hopping probabilities so that one can systematically reduce all errors and achieve maximally efficient accuracy; scattering calculations confirm that one can choose a fairly large classical time step. Furthermore, the robust scheme presented here uses both the “local diabatic” and adiabatic interpolation and thus borrows elements from both the Granucci/Persico and Meek/Levine algorithms. Our findings should be broadly applicable in the future.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Toward Automated Sampling of Polymorph Nucleation and Free Energies with the SGOOP and Metadynamics

Understanding the driving forces behind the nucleation of different polymorphs is of great importance for material sciences and the pharmaceutical industry. This includes understanding the reaction coordinate that governs the nucleation process and correctly calculating the relative free energies of different polymorphs. Here, we demonstrate, for the prototypical case of urea nucleation from the melt, how one can learn such a one-dimensional reaction coordinate as a function of prespecified order parameters and use it to perform efficient biased all-atom molecular dynamics simulations. The reaction coordinate is learnt as a function of the generic thermodynamic and structural order parameters using the “spectral gap optimization of order parameters (SGOOP)” approach [Tiwary, P. and Berne, B. J. Proc. Natl. Acad. Sci. U.S.A. (2016)] and is biased using well-tempered metadynamics simulations. The reaction coordinate gives insights into the role played by different structural and thermodynamics order parameters, and the biased simulations obtain accurate relative free energies for different polymorphs. This includes an accurate prediction of the approximate pressure at which urea undergoes a phase transition and one of the metastable polymorphs becomes the most stable conformation. Here, we believe the ideas demonstrated in this work will facilitate efficient sampling of nucleation in complex, generic systems.

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DOE OSTI2023

Neural Network Water Model Based on the MB-Pol Many-Body Potential

The MB-pol many-body potential accurately predicts many properties of water, including cluster, liquid phase, and vapor–liquid equilibrium properties, but its high computational cost can make applying it in large-scale simulations quite challenging. Here, in order to address this limitation, we developed a “deep potential” neural network (DPMD) model based on the MB-pol potential for water. We find that a DPMD model trained on mostly liquid configurations yields a good description of the bulk liquid phase but severely underpredicts vapor–liquid coexistence densities. By contrast, adding cluster configurations to the neural network training set leads to a good agreement for the vapor coexistence densities. Liquid phase densities under supercooled conditions are also represented well, even though they were not included in the training set. These results confirm that neural network models can combine accuracy and transferability if sufficient attention is given to the construction of a representative training set for the target system.

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DOE OSTI2023

Synthesis of Acid Hydrazides from Carboxylic Acids in Continuous Flow

A concise methodology for the synthesis of acid hydrazides from carboxylic acids via a continuous flow process in yields ranging from 65 to 91% is described. Using short residence times of between 13 and 25 mins, the conditions proved amenable to a variety of mono- and diacids, including aliphatic, aromatic, and heteroaromatic functionalities. Furthermore, to demonstrate scalability, a large-scale (200 g) synthesis of azelaic dihydrazide was conducted over a continuous run of 9 h with an 86% overall yield, equating to a 22 g/h output.

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