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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 1,693 records · Page 94
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Role of Scaffold Architecture and Excess Surface Polymer Layers in a 3D-Interconnected Ceramic/Polymer Composite Electrolyte

3D-interconnected ceramic/polymer composite electrolytes offer promise to combine the benefits of both ceramic and polymer electrolytes. However, an in-depth understanding of the role of the ceramic scaffold's architecture, and the associated polymer/ceramic interfaces on the electrochemical properties of such composite electrolytes is still incomplete. Here, these factors are systematically evaluated using an interconnected composite electrolyte with a tunable and well-defined architecture. The ionic conductivity of the ceramic scaffold is strongly dependent on its porosity and tortuosity, as demonstrated experimentally and via theoretical modeling. The connectivity of the ceramic framework avoids the high interfacial impedance at the polymer/ceramic electrolyte interface within the composite. However, this work discovers that the interfacial impedance between the bulk composite and excess surface polymer layers of the composite membrane dominates the overall impedance, resulting in a 1–2 order drop of ionic conductivity compared to the ceramic scaffold. Despite the high impedance interfaces, an improved Li + transference number is found compared to the neat polymer (0.29 vs 0.05), attributed to the ceramic phase's contributions toward ion transport. Further, this leads to flatter overpotentials in lithium symmetric cell cycling. These results are expected to guide future research directions toward scalable manufacturing of composite electrolytes with optimized architecture and interfaces.

25 ENERGY STORAGE↗
DOE OSTI2023

Assessing the Intrinsic Roles of Key Dopant Elements in High–Nickel Layered Oxide Cathodes in Lithium–Based Batteries

A rational compositional design is critical for utilizing LiNiO 2 -based cathodes with Ni contents > 90% as promising next-generation cathode materials. Unfortunately, the lack of a fundamental understanding of the intrinsic roles of key elements, such as cobalt, manganese, and aluminum, makes the rational compositional design of high-Ni cathodes with a limited range of dopants (<10%) particularly challenging. Here, with 5% single-element doped cathodes, viz., LiNi 0.95 Co 0.05 O 2 , LiNi 0.95 Mn 0.05 O 2 , and LiNi 0.95 Al 0.05 O 2 , along with undoped LiNiO 2 (LNO), the influences of the dopants are systematically examined through a control of cutoff charge energy density and a common practice of cutoff charge voltage. Comprehensive investigations into the electrochemical properties, combined with in-depth analyses of the structural and interfasial stabilities and electrolyte decomposition pathways through advanced characterizations, unveil the following: i) the intrinsic role of dopants regulates the cathode energy density or state-of-charge and, more critically, the occurrence of H2–H3 phase transition, which essentially dictates cyclability; ii) undoped LNO can be stabilized well with the avoidance of H2–H3 phase transition; and iii) Co provides more merits overall with an optimized electrochemical operating condition. Finally, this work provides guidance for the compositional design of high-energy-density high-Ni cathodes and sheds light on the challenges of removing Co.

25 ENERGY STORAGE↗
DOE OSTI2024

Evolution of the Electronic and Excitonic Properties in 2D Ruddlesden–Popper Perovskites Induced by Bifunctional Ligands

2D Ruddlesden–Popper metal‐halide perovskites exhibit structural diversity due to a variety of choices of organic ligands. Incorporating bifunctional ligands in such materials is particularly intriguing since it can result in novel electronic properties and functions. However, an in‐depth understanding of the effects of bifunctional ligands on perovskite structures and, consequently, their electronic and excitonic properties, is still lacking. Here, in this work, n = 1 2D perovskites built with organic ligands containing ─CN, ─OH, ─COOH, ─phenyl (Ph), and ─CH 3 functional groups are investigated using ultraviolet and inverse photoemission spectroscopies, density functional theory calculations, and tight‐binding model analyses. The experimentally determined electronic gaps of the ─CN, ─COOH, ─Ph, and ─CH 3 based perovskites exhibit a strong correlation with the in‐plane Pb─I─Pb bond angle, while the ─OH based perovskite deviates from the linear trend. Based on the band structure calculations, this anomaly is attributed to the out‐of‐plane dispersion, caused predominantly by significant interlayer electronic coupling that is present in ─OH based perovskites. These results highlight the complex and diverse impacts of organic ligands on electronic properties, especially in terms of the involvement of strong interlayer electronic coupling. The impact of the bifunctional ligands on the evolution of the exciton binding energy is also addressed.

2D perovskites↗
DOE OSTI2024

Vacancy Mediated Electrooxidation of 5‐Hydroxymethyl Furfuryl Using Defect Engineered Layered Double Hydroxide Electrocatalysts

Abstract Electrochemical biomass oxidation coupled with hydrogen evolution offers a promising route to generate value‐added chemicals and clean energy. The complex adsorption behavior of 5‐hydroxymethyl furfural (HMF) and hydroxyl ions (OH − ) on the electrocatalyst surface during HMF electrooxidation reaction (HMFOR) necessitates an in‐depth understanding of active sites available for adsorption. Herein, oxygen vacancy (V O ) defects are introduced in NiFe layered double hydroxide (LDH) using Ce dopants to manipulate electronic structure. Synchrotron‐based HE‐XRD and XAS indicate negligible V O in La‐doped NiFe while Ce doping leads to V O defects due to flexible Ce redox (Ce 3+ ↔ Ce 4+ ). The V O ‐rich Ce‐NiFe exhibits higher Faradic efficiency of ≈90% to produce 2,5‐furan dicarboxylic acid (FDCA), far greater than ≈60% for NiFe V O in Ce‐NiFe act as alternative active sites for OH − adsorption, hence reducing adsorption competition for the same metal sites. DFT calculation results corroborate experimental findings by showcasing that the presence of V O in Ce‐NiFe manipulates the adsorption energies and facilitates the chemical adsorption OH − in V O to improve HMFOR. In situ HE‐XRD derived pair distribution function coupled to RMC simulations confirm OH − trapping in V O and HMF adsorption on metal centers as evident by interlayer distance evolution. Taken together, this work showcases routes for dual‐site electrocatalyst design for improved biomass electrooxidation.

Chemistry↗
DOE OSTI2025

In Situ Diffraction and Ex Situ Transmission X‐Ray Microscopy Studies of Solid‐State Upcycling for NMC Cathodes

Upcycling of recycled LiNi 0.6 Mn 0.2 Co 0.2 O 2 (NMC622) cathodes offers an economical route to produce cathode materials with increased energy density (i.e., LiNi 0.8 Mn 0.1 Co 0.1 O 2 , NMC811) that meet the performance needs of present-day electric vehicles. In this work, solid-state upcycling of NMC622 via calcination with Ni(OH) 2 and LiOH was monitored using in situ synchrotron powder X-ray diffraction measurements. Sequential Rietveld refinements indicate that the calcination proceeds by initially converting Ni(OH) 2 to a rocksalt NiO phase followed by lithiation of NiO to form LiNiO 2 (LNO), with both NMC and LNO phases present in nearly equal proportions at the calcination endpoint. Variable-energy transmission X-ray microscopy tomograms of upcycled samples reveal that the NMC and LNO domains are intermixed at sub-micron length scales. Depth-dependent analysis of multi-elemental fitting maps matches the expected NMC811 composition at the secondary particle level and indicates that transition metal diffusion is not limited by the secondary particle size.

cathode upcycling↗
DOE OSTI2026

Neutron Scattering in Sodium-Ion Battery Research: Progress and Prospects

Sodium-ion batteries have attracted renewed interest in recent years and are widely studied as a complementary power source to Li-ion batteries for large-scale stationary energy storage and small electric vehicles. Compared with Li-ion batteries, Na-ion batteries offer several advantages, including elemental abundance, lower cost, improved safety, and better low-temperature performance. An in-depth understanding of Na-ion batteries across multiple length and time scales has further accelerated the rapid development of this technology. Among the various advanced characterization techniques used to study Na-ion batteries, neutron scattering has gained significant traction in recent years. It has become a powerful and versatile tool for probing structure, morphology, and sodium-ion dynamics over a wide range of length and time scales. In this article, we will briefly review the development of neutron scattering technology and highlight recent advances in applying neutron-based techniques—including neutron diffraction, total scattering, small-angle scattering, quasi-elastic/inelastic scattering, and neutron imaging—to Na-ion battery materials. We also provide perspectives on future technique developments, particularly in the realm of in situ and operando neutron scattering characterization, and discuss how these approaches could further enhance our understanding of Na-ion battery systems.

Liu, Jue [ORNL] (ORCID:000000024453910X)↗
DOE OSTI2026

Localized Heterogeneous Nucleation for Vapor‐Assisted Sequential Deposition of Metal Halide Perovskites

Vapor-assisted hybrid two-step deposition, which combines thermally evaporated inorganic layers with solution-processed organic halides to form halide perovskites, has emerged as a scalable and industry-compatible route for textured tandem photovoltaics. However, this process is often hindered by reaction-limited phase formation, particularly when compact, non-porous, and highly crystalline inorganic layers formed by thermal evaporation restrict subsequent conversion, resulting in incomplete reaction and pronounced depth-dependent heterogeneity. In this study, we introduce a strategy to regulate the inorganic precursor layer by incorporating localized heterogeneous nucleation sites. Sparsely distributed hydrophilic metal oxide species serve as effective nucleation centers during vapor deposition, enabling effective control over film morphology and crystal orientation from the early stages of growth. This tailored inorganic framework facilitates the subsequent incorporation of organic halides, alleviating reaction limitations and suppressing residual unreacted precursors. Consequently, the perovskite films exhibit improved stoichiometric uniformity and enhanced optoelectronic quality, enabling wide-bandgap perovskite solar cells with markedly improved performance and operational stability. This work provides important mechanistic insight into crystal growth engineering of vapor-deposited perovskite thin films.

nucleation↗
DOE OSTI2024

Representing cropping systems with the MEMS 2 ecosystem model

Abstract Croplands have been the focus of substantial investigation due to their considerable potential for sequestering carbon. Understanding the potential for soil organic carbon (SOC) sequestration and necessary management strategies will be enabled with accurate process‐based models. Accurately representing crop growth and agricultural practices will be critical for realistic SOC modeling. The MEMS 2 model incorporates a current understanding of SOC formation and stabilization, measurable SOC pools, and deep SOC dynamics and is seen as a highly promising tool to inform management intervention for SOC sequestration. Thus far, MEMS 2 has been developed to represent grasslands. In this study, we further developed MEMS 2 to model annual grain crops and common agricultural practices, such as irrigation, fertilization, harvesting, and tillage. Using four Ameriflux sites, we demonstrated an accurate simulation of crop growth and development. Model performance was strong for simulating aboveground biomass (index of agreement [d] range of 0.89–0.98) and green leaf area index (dfrom 0.90 to 0.96) across corn, soybean, and winter wheat. Good agreement with observations was also achieved for net ecosystem CO 2 exchange (dfrom 0.90 to 0.96), evapotranspiration (dfrom 0.91 to 0.94), and soil temperature (dof 0.96), while discrepancy with the available soil water content data remain (dfrom 0.14 to 0.81 at four depths to 100 cm). While we will continue model testing and improvement, MEMS 2 (version 2.14) has now demonstrated its ability to effectively simulate the growth of common grain crops and practices.

Agriculture↗
DOE OSTI2022

Modeling of deposit formation in mesoporous substrates via atomic layer deposition: Insights from pore‐scale simulation

Atomic layer deposition (ALD) has been a promising technique in fabricating membranes and tuning their properties with a precision at the atomic level. Fabrication of zeolitic imidazolate framework (ZIF) membranes using the ligand-induced permselectivation (LIPS) method starts with the formation of an oxide in a mesoporous substrate by ALD and is followed by the transformation of this oxide to ZIF using imidazolate vapor treatment. The objective of the ALD step is to block the mesopores with a thin deposit, that is, one with small penetration depth and small thickness on the top surface of the substrate. Unlike typical ALD on nonporous substrates, where all available sites react per ALD cycle, thin deposit formation in a mesoporous substrate requires that only a small fraction of the available deposition sites (i.e., close to the substrate surface) is subjected to ALD. Consequently, reactant dosing and duration of pulses are important process variables which, together with diffusion and reaction kinetics determine the deposit structure. Quantitative understanding of the interplay of these variables and phenomena can enable the rational design of ALD within mesoporous substrates. Here, we extend our earlier modeling effort considering the coexistence of ALD both inside the pores and on the external surface of the substrate. Finite-volume based models were developed and validated to simulate the two distinct modes of deposition cycle by cycle. The total mass uptake of the substrate with ALD cycles can be predicted using the combined surface deposition and pore reaction–diffusion models as affirmed by in situ quartz crystal microbalance experimental data. The ALD reactor model combined with the deposition model can accurately capture the number of ALD cycles needed to block the pores of the substrate. Based on the model, we designed a modified ALD process and examined the performance of the corresponding LIPS membranes. Furthermore, the present modeling work provides a new understanding of the deposit formation via ALD within mesoporous substrates for a variety of membrane applications.

atomic layer deposition↗
DOE OSTI2025

Uncontrolled Learning: Codesign of Neuromorphic Hardware Topology for Neuromorphic Algorithms

Neuromorphic computing has the potential to revolutionize future technologies and our understanding of intelligence, yet it remains challenging to realize in practice. The learning-from-mistakes algorithm, inspired by the brain's simple learning rules of inhibition and pruning, is one of the few brain-like training methods. This algorithm is implemented in neuromorphic memristive hardware through a codesign process that evaluates essential hardware trade-offs. While the algorithm effectively trains small networks as binary classifiers and perceptrons, performance declines significantly with increasing network size unless the hardware is tailored to the algorithm. This work investigates the trade-offs between depth, controllability, and capacity—the number of learnable patterns—in neuromorphic hardware. This highlights the importance of topology and governing equations, providing theoretical tools to evaluate a device's computational capacity based on its measurements and circuit structure. The findings show that breaking neural network symmetry enhances both controllability and capacity. Additionally, by pruning the circuit, neuromorphic algorithms in all-memristive circuits can utilize stochastic resources to create local contrasts in network weights. Through combined experimental and simulation efforts, the parameters are identified that enable networks to exhibit emergent intelligence from simple rules, advancing the potential of neuromorphic computing.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2022

Solving Large‐Scale Linear Systems of Equations by a Quantum Hybrid Algorithm

Abstract Today's intermediate‐scale quantum computers, although imperfect, already perform computational tasks that are manifestly beyond the capabilities of modern classical supercomputers. However, so far, quantum‐enabled large‐scale solutions have been realized only for limited set of problems. Here a hybrid algorithm based on phase estimation and classical optimization of the circuit width and depth is employed for solving a specific class of large linear systems of equations ubiquitous to many areas of science and engineering. A classification of linear systems based on the entanglement properties of the associated phase‐estimation unitary operation is introduced, enabling a highly efficient search for solutions that is facilitated by a straightforward matrix‐to‐circuit map. A 2 17 ‐dimensional problem is implemented on several IBM quantum computer superconducting quantum processors, a record‐breaking result for a linear system solved by a quantum computer. Demonstrated realisation sets a clear benchmark in the quest for the future quantum speedup in the linear systems of equations solution.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2025

Quantum‐Classical Simulation of Quantum Field Theory by Quantum Circuit Learning

Abstract Quantum circuit learning is employed to simulate quantum field theories (QFTs). Typically, when simulating QFTs with quantum computers, significant challenges are encountered due to the technical limitations of quantum devices when implementing the Hamiltonian using Pauli spin matrices. To address this challenge, quantum circuit learning is leveraged, employing a compact configuration of qubits and low‐depth quantum circuits to predict real‐time dynamics in quantum field theories. The key advantage of this approach is that a single‐qubit measurement can accurately forecast various physical parameters, including fully‐connected operators. To demonstrate the effectiveness of this method, it is used to predict quench dynamics, chiral dynamics and jet production in a 1+1‐dimensional model of quantum electrodynamics. It is found that our predictions closely align with the results of rigorous classical calculations, exhibiting a high degree of accuracy. This hybrid quantum‐classical approach illustrates the feasibility of efficiently simulating large‐scale QFTs on cutting‐edge quantum devices.

Ikeda, Kazuki [Department of Physics University of↗
DOE OSTI2020

An Atomic View of Cation Diffusion Pathways from Single‐Crystal Topochemical Transformations

Abstract The diffusion pathways of Li‐ions as they traverse cathode structures in the course of insertion reactions underpin many questions fundamental to the functionality of Li‐ion batteries. Much current knowledge derives from computational models or the imaging of lithiation behavior at larger length scales; however, it remains difficult to experimentally image Li‐ion diffusion at the atomistic level. Here, by using topochemical Li‐ion insertion and extraction to induce single‐crystal‐to‐single‐crystal transformations in a tunnel‐structured V 2 O 5 polymorph, coupled with operando powder X‐ray diffraction, we leverage single‐crystal X‐ray diffraction to identify the sequence of lattice interstitial sites preferred by Li‐ions to high depths of discharge, and use electron density maps to create a snapshot of ion diffusion in a metastable phase. Our methods enable the atomistic imaging of Li‐ions in this cathode material in kinetic states and provide an experimentally validated angstrom‐level 3D picture of atomic pathways thus far only conjectured through DFT calculations.

Handy, Joseph V.↗
DOE OSTI2023

Designing High‐Donicity Anions for Rechargeable Potassium Superoxide/Peroxide Batteries

Abstract A battery cathode based on the superoxide/peroxide redox not only inherits the advantage of oxygen (O 2 ) batteries in high capacities and low costs but also overcomes the disadvantages in O 2 storage, electrolyte evaporation, and anode deactivation due to O 2 crossover. Herein, we report an enhanced potassium superoxide (KO 2 )/peroxide (K 2 O 2 ) conversion by adopting a high‐donicity anion additive in the ether‐based electrolyte. Such an anion was synthesized via a “Solvent‐in‐Anion” strategy and validated to enhance the electron donicity of the electrolyte. The use of high‐donicity anion could lead to enhanced KO 2 utilization (≈90.2 %) by retarding electrode passivation and allow the full charging back of K 2 O 2 through the solution‐mediated pathway without electrocatalysts. No apparent cell degradation is observed during the first 120 cycles by controlling the reversible depth‐of‐discharge capacity at 292 mAh g −1 within an O 2 ‐free region. The K−KO 2 cell delivers a high energy efficiency (>84.4 %) and a lifespan of over 1440 hours.

Qin, Lei↗
DOE OSTI2023

Solid‐Adsorbed Polymer‐Electrolyte Interphases for Stabilizing Metal Anodes in Aqueous Zn and Non‐Aqueous Li Batteries

Abstract Polymers are known to adsorb spontaneously from liquid solutions in contact with high‐energy substrates to form configurationally complex, but robust phases that often exhibit higher durability than might be expected from the individual physical bonds formed with the substrate. Rational control of the physical, chemical, and transport properties of such interphases has emerged as a fundamental opportunity for scientific and technological advances in energy storage technology but requires in‐depth understanding of the conformation states and electrochemical effect of the adsorbed polymers. Here, we analyze the interfacial adsorption of oligomeric polyethylene glycol (PEG) chains of moderate sizes dissolved in protic and aprotic liquid electrolytes and find that there is an optimum polymer molecular weight of approximately 400 Da at which the highest columbic efficiency is achieved for both Zn and Li deposition. These findings point to a simple, versatile approach for extending the lifetime of batteries.

Jin, Shuo↗
DOE OSTI2020

Caught in the H inact : Crystal Structure and Spectroscopy Reveal a Sulfur Bound to the Active Site of an O 2 -stable State of [FeFe] Hydrogenase

[FeFe] hydrogenases are the most active H 2 converting catalysts in nature, but their extreme oxygen sensitivity limits their use in technological applications. The [FeFe] hydrogenases from sulfate reducing bacteria can be purified in an O 2 -stable state called H inact . To date, the structure and mechanism of formation of H inact remain unknown. Our 1.65 Å crystal structure of this state reveals a sulfur ligand bound to the open coordination site. Furthermore, in-depth spectroscopic characterization by X-ray absorption spectroscopy (XAS), nuclear resonance vibrational spectroscopy (NRVS), resonance Raman (RR) spectroscopy and infrared (IR) spectroscopy, together with hybrid quantum mechanical and molecular mechanical (QM/MM) calculations, provide detailed chemical insight into the Hinact state and its mechanism of formation. This may facilitate the design of O 2 -stable hydrogenases and molecular catalysts.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Ultrafast Metal Electrodeposition Revealed by In Situ Optical Imaging and Theoretical Modeling towards Fast–Charging Zn Battery Chemistry

Metallic Zn is a preferred anode material for rechargeable aqueous batteries towards a smart grid and renewable energy storage. Importantly, understanding how the metal nucleates and grows at the aqueous Zn anode is a critical and challenging step to achieve full reversibility of Zn battery chemistry, especially under fast-charging conditions. Here, by combining in situ optical imaging and theoretical modeling, we uncover the critical parameters governing the electrodeposition stability of the metallic Zn electrode, that is, the competition among crystallographic thermodynamics, kinetics, and Zn 2+ -ion diffusion. Moreover, steady-state Zn metal plating/ stripping with Coulombic efficiency above 99 % is achieved at 10-100 mA cm -2 in a reasonably high concentration (3 M) ZnSO 4 electrolyte. Significantly, a long-term cycling-stable Zn metal electrode is realized with a depth of discharge of 66.7% under 50 mA cm -2 in both Zn || Zn symmetrical cells and MnO 2 || Zn full cells.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗