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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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All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

A Novel Process for Converting Coal to High-Value Polyurethane Products

Battelle has demonstrated a patented process for making high-value, polyurethane (PU) foam from coal, based on preparing liquefied coal via direct liquefaction, converting it to polyols as an intermediate via ozonation, and then making PU foams from these polyols. This process represents a breakthrough in innovative utilization of U.S. coals, and is applicable to bituminous as well as sub-bituminous coals. The resulting PU foam products are projected to have an extremely high value (i.e., over $\$5,000$ /ton), with nearly 100% of carbon utilization from coalderived liquid feedstock, and 31.5% to 43.5% of the carbon in the PU foam polyol product being bio-based. The targeted products represent an extremely large (i.e., over $80 billion/year), existing PU foam market, which could expand into making coatings and adhesives. The process can further help reduce petroleum imports, while improving the economics of PU foam production. This work was completed with funding from the National Energy Technology Laboratory (NETL), with cost share from the State of Ohio’s Ohio Development Services Agency (ODSA) and others, and has advanced the process to 10 kg/day continuous scale and thus to Technology Readiness Level (TRL) 5. A total of 48 coal-based polyols were prepared and evaluated. The initial 28 polyols focused on range finding for ideal conditions. The later 20 polyols were produced as part of process optimizations. These optimizations were targeted around a continuous ozonolysis process to evaluate extended time reactions and to create the necessary intermediate for production of 1-gallon samples of polyol. The most unique attribute of Battelle’s polyol is in the utilization of coal’s aromaticity to gain final foam rigidity. Typically, polyols depend on the isocyanate fraction and cross-linking to gain rigidity. By utilizing coal, we were able to maintain rigidity while reducing the overall hydroxyl value of the polyol. This is important as lower hydroxyl value leads to greater percent weight of the coal-based polyol because less isocyanate is required for foaming. This leads to greater foam cost savings. This report provides the details, process, and process cost models of the conversion of coal to polyols and further to PU foams. Battelle’s process begins with coal liquids. These liquids can be obtained by two processes: coal coking or pyrolysis to produce coal tar, and Battelle’s biobased coal-to-liquids (CTL) process to produce heavy syncrude after liquifying >85% coal. After liquification, Battelle utilizes ozonolysis to create functionalization on the polyaromatic coal structure. The functionalization is then converted to the final polyester polyol through transesterification, or to hydroxyamide polyol through amidification. Equivalent or better standard properties have been obtained for 2 lb/ft 3 density rigid, water and freon-alternative blown foams, including compressive strength, density, R-value, and dimensional stability. Target applications for these foams are insulation, packaging, and energy-absorbing foams. Some exploratory testing also showed promise for adhesives applications. A detailed economic analysis showed that Battelle’s polyol process is economical, at a 140 metric tons per day (MTD) polyol production scale. An attractive return on investment (ROI) at competitive pricing validates the process is ready for a pilot-plant demonstration. A scale-up plan is provided.

01 COAL, LIGNITE, AND PEAT↗
DOE OSTI2025

Differentiable lagrangian shock hydrodynamics with application to stable shock acceleration of density interfaces

We develop a gradient based optimization approach for the equations of compressible, Lagrangian hydrodynamics and demonstrate how it can be employed to automatically uncover strategies to control hydrodynamic instabilities arising from shock acceleration of density interfaces. Strategies for controlling the Richtmyer-Meshkov instability (RMI) are of great benefit for inertial confinement fusion (ICF) where shock interactions with many small imperfections in the density interface lead to instabilities which rapidly grow over time. These instabilities lead to mixing which, in the case of laser driven ICF, quenches the runaway fusion process ruining the potential for positive energy return. Here, we demonstrate that control of these instabilities can be achieved by optimization of initial conditions with ( > 100) parameters. Optimizing over a large parameter space like this is not possible with gradient-free optimization strategies. This requires computation of the gradient of the outputs of a numerical solution to the equations of Lagrangian hydrodynamics with respect to the inputs. We show that the efficient computation of these gradients is made possible via a judicious application of (i) adjoint methods, the exact formal representation of sensitivities involving partial differential equations, and (ii) automatic differentiation (AD), the algorithmic calculation of derivatives of functions. Careful regularization of multiple operators including artificial viscosity and timestep control is required. We perform design optimization of > 100 parameter energy field driving the Richtmyer Meshkov instability showing significant suppression while simultaneously enhancing the acceleration of the interface relative to a nominal baseline case.

Hydrophysics↗
DOE OSTI2025

Single-shot in-line x-ray phase-contrast imaging of void-shockwave interactions in fusion energy materials

Recent breakthroughs in nuclear fusion, specifically the report of reactions exceeding scientific breakeven at the National Ignition Facility (NIF), highlight the potential of inertial fusion energy (IFE) as a sustainable and virtually limitless energy source. However, further progress in IFE requires characterization of defects in ablator materials and how they affect fuel capsule compression. Voids within the ablator can degrade energy yield, but their impact on the density distribution has primarily been studied through simulations, with limited high-resolution experimental validation. To address this, we used the x-ray free-electron laser (XFEL) at the matter in extreme conditions (MECs) instrument at the Linac coherent light source (LCLS) to capture 2D x-ray phase-contrast (XPC) images of a void-bearing sample with a composition similar to inertial confinement fusion (ICF) ablators. By driving a compressive shockwave through the sample using MEC's long-pulse laser system, we analyzed how voids influence shockwave propagation and density distribution during compression. To quantify this impact, we extracted phase information using two phase retrieval algorithms. First, we applied the contrast transfer function (CTF) method, paired with Tikhonov regularization and a fast optimization approach to generate an initial phase estimate. We then refined the result using a projected gradient descent (PGD) method that works directly with the sample's refractive index. Comparing these results with radiation adaptive grid Eulerian (xRAGE) radiation hydrodynamic simulations enables identification of model validation needs or improvements. By calculating phase maps in situ, it becomes possible to reconstruct areal density maps, improving understanding of laser-capsule interactions and advancing IFE research.

Hodge, D. S. [Colorado State Univ., Fort Collins, ↗
DOE OSTI2018

Hydrogen at Scale (H 2 @Scale): Key to a Clean, Economic, and Sustainable Energy System

Much of hydrogen's value to the energy-system lies in its ability to be cleanly and efficiently converted between chemical and electrical energy, while also possessing the high energy density and long-term storage potential of chemical bonds. For these reasons, hydrogen's importance is expected to grow substantially in the coming decades, providing cross-sector and cross-temporal impact through clean, efficient processes. Many of these processes are electrochemical in nature, such as electrolysis of water and electricity production using fuel cells. Hydrogen also offers significant flexibility in how it can integrate into the energy system as a function of scale (from W to GWs), source (fossil fuels, nuclear, biomass, solar, wind, thermal), and end use (grid, buildings, industry, transportation). This flexibility, along with the ability to be used as a dispatchable load or power generation source, allows hydrogen and hydrogen-based processes to couple with the overall energy system in an integrated or hybridized fashion, offering dramatic system optimization potential. However, achieving the scale necessary to have impact - the vision 'Hydrogen at Scale' (H2@Scale) still has research challenges, many of which center around electrochemistry.

08 HYDROGEN↗
DOE OSTI2023

Adaptive Discovery and Mixed-Variable Optimization of Next Generation Synthesizable Microelectronic Materials

Design of new microelectronic materials is characterized by several challenges such as high-dimensionality of the atomic structure-composition variable space, formidable cost of directly using high-fidelity simulations for design optimization, dispersity in literature-reported similar materials and synthesis methods, complex physical mechanisms, and mixed qualitative and quantitative design variables that lead to a disjointed design space. Even though machine learning (ML) techniques have been employed to expedite materials innovation, existing methods treat ML and design optimization as two separate processes, failing to resolve the fundamental challenges associated with high dimensionality and mixed-variable complexity. We have developed a ML enhanced mixed-variable material design optimization framework to efficiently extract useful information from existing data in literature and physics-based simulations to guide the autonomous search for optimal materials. Our proposed framework is composed of four computational modules: (1) a natural language processing (NLP) based virtual screening module, (2) classification based concept exploration module, (3) a density functional theory (DFT)-based high-fidelity evaluation model, and (4) a novel latent-variable Gaussian process (LVGP) ML model for mixed-variable problems with uncertainty quantification, which seamlessly integrates with Bayesian Optimization (BO) and achieves superb efficiency through embedded physics-based dimension reduction. Our approach is demonstrated and validated using the testbed of functional materials exhibiting metal-insulation transitions (MITs), with the targeted reversible resistivity changes (∼10^5) near room temperature. At the end of the 30-month project, we have developed a series of new ML techniques using NLP, conditional variational autoencoders, active learning, latent-variable Gaussian processes, integrated with Bayesian optimization. Our project has resulted in new predicted MITs compounds and improved understanding of MITs microscopic mechanisms, which in turn will revolutionize microelectronics science to provide energy-saving solutions. Our research has improved both creativity and efficiency in transforming rare-event discoveries of new functional materials to persistent innovations. In addition to open-sourcing the online MIT database and the classification model, the LVGP open source code has been downloaded more than 15,000 times within two years. More than 40 MIT compounds have been identified and many have been pursued experimentally via collaborators. The research results are published in close to 20 collaborative papers in high-impact journals, such as Chem. Mater., Appl. Phys. Rev., Sci. Rep., among others of design space.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Ferromagnetic Atomic d ‐ p Orbital Hybridization for Promoting Al‐S Batteries

Rechargeable aluminum‐sulfur batteries (Al‐S) are emerging as a promising alternative energy storage system beyond lithium‐ion batteries due to their high energy density, abundant material resources, and economic efficiency. However, their practical application remains challenged by sluggish conversion kinetics, polysulfide shuttling, and low sulfur cathode utilization. While extensive studies have focused on enhancing polysulfide adsorption through catalytic strategies, the roles of electronic structure in dictating catalytic performance remain underexplored. Here, this work unveils the critical effect of unpaired electronic structure on the catalytic performance of single atom ferromagnetic transition metals through a systematic evaluation of three typical atomically dispersed ferromagnetic single atoms—Fe, Co, and Ni—supported on porous carbon (denoted as PC‐SAFAs). Comprehensive characterizations and density functional theory (DFT) calculations reveal that the PC‐SAFe catalysts, exhibiting the highest spin polarization arising from unpaired electrons, demonstrate the strongest interactions with polysulfide, thereby facilitating rapid and reversible polysulfide conversion reactions. Consequently, Al‐S batteries incorporating the optimized PC‐SAFe cathode achieve an impressive specific capacity of 508.8 mAh g −1 at 1.0 A g −1 after 500 cycles, along with much improved rate capability. In conclusion, this work provides a deeper understanding of the role of electronic structure in catalytic chemistry, and offers new insights for developing high‐performance Al‐S batteries.

36 MATERIALS SCIENCE↗
DOE OSTI2017

Improved treatment of exact exchange in Quantum ESPRESSO

Here, we present an algorithm and implementation for the parallel computation of exact exchange in Quantum ESPRESSO (QE) that exhibits greatly improved strong scaling. QE is an open-source software package for electronic structure calculations using plane wave density functional theory, and supports the use of local, semi-local, and hybrid DFT functionals. Wider application of hybrid functionals is desirable for the improved simulation of electronic band energy alignments and thermodynamic properties, but the computational complexity of evaluating the exact exchange potential limits the practical application of hybrid functionals to large systems and requires efficient implementations. We demonstrate that existing implementations of hybrid DFT that utilize a single data structure for both the local and exact exchange regions of the code are significantly limited in the degree of parallelization achievable. We present a band-pair parallelization approach, in which the calculation of exact exchange is parallelized and evaluated independently from the parallelization of the remainder of the calculation, with the wavefunction data being efficiently transformed on-the-fly into a form that is optimal for each part of the calculation. For a 64 water molecule supercell, our new algorithm reduces the overall time to solution by nearly an order of magnitude.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2015

General study on the crystal, electronic and band structures, the morphological characterization, and the magnetic properties of the Sr{sub 2}DyRuO{sub 6} complex perovskite

A comprehensive investigation of the general properties of the Sr{sub 2}DyRuO{sub 6} complex perovskite was undertaken. Crystal structure characterization performed by X-ray diffraction measurements and Rietveld analysis allowed establishing that the material crystallizes in a distorted monoclinic perovskite-like structure belonging to the P2{sub 1}/n (#14) space group, with alternating distribution of Dy{sup 3} {sup +} (2c: 0, 0.5, 0) and Ru{sup 5} {sup +} (2d: 0.5, 0, 0). Because of the mismatch in the ionic radii, the DyO{sub 6} and RuO{sub 6} octahedra are forced to tilt around the cubic directions so as to optimize the Sr–O inter-atomic bond lengths. Morphological characterization carried out by scanning electron microscopy indicated a particle size D = 37.17 nm and an activation energy Q = 109.8 kJ/mol. Semi-quantitative compositional study, performed through energy-dispersive X-ray experiments, corroborated that the pure phase of the Sr{sub 2}DyRuO{sub 6} was correctly obtained. Magnetic properties determined from the fit of the Curie–Weiss law to the curves of magnetic susceptibility as a function of temperature showed that Sr{sub 2}DyRuO{sub 6} exhibits an antiferromagnetic-like behavior at low temperatures as a consequence of a magnetic transition at T = 38 K. Data collected with respect to the field dependence of the magnetization showed the existence of a weak ferromagnetic moment relationship with antiferromagnetic-like behavior. Density functional theory allowed establishing the optimum electronic structure for Sr{sub 2}DyRuO{sub 6}, and the study of the density of states showed that Dy{sup 3} {sup +} and Ru{sup 5} {sup +} are responsible for the magnetic character of the compound, with the prediction that at T = 0 K it behaves as a half-metallic material. The spin magnetic moment of the cell is close to 16 μ{sub B}, and the integer number of Bohr magneton is a signature of half-metallic character. Evolution of crystal structure at high temperature revealed that Sr{sub 2}DyRuO{sub 6} does not undergo any structural phase transitions, since the Bragg reflections [hkl] do not undergo changes, and the structure is preserved. - Highlights: • General properties of the Sr{sub 2}DyRuO{sub 6} complex perovskite are widely discussed. • Structural description of octahedral distortions from X-ray diffraction analysis is performed. • Morphological and compositional characteristics are related with the physical properties reported. • Antiferromagnetic response is discussed form experimental results. • Theoretical calculations reveal the possible half-metallic character of material.

36 MATERIALS SCIENCE↗
DOE OSTI2021

A Machine Learning Approach for the Prediction of Formability and Thermodynamic Stability of Single and Double Perovskite Oxides

Perovskite oxides continue to attract huge interest due to their fascinating and wide-ranging properties for diverse applications. The tunability of these properties may be further enhanced by increasing their compositional complexity via double perovskite-ordered configurations containing multiple cations. In this work, we focus on an exhaustive chemical space of single and double oxide perovskites and optimally explore this space to identify novel compositions that are likely to form stable compounds. Critically, we examine the relationship between formability, the practical ability to synthesize a compound, and stability, the thermodynamic preference to form the structure. Our formability and stability training data sets were enumerated from the available experimental literature and in-house density functional theory computations and contained 1505 and 3469 examples, respectively, representing state-of-the-art in the current open literature in perovskite and double perovskite compounds. Subsequently, cross-validated and highly accurate machine learning classification models are built using these training data sets and employed to screen for novel stable oxide perovskites. The study identifies (1) atomic features relevant to prediction of formability and stability in perovskite and double perovskite compounds, (2) the importance of including energy contributions due to local structural relaxations going beyond the high symmetry perovskite phase, and (3) 437,828 double perovskite compounds that are likely to be stable and 891,188 compounds that are likely to be formable. From the intersection of this large chemical space of formable and stable oxide perovskites, 414 compositions are identified as the most promising candidates for future experimental synthesis of novel oxide perovskites. The developed models may be generalized and have implications beyond perovskite discovery if applied to other families of compounds.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2017

Geometry and growth contributions to cosmic shear observables

We explore the sensitivity of weak-lensing observables to the expansion history of the Universe and to the growth of cosmic structures, as well as the relative contribution of both effects to constraining cosmological parameters. We utilize ray-tracing dark-matter-only N-body simulations and validate our technique by comparing our results for the convergence power spectrum with analytic results from past studies. We then extend our analysis to non-Gaussian observables which cannot be easily treated analytically. We study the convergence (equilateral) bispectrum and two topological observables, lensing peaks and Minkowski functionals, focusing on their sensitivity to the matter density Ω m and the dark energy equation of state w. We find that a cancellation between the geometry and growth effects is a common feature for all observables and exists at the map level. It weakens the overall sensitivity by factors of up to 3 and 1.5 for w and Ω m , respectively, with the bispectrum worst affected. However, combining geometry and growth information alleviates the degeneracy between Ω m and w from either effect alone. As a result, the magnitudes of marginalized errors remain similar to those obtained from growth-only effects, but with the correlation between the two parameters switching sign. Furthermore, these results shed light on the origin of the cosmology sensitivity of non-Gaussian statistics and should be useful in optimizing combinations of observables.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2019

Genome-wide association analysis of stalk biomass and anatomical traits in maize

Maize stover is an important source of crop residues and a promising sustainable energy source in the United States. Stalk is the main component of stover, representing about half of stover dry weight. Characterization of genetic determinants of stalk traits provide a foundation to optimize maize stover as a biofuel feedstock. We investigated maize natural genetic variation in genome-wide association studies (GWAS) to detect candidate genes associated with traits related to stalk biomass (stalk diameter and plant height) and stalk anatomy (rind thickness, vascular bundle density and area). Using a panel of 942 diverse inbred lines, 899,784 RNA-Seq derived single nucleotide polymorphism (SNP) markers were identified. Stalk traits were measured on 800 members of the panel in replicated field trials across years. GWAS revealed 16 candidate genes associated with four stalk traits. Most of the detected candidate genes were involved in fundamental cellular functions, such as regulation of gene expression and cell cycle progression. Two of the regulatory genes ( Zmm22 and an ortholog of Fpa) that were associated with plant height were previously shown to be involved in regulating the vegetative to floral transition. The association of Zmm22 with plant height was confirmed using a transgenic approach. Transgenic lines with increased expression of Zmm22 showed a significant decrease in plant height as well as tassel branch number, indicating a pleiotropic effect of Zmm22 . Substantial heritable variation was observed in the association panel for stalk traits, indicating a large potential for improving useful stalk traits in breeding programs. Genome-wide association analyses detected several candidate genes associated with multiple traits, suggesting common regulatory elements underlie various stalk traits. Finally, results of this study provide insights into the genetic control of maize stalk anatomy and biomass.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Inferring relative dose-dependent color center populations in proton irradiated thoria single crystals using optical spectroscopy

In this work, we have utilized photoluminescence spectroscopy and optical ellipsometry to characterize the dose-dependence of the photoluminescence emission intensity and changes in optical absorption of thoria single crystals subject to irradiation with energetic protons at room- and elevated-temperatures. The photoluminescence peaks and the optical absorption bands are attributed to creation of new electronic states emerging from defects resulting from displacement damage. These bands are most likely associated with electrons trapped at the oxygen vacancy sites similar to color centers formed in other irradiated oxides and halides. Our experimental observations are supported by a standard density functional theory calculation of the electronic structure in pristine and oxygen vacancy-bearing thoria crystals. The dose-dependence of the intensity of the photoluminescence peaks is used to parameterize a rate theory model that estimates the concentration of color centers in the irradiated crystals. This parameterization provides optimized migration barrier parameters for oxygen interstitials and vacancies that simultaneously capture the optical response of the crystals irradiated at room- and elevated-temperature. These optical spectroscopy techniques offer a promising pathway to characterize the population of color centers formed at the sites of oxygen anion vacancies, particularly in irradiated nuclear fuels, where atomic-level defects cannot be readily imaged using electron microscopy. When combined with other direct and indirect characterization tools, our approach can provide new insight into defect formation and accumulation in energy materials over single atomic to extended length scales.

36 MATERIALS SCIENCE↗
DOE OSTI2018

First‐principles study in an inter‐granular glassy film model of silicon nitride

Abstract Based on a previously constructed intergranular glassy film ( IGF ) model for bulk silicon nitride, a large periodic model of 3864 atoms containing 2 grains of different orientations from the main bulk β‐Si 3 N 4 and 2 IGF s was fully relaxed using the ab initio density‐functional theory package VASP . The relaxed structure was then used to calculate the electronic structure, density of states, interatomic bonding, partial charge distribution, and electron localization using the OLCAO method. Analysis of the data focuses on the interfacial regions between bulk β‐Si 3 N 4 and the Si‐O‐N glass layer with different orientations. The total bond order density ( TBOD ) is evaluated in different interfacial and bulk regions. We show minor differences in the internal cohesion between crystalline grains of different facets. However, the overall charges in the bulk crystal grains and in the glassy regions are electropositive which are balanced by the negatively charged interfacial region between the two. The presence of a less rigid glassy layer is the reason for structural flexibility in ceramics without a huge penalty in the steric energy. The optimization of the interfacial structure and bonding via the creation of defective sites is the atomic origin for the existence of the IGF in silicon nitride. The insights obtained from this detailed quantum mechanical analysis of a realistic IGF model are discussed including implications on the strength, fracture toughness, and processing methods. We also discuss the potential applications of our method to other complex materials systems.

Ching, Wai‐Yim↗
DOE OSTI2019

Designing Optimal Perovskite Structure for High Ionic Conduction

Solid-oxide fuel/electrolyzer cells are limited by a dearth of electrolyte materials with low ohmic loss and an incomplete understanding of the structure-property relationships that would enable the rational design of better materials. In this work, using epitaxial thin-film growth, synchrotron radiation, impedance spectroscopy, and density-functional theory, the impact of structural parameters (i.e., unit-cell volume and octahedral rotations) on ionic conductivity is delineated in La 0.9 Sr 0.1 Ga 0.95 Mg 0.05 O 3-σ . As compared to the zero-strain state, compressive strain reduces the unit-cell volume while maintaining large octahedral rotations, resulting in a strong reduction of ionic conductivity, while tensile strain increases the unit-cell volume while quenching octahedral rotations, resulting in a negligible effect on the ionic conductivity. Calculations reveal that larger unit-cell volumes and octahedral rotations decrease migration barriers and create low-energy migration pathways, respectively. The desired combination of large unit-cell volume and octahedral rotations is normally contraindicated, but through the creation of superlattice structures both expanded unit-cell volume and large octahedral rotations are experimentally realized, which result in an enhancement of the ionic conductivity. All told, the potential to tune ionic conductivity with structure alone by a factor of ≈ 2.5 at around 600 degrees C is observed, which sheds new light on the rational design of ion-conducting perovskite electrolytes.

36 MATERIALS SCIENCE↗
DOE OSTI2017

Co,N-codoped graphene as efficient electrocatalyst for hydrogen evolution reaction: Insight into the active centre

Co and N co-doped carbon (CNC) material is one of the most promising precious-metal-free catalyst for hydrogen evolution reaction (HER), however, widespread application of CNC will require continuous innovation and optimization of fabrication to maximize electrocatalytic performance, which is always a challenge. Herein, two types of three-dimensional (3D) graphene materials synthesized by one-step of simultaneous doping (Co,N/3DG-1) and two-step of sequential doping (Co,N/3DG-2) respectively, are evaluated and correlated their electrocatalytic activity for HER with experimental parameters. The results indicate that Co,N/3DG-2 exhibits significantly better electrocatalytic activity than Co,N/3DG-1. The structure analysis reveals that Co,N/3DG-2 has more moderate Co-N coordinated number than Co,N/3DG-1. Density functional theory calculations unravels that the equilibrium C and N around Co atom is more favorable to the adsorption and desorption of hydrogen. In conclusion, the results shed new light on the rational design of dual hetero-atom co-doped carbon materials, which may be applicable to other energy conversion and storage systems.

electrocatalyst↗
DOE OSTI2020

Superlattice-Structured Films by Magnetron Sputtering as New Era Electrodes for Advanced Lithium-ion Batteries

Sustaining sound structures in Si-based anodes is extremely challenging because of the high volumetric expansion that occurs upon cycling. To maintain high capacities over cycles, new designs rely on engineering-specific hierarchical geometries and/or optimized composite compositions such that at least one of the multiple elements serves as buffer and/or electron conductive pathways in the electrodes. In this paper, we report an innovative design in which alternating layers of periodic atomic structures involving multiple elements form a new anode material for lithium-ion batteries. In this work, a superlattice-structured amorphous film made using Si, Mo, and Cu is fabricated by a simple and scalable magnetron sputtering process for the first time. This continuous and repetitive superlattice formation along the film thickness provides a homogeneous stress-strain distribution. The Mo-Cu layer in the superlattice acts as an inactive-conductive layer and as a backbone to handle the volume expansion of active Si upon cycling. This nano-functional superlattice approach enables harnessing the high energy density of Si while maintaining its structural stability. As a result, the electrode exhibits high specific capacity and capacity retention even at high cycling rates. The possible use of the film in a full cell is also evaluated by cycling it vs. the LiMn 1.5 Ni 0.5 O 4 cathode. The full cell maintains a stable capacity of about 900 mAh g anode -1 over 150 cycles, at ~600 mA g -1 rate. The remarkable performance of this nano-functional superlattice film is found to be promising as anodes for applications that require high energy, long calendar life, and excellent abuse tolerance such as electric vehicle batteries.

25 ENERGY STORAGE↗
DOE OSTI2018

Protonic ceramic electrochemical cells for hydrogen production and electricity generation: exceptional reversibility, stability, and demonstrated faradaic efficiency

Here, we demonstrate exceptional performance for steam electrolysis at intermediate temperatures (500–650 °C) using protonic ceramic electrolyte cells comprised of the proton-permeable, high-activity mixed conductor PrBa 0.5 Sr 0.5 Co 1.5 Fe 0.5 O 5+δ (PBSCF) as the air electrode, the highly proton-conductive and chemically stable perovskite oxide BaZr 0.4 Ce 0.4 Y 0.1 Yb 0.1 O 3 (BZCYYb4411) as the electrolyte, and a composite of Ni–BZCYYb4411 as the fuel electrode. Cells constructed from this material set have been shown previously to function efficiently in fuel cell mode. We demonstrate here reversible operation, enabling hydrogen production when excess electricity is available and immediate electricity generation from stored hydrogen when power demand is high. The cells are stable under cyclic operation and also under prolonged continuous operation in electrolysis mode, undergoing minimal loss in electrochemical characteristics after 500 h at 550 °C. Microstructurally optimized cells yield a remarkable current density of -1.80 A cm -2 at 600 °C and an operating voltage of 1.3 V, of which, based on an electrochemically deduced faradaic efficiency of 76%, -1.37 A cm -2 contributes to useful hydrogen.

25 ENERGY STORAGE↗