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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 199 records · Page 11
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Electron transfer calculations between edge sharing octahedra in hematite, goethite, and annite

A key reaction underlying the charge transport in iron containing oxides, clays, micas is the Fe$^{2+}$-Fe$^{3+}$ exchange reaction between edge-sharing iron octahedra. These reactions facilitate conduction in these minerals by the thermally-activated hopping of small polarons across the lattice. Depending on the mineral and local charge state the small polaron can either encase an electron or hole. The probability for conduction of small polarons depends strongly on the height and adiabicity of the reaction barrier, with larger and more diabatic barriers yielding slow conduction associated with either weak coupling or a large prerequisite rearrangement of the lattice during charge transport. To model these reactions, a first principle electron transfer (ET) method was developed to model the small polaron hopping between the edge-sharing octahedra sites in hematite ($e^{-}$ polaron), goethite ($e^{-}$ polaron), and annite ($h^{+}$ polaron) bulk structures. The ET method is based on electronic structure methods (i.e., plane-wave Density Functional Theory) capable of performing calculations with periodic cells and large size systems efficiently while at the same time being accurate enough to be used in the estimation of the electron-transfer coupling matrix element, $V_{AB}$, and the electron transfer transmission factor, $\kappa_{el}$. Additionally, the calculations confirmed the existence of small polarons in all three minerals, and the reactions were predicted to be strongly adiabatic. It was found that transfer of a hole in the octahedral layer of annite had an adiabatic barrier of $0.311$ eV, and the transfer of an extra electron in hematite and goethite had adiabatic barriers of $0.242$ eV and $0.232$ eV respectively. The electronic coupling parameters,$V_{AB}$, were found to be $0.188$ eV, $0.196$ eV, and $0.102$ eV respectively for hematite, goethite, and annite. While similar bonding topologies pertain, the underlying basis for the differences is the subtle differences in local structures.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

A fine pore-preserved deep neural network for porosity analytics of a high burnup U-10Zr metallic fuel

Abstract U-10 wt.% Zr (U-10Zr) metallic fuel is the leading candidate for next-generation sodium-cooled fast reactors. Porosity is one of the most important factors that impacts the performance of U-10Zr metallic fuel. The pores generated by the fission gas accumulation can lead to changes in thermal conductivity, fuel swelling, Fuel-Cladding Chemical Interaction (FCCI) and Fuel-Cladding Mechanical Interaction (FCMI). Therefore, it is crucial to accurately segment and analyze porosity to understand the U-10Zr fuel system to design future fast reactors. To address the above issues, we introduce a workflow to process and analyze multi-source Scanning Electron Microscope (SEM) image data. Moreover, an encoder-decoder-based, deep fully convolutional network is proposed to segment pores accurately by integrating the residual unit and the densely-connected units. Two SEM 250 × field of view image datasets with different formats are utilized to evaluate the new proposed model’s performance. Sufficient comparison results demonstrate that our method quantitatively outperforms two popular deep fully convolutional networks. Furthermore, we conducted experiments on the third SEM 2500 × field of view image dataset, and the transfer learning results show the potential capability to transfer the knowledge from low-magnification images to high-magnification images. Finally, we use a pre-trained network to predict the pores of SEM images in the whole cross-sectional image and obtain quantitative porosity analysis. Our findings will guide the SEM microscopy data collection efficiently, provide a mechanistic understanding of the U-10Zr fuel system and bridge the gap between advanced characterization to fuel system design.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Adaptive elasticity policies for staging-based in situ visualization

In situ processing aims to alleviate the growing gap between computation and I/O capabilities by performing data processing close to the data source. In situ processing is widely used to process data generated by multiple data sources, including observation data from edge devices or scientific observational facilities and the simulation data generated by scientific computation on a high-performance computing (HPC) platform. For a scientific workflow that is run on an HPC platform and composed of a simulation program and an in situ data analytics or visualization (abbreviated as ana/vis) task, there is an implicit assumption that the computing resources assigned to the workflow keep static during the workflow execution. However, with the converging trend between the HPC and cloud computing platform, running the in situ ana/vis task in an elastic way is promising to decrease its overhead and improve its resource utilization rate. Resource elasticity represents the ability to change resource configurations such as the number of computing nodes/processes during workflow execution. An elastic job may dynamically adjust resource configurations; it may use a few resources at the beginning and more resources toward the end of the job when interesting data appear. However, it is hard to predict a priori how many computing nodes/processes need to be added/removed during the workflow execution to adapt to changing workflow needs. How to efficiently guide elasticity operations, such as growing or shrinking the number of processes used for in situ analysis during workflow execution, is an open-ended research question. In this article, we present adaptive elasticity policies that adopt workflow runtime information collected during workflow execution to predict how to trigger the addition/removal of processes in order to minimize in situ processing overhead. Taking in situ visualization tasks as an example, we integrate the presented elasticity policies into a staging-based elastic workflow and evaluate its efficiency in multiple elasticity scenarios. Compared with the situation without elasticity or with a static elasticity policy that uses a fixed number of processes for each rescaling operation, the adaptive elasticity policy can save overhead in finding a proper resource configuration and improve resource utilization efficiency. Furthermore, one experiment illustrates that the adaptive elasticity policy saves 41% of core-hours compared with the situation without the resource elasticity.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Analysis of basic airflow configurations for separate sensible and latent cooling systems with indoor air recirculation

Separate sensible and latent cooling (SSLC) is a technology with efficiency and comfort advantages over conventional cooling systems used for space conditioning of buildings. Using multiple cooling processes at different temperatures allows SSLC to save energy by raising the evaporation temperature of the sensible cooling process. In this paper, all possible airflow configurations of SSLC systems are enumerated under the following constraints: exactly two heat exchangers are used, and air is recirculated to the conditioned space (no exhaust or outdoor air treatment). Seven designs are identified, with varying free operating variables, and each is modeled. Analysis reveals that several configurations are equivalent, and there is only one unique basic airflow SSLC configuration: the one with the sensible and latent heat exchangers placed in series. The efficiency of the SSLC system is compared against that of the conventional system. Under standard conditions, an SSLC system can improve the coefficient of performance by 14.8%. In addition to the numerical simulation, the optimal operating condition of the basic air configuration of the SSLC system is derived analytically. The basic SSLC system is shown to offer the highest performance improvement when the outdoor temperature is relatively cool and the space sensible heat ratio is high.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2021

In Situ, Protein-Mediated Generation of a Photochemically Active Chlorophyll Analogue in a Mutant Bacterial Photosynthetic Reaction Center

All possible natural amino acids have been substituted for the native LeuL185 positioned near the B-side bacteriopheophytin (H B ) in the bacterial reaction center (RC) from Rhodobacter sphaeroides. Additional mutations are present that enhance electron transfer to the normally inactive B-side cofactors. About half the isolated RCs with Glu at L185 contain a magnesium chlorin (C B ) in place of H B . The chlorin is not the common BChl a oxidation product 3-desvinyl-3-acetyl chlorophyll a with a C-C bond in ring D and a C=C bond in ring B, but has properties consistent with reversal of these bond orders, giving 17,18-didehydro BChl a. In such RCs, charge-separated state P + C B – forms with ~5% yield. The other half of the GluL185-containing RCs have a bacteriochlorophyll a (BChl a) denoted β B in place of H B . Residues His, Asp, Asn and Gln at L185 yield RCs with ≥85% β B in the H B site, while most other amino acids result in RCs that retain H B (≥95%). To our knowledge, neither bacterial RCs that harbor five BChl a and one chlorophyll analog nor ones with six BChl a have been reported previously. The finding that altering the local environment within a cofactor binding site of a transmembrane complex leads to in situ generation of a photoactive chlorin with an unusual ring oxidation pattern suggests new strategies for amino-acid control over pigment type at specific sites in photosynthetic proteins.

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

Evaluating Spatial Accelerator Architectures with Tiled Matrix-Matrix Multiplication.

There is a growing interest in custom spatial accelerators for machine learning applications. These accelerators employ a spatial array of processing elements (PEs) interacting via custom buffer hierarchies and networks-on-chip. The efficiency of these accelerators comes from employing optimized dataflow (i.e., spatial/temporal partitioning of data across the PEs and fine-grained scheduling) strategies to optimize data reuse. The focus of this work is to evaluate these accelerator architectures using a tiled general matrix-matrix multiplication (GEMM) kernel. To do so, we develop a framework that finds optimized mappings (dataflow and tile sizes) for a tiled GEMM for a given spatial accelerator and workload combination, leveraging an analytical cost model for runtime and energy. Finally, our evaluations over five spatial accelerators demonstrate that the tiled GEMM mappings systematically generated by our framework achieve high performance on various GEMM workloads and accelerators.

42 ENGINEERING↗
DOE OSTI2022

MELCOR Accident Progression and Source Term Demonstration Calculations for a HTGR

MELCOR is an integrated thermal hydraulics, accident progression, and source term code for reactor safety analysis that has been developed at Sandia National Laboratories for the United States Nuclear Regulatory Commission (NRC) since the early 1980s. Though MELCOR originated as a light water reactor (LWR) code, development and modernization efforts over the past decades have expanded its application scope to include non-LWR reactor concepts. Current MELCOR development efforts include providing the NRC with the analytical capabilities to support regulatory readiness for licensing non-LWR technologies under Strategy 2 of the NRC's near-term Implementation Action Plans. Beginning with the Next Generation Nuclear Project (NGNP), MELCOR ha s undergone a range of enhancements to provide analytical capabilities for modeling the spectrum of advanced non-LWR concepts. This report describes the generic plant model developed to demonstrate MELCOR capabilities to perform high-temperature gas reactor (HTGR) safety evaluations. The generic plant model is based on publicly available PMBR-400 design information. For plant aspects (e.g., reactor building size and leak rate) that are not described in the PBMR-400 references, the analysts made assumptions needed to construct a MELCOR full-plant model. The HTGR model uses a TRi-structural ISOtropic (TRISO)-particle fuel pebble-bed reactor with a primary system rejecting heat to a recuperative heat exchange r. Surrounding the reactor vessel is a reactor cavity contained within a confinement room cooled by the Reactor Cavity Cooling System (RCCS). Example calculations are performed to show the plant response and MELCOR capabilities to characterize a range of accident conditions. The accidents selected for evaluation consider a range of degraded and failed modes of operation for key safety functions providing reactivity control, primary system heat removal and reactor vessel decay heat removal, and confinement cooling.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2025

Jipole: A Differentiable ipole-based Code for Radiative Transfer in Curved Spacetimes

Recent imaging of supermassive black holes by the Event Horizon Telescope has relied on exhaustive parameter-space searches, matching observations to large, precomputed libraries of theoretical models. As observational data become increasingly precise, the limitations of this computationally expensive approach grow more acute, creating a pressing need for more efficient methods. In this work, we present Jipole, an automatically differentiable (AD), ipole-based code for radiative transfer in curved spacetimes, designed to compute image gradients with respect to underlying model parameters. These gradients quantify how parameter changes—such as the black hole’s spin or the observer’s inclination—affect the image, enabling more efficient parameter estimation and reducing the number of required images. We validate Jipole against ipole in two analytical tests and then compare pixelwise intensity derivatives from AD with those from finite-difference methods. We then demonstrate the utility of these gradients by performing parameter recovery for an analytical model in three increasingly complex cases for the injected image: ideal, blurred, and blurred with added noise. In most cases, high-accuracy fits are obtained in only a few optimization steps, failing only in cases with extremely low signal-to-noise ratios. These results highlight the potential of AD-based methods to accelerate robust, high-fidelity model-data comparisons in current and future black hole imaging efforts.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2024

Custom Accessors: Enabling Scalable Data Ingestion, (Re-)Organization, and Analysis on Distributed Systems

The emerging class of high velocity and high volume data analytic workflows comprise interwoven data ingestion, organization, and processing stages, with ingestion and organization steps often contributing comparable or even higher computational costs than actual processing steps. Since complex workflows consist of a variety of phases that view and use data differently, being able to construct efficient, scalable, distributed data structures (arrays, vectors, sets, maps, and multi-maps) is essential and requires custom methods to extend and shrink containers, analyze and position data, and, maintain globallyconsistent meta-data. In this paper, we propose a novel datastructure access paradigm based on the concept of Accessors. At a high level, accessors are customizable callable objects that can modify the behavior of insert, read, update, and delete operations for distributed containers while preserving atomicity guarantees. Accessors provide a very clean and natural way to implement a variety of programming patterns, e.g., conditional insertion/deletion and cascading computations, which would be otherwise hard (or even impossible) to express in parallel and distributed settings without using locks. We demonstrate the practicality and usefulness of our approach with two representative use cases and study the performance of these applications on a distributed High-Performance Computing system. Our analysis highlights that our proposed abstraction allows for an effective overlapping and concurrent execution of different workflow steps (e.g., data ingestion and analysis), which in a conventional analytics pipeline would execute sequentially, contributing cumulatively to the overall latency.

Castellana, Vito G. [BATTELLE (PACIFIC NW LAB)] (O↗
DOE OSTI2023

Electrodeposited nickel coatings for exceptional corrosion mitigation in industrial grade molten chloride salts for concentrating solar power

Molten chloride salt eutectics are attractive candidates for use as thermal energy storage media and heat transfer fluids in generation-three concentrating solar thermal power (Gen3 CSP) plants. However, corrosion of alloys in molten chloride salts, especially at high temperatures, is an extremely challenging problem that studies focus on lower temperatures, shorter durations, or analytical grade, and high-purity, salts. To date, there has been no study on corrosion or corrosion mitigation in an industrial-grade salt at a high temperature such as 750 °C. To alleviate this knowledge gap, the study presents new multiscale fractal-textured Ni coatings on various alloy surfaces for effective corrosion mitigation at 750 °C in molten chloride salts. Using the electrodeposition method, durable double-layer textured coatings were formed on stainless steel alloys (SS316, SS310, and SS347) and In800H. The corrosion performance of the coatings is investigated in both analytical-grade purity and, for the first time, practically relevant industrial-grade chloride salts. Ni-coated ferrous alloys showed an exceptionally reduced corrosion rate in the range of 350–480 μm/y in analytical-grade salts, and between 450 and 490 μm/y in purified industrial-grade salts at 750 °C. Ni coatings on ferrous alloys reduced corrosion rates by as much as 70% compared to uncoated surfaces and were comparable to the expensive Ha230 alloy with a high Ni content. As a result, by the use of innovative fractal corrosion mitigation coatings, for the first time, low-cost structural alloys are rendered viable for use with industrial-grade chloride salts, which is profoundly beneficial in practical systems.

14 SOLAR ENERGY↗
DOE OSTI2024

Molecular insights into the in situ early-stage assembly of metal–organic frameworks on cellulose nanofibrils

The integration of metal–organic frameworks (MOFs) into renewable matrices, including those derived from cellulose, to create cellulose/MOF hybrids has attracted significant interest due to the synergistic combination of cellulosic biopolymer properties and MOFs' multifunctional features. The interfacial interactions between cellulose and MOF not only ensure stable bonding, but ultimately also determine the bulk physical properties of the macroscopic composites. However, the mechanistic understanding of the in situ assembly between the two materials remains unclear. In this study, we employ a combination study of synthesis, experimental characterization, and molecular dynamics simulations to explore the early-stage assembly of a cellulose/MOF hybrid. Our results revealed that the growth of MOF clusters on the 2,2,6,6-tetramethyl-1-piperidinyloxy oxidized cellulose nanofibrils (TOCNF) follows an inhomogeneous sequential transformation pathway. The carboxylates of TOCNF form coordination-like bonds with the metal ions, while the hydroxyl groups of TOCNF form hydrogen bonds with MOF ligands. These interactions provide the initial nucleation sites that mediate the growth of MOF clusters and also guide the assembly of larger MOF clusters onto the TOCNF substrate. In conclusion, the fundamental insights into the in situ assembly of MOF nanoparticles on cellulosic substrates are essential for the rational design of high-performance materials with tailored morphology and optimized properties.

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

Charge carrier nonadiabatic dynamics in non-metal doped graphitic carbon nitride

Graphitic carbon nitride (GCN) has attracted significant attention due to its excellent performance in photocatalytic applications. Non-metal doping of GCN has been widely used to improve the efficiency of the material as a photocatalyst. Using a combination of time-domain density functional theory with nonadiabatic molecular dynamics, we study the charge carrier dynamics in oxygen and boron doped GCN systems. The reported simulations provide a detailed time-domain mechanistic description of the charge separation and recombination processes that are of fundamental importance while evaluating the photovoltaic and photocatalytic performance of the material. The appearance of smaller energy gaps due to the presence of dopant states improves the visible light absorption range of the doped systems. At the same time, the nonradiative lifetimes are shortened in the doped systems as compared to the pristine GCN. In the case of boron doped at a carbon (B–C–GCN), the charge recombination time is very long as compared to the other two doped systems owing to the smaller electron–phonon coupling strength between the valence band maximum and the trap state. The results suggest B–C–GCN as the most suitable candidate among three doped systems studied in this work for applications in photocatalysis. Finally, this work sheds light into the influence of dopants on quantum dynamics processes that govern GCN performance and, thus, guides toward building high-performance devices in photocatalysis.

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

Analysis of TATB by uHPLC-DAD (V.2.2)

The following procedure describes the method for determining the purity of 1,3,5-triamino 2,4,6-trinitrobenzene (TATB) samples using a High-Performance Liquid Chromatography (HPLC) system fitted with a Diode Array Detector (DAD).

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Acceleration of Graph Neural Network-Based Prediction Models in Chemistry via Co-Design Optimization on Intelligence Processing Units

Atomic structure prediction and associated property calculations are the bedrock of chemical physics. Since high-fidelity ab initio modeling techniques for computing the structure and properties can be prohibitively expensive, this motivates the development of machine-learning (ML) models that make these predictions more efficiently. Training graph neural networks over large atomistic databases introduces unique computational challenges such as the need to process millions of small graphs with variable size and support communication patterns that are distinct from learning over large graphs such as social networks. We demonstrate a novel hardware-software co-design approach to scale up the training of atomistic graph neural networks (GNN) for structure and property prediction. First, to eliminate redundant computation and memory associated with alternative padding techniques and to improve throughput via minimizing communication, we formulate the effective coalescing of the batches of variable-size atomistic graphs as the bin packing problem and introduce a hardware-agnostic algorithm to pack these batches. In addition, we propose hardware-specific optimizations including a planner and vectorization for the gather-scatter operations targeted for Graphcore’s Intelligence Processing Unit (IPU), as well as model-specific optimizations such as merged communication collectives and optimized softplus. Putting these all together, we demonstrate the effectiveness of the proposed co-design approach by providing an implementation of a well-established atomistic GNN on the Graphcore IPUs. We evaluate the training performance on multiple atomistic graph databases with varying degrees of graph counts, sizes and sparsity. Here, we demonstrate that such a co-design approach can reduce the training time of atomistic GNNs and can improve the performance by up to 1.5× compared to the baseline implementation of the model on the IPUs. Additionally, we compare our IPU implementation with a Nvidia GPU-based implementation and show that our atomistic GNN implementation on the IPUs can run 1.8× faster on average compared to the execution time on the GPUs.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

GraphTango: A Hybrid Representation Format for Efficient Streaming Graph Updates and Analysis

Abstract Streaming graph processing performs batched updates and analytics on a time-evolving graph. The underlying representation format of the graph largely determines the throughputs of these updates and analytics phases. Existing representation formats usually employ variations of hash tables or adjacency lists. However, a recent study showed that the adjacency-list-based approaches perform poorly on heavy-tailed graphs, and the hash table-based approaches suffer on short-tailed graphs. We propose GraphTango, a hybrid representation format that provides excellent update and analytics throughput regardless of the graph’s degree distribution. GraphTango dynamically switches among three different formats based on a vertex’s degree: (i) Low-degree vertices store the edges directly with the neighborhood metadata, confining accesses to a single cache line, (2) Medium-degree vertices use adjacency lists, and (3) High-degree vertices use hash tables as well as adjacency lists. In this case, the adjacency list provides fast traversal during the analytics phase, while the hash table provides constant-time lookups during the update phase. We further optimized the performance by designing an open-addressing-based hash table that fully utilizes every fetched cache line. In addition, we developed a thread-local lock-free memory pool that allows fast growing/shrinking of the adjacency lists and hash tables in a multi-threaded environment. We evaluated GraphTango with the help of the SAGA-Bench framework and compared it with four other representation formats: Stinger, Degree-aware Robin Hood Hashing, and two adjacency list-based formats with different workload balancing scheme. On average, GraphTango provides 4.5x higher insertion throughput, 3.2x higher deletion throughput, and 1.1x higher analytics throughput over the next best format. Furthermore, we integrated GraphTango with the state-of-the-art graph processing frameworks DZiG and RisGraph. Compared to the vanilla DZiG and vanilla RisGraph , [ GraphTango + DZiG ] and [ GraphTango + RisGraph ] reduces the average batch processing time by 2.3x and 1.5x, respectively.

Ahmed, Alif↗
DOE OSTI2021

Saccharide analysis of onion outer epidermal walls

Abstract Background Epidermal cell walls have special structural and biological roles in the life of the plant. Typically they are multi-ply structures encrusted with waxes and cutin which protect the plant from dehydration and pathogen attack. These characteristics may also reduce chemical and enzymatic deconstruction of the wall for sugar analysis and conversion to biofuels. We have assessed the saccharide composition of the outer epidermal wall of onion scales with different analytical methods. This wall is a particularly useful model for cell wall imaging and mechanics. Results Epidermal walls were depolymerized by acidic methanolysis combined with 2M trifluoracetic acid hydrolysis and the resultant sugars were analyzed by high-performance anion-exchange chromatography with pulsed amperometric detection (HPAEC-PAD). Total sugar yields based on wall dry weight were low (53%). Removal of waxes with chloroform increased the sugar yields to 73% and enzymatic digestion did not improve these yields. Analysis by gas chromatography/mass spectrometry (GC/MS) of per- O -trimethylsilyl (TMS) derivatives of the sugar methyl glycosides produced by acidic methanolysis gave a high yield for galacturonic acid (GalA) but glucose (Glc) was severely reduced. In a complementary fashion, GC/MS analysis of methyl alditols produced by permethylation gave substantial yields for glucose and other neutral sugars, but GalA was severely reduced. Analysis of the walls by 13 C solid-state NMR confirmed and extended these results and revealed 15% lipid content after chloroform extraction (potentially cutin and unextractable waxes). Conclusions Although exact values vary with the analytical method, our best estimate is that polysaccharide in the outer epidermal wall of onion scales is comprised of homogalacturonan (~ 50%), cellulose (~ 20%), galactan (~ 10%), xyloglucan (~ 10%) and smaller amounts of other polysaccharides. Low yields of specific monosaccharides by some methods may be exaggerated in epidermal walls impregnated with waxes and cutin and call for cautious interpretation of the results.

09 BIOMASS FUELS↗
DOE OSTI2020

Solvent effects on the heterogeneous growth of TiO 2 nanostructure arrays by solvothermal synthesis

One-dimensional titanium dioxide (TiO 2 ) nanostructure arrays (nanoarrays) are important metal oxide nanomaterials that can be synthesized via facile solvothermal methods. The properties of the organic solvents can impose significant effects on the microstructures and properties of the final products. However, the discussions were limited to the homogeneously nucleated TiO 2 nanomaterials in free-standing powder form, while the solvent effects are less understood during the heterogeneous growth of TiO 2 nanoarrays on a substrate surface. In this work, six organic compounds, namely 2-butanone, n-decane, n-hexane, toluene, ethylene glycol and ethanol, were selected as the solvents for the solvothermal synthesis of TiO 2 nanoarrays on the cordierite monolithic substrates. Special attentions are paid to the morphology, crystallinity, specific surface area, and porosity of the samples. The heterogeneous growth of TiO 2 nanoarrays on substrate surfaces is found to favor the solvents with moderate dielectric constants, which can be partially dissolved in the aqueous solution and modulate the reaction rate during the solvothermal synthesis. Organic solvents with low dielectric constants may result in a complete separation between the precursors and aqueous solution, and therefore slow down the overall reaction, causing the insufficient growth of the nanoarrays. The TiO 2 nanoarrays are obtained with optimum morphology from the combination of 2-butanone and titanium (IV) butoxide as solvent and precusor, respectively, with a high specific surface area up to 56 m 2 /g including cordierite substrate given a micron thickness. When loaded with Pt catalyst, the TiO 2 nanoarray-based monolithic catalysts show excellent low-temperature catalytic activity and hydrothermal stability for the CO and hydrocarbon oxidation under the simulated exhausted conditions. This article shall shed light on a better understanding of the growth mechanism and rational design of TiO 2 nanoarrays for high-performance catalytic converters.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

A review of composite polymer-ceramic electrolytes for lithium batteries

All solid-state lithium batteries are garnering attention in both academia and industry. Lithium-ion conductive polymers and lithium-ion conductive ceramics are the two major classes of solid electrolytes that have prevalently been pursued for many years. However, each of them has its own advantages and disadvantages. One approach to overcome the disadvantages and get the best out of each of those materials is a solid composite electrolyte that combines the advantages of inorganic ceramic electrolytes and solid polymer electrolytes. Such composite electrolytes can offer acceptable ionic conductivity, high mechanical strength, and favorable interfacial contact with electrodes, which can greatly improve the electrochemical performance of all-solid-state batteries compared to cells based on a polymer electrolyte alone or a ceramic electrolyte alone. We present in this review the state-of-the-art composite polymer-ceramic electrolytes in view of their electrochemical and physical properties for the applications in lithium batteries. The review mainly encompasses the polymer matrices, various ceramic filler materials, and the polymer/ceramics composite systems. Specifically, the structures, ionic conductivities, electrochemical/chemical stabilities, and fabrications of solid composite electrolytes are discussed in-depth. On the basis of previous work, a perspective on future research directions is highlighted for developing high-performance composite polymer-ceramic electrolytes.

25 ENERGY STORAGE↗