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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 1,045 records · Page 58
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Improving OFDR Distributed Fiber Sensing by Fibers With Enhanced Rayleigh Backscattering and Image Processing

This article investigates using optical fibers with enhanced backscattering profiles to improve distributed fiber sensor performance and reduce instrumentation costs. Using a femtosecond (fs) laser direct writing technique, the Rayleigh backscattering profile of a standard telecom fiber was enhanced by more than 40 dB to improve the signal-to-noise ratio (SNR) for optical frequency domain reflectometry (OFDR). The enhanced backscattering signals enable effectively distributed strain measurements using a low-cost tunable laser (TL). Median filtering is applied to denoise cross correlation results to further improve measurement outcomes. Results presented in this article show that a TL with a 1-nm tuning range, which is far less than the tuning range used in commercial OFDR interrogators, can perform effectively distributed strain measurements using sensing fibers with enhanced backscattering profiles. The sensing fiber with over 40-dB backscattering enhancement achieved 4.8-cm spatial resolution in strain measurements with a root mean square accuracy of less than 2.70 με when 10–50 με were exerted to the sensing fiber. In conclusion, results presented in this article reveal both the potential and limitations of sensing fibers with enhanced backscattering for OFDR-based distributed fiber sensors.

42 ENGINEERING↗
DOE OSTI2023

Organic carbon enables the biotic engineering of beneficial soil structure in Profundihumic and Haplic Ferralsols

We investigated how organic matter may, directly and indirectly, modify the porosity of Ferralsols, that is, deeply weathered soils of the tropics and subtropics. Although empirical and anecdotal evidence suggests that organic matter accumulation may increase porosity, a mechanistic understanding of the processes underlying this beneficial effect is lacking, especially so for Ferralsols. To achieve our end, we leveraged the fact that the Profundihumic qualifier of Ferralsols (PF) is distinguished from Haplic Ferralsols (HF) by both a much larger average carbon content in the first 1 m of soil depth (19 kg C m -3 in PF vs. 10 kg C m -3 in HF) and a significantly lower bulk density (1.05 ± 0.08 kg L -1 in PF vs. 1.21 ± 0.05 kg L -1 in HF). Through exhaustive modelling of carbon – bulk density relationships, we demonstrate that the lower bulk density of PF cannot be satisfactorily explained by a simple dilution effect. Rather, we found that bulk density correlated with carbon content when combined with carbon: nitrogen ratio (r 2 = 0.51), black carbon content (r 2 = 0.75), and Δ 14 C (r 2 =0.81). Total pore space was greater in PF (61± 3%) than in HF (55 ± 2%), but x-ray computed tomography revealed that pore space inside soil aggregates of 4–5 mm diameter does not vary between the studied Ferralsols. We further observed nearly twice as many roots and burrows in PF compared with HF. We thus infer that the mechanism responsible for the increase in porosity is most likely an enhancement of resource availability (e.g., energy, carbon, and nutrients) for the organisms (earthworms, ants, termites, etc.) that physically displace soil particles and promote soil aggregation. As a result of increased resource availability, soil organisms can create especially the mesoscale structural soil features necessary for unrestricted water flow and rapid gas exchange. In conclusion, this insight paves the way for the development of land management technologies to optimize the physical shape and capacity of the soil bioreactor.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Hydraulically‐vulnerable trees survive on deep‐water access during droughts in a tropical forest

Summary Deep‐water access is arguably the most effective, but under‐studied, mechanism that plants employ to survive during drought. Vulnerability to embolism and hydraulic safety margins can predict mortality risk at given levels of dehydration, but deep‐water access may delay plant dehydration. Here, we tested the role of deep‐water access in enabling survival within a diverse tropical forest community in Panama using a novel data‐model approach. We inversely estimated the effective rooting depth (ERD, as the average depth of water extraction), for 29 canopy species by linking diameter growth dynamics (1990–2015) to vapor pressure deficit, water potentials in the whole‐soil column, and leaf hydraulic vulnerability curves. We validated ERD estimates against existing isotopic data of potential water‐access depths. Across species, deeper ERD was associated with higher maximum stem hydraulic conductivity, greater vulnerability to xylem embolism, narrower safety margins, and lower mortality rates during extreme droughts over 35 years (1981–2015) among evergreen species. Species exposure to water stress declined with deeper ERD indicating that trees compensate for water stress‐related mortality risk through deep‐water access. The role of deep‐water access in mitigating mortality of hydraulically‐vulnerable trees has important implications for our predictive understanding of forest dynamics under current and future climates.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Phosphorus limitation of early growth differs between nitrogen‐fixing and nonfixing dry tropical forest tree species

Summary Tropical forests are often characterized by low soil phosphorus (P) availability, suggesting that P limits plant performance. However, how seedlings from different functional types respond to soil P availability is poorly known but important for understanding and modeling forest dynamics under changing environmental conditions. We grew four nitrogen (N)‐fixing Fabaceae and seven diverse non‐N‐fixing tropical dry forest tree species in a shade house under three P fertilization treatments and evaluated carbon (C) allocation responses, P demand, P‐use, investment in P acquisition traits, and correlations among P acquisition traits. Nitrogen fixers grew larger with increasing P addition in contrast to non‐N fixers, which showed fewer responses in C allocation and P use. Foliar P increased with P addition for both functional types, while P acquisition strategies did not vary among treatments but differed between functional types, with N fixers showing higher root phosphatase activity (RPA) than nonfixers. Growth responses suggest that N fixers are limited by P, but nonfixers may be limited by other resources. However, regardless of limitation, P acquisition traits such as mycorrhizal colonization and RPA were nonplastic across a steep P gradient. Differential limitation among plant functional types has implications for forest succession and earth system models.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

A Mesorhizobium japonicum quorum sensing circuit that involves three linked genes and an unusual acyl-homoserine lactone signal

ABSTRACT Members of the genus Mesorhizobium, which are core components of the rhizosphere and specific symbionts of legume plants, possess genes for acyl-homoserine lactone (AHL) quorum sensing (QS). Here we show Mesorhizobium japonicum MAFF 303099 (formerly M. loti ) synthesizes and responds to N -[(2 E , 4 E )-2,4-dodecadienoyl] homoserine lactone (2 E, 4 E- C 12:2 -HSL). We show that the 2 E, 4 E- C 12:2 -HSL QS circuit involves one of four luxR-luxI -type genes found in the sequenced genome of MAFF 303099. We refer to this circuit, which appears to be conserved among Mesorhizobium species, as R1-I1. We show that two other Mesorhizobium strains also produce 2 E, 4 E- C 12:2 -HSL. The 2 E, 4 E- C 12:2 -HSL is unique among known AHLs in its arrangement of two trans double bonds. The R1 response to 2 E, 4 E- C 12:2 -HSL is extremely selective in comparison with other LuxR homologs, and the trans double bonds appear critical for R1 signal recognition. Most well-studied LuxI-like proteins use S -adenosylmethionine and an acyl-acyl carrier protein as substrates for synthesis of AHLs. Others that form a subgroup of LuxI-type proteins use acyl-coenzyme A substrates rather than acyl-acyl carrier proteins. I1 clusters with the acyl-coenzyme A-type AHL synthases. We show that a gene linked to the I1 AHL synthase is involved in the production of the QS signal. The discovery of the unique I1 product enforces the view that further study of acyl-coenzyme A-dependent LuxI homologs will expand our knowledge of AHL diversity. The involvement of an additional enzyme in AHL generation leads us to consider this system a three-component QS circuit. IMPORTANCE We report a Mesorhizobium japonicum quorum sensing (QS) system involving a novel acyl-homoserine lactone (AHL) signal. This system is known to be involved in root nodule symbiosis with host plants. The chemistry of the newly described QS signal indicated that there may be a dedicated cellular enzyme involved in its synthesis in addition to the types known for production of other AHLs. Indeed, we report that an additional gene is required for synthesis of the unique signal, and we propose that this is a three-component QS circuit as opposed to the canonical two-component AHL QS circuits. The signaling system is exquisitely selective. The selectivity may be important when this species resides in the complex microbial communities around host plants and may make this system useful in various synthetic biology applications of QS circuits.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Seasonality and longer-term development generate temporal dynamics in the Populus microbiome

ABSTRACT Temporal variation in community composition is central to our understanding of the assembly and functioning of microbial communities, yet the controls over temporal dynamics for microbiomes of long-lived plants, such as trees, remain unclear. Temporal variation in tree microbiomes could arise primarily from seasonal (i.e., intra-annual) fluctuations in community composition or from longer-term changes across years as host plants age. To test these alternatives, we experimentally isolated temporal variation in plant microbiome composition using a common garden and clonally propagated plants, and we used amplicon sequencing to characterize bacterial/archaeal and fungal communities in the leaf endosphere, root endosphere, and rhizosphere of two Populus spp. over four seasons across two consecutive years. Microbial community composition differed among seasons and years (which accounted for up to 21% of the variation in microbial community composition) and was correlated with seasonal dissimilarity in climatic conditions. However, microbial community dissimilarity was also positively correlated with time, reflecting longer-term compositional shifts as host trees aged. Together, our findings demonstrate that temporal patterns in tree microbiomes arise from both seasonal fluctuations and longer-term changes, which interact to generate unique seasonal patterns each year. In addition to shedding light on two important controls over the assembly of plant microbiomes, our results also suggest future studies of tree microbiomes should account for background temporal dynamics when testing the drivers of spatial patterns in microbial community composition and temporal responses of plant microbiomes to environmental change. IMPORTANCE Microbiomes are integral to the health of host plants, but we have a limited understanding of the factors that control how the composition of plant microbiomes changes over time. Especially little is known about the microbiome of long-lived trees, relative to annual and non-woody plants. We tested how tree microbiomes changed between seasons and years in poplar (genus Populus ), which are widespread and ecologically important tree species that also serve as important biofuel feedstocks. We found the composition of bacterial, archaeal, and fungal communities differed among seasons, but these seasonal differences depended on year. This dependence was driven by longer-term changes in microbial composition as host trees developed across consecutive years. Our findings suggest that temporal variation in tree microbiomes is driven by both seasonal fluctuations and longer-term (i.e., multiyear) development.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Importance of suberin biopolymer in plant function, contributions to soil organic carbon and in the production of bio-derived energy and materials

Abstract Suberin is a hydrophobic biopolymer of significance in the production of biomass-derived materials and in biogeochemical cycling in terrestrial ecosystems. Here, we describe suberin structure and biosynthesis, and its importance in biological (i.e., plant bark and roots), ecological (soil organic carbon) and economic (biomass conversion to bioproducts) contexts. Furthermore, we highlight the genomics and analytical approaches currently available and explore opportunities for future technologies to study suberin in quantitative and/or high-throughput platforms in bioenergy crops. A greater understanding of suberin structure and production in lignocellulosic biomass can be leveraged to improve representation in life cycle analysis and techno-economic analysis models and enable performance improvements in plant biosystems as well as informed crop system management to achieve economic and environmental co-benefits.

09 BIOMASS FUELS↗
DOE OSTI2021

Data from: "Ecophysiological variation in two provenances of Pinus flexilis seedlings across an elevation gradient from forest to alpine"

This archive contains data used to support conclusions drawn in “Ecophysiological variation in two provenances of Pinus flexilis seedlings across an elevation gradient from forest to alpine”, by Reinhardt et al., 2011. Data were collected over one summer season in plots within the Alpine Treeline Warming Experiment (ATWE), before climate manipulations began. The experiment was located on Niwot Ridge, in the Front Range of the Colorado Rocky Mountains. This data package includes five comma-separated-values (.csv) files, five Microsoft Excel (.xlsx) files, one .pdf file, and two types of geospatial files: keyhole markup language (.kml), and ESRI shapefiles (.shp). .csv files can be opened using any simple text-editing software (such as Notepad and TextEdit), R, and Microsoft Excel. .xlsx files can only be opened using Microsoft Excel. The .pdf file can be opened using Adobe Acrobat Reader or any other compatible file viewing software. The .kml file can be opened using Google Earth and Google Maps, and shapefiles can be opened using any software compatible with the file type, such as ESRI’s ArcGIS suite and QGIS.Data archived contain gas exchange and plant physiology measurements, non-structural carbohydrate data, among others. Geospatial files are also provided for additional locational context. The files and their contents in this data package are summarized under "Data Summary" in the included Data User's Guide. All files (excluding geospatial) are available in both Microsoft Excel and in .csv format, and are indicated in the Data Summary list as well.-----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------Climate change is predicted to cause upward shifts in forest tree distributions, which will require seedling recruitment beyond current forest boundaries. However, predicting the likelihood of successful plant establishment beyond current species’ ranges under changing climate is complicated by the interaction of genetic and environmental controls on seedling establishment. To determine how genetics and climate may interact to affect seedling establishment, we transplanted recently germinated seedlings from high- and low-elevation provenances (HI and LO, respectively) of Pinus flexilis in common gardens arrayed along an elevation and canopy gradient from subalpine forest into the alpine zone and examined differences in physiology and morphology between provenances and among sites. Plant dry mass, projected leaf area and shoot:root ratios were 12–40% greater in LO compared with HI seedlings at each elevation. There were no significant changes in these variables among sites except for decreased dry mass of LO seedlings in the alpine site. Photosynthesis, carbon balance (photosynthesis/respiration) and conductance increased >2× with elevation for both provenances, and were 35–77% greater in LO seedlings compared with HI seedlings. There were no differences in dark-adapted chlorophyll fluorescence (Fv/Fm) among sites or between provenances. Our results suggest that for P. flexilis seedlings, provenances selected for above-ground growth may outperform those selected for stress resistance in the absence of harsh climatic conditions, even well above the species’ range limits in the alpine zone. This indicates that forest genetics may be important to understanding and managing species’ range adjustments due to climate change.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

2017 Meander C sediment characterization from the East River, Colorado

This dataset includes characterization data collected on sediment samples from Meander C as part of the Watershed Function Scientific Focus Area (SFA) located in the Upper Colorado River Basin. The data were collected to investigate the nature of mineral-organic associations across the meander transect and with depth. Samples were collected in 2017, and analyzed using sequential extractions (water, pyrophosphate, HCl, and dithionite) and density fractionation. Data collected include: texture, pH, root biomass, and metals (Fe, Al, Ca, Si) of bulk sediment samples; C and N of heavy fraction; and extractable OC, Fe, and Al, and organic matter characterization using high-resolution mass spectrometry (FT-ICR-MS) of sequential extractions. Sample locations are included in the ‘sample_metadata.xlsx” file. Sediment characterization data is included in the accompanying csv files: bulk and density fractions (MCB2017_density-and-bulk-fractions.csv), sequential extractions (MCB2017_sequential-extractions.csv), and FT-ICR-MS data from sequential extractions in three files to be read by the R package ftmsRanalysis (MCB2017_FTICRMS-sequential-edata.csv, MCB2017_FTICRMS-sequential-emeta.csv, and MCB2017_FTICRMS-sequential-fdata.csv). Sediment was collected in triplicate; ID’s refer to individual samples.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Model code and data: biomass allocation adjustments induced by elevated CO2 and warming in a C3 brackish marsh, 2017-2022, Maryland

This dataset and R script accompany the published paper Bruns et al. (2024) in Geophysical Research Letters. The data are from the first six years of a field manipulation of whole-ecosystem warming and elevated CO2 experiment (Salt Marsh Accretion Response to Temperature eXperiment, or SMARTX) in the Smithsonian's Global Change Research Wetland (GCReW), a brackish, microtidal wetland site on a subestuary of the Chesapeake Bay. These data were generated to understand how warming and elevated CO2 interact to structure ecosystem-level responses to global change, particularly in terms of carbon sequestration. The dataset covers 2017-2022 and includes peak annual above ground biomass, annual belowground fine root productivity, and porewater NH4 for each experimental plot. The overall experiment is replicated in two locations on the marsh, a lower elevation zone dominated the C3 sedge S. Americanus and a higher elevation plot dominated by the C4 species. This paper and its data release is only for the C3 plot. Variable descriptions for data file is available in variable_descriptions.pdf. The R script Bruns_et_al_2024_GRL_make_figures.Rmd contains model code and other scripts used to generate all paper figures.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Validation Progress and Plans for ENDF/B-VIII.1β1 at ORNL [Slides]

This presentation opens with a ORNL definition of ENDF/B-VIII.1β1. Following with keff results for CE calculations with VALID. Additionally provided are Preliminary Root Cause Analysis (RCA) results. This presentation then concludes with future plans for additional validation.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2023

Discovery of a novel filamentous prophage in the genome of the Mimosa pudica microsymbiont Cupriavidus taiwanensis STM 6018

Integrated virus genomes (prophages) are commonly found in sequenced bacterial genomes but have rarely been described in detail for rhizobial genomes. Cupriavidus taiwanensis STM 6018 is a rhizobial Betaproteobacteria strain that was isolated in 2006 from a root nodule of a Mimosa pudica host in French Guiana, South America. Here we describe features of the genome of STM 6018, focusing on the characterization of two different types of prophages that have been identified in its genome. The draft genome of STM 6018 is 6,553,639 bp, and consists of 80 scaffolds, containing 5,864 protein-coding genes and 61 RNA genes. STM 6018 contains all the nodulation and nitrogen fixation gene clusters common to symbiotic Cupriavidus species; sharing >99.97% bp identity homology to the nod / nif / noeM gene clusters from C. taiwanensis LMG19424 T and “ Cupriavidus neocalidonicus” STM 6070. The STM 6018 genome contains the genomes of two prophages: one complete Mu-like capsular phage and one filamentous phage, which integrates into a putative dif site. This is the first characterization of a filamentous phage found within the genome of a rhizobial strain. Further examination of sequenced rhizobial genomes identified filamentous prophage sequences in several Beta-rhizobial strains but not in any Alphaproteobacterial rhizobia.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

A Systems Biology Approach to Identify Essential Epigenetic Regulators for Specific Biological Processes in Plants

Upon sensing developmental or environmental cues, epigenetic regulators transform the chromatin landscape of a network of genes to modulate their expression and dictate adequate cellular and organismal responses. Knowledge of the specific biological processes and genomic loci controlled by each epigenetic regulator will greatly advance our understanding of epigenetic regulation in plants. To facilitate hypothesis generation and testing in this domain, we present EpiNet, an extensive gene regulatory network (GRN) featuring epigenetic regulators. EpiNet was enabled by (i) curated knowledge of epigenetic regulators involved in DNA methylation, histone modification, chromatin remodeling, and siRNA pathways; and (ii) a machine-learning network inference approach powered by a wealth of public transcriptome datasets. We applied GENIE3, a machine-learning network inference approach, to mine public Arabidopsis transcriptomes and construct tissue-specific GRNs with both epigenetic regulators and transcription factors as predictors. The resultant GRNs, named EpiNet, can now be intersected with individual transcriptomic studies on biological processes of interest to identify the most influential epigenetic regulators, as well as predicted gene targets of the epigenetic regulators. We demonstrate the validity of this approach using case studies of shoot and root apical meristem development.

root apical meristem↗
DOE OSTI2024

Panama Rainforest Changes with Experimental Drought (PaRChED): Initial Effects of Partial Throughfall Exclusion on Soil Dynamics in Lowland Forests Across Variation in Rainfall and Soil Fertility

Changes in rainfall are predicted across tropical regions, with effects on nutrient, water, and carbon cycling. This chapter summarizes results from the first two years of a throughfall exclusion experiment in four lowland Panamanian forests that span a 1,000-mm change in rainfall and variation in soil fertility. Soil respiration (i.e., soil carbon dioxide [CO2 ] flux) declined with throughfall exclusion, with a site*season interaction, and the radiocarbon age of respired carbon was older in exclusion versus control plots. The decline in soil CO2 flux could be related to reduced fine root production and soil microbial biomass. Microbial community composition also changed with throughfall exclusion in infertile soils, and soil nutrients accumulated more in exclusion versus control plots during the dry season. The net effects on soil carbon storage will depend on the relative strengths of these effects over time. Continued research could improve predictions of tropical forest-climate feedbacks with changes in precipitation.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

RESOLVING THE ELECTROCHEMICAL EQUATIONS OF A SOLID OXIDE FUEL CELL FOR USE IN TRANSIENT SIMULATION AND INTEGRATION INTO CYBER-PHYSICAL SYSTEMS

A major challenge with complex cyber-physical systems stems from long model computational time that creates a mismatch between the model system and the physical system. The numerical modeling of solid oxide fuel cells (SOFCs) presents particular challenges due to the highly coupled nature of the underlying equations and the multiphysics needed to fully resolve their behavior during a transient event. To this end current approaches revolve around splitting the computational efforts into resolving temperature effects and resolving electrochemical effects. Current methods employed for the transient simulation of an SOFC for implementation in the Hybrid Performance (HyPer) facility cyberphysical plant at the National Energy Technology Laboratory reveal a distinct need for accelerated results with a high degree of stability. To this aim, an investigation into the computational time for the code reveals that the underlying electrochemical algorithm takes an order of magnitude more time than its thermal counterpart and has a tendency to vary in terms of iteration time and as such a rework of the underlying system is proposed. The primary method for accelerated electrochemical algorithm solutions is to employ higher order root finding recipes for the resolution of the highly coupled electrochemical equations. This is done with the intention to reduce the overall number of subiterations necessary for resolving voltage, current density, and species concentration, properties of the fuel cell that are all directly coupled and require nested iterative approaches. The overall objective of this approach is an order of magnitude reduction in calculation time without sacrificing stability and increasing accuracy. Specific approaches involve using both bounded and unbounded techniques, such as the False Position method and the Secant method (or if applicable Newton-Raphson) respectively, the drawbacks being slower convergence for False Position and instability for the Secant or Newton-Raphson methods. Current preliminary results on simplified versions of the parent functions involved for electrochemical calculations indicate a reduction in computational steps by a factor of two for the secant method and a factor of three for Newton-Raphson. When implemented into new modified electrochemical algorithms, the results indicate a possible order of magnitude reduction in calculation time.

Arias, Jesus↗
DOE OSTI2025

Artificial Intelligence and Machine Learning Applications in Modern Power Systems

Machine learning (ML) and artificial intelligence (AI) algorithms offer valuable tools for the analysis and interpretation of large datasets. These tools have the capability to uncover insights that may not be readily apparent within these datasets. In recent years, the integration of ML and AI has become increasingly prevalent in various applications within the power system domain. One of the earliest instances of machine learning in power systems can be traced back to demand forecasting, where artificial neural networks were employed for short-term load forecasting. In contemporary power systems, an abundance of high-resolution geospatial and temporal data is generated at various time intervals, ranging from sub-seconds (Phasor Measurement Units or PMUs) to seconds (Supervisory Control and Data Acquisition or SCADA), minutes (Process Information or PI), and extending to days, months, and years. These datasets contain valuable information concerning system reliability and performance. This information holds the potential to offer critical insights into system operations, as well as solutions for predicting and mitigating contingencies to prevent cascading outages. Despite the immense power of machine learning tools, system operators, planners, and utilities often exhibit hesitancy in fully embracing AI-enabled system operations and planning. This cautious approach persists, even as numerous diverse applications of machine learning continue to emerge in the realm of power systems. In this chapter, our focus will delve deep into ML and AI applications tailored for power systems. These applications aim to furnish system operators with enhanced situational awareness and augment their decision-making capabilities, especially during challenging operating conditions. Specific areas of interest encompass root cause analyses of electricity market datasets and the strategic selection of representative samples from vast power system databases for training ML/AI models. Finally, the chapter will conclude with a short discussion on the future of ML/AI in power systems and possible directions that the industry is moving towards.

power system applications, machine learning (ML), ↗
DOE OSTI2021

Hydrogen-Bonding Reinforced Flexible Composite Electrodes for Enhanced Energy Storage

The lack of advanced electrode materials is one of the main factors hindering the development of flexible rechargeable aqueous batteries (RABs) for high specific energy density and structural stability. It is also challenging to achieve high-capacity performance for both the positive and negative electrodes simultaneously. In this work, it is demonstrated that, by smartly designing the composite structures of positive and negative electrodes via one-step electrodeposition strategy, the energy storage performance of the RAB is largely enhanced. For positive electrode material synthesis, Co-Cu double hydroxides (Co-Cu-DH) nanosheets are skillfully rooted into electroreduced graphene oxide (eRG) via hydrogen bonding, in which graphene oxide reduction, Co-Cu-DH nucleation/growth, and formation of hydrogen bonding between Co-Cu-DH and eRG simultaneously occur. Moreover, when a RAB based on Co-Cu-DH@eRG//FeOOH@eRG using the same composite design strategy is established, a wide operating voltage window of ≈1.8 V, a high specific energy density of ≈142.8 Wh kg –1 at ≈890 W kg –1 , and long-term cyclic stability (88.5% of capacity retention after 12 000 cycles) are obtained. This study presents a general compositing strategy for the development of advanced electrode materials, and it is expected to stimulate future material synthesis/design in RABs toward the goal of high energy density storage.

25 ENERGY STORAGE↗