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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

Adapting the Technology Performance Level Integrated Assessment Framework to Low-TRL Technologies Within the Carbon Capture, Utilization, and Storage Industry, Part I

With the urgent need to mitigate climate change and rising global temperatures, technological solutions that reduce atmospheric CO 2 are an increasingly important part of the global solution. As a result, the nascent carbon capture, utilization, and storage (CCUS) industry is rapidly growing with a plethora of new technologies in many different sectors. There is a need to holistically evaluate these new technologies in a standardized and consistent manner to determine which technologies will be the most successful and competitive in the global marketplace to achieve decarbonization targets. Life cycle assessment (LCA) and techno-economic assessment (TEA) have been employed as rigorous methodologies for quantitatively measuring a technology's environmental impacts and techno-economic performance, respectively. However, these metrics evaluate a technology's performance in only three dimensions and do not directly incorporate stakeholder needs and values. In addition, technology developers frequently encounter trade-offs during design that increase one metric at the expense of the other. The technology performance level (TPL) combined indicator provides a comprehensive and holistic assessment of an emerging technology's potential, which is described by its techno-economic performance, environmental impacts, social impacts, safety considerations, market/deployability opportunities, use integration impacts, and general risks. TPL incorporates TEA and LCA outputs and quantifies the trade-offs between them directly using stakeholder feedback and requirements. In this article, the TPL methodology is being adapted from the marine energy domain to the CCUS domain. Adapted metrics and definitions, a stakeholder analysis, and a detailed foundation-based application of the systems engineering approach to CCUS are presented. The TPL assessment framework is couched within the internationally standardized LCA framework to improve technical rigor and acceptance. It is demonstrated how stakeholder needs and values can be directly incorporated, how LCA and TEA metrics can be balanced, and how other dimensions (listed earlier) can be integrated into a single metric that measures a technology's potential.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2022

Construction of Fluorine- and Piperazine-Engineered Covalent Triazine Frameworks Towards Enhanced Dual-Ion Positive Electrode Performance

Organic positive electrodes featuring lightweight, and tunable energy storage modes by molecular structure engineering have promising application prospects in dual-ion batteries. Herein, a series of highly porous covalent triazine frameworks (CTFs) were synthesized under ionothermal conditions using fluorinated aromatic nitrile monomers containing a piperazine ring. Fluorinated monomers can result in more defects in CTFs, leading to a higher surface area up to 2515 m 2 /g and a higher N content of 11.34 wt% compared to the products from the non-fluorinated monomer. The high surface area and abundant redox sites of these CTFs afforded high specific capacities (up to 279 mAh/g at 0.1 A/g), excellent rate performance (89 mAh/g at 5 A/g), and durable cycling performance (92.3% retention rate after 500 cycles at 2.0 A g -1 ) as dual-ion positive electrodes

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

Measurement and applications: Exploring the challenges and opportunities of hierarchical federated learning in sensor applications

Sensor applications have become ubiquitous in modern society as the digital age continues to advance. AI-based techniques (e.g., machine learning) are effective at extracting actionable information from large amounts of data. An example would be an automated water irrigation system that uses AI-based techniques on soil quality data to decide how to best distribute water. However, these AI-based techniques are costly in terms of hardware resources, and Internet-of-Things (IoT) sensors are resource-constrained with respect to processing power, energy, and storage capacity. These limitations can compromise the security, performance, and reliability of sensor-driven applications. To address these concerns, cloud computing services can be used by sensor applications for data storage and processing. Unfortunately, cloud-based sensor applications that require real-time processing, such as medical applications (e.g., fall detection and stroke prediction), are vulnerable to issues such as network latency due to the sparse and unreliable networks between the sensor nodes and the cloud server [1]. As users approach the edge of the communications network, latency issues become more severe and frequent. A promising alternative is edge computing, which provides cloud-like capabilities at the edge of the network by pushing storage and processing capabilities from centralized nodes to edge devices that are closer to where the data are gathered, resulting in reduced network delays [2], [3].

Po-Leen Ooi, Melanie↗
DOE OSTI2022

Techno-Economic Analysis of a Cryogenic Flux Capacitor for Grid Storage

Abstract The Cryogenic Flux Capacitor (CFC) is a cold, dense fluid storage core with integrated design features that afford the designer flexibility and provide new possibilities for the storage and discharge of energy. The stored energy, in this case, is represented by hydrogen physically bonded within the nanoscale pores within the aerogel composite blanket material, and the process of bonding or debonding is governed by principles of physical adsorption (physisorption) and thermodynamics. The large surface area afforded by the nanoporous aerogel (∼1,000 m2/g) allows for storage densities close to, or in some cases exceeding, that of normal boiling point liquids. Its performance easily exceeds what can be achieved via ambient temperature, high-pressure gas storage for an equivalent volume. CFC storage is predicted to be easily scalable, is constructed from readily available commercial materials, lends itself to a range of pressure applications, and is geometry insensitive. The high energy density of CFC-stored hydrogen allows long durations of storage, such as daily to monthly cycling, which corresponds to approximately 10 to 100 hours of duration, respectively. The techno-economic analysis examines different types of hydrogen storage for commercial viability. The assessment includes the use of hydrogen blended with natural gas in a combined cycle gas turbine. The study provides results for a range of blends from 100% natural gas to 100% hydrogen. The required fuel usages are estimated for the intended application in a grid scenario that features large amounts of renewable penetration, 10 hours, and as a baseload, 100 hours. The study presents preliminary estimates of the capital cost of storage and operating cost of storage. In addition, the cost of firing natural gas and capturing the carbon dioxide (CO2) in a carbon capture and sequestration (CCS) system is assessed. Based on the study, it is shown that CFC can competitively meet performance and cost needs for grid-based energy storage.

08 HYDROGEN↗
DOE OSTI2025

Computationally efficient models for aqueous organic redox flow batteries

The rising usage of intermittent energy has garnered the need for large scale energy storage systems. Redox flow batteries (RFB) based energy storage system shows promising potential. Numerical simulations and machine learning approaches have been widely used to study RFB performance. The development of autonomous material discovery framework and digital twin of energy storage system usually needs to query cell performance through fast response models. In this study, two computationally efficient models are introduced: a physics-based analytical flow battery model (EZBattery), and a machine learning operator model (Deep Operator Network, denoted by DeepONet). Both models can provide cell performance near instantly, and prediction accuracy was systematically examined on an application of evaluating the performances of a 780 cm 2 aqueous organic redox flow battery (AORFB), using potential anolyte candidates in dihydroxyphenazine (DHP)-based family of organic materials. A validated computationally expansive 3-dimensional multi-physics finite element model by COMSOL was used as the ground truth and provided the training data set for the DeepONet. 1280 samples were generated with 10 properties to mimic the different possible anolyte candidates, and the cell performances were evaluated under 10 different combined operating conditions. The accuracy comparisons for the two computationally efficient models show that both models can provide comparable accuracy in predicting cell charging/discharging voltage curves. DeepONet can provide slightly higher overall accuracy than EZBattery with faster calculation speed, but highly relies on the training dataset. EZBattery does not need a training dataset and can provide interpretable physics-based explanations of the results, while being more flexible to adjust to adapt any different cell designs, flow battery architectures, and electrolyte materials.

Analytical model↗
DOE OSTI2020

Metal Organic Frameworks for Xenon Storage Applications

The demand for cheap and convenient xenon storage continues to rise due to its wide spectrum of applications. It is expected that solid-state adsorbents can provide significant advantages over the current isolated stainless-steel tank-based storage technologies. In this context, we investigated metal organic frameworks for use as adsorbents for xenon. Initially, three representative MOFs were synthesized and characterized in terms of Xe storage. The results were used to validate a computational modeling approach, which was later extended to a larger set of materials. The collected results allowed us to rationalize the key parameters (pore volume, surface area, void fraction etc.), which are important for good performance and selection of the best materials for xenon storage

Noble gas, Storage, MOFs↗
DOE OSTI2023

Annual Technology Baseline: The 2023 Electricity Update

Consistent cost and performance data for various electricity generation technologies can be difficult to find and may change frequently for certain technologies. With the Annual Technology Baseline (ATB), the National Renewable Energy Laboratory annually provides an organized and centralized set of such cost and performance data. The ATB uses the best information from the Department of Energy national laboratories' renewable energy analysts. The ATB has been reviewed by experts and it includes the following electricity generation and storage technologies: land-based wind, offshore wind, distributed wind, utility-scale solar photovoltaics (PV), commercial-scale solar PV, residential-scale solar PV, concentrating solar power, geothermal power, hydropower, utility-scale battery storage, commercial battery storage, residential battery storage, pumped storage hydropower, coal, and natural gas. EIA data for nuclear and conventional biopower are included for reference. This webinar presentation introduces the 2023 update to the ATB Electricity data and documentation.

capacity factor↗
DOE OSTI2023

On Energy Storage Chemistry of Aqueous Zn-Ion Batteries: From Cathode to Anode

Rechargeable aqueous zinc-ion batteries (ZIBs) have resurged in large-scale energy storage applications due to their intrinsic safety, affordability, competitive electrochemical performance, and environmental friendliness. Extensive efforts have been devoted to exploring high-performance cathodes and stable anodes. However, many fundamental issues still hinder the development of aqueous ZIBs. Here, we critically review and assess the energy storage chemistries of aqueous ZIBs for both cathodes and anodes. First, this review presents a comprehensive understanding of the cathode charge storage chemistry, probes the existing deficiencies in mechanism verification, and analyzes contradictions between the experimental results and proposed mechanisms. Then, a detailed summary of the representative cathode materials and corresponding comparative discussion is provided with typical cases encompassing structural features, electrochemical properties, existing drawbacks, and feasible remedies. Subsequently, the fundamental chemical properties, remaining challenges, and improvement strategies of both Zn metal and non-Zn anodes are presented to thoroughly explore the energy storage chemistry of ZIBs and pursue the development of high-performance ZIBs. Furthermore, the progress of mechanistic characterization techniques and theoretical simulation methods used for ZIBs is timely reviewed. Finally, here we provide our perspectives, critical analysis, and insights on the remaining challenges and future directions for development of aqueous ZIBs.

25 ENERGY STORAGE↗
DOE OSTI2022

Hydrogen Storage for Flexible Fossil Fuel Power Generation: Integration of Underground Hydrogen Storage with Gas Turbine (Final Report)

As the nation continues to encourage, through market structures and financial incentives, the proliferation of intermittent renewable electricity, how to optimize the ever-changing electric grid and identify means to retain and improve resilience, while ensuring continued reductions in GHG emissions, will be critical. According to Bloomberg, wind & solar generated 10.5% of US electricity in 2020 and that percentage continues to grow. In support of expanding renewable energy use, and to address its intermittent nature, this project will develop the Hydrogen Storage for Flexible Fossil Fuel Power Generation platform that is dispatchable, reliable, repeatable and have the ability to produce zero or negative carbon power while interfacing with geology capable of CO2 and hydrogen storage. GTI Energy (GTIE) and team members Illinois State Geological Survey (ISGS), Mitsubishi Heavy Industries America (MHIA), Ameren Illinois, Hexagon Purus, and the Low Carbon Resources Initiative (LCRI) completed a Phase I Conceptual Study under contract DE-FE0032012 for Hydrogen Storage for Flexible Fossil Fuel Power Generation: Integration of Underground Hydrogen Storage with Gas Turbine. The Hydrogen Storage for Flexible Fossil Fuel Power Generation platform addresses the intermittent nature of the expanding use of Variable Renewable Energy (VRE) generation. The low cost of the electricity (COE) generated results in greater dispatch and more operation at higher power levels (higher efficiency), fewer short intervals, and fewer start/stop cycles. The reliable, resilient system can produce zero carbon power and store hydrogen. It will demonstrate hydrogen storage in geologic formations like those used in natural gas underground storage thus enabling large scale storage of hydrogen in sedimentary strata across the United States rather than in geographically restricted salt caverns. The Phase I study confirmed the system is feasible and generates power at lower cost than other low carbon approaches. The demonstration defines the pathway for broad commercial application and will accelerate the development of larger systems suitable for centralized utility scale electricity production. The study advanced the maturity of the H 2 storage-based system with flexible power generation by completing a Pre-FEED study (Phase II). The Pre-FEED focused on the selected Energy Farm on the University of Illinois Urbana-Champaign (UIUC) site that includes above ground and underground hydrogen storage, low-carbon hydrogen production (GTI’s Compact Hydrogen Generator, CHG) with underground CO2 sequestration, and a 40-MW class gas turbine. The Pre-FEED addressed the entire system and its interconnection to the natural gas and electric grid and mitigation of key risks, such as storage behavior, load-following, and system operation. During Phase 1 of the project, the team completed key tasks, which moved the entire demonstration project, specific components and approaches closer to commercialization. These Phase I Accomplishments include: Completing System Requirements Review; Completing System Layout and Modeling - Heat & Mass Balance and Process Flow Diagram; Completing modelling of 9 turbine performance cases; Evaluating rock strata for underground storage of hydrogen and sequestration of carbon dioxide; Completing initial modelling of underground storage of hydrogen and withdrawal with evaluation of loss and water production; Identifying roadable storage for above ground hydrogen storage; Identifying existing electrical infrastructure for receiving/delivering electricity; Identifying existing gas supply infrastructure for receiving natural gas; Document concept design/development plans in required reports. Conclusions: The 12-month Feasibility study in Phase I study was completed and confirmed the system is feasible and generates power at lower cost than other low carbon approaches and even lower cost than the reference NGCC plant without carbon capture when taking advantage of 45Q carbon credits. The study enabled the fidelity of the concept to be improved and allowed identification of the requirements for the system. Defining the individual system and component requirements was performed via the system requirements review with the whole team. These requirements were then incorporated into and iterated with our Heat & Mass Balance process model and process flow diagrams were generated to reflect the overall system. This information was then used to complete the TEA and show economic feasibility. Large scale non-salt geologic storage of hydrogen is an enabling technology for a hydrogen-fired turbine that can be retrofitted into large-scale electric generating units (EGU). Our demonstration will include 428 MWh or ~4 hours full load of hydrogen storage (above and underground). Carbon capture inherent to the CHG process can capture 90% CO 2 (with upgrades to >98%). This system provides a COE of 23% savings relative to an NGCC with a post combustion amine system. Our proposed storage system decouples carbon capture and hydrogen production from power production; therefore, we expect our proposed system’s efficiency and variable COE to be superior resulting in overall higher dispatch and reduced deep cycling. Our demonstration will be full to multi-day hydrogen storage and has the potential for longer (seasonal) duration commercially. The demonstration defines the pathway for broad commercial application and will accelerate the development of larger systems suitable for centralized utility scale electricity production.

03 NATURAL GAS↗
DOE OSTI2020

Super resolution for root imaging

Premise High‐resolution cameras are very helpful for plant phenotyping as their images enable tasks such as target vs. background discrimination and the measurement and analysis of fine above‐ground plant attributes. However, the acquisition of high‐resolution images of plant roots is more challenging than above‐ground data collection. An effective super‐resolution (SR) algorithm is therefore needed for overcoming the resolution limitations of sensors, reducing storage space requirements, and boosting the performance of subsequent analyses. Methods We propose an SR framework for enhancing images of plant roots using convolutional neural networks. We compare three alternatives for training the SR model: (i) training with non‐plant‐root images, (ii) training with plant‐root images, and (iii) pretraining the model with non‐plant‐root images and fine‐tuning with plant‐root images. The architectures of the SR models were based on two state‐of‐the‐art deep learning approaches: a fast SR convolutional neural network and an SR generative adversarial network. Results In our experiments, we observed that the SR models improved the quality of low‐resolution images of plant roots in an unseen data set in terms of the signal‐to‐noise ratio. We used a collection of publicly available data sets to demonstrate that the SR models outperform the basic bicubic interpolation, even when trained with non‐root data sets. Discussion The incorporation of a deep learning–based SR model in the imaging process enhances the quality of low‐resolution images of plant roots. We demonstrate that SR preprocessing boosts the performance of a machine learning system trained to separate plant roots from their background. Our segmentation experiments also show that high performance on this task can be achieved independently of the signal‐to‐noise ratio. We therefore conclude that the quality of the image enhancement depends on the desired application.

Ruiz‐Munoz, Jose F.↗
DOE OSTI2023

Multi–Modular Design of Stable Pore–Space–Partitioned Metal–Organic Frameworks for Gas Separation Applications

Pore space partition (PSP) is an effective materials design method for developing high-performance small-pore materials for storage and separation of gas molecules. The continued success of PSP depends on broad availability and judicious choice of pore-partition ligands and better understanding of each structural module on stability and sorption properties. Here, by using substructural bioisosteric strategy (sub-BIS), a dramatic expansion of pore-partitioned materials is targeted by using ditopic dipyridyl ligands with non-aromatic cores or extenders, as well as by expanding heterometallic clusters to uncommon nickel–vanadium and nickel–indium clusters rarely known before in porous materials. The dual-module iterative refinement of pore-partition ligands and trimers leads to remarkable enhancement of chemical stability and porosity. Here a family of 23 pore-partitioned materials synthesized from five pore-partition ligands and seven types of trimeric clusters is reported. New materials with such compositionally and structurally diverse framework modules reveal key factors that dictate stability, porosity, and gas separation properties. Among these, materials based on heterometallic vanadium–nickel trimeric clusters give rise to the highest long-term hydrolytic stability and remarkable uptake capacity for CO 2 , C 2 H 2 /C 2 H 4 /C 2 H 6 , and C 3 H 6 /C 3 H 8 hydrocarbon gases. Here, the breakthrough experiment shows the potential application of new materials for separating gas mixtures such as C 2 H 2 /CO 2 .

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2026

Random 3D Interpenetrating Electrode Design for Energy Storage Applications

We introduce the concept of random interpenetrating electrode structures, inspired by spinodal decomposition, as a transformative approach for energy storage applications. While ordered architectures, such as double gyroids and Kelvin cell structures, have long been favored for their structural uniformity and surface area utilization, we demonstrate that random structures offer distinct advantages including shorter diffusion pathways, higher packing density, and enhanced reaction kinetics, particularly at low temperatures. Using a combination of computational and electrochemical analysis, we show that random architecture outperforms their ordered counterparts in scenarios where diffusion dominates. This work represents the first systematic exploration of random structures in energy storage, highlighting their potential to overcome limitations of traditional designs. However, challenges such as structural reproducibility and scalability remain, necessitating further investigation into fabrication techniques and material selection. By establishing a framework to optimize random electrode architectures, we provide critical insights into the interplay between geometry, diffusion, and reaction kinetics. This study not only introduces a new design principle for 3D electrodes but also opens pathways for next-generation energy storage systems that demand both high performance and adaptability to a range of operating conditions.

Materials science↗
DOE OSTI2020

Software Framework for Federated Science Instruments

There is an unprecedented promise of enhanced capabilities for federations of leadership computing systems and experimental science facilities by leveraging software technologies for fast and efficient operations. These federations seek to unify different science instruments, both computing and experimental, to effectively support science users and operators to execute complex workflows. The FedScI project addresses the software challenges associated with the formation and operation of federated environments by leveraging recent advances in containerization of software and softwarization of hardware. We propose a software framework to streamline the federation usage by science users and it’s provisioning and operations by facility providers. A distinguishing element of our work is the support for improved interaction between experimental devices, such as beam-line instruments, and more traditional high-performance computing resources, including compute, network, storage systems. We present guiding principles for the software framework and highlight portions of a current prototype implementation. We describe our science use case involving neutron imaging beam-lines (SNAP/BL-3, Imaging/CG-1D) at the Spallation Neutron Source and High Flux Isotope Reactor facilities at Oak Ridge National Laboratory. Additionally, we detail plans for a more direct instrument interaction within a federated environment, which could enable more advanced workflows with feedback loops to shorten the time to science.

Naughton III, Thomas↗
DOE OSTI2023

Transition in helium bubble strengthening of copper from quasi-static to dynamic deformation

Damage from low-temperature irradiation and the subsequent degradation of materials performance pose significant challenges for the storage of radioactive materials and for peripheral components in some nuclear reactor designs. Fully understanding the mechanical behavior of such materials requires test data for strain rates in both the quasi-static (< 10/s) and dynamic (>> 10/s) regimes. While dynamic testing has generally been avoided in the past for neutron irradiated (contamination concerns) and ion irradiated (insufficient volume) materials, surface-sensitive Richtmyer-Meshkov instability (RMI) tests were used in the present work to overcome these limitations. Here, nanopillar compression, nanoindentation, and RMI testing data from a helium implanted surface layer (~10 µm thick) were compiled to explore the effects of helium bubbles on the materials strength of high-purity copper at strain rates of 0.001/s – 10 8 /s. While nano-mechanical testing revealed increases in yield strength and hardness with increasing helium dose from 1000 to 4000 appm He, RMI indicated no significant changes in strength as compared to unimplanted copper. Here, this discrepancy in behavior was rationalized through a combination of recent literature and follow-on molecular dynamics (MD) simulations, leading to the conclusion that the nanoscale helium bubbles acting as dispersed barriers to dislocation motion at quasi-static strain rates collapse under shock loading and cease to be effective barriers at high strain rates.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Hydrogen and water interactions with CrMnFeCoNi alloy from density functional theory calculations

High entropy alloys (HEAs) are a promising class of materials with remarkable mechanical and catalytic properties. Among these, the quinary CrMnFeCoNi alloy (also called “Cantor alloy”) has attracted considerable attention given its thermodynamic stability and remarkable mechanical properties under different temperatures. Given that various degradation mechanisms involve multiple contaminants, such as hydrogen and water in hydrogen embrittlement and surface poisoning, respectively, understanding their interactions with the Cantor alloy is critical for its practical applications as structural, nuclear, or hydrogen storage material. In this work, we perform first-principles calculations based on Density Functional Theory (DFT) to investigate such interactions when considering various microstructures, including bulk materials and those containing certain defects, such as grain boundaries, stacking faults, and vacancies. We also employ Global Sensitivity Analysis to identify the importance of different factors in the stability of the impurities. We find that the accuracy of the H formation energy is significantly affected by spin polarization and chemical short-range order. The study also identifies a strong tendency for hydrogen interstitials to segregate to Σ5(210)/[001] symmetric tilt grain boundary, even when H concentrations are high, suggesting that a certain type of grain boundaries acts as H sinks within the alloy. Further, this result is reinforced by the low formation energy of vacancy-hydrogen complexes, which can contain multiple hydrogen atoms. Finally, the surface reactivity analysis reveals that the adsorption energy of oxygen and hydroxyl groups is highly sensitive to the specific metal atom involved in the binding, with a clear preference for chromium atoms, which could have implications for the alloy’s oxidation and corrosion behavior.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Robust hierarchical three dimensional nickel cobalt tungstate-MXene nanocomposite for high performance symmetric coin cell supercapacitors

Design of rational electrode materials with hierarchically structured pseudocapacitive materials has been identified as a successful strategy for revamping the electrochemical characteristics of supercapacitors. However, the simultaneous assurance of strong electrical conductivity and higher specific capacitance via a simple and cost-effective synthesis protocol is of concern today. In this work, Ni-CoWO 4 incorporated MXene nanocomposite has been successfully prepared by a facile hydrothermal process. The structure, morphology, stoichiometry, and chemical characterization of the prepared Ni-CoWO 4 , Ti 3 C 2 T x , and Ni-CoWO4@MXene nanocomposite were explored extensively. MXene demonstrated a layered 2D nanoscale structure whereas pure Ni-CoWO 4 was composed of spherical nanoparticles. The composite Ni-CoWO 4 @MXene revealed the morphology of spherical Ni-CoWO 4 nanoparticles decorated on MXene sheets. Furthermore, a series of electrochemical characterizations illustrated the contribution of the delightful morphology of Ni-CoWO 4 @MXene composite to excellent electrochemistry. The resultant Ni-CoWO 4 @MXene electrode exhibited high specific capacitance of 582 Fg -1 at 1 A g -1 and 93.5 % capacitance retention over the 10,000 cycles., which is higher than that of the individual counterparts Ni-CoWO 4 and MXene. The excellent electrochemical performance of Ni-CoWO 4 @MXene is attributed to the synergistic interaction between Ni-CoWO4 nanoparticles and nanolayered MXene that may create new active sites that enhanced the charge transfer, charge/discharge kinetics and the electrical conductivity. Significantly, the unique Ni-CoWO 4 @MXene supercapacitor prototype delivered a higher energy density of 85.7 Wh kg -1 and power density of 0.85 kW kg -1 establishing its superiority over other Cosingle bondW based supercapacitors. A theoretical study was also performed to correlate the improved charge storage capacity of the prepared Ni-CoWO 4 @MXene composite.

25 ENERGY STORAGE↗
DOE OSTI2025

Regen: An object layout regenerator on large-scale production HPC systems

This article proposes an object layout regenerator called Regen which regenerates and removes the object layout dynamically to improve the read performance of applications. Regen first detects frequent access patterns from the I/O requests of the applications. Second, Regen reorganizes the objects and regenerates or preallocates new object layouts according to the identified access patterns. Finally, Regen removes or reuses the obsolete or regenerated object layouts as necessary. As a result, Regen accelerates access to objects by providing a flexible object layout. We implement Regen as a framework on top of Proactive Data Container (PDC) and evaluate it on Cori supercomputer, a production-scale HPC system, by using realistic HPC I/O benchmarks. The experimental results show that Regen improves the I/O performance by up to 16.92 × compared with an existing system.

Distributed file system↗
DOE OSTI2020

Probing local electrochemistry via mechanical cyclic voltammetry curves

Understanding the mechanical response of an electrode during electrochemical cycling and its correlation to the device electrochemical performance is crucial to improving the performance of insertion-type energy storage devices, electrochemical actuators, water purification, ion separation and neuromorphic computing applications. Here, we visualized the electro-chemo-mechanical coupling behaviors during charge storage of anhydrous and hydrated WO 3 electrodes via in situ atomic force microscopy (AFM) and developed the concept of mechanical cyclic voltammetry (mCV) curves. The relationship between electrochemical current and strain was investigated with simplified models and the results revealed that the proton insertion/deinsertion process could be described through potential-dependent electro-chemo-mechanical coupling coefficients which might indicate changes in insertion processes during electrode cycling. The mCV mapping results highlight the local heterogeneity and show that the charging processes varied across the electrode. These local variations could be further correlated to local morphology, crystal orientations or chemical compositions with proper electrode designs.

36 MATERIALS SCIENCE↗