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At least 1,315 records · Page 73

Process Optimization of Carbon Electrode Materials Manufacturing by Experimental Study and Machine Learning Techniques

Electrospun carbon fibers from coal have been investigated as electrodes for batteries and supercapacitors. Despite the excellent properties of coal-derived carbon fibers (CCNF) for energy storage devices, there still lacks systematic understanding on how various process parameters affect final electrode performances, which poses challenges to scale from pilot to high volume manufacturing. The goals of this project are twofold. First, we focuse on process optimization for converting a new precursor from powder river basin (PRB) coal, referred to as coal-based polyurethane (CPU) to CCNF using electrospinning. Second, different machine learning techniques will be examined using experimental data from this work and open literature. Specifically, for CPU the following process parameters need to be characterized and optimized in order to produce CCNFs with desirable mechanical integrity and physiochemical properties: precursor composition and viscosity, operating voltage and distance, oxidation and carbonization temperature and duration. Consequently, physiochemical properties of the fibers were characterized to correlate these process parameters with desirable electrochemical performance. Given the complex nature of the fiber production process, ML models are assessed for their ability to capture the nonlinear relationship between process parameters and the electrochemical properties in applications including supercapacitors. As such, we applied various machine learning techniques, to determine which technique produces a model that best predicts device function.

Cincotta, Robert E.F.↗

Establishment of a Vertically Integrated Domestic Manufacturing Process for Production of Substrates Needed for Manufacture of Gas Diffusion Layers

In this project, AvCarb, LLC evaluated the baseline performance metrics of commercial carbon veils and their corresponding Gas Diffusion Layers (GDLs) with the goal of establishing an optimized, vertically integrated production system for wet-laid nonwoven substrates used in gas diffusion media for electrochemical energy storage and conversion devices. Mechanical testing and microstructural characterization were conducted and used to develop a multiscale computational model capable of simulating and predicting the performance of GDLs in fuel cells. Although the project successfully generated foundational transport and modeling data, it was terminated prior to identifying the critical GDL design parameters necessary for full optimization. The program aimed to improve carbon veil fabrication through enhanced fiber dispersion, fiber-fiber adhesion control, and improved web formation, enabling the production of high-quality, uniform substrates. Simulations were intended to guide mixing and solution delivery system design and process conditions, followed by production-scale trials to evaluate fiber dispersion, web uniformity, and mechanical robustness. At full deployment, the proposed production line would have been capable of producing approximately 650,000 m² of carbon veil annually. This capability remains strategically important, as the United States currently lacks a domestic source of wet-laid nonwoven carbon substrates that satisfy the stringent quality requirements for fuel-cell GDLs and electrolyzers representing an ongoing supply-chain vulnerability. Beyond supply-chain benefits, the project established a robust benchmarking dataset for existing commercial carbon veils while advancing next-generation material concepts targeting improved performance and manufacturing consistency.

Olson, Cynthia Lemay↗

In situ anodic electrodeposition of two-dimensional conductive metal-organic framework@nickel foam for high-performance flexible supercapacitor

Owing to their large specific surface area and well-defined porosity, metal-organic frameworks (MOFs) have long been considered as promising materials for energy storage. Unfortunately, their straightforward utilization in supercapacitors was hindered for years due to poor conductivity until the emergence of 2D conductive MOF materials. To date, several 2D conductive MOF-based supercapacitors have been reported. Nevertheless, almost all these supercapacitors were fabricated from MOF powders through a slurry coating method or dense packing method, which negatively affected their capacitor performance. Herein, we have developed an anodic electrodeposition (AED) approach to fabricate a uniformly deposited 2D conducting MOF on nickel foam and use it directly as electrodes for supercapacitors without any additives. Finally, the superior performance of the 2D conducting MOF on nickel foam in both aqueous and organic electrolytes was then disclosed by a series of electrochemical measurements, demonstrating the significant advantages of the AED approach over traditional methods.

2D conductive metal-organic frameworks↗

Bioinspired mechanically interlocking holey graphene@SiO 2 anode

Mechanically interlocking structures that can enhance adhesion at the interface and regulate the stress distribution have been widely observed in biological systems. Inspired by the biological structures in the wings of beetles, we synthesized a holey graphene@SiO 2 anode with strong mechanical interlocking, characterized it electrochemically, and explained its performance by finite element analysis and density functional calculations. The mechanically interlocking structure enhances lithium-ion (Li + ) storage by transmitting the strain from SiO 2 to the holey graphene and by a mechano-electrochemical coupling effect. The interlocking fit hinders the abscission of SiO 2 and the distinctive structure reduces the stress and strain of SiO 2 during (de)lithiation. The positive mechano-electrochemical coupling effect preserves the amount of electrochemically active phase (Li x Si) during cycles and facilitates Li + diffusion. Therefore, the capacity shows only a slight attenuation after 8000 cycles (cycling stability), and the specific capacity is ~1200 mA h g –1 at 5 A/g (rate-performance). This study furnishes a novel way to design high-performance Li + /Na + /K + /Al 3+ anodes with large volume expansion.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Chemical preintercalation of magnesium ions into ⍺-MoO 3 structure for improved electrochemical stability in Li-ion cells

Chemical preintercalation of layered materials, used as electrodes in intercalation-based energy storage devices, represents a promising strategy to enhance electrochemical stability and extend cycle life. However, standardized synthesis approaches for the chemical preintercalation of diverse ions into various layered materials are lacking, necessitating the development of specific synthesis routes for each ion and layered phase combination. In this study, we present the first successful demonstration of Mg 2+ ion chemical preintercalation into the interlayer region of α-MoO 3 , revealing its stabilizing effect during cycling in non-aqueous Li-ion cells. Using ethanol during hydrothermal treatment facilitated molybdenum reduction, which was critical for Mg 2+ ion preintercalation. Interestingly, we found that Mg preintercalation was accompanied by the incorporation of water. Mg-preintercalated α-MoO 3 exhibited enhanced charge storage capacity, electrochemical stability, and power capability compared to pristine α-MoO 3 electrodes. This improved performance is attributed to the structural stabilization provided by Mg 2+ pillars, which prevent undesirable phase transformations during repeated Li intercalation/deintercalation, and increased Li + ion diffusion due to the shielding of electrostatic interactions between electrochemically cycled ions and the α-MoO 3 lattice, enabled by structural water. In conclusion, our study offers new insights into developing chemical preintercalation synthesis approaches that can be broadly applied to a wide range of pillaring ions and layered material hosts.

25 ENERGY STORAGE↗

Using temperature and flow fields to detect gas leakage from canisters containing spent nuclear fuel: Applications to RAMM-TM

The multi-physics STAR-CCM+ code has been used to simulate the temperature and flow fields in canister gas leakage experiments conducted by using a 1/4.5-scale model storage cask. The simulations were conducted at Argonne National Laboratory’s Laboratory Computing Resource Center, utilizing high-performance computing resources. Development of STAR-CCM+ simulation models for the 1/4.5-scale model cask is described herein, followed by validation of the simulation results against experimental data. Canister depressurization and thermal response during gas leakage are discussed, along with analyses of the leakage path and allowable leakage rate. The insights gained from the STAR-CCM+ simulations and leakage analyses will help guide future experiments and actual industry applications of Argonne’s Remote Area Modular Monitoring system for canister surface temperature measurement (RAMM-TM) to enable effective aging management of spent fuel during extended dry storage, as well as help reduce risks to public safety and health and protect the environment.

Canister gas leakage↗

Wabash CarbonSAFE: Detailed Site Characterization Plan, Task 11.0, Technical Report

Wabash CarbonSAFE established that commercial-scale CO 2 storage in the Potosi Dolomite –Maquoketa Group storage complex associated with the Wabash Valley Resources (WVR) plant site near Terre Haute, IN is highly feasible. The CarbonSAFE project team performed this evaluation through extensive data acquisition and analysis including 2D seismic reflection data, wireline logs, well testing, and core/cuttings from the Wabash #1 stratigraphic test well (now plugged and abandoned). This document summarizes work detailed in separate Wabash CarbonSAFE reports and consolidates the geologic characterization, well testing, and storage complex modeling results for the Mt. Simon Sandstone and Potosi Dolomite, two distinct reservoirs characterized at the Wabash CarbonSAFE project site. The report then presents recommendations for the next steps for site characterization, identifies data gaps for future activities, and provides an overall assessment of site potential.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

A WISER way for simulating the performance of gratings

Soft X-ray monochromators for synchrotron radiation sources have been continuously developed over the years, improving energy resolution and stability. Great effort has been made in improving the surface quality of the optics involved, reaching values permitting diffraction-limited images. Still, one problem has not been solved, nor fully understood, yet: groove placing errors. Nowadays, these are one of the major factors responsible for resolving the power reduction of diffraction-gratings-based X-ray monochromators. Despite decades of use of gratings, there is not yet a universally established method for predicting and simulating the effect of groove placing errors on monochromator performance. This is especially important in the new scenario of high-coherent X-ray sources, i.e. diffraction-limited storage rings and free-electron lasers. To address this problem, in this article an approach based on WISER (Wavefront propagatIon Simulation codE libRary) is presented. WISER is a physical optics simulation package, also available in the user-friendly Orange Synchrotron Radiation Suite – OASYS. Even though it was originally conceived to assess the focusing performance of X-ray mirrors in the presence of height defects, it perfectly simulates the performance of a periodic (or quasi-periodic) structure like a diffraction grating. In this article, the way to use WISER and its application to a specific case, e.g. the design of a monochromator for the upgrade of a beamline at the Advanced Light Source, are shown. A simple rule for estimating how well the grooves are placed on a grating, based on calculation of the Strehl ratio, is also presented.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Electrolytes with moderate lithium polysulfide solubility for high-performance long-calendar-life lithium–sulfur batteries

Lithium–sulfur (Li-S) batteries with high energy density and low cost are promising for next-generation energy storage. However, their cycling stability is plagued by the high solubility of lithium polysulfide (LiPS) intermediates, causing fast capacity decay and severe self-discharge. Exploring electrolytes with low LiPS solubility has shown promising results toward addressing these challenges. However, here, we report that electrolytes with moderate LiPS solubility are more effective for simultaneously limiting the shuttling effect and achieving good Li-S reaction kinetics. We explored a range of solubility from 37 to 1,100 mM (based on S atom, [S]) and found that a moderate solubility from 50 to 200 mM [S] performed the best. Using a series of electrolyte solvents with various degrees of fluorination, we formulated the S ingle- S olvent, S ingle- S alt, S tandard S alt concentration with M oderate L i PSs so l ubility E lectrolytes (termed S 6 MILE ) for Li-S batteries. Among the designed electrolytes, Li-S cells using fluorinated-1,2-diethoxyethane S 6 MILE (F4DEE-S 6 MILE) showed the highest capacity of 1,160 mAh g −1 at 0.05 C at room temperature. At 60 °C, fluorinated-1,4-dimethoxybutane S 6 MILE (F4DMB-S 6 MILE) gave the highest capacity of 1,526 mAh g −1 at 0.05 C and an average CE of 99.89% for 150 cycles at 0.2 C under lean electrolyte conditions. This is a fivefold increase in cycle life compared with other conventional ether-based electrolytes. Moreover, we observed a long calendar aging life, with a capacity increase/recovery of 4.3% after resting for 30 d using F4DMB-S 6 MILE. Furthermore, the correlation between LiPS solubility, degree of fluorination of the electrolyte solvent, and battery performance was systematically investigated.

25 ENERGY STORAGE↗

Geological Thermal Energy Storage Using Solar Thermal and Carnot Batteries: Techno-Economic Analysis: Preprint

Energy storage is increasingly necessary as Variable Renewable Energy (VRE) technologies are deployed. Seasonal energy storage can shift energy generation from the summer to the winter, but these technologies must have extremely large energy capacities and low costs. Geological Thermal energy storage (GeoTES) is proposed as a solution for long-term energy storage. Excess thermal energy can be stored in permeable reservoirs such as aquifers and depleted hydrocarbon reservoirs for several months. In this article, we describe a techno-economic model that has been developed to evaluate GeoTES systems. The models are developed by combining the output of specialist models which enables the performance and cost of both the subsurface and surface systems to be captured. Off-design models are developed so that the performance can be evaluated at each hour of the year. GeoTES can be charged with two different energy sources: (1) concentrating solar thermal and (2) renewable electricity using heat pumps (henceforth known as a "Carnot Battery"). The stored thermal energy can be used to generate electricity and - uniquely - also directly produce heat that can be used by industrial processes. Furthermore, Carnot-Battery-GeoTES can also be used to form a cold storage reservoir. Preliminary results that quantify the technical and economic performance of these two GeoTES systems are presented.

carnot battery↗

Safe, Low-Cost, High Energy-Density, Solid-State Li-Ion Batteries

We developed intrinsically safe, robust, low-cost, high-energy-density solid-state Li-ion batteries, by integrating high conductivity garnet-type solid Li ion electrolytes and several different cathodes in tailored microstructures, fabricated by low-cost supported thin-film ceramic techniques, to overcome the primary technological barriers to next generation battery technology. In this ARPA-E project we employed Li-garnet solid-state electrolytes pioneered by one of the co-investigators (Thangadurai) which has room temperature (RT) conductivity of ~10 -3 S cm -1 . The highly stable garnet SSE allowed the use of S, NMC, and other cathodes with Li metal anodes without stability or flammability concerns. We studied the garnet’s stability when exposed to CO 2 and humidity (with or without an ALD coating) and showed that the material can be processed in ambient air for most steps prior to battery assembly, significantly reducing production costs. We extensively studied and scaled up the synthesis of the powder and explored external suppliers of garnet to determine the best pathway for commercial success. We used low-cost and scalable tapecasting fabrication methods to create porous-dense-porous “trilayer” solid electrolyte microstructures with a ~20 μm separating dense layer, and >70% porosity porous layers to host the electrodes. These scalable multilayer ceramic fabrication techniques, without need for dry rooms or vacuum equipment, also provide for dramatically reduced manufacturing costs. The tailored microstructured electrode supports (scaffold) increased interfacial area ~50x, overcoming the high impedance typical of planar geometry SSLiBs, resulting in record-setting 10 mA/cm 2 lithium cycling in a symmetric cell. We expanded our tapecasting ability and showed tapes >25m in length by the end of the project. We demonstrated the ability to sinter garnet without the use of a garnet powderbed, which could have been a major obstacle and waste of material at scale. At the same time, we expanded the size of our trilayers from coin cells (0.7 cm 2 ) to the full format design (30 cm 2 ). To develop full cells, we demonstrated 250 Wh/kg at room temperature with commercial NMC electrode films in a bilayer configuration. Similarly, we demonstrated 280 Wh/kg trilayer Li-S cells at room temperature with >90% capacity retention over 300 cycles. At 90°C we demonstrated 350 Wh/kg with a Li-S trilayer. The high thermal stability of the garnet electrolyte also enabled extended cycling (400 cycles) of a Li-TiS 2 cell at 150 °C, showcasing the exceptional safety and nonflammability of the solid-state trilayer batteries. Ion Storage Systems has taken this technology and knowledge to produce trilayer garnet electrolytes and is building out facilities to commercialize high performance solid state batteries. ISS has hired a strong staff, identified and communicated with a large number of potential partners, and successfully secured follow-on funding.

25 ENERGY STORAGE↗

Developing Novel Electrode Materials for Aqueous Battery

Aqueous rechargeable batteries (ARBs) are particularly interesting for large-scale energy storage due to their inherent safety, superior rate capability and environmental friendliness. However, ARBs are not widely explored as yet, so we proposed designing, preparing, and testing new intercalation materials for ARBs. Development of these electrodes will enrich the electrode chemistry of existing ARBs, open up new avenues for high-performance electrode and system design, offer opportunities to improve energy efficiency of water purification, and inform future development of controls strategies and management systems for stationary aqueous energy storage. Researchers from Bosch and LBNL collaborated on relevant materials to pursue and the general design of experiments to implement. Bosch researchers prepared and fabricated the electrodes and used various characterization facilities at LBNL to evaluate electrode performance in-device. The research collaboration resulted in identifying electrode materials capable of Na + and Ca 2+ intercalation in aqueous systems, and their application for desalination was explored using testing platform available at LBNL. Besides the specific materials and their performance, the data collected during the study was also used to inform a broader techno-economic analysis to compare intercalation-desalination technique to commercially available capacitive desalination approach. Outcomes of this research effort will be published in peer-reviewed journals.

25 ENERGY STORAGE↗

Identifying Hydrometeorological Factors Influencing Reservoir Releases Using Machine Learning Methods

Simulation of reservoir releases plays a critical role in social-economic functioning and our nation's security. How-ever, it is challenging to predict the reservoir release accurately because of many influential factors from natural environments and engineering controls such as the reservoir inflow and storage. Moreover, climate change and hydrological intensification causing the extreme precipitation and temperature make the accurate prediction of reservoir releases even more challenging. Machine learning (ML) methods have shown some successful applications in simulating reservoir releases. However, previous studies mainly used inflow and storage data as inputs and only considered their short-term influences (e.g, previous one or two days). In this work, we use long short-term memory (LSTM) networks for reservoir release prediction based on four input variables including inflow, storage, precipitation, and temperature and consider their long-term influences. We apply the LSTM model to 30 reservoirs in Upper Colorado River Basin, United States. We analyze the prediction performance using six statistical metrics. More importantly, we investigate the influence of the input hydrometeorological factors, as well as their temporal effects on reservoir release decisions. Results indicate that inflow and storage are the most influential factors but the inclusion of precipitation and temperature can further improve the prediction of release especially in low flows. Additionally, the inflow and storage have a relatively long-term effect on the release. These findings can help optimize the water resources management in the reservoirs.

Fan, Ming↗

Resilience of the Electric Grid Through Trustable IoT-Coordinated Assets

The electricity grid has evolved from a physical system to a cyberphysical system with digital devices that perform measurement, control, communication, computation, and actuation. The increased penetration of distributed energy resources (DERs) including renewable generation, flexible loads, and storage provides extraordinary opportunities for improvements in efficiency and sustainability. However, they can introduce new vulnerabilities in the form of cyberattacks, which can cause significant challenges in ensuring grid resilience. We propose a framework in this paper for achieving grid resilience through suitably coordinated assets including a network of Internet of Things devices. A local electricity market is proposed to identify trustable assets and carry out this coordination. Situational Awareness (SA) of locally available DERs with the ability to inject power or reduce consumption is enabled by the market, together with a monitoring procedure for their trustability and commitment. With this SA, we show that a variety of cyberattacks can be mitigated using local trustable resources without stressing the bulk grid. Multiple demonstrations are carried out using a high-fidelity cosimulation platform, real-time hardware-in-the-loop validation, and a utility-friendly simulator.

distributed energy resources↗

Hydrogen Storage System Modeling: Public Access, Maintenance, and Enhancements

This presentation summarizes the Fiscal Year 2020 status and accomplishments for the Hydrogen Storage System Modeling project, a collaborative effort to manage, update, and enhance hydrogen storage system models developed under the Hydrogen Storage Engineering Center of Excellence (HSECoE). The project goal is to provide validated modeling tools that will be used by researchers to evaluate the performance of their new materials in engineered systems relative to the DOE technical targets.

AMR↗

2021 Annual Technology Baseline (ATB) Cost and Performance Data for Electricity Generation Technologies

Starting in 2015 NREL has presented the Annual Technology Baseline (ATB) in an Excel workbook that contains detailed cost and performance data, both current and projected, for renewable and conventional technologies. The workbook includes a spreadsheet for each technology. This version of the workbook provides the final updates to data for the 2021 ATB. In 2019 and 2020, NREL has also provided selected data in Tableau workbooks and structured summary csv files. The data for 2015 - 2020 is located on https://data.nrel.gov. In 2021 and going forward, the data is cloud optimized and provided in the OEDI data lake. A website documents this and future data at https://atb.nrel.gov.

Array↗

Cold Climate Integrated Heat Pump with Energy Storage for Grid-Responsive Control

An air-source integrated heat pump (ASIHP) is a multifunctional unit, capable of space cooling, space heating, and water heating. We developed a packaged cold climate ASIHP, using a multi-stage compressor, capable of working down to -25°C, and providing 100% rated capacity down to -15°C with a heating COP > 2.2. An innovative system configuration and related controls were developed to solve charge balance in the integrated heat pump, smooth charge migration, and mode transition among multiple working modes. Extensive laboratory investigations for individual modes were performed to verify the performance. Its integrated heating capability provides speedy water heating to meet domestic hot water use and store heating energy in a phase change material ceiling/panel. The heating energy storage can be used to shift the load when the electricity price is high. Based on the performance data and a calibrated model from the laboratory testing, we conducted building energy simulations driven by a model predictive control, using EnergyPlus in one U.S. cold climate zone to investigate the grid-responsive control strategy and estimate the utility cost reduction potential.

Shen, Bo↗

An approach for fast and accurate simulation of phase change material based thermal energy storage in buildings

Latent heat thermal energy storage (LHTES) has significant potential for mitigating peak electricity demand and enabling load shifting in buildings. Phase Change Material embedded heat exchangers (PCM-HX) can significantly improve energy demand management due to high storage capacity. However, PCM-HX evaluation typically depends on computationally expensive fully transient simulations, posing significant challenges for scalable system- and building-level energy assessments across different climates and system architectures. This paper presents a generalized, accurate, and computationally efficient methodology for simulating building energy systems integrated with LHTES. The PCM-HX transient performance is represented by performance maps generated using a Generalized Resistance-Capacitance Model (GRCM) that enables accurate predictions of arbitrary PCM-HXs at low computational cost. The feasibility of the proposed approach was verified using a case study considering a dual-mode heat pump-thermal energy storage (HP-TES) system simulated in Modelica with Spawn of EnergyPlus™ for a DOE prototype small office building in two locations: Tampa, FL, and International Falls, MN. The PCM-HX performance maps provided accurate predictions of PCM-HX transient behavior, with mean absolute percentage deviations within 2–4% compared to GRCM while also achieving at least 1800× reduction in computational time. Moreover, the HP-TES system achieved energy savings of up to 17.4% in Tampa, FL, and 62.2% in International Falls, MN, demonstrating the broader applicability of the proposed methodology across different climate zones. This work highlights the importance of robust PCM-HX models in enabling accurate and computationally efficient building-level simulations and enabling future research opportunities for investigating optimized HP-TES designs and advanced control strategies for grid-interactive buildings.

Modelica↗