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At least 325 records · Page 18

Nanostructures for Electrical Energy Storage (NEES) (2020 Final Technical Report)

Nanostructures for Electrical Energy Storage (NEES, www.efrc.umd.edu) was an Energy Frontier Research Center supported by the DOE Office of Science, Basic Energy Sciences, from 8/1/2009 to 7/31/2020. Led by the University of Maryland, NEES enjoyed extensive collaborations with its funded partners, including two DOE Laboratories and six universities. The NEES vision has been to reveal a set of scientific insights and design principles that can underpin a next-generation electrical energy storage approach, building on advances in nanoscale science and technology to achieve simultaneous high power and high energy over extended charge/discharge cycling. The vision is motivated by the recognition that scaling into the nano regime opens the door to new physical phenomena and that the tools enlisted in nanoscale research provide major new opportunities for the synthesis not only of materials at molecular scale but for structures at nano scale and above. NEES has translated this vision into its research program based on two observations. First, while the behavior of ions and electrons in electrolytes and in electrode materials is crucial to electrical energy storage (or more appropriately electrochemical energy storage), it is the transport of ion and electron charge between different structural components of a storage device that ultimately determine its performance. With it well recognized that the choice of electrode materials typically constrain ion transport kinetics as well as maximum ion concentration, the search for better electrode materials has been a primary driver of battery research. At the same time the synthesis of electrodes is typically based on aggregation of particles with varying size, shape, and orientation in the electrode. Together with the presence of additional materials to impart electrical conductivity and cohesion to the composite electrode, change in electrode materials is necessarily accompanied by structural changes at the nano/micro scale that are difficult to categorize and manage. From the beginning, NEES’ vision has been to create and study simpler, highly controlled spatial arrangements of known materials as battery components (electrodes, current collectors, and electrolyte) and to understand how design and structure above the molecular scale determines the energy storage performance available from known materials. Second, advances in nanoscience dramatically expanded the portfolio of synthesis methods, structural motifs, and new phenomena available for research. Some of these gave rapid access to new building blocks at the deep nanoscale (e.g., carbon nanotubes grown by self-assembly, nanoscale arrays formed by electrochemical self-alignment, monolayer films controlled by self-limiting reaction). Such advances served as the enabler for the NEES vision to be pursued experimentally through study of 3D structures created and controlled at the nano, micro, and meso scales. Here, we use meso as in the BES MESO Report, implying not only intermediate or varying length scales, but very much the way behavior is influenced by other factors including aggregation of nanocomponents at different densities and spatial configurations, statistical variations in the aggregates, hierarchical architectures in which they can be assembled, or local 3D configurations that result from the architectures. Over its life cycle, NEES has pursued two overarching goals: (1) to understand the scientific fundamentals of electrochemical storage from the nanoscale to the mesoscale; and (2) to create and learn from innovative, controlled, heterogeneous nanostructures, where such nanostructures can enable the first goal and serve as models for future paradigms in energy storage. Specific goals have included: Synthesize heterogeneous nanostructures comprised of multiple materials arranged in controlled fashion and characterize their behavior; Demonstrate and elucidate design principles for achieving simultaneous high power and high energy; Develop materials processes which enable precision control of thin layers and 3D structures; Investigate the impact of artificial interphases on electrode stability during ion insertion/deinsertion; Create dense arrays of nanostructures to understand how the architecture of these assemblies, along with nanostructure design, influences energy storage behavior at the mesoscale; Identify and understand the consequences of nanoconfinement and local inhomogeneities in 3D mesoscale arrays; Develop and apply computational models to stimulate, guide and interpret experiments.

25 ENERGY STORAGE↗

Engineering evaluation of a sodium hydroxide thermal energy storage module

An engineering evaluation of thermal energy storage prototypes was performed in order to assess the development status of latent heat storage media. The testing and the evaluation of a prototype sodium hydroxide module is described. This module stored off-peak electrical energy as heat for later conversion to domestic hot water needs.

Perdue, D. G.↗

Redundant disk arrays: Reliable, parallel secondary storage

During the past decade, advances in processor and memory technology have given rise to increases in computational performance that far outstrip increases in the performance of secondary storage technology. Coupled with emerging small-disk technology, disk arrays provide the cost, volume, and capacity of current disk subsystems, by leveraging parallelism, many times their performance. Unfortunately, arrays of small disks may have much higher failure rates than the single large disks they replace. Redundant arrays of inexpensive disks (RAID) use simple redundancy schemes to provide high data reliability. The data encoding, performance, and reliability of redundant disk arrays are investigated. Organizing redundant data into a disk array is treated as a coding problem. Among alternatives examined, codes as simple as parity are shown to effectively correct single, self-identifying disk failures.

Gibson, Garth Alan↗

Mass optical storage-tape (MOST)

In today's large mainframe and supercomputer environment there exists a continuous demand for increased performance in digital storage systems. The user need for near-line storage capacity is currently doubling every four years. In addition to higher capacity, a desire exists for higher data transfer rates, and longer term database archivability, at lower, and lower cost. Each component of this quartet of demands appears to be insatiable. Magnetic tape technology presently dominates the digital mass storage markets, but the continuous growth of requirements is drawing attention to the limitations of the technology as an archival mass storage medium. The lowest cost option currently available for long term data storage is to use magnetic tape, although it is not well suited to meeting the need for many tens of years of reliable storage. Today, the majority of magnetic tape mass storage systems are based on the IBM 3480/3490 (or compatible) tape drives. These drives offer only moderate transfer rates and relatively small increments of storage, both of which create a logistics problem due to the large numbers of cartridges necessary in a typical system and the time taken to transfer data. Both higher cartridge capacity and data transfer rates are available in some helical scan magnetic tape systems; however, these command a substantially higher price, exacerbating the cost problem, and are not compatible with most installed systems or tape databases.

Oakley, William S.↗

Keratin-derived functional carbon with superior charge storage and transport for high-performance supercapacitors

In this work, we report a scalable method to synthesize hierarchically porous, hetero-atom doped activated carbon nanosheet from waste biomass-human hair, and demonstrates the use of this carbon as an ultra-high performance electrode material for supercapacitor applications. Microscopic analyses reveal that sheet size ranges from 50 to 200 nm having a thickness of 15–27 nm. As-synthesized, carbon nanosheets possess a hierarchical porous structure having a specific surface area of 1548 m 2 g -1 . Heteroatom concentration (nitrogen, oxygen, and sulfur) of around 25% is confirmed from XPS analysis. Therefore, the novel interconnected hierarchical porous nanosheets structure enables fast adsorption and transportation of ions during electrochemical processes. Also, the abundant chemically available electroactive heteroatom species in the material enhance the wettability of ions and contribute to pseudocapacitance. The electrochemical analyses through cyclic voltammetry and galvanostatic charge-discharge measurements in 6 M KOH reveal the quasi-EDLC behavior of the activated carbons due to the presence of heteroatoms. A reprensentative KOH activated carbon shows an excellent specific capacitance value of 999 F g -1 at a current density of 1 A g -1 . Furthermore, the symmetrically assembled two-electrode device also delivers a maximum energy density of 32 W h Kg -1 at a power density of 325 W Kg -1 . In addition, excellent cyclic stability of 98% capacitance retention is observed after 10,000 continuous GCD cycles even at a high current density of 5 A g -1 . Symmetric flexible supercapacitor device using KOH-PVA-K3FeCN6 as redox gel polymer electrolyte shows a synergistic specific capacitance of 145 mF cm -1 at a current density of 0.8 mA cm -1 exhibiting very less deviation in bending mode. Therefore, this waste biomass derived heteroatom doped hierarchical porous carbon nanosheets can be a promising material for cost-effective high- performance supercapacitor.

42 ENGINEERING↗

A first principles framework to predict the transient performance of latent heat thermal energy storage

Thermal energy storage (TES) is increasingly recognized as an essential component of efficient Combined Heat and Power (CHP), Concentrated Solar Power (CSP), Heating Ventilation and Air Conditioning (HVAC), and refrigeration as it reduces peak demand while helping to manage intermittent availability of energy (e.g., from solar or wind). Latent Heat Thermal Energy Storage (LHTES) is a viable option because of its high energy storage density. Parametric analysis of LHTES in terms of dimensionless numbers is highly desired as a tool to model LHTES systems. One approach is to develop a model equation so as to minimize the error between the model and data obtained from experiments or simulations. While this approach can produce an accurate correlation applicable within the range of data used for its creation, it does not provide physical understanding of the rate-limiting process controlling the transient behavior of the device. In this paper we present an alternative approach whereby the potential rate-limiting processes are identified from first principles and then the key process is determined as a function of time as a LHTES device is charged. For example, in a simple geometry, the melt-fraction can be expected to vary linearly in time if the heat transfer rate is limited by natural convection of the phase changing material and we show it scales with the PCM Grashof number as $Gr^1_p$ and PCM Prandtl number as $Pr_p^{(1/3)}$. On the other hand, if surface area of solid PCM limits the heat transfer rate, the melt fraction increases asymptotically to reach full melting. The existence of these linear and asymptotic regions and the $Gr^1_pP r^{1/3}_p$ shape of the melt fraction curve is verified using our database of 64 simulations. Of practical importance in designing LHTES devices is the melt fraction at which the heat transfer rate ceases to be limited by convection, after which the heat storage rate deteriorates. For our geometry, this is found to be about 90%. This test case of our methodology shows the value of our approach, that predicting heat storage rate based on the rate-limiting physical phenomenon as a function of time is an effective approach to modeling LHTES devices.

25 ENERGY STORAGE↗

Impact of Electrolyte Solvent on Li 4 Ti 5 O 12 /LiNi 0.90 Mn 0.05 Co 0.05 O 2 Battery Performance for Behind-the-Meter Storage Applications

Behind-the-Meter Storage (BTMS) systems require dedicated development of battery materials that target long cycle life and low cost at the system level. Pairing Li 4 Ti 5 O 12 (LTO) and LiNi 0.9 Mn 0.05 Co 0.05 O 2 (NMC90-5-5) shows promise to achieve targets for BTMS applications; however, minimal literature is available that discusses electrolyte solvent selection for this pairing. This study explores the role of electrolyte solvent on cycle life in LTO/NMC90-5-5 batteries. Four model electrolytes are evaluated; the baseline, Gen2, is compared with 1M LiPF 6 added to each of three separate solvents: ethylene carbonate (EC), ethyl methyl carbonate (EMC), and fluoroethylene carbonate (FEC). An additional consideration is that NMC90-5-5 undergoes an H2→H3 phase transition that allows for a significant increase to capacity; however, it’s unclear how this phase transition impacts electrolyte stability and cycle life. Therefore, the phase transition is avoided or accessed by cycling to 2.6V or 2.7V, respectively. The cells with Gen2, cycled to 2.6V, show the highest capacity retention due to EC passivating the LTO, EMC improving stability at the NMC90-5-5, and avoiding increased degradation from the 2.7V protocol. Despite having high initial reactivity that causes Li-depletion, FEC was the only solvent to avoid increased degradation when moving to the higher termination voltage.

25 ENERGY STORAGE↗

Simulation of mass storage systems operating in a large data processing facility

A mass storage simulation program was written to aid system designers in the design of a data processing facility. It acts as a tool for measuring the overall effect on the facility of on-line mass storage systems, and it provides the means of measuring and comparing the performance of competing mass storage systems. The performance of the simulation program is demonstrated.

Holmes, R.↗

Applications of thermal energy storage in the cement industry

In the manufacture of cement, literally trillions of Btu's are rejected to the environment each year. The purpose of this feasibility study program was to determine whether thermal energy storage could be used to conserve or allow alternative uses of this rejected energy. This study identifies and quantifies the sources of rejected energy in the cement manufacturing process, established use of this energy, investigates various storage system concepts, and selects energy conservation systems for further study. Thermal performance and economic analyses are performed on candidate storage systems for four typical cement plants representing various methods of manufacturing cement. Through the use of thermal energy storage in conjunction with waste heat electric power generation units, an estimated 2.4 x 10 to the 13th power Btu/year, or an equivalent on investment of the proposed systems are an incentive for further development.

Jaeger, F. A.↗

Effects of long term storage on aerospace nickel cadmium cell performance

Evaluation of the long term effects on aerospace nickel cadmium cells is described. A number of 6Ah and 12Ah capacity cells which were stored in shorted condition for 9 to 11 years at the Goddard Space Flight Center were selected for the study. Of the three tests which were initiated (initial and final destruction analyses of the test cells, electrical characterization tests, and life cycling tests) only the electrical characterization tests are completed; the other tests are scheduled to be completed by February 1987. The preliminary electrial performance data from the life cycling test and chemical composition data from the destructive testing indicate no anomalous behavior.

Yi, Thomas Y.↗

Database Performance Monitoring for DUNE

This report presents the research, design, and implementation of improved PostgreSQL monitoring for DUNE Rucio database services using Checkmk. The project began with a request to improve dashboard visibility for database performance metrics, including connection usage, configured connection limits, lock activity, wait behavior, storage trends, query performance, and saturation alerts. The initial implementation focused on the dune_rucio_prod database on the rucio_prod PostgreSQL instance because connection saturation and lock contention are direct reliability risks for database-backed services. Existing Checkmk PostgreSQL monitoring was investigated, and several gaps were identified. Built-in connection monitoring did not clearly separate active, idle, idle-in-transaction, total, and usage-percent metrics, while the built-in lock monitoring simplified PostgreSQL lock modes into shared and exclusive categories. To address these gaps, two DSG-specific Checkmk local checks were created: one for connection-state monitoring and one for lock-state monitoring. These checks supplement the built-in PostgreSQL checks and provide additional performance data for dashboard graphs, service states, and alerts.

Bowers, Elliot [Cabrillo Coll.]↗

A deep learning-based battery sizing optimization tool for hybridizing generation plants

Hybrid generation and energy storage systems offer the ability to increase flexibility of the combined asset. This flexibility can be used to increase provision of services already provided by the generation asset, such as timing sale of electricity to the energy market during high price periods, and also enable provision of additional services, such as ancillary services or contribute to resource adequacy. From a generation asset owner perspective, the decision to hybridize includes selecting an energy storage system that, among other factors, maximizes financial performance of the energy storage investment. Yet, existing tools to optimize energy storage sizing are either too rudimentary (i.e., based on “rules of thumb”) or too complex to implement (i.e., require specialized engineering and software knowledge and a high-performance computer to run). This work presents a novel deep learning-based battery sizing optimization tool that is designed to help generation asset owners easily assess preliminary sizing considerations for potential battery investments to hybridize their generation facility. The tool uses deep learning to predict revenue over a broad search space of potential battery sizes, estimates capital and operating costs (including accounting for battery degradation), and computes financial performance of each potential battery system investment, recommending a system with maximum financial performance. The tool is tested and validated for hydropower assets. Finally, this tool will help a greater cross-section of industry consider investments in battery systems, increasing their revenue and helping them compete in rapidly evolving electrify markets.

13 HYDRO ENERGY↗

Porous potassium tantalate-reduced graphene oxide nano cube architecture for high performance hybrid supercapacitors

Energy storage has always been a major concern in the present-day situation. Advanced energy storage devices are batteries, supercapacitor and solar cells. However, advancements have been noteworthy in the field of high-performance hybrid supercapacitors. On this note, we have fabricated a hybrid supercapacitor electrode material Potassium tantalate nano cube (KT NCs) and its reduced graphene oxide composite (KT-rGO NCs) and tested its electrochemical performance. The materials showed high performances with specific capacitance of 565 F/g for KT NCs and 850 F/g for KT-rGO NCs respectively. Energy densities of both KT NCs & KT-rGO NCs are 28.24 Wh/Kg and 29.50 Wh/kg with good retention capacities. Further detailed study of both KT NCs and KT-rGO NCs are carried out with characterization techniques like XRD, FTIR, BET, Raman and HRTEM for structural analysis and electrochemical measurements to analyse various parameters pertaining to its charge storage capacity.

36 MATERIALS SCIENCE↗

Model Formulations: Market clearing models, market design specifications, and dispatch simulation

This document provides various model formulations that will be implemented for the Energy Storage Participation Algorithm pilot competition (ESPA-Comp). This competition will assess the performance of different storage offer algorithms in terms of their ability to maximize the value of storage resources participating under various market designs that vary in the range of complexity of possible storage offers. The model formulations include a general market clearing optimization model and specification to implement it in various market designs. We provide specifications for three market designs to be tested in ESPA-Comp, which we call the two-settlement, multi-settlement, and rolling horizon forward markets. The market designs include different trading frequencies and offer formats. Storage resources participating in the market are provided with primitive values for the resource’s physical capabilities, and they are provided with a storage offer format that their algorithms will be tasked with populating. A detailed physical model is used to assess each storage resource’s ability to maintain its scheduled dispatch according to its state-of-charge, operating temperature, and power conversion efficiency.

25 ENERGY STORAGE↗

Water-Pillared Sodium Vanadium Bronze Nanowires for Enhanced Rechargeable Magnesium Ion Storage

Owing to the advantages of high safety, low cost, high theoretical volumetric capacities, and environmental friendliness, magnesium-ion batteries (MIBs) have more feasibility for large-scale energy storage compared to lithium-ion batteries. However, lack of suitable cathode materials due to sluggish kinetics of magnesium ion is one of the biggest challenges. Herein, water-pillared sodium vanadium bronze nanowires (Na 2 V 6 O 16 ·1.63H 2 O) are reported as cathode material for MIBs, which display high performance in magnesium storage. The hydrated sodium ions provide excellent structural stability. The charge shielding effect of lattice water enables fast Mg 2+ diffusion. It exhibits high specific capacity of 175 mAh g -1 , long cycle life (450 cycles), and high coulombic efficiency (≈100%). At high current density of 200 mA g -1 , the capacity retention is up to 71% even after 450 cycles (compared to the highest capacity), demonstrating excellent long-term cycling performance. The nature of charge storage kinetics is explored. Furthermore, a highly reversible structure change during the electrochemical process is proved by comprehensive electrochemical analysis. The remarkable electrochemical performance makes Na 2 V 6 O 16 ·1.63H 2 O a promising cathode material for low-cost and safe MIBs.

36 MATERIALS SCIENCE↗

Feature Engineering and Ensemble Methods for Imbalanced ICS Intrusion Detection: Pipeline Audit and Constrained Evaluation

Industries are becoming increasingly connected and are more vulnerable to cyberattacks due to the widened attack surface. Industrial Control Systems (ICS) are among the most critical sectors that malicious actors can target, as such attacks can cause significant operational disruption and physical damage. It is imperative to detect such attacks as early as possible. This paper evaluates constraint-conditioned optimistic performance estimates for traditional ML models in ICS intrusion detection (i.e., estimates obtained under contiguous, non-shuffled temporal evaluation without test-set alteration, but with pre-split feature engineering that may introduce temporal leakage, due to dataset constraints). Our findings are threefold. First, we quantify how iterative feature engineering affects tree-based ensemble performance and examine how pipeline decisions (split strategy, sampling scope, and cleaning policy) can inflate or reduce reported IDS results under constraint-bound evaluation. Second, we compare intrinsic class-imbalance handling across ensemble models. Third, under our current pipeline constraints (including pre-split feature engineering), CatBoost achieves the best performance on Water Storage Tank (accuracy: 0.9831, class-1 F1: 0.9682), while Light- GBM achieves the best performance on Gas Pipeline (accuracy: 0.9618, class-1 F1: 0.9086).

97 MATHEMATICS AND COMPUTING↗