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At least 1,027 records · Page 57

Zinc batteries for grid-scale energy storage: Challenges, opportunities, and future directions

The global electricity sector is undergoing rapid transformation, increasing demand for reliable stationary energy storage and intensifying the need for safe, cost-effective, and scalable technologies for grid-scale applications. While lithium-ion batteries currently dominate the market, concerns over cost, safety, and resource availability motivate the exploration of alternative chemistries. Zinc-based batteries have emerged as a promising option due to the abundance, low cost, and wide geographic distribution of zinc, combined with the inherent safety of aqueous electrolytes. This perspective examines the potential of zinc batteries for stationary energy storage, with particular focus on rechargeable zinc-air systems. We discuss the evolution of zinc battery technologies and compare zinc-air, zinc-bromine, nickel-zinc, and aqueous zinc-ion chemistries, highlighting their advantages for grid applications. Key challenges limiting rechargeable zinc battery performance are analyzed, including dendrite formation and corrosion at the zinc anode, electrolyte degradation from carbonation and evaporation, and sluggish oxygen electrocatalysis at the air cathode. Emerging strategies to address these limitations are reviewed, including advanced electrode architectures, electrolyte engineering, catalyst development, and system-level design improvements. Lastly, we outline future research directions and opportunities for developing durable, efficient, and economically viable zinc-based energy storage systems for grid-scale applications.

Aqueous electrolytes↗

Electrochemical leaching of critical materials from lithium-ion batteries: A comparative life cycle assessment

The manufacturing of lithium-ion batteries (LIB) requires critical materials such as cobalt (Co) and lithium (Li) that are essential for clean-energy products including electric vehicles. Because of their rapidly increasing demand and limited supply, the recycle and reuse of these materials from end-of-life LIB have garnered a lot of interest. Electrochemical leaching has emerged as a sustainable method to extract critical materials out of LIBs, so life cycle assessment was conducted to compare the environmental impacts with traditional peroxide-based leaching and another emerging technology – SO 2 -based leaching. The results showed that electrochemical leaching reduces the global warming potential (GWP) by 80%-87% compared to peroxide-based leaching due to a lower acid consumption, avoidance of hydrogen peroxide, and regeneration of reducing agent iron (II) sulfate and compares well with SO 2 -based leaching in most impact categories. Furthermore, the analysis suggested renewable energy can further reduce the environment footprint of electrochemical leaching.

36 MATERIALS SCIENCE↗

Thermomechanical and sequential stress performance of photovoltaic backsheets

Photovoltaic backsheet technology is utilized to protect the interior components of solar modules from environmental stress as well as provide electrical insulation to the module. The growing demand for solar energy and longer module service life requirements have brought backsheet performance into focus. Despite being a protective packaging material, many backsheets have exhibited failure in the field, limiting the performance and service life of entire modules. Most backsheets consist of multiple polymeric layers laminated together using adhesives. A new backsheet, with a high performance polyamide structure, has been developed as the solution to module failure. Primarily, it contains a unique polyamide-ionomer alloy targeted at improved weather resistance. In this study, several photovoltaic industry standard backsheets, and the novel polyamide compositions of multilayered backsheets fabricated from the coextrusion process, were examined using thermomechanical analysis (TMA). The coefficient of thermal expansion (CTE) for entire backsheets and their constituent layers was used to model the thermomechanical behavior of various backsheet constructions. Subsequently, thermal cycling was performed in the TMA to examine the intrinsic thermal behavior of the backsheets. Thermal cycling in the TMA indicates the resilience and dimensional stability in the coextruded structures as opposed to the laminated structures. Lastly, results from a Module Accelerated Sequential Testing (MAST), are included to show the mechanical integrity of these backsheets after sequential exposure to stressors including damp heat, ultra-violet (UV) light radiation, and thermal cycling. The laminate backsheets deteriorated extensively after sequential exposure to these stressors, while the novel coextruded structures retained their physical properties.

14 SOLAR ENERGY↗

Sustainable Critical Minerals: Mining, Production, and Legacy

Critical minerals (CMs) are required in renewable energy systems, electric vehicles, electronics, and national defense. Global demand has increased rapidly due to energy and digital transitions, and the United States has become increasingly reliant on vulnerable supply chains. Geological scarcity, trade barriers, environmental hurdles, and processing challenges impede domestic CM production growth. Emerging strategies, including circular economy practices and advanced sustainable mining and processing techniques, can mitigate supply chain and economic risks. To advance these approaches, consistent research priorities, policy revisions, and technology investments are required to develop a resilient CM supply. Doing so with a focus on sustainability goals can simultaneously advance domestic economic and technological goals while limiting environmental impacts and supporting global environmental goals.

biomining↗

Network-Aware and Welfare-Maximizing Dynamic Pricing for Energy Sharing

The proliferation of behind-the-meter (BTM) distributed energy resources (DER) within the electrical distribution network presents significant supply and demand flexibilities, but also introduces operational challenges such as voltage spikes and reverse power flows. In response, this paper proposes a network-aware dynamic pricing framework tailored for energy-sharing coalitions that aggregate small, but ubiquitous, BTM DER downstream of a distribution system operator's (DSO) revenue meter that adopts a generic net energy metering (NEM) tariff. By formulating a Stackelberg game between the energy-sharing market leader and its prosumers, we show that the dynamic pricing policy induces the prosumers toward a network-safe operation and decentrally maximizes the energysharing social welfare. The dynamic pricing mechanism involves a combination of a locational ex-ante dynamic price and an ex-post allocation, both of which are functions of the energy sharing's BTM DER. The ex-post allocation is proportionate to the price differential between the DSO NEM price and the energy-sharing locational price. Simulation results using real DER data and the IEEE 13-bus test systems illustrate the dynamic nature of network-aware pricing at each bus, and its impact on voltage.

aggregates↗

Ammonia-Based Energy Storage Technology

The University of North Dakota Energy & Environmental Research Center (EERC), in partnership with the U.S. Department of Energy National Energy Technology Laboratory (NETL), Basin Electric Power Cooperative, Minnkota Power Cooperative, Otter Tail Power Company, and the North Dakota Industrial Commission (energy technology research and development sponsor), undertook a project to model, validate, and advance (from Technology Readiness Level [TRL] 2 to TRL 3) the ammonia-based energy storage technology (NH 3 -BEST) concept. The concept is designed to enable electricity-generating unit (EGU) accommodation of power demand fluctuations while steadily operating within an optimal-performance baseline power output range, ensuring maximum EGU operational efficiency and minimum degradation of materials, equipment, and performance because of load-cycling-driven stresses.

25 ENERGY STORAGE↗

Optimization of Conditions for Photoluminescence-Based Sensing of Critical Minerals: Strategies and Outlook

Economically critical minerals and metals are vital to America’s security, with application areas in energy, advanced technologies, and defense systems. The growing implementation of renewable energy sources such as electric vehicles is expected to significantly increase demand for these minerals, while the global supply is monopolistic, with most of the production occurring in a few countries outside of the US. To mitigate potential supply chain vulnerabilities, the domestic production of economically critical metals has become a bipartisan priority of the US government, and unconventional sources such as coal and its utilization byproducts such as fly ash and acid mine drainage are being actively explored as an alternative method for meeting domestic demand. Slow and expensive characterization methods for critical metals present a significant pain point for domestic production, which has led to the exploration of alternative low-cost, portable platforms capable of detecting target metals during resource prospecting and downstream process monitoring. The National Energy Technology Laboratory has developed a portable fiber optic-based luminescence spectrometer that utilizes a metal-organic framework (MOF) material to detect and distinguish parts-per-billion levels of the visible-emitting rare earth elements terbium, dysprosium, samarium, and europium, which are all economically critical metals. Although preliminary results with this system are promising, a crucial barrier to practical deployment is the ability to operate in low pH, high ionic strength environments, as acidic conditions and the presence of other metal ions can significantly reduce luminescence signal. Here, current strategies related to sample treatment, material design, and sensor configuration are discussed in the context of improving sensor performance in application-relevant conditions. Additionally, future opportunities, such as the optimization of the sensing binding environment through computational methods and specific metals to be removed for treatment will be discussed, presenting a forward-looking view for innovation in luminescent sensing of critical metals.

36 MATERIALS SCIENCE↗

CRADA Number NFE-21-08827 with DayLyte, Inc. (CRADA Final Report)

DayLyte Batteries is developing an aqueous Sodium-Air battery made with abundant materials while being half to a third the weight of Li-ion to power electric aircraft, electric vehicles and provide renewable energy on demand. To make this battery practical, DayLyte is developing a thin film ceramic Nasicon solid electrolyte amenable to rapid scaleup as well as a protective coating that will protect the solid electrolyte from 50wt% NaOH during the battery’s end-of-discharge while still allowing Na-ions to pass back and forth. If the thin film solid electrolyte and stable coating can be developed it will open the world to step change in battery performance all while not sacrificing the environment on the way. The project was designed to first focus on making and characterizing the Nasicon membrane followed by measuring its electrochemical performance, then assembling a full cell, optimizing its NaOH stability and then optimize the overall prototype design. Over the past two years, we have significantly improved the Nasicon film uniformity, demonstrated protective ligands that are stable in 50wt% NaOH by measuring no mass change with a quartz crystal microbalance, tested different heating methods like tube furnace and rapid heating and developed glassy carbon coatings on the current collector to prevent Nasicon-current collector alloying. We have found that getting film uniformity as measured by electrochemical impedance spectroscopy (EIS) is difficult because of different factors like surface roughness, deposition uniformity and heat treatment time and uniformity. The glassy carbon coating should significantly reduce the surface roughness and by tuning the coating conditions the film deposition uniformity improves and using an automated heating method should lead to much improved film uniformity.

25 ENERGY STORAGE↗

Liquid Copper and Iron Production from Chalcopyrite, in the Absence of Oxygen

Clean energy infrastructure depends on chalcopyrite: the mineral that contains 70% of the world’s copper reserves, as well as a range of precious and critical metals. Smelting is the only commercially viable route to process chalcopyrite, where the oxygen-rich environment dictates the distribution of impurities and numerous upstream and downstream unit operations to manage noxious gases and by-products. However, unique opportunities to address urgent challenges faced by the copper industry arise by excluding oxygen and processing chalcopyrite in the native sulfide regime. Through electrochemical experiments and thermodynamic analysis, gaseous sulfur and electrochemical reduction in a molten sulfide electrolyte are shown to be effective levers to selectively extract the elements in chalcopyrite for the first time. We present a new process flow to supply the increasing demand for copper and byproduct metals using electricity and an inert anode, while decoupling metal production from fugitive gas emissions and oxidized by-products.

36 MATERIALS SCIENCE↗

Using Real-Time Electricity Prices to Leverage Electrical Energy Storage and Flexible Loads in a Smart Grid Environment Utilizing Machine Learning Techniques

With exposure to real-time market pricing structures, consumers would be incentivized to invest in electrical energy storage systems and smart predictive automation of their home energy systems. Smart home automation through optimizing HVAC (heating, ventilation, and air conditioning) temperature set points, along with distributed energy storage, could be utilized in the process of optimizing the operation of the electric grid. Using electricity prices as decision variables to leverage electrical energy storage and flexible loads can be a valuable tool to optimize the performance of the power grid and reduce electricity costs both on the supply and demand sides. Energy demand prediction is important for proper allocation and utilization of the available resources. Manipulating energy prices to leverage storage and flexible loads through these demand prediction models is a novel idea that needs to be studied. In this paper, different models for proactive prediction of the energy demand for an entire city using different machine learning techniques are presented and compared. The results of the machine learning techniques show that the proposed nonlinear autoregressive with exogenous inputs neural network model resulted in the most accurate predictions. These prediction models pave the way for the demand side to become an important asset for grid regulation by responding to variable price signals through battery energy storage and passive thermal energy storage using HVAC temperature set points.

25 ENERGY STORAGE↗

Network-Aware and Welfare-Maximizing Dynamic Pricing for Energy Sharing: Preprint

The proliferation of behind-the-meter (BTM) distributed energy resources (DER) within the electrical distribution network presents significant supply and demand flexibilities, but also introduces operational challenges such as voltage spikes and reverse power flows. In response, this paper proposes a network-aware dynamic pricing framework tailored for energy-sharing coalitions that aggregate small, but ubiquitous, BTM DER downstream of a distribution system operator's (DSO) revenue meter that adopts a generic net energy metering (NEM) tariff. By formulating a Stackelberg game between the energy-sharing market leader and its prosumers, we show that the dynamic pricing policy induces the prosumers toward a network-safe operation and decentrally maximizes the energysharing social welfare. The dynamic pricing mechanism involves a combination of a locational ex-ante dynamic price and an ex-post allocation, both of which are functions of the energy sharing's BTM DER. The ex-post allocation is proportionate to the price differential between the DSO NEM price and the energy sharing locational price. Simulation results using real DER data and the IEEE 13-bus test systems illustrate the dynamic nature of network-aware pricing at each bus, and its impact on voltage.

energy communities↗

Fitness-for-Service Analysis of Reactor Components under Flexible Load-Following Operating Conditions

Conventional power-generation plants, including nuclear plants, have been traditionally designed to provide a steady baseload energy capacity, optimizing output efficiency while minimizing variable costs. However, the growing adoption of large-scale renewable energy-generation systems, which rely on intermittent sources such as solar and wind, has introduced more variability into the energy supply in interconnected electricity grids. As a result, the next generation of power plants needs to operate in what is known as the load-following mode, requiring flexible adjustments in electricity production to align with the energy demand on the grid. This transition from the steady baseload operation to load-following operating conditions can significantly increase the number of times various plant components are exposed to transient stresses. This increased thermo-mechanical cycling can lead to accelerated material degradation, thereby elevating the risk of premature failure of a component. It becomes imperative to conduct a comprehensive analysis of fatigue, creep-fatigue, and stress corrosion cracking life, to assess the resilience of the various engineering components under these flexible load-following operating conditions. This study aims to develop a comprehensive numerical model of a light-water reactor pressure vessel (RPV) to investigate its degradation under various operating scenarios. This coupled thermo-mechanical finite element analysis evaluated the stress response of the RPV caused by considering fluctuations in thermal and mechanical loads caused by the varying pressure and temperature occurring during the load-following operation. Critical locations on the RPV are subsequently identified based on the stress response. The stress intensity factors for the postulated flaws at those locations are then calculated, followed by an evaluation of the reactor's life in accordance with the ASME Boiler and Pressure Vessel Code Section XI. This comprehensive life assessment covers a number of transients expected during the flexible load-following operation, providing invaluable insights into the RPV's structural integrity. Moreover, the development methodology can be adapted to other reactor components, as well as components of conventional power stations that are affected by varying operating conditions.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Impact analysis of personalized thermostat demand response

Demand response (DR) aims to curtail peak electric load to avoid running inefficient power plants, reduce costly transmission capacity increases, and improve grid reliability. One method of DR for residential settings involves the utility or third part remotely adjusting thermostat temperatures. Cooling setpoints may be increased 2°F – 6°F for hours, irrespective of occupant comfort. To maintain their comfort, occupants override these setpoint changes impacting the reliability of DR services provided to the grid. This paper presents a preliminary impact analysis of replacing the current DR approach of uniform thermostat setbacks for an entire population with personalized and context aware DR based on a dynamic model of occupant thermal comfort behavior. Over 151k interactions with ecobee thermostats are analyzed to predict the impact of such personalized DR on overrides, energy curtailment magnitude, and reliability.

Kane, Michael↗

Three-dimensional electronic scaffolds for monitoring and regulation of multifunctional hybrid tissues

Recently, the integration of electronic elements with cellular scaffolds has brought forth the ability to monitor and control tissue function actively by using flexible free-standing two-dimensional (2D) systems. Capabilities for electrically probing complex, physicochemical and biological three-dimensional (3D) microenvironments demand, however, 3D electronic scaffolds with well-controlled geometries and functional-component distributions. This work presents the development of flexible 3D electronic scaffolds with precisely defined dimensions and microelectrode configurations formed using a process that relies on geometric transformation of 2D precursors by compressive buckling. It demonstrates a capability to fabricate these constructs in diverse 3D architectures and/or electrode distributions aimed at achieving an enhanced level of control and regulation of tissue function relatively to that of other approaches. In addition, this work presents the integration of these 3D electronic scaffolds within engineered 3D cardiac tissues, for monitoring of tissue function, controlling tissue contraction through electrical stimulation, and initiating on-demand, local release of drugs, each through well-defined volumetric spaces. These ideas provide opportunities in fields ranging from in vitro drug development to in vivo tissue repair and many others.

3D electronic scaffolds↗

Vehicle-to-manufacturing (V2M) system: A novel approach to improve energy demand flexibility for demand response towards sustainable manufacturing

The U.S. manufacturing sector accounts for 77% of the industrial energy consumption, but its participation in demand response (DR) programs is largely lagged behind. The limited flexibility in production scheduling under high capacity utilization and the lack of DR schemes that incorporate energy demand flexibility measures are deemed as major barriers. In this study, a framework of the interactive vehicles-to-manufacturing (V2M) energy sharing system is proposed to improve the energy demand flexibility of the aggregated system and enhance the DR effectiveness for manufacturers. The V2M-based DR scheme aims to reduce the energy cost by load shifting through joint production and energy sharing control, which can eventually promote manufacturing DR implementation even under high capacity utilization requirements and dynamic real-time electricity prices. The V2M system is modeled based on a discrete-Markov chain considering the complex interconnections among various manufacturing resources and multi-directional energy flows among manufacturing facilities, electric vehicles, and the power grid. Based on the system model, a mixed-integer nonlinear programming (MINLP) problem is formulated to identify the optimal DR scheme. The effectiveness of the proposed approach is validated through comparisons with traditional manufacturing DR schemes. Finally, the results show that a 2.1 to 6.5 times energy demand flexibility improvement and an additional 4.7% to 6.9% energy cost reduction can be achieved by the proposed approach.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Tunable Nanoscale Evolution and Topological Phase Transitions of a Polar Vortex Supercrystal

Here, understanding the phase transitions and domain evolutions of mesoscale topological structures in ferroic materials is critical to realizing their potential applications in next-generation high-performance storage devices. Here, the behaviors of a mesoscale supercrystal are studied with 3D nanoscale periodicity and rotational topology phases in a PbTiO 3 /SrTiO 3 (PTO/STO) superlattice under thermal and electrical stimuli using a combination of phase-field simulations and X-ray diffraction experiments. A phase diagram of temperature versus polar state is constructed, showing the formation of the supercrystal from a mixed vortex and α-twin state and a temperature-dependent erasing process of a supercrystal returning to a classical α-twin structure. Under an in-plane electric field bias at room temperature, the vortex topology of the supercrystal irreversibly transforms to a new type of stripe-like supercrystal. Under an out-of-plane electric field, the vortices inside the supercrystal undergo a topological phase transition to polar skyrmions. These results demonstrate the potential for the on-demand manipulation of polar topology and transformations in supercrystals using electric fields. The findings provide a theoretical understanding that may be utilized to guide the design and control of mesoscale polar structures and to explore novel polar structures in other systems and their topological nature.

P=phase-field simulations↗

Enhancing Responsiveness and Resilience with Distributed Applications in the Grid

A number of trends are increasing the variability in electric power systems resulting in a need for new approaches in control. The increased variability is originating from distributed energy resources and an increasing demand for personalized energy choice from customers grid-edge. Electricity distribution systems continue to incorporate increasing numbers of intelligent end devices, automated switchgear, and sensing and measurement devices which are providing more visibility and control at the grid-edge. Traditional distribution system planning and operations techniques must evolve to meet the new complexity while continuing to deliver safe, reliable, and cost-effective energy. New technologies are enabling new capabilities at the grid-edge to respond to these needs. Distributed applications can deploy intelligence across the distribution grid with peer-to-peer communications and a shared data context for their local environment. These applications can cooperate with each other to respond quickly to changing grid conditions. This enables a layered coordination framework spanning the centralized Advanced Distribution Management System functions with wide area visibility to these new distributed applications running at intelligent devices and meters throughout the distribution system. This paper describes an open-architecture, open-source system approach for commercial scale integration of devices and intelligence at the grid-edge.

Ogle, James P.↗

Demand-Side Grid (dsgrid) TEMPO Light-Duty Vehicle Charging Profiles v2022

Simulated hourly electric vehicle charging profiles for light-duty household passenger vehicles in the contiguous United States, 2018-2050. Profiles are differentiated by scenario, county, household and vehicle types, and charging type. Data was produced in 2022 using the Transportation Energy & Mobility Pathway Options (TEMPO) model and published in demand-side grid (dsgrid) toolkit format. Data are available for three adoption scenarios: "AEO Reference Case", which is aligned with the U.S. EIA Annual Energy Outlook 2018 (linked below), "EFS High Electrification", which is aligned with the High Electrification scenario of the Electrification Futures Study (linked below), and "All EV Sales by 2035", which assumes that average passenger light-duty EV sales reach 50% in 2030 and 100% in 2035. The charging shapes are derived from two key assumptions of which data users should be aware: "ubiquitous charger access", meaning that drivers of vehicles are assumed to have access to a charger whenever a trip is not in progress, and "immediate charging", meaning that immediately after trip completion, vehicles are plugged in and charge until they are either fully recharged or taken on another trip. These assumptions result in a bounding case in which vehicles' state of charge is maximized at all times. This bounding case would minimize range anxiety, but is unrealistic from the point of view of both electric vehicle service equipment (EVSE) (i.e., charger) access, and plug-in behavior as it can result in dozens of charging sessions per week for battery electric vehicles (BEVs) that in reality are often only plugged in a few times per week.

Array↗