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At least 793 records · Page 44

Design principles of heterointerfacial redox chemistry for highly reversible lithium metal anode

High electrochemical reversibility is required for the application of high-energy-density lithium (Li) metal batteries; however, inactive Li formation and SEI (solid electrolyte interface)-instability-induced electrolyte consumption cause low Coulombic efficiency (CE). The prior interfacial chemical designs in terms of alloying kinetics have been used to enhance the CE of Li metal anode; however, the role of its redox chemistry at heterointerfaces remains a mystery. Herein, the relationship between heterointerfacial redox chemistry and electrochemical transformation reversibility is investigated. It is demonstrated that the lower redox potential at heterointerface contributes to higher CE, and this enhancement in CE is primarily due to the regulation of redox chemistry to Li deposition behavior rather than the formation of SEI films. Low oxidation potential facilitates the formation of the surface with the highly electrochemical binding feature after Li stripping, and low reduction potential can maintain binding ability well during subsequent Li plating, both of which homogenize Li deposition and thus optimize CE. In particular, Mg hetero-metal with ultra-low redox potential enables Li metal anode with significantly improved CE (99.6%) and stable cycle life for 700 cycles at 3.0 mA cm -2 . This work provides insight into the heterointerfacial design principle of next-generation negative electrodes for highly reversible metal batteries.

25 ENERGY STORAGE↗

Electrification Futures Study: Scenarios of Power System Evolution and Infrastructure Development for the United States

This report is one in a series of Electrification Futures Study (EFS) publications. The EFS is a multiyear research project to explore potential widespread electrification in the future energy system of the United States. Electrification is defined as the substitution of electricity for direct combustion of non-electricity-based fuels used to provide similar services. The EFS is specifically designed to examine electric technology advancement and adoption for end uses in the major economic sectors of the United States, electricity consumption growth and load profiles, future power system infrastructure development and operations, and economic and environmental implications of electrification. Because of the expansive scope and the multiyear duration of the study, research findings and supporting data will be published as a series of reports, with each report being released on its own time frame.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Enhanced thermal reliability and performance of calcium chloride hexahydrate phase change material using cellulose nanofibril and graphene nanoplatelet

In recent years, thermal energy storage (TES) has gained attention for its role in enhancing renewable energy solutions and sustainable energy consumption. The usage of strontium chloride hexahydrate (SCH), graphene nanoplatelet (GNP), and cellulose nanofibril (CNF) additives were investigated to enhance the performance of calcium chloride hexahydrate (CCH) based on the melting/solidification behavior for TES applications. In this work, we develop a promising phase-change-material (PCM) formulation by introducing these additives that reduce supercooling, improve the thermal conductivity and stabilizing the energy storage capacity of CCH. Rheological characterizations demonstrated that the addition of 1 wt% of CNF into CCH produced the required improvement in viscosity and boosted solid-like rheological behavior. Structural characterizations show a physical mixing of the materials within the PCM composites. Our observations show that the amphiphilicity of CNF enables the surface attachment to GNP via hydrophobic interactions providing effective dispersion of GNP throughout the PCM composite. The addition of a nucleating agent, SCH decreased the degree of supercooling of ~20 g of CCH from >20 °C to 3 °C at a cooling rate of 5 °C/min. Thermal characterization showed the resulting PCM composite has a latent heat of melting of 186 Jg -1 , phase change temperature of 32 °C, and stable thermal properties after being subjected to 70 melt-freeze cycles. Adding CNF and GNP to pure CCH increased its thermal conductivity by 76 %. The high thermal conductivity of GNP and its effective dispersion by CNF is responsible for this enhancement. The study highlights the use of biodegradable nanocellulose for the preparation of sustainable PCM composites with improved performance. In conclusion, these PCM composites are scalable, they have potential to increase energy efficiency and revolutionalize the heating/cooling applications in buildings and other TES systems.

25 ENERGY STORAGE↗

Enhancing flexibility for climate change using seasonal energy storage (aquifer thermal energy storage) in distributed energy systems

Long-term energy storage is expected to play a vital role in the deep decarbonization of building energy sectors, while enhancing the flexibility of buildings to withstand future climate variations. However, it is challenging to design distributed multi-energy systems (DMES) while taking into account the uncertainties introduced by climate change, since stochastic optimization of such systems is difficult. The present study introduces a stochastic optimization model to address this bottleneck, taking into account DMES including aquifer thermal energy storage (ATES) as the long-term thermal storage. For the first time, a novel optimization algorithm links ATES with the DMES optimization model with the support of a simplified geotechnical model. Subsequently, a case study was conducted, focusing on a residential district in Chicago where the impact of future climate condition, energy demand, and solar and wind energy potentials were evaluated using Weather Research and Forecasting (WRF) data (up to 2080) and the EnergyPlus model. The study revealed that ATES is an attractive way to improve the renewable energy penetration level and minimize the dependence on fossil fuels with reasonable support from the grid to assist the fluctuations in both demand and generation. Furthermore, ATES notably reduces fuel consumption and dependence while greatly enhancing the flexibility of the energy system to withstand fluctuations in demand and renewable energy generation brought by future climate variations. These qualities will make ATES an important part of distributed energy systems, even though it is not currently the lowest cost alternative due to lack of technology maturity. Furthermore, the design platform introduced in the present study can be used to design DMES enhancing flexibility to accommodate future climate variations.

25 ENERGY STORAGE↗

Depolymerization of Hydroxylated Polymers via Light-Driven C–C Bond Cleavage

The accumulation of persistent plastic waste in the environment is widely recognized as an ecological crisis. New chemical technologies are necessary both to recycle existing plastic waste streams into high-value chemical feedstocks and to develop next-generation materials that are degradable by design. Here, we report a catalytic methodology for the depolymerization of a commercial phenoxy resin and high molecular weight hydroxylated polyolefin derivatives upon visible light irradiation near ambient temperature. Proton-coupled electron transfer (PCET) activation of hydroxyl groups periodically spaced along the polymer backbone furnishes reactive alkoxy radicals that promote chain fragmentation through C–C bond β-scission. The depolymerization produces well-defined and isolable product mixtures that are readily diversified to polycondensation monomers. In addition to controlling depolymerization, the hydroxyl group modulates the thermomechanical properties of these polyolefin derivatives, yielding materials with diverse properties. Furthermore, these results demonstrate a new approach to polymer recycling based on light-driven C–C bond cleavage that has the potential to establish new links within a circular polymer economy and influence the development of new degradable-by-design polyolefin materials.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Dual Impacts of Space Heating Electrification and Climate Change Increase Uncertainties in Peak Load Behavior and Grid Capacity Requirements in Texas

Around 60% of households in Texas currently rely on electricity for space heating. As decarbonization efforts increase, non‐electrified households could adopt electric heat pumps, significantly increasing peak (highest) electricity demand in winter. Simultaneously, anthropogenic climate change is expected to increase temperatures, the potential for summer heat waves, and associated electricity demand for cooling. Uncertainty regarding the timing and magnitude of these concurrent changes raises questions about how they will jointly affect the seasonality of peak demand, firm capacity requirements, and grid reliability. This study investigates the net effects of residential space heating electrification and climate change on long‐term demand patterns and load shedding potential, using climate change projections, a predictive load model, and a direct current optimal power flow (DCOPF) model of the Texas grid. Results show that full electrification of residential space heating by replacing existing fossil fuel use with higher efficiency heat pumps could significantly improve reliability under hotter futures. Less efficient heat pumps may result in more severe winter peaking events and increased reliability risks. As heating electrification intensifies, system planners will need to balance the potential for greater resource adequacy risk caused by shifts in seasonal peaking behavior alongside the benefits (improved efficiency and reductions in emissions).

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Optimization of a Mixed Fleet of Aerial Drones for Medical Supplies: A Case Study of Blood Delivery Logistics

Aerial drones have emerged as an innovative solution for faster transportation of time-sensitive items (e.g., emergency medical supplies), potentially reducing the transmission of contagious diseases and enhancing healthcare availability through contactless autonomous delivery. We study fleet sizing and efficient scheduling of a mixed fleet of drones for delivering time-sensitive medical items having distinct release and due times to minimize the required fleet size and fleet composition, the required number of additional batteries, and the total energy consumption. We continuously track the remaining battery energy of drones to determine the optimal timing for battery replacement, rather than replacing the battery at each node. Using actual drone flight test data, we employed a machine learning (ML) method to estimate the energy consumption of different drone types during flight segments for different operating parameters. We present a novel mixed-integer programming model to efficiently formulate the problem that integrates the estimated energy consumption functions from ML. We propose a new greedy heuristic (GH) algorithm and a customized genetic algorithm (GA) for solving large-scale instances of this problem faster. Results demonstrate that the GH algorithm is substantially faster than the accelerated CPLEX and the GA, while sacrificing the solution quality by a small amount. Results based on an actual blood sample delivery case study from Pendleton, Oregon, United States, show that using a mixed fleet of drones reduces the total cost and total energy consumption up to 18.18% and 28.7%, respectively, compared to using a homogeneous fleet.

29 - ENERGY PLANNING, POLICY AND ECONOMY↗

Evaluation of Thin Triple-Pane Windows in the PNNL Lab Homes

In recent years, improvements in glass manufacturing have allowed the production of thin triple-pane windows, which are manufactured with a thickness similar to standard double-pane windows. Because this highly insulating “thin triple” glass product can be incorporated into almost any existing window frame and can be fabricated at a modest added cost, the U.S. Department of Energy is sponsoring laboratory and field demonstration testing of thin triple-pane windows to validate thermal performance and installation requirements in real-life field settings. To examine the performance of thin triple-pane windows, the Pacific Northwest National Laboratory (PNNL) evaluated the windows at the PNNL Lab Homes, a matched pair of homes located on PNNL’s campus in Richland, Washington. In this study, one Lab Home contained a complete set of nine thin triple-pane windows, while the other Lab Home contained baseline double-pane windows. The Lab Homes experiments demonstrated significant that replacing clear glass double-pane windows with thin triple-pane windows provided year-round energy savings and reduced peak demand both in the heating and cooling seasons. The Lab Homes experiments also validated other performance benefits of the thin triple-pane windows including reduced condensation potential, more even temperatures throughout the home and near the windows, and reduced sound attenuation through the windows, leaving the home quieter and more comfortable for the occupants.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Electric-Field De-Wetting for Enhanced Drying

Drying processes are one of the most energy intensive operations. Drying accounts for anywhere from 12 to 20% of the energy consumption in the industrial sector. While many different drying processes and thus technologies exist and each is appropriate for particular applications, convective heated-air dryers account for about 85% of all industrial dryers, where air is heated by the combustion of fossil fuels prior to being forced through the product. The electric-field dewetting concept evaluated has the potential to increase heat pumping efficiency by 30% assuming a typical sensible heat ratio of 70%. At full deployment, this can reduce drying energy by 25%. Further, the technology can benefit the performance of air-source heat pumps in general and broaden their application base resulting in greater energy reductions.

42 ENGINEERING↗

Assessment of Commercial Building Lighting as a Frequency Regulation Resource

This paper evaluates the potential for automated lighting control as a resource for frequency regulation of the electric grid system in the context of current energy policies, economic incentives, and technological trends. The growing prevalence of renewable energy has increased the need for ancillary services to maintain grid frequency and stability. While demand side resources like heating, ventilating, and air-conditioning systems, as well as water treatment plants are already evaluated as regulation service providers, the potential application to electrical lighting systems has largely been ignored. Yet, aggregations of lighting systems that are retrofitted with intelligent controls could conceivably contribute to frequency regulation services with little impact on user comfort. To further explore the feasibility of lighting potential, this paper explores (1) how lighting control systems are limited by visual comfort perception and acceptability, (2) how such limitations impact the performance of the lighting system as an frequency regulation resource, and (3) how the market potential of lighting systems as demand side resources compares in different regional transmission organizations. Finally, the impact of developing technologies on the application of lighting systems for frequency regulation is discussed.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Pulsed Electric Field Processing of Apples

Pulsed electric field (PEF) processing is a nonthermal technology that has the potential to improve the efficiency of apple processing, particularly for firm cultivars that are growing in popularity. This study evaluated the effects of PEF pretreatment on the processability and product quality of Cosmic Crisp apples, a modern cultivar known for its firmness. Apples were treated with PEF and assessed for tissue softening, mechanical energy requirements, particle size reduction, browning tendencies, and juice yield. PEF treatment significantly softened the apple tissue, as demonstrated by reduced compression forces in Instron testing, and this softening translated to decreased grinding energy during applesauce production. There were no changes to the particle size distribution of the resulting applesauce. PEF treatment also altered browning behavior and produced higher juice yields following mechanical disruption, suggesting enhanced membrane permeability and mass transfer. Together, these results show that PEF pretreatment can reduce mechanical energy demands and increase extractability without reducing product quality in firm apple varieties. These outcomes highlight the potential of PEF to increase the value recovered from processing-grade apples and to support more efficient and sustainable apple processing operations.

32 - ENERGY CONSERVATION, CONSUMPTION, AND UTILIZA↗

Review of heat transfer enhancement techniques in two-phase flows for highly efficient and sustainable cooling

We show that two-phase internal flow is ubiquitous to many systems due to its ability to transfer large amounts of heat effectively. Recent advances motivated by sustainability have pushed towards augmenting the heat transfer between the tube and the two-phase working fluid. Augmenting heat transfer in two-phase flows enables process intensification, and compactness leading to reduced cost and material consumption. This review investigates the effect of heat transfer enhancement techniques on different fluids including R134a, R407C, R22, etc … The techniques are categorized into passive and active and focus on durable enhancement methods which do not include surface structuring or coating. Passive techniques utilize geometrical and surface modifications to induce better mixing. Several passive techniques are analyzed including fins, inserts, and more. In analyzing these techniques, the effect of changing geometric parameters is studied, and the limitations are highlighted. Further, active techniques that enable heat transfer enhancement through applying power are also investigated. Electrohydrodynamic approaches are analyzed and compared to passive techniques. Additionally, the implications of heat exchange enhancement in the context of global energy are discussed. An energy analysis discretized by the use sector is conducted, with an emphasis on predicting the future potential for renewable and sustainable development. Moreover, although active approaches provide the highest heat transfer enhancement, due to implementation difficulties, passive techniques are more frequently adopted. The review ends with discussion of next-generation heat exchangers which will rely more on additive manufacturing due to its flexibility and reduced cost per part as the technology matures.

Nusselt number↗

AutonomieAI: An efficient and deployable vehicle energy consumption estimation toolkit

Here, this paper presents AutonomieAI, a novel toolkit designed for efficient energy estimation of vehicles across diverse trip scenarios, routes, and drive cycles, applicable to a broad range of vehicle powertrain technologies. It leverages state-of-the-art Machine Learning techniques to deliver real-time energy prediction of vehicles, enabling co-simulation with transportation level system tools and opening doors for large-scale optimization at city, network or national level. Benchmark results show that AutonomieAI achieves high accuracy, with an average percentage error below 2% for most powertrain types, and computational efficiency capable of processing over 10,000 trips per second. Applications of AutonomieAI have potential to offer the flexibility to assist in solving eco-routing problems, optimize for vehicle and powertrain selection, study charging decision behavior, and optimize for charging station placement. AutonomieAI is the result of large neural network based model architectures, trained on very large and unique high fidelity vehicle simulation data. It is lightweight, deployable, efficient and has accuracy comparable to specialized and complex physics based simulation softwares.

Autonomie↗

Ecologically inspired metrics for transitioning to a sustainable and resilient circular economy with application to multilayer plastic films

Current Circular Economy (CE) frameworks applied to product chains exhibit notable shortcomings. These include neglecting the resilience and robustness of design, requiring detailed economic and environmental data for impact assessment, and relying on qualitative rather than quantitative metrics capturing certain CE design aspects. In the current contribution, we addressed these shortcomings by developing an Ecologically inspired (Eco-inspired) Framework using the mathematical foundations of Ecological Network Analysis (ENA). While ENA metrics have previously found application in designing circular economies, particularly in Industrial Symbiosis (IS) networks, our adaptation tailors these metrics for use in product-level CE, recognizing the inherent distinctions between product-level CE and IS. Our Eco-inspired Framework comprises three key categories to provide holistic and granular-level metrics for designing product-level CE. The first set of metrics assesses circularity and resource efficiency. The second set gauges network intensity and robustness as complementary indicators ensuring a CE is both sustainable and resilient. The third group of metrics evaluates enhancement potential of CE strategies through introducing quantitative metrics for measuring the degree of closed-loop strategies and average circularity level of a CE design. The three comprehensive set of indicators within the Eco-inspired Framework uniquely captures various facets of circular design, whether originating from technological innovations and recovery improvement at the end of life (EoL), shifts in human consumption patterns, alterations in product design, or changes in business models. The framework’s application is tested in designing a CE for multilayer Polyethylene-Polyamide (PE-PA) films. Using the Eco-inspired Framework, we identified the best strategy for designing a resilient and sustainable CE for PE-PA films. A diverse set of EoL strategies along with a reduction in product consumption can improve circularity and resilience by 650% and 255%, respectively, and mitigate greenhouse gas emissions by 90%. The framework minimizes trade-offs between sustainability and circularity goals and offers insights on how to enhance each strategy for achieving a resilient and sustainable CE for products.

54 ENVIRONMENTAL SCIENCES↗

Model-Based Energy and Cost Analysis of Direct Air Capture Using ePTFE-Based Laminate-Structured Gas–Solid Contactors

Carbon dioxide removal (CDR) technologies will play a significant role in limiting global warming if implemented on a large scale. Direct air capture (DAC) is a scalable approach for removing atmospheric carbon, yet the true scope of its scalability remains unclear due to the early stage of technology development and high first plant costs. This study provides groundwork for understanding the technoeconomic trade-offs in developing DAC systems using laminate-structured gas–solid contactors, encompassing the analysis of both contactor and process design spaces. The robust mass transfer and process models outlined in this study provide tools for evaluating DAC processes and designing DAC plants based on cost and energy analysis. First, the key contactor geometrical parameters are identified to understand the CO 2 productivity–energy demand trade-offs, where geometries yielding higher mass transfer rates can achieve higher CO 2 productivities at the expense of energy consumption by fans and steam use. Next, a detailed process parametric study is conducted for DAC systems coupled with steam-assisted temperature-vacuum swing adsorption (S-TVSA) to visualize the trade-offs in the multidimensional design space. The main cost driver dramatically changes over different process conditions, but the operating cost prevailed on the Pareto front, with potential to operate as low as 150 $/tonne-CO 2 (within the cost range of 148–504 $/tonne-CO 2 in this study where the DAC system is coupled with industrial facilities for steam production).

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Paintable Heat-Reflective Coatings for Low-Cost Energy Efficient Windows

The major objective of this effort is to manufacture a paintable coating to inexpensively retrofit energy-inefficient windows with a heat-reflective, visibly transparent film. This coating will drastically reduce cooling costs for millions of homes and buildings and lower the Nation’s greenhouse gas emissions. Widespread implementation could reduce the national consumption of electricity for cooling by billions of kWh, saving billions of dollars per year. This improved energy efficiency would decrease CO2 emissions by billions kg per year, the equivalent to removing millions of cars from the road. Although near-IR reflective adhesive films are commercially available products and have demonstrated significant energy efficiency enhancement, high upfront costs largely deter potential consumers across all sectors. The technology developed under this award was proposed to disrupt the building envelope market, by providing an inexpensive coating that can be directly applied by consumers to improve the energy efficiency of virtually all window types. The proof of concept for a paintable, DIY applicable, visibly transparent, and infrared reflective coating was achieved, laying the foundation for future technology development in this area.

14 SOLAR ENERGY↗

Efficient human activity recognition with spatio-temporal spiking neural networks

In this study, we explore Human Activity Recognition (HAR), a task that aims to predict individuals' daily activities utilizing time series data obtained from wearable sensors for health-related applications. Although recent research has predominantly employed end-to-end Artificial Neural Networks (ANNs) for feature extraction and classification in HAR, these approaches impose a substantial computational load on wearable devices and exhibit limitations in temporal feature extraction due to their activation functions. To address these challenges, we propose the application of Spiking Neural Networks (SNNs), an architecture inspired by the characteristics of biological neurons, to HAR tasks. SNNs accumulate input activation as presynaptic potential charges and generate a binary spike upon surpassing a predetermined threshold. This unique property facilitates spatio-temporal feature extraction and confers the advantage of low-power computation attributable to binary spikes. We conduct rigorous experiments on three distinct HAR datasets using SNNs, demonstrating that our approach attains competitive or superior performance relative to ANNs, while concurrently reducing energy consumption by up to 94%.

60 APPLIED LIFE SCIENCES↗