Exploring the future energy-mobility nexus: The transportation energy & mobility pathway options (TEMPO) model
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Muratori, Matteo↗
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The Transportation Energy and Mobility Pathway Options (TEMPO) Model: Overview and Validation of V1.0 [Slides]
This presentation documents the approaches and methods used in the Transportation Energy & Mobility Pathway Options™ (TEMPO) model to evaluate passenger and freight demand for transportation and mobility services, project vehicle ownership and technology adoption decisions, and determine transport mode choices to derive scenarios of future energy use and emissions. TEMPO is an all-inclusive transportation demand model that covers the entire United States, with an implicit spatial resolution and an hourly temporal resolution that allows for generating time-resolved energy use profiles to assess multisectoral integration aspects. Key features of the TEMPO model include the ability to perform endogenous out-of-sample forecasting to extrapolate recent emerging trends and analyze impacts of disruptive technological breakthroughs and behavioral changes. TEMPO employs an innovative representation of passenger mobility demand stemming from household-level decisions that determine vehicle adoption, ownership, and use based on sociodemographics (e.g., income, household composition), technology attributes (e.g., travel cost, time), geography (e.g., urban, suburban, rural) and population-specific multiday mobility and travel requirements. This representation enables a more forward-looking perspective on the use of new mobility options and the adoption of alternative fuel vehicles, as well as a more accurate representation of their energy usage profiles than previous modeling approaches. A comparison with the U.S. Energy Information Administration’s Annual Energy Outlook showcases the ability of TEMPO to accurately replicate widely accepted projections by representing the key elements of the entire transportation sector at the appropriate level of resolution. TEMPO is intended to generate future scenarios of technology adoption, energy use, and emissions in the transportation sector to compare alternatives, inform decision makers, and assess integration with energy infrastructure and supply systems at an appropriate spatiotemporal resolution.
29 ENERGY PLANNING, POLICY, AND ECONOMY↗
Life Cycle Assessment for Closed-Loop Pumped Hydropower Energy Storage in the United States
The federal government has initiated an aggressive set of policies to achieve a net-zero carbon emission goal for the electricity sector by 2050. As a result, rapid growth in deployment of renewable energy technologies is expected. Most commercially mature technologies are temporally variable and do not provide grid inertia, while renewable technologies with high projected deployment have intermittent generation methods. Energy storage technologies are needed to both dispatch power on-demand and help provide the needed grid inertia. Pumped storage hydro (PSH) is a well-established technology that has gained renewed interest in recent years offering energy-balancing, grid stability, control of electrical network frequency, and large-scale storage capacity. For widespread adoption of PSH, more information is needed regarding its current life cycle environmental impacts. The objective of this study is to perform a full life cycle assessment (LCA) of new closed-loop PSH in the U.S. The functional unit for this study is 1 kWh of electrical power delivered to the grid and the base case project lifetime is 80 years. The life cycle inventory for this project accounts for all material and energy flows associated with the green-field construction, operation, maintenance, and decommissioning of a closed-loop PSH plant in the U.S. Collected data represents a range of potential PSH specifications and geographic locations coming from all prospective closed-loop PSH installations in the U.S. with data available. In addition, existing PSH installations are used to provide assumptions for inventory inputs. Results presented will include the global warming potential (GWP IPCC 100a) and Energy Return on Investment (EROI) from our base case (average PSH installation) as well as from scenario analyses and model sensitivity. These results will be compared to the impacts from existing PSH sites and alternate storage technologies. Methods align with the assumptions and guidelines put in place by previous PSH LCAs to ensure an accurate comparison with the results from this report.
ENERGY PLANNING, POLICY, AND ECONOMY,HYDRO ENERGY↗
How the Allocation of Lander Functions Impacts Human Lunar Exploration Architecture Propellant Demands
As NASA looks to the moon as a proving ground for the technologies required to conduct the first human exploration campaign of Mars, this study assesses the potential propellant demands that a sustained human lunar presence would require. In particular, this study evaluates how the allocation and distribution of vehicle functions to a different number of vehicles can impact the propellant required to conduct a human lunar exploration mission. Four different transportation architectures for human lunar exploration and three different refueling assumptions were defined. The impact on the propellant required for a mission was assessed for all architectures and refueling assumptions for ranges of crew payload mass, vehicle inert mass fraction, and a sensitivity to the mission maneuver velocity magnitudes. The results of this analysis show that aggregating vehicle functions to a single-stage lander vehicle can have a positive impact on the architecture's level of vehicle reusability and that an increase in the number of refueling opportunities reduces the mass of the vehicles and of the propellant required per mission.
Matteo A. Clark↗
Aviation Frontiers: On-Demand Aircraft
Throughout the 20th Century, NASA has defined the forefront of aeronautical technology, and the aviation industry owes much of its prosperity to this knowledge and technology. In recent decades, centralized aeronautics has become a mature discipline, which raises questions concerning the future aviation innovation frontiers. Three transformational aviation capabilities, bounded together by the development of a Free Flight airspace management system, have the potential to transform 21st Century society as profoundly as civil aviation transformed the 20th Century. These mobility breakthroughs will re-establish environmental sustainable centralized aviation, while opening up latent markets for civil distributed sensing and on-demand rural and regional transportation. Of these three transformations, on-demand aviation has the potential to have the largest market and productivity improvement to society. The information system revolution over the past 20 years shows that vehicles lead, and the interconnecting infrastructure to make them more effective follows; that is, unless on-demand aircraft are pioneered, a distributed Air Traffic Control system will likely never be established. There is no single technology long-pole that will enable on-demand vehicle solutions. However, fully digital aircraft that include electric propulsion has the potential to be a multi-disciplinary initiator of solid state technologies that can provide order of magnitude improvements in the ease of use, safety/reliability, community and environmental friendliness, and affordability.
Moore, Mark D.↗
High Temperature Devices for Aerospace Applications
This presentation will overview important new capabilities and benefits that next-generation higher temperature electronics promise for a variety of aerospace systems and missions. Initial aerospace infusions of higher temperature electronics to be discussed include jet engines and the prolonged robotic exploration of the Venus surface. Complete redesign of systems compared to prior conventional electronics practices would yield the most revolutionary benefits. However, the inherent higher risk and expense associated with new technology adoption will likely drive a more evolutionary technology infusion process, especially since flight qualification demands large safety margins and testing that ensures reliable operation for far longer than actual mission duration. SiC pn-junction based devices are inherently capable of the most durable operation at the highest application temperatures compared other transistor technologies, but such integrated circuits (ICs) will never achieve integration levels near today’s silicon ICs. Extreme temperature high-power devices will also be de-rated compared to room-temperature performance. While the high temperature market will always be small compared to the conventional temperature mass-market, compatibility and leveraging of existing foundry manufacturing is vital to the establishment of a sustainable high temperature electronics ecosystem sufficient to significantly improve aerospace systems.
High Temperature↗
Toward a life cycle approach for classifying the toxicity of refrigerants
Refrigeration and air conditioning currently account for ~20% of the total electricity consumption in buildings around the world (IEA, 2018). Over the next three decades, as global temperatures are projected to increase, urbanization and economic growth will lead to an increased demand for refrigeration and cooling. While technological advances have led to increased cooling capacity and safer refrigerants over the years, emissions from refrigeration systems can affect the environment by contributing to greenhouse gas emissions or by depleting the ozone layer, depending on the gas emitted. Further, because of ongoing and pending policy and regulatory changes to avert ozone depletion and global climate change, there is an increasing focus on adopting compounds that are efficient at cooling while also reducing emissions and other adverse environmental impacts.
54 ENVIRONMENTAL SCIENCES↗
ReSpike: A Co-Design Framework for Evaluating SNNs on ReRAM-Based Neuromorphic Processors
With Moore’s law approaching its end, traditional von Neumann architectures are struggling to keep up with the exceeding performance and memory requirements of artificial intelligence and machine learning algorithms. Unconventional computing approaches such as neuromorphic computing that leverage spiking neural networks (SNNs) to perform computation are gaining traction and seek the paradigm shift necessary to sustain the increasing demands of modern applications. Novel memory technologies, such as resistive RAM (ReRAM), employ a crossbar architecture that possesses the inherent capability of efficiently computing vector-matrix multiplication—a dominant operation in SNNs. The prospect of naturally mapping SNNs to the crossbar structures provides a unique opportunity for achieving a high-performance, power-efficient neuromorphic system. In this work, we present ReSpike, which is a new framework, behavioral simulator, and architectural design based on ReRAM crossbar architectures, enabling modeling and co-design to achieve efficient execution of SNNs. We drive this co-design forward by quantifying the impact that ReRAM cell nonidealities have on the corresponding accuracy of an SNN application.
Asifuzzaman, Kazi [ORNL] (ORCID:0000000240044791)↗
Accelerated screening of functional atomic impurities in halide perovskites using high-throughput computations and machine learning
The pressing need for novel materials that can serve rising demands in solar cell and optoelectronic technologies makes the nexus of halide perovskites, high-throughput computations, and machine learning, very promising. Ever increasing amounts of data on the structure, fundamental properties, and device performance of halide perovskites provide opportunities for learning chemical rules and design principles that make these materials attractive, and applying them across wide chemical spaces. In this work, we show that impurity properties of halide perovskites computed using density functional theory (DFT) can be combined with machine learning (ML) to deliver predictive models and quick identification of optoelectronically active impurity atoms. Our computation lead to the largest reported dataset of the formation energies and charge transition levels of Pb-site impurities in methylammonium lead halide (MAPbX 3 ) perovskites. Descriptors are defined to uniquely represent any impurity atom in any MAPbX 3 compound and mapped to the computed impurity properties using regression techniques such as Gaussian process regression, neural networks, and random forests. We use the best optimized predictive models to make predictions for hundreds of impurities across 9 MAPbX 3 compounds and create lists of dominating impurities, that is, impurities that can shift the equilibrium Fermi level in the perovskite as determined by native point defects. Finally, this accelerated screening powered by computations and machine learning can guide the identification of problematic impurities that may cause undesired recombination of charge carriers, as well as impurities that can be deliberately introduced to tune the perovskite conductivity and resulting photovoltaic absorption.
36 MATERIALS SCIENCE↗
Data-driven search for promising intercalating ions and layered materials for metal-ion batteries
The rise in demand for lithium-ion batteries has led to a large-scale search for electrode materials and intercalating ion species to meet the demands of next-generation energy technologies. Recent efforts largely focus on searching for cathodes that can accommodate large amounts of intercalating ions, but similar work on anodes is relatively limited. This study utilizes machine learning methods to find alternative two-dimensional (2D) materials and intercalating ions beyond Li for metal-ion batteries with high-power efficiencies. The approach first uses density functional theory (DFT) calculations to estimate the theoretical capacities and voltages of various metal ions on 2D materials. The DFT-generated data also provide insights into the local structural accommodation upon ion intercalation on various 2D materials. Significant changes to the lattice can result in irreversible changes to the bonding environments in the anode material, resulting in poor cycling stability. Next, this study develops a binding energy and structural accommodation-based classification model to screen anode materials for next-generation batteries. The classification model selects intercalating ions and 2D material pairs suitable for batteries based on the calculated voltage and volumetric changes in the 2D material upon intercalation. Finally, this study builds a regression model to accurately predict the binding energies of the various intercalating ions on 2D materials. The approach highlights the importance of different elemental and structural features for classification and regression tasks. In conclusion, the insights gained from this study on the role of involved features, such as electronegativities of the constituent ions and the presence of unfilled electronic levels, will help to streamline further studies towards the search for future layered battery materials.
36 MATERIALS SCIENCE↗
Project developer options to enhance the value of solar electricity as solar and storage penetrations increase
Increasing the penetration of photovoltaics (PV) reduces the marginal grid value of PV electricity. The declining grid value of PV with higher penetration could limit the technology's economic attractiveness and future demand. Various strategies have been proposed for preserving this value. Using a consistent framework, we analyze the net value (accounting for both cost and grid value) of more than ten strategies in the United States. Here, grid value is estimated from coincident wholesale power market prices and PV generation using observed historical prices or modeled future prices with up to 30% PV penetration. We find that established and emerging strategies designed to shift the timing of standalone PV generation at the expense of total generation—including orienting monofacial PV modules west or bifacial modules vertically—result in minor net-value benefits or penalties. Adding energy storage to such systems magnifies the net-value loss, because configurations that change the timing of PV production become redundant when the energy-shifting capabilities of storage are added. The largest net-value gains come from strategies that maximize generation (solar tracking plus oversized PV arrays) in conjunction with storage, especially at high PV penetrations. PV systems are long-lived assets. Our results suggest that efforts to promote generation-maximizing strategies today may yield increasing net-value benefits as PV and storage deployments continue to accelerate in the United States over the coming decades.
14 SOLAR ENERGY↗
A framework and calculator for evaluating the impacts of shelf life extension and other food loss and waste reduction technologies
Optimization of the food supply chain (FSC) depends on reducing food waste, especially at the consumer stage, where a substantial portion of food is not eaten, but instead disposed of via landfill, incineration, or in-sink disposals. One key strategy is to increase the time that consumers have before food goes bad or expires. This study developed a framework to assess the efficacy of shelf-life extension (SLE) technologies for mitigating food loss and waste (FLW), such as packaging improvements. The impact flows through the entire FSC, reducing FLW, energy use, and other inputs at each stage. The framework and resulting calculator can be used to evaluate the impact of FLW reduction at any stage for any food commodity. As shown by two SLE cases, the calculator is valuable for policy-makers, government entities, and professionals, specifically those in marketing, business development, and capital projects teams, to comprehensively evaluate the impacts of FLW reduction technologies and practices. The framework and calculator are sensitive to the shape of the consumption curve, the fraction of inedible waste, and the current shelf life. The calculator was used to assess the impacts of the United States goal of reducing food waste by consumers through various SLE lengths. It was found that uptake of several near-ready-to-deploy SLE technologies would reduce annual food production demand by about 10–19 MMT and supply chain energy consumption by 240–410 PJ in the United States.
Food loss and waste (FLW)↗
Adsorption of rare earth elements in carboxylated mesoporous carbon
The separation of Rare Earth Elements (REEs) from various non-conventional sources is critically important to maintain the supply–demand balance of REEs in the western world. Here, in this research, we have investigated coal Fly Ash (CFA) as the non-conventional source of REEs. In order to recover REEs, we have synthesized carboxylate-functionalized mesoporous carbon (CMC) to harness the chelation-induced adsorption of REEs. These adsorbents were characterized with pore textural properties, FTIR spectroscopy, and SEM-EDX mapping. In the initial study with single-component La(III) Dy(III) and Lu(III), it was revealed that CMC can adsorb those REEs 2–4 times more than that of pristine mesoporous carbon confirming the effective role of the carboxylate group in the REE separation. Furthermore, the affiliation of the carboxylate group towards heavier REEs (Lu>Dy>La, when present is equal amounts) provides an added benefit of this adsorbent owing to the high demand for heavier REEs in the technology sectors. The leachate solution produced from CFA contained sixteen REEs in the range of 50–200 ppb for most of the REEs. It was revealed that CMC can extract 80–90% of all the REEs thereby further confirming the success of the CMC as an effective REE sorbent. Three successive cycles of adsorption and desorption of REEs with the same CMC revealed the consistent adsorption capacity of REEs. In-situ X-ray Absorption Near Edge Spectroscopy (XANES) analysis confirmed the +3 oxidation states of La, Dy, and Lu within CMC. In-situ Extended X-ray Absorption Fine Structure (EXAFS) analysis revealed the shortening of mean La-O, Dy-O, and Lu-O bond distance by 0.03–0.05 Å thereby confirming the coordination of these REEs with carboxylate groups present on CMC.
36 MATERIALS SCIENCE↗
Influence of the Anionic Zinc-Adeninate Metal–Organic Framework Structure on the Luminescent Detection of Rare Earth Ions in Aqueous Streams
Rare earth elements (REEs) are critical to numerous technologies; however, a combination of increasing demand, environmental concerns, and monopolistic marketplace conditions has spurred interest in boosting the domestic REE production from sources such as coal utilization byproducts. The economic viability of this approach requires rapid, inexpensive, and sensitive analytical techniques capable of characterizing the REE content during resource exploration and downstream REE processing (e.g., analyzing REE separation, concentration, and purification production steps). Luminescence-based sensors are attractive because many REEs may be sensitized to produce element-specific emission. Hence, a single material may simultaneously detect and distinguish multiple REEs. Metal–organic frameworks (MOFs) can sensitize multiple REEs, but their viability has been hindered by sensitivity and selectivity challenges. Understanding how the MOF structure impacts the REE sensing efficacy is critical to the rational design of new sensors. Here, we evaluate the sensing performance of seven different anionic zinc-adeninate MOFs with different organic linkers and/or structures for the visible-emitting REEs Tb, Dy, Sm, and Eu. The choice of a linker determines which REEs are sensitized and significantly influences their sensitivity and selectivity against competing species (here, Fe(II) and HCl). For a given linker, structural changes to the MOF can further fine-tune the performance. The MOFs produce some of the lowest detection limits (sub-10 ppb for Tb) reported for the aqueous sensitization-based REE detection. Importantly, the most selective MOFs demonstrated the ability to sensitize the REE signal at sub-ppm levels in a REE-spiked acid mine drainage matrix, highlighting their potential for use in real-world sensing applications.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
In situ visualization of multicomponents coevolution in a battery pouch cell
Lithium-ion battery (LIB) is a broadly adopted technology for energy storage. With increasing demands to improve the rate capability, cyclability, energy density, safety, and cost efficiency, it is crucial to establish an in-depth understanding of the detailed structural evolution and cell-degradation mechanisms during battery operation. Here, we present a laboratory-based high-resolution and high-throughput X-ray micro–computed laminography approach, which is capable of in situ visualizing of an industry-relevant lithium-ion (Li-ion) pouch cell with superior detection fidelity, resolution, and reliability. This technique enables imaging of the pouch cell at a spatial resolution of 0.5 μm in a laboratory system and permits the identification of submicron features within cathode and anode electrodes. We also demonstrate direct visualization of the lithium plating in the imaged pouch cell, which is an important phenomenon relevant to battery fast charging and low-temperature cycling. Our development presents an avenue toward a thorough understanding of the correlation among multiscale structures, chemomechanical degradation, and electrochemical behavior of industry-scale battery pouch cells.
25 ENERGY STORAGE↗
Critical-Element-Free Permanent-Magnet Materials Based on Ce 2 Fe 14 B
Developing a critical-element-free low-cost permanent magnet is an urgent necessity in view of rapidly developing technologies and the associated huge market demand for Nd 2 Fe 14 B-based magnets. Here, inspired by the abundant and low-cost nature of Ce and these high-performance Nd 2 Fe 14 B permanent magnets, we explore whether it is in fact possible to attain a useful performance in alloys based on the sister material Ce 2 Fe 14 B, employing both experimental and theoretical efforts. Experimentally, we study Ce 2 Fe 14 B with Co, La, and Zr substitutions. The Zr substitution is explored in view of Zr’s frequent role in enhancing magnetic anisotropy in permanent magnets, while the Co and La substitutions serve to remedy the too-low Curie point of 433 K in the base alloy. While we find no Zr-related anisotropy enhancement either experimentally or theoretically, the cosubstitution of La and Co indeed improves the Curie temperature as well as the magnetization, M s , with a potential energy product as high as 38 MG Oe. These properties together suggest optimization of the alloy LaCeFe 12.7 Co 1.3 B (with only 7 wt % cobalt) as a critical-element-free permanent magnet. While the substituted elements do not enhance magnetic anisotropy, from theory, we find a substantial increase, to a first anisotropy constant, K1, as high as 4.24 MJ/m 3 , associated with Bi substitution for Ce. In this paper, our experimental and theoretical results demonstrate the great potential of La, Co, and Bi substitutions in developing low-cost and critical-element-free Ce 2 Fe 14 B-based permanent magnets.
36 MATERIALS SCIENCE↗
Silicon Carbide Inverter for Off-Road Heavy-Duty Applications: The Importance of Thermal and Thermomechanical Design in Power Electronics Packaging
Electrification of drivetrain systems is now seen as a major opportunity by the transportation industry across the globe to reduce the greenhouse gas emissions and revolutionize the travel patterns of millions of people. The cumulative number of plug-in hybrid and battery electric vehicles (EVs) sold in the United States has now surpassed 2 million in 2021, according to the International Energy Agency. The introduction of EVs in different classes of passenger vehicles and the continued drop in prices spurred by government incentives have attracted the attention of consumers despite certain barriers, such as higher initial cost and range anxiety. In the United States, the EV market share is now growing at an exponential pace, with the domestic automakers allocating a lion's share of new and future car sales to EVs. Additionally, different market studies project decreasing cost and rising sales of medium- and heavy-duty electric trucks. Although electrification initiatives are strongly pursued in the on-road passenger vehicle market, off-highway sectors, such as construction, mining, and agriculture, are also gradually implementing electric drivetrain technologies in their machineries. As EVs grow in popularity on a global scale, innovative drivetrain technologies must meet the increasing energy demand by significantly increasing system efficiency.
ADVANCED PROPULSION SYSTEMS↗
BSM (Bioenergy Scenario Model) 2023 FKA: Biomass Scenario Model [SWR-09-09]
The U.S. Department of Energy's (DOE's) Bioenergy Technologies Office and the National Renewable Energy Laboratory (NREL) developed the BSM (Bioenergy Scenario model) to explore the development of a U.S. biofuels industry. The BSM is a system dynamics model built on the STELLA software platform. The model represents the dynamic interactions of the major sectors of the biofuels industry—feedstock production, feedstock logistics, biomass to biofuels conversion, and biofuels end use, including fuels inventory, dispensing, distribution, fuel use, and the vehicle fleet. The BSM represents contextual aspects of the developing biofuels industry, including investment in new biomass to biofuel conversion technologies, competition from petroleum fuels, vehicle demand for biofuels, and various government policies, using all of these to simulate the development of the industry. The purpose of the BSM is to generate and explore plausible scenarios for the evolution of a biofuels industry in the United States, and as a high-level system model it is not designed for precise, quantitative forecasting. Instead, it is best used to (1) analyze and evaluate alternate policies; (2) generate scenarios; (3) identify high-impact levers and bottlenecks to system evolution; and (4) seed focused discussion among policymakers, analysts, and stakeholders.
Bush, Brian↗