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At least 73 records · Page 4

Efficient backward x-ray emission in a finite-length plasma irradiated by a laser pulse of picosecond duration

Motivated by experiments employing picosecond-long, kilojoule laser pulses, we examined x-ray emission in a finite-length underdense plasma irradiated by such a pulse using two-dimensional particle-in-cell simulations. We found that, in addition to the expected forward emission, the plasma also efficiently emits in the backward direction. Our simulations reveal that the backward emission occurs when the laser exits the plasma. The longitudinal plasma electric field generated by the laser at the density down-ramp turns around some of the laser-accelerated electrons and re-accelerates them in the backward direction. As the electrons collide with the laser, they emit hard x rays. The energy conversion efficiency is comparable to that for the forward emission, but the effective source size is smaller. We show that the picosecond laser duration is required for achieving a spatial overlap between the laser and the backward energetic electrons. At peak laser intensity of 1.4×1020 W/cm2, backward-emitted photons (energies above 100 keV and 10° divergence angle) account for 2×10−5 of the incident laser energy. This conversion efficiency is three times higher than that for similarly selected forward-emitted photons. The source size of the backward photons (5 μm) is three times smaller than the source size of the forward photons.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY

The DREAM approach to demand-side emissions reductions in Indonesia, 2020–2060

Indonesia’s current energy system modeling is heavily focused on the supply side, but emissions reductions in the demand sector have a significant impact on advancing Indonesia’s ambitious emissions reductions goals. To address the gap, we develop a new modeling tool DREAM Indonesia based on a bottom-up, technology-rich demand side framework and formulate projections of demand-side emissions reductions in Indonesia in 2020–2060. We find that demand-side energy efficiency and electrification can halve the growth rate of final energy demand to 1.4% annually over 2020–2060 and reverse the growing trend of emissions. The feasibility of full electrification by 2060, coupled with rapid adoption of existing technologies, positions the building sector as a model for achievable decarbonization and a cornerstone of Indonesia’s emissions reductions ambitions. In the industrial sector, extensive emissions reductions of 87% by 2060 (compared to business-as-usual) are achievable through energy efficiency improvements, alongside enhanced material efficiency measures including optimized material usage, low-carbon substitutions, innovative technologies, and increased circularity. In the transportation sector, balancing final energy demand by incorporating energy efficiency improvements across all transport modes, along with electrification particularly in road transportation, could decrease the emissions by up to 82% in 2060 compared to business-as-usual. This study provides insights and modeling approaches for rapidly growing Asian economies as well as other developing countries facing combined development and decarbonization challenges.

DREAM Indonesia

2024 Annual Merit Review - Vehicle Technologies Office: Results Report

The 2024 U.S. Department of Energy (DOE), Office of Energy Efficiency and Renewable Energy’s (EERE) Vehicle Technologies Office (VTO) Annual Merit Review (AMR) was held June 3-6, 2024, in Arlington, Virginia. The review encompassed work done by VTO: 226 individual activities were reviewed by 218 reviewers. Exactly 888 individual review responses were received for the VTO technical reviews. Each project was reviewed by 2–7 independent reviewers, with a majority of projects having 4–5 reviewers. The objective of the meeting was to review the accomplishments and plans for VTO over the previous 12 months, and provide an opportunity for industry, government, and academia to give inputs to DOE with a structured and formal methodology. The meeting also provided attendees with a forum for interaction and technology information transfer.

33 ADVANCED PROPULSION SYSTEMS

Breakthrough Zn(II) Catalyst for Direct Air Capture Employing CO 2 Hydration

Direct air capture (DAC) represents a vital technology for atmospheric CO₂ remediation, but few studies have tested catalysts at dilute atmospheric CO₂ concentrations. Inspired by the carbonic anhydrase metalloenzyme, we report a catalytic DAC strategy employing robust zinc(II) enzyme mimics that enable efficient CO₂ sequestration pathways. A catalyst-mediated CO₂ hydration cycle in aqueous sorbents facilitates accelerated capture from dilute atmospheric air, thereby addressing the kinetic limitations observed in carbonate-based systems. Our developed complexes [ZnC1] and [ZnC2] enhance capture rates up to two-fold at millimolar concentrations and improve CO₂ mass transfer by 40-60% in 1 M K₂CO₃ sorbent under ambient conditions. These bench-stable, earth-abundant zinc catalysts operate effectively under dilute CO₂ concentrations, overcoming the kinetic limitations of conventional carbonate-based sorbents. As a result, mechanistic studies support a biomimetic catalytic cycle that facilitates rapid CO₂ conversion, demonstrating that catalyst-assisted DAC can enable energy-efficient, scalable carbon capture technologies.

Atmospheric chemistry

Human Factors and Technologies Design to Improve User Acceptance of Pooled Rideshare for Increasing Transportation System Energy Efficiency

This multi-year project delivered a comprehensive, human-factors-driven framework to understand, model, and improve pooled rideshare (PR) adoption in the United States. Through three large-scale national survey studies involving more than 16,000 participants across multiple cities and demographic groups, the research established one of the most extensive datasets to date on user perceptions, behavioral barriers, and service expectations related to pooled rideshare. These data revealed key human factors barriers of user acceptance of PR and suggested potential actionable experience optimizations that could lead to increased PR usage. This foundational knowledge guided the development of novel human-factors models and behavioral choice models that quantify how psychological, demographic, and trip-level factors influence willingness to pool. Building on these empirical insights, the project developed advanced behavioral modeling tools, including mixed logit and integrated choice and latent variable models, to capture both observable and latent influences on PR adoption. These models significantly improved the ability to predict riders’ acceptance of pooled trips, explaining choice heterogeneity through latent constructs such as safety, service experience, privacy concerns, time sensitivity, and environmental attitudes. Together, these models provide a robust analytical foundation for designing PR systems that more effectively meet user needs. The project translated human-factors insights and behavioral models into actionable technology innovations by extending POLARIS—an agent-based, activity-based travel simulation platform—into a fully functional pooled rideshare simulation environment. New PR modules, acceptance models, and regional scenarios were implemented for Greenville, SC and Austin, TX, enabling high-fidelity validation of algorithmic strategies under realistic demand and traffic conditions. The simulation platform supported the development and evaluation of adaptive discount-based assignment algorithms, enhanced willingness-to-pay formulations, demographic-aware incentive mechanisms, and a proactive joint assignment and repositioning strategy. Simulation results demonstrated substantial gains in pooling uptake, average vehicle occupancy, energy efficiency, and fleet profitability. In Greenville, pooling adoption more than doubled, while reductions in vehicle-miles traveled and energy consumption were significant. In Austin, pooling improvements were achieved with minimal service-quality trade-offs, and profitability increased across all fleet sizes. Through this research, we developed a comprehensive understanding of the human factors barriers that limit user acceptance of pooled rideshare services. These insights enabled the design of human-factors-aware pooled rideshare technologies that more effectively address user concerns and improve adoption rates. By integrating these models into an advanced agent-based simulation framework, we demonstrated that higher adoption of pooled rideshare can lead to measurable improvements in energy efficiency and system performance. Together, these contributions establish a validated pathway from human-centered analysis to technology development and energy-saving outcomes, supporting national goals for more sustainable and efficient mobility systems.

Jia, Yunyi

Next-Generation Energy Technologies for Connected and Automated On-Road Vehicles (NEXTCAR) - Predictive Data-Driven Vehicle Dynamics and Powertrain Control: from ECU to the Cloud (Final Scientific/Technical Report)

This project developed and demonstrated a predictive, data-driven vehicle control system designed to improve energy efficiency and driving performance. The team created intelligent self-driving car technology that optimizes fuel and electricity use by proactively planning vehicle actions. By combining Level 4 autonomous driving capabilities with vehicle-to-everything (V2X) connectivity, the system enables vehicles to adjust speed and change lanes in response to traffic signals, surrounding vehicles, and road conditions, reducing unnecessary stops and delays. In testing, the system improved vehicle fuel economy by more than 30% and reduced travel time by approximately 10%, compared to a conventional adaptive cruise control baseline. These results demonstrate the technical effectiveness of using predictive, V2X-enabled strategies, such as traffic light timing and surrounding traffic awareness, to inform real-time vehicle powertrain control and driving behavior. Additionally, a supporting cloud platform was developed to provide dispatch and route recommendations as well as to log vehicle data, demonstrating the economic feasibility of this approach at the fleet level. By optimizing dispatching and routing operations, this technology enables electric fleet operators to use their vehicles more efficiently and reduce reliance on diesel backups, lowering both operating costs and energy consumption. Overall, this project’s technology advances the future of clean, energy-efficient transportation, enabling vehicles and fleets to reduce energy waste, cut costs, and lower emissions through intelligent automation and connectivity.

33 ADVANCED PROPULSION SYSTEMS

Electronic Structural Optimization of the Air Electrodes for Reversible Protonic Ceramic Electrochemical Cells via IIIA Cation Doping

Reversible protonic ceramic electrochemical cells (R-PCECs) have emerged as a novel technology for clean and efficient energy generation and storage. Improving the oxygen and proton conduction characteristics and stability of air electrodes at intermediate temperatures is crucial for achieving a high performance. Herein, we optimize the electronic structure of a state-of-the-art PrBa 0.8 Ca 0.2 Co 2 O 5+δ (PBCC) air electrode via doping IIIA cations (Al 3+ , Ga 3+ , and In 3+ ). Also, it is shown that PrBa 0.8 Ca 0.2 Co 1.9 Ga 0.10 O 5+δ (PBCCGa 0.10 ) exhibits improved oxygen reaction activity and hydration capability. Density functional theory calculations confirm that Ga doping provides the most favorable electronic structure. An R-PCEC with PBCCGa 0.10 achieves a peak power density of 2.21 W cm -2 and a current density of −4.64 A cm -2 at 1.3 V at 650 °C. Additionally, the PBCCGa 0.10 electrode performs good operational stability in FC mode (for about 100 h), EC mode (for about 100 h), and reversible cyclic testing (over 200 h) at 600 °C.

30 DIRECT ENERGY CONVERSION

Ultrafast Oxygen Conduction in Sillén Oxychlorides

Oxygen ion conductors are crucial for enhancing the efficiency of various clean energy technologies, including fuel cells, solid oxide air batteries, electrolyzers, membranes, sensors, and more. In this study, a structure-similarity analysis of ≈62k oxygen-containing compounds identified the MBi 2 O 4 X (M = rare-earth element, X = halogen element) family as promising candidates for fast oxygen transport. Among these, LaBi 2 O 4 Cl is found as an ultrafast oxygen conductor with an ultralow migration barrier of 0.1 eV based on ab initio studies. Its 2D layered structure, featuring a “triple fluorite” layer, supports diffusion of both oxygen vacancies and interstitials. In addition to vacancy diffusion with a 0.1 eV barrier, ab initio studies show interstitial diffusion exhibits a modest barrier of 0.6–0.8 eV. Frenkel pairs are found to be the dominant defects in intrinsic LaBi 2 O 4 Cl, facilitating significant vacancy-mediated oxygen diffusion at elevated temperatures. With 2.8% oxygen vacancies, LaBi 2 O 4 Cl is predicted to achieve a conductivity of 0.3 S/cm at 25 °C in a single crystal. Experimental synthesis and characterization of polycrystalline LaBi 2 O 4 Cl and Sr-doped LaBi 2 O 4 Cl revealed conductivity exceeding that of YSZ and LSGM below 400 °C, with lower activation energies, achieving a total conductivity of 0.1−0.2 mS/cm at 300 °C. Here, while these results confirm its potential of fast oxygen transport, we suggest further experimental optimization of LaBi 2 O 4 Cl, including aliovalent doping and microstructure refinement, could significantly enhance its performance, facilitating fast oxygen conduction approaching room temperature.

Defects

Slippery liquid infused porous surface (SLIPS) condensers for high efficiency air gap membrane distillation

Abstract To address growing water scarcity, we must improve the energy efficiency of thermal desalination technologies such as air gap membrane distillation. However, promising functional materials such as slippery liquid infused porous surfaces have not yet implemented for any desalination technology. Here, we fabricate and test slippery liquid infused porous surfaces (using Krytox 16,256 lubricant and CuO nanostructures) in an air gap membrane distillation apparatus. System-level transport models, validated by experimental data, establish a framework for improving performance through enhanced condensation surfaces. Results are obtained across a range of temperatures (50–80 °C), salinities (5–105 g/kg), and module lengths. We find that small air gap thickness and efficient droplet shedding significantly improves performance. The CuO Krytox process achieves these with a conductive-self-limiting coating, high nanostructure rugosity, strong covalent and metallic bonding, high hydrophobicity, minimal droplet pinning sites, and ultra-low contact angle hysteresis. The greatest efficiency enhancement from SLIPS is derived from the improved droplet shedding, which allows for reduced gap sizes without flooding, and is further augmented by the increased permeate flux.

Yogi, Yashwant S.

Evolution of size-selected Pt cluster catalysts on prototypical oxide supports

The current quest for new pathways into sustainable, efficient and durable energy conversion technologies makes the used for a fundamental understanding of the atomic-scale phenomena underlying catalytic processes ever more pressing. In this context, characterizing catalyst particles in situ provides valuable information about the evolution of their composition, structure, oxidation state and charge state during an ongoing process. To disentangle the influence of individual parameters – temperature, pressure, gas composition, cluster size, as well as support acidity, redox state and defect density – it is crucial to control them precisely and separately in experiments. At the example of size-selected Pt n clusters – i.e. sub-nm particles defined to the exact number of atoms – on flat oxide supports, we follow their rich evolution phenomena via (synchrotron-based) X-ray photoelectron spectroscopy (XPS) and scanning tunnelling microscopy (STM) during temperature ramps and in various gas environments. Here, we present our experience with these highly defined, yet complicated-to-create samples in ultra-high vacuum (UHV) and at mbar pressures. We discuss their stability during transport to synchrotrons and under reaction conditions on three prototypical oxide supports and show the various phenomena that can be disentangled. Ptn clusters on the non-reducible silicon dioxide, SiO 2 , remain size-selected and show remarkable stability. Doping strongly influences the size-dependent binding energy shifts and changes the Pt response to oxidative and reaction conditions, which we attribute to different cluster geometries: p-type doping leads to wetting, enhanced sinter resistance and a diminished response to oxidative environments, compared to clusters on n-type doped samples. We compare the system with our previous findings of a similar change in dimensionality for Pt 20 clusters on the reducible ceria, CeO 2 (111), support, induced by modulation of its O vacancy density. The Pt n /CeO 2 system is particularly interesting for strategies to stabilize and redisperse Pt clusters dynamically. Finally, we study the evolution of Pt n clusters on another reducible oxide support, magnetite, Fe 3 O 4 (001), in 0.1 mbar alternating redox conditions at RT and elevated temperature. In analogy to findings previously reported for Pt/TiO 2 (110), the clusters either become encapsulated by a thin oxide film via strong metal–support interaction (SMSI) or deeply buried in the magnetite. Overall, our approach of following the evolution of size-selected clusters on oxide supports leads to fundamental atomic-scale insights on nano-scale catalyst materials, on our path to sustainable, dynamic and self-repairing catalysts.

Falling, Lorenz J. [Technical Univ. of Munich (Ger

Developing an Automated Microscopic Traffic Simulation Scenario Generation Tool

Traffic simulation is an effective tool for urban planners, traffic engineers, and researchers to study traffic. In particular, microscopic traffic simulation, which simulates individual vehicles’ movements within a transportation network, has demonstrated its importance in analyzing and managing transportation systems. However, integrating data from various sources, generating traffic scenarios, and importing information into traffic simulators to conduct microscopic simulations have always been a challenge. This paper presents a solution to overcome this challenge: RealTwin, a comprehensive tool for automated scenario generation for microscopic traffic simulation. Following a streamlined scenario generation and calibration workflow, RealTwin effectively bridges gaps between traffic data from various sources and traffic simulators, making microscopic traffic simulation more accessible for researchers and engineers across various levels of expertise. Using RealTwin to generate a real-world traffic scenario in Simulation of Urban Mobility (SUMO), VISSIM, and AIMSUN, RealTwin’s ability is demonstrated in the construction of realistic and consistent traffic scenarios in different simulators. Furthermore, this paper introduces and illustrates RealTwin’s capability for technology (e.g., autonomous vehicle) scenario generation. This feature can contribute to more comprehensive microscopic simulations, facilitating the analysis of potential effects of various technological innovations on mobility, energy efficiency, and safety. Finally, RealTwin is used to calibrate a simulation in SUMO. In conclusion, the calibration module enhances RealTwin’s ability to generate consistent simulations across different platforms and more realistic simulations that reflect real-world traffic operations.

autonomous vehicle

Macro-micro multiscale modeling to assist the design of HPDC Al castings microstructure and alloys for EV super-large body structures (Phase 1)

Implementation of High Pressure Die Casting (HPDC) Aluminum (Al) body structures for high volume electrified vehicles (EV) to improve electric efficiency remains a key strategy within many original equipment manufacturers (OEM)s. In addition to high strength for safety requirements, superior Self Piercing Riveting (SPR) performance is demanded for HPDC Al alloys to be compatible with high volume SPR joining. In this work, it is proposed to extend and validate an existing Contractor finite element multiscale macro-micro modeling approach to quantify the influence of the microstructure of HPDC alloys on the fracture strain/displacement under 3-point bend and clinch testing. The success of this work will allow to replace solution treatment stage with low energy consumption heat treatment (HT) processes, or to design new non heat treatable (NHT) HPDC Al alloys to eliminate HT requirements. Ultimately, this project will facilitate the application of HPDC Al alloys for super-large vehicle structures to significantly reduce vehicle weight and thus improving energy efficiency. The purpose of this project is to extend and validate an existing f

99 GENERAL AND MISCELLANEOUS

Developing Smart Building Technology Modules to Enhance Workforce Preparedness: A Case for AI-Driven Academic and Professional Education

Smart building technologies are resources that improve building energy efficiency and resilience, reduce carbon emissions, and provide load flexibility to the grid. However, in both academic curricula and building professionals’ continuing education, there is a lack of systematic instruction on methods to integrate multiple energy systems including distributed energy resources (DER), smart building technologies, AI (Artificial Intelligence) tools and key concepts, components, and controls, including “Internet of Things” (IoT) devices. In today’s dynamic workforce, this major gap in smart building technology education prevents stakeholders from being able to attract talent with an understanding and preparation to adopt smart building technologies in building design and operations. A federally funded project included a partnership between Slipstream and Texas A&M University (TAMU) to develop a semester-long smart building curriculum for engineering college students with the ability to adapt the contents for workforce development of professionals in building services. The final product consists of 16 training videos adapted for building professionals and the public. The educational content and training materials cover the benefits of building energy systems, the latest sensor technologies and IoT devices, all with a focus on smart building technologies. The key drivers are on topics related to smart building controls (i.e., energy management information systems), smart building control platforms, cybersecurity, grid-interactive-efficient buildings (GEBs), smart building control methods, and occupant-centric control. Although not explicitly included the technologies nod to the need for AI driven technologies to prepare engineers and industry professionals to be future ready. This paper describes the project approach, provides outlines of the training materials, and identifies lessons learned in creating the content for this course. The authors suggest ways to scale the instruction of smart building concepts to empower the workforce to accelerate the adoption of smart building technologies and AI-based teaching and learning in higher education and building sector.

99 GENERAL AND MISCELLANEOUS

Fighting the climate crisis with caloric heat pumping: Innovations to enable widespread adoption

Caloric heat pumping is a cross-cutting thermal energy technology that can cover a wide range of applications and temperatures, from millikelvins to hundreds of kelvins, with a working medium that has zero global warming potential. The technology promises cost savings and high efficiency, having 60% Carnot efficiency demonstrated to date. The Energy Earthshots™ Initiative, launched by the U.S. Department of Energy, aims to fight the climate crisis and overcome technological barriers to a decarbonized economy. The initiative focuses on the development of energy solutions that increase efficiency, reduce greenhouse gas emissions, and ensure affordability. Three out of eight Energy Earthshots™ look for alternative thermal energy technologies for extensive temperature ranges, from hydrogen liquefaction to metal-treating temperatures. Caloric heat pumping can fulfill all these requirements; however, at the current stage, caloric systems have limited presence in real-world applications. Further, this perspective discusses key efforts to address barriers hindering the widespread adoption of caloric technology. We focus on essential breakthroughs in and effective approaches to material discovery and draw a path to high-power-density, grid-interactive caloric systems to support achieving the ambitious net-zero carbon economy goal.

42 ENGINEERING

MEP Core Tools

This slide deck provides an update on the progress of the project titled "MEP Core Tools" funded by the Energy Efficient Mobility Systems program in the Vehicle Technologies Office at the Department of Energy.

29 ENERGY PLANNING, POLICY, AND ECONOMY

Protein engineering for critical metal recovery beyond REEs

Achieving decarbonization and electrification goals will require expanded production of critical minerals (CM), including Li, Co, Cu, rare earths, Ni, and graphite, whose supply chains are geopolitically vulnerable. Problematically, current extraction and separation processes pose severe environmental burdens that impede the development of a diversified domestic supply chain and undercut the environmental benefits of energy technologies [1, 2]. The development of efficient, economical, and environmentally sustainable processing technologies is thus important for meeting the CM demand of the emerging energy technology market. To this end, we have recently developed an all-aqueous protein-based process for rare earth element (REE) extraction and separation. To extend our protein-based approach to critical metals beyond REEs, the goal of this project was to develop a protein discovery and engineering pipeline to generate a panel of proteins that selectively bind target critical metals.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH

Energy-Efficient Capacitive Deionization through Electrode Modification and Process Development

Electrochemical separation technologies, such as capacitive deionization (CDI), are promising for addressing global energy and water challenges. However, there is a need to improve the performance, better understand property-performance relationships, and evaluate the longevity of CDI electrodes. This study explores the chemical modification of electrodes and the adjustment of CDI operating parameters. Results indicate that nitric acid (HNO3) conditioning of activated carbon cloth (ACC) electrodes removes metal oxides, introduces oxygen and nitrogen functionalities, and increases the specific capacitance (16% at 1 mV/s). Moreover, these changes in electrode properties positively impact device-level CDI performance. Through HNO3-conditioning of the ACC and tuning of the operational parameters, this work demonstrates higher electrosorption capacity (4.0x), greater charge efficiency (90% vs 24%), and lower energy consumption (3.8x). Despite these enhancements, limitations of the HNO 3 -conditioned ACC include decreased desorption kinetics and a 32% loss in electrosorption capacity after 200 cycles. Overall, this work provides guidance on using oxidative pretreatment via HNO 3 to modify ACC electrodes for CDI and evaluates the trade-offs associated with varying operational parameters.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH