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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 1,189 records · Page 66

An Anthradithiophene Donor Polymer for Organic Solar Cells with a Good Balance between Efficiency and Synthetic Accessibility

Over the past few years, the organic photovoltaics technology (OPV) has reached remarkable power conversion efficiencies (PCEs), mostly thanks to the advent of nonfullerene acceptors as well as to a high level of materials engineering. Yet, the complex materials syntheses behind these results ultimately limit technological readiness. The quest for scalable organic compounds offering high PCE and reasonably low synthetic complexity is a must to close the gap between laboratory R&D and commercial products. The synthesis and full characterization of a new conjugated polymer called PATTD is reported herein, based on a novel anthradithiophene as an electron–rich building block coupled with a commercially available dithienylbenzodithiophenedione as an electron–withdrawing comonomer. Its photovoltaic properties are studied in blends with IT–4F and IDIC as acceptors. PATTD:IT–4F–based photovoltaic devices exhibit a PCE approaching 10% and over 2300 h shelf–life stability. Finally, the PATTD scalability factor (SF), together with the PATTD–based photovoltaic performances, lead to a PCE/SF value equal to 0.297, placing such devices into the innermost circle of OPV materials, achieving one of the best compromises between efficiency and synthetic complexity and at the same time offering promising industrial perspectives.

14 SOLAR ENERGY↗

The new physics case for beam-dump experiments with accelerated muon beams

As the field examines a future muon collider as a possible successor to the LHC, we must consider how to fully utilize not only the high-energy particle collisions, but also any lower-energy staging facilities necessary in the R&D process. An economical and efficient possibility is to use the accelerated muon beam from either the full experiment or from cooling and acceleration tests in beam-dump experiments. Beam-dump experiments are complementary to the main collider as they achieve sensitivity to very small couplings with minimal instrumentation. We demonstrate the utility of muon beam-dump experiments for new physics searches at energies from 10 GeV to 5 TeV. We find that, even at low energies like those accessible at staging or demonstrator facilities, it is possible to probe new regions of parameter space for a variety of generic BSM models, including muonphilic, leptophilic, L μ − L τ , and dark photon scenarios. Such experiments could therefore provide opportunities for discovery of new physics well before the completion of the full multi-TeV collider.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Accelerating template generation in resonant anomaly detection searches with optimal transport

We introduce Resonant Anomaly Detection with Optimal Transport (RAD-OT), a method for generating signal templates in resonant anomaly detection searches. RAD-OT leverages the fact that the samples from the conditional probability density of the target features vary approximately linearly along the optimal transport path connecting the resonant feature. This does not assume that the conditional density itself is linear with the resonant feature, allowing RAD-OT to efficiently capture multimodal relationships, changes in resolution, etc. By solving the optimal transport problem, RAD-OT can quickly build a template by interpolating between the background distributions in two sideband regions. We demonstrate the performance of RAD-OT using the LHC Olympics R&D dataset, where we find comparable sensitivity and improved stability with respect to deep learning-based approaches.

Automation↗

Minimizing Optimal Transport for Functions with Fixed-Size Nodal Sets

Consider the class of zero-mean functions with fixed L ∞ and L 1 norms and exactly N ϵ N nodal points. Which functions f minimize W p (f + ,f – ), the Wasserstein distance between the measures whose densities are the positive and negative parts? We provide a complete solution to this minimization problem on the line and the circle, which provides sharp constants for previously proven “uncertainty principle”-type inequalities, i.e., lower bounds on N • W p (f + ,f – ). We further show that, while such inequalities hold in many metric measure spaces, they are no longer sharp when the non-branching assumption is violated; indeed, for metric star-graphs, the optimal lower bound on W p (f + ,f – ) is not inversely proportional to the size of the nodal set, N. Here, based on similar reductions, we make connections between the analogous problem of minimizing W p (f + ,f – ) for f defined on Ω C R d with an equivalent optimal domain partition problem.

97 MATHEMATICS AND COMPUTING↗

Fusion Innovation and the Valley of Death—Lessons from Fission

Over the past several decades, the United States (U.S.) and other countries have done important research and development in advanced nuclear energy technologies, both fission and fusion. The urgency of our current climate, energy, and security needs have prompted a concerted effort by innovators, investors, and the public sector to transition from research and development (R&D) to demonstration and commercialization—to cross the proverbial “valley of death.” The stakes are high: humanity needs clean energy options, and the failure of any promising alternative will lower our odds of success. The process of moving an innovation into use has often been described in phases that begin with early research and end with deployment at scale. Between those two phases lies an area often referred to as the “valley of death” because it can require a long period of time, large investments, and often includes significant challenges related to regulation, standardization, and entering markets already structured around incumbent technologies. What can we learn from recent experience with fission to inform our path forward with fusion? At least five key lessons rise to the top: 1) Set bold targets; 2) Empower the private sector; 3) Engage with regulators and the public; 4) Address costs and markets; and 5) Deliver results. Here, this editorial will consider each of these in turn.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

SPLENDAQ: A Detector-Agnostic Data Acquisition System for Small-Scale Physics Experiments

Many scientific applications from rare-event searches to condensed matter system characterization to high-rate nuclear experiments require time-domain triggering on a raw stream of data, where the triggering is generally threshold-based or randomly acquired. When carrying out detector R &D, there is a need for a general data acquisition (DAQ) system to quickly and efficiently process such data. In the SPLENDOR collaboration, we are developing the Python-based SPLENDAQ package for this exact purpose—it offers two main features for offline analysis of continuous data: a threshold triggering algorithm based on the time-domain optimal filter formalism and an algorithm for randomly choosing nonoverlapping segments for noise measurements. Further, combined with the commercially available Moku platform, developed by Liquid Instruments, we have a full pipeline of event building off raw data with minimal setup. Here, we review the underlying principles of this detector-agnostic DAQ package and give concrete examples of its utility in various applications.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Chapter 1.18 - The Promise of Perovskite Solar Cells

Perovskite solar cells (PSCs) based on a new class of semiconductors - organic and inorganic hybrid halide perovskites - have emerged as a disruptive photovoltaic (PV) technology that is potentially cost-effective, scalable, and highly efficient, with an expectation for future deployment at terawatt scale. This new PV technology has drawn significant R&D attention from academics and industries as an alternate to compete with traditional PV technologies to help mitigate challenges associated with global energy demand. The synthesis of the hybrid halide perovskites was reported in the 1970s. The structural knowledge, solution processing and optoelectronic characteristics of this hybrid material family were further studied in the 1990s. It is until 2009-2012 when the use of methylammonium lead triiodide (MAPbI3) was first demonstrated in PV cells worldwide researchers have started to show a general interest in using hybrid halide perovskites for PV and other optoelectronic applications.

perovskite↗

Physics-informed machine learning for building performance simulation-A review of a nascent field

Building performance simulation (BPS) is critical for understanding building dynamics and behavior, analyzing the performance of the built environment, optimizing energy efficiency, improving demand flexibility, and enhancing building resilience. However, conducting BPS is not trivial. Traditional BPS relies on accurate building energy models, which are primarily physics-based and heavily dependent on detailed building information, expert knowledge, and case-by-case model calibrations, significantly limiting their scalability. With the development of sensing technology and the increased availability of data, there is growing attention and interest in data-driven BPS. However, purely data-driven models often suffer from limited generalization ability and a lack of physical consistency, resulting in poor performance in real-world applications. To address these limitations, recent studies have begun integrating physics priors into data-driven models, a methodology known as physics-informed machine learning (PIML). PIML is an emerging field where its definitions, methodologies, evaluation criteria, application scenarios, and future directions remain open. To bridge those gaps, this study systematically reviews the state-of-the-art PIML for BPS, offering a comprehensive definition of PIML and comparing it to traditional BPS approaches regarding data requirements, modeling effort, performance, and computational cost. We also summarize the commonly used methodologies, validation approaches, application domains, available data sources, open-source packages, and testbeds. In addition, this study provides a general guideline for selecting appropriate PIML models based on BPS applications. Finally, this study identifies key challenges and outlines future research directions, providing a solid foundation and valuable insights to advance R&D of PIML in BPS.

Jiang, Zixin↗

Life cycle analysis of dedicated energy crops for fuel production in the United States

Dedicated energy crops are promising feedstocks to make biofuels including jet fuels. This study applies life cycle analysis (LCA) to estimate direct well-to-wake (WTW) greenhouse gas (GHG) emissions (g CO 2 e/MJ) for jet fuel derived from five energy crops-biomass sorghum, miscanthus, switchgrass, poplar, and willow-via Fischer-Tropsch-to-Jet (FTJ) and Ethanol-to-Jet (ETJ) pathways. The WTW boundary includes direct emissions from biomass production, fuel production, and fuel combustion. The R&D GREET model is expanded to conduct the LCA, using national average biomass yields and farming inputs from the 2023 Billion-Ton Study. In addition, this study estimates emissions from market-mediated effects, including induced land-use change, induced other crop (non-feedstock) production changes, and induced livestock production changes using global economic and emissions factor models. On a per-dry U.S. ton basis, cultivation and harvest emissions are lowest for willow (51,565 g CO 2 e) and highest for biomass sorghum (104,488 g CO 2 e). Per-acre results show similarly high emissions for sorghum and lowest values for poplar and willow. Direct WTW emissions are substantially lower for FTJ (biomass sorghum: 5.5; miscanthus: 10.3; switchgrass: 11.7; poplar: 11.9; and willow: 8.7 g CO 2 e/MJ) than ETJ (33.2; 33.8; 34.8; 36.2; and 31.7 g CO 2 e/MJ, respectively). When market-mediated emissions are included, miscanthus exhibits the lowest total emissions across energy crop pathways. Although results are sensitive to modeling assumptions, they indicate that high-yielding perennial and woody crops, particularly when planted on marginal land, could significantly reduce WTW emissions for bio-jet fuels by combining low direct emissions with soil carbon gains and favorable market-mediated effects.

Billion-Ton Study↗

Upstream considerations for gas fermentation processes

Gas fermentation enables the production of fuels, chemicals, and foods from gaseous carbon sources and could serve as a technology for valorizing carbon that may otherwise be emitted to the atmosphere. In this review, we focus on upstream feedstock considerations: the supply of carbon and the supply of electrical power. Electrical power serves a dual role, providing both process energy and biochemical redox potential (via hydrogen or reduced intermediates). We define gas fermentation as bioprocesses involving gaseous feedstocks metabolized by microbes, distinct from microbial electrosynthesis. Trends in CO 2 point sources and low-carbon electricity systems are analyzed, highlighting opportunities and challenges for future deployment. This review synthesizes current knowledge and identifies key R&D priorities for process integration at industrial scale.

09 BIOMASS FUELS↗

Perspectives on the relationship between materials chemistry and roll-to-roll electrode manufacturing for high-energy lithium-ion batteries

As lithium-ion battery (LIB) active material and cell manufacturing costs continue to drop with wider adoption of electric vehicles, electrode and cell processing costs remain too high in terms of reaching the ultimate U.S. Department of Energy (DOE) cell cost target of $80/kWh. This paper primarily covers major materials chemistry advancements made over the last 10 years at Oak Ridge National Laboratory (ORNL) in the space of advanced manufacturing science for LIBs with the aim of simultaneously meeting the ultimate cost target, 500 Wh/kg gravimetric energy density, 10-15-min fast charge times, and 1000 deep discharge cycles. Aqeous electrode processing with a variety of active anode and cathode materials is now a standard procedure at the DOE Battery Manufacturing R&D Facility at ORNL (BMF), including the latest processes developed for Ni-rich cathodes. New results on cobalt-free LiNi 0.8 Fe 0.1 Al 0.1 O 2 (NFA 811) are also included and discussed in an electrode processing advantage context. In addition, colloidal processing advancements have been made for Si/C composite anodes for achieving >600 mA h/g capacities. Optimization of electrode coating parameters and drying protocols have been completed, which has elucidated how key processing variables need to be changed when parameters such as slurry solids loading, solvent type, and wet electrode thickness are changed. ORNL has also increased the line speeds at which thick cathodes can be processed using ultra-fast electron beam (EB) curing and substantially decreased formation cycling times to <1 day. Finally, key details of these advancements are discussed in the context of materials chemistry and process-property-performance relationships.

25 ENERGY STORAGE↗

A review of thermal physics and management inside lithium-ion batteries for high energy density and fast charging

Traditionally it has been assumed that battery thermal management systems should be designed to maintain the battery temperature around room temperature. That is not always true as lithium-ion battery (LIB) R&D is pivoting towards the development of high energy density and fast charging batteries. Therefore, it is necessary to have a comprehensive review of thermal considerations for LIBs targeted for high energy density and fast charging, i.e., the optimal thermal condition, thermal physics (heat transport and generation) inside the battery, and thermal management strategies. As the energy density and charge rate increases, the optimal battery temperature can shift to be higher than room temperature. In the first part of the review various sources of heat generation inside LIBs and various approaches to minimizing battery heat generation are summarized. The importance of heat of mixing due to ion diffusion during fast charging is also highlighted. To improve the temperature uniformity and avoid excessive internal temperature rise, heat transfer inside the battery needs to be enhanced, and reducing the thermal contact resistance between the electrodes and separator can significantly increase the effective thermal conductivity of batteries. In the second part of the review various challenges and latest developments related to thermal transport and properties of LIBs are discussed. Finally, a summary of latest advancement on smart control of internal temperature of LIBs is discussed as depending on the ambient temperature and the optimal temperature; the battery heat needs to be retained or dissipated to elevate or avoid temperature rise.

25 ENERGY STORAGE↗

A tri-level distribution locational marginal price-based demand response framework

Here, in this paper, we propose a tri-level, nested, two-stage price-based demand response (PBDR) framework that considers distribution locational marginal price (DLMP) as DR enabler between load-serving entities (LSE), demand response providers (DRPs), and customers in the day-ahead distribution market. It enables LSE and customer interactions by using multiple DRPs, positioned in-between, and independently optimizes their objectives. The problem is formulated using linear power flow with approximated power losses and its application in DLMP as DR pricing. The tri-level problem is solved using a nested reformulation & decomposition (R&D) method and tested on the real Indian-108 bus distribution system under various dynamic pricings. Further, the temporal–spatial variations in DLMPs are assessed using fairness criteria. Numerical analyses demonstrate that DLMP applications can effectively improve economic efficiency, and transparency in DR programs valuation with a favorable fairness margin. The results show that DLMP as DR pricing signal induces (0-2) % variation in DLMP for DR participation up to 10 %. Further, it gives over 90 % fairness over temporal–spatial variation for all the customers.

24 POWER TRANSMISSION AND DISTRIBUTION↗

GAMBL – A dual-cooled fusion blanket using SiC-based structures

We describe a novel fusion reactor blanket concept called GAMBL – GA Modular BLanket. This design concept exploits the advantages of SiC-based structures while minimizing their limitations. Material microstructures are tailored for different functions throughout the first wall and blanket, including the use of graded W/SiC composites to enhance heat transfer capabilities and resist erosion at the plasma-facing surface. The design contains a decoupled first wall and breeding blanket, which we show can provide adequate tritium breeding. By decoupling the breeding part of the blanket, we can operate at very low PbLi breeder pressure and support gravity loads in simple, radiatively-cooled structural beams that do not contain coolant. First wall performance capabilities are enhanced by eliminating constraints imposed by the deep blanket. We have performed initial fluid, thermal, mechanical and neutronics analysis of this concept to show its capabilities to meet the design requirements. R&D needs are mostly related to materials development. Except for unique manufacturing needs, no new facilities are required beyond existing or planned facilities for the US base program on steel-based DCLL blankets.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Sustainable aviation fuels from biomass and biowaste via bio- and chemo-catalytic conversion: Catalysis, process challenges, and opportunities

Sustainable aviation fuel (SAF) production from biomass and biowaste streams is an attractive option for decarbonizing the aviation sector, one of the most-difficult-to-electrify transportation sectors. Despite ongoing commercialization efforts using ASTM-certified pathways (e.g., lipid conversion, Fischer-Tropsch synthesis), production capacities are still inadequate due to limited feedstock supply and high production costs. New conversion technologies that utilize lignocellulosic feedstocks are needed to meet these challenges and satisfy the rapidly growing market. Combining bio- and chemo-catalytic approaches can leverage advantages from both methods, i.e., high product selectivity via biological conversion, and the capability to build C-C chains more efficiently via chemical catalysis. Herein, conversion routes, catalysis, and processes for such pathways are discussed, while key challenges and meaningful R&D opportunities are identified to guide future research activities in the space. Bio and chemo-catalytic conversion primarily utilize the carbohydrate fraction of lignocellulose, leaving lignin as a waste product. This makes lignin conversion to SAF critical in order to utilize whole biomass, thereby lowering overall production costs while maximizing carbon efficiencies. Thus, lignin valorization strategies are also reviewed herein with vital research areas identified, such as facile lignin depolymerization approaches, highly integrated conversion systems, novel process configurations, and catalysts for the selective cleavage of aryl C–O bonds. The potential efficiency improvements available via integrated conversion steps, such as combined biological and chemo-catalytic routes, along with the use of different parallel pathways, are identified as key to producing all components of a cost-effective, 100% SAF.

09 BIOMASS FUELS↗

Grid-responsive hydrogen production: Capital utilization and current density vs. efficiency in variable electricity markets

To achieve low-cost hydrogen production from water electrolyzers, grid tied electrolysis may need to operate dynamically to minimize the cost of supplying energy to the electrolyzer stack and produce hydrogen during low-cost hours and turn off/down during high-cost hours. Operating systems in this way can decrease capital utilization (capacity factor) and electricity costs. This strategy would shift the dominant cost drivers away from electricity (and thus efficiency) to the capital costs of the system, due to the underutilized capital when operating at low-capacity factors. Increasing the operational current density of the system could, in effect, reduce the capital cost of the system while producing hydrogen at a lower efficiency on a per unit energy basis. In the variable electricity cost profiles analyzed in this paper, increasing the current density for liquid alkaline from 0.5 A/cm2 to 1.5 Ac/m2 and proton exchange membrane electrolyzers from 2 A/cm2 to 4 A/cm2 resulted in substantial reductions in the levelized cost of hydrogen. Additionally, as capacity factors and electricity costs decrease, the optimal operating current density of the electrolyzer systems analyzed increases. These findings suggest R&D efforts should focus on increasing the operational current densities, reducing the turn down ratios, and understanding the durability implications of those strategies on low-temperature liquid alkaline and proton exchange membrane electrolyzers.

08 HYDROGEN↗

Practical and thermodynamic constraints on electromicrobially accelerated CO 2 mineralization

By the end of the century, tens of gigatonnes of CO 2 will need to be removed from the atmosphere every year to maintain global temperatures. Natural weathering of ultramafic rocks and subsequent mineralization reactions can convert CO 2 into ultra-stable carbonates. Although this will draw down all excess CO 2 , it will take thousands of years. CO 2 mineralization could be accelerated by weathering ultramafic rocks with biodegradable lixiviants. We show that if these lixiviants come from cellulosic biomass, this demand could monopolize the world’s biomass supply. We demonstrate that electromicrobial production technologies (EMP) that combine renewable electricity and microbial metabolism could produce lixiviants for as little as $\$200$ to $\$400$ per tonne at solar electricity prices achievable within the decade. We demonstrate that EMP could make enough lixiviants to sequester a tonne of CO 2 for less than $\$100$. This work highlights the potential of this approach and the need for extensive R&D.

59 BASIC BIOLOGICAL SCIENCES↗

Seasonal effects on electric vehicle energy consumption and driving range: A case study on personal, taxi, and ridesharing vehicles

The variation in BEV energy consumption and driving range under different weather and driving conditions can affect the usefulness and consumer acceptance of these vehicles. Thus, there is a need to better understand and quantify seasonal factors that affect consumption and range under real-world driving conditions. In this paper, a dataset representing the real-world driving activity of 197 BEVs of the same model recorded over 12 months at a polling frequency of 0.1 Hz is analyzed to estimate BEV performance across different driving applications (personal driving, taxi operation, and ridesharing) and seasons (spring/autumn, summer, and winter). The results show that the electricity consumption, travel patterns, and charging patterns of BEVs vary significantly by both vehicle application and season. For example, BEV models with a range of 160 km, recharged every 1.6 days on average, can meet most trip demands of personal vehicles. However, the same BEV model when used for ridesharing or taxi purposes, is driven much more and recharged more frequently. The results also show that actual BEV electricity consumption (EC) differs significantly from the consumption predicted by the New European Driving Cycle (NEDC) test, with real-world EC being 7%–10% higher than predicted by the NEDC test cycle. Furthermore, the real-world range of personal-use BEVs in winter is only 64% of the NEDC-estimated range. The study found that, when the ambient temperature is lower than 10 °C, electricity consumption increases 2.4 kWh/100 km for every 5 °C decrease in temperature. When it is higher than 28 °C, EC increases 2.3 kWh/100 km for every 5 °C increase in temperature. Furthermore, these findings imply that manufacturers should design BEVs with application-appropriate driving ranges and make R&D investments for improving battery performance in cold environments.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗