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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 37 records · Page 2

Predicting Trends in VOC Through Rapid, Multimodal Characterization of State-of-the-Art p-i-n Perovskite Devices

Perovskite photovoltaic technologies are approaching commercial deployment, yet single junction and tandem architectures both still have significant room to improve power conversion efficiency and stability. The ability to perform rapid screening of material quality after altering processing conditions is critical to accelerating the optimization and commercialization of perovskite-based technologies. Currently, researchers utilize a wide range of stand-alone metrology tools to isolate sources of power loss throughout a device stack, which can be slow and labor intensive. Here, we demonstrate the use of a multimodal metrology approach to rapidly determine the maximum achievable and predicted open circuit voltages of >100 perovskite devices during fabrication. Acquisition of these different data is facilitated by combining them into a single integrated measurement platform. We show that these data and automated analysis can be used to rapidly understand and ultimately predict quantitative trends in open circuit voltages of state-of-the-art device architectures. The data and automated analysis workflow presented provides a reliable approach to quickly identify absorber and charge transport layer combinations that can lead to improved open circuit voltages.

14 SOLAR ENERGY

The strong coupling constant: state of the art and the decade ahead

Theoretical predictions for particle production cross sections and decays at colliders rely heavily on perturbative Quantum Chromodynamics (QCD) calculations, expressed as an expansion in powers of the strong coupling constant α$_{S}$. The current O(1%)uncertainty of the QCD coupling evaluated at the reference Z boson mass, αS(mZ2)=0.1179±0.0009, is one of the limiting factors to more precisely describe multiple processes at current and future colliders. A reduction of this uncertainty is thus a prerequisite to perform precision tests of the Standard Model as well as searches for new physics. This report provides a comprehensive summary of the state-of-the-art, challenges, and prospects in the experimental and theoretical study of the strong coupling. The current αS(mZ2)world average is derived from a combination of seven categories of observables: (i) lattice QCD, (ii) hadronic τ decays, (iii) deep-inelastic scattering and parton distribution functions fits, (iv) electroweak boson decays, hadronic final-states in (v) e$^{+}$e$^{−}$, (vi) e–p, and (vii) p–p collisions, and (viii) quarkonia decays and masses. We review the current status of each of these seven αS(mZ2)extraction methods, discuss novel α$_{S}$ determinations, and examine the averaging method used to obtain the world-average value. Each of the methods discussed provides a ‘wish list’ of experimental and theoretical developments required in order to achieve the goal of a per-mille precision on αS(mZ2)within the next decade.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS

Deep-learning methods for contrast enhancement and artifact reduction in cryo-electron tomography: a systematic analysis of the state of the art and proposed improvements

Cryo-electron tomography (cryo-ET) has emerged as the preferred technique for visualizing the organization of macromolecular complexes in situ and resolving their structures at subnanometre resolution [Tegunov et al. (2021)View full citation, Nat. Methods, 18, 186–193]. Despite improvements in data quality as a result of advances in detector technology, microscope stability and stage precision, the analysis and interpretation of tomograms remains challenging due to a low signal-to-noise ratio and reconstruction artifacts stemming from experimental constraints in specimen tilt during data collection resulting in a missing wedge in the Fourier space. Recently, self-supervised deep-learning methods have been proposed for contrast enhancement and reduction of resolution anisotropy in reconstructed tomograms. Here, we evaluate several state-of-the-art deep-learning methods which aim to improve the interpretability of cryo-ET reconstructions, with a focus on their performance on downstream tasks of template matching, sub­tomogram averaging and segmentation. We propose new training architectures and a loss function based on Fourier shell correlation that show improved performance over the standard U-Net with L1/L2 losses. We demonstrate our analysis on four diverse experimental datasets: purified 80S ribosomes, in situ Chlamydomonas reinhardtii, immature HIV-1 virus-like particles and INS-1E cells.

contrast enhancement

State of the Art in Thermal Catalytic Upgrading of Biomass and Biomass-Derived Intermediates

Biomass-derived energy sources represent a promising domestic route for fuel and chemical production, taking advantage of largely underutilized biological and waste resources. Heterogeneous catalysis plays a key role in these biomass conversion processes, as reflected by all American Society for Testing and Materials–approved pathways for producing sustainable aviation fuel proceeding through a catalytic step. This concise review seeks to establish the state of the art in thermal catalytic process development for various biomass-derived feedstocks and the current enabling capabilities that aid this development. Research needs are identified and described throughout the article, as further advancements in heterogeneous catalysis are required to improve the affordability and realize the full potential of biomass-derived products.

09 BIOMASS FUELS

Cost and Performance Estimates for State-of-the-Art and Advanced 1×1 H-Class Natural Gas-Fired Power Plants

As an extension of NETL's Fossil Energy Baseline for Electricity Generating Units Volume 1: Coal and Natural Gas to Electricity (FEB Rev 4a, this study develops cost and performance estimates for analogous NGCC cases using a state-of-the-art 2023 vintage H-Class CT in a 1×1 configuration, where a single combustion turbine and heat recovery steam generator are coupled to a single steam turbine on a common shaft. These 1×1 H-Class cases are used to develop cost and performance estimates of X-Class 1×1 NGCC cases with advanced performance characteristics, analogous to NETL’s cost and performance projections report.

20 FOSSIL-FUELED POWER PLANTS

Field Evaluation of the High Efficiency Dehumidification System (HEDS) at the Timken Museum of Art - Summary of Measurement and Verification (M&V) Results from Summer 2023

The National Renewable Energy Laboratory (NREL) is performing a measurement and verification (M&V) assessment of the Conservant High Efficiency Dehumidification System (HEDS) at the Timken Museum of Art in San Diego, California. The HEDS was selected for evaluation by the U.S. Department of Energy (DOE) High Impact Technology Catalyst (HIT) evaluation program in 2022. This report documents recently completed analysis of data collected as an initial assessment of the HEDS system performance. Data was collected for the summer M&V during several weeks in August and September 2023 while operating the Timken Museum's HVAC system in several operating modes.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI

Field Evaluation of the High Efficiency Dehumidification System (HEDS) at the Timken Museum of Art - Measurement and Verification (M&V) Results from Summer, Winter and Spring Evaluation Periods

The High Efficiency Dehumidification System (HEDS) technology from Conservant Systems Inc., installed at the Timken Museum of Art in San Diego, California, was evaluated to determine its performance relative to appropriate baseline operation. Data was collected for measurement and verification for several weeks during three evaluation periods: Summer (Aug-Sep 2023), Winter (Dec 2023-Feb 2024) and Spring (May-Jun 2024). The evaluation included operating the heating, ventilation and air conditioning (HVAC) system in both constant air volume (CAV) and variable air volume (VAV) modes, with and without the HEDS energy recovery and HVAC system optimization technology enabled. The electricity consumption of the chiller and the gas-supplied reheat energy were measured to characterize savings achieved by the HEDS operation. Based on these measurements, the HEDS was responsible for chiller electrical load savings during the summer evaluation period of 39% and 42% for the CAV and VAV operating modes, respectively; 97% and 100% chiller electrical load reductions were observed during the winter evaluation for the CAV and VAV operating modes, respectively; and the corresponding reductions during the spring evaluation were 42% and 52% for CAV and VAV operation, respectively. The measured reheat energy reductions, which are typically provided by natural gas, due to the HEDS during summer were 64% and 97% in CAV and VAV operating modes, respectively, while the corresponding values were 99% and 78% during the winter evaluation, and 59% and 56% during the spring evaluation.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI

Benchmarking State-of-the-Art Theory and Empirical Models of Pionless Neutrino-Argon Scattering in GENIE

Neutrino event generators require a delicate balance between theory and empirically-driven models to achieve reliable simulations. GENIE is the most commonly used generator, bridging theory and experiment in modern neutrino physics. Its flexible framework makes it ideal for comparing different models across all aspects of neutrino interactions—from the nuclear ground state and primary vertex to final-state interactions. Recently, GENIE has incorporated several state-of-the-art, theory-driven models, including spectral-function descriptions of the nuclear ground state, axial form factors from first-principles lattice QCD calculations, and the Liège intranuclear cascade model for simulating final-state interactions. Compared to the previous baseline models in GENIE—such as the local Fermi gas, dipole-like axial form factor, and hA final-state interaction model—the new implementations are more physically realistic and incorporate more complete physics, including nuclear de-excitation. This poster presents the implementation of new models in GENIE and their performance in comparisons among these models against recent MicroBooNE cross-section measurements.

Liu, Liang [Fermilab] (ORCID:000000026753925X)

Benchmarking State-of-the-Art Theory and Empirical Models of Pionless Neutrino-Argon Scattering in GENIE

Neutrino event generators require a delicate balance between theory and empirically-driven models to achieve reliable simulations. GENIE is the most commonly used generator, bridging theory and experiment in modern neutrino physics. Its flexible framework makes it ideal for comparing different models across all aspects of neutrino interactions—from the nuclear ground state and primary vertex to final-state interactions. Recently, GENIE has incorporated several state-of-the-art, theory-driven models, including spectral-function descriptions of the nuclear ground state, axial form factors from first-principles lattice QCD calculations, and the Liège intranuclear cascade model for simulating final-state interactions. Compared to the previous baseline models in GENIE—such as the local Fermi gas, dipole-like axial form factor, and hA final-state interaction model—the new implementations are more physically realistic and incorporate more complete physics, including nuclear de-excitation. This poster presents the implementation of new models in GENIE and their performance in comparisons among these models against recent MicroBooNE cross-section measurements.

Liu, Liang [Fermilab] (ORCID:000000026753925X)

Condition monitoring of wind turbine drivetrains: state-of-the-art technologies, recent trends, and future outlook

As global wind capacity expands, reducing operations and maintenance costs is critical to lowering the levelized cost of energy. This paper explores the state of the art in condition monitoring and prognostic strategies for wind turbine drivetrains, which are among the most failure-prone and maintenance-intensive subsystems. Current diagnostic methodologies are evaluated, covering supervisory control and data acquisition (SCADA) data, high-frequency vibration and acoustic analysis, machine learning and digital twin frameworks. Finally, practical challenges are identified that limit wide-scale industrial adoption, in order to guide future research and industrial efforts.

17 WIND ENERGY

DOE ART Graphite R&D Introduction

Introduction of ART Graphite R&D to include oxidation activities, oxidation resistant graphite, model development, ASME component failure, ASME code development (design rules), ceramic composites, AGC update, molten salt intrusion, split-disk studies, wear testing, and concluding remarks.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS

Material selection and manufacturing for high‐temperature heat exchangers: Review of state‐of‐the‐art development, opportunities, and challenges

Abstract Many energy systems demand heat transfer at high temperatures to keep up with high demand for power, so high‐temperature material that can perform and last under these harsh conditions is needed for heat exchangers. The engineering requirements for these high‐temperature heat exchanger material call for high thermal conductivity, high resistance to fracture, high resistance to creep deformation, environmental stability in environments associated with the application, and high modulus of elasticity while maintaining low cost to make and maintain. Naturally, ceramics are a good solution for this endeavor. In the past, high‐temperature heat exchangers made from ceramics have been used. We provide examples of ceramics in relevant heat exchange applications and provide motivation where additive manufacturing (AM) can improve efficiency. AM for the relevant material is under development, and we provide insight on the AM of ceramic materials and examples of AM heat exchangers keeping cost in mind. The motivation of the review paper is to provide a framework for material and manufacturing selection for high‐temperature heat exchangers for AM to keep up with the demand for better efficiency, better material, better manufacturing, and cost moving forward with AM technology in high‐temperature ceramic heat exchangers.

36 MATERIALS SCIENCE

Uncertainty in inventories for life cycle assessment: State‐of‐the‐art, challenges, and new technologies

Uncertainty is a critical factor that can hinder the quality and potential applications of life cycle assessment (LCA) results. A prominent source of uncertainty stems from the life cycle inventory (LCI) data. Various methodologies exist to estimate the uncertainty associated with LCI data, primarily based on the widely used structured pedigree matrix approach or the computationally intensive Monte Carlo simulation. This perspective review explores how new technologies (e.g., computational algorithms and data collection methods) from data science and related fields can contribute to identifying, quantifying, and reducing uncertainty in LCI modeling. A brief overview of the sources of uncertainty in LCI modeling and how they are addressed in current LCA practice is provided. Additionally, several new technologies are identified, and the potential benefits of their implementation in reducing uncertainties in LCI modeling are discussed. This perspective review concludes by identifying potential areas that require further development for these technologies.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI

Challenges and Opportunities in State‐of‐the‐Art Proteomics Analysis for Biomarker Development From Plasma Extracellular Vesicles

Extracellular vesicles (EVs) are membrane-bound particles secreted by cells, playing crucial roles in intercellular communication. The composition of EVs can undergo changes in response to stress and disease conditions, making them excellent biomarker candidates. However, extracting protein information from EVs can be challenging due to their low abundance in complex biofluids and copurification with contaminant proteins and particles. Techniques to enrich EVs have their strengths and limitations, without one being able to purify EVs to complete homogeneity. This can lead to compromised recovery rates and increased complexity, making data interpretation difficult. In this viewpoint article, we explore the concept that better characterization of EV composition, followed by quantification of EV proteins in complex samples, might be a more viable route for biomarker development. Mass spectrometers can provide reproducible deep coverage of the EV proteome, despite sample impurities. This paradigm shift presents opportunities to integrate advanced bioinformatics tools to refine the EV proteome landscape, identify novel biomarkers, and streamline validation processes in biomarker development. By focusing on leveraging technology rather than achieving absolute purity, this approach can transform current practices and open opportunities for robust biomarker discovery. Herein, we highlight not only such opportunities but also challenges to implement this concept.

Dakup, Panshak P. [Pacific Northwest National Labo

Cost-Benefit Analysis of Electricity Resilience Projects: State of the Art and Gap Analysis

Utilities and regulators must weigh the benefits of electricity resilience projects against their costs, which would be passed on to customers. Cost-benefit analysis (CBA) is an appropriate method for assessing this tradeoff. Here, in this paper we review the literature on CBA of electricity resilience projects and analyze gaps in the available methods and tools. The costs of resilience projects are typically straightforward to estimate but their benefits — particularly the avoided costs of power interruptions — are complex to quantify and monetize. A common perception among practitioners is that current CBA tools are not sufficiently mature to be adopted into real-world practice. We propose an electricity resilience CBA framework consisting of several elements: risks, physical impacts, power interruptions, economic impacts, and resilience projects. While methods for some elements are well-developed, there is a need for novel approaches to value avoided power interruptions, integrate multiple risks and benefit streams, and incorporate uncertainty.

Cost-benefit analysis

Thermodynamics and its prediction and CALPHAD modeling: Review, state of the art, and perspectives

Thermodynamics is a science concerning the state of a system, whether it is stable, metastable, or unstable, when interacting with its surroundings. The combined law of thermodynamics derived by Gibbs about 150 years ago laid the foundation of thermodynamics. In Gibbs combined law, the entropy production due to internal processes was not included, and the 2nd law was thus practically removed from the Gibbs combined law, so it is only applicable to systems under equilibrium, thus commonly termed as equilibrium or Gibbs thermodynamics. Gibbs further derived the classical statistical thermodynamics in terms of the probability of configurations in a system in the later 1800's and early 1900's. With the quantum mechanics (QM) developed in 1920's, the QM-based statistical thermodynamics was established and connected to classical statistical thermodynamics at the classical limit as shown by Landau in the 1940's. In 1960's the development of density functional theory (DFT) by Kohn and co-workers enabled the QM prediction of properties of the ground state of a system. On the other hand, the entropy production due to internal processes in non-equilibrium systems was studied separately by Onsager in 1930's and Prigogine and co-workers in the 1950's. In 1960's to 1970's the digitization of thermodynamics was developed by Kaufman in the framework of the CALculation of PHAse Diagrams (CALPHAD) modeling of individual phases with internal degrees of freedom. CALPHAD modeling of thermodynamics and atomic transport properties has enabled computational design of complex materials in the last 50 years. Our recently termed zentropy theory integrates DFT and statistical mechanics through the replacement of the internal energy of each individual configuration by its DFT-predicted free energy. The zentropy theory is capable of accurately predicting the free energy of individual phases, transition temperatures and properties of magnetic and ferroelectric materials with free energies of individual configurations solely from DFT-based calculations and without fitting parameters, and is being tested for other phenomena including superconductivity, quantum criticality, and black holes. Those predictions include the singularity at critical points with divergence of physical properties, negative thermal expansion, and the strongly correlated physics. Furthermore, those individual configurations may thus be considered as the genomic building blocks of individual phases in the spirit of the materials genome®. This has the potential to shift the paradigm of CALPHAD modeling from being heavily dependent on experimental inputs to becoming fully predictive with inputs solely from DFT-based calculations and machine learning models built on those calculations and existing experimental data through newly developed and future open-source tools. Furthermore, through the combined law of thermodynamics including the internal entropy production, it is shown that the kinetic coefficient matrix of independent internal processes is diagonal with respect to the conjugate potentials in the combined law, and the cross phenomena that the phenomenological Onsager flux and reciprocal relationships are due to the dependence of the conjugate potential of a molar quantity on nonconjugate molar quantities and other potentials, which can be predicted by the zentropy theory and CALPHAD modeling.

42 ENGINEERING

Novel application of the modal strain energy technique for state-of-the-art damping predictions

Structural damping, which measures the energy dissipation of a vibrating structure, is a key modeling input for lightweight structures but is notoriously hard to predict. This work utilizes vibration-based measurements of centimeter-scale coupons and the modal strain energy approach to predict structural damping of a lightly damped structure. The approach was originally validated with panels shorter than a meter in length. This work extends the validation to a 2.75 m beam made of unidirectional and biaxial glass fiber laminates bonded by adhesive. The comparison between three-dimensional finite element model predictions and full-scale experimental measurements of damping show an average error of 5.2% for the first five modes. Additionally, the modal strain energy approach is newly applied with a one-dimensional geometrically exact beam theory model and a two-dimensional sectional analysis solver. This beam approach accurately predicts the damping behavior of the first bending modes but loses accuracy for higher order modes that are dominated by three-dimensional effects. This novel approach provides faster simulations while allowing arbitrary beam cross sections. The paper also investigates traditional and high-force dynamic mechanical analysis to measure structural damping of coupons. Both alternatives show significant errors in attempted validation against the theoretical thermoelastic damping of aluminum coupons.

17 WIND ENERGY