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At least 649 records · Page 36

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DOE OSTI2026

Documentation, assessment, and improvements of fission gas modeling capabilities in BISON

Fission gas behavior critically affects nuclear fuel performance, influencing thermal conductivity, microstructure, swelling, and fuel-cladding interactions. The Simple Integrated Fission Gas Release and Swelling (Sifgrs) model, implemented within the BISON fuel performance code, provides advanced capabilities for modeling these phenomena. This manuscript reviews and assesses Sifgrs’ modular structure and submodels describing intragranular, intergranular, and release mechanisms. The modular implementation enables rapid improvements as our understanding advances and new fuel forms emerge. After an overview of capabilities, we present a comprehensive validation suite, comparing predictions to experimental data from tests under normal and transient conditions, including reproduction of the Vitanza curve. Results demonstrate Sifgrs’ accuracy, robustness, and applicability. Current limitations and ongoing efforts are discussed, including mechanistic, multiscale modeling, uncertainty quantification, and validation within the Nuclear Energy Advanced Modeling and Simulation (NEAMS) program, supporting the safe and efficient use of nuclear fuels.

BISON↗

DOE OSTI2025

Multi-Scale Modeling for Plasma-Enhanced Ammonia Decomposition over Carbides and Nitrides

Ammonia is a carbon-free hydrogen carrier, but its decomposition typically requires high temperatures over costly Ru-based catalysts due to the large barrier for N≡N bond formation. We develop a multiscale framework combining density functional theory, zero-dimensional plasma kinetics, and microkinetic modeling to elucidate how non-thermal plasma (NTP) enables low-temperature NH 3 decomposition over Co-based carbides and nitrides, benchmarked against Ru and Co. Under thermal conditions, all catalysts are limited by N≡N bond formation, with Co 3 C(001) most active owing to its negatively charged surface, strong N* binding, and low activation barriers of N≡N bond formation. Plasma-induced vibrational excitation of NH 3 and its reactive radicals promotes a radical-driven •NH 2 –N* coupling pathway that dominates on Co 3 C(001) and Co 3 N(001), shifting the rate-limiting step to NH 3 (v1) dissociation, increasing turnover frequencies by up to 6 orders of magnitude, and reducing the temperature needed to reach a turnover frequency of 5 s –1 from >680 °C (Ru and Co under thermal condition) to 267 °C (Co 3 C) and 415 °C (Co 3 N). These results identify Co-based carbides and nitrides as promising plasma-active catalysts for energy-efficient hydrogen production from ammonia.

ammonia decomposition↗

DOE OSTI2026

Imaging from Macro to Nanoscale: Multimodal Advances in Chemical and Biomedical Imaging

Imaging increasingly serves as a multiscale framework for linking molecular mechanisms to cellular behavior, tissue architecture, and organ phenotypes in biology and unraveling fundamental processes in chemistry, physics and materials science. This Perspective highlights recent advances in chemical and biomedical imaging across macro-, micro-, and nanoscales, using representative examples published in Chemical and Biomedical Imaging (CBMI). At the macroscale, we discuss chemically selective MRI, including endogenous and exogenous CEST strategies, together with photoacoustic imaging as a hybrid modality with functional and chemical contrast. At the microscale, we consider fluorescence, label-free optical and vibrational imaging, and selected X-ray approaches that expand sensitivity, specificity, and temporal resolution in biological and materials systems. At the nanoscale, we highlight super-resolution fluorescence microscopy, single-molecule methods, tip-enhanced Raman spectroscopy, and correlative imaging strategies that resolve local heterogeneity and molecular organization. Across scales, a common theme emerges that advances in probes, contrast mechanisms, instrumentation, and sample handling are enabling chemically informed imaging that connects molecular specificity with biological context.

multiscale imaging↗

DOE OSTI2026

Substitution-Mediated Calcination of Nickel-Based Cathodes: Decoupling Lithiation and Crystallization

Nickel-based layered cathodes such as LiNiO 2 offer high energy density for lithium-ion batteries, yet improvements in cycling performance and safety are required for practical use–often achieved through manganese and cobalt substitution as in LiNi 0.80 Mn 0.10 Co 0.10 O 2 (NMC811). However, how such substitution impacts calcination, the key process that governs lithiation, structural ordering, crystallization, and ultimately the resulting material properties, remains unclear. Here, in this study, we investigate substitution-mediated calcination dynamics in NMC811 compared to LiNiO 2 using multiscale-correlated in situ spectroscopy and atomistic-to-mesoscale modeling. While both systems progress through the same sequence of intermediates toward the thermodynamically favored layered phase, NMC811 exhibits an earlier onset of layering, concurrent with hydroxide decomposition followed by sluggish crystallization. Modeling reveals that Mn and Co lower the energy barrier for lithium incorporation and ordering but increase the penalty for interlayer gliding, thereby slowing crystal growth at elevated temperatures. This substitution-mediated decoupling of lithiation and crystallization explains the fine-grained microstructure observed in NMC811 versus coarsened particles in LiNiO 2 and establishes a mechanistic framework for predictive microstructure engineering of Ni-based cathodes.

Calcination↗

DOE OSTI2025

Coupled Climate Simulations With E3SM‐MMF

Simulations of the recent historical period from 1950 to 2014 are conducted with E3SM‐MMF, which uses an embedded 2D cloud resolving model that runs efficiently on GPUs in place of traditional parameterizations for cloud and turbulence. Analysis of the climate and variability reveal several aspects where E3SM‐MMF produces smaller biases compared to E3SMv2, including better agreement with the observed evolution of global mean surface temperature, although the representation of ENSO is too weak and fast. Three idealized abrupt CO 2 experiments were also conducted to assess climate sensitivity and feedbacks. These yield three estimates of effective climate sensitivity (4.38, 5.21, and 6.06 K), with a corresponding spread in the shortwave cloud feedbacks. These estimates are on the higher end of sensitivity estimates from CMIP ensembles, and the spread indicates substantial state‐dependent feedbacks. These results demonstrate how multiscale modeling framework (MMF) models can be used for climate relevant experiments and projections by leveraging modern GPU enabled computational platforms. The unique qualities of E3SM‐MMF shown in previous literature are largely still present, but various instances of reduced biases suggest that MMF models have utility in improving future projections.

E3SM↗

DOE OSTI2025

Characterization of Field-Exposed Photovoltaic Modules Featuring Signs of Contact Degradation

Here, this work investigates several photovoltaic (PV) modules that have shown signs of metal contact corrosion due to field exposure in a hot and humid climate. This includes two multicrystalline silicon aluminum back surface field systems with 10 and 14 years of exposure and one monocrystalline silicon passivated emitter and rear cell system with four years of exposure. A comprehensive, multiscale characterization process is used to evaluate these PV modules in great detail. Current–voltage (I−V), Suns-V OC measurements, electroluminescence imaging, infrared imaging, and ultraviolet fluorescence imaging were performed, and locations of interest were cored and analyzed using cross-sectional scanning electron microscopy (SEM). A rigorous, quantitative analysis procedure for the cross-sectional SEM images is proposed and implemented. Careful characterization does reveal that some of these PV modules do indeed exhibit the same classic signs of acetic-acid-based corrosion of the glass frit that is present at the silver/silicon interface, which have been observed previously in PV modules exposed to damp heat in an environmental chamber.

14 SOLAR ENERGY↗

DOE OSTI2025

Gaussian Process Regression under Computational and Epistemic Misspecification

Gaussian process regression is a classical kernel method for function estimation and data interpolation. In large data applications, computational costs can be reduced using low-rank or sparse approximations of the kernel. This paper investigates the effect of such kernel approximations on the interpolation error. We introduce a unified framework to analyze Gaussian process regression under important classes of computational misspecification: Karhunen-Loève expansions that result in low-rank kernel approximations, multiscale wavelet expansions that induce sparsity in the covariance matrix, and finite element representations that induce sparsity in the precision matrix. Furthermore, our theory also accounts for epistemic misspecification in the choice of kernel parameters.

Gaussian process regression↗

DOE OSTI2024

Rapid Design of Cost-Effective Refractory High Entropy Alloys Strengthened by Precipitation

Funded by the ARPA-E ULTIMATE program, this project aims to develop cost-effective refractory high entropy alloys (RHEAs) for gas turbine blades applications at 1300 degree Celsius and above. The alloy design focuses on carbides precipitation strengthening in a strong and ductile solid solution BCC matrix. The goal is to achieve balanced mechanical properties including room temperature ductility & fracture toughness and high temperature strength and creep resistance, while maintaining comparable oxidation resistance and densities to Ni-base superalloys. To accelerate alloy design, multiscale modeling including CALPHAD and first-principles density functional theory (DFT) calculations and machine learning are performed. Specifically, high throughput phase diagram calculations and screening are carried out using CALPHAD; DFT calculations are performed to predict intrinsic ductility, grain boundary strengthening potential, coefficient of thermal expansion (CTE) and temperature-dependent elastic constants. Temperature dependent yield stress, creep strain and CTE are also predicted using machine learning. Down-selected alloys are synthesized in small buttons of about 250g using arc melting for rapid evaluation on microstructure and mechanical properties before employing plasma arc melting and additive manufacturing for producing large ingots. Preliminary computational and experimental results of this project will be presented and future direction in RHEA development will be discussed.

high temperature materials↗

NASA NTRS2013

Genesis of Hurricane Sandy (2012) Simulated with a Global Mesoscale Model

In this study, we investigate the formation predictability of Hurricane Sandy (2012) with a global mesoscale model. We first present five track and intensity forecasts of Sandy initialized at 00Z 22-26 October 2012, realistically producing its movement with a northwestward turn prior to its landfall. We then show that three experiments initialized at 00Z 16-18 October captured the genesis of Sandy with a lead time of up to 6 days and simulated reasonable evolution of Sandy's track and intensity in the next 2 day period of 18Z 21-23 October. Results suggest that the extended lead time of formation prediction is achieved by realistic simulations of multiscale processes, including (1) the interaction between an easterly wave and a low-level westerly wind belt (WWB) and (2) the appearance of the upper-level trough at 200 hPa to Sandy's northwest. The low-level WWB and upper-level trough are likely associated with a Madden-Julian Oscillation.

multiscale processes↗

NASA NTRS2011

Analysis of Ultra High Resolution Sea Surface Temperature Level 4 Datasets

Sea surface temperature (SST) studies are often focused on improving accuracy, or understanding and quantifying uncertainties in the measurement, as SST is a leading indicator of climate change and represents the longest time series of any ocean variable observed from space. Over the past several decades SST has been studied with the use of satellite data. This allows a larger area to be studied with much more frequent measurements being taken than direct measurements collected aboard ship or buoys. The Group for High Resolution Sea Surface Temperature (GHRSST) is an international project that distributes satellite derived sea surface temperatures (SST) data from multiple platforms and sensors. The goal of the project is to distribute these SSTs for operational uses such as ocean model assimilation and decision support applications, as well as support fundamental SST research and climate studies. Examples of near real time applications include hurricane and fisheries studies and numerical weather forecasting. The JPL group has produced a new 1 km daily global Level 4 SST product, the Multiscale Ultrahigh Resolution (MUR), that blends SST data from 3 distinct NASA radiometers: the Moderate Resolution Imaging Spectroradiometer (MODIS), the Advanced Very High Resolution Radiometer (AVHRR), and the Advanced Microwave Scanning Radiometer ? Earth Observing System(AMSRE). This new product requires further validation and accuracy assessment, especially in coastal regions.We examined the accuracy of the new MUR SST product by comparing the high resolution version and a lower resolution version that has been smoothed to 19 km (but still gridded to 1 km). Both versions were compared to the same data set of in situ buoy temperature measurements with a focus on study regions of the oceans surrounding North and Central America as well as two smaller regions around the Gulf Stream and California coast. Ocean fronts exhibit high temperature gradients (Roden, 1976), and thus satellite data of SST can be used in the detection of these fronts. In this case, accuracy is less of a concern because the primary focus is on the spatial derivative of SST. We calculated the gradients for both versions of the MUR data set and did statistical comparisons focusing on the same regions.

sea surface temperature SST)↗

NASA NTRS2018

Production of Negative Hydrogen Ions Within the MMS Fast Plasma Investigation Due to Solar Wind Bombardment

The particle data delivered by the Fast Plasma Investigation instrument aboard National Aeronautics and Space Administration's Magnetospheric Multiscale (MMS) mission allow for exceptionally high-resolution examination of the electron and ion phase space in the near-Earth plasma environment. It is necessary to identify populations which originate from instrumental effects. Using Fast Plasma Investigation's Dual Electron Spectrometers, we isolate a high-energy (approximately kiloelectron volt) beam, present while the spacecraft are in the solar wind, which exhibits an azimuthal drift with period associated with the spacecraft spin. We show that this population is consistent with negative hydrogen ions H− generated by a double charge exchange interaction between the incident solar wind H+ ions and the metallic surfaces within the instrument. This interaction is likely to occur at the deflector plates close to the instrument aperture. The H− density is shown to be approximately 0.2-0.4% of the solar wind ion density, and the energy of the negative ion population is shown to be 70% of the incident solar wind energy. These negative ions may introduce errors in electron velocity moments on the order of 0.2-0.4% of the solar wind velocity and significantly higher errors in the electron temperature.

Magnetospheric Multiscale↗

NASA NTRS2018

In Situ Observation of Magnetic Reconnection Between an Earthward Propagating Flux Rope and the Geomagnetic Field

It has been proposed that, in the near-Earth magnetotail, earthward propagating flux ropes can merge with the Earth's dipole magnetic field and dissipate its magnetic energy. However, the reconnection diffusion region related to this process has not been identified. Here we report the first in situ observation of magnetic reconnection between an earthward propagating flux rope and the closed magnetic field lines connecting to Earth. Magnetospheric Multiscale (MMS) spacecraft crossed a vertical current sheet between the leading edge of the flux rope (negative B(sub z)) and the geomagnetic field (positive B(sub z)). The subion-scale current sheet, super-Alfvénic electron outflow, Hall magnetic and electric field, conversion of magnetic energy to plasma energy (J·E > 0), and magnetic null were observed during the crossing. All the above signatures indicate that MMS detected the reconnection diffusion region. This result is also relevant to other planets with intrinsic magnetosphere.

Magnetospheric Multiscale↗

NASA NTRS2018

Generation of Electron Whistler Waves at the Mirror Mode Magnetic Holes: MMS Observations and PIC Simulation

The Magnetospheric Multiscale mission has observed electron whistler waves at the center and at the edges of magnetic holes in the dayside magnetosheath. The magnetic holes are nonlinear mirror structures since their magnitude is anticorrelated with particle density. In this article, we examine the growth mechanisms of these whistler waves and their interaction with the host magnetic hole. In the observations, as magnetic holes develop and get deeper, an electron population gets trapped and develops a temperature anisotropy favorable for whistler waves to be generated. In addition, the decrease in magnetic field magnitude and the increase in density reduce the electron resonance energy, which promotes the electron cyclotron resonance. To investigate this process, we used expanding box particle-in-cell simulations to produce the mirror instability, which then evolve into magnetic holes. The simulation shows that whistler waves can be generated at the center and edges of magnetic holes, which reproduces the primary features of the MMS observations. The simulation shows that the electron temperature anisotropy develops in the center of the magnetic hole once the mirror instability reaches its nonlinear stage of evolution. The plasma is then unstable to whistler waves at the minimum of the magnetic field structures. In the saturation regime of mirror instability, when magnetic holes are developed, the electron temperature anisotropy appears at the edges of the holes and electron distributions become more isotropic at the magnetic field minimum. At the edges, the expansion of magnetic holes decelerates the electrons, which leads to temperature anisotropies.

Magnetospheric Multiscale↗

NASA NTRSDate not supplied

Geometric Requirements for Modeling Polycrystalline Representative Volume Elements Using the Generalized Method of Cells

To accurately predict the mechanical response of advanced metallic parts, the grain structure of the metal must be considered and coupled to the macroscale in a multiscale model. The size of the microscale representative volume element must be sufficiently large, and the grid used to discretize the microscale must be adequately refined, in order to ensure an accurate and converged solution. The generalized method of cells is used to predict the mechanical properties of polycrystalline representative volume elements of copper containing randomly oriented grains with the properties of a single face-centered-cubic crystal. Moreover, the results of a parametric study are used to conclude the geometric requirements for an objective microscale model, with respect to the elastic stiffness.

Multiscale Modeling↗

NASA NTRSDate not supplied

Guided Design of Alloys

Using multiscale materials modeling, we are designing stronger alloys for the airspace applications. We focus on improving mechanical properties of materials at operating temperature. We employ basic science and fundamental theory for guided design of the next-generation alloys. Among the examples, we consider precipitated superalloys with a local phase transformation strengthening. We acknowledge funding by NASA’s Aeronautics Research Mission Directorate (ARMD) via Transformational Tools and Technologies (TTT) Project.

multiscale↗

NASA NTRSDate not supplied

Guided Design of Alloys: Part 2

Multiscale↗

NASA NTRSDate not supplied

TPS Certification by Analysis: Model-Driven Characterization of Properties and Failure in Woven Thermal Protection Systems

Woven, ablative thermal protection system (TPS) materials provide a robust option for aggressive (re)entries and thus have been baselined for the upcoming Mars Sample Return (MSR) mission's Earth Entry System (EES). The reliability requirements for MSR-EES necessitate understanding of material property variability, which could be significant given the complex structure and anisotropic nature of properties in TPS weaves, as well as the response to potential impact with micrometeoroids or orbital debris during the EES re-entry. The TPS Certification by Analysis effort within the Entry Systems Modeling project seeks to provide computational models and analyses that support the certification against such material-based risks. For the present talk, focus will be given to the characterization of baseline woven TPS material properties and mechanical failure limits, which entails (1) use of computational techniques (e.g., machine learning) to interpret computed tomography images of the weave to generate representative structural models and (2) application of multiscale material modeling approaches to characterize thermomechanical and failure properties.

thermal protection systems↗

NASA NTRSDate not supplied

ICME: The Design of Fit-for-Purpose Materials

With the increased emphasis on reducing the cost and time to market of new materials, ICME (Integrated Computational Materials Engineering) has become a fast growing discipline within materials science and engineering. The vision of ICME is compelling in many respects, not only for the value added in reducing time to market for new products with advanced, tailored materials, but also for enhanced efficiency and performance of these materials. Although the challenges and barriers (both technical and cultural) are formidable, substantial cost, schedule, and technical benefits can result from broad development, implementation, and validation of ICME principles. ICME is an integrated approach to the design of products, and the materials that comprise them, by linking material and structural models at multiple time and length scales. NASA’s Transformational Tools and Technology (TTT) Project sponsored a study (performed by a team led by Pratt & Whitney) in 2016 to define the potential 25-year future state required for integrated multiscale modeling of materials and systems (e.g., load-bearing structures) to accelerate the pace and reduce the expense of innovation in future aerospace and aeronautical systems. This talk will briefly review ICME, the findings of the 2040 Vision study, and discuss NASA’s TTT 2040 implementation activities: with special emphasis on recent accomplishments. The 2040 study, NASA CR 2018- 219771, envisions the development of a cyber-physical-social ecosystem comprised of experimentally verified and validated computational models, tools, and techniques, along with the associated digital tapestry, that impacts the entire supply chain to enable cost-effective, rapid, and revolutionary design of fit-for-purpose materials, components, and systems by enabling the engineer to not only “design-with-the” material but also concurrently “design-the” material.

multiscale analysis↗