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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 685 records · Page 38
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Enhancing hyperspectral EELS analysis of complex plasmonic nanostructures with pan-sharpening

Nanoscale hyperspectral techniques—such as electron energy loss spectroscopy (EELS)—are critical to understand the optical response in plasmonic nanostructures, but as systems become increasingly complex, the required sampling density and acquisition times become prohibitive for instrumental and specimen stability. As a result, there has been a recent push for new experimental methodologies that can provide comprehensive information about a complex system, while significantly reducing the duration of the experiment. In this work, we present a pan-sharpening approach to hyperspectral EELS analysis, where we acquire two datasets from the same region (one with high spatial resolution and one with high spectral fidelity) and combine them to achieve a single dataset with the beneficial properties of both. This work outlines a straightforward, reproducible pathway to reduced experiment times and higher signal-to-noise ratios, while retaining the relevant physical parameters of the plasmonic response, and is generally applicable to a wide range of spectroscopy modalities.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Uncertainty Quantification and Sensitivity Analysis of Low-Dimensional Manifold via Co-Kurtosis PCA in Combustion Modeling

For multi-scale multi-physics applications e.g., the turbulent combustion code Pele, robust and accurate dimensionality reduction is crucial to solving problems at exascale and beyond. A recently developed technique, Co-Kurtosis based Principal Component Analysis (CoK-PCA) which leverages principal vectors of co-kurtosis, is a promising alternative to traditional PCA for complex chemical systems. To improve the effectiveness of this approach, we employ Artificial Neural Networks for reconstructing thermo-chemical scalars, species production rates, and overall heat release rates corresponding to the full state space. Our focus is on bolstering confidence in this deep learning based non-linear reconstruction through Uncertainty Quantification (UQ) and Sensitivity Analysis (SA). UQ involves quantifying uncertainties in inputs and outputs, while SA identifies influential inputs. One of the noteworthy challenges is the computational expense inherent in both endeavors. To address this, we employ the Monte Carlo methods to effectively quantify and propagate uncertainties in our reduced spaces while managing computational demands. Our research carries profound implications not only for the realm of combustion modeling but also for a broader audience in UQ. By showcasing the reliability and robustness of CoK-PCA in dimensionality reduction and deep learning predictions, we empower researchers and decision-makers to navigate complex combustion systems with greater confidence.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Online data-driven changepoint detection for high-dimensional dynamical systems

In this study, the detection of anomalies or transitions in complex dynamical systems is of critical importance to various applications. In this study, we propose the use of machine learning to detect changepoints for high-dimensional dynamical systems. Here, changepoints indicate instances in time when the underlying dynamical system has a fundamentally different characteristic—which may be due to a change in the model parameters or due to intermittent phenomena arising from the same model. We propose two complementary approaches to achieve this, with the first devised using arguments from probabilistic unsupervised learning and the latter devised using supervised deep learning. To accelerate the deployment of transition detection algorithms in high-dimensional dynamical systems, we introduce dimensionality reduction techniques. Our experiments demonstrate that transitions can be detected efficiently, in real-time, for the two-dimensional forced Kolmogorov flow and the Rössler dynamical system, which are characterized by anomalous regimes in phase space where dynamics are perturbed off the attractor at potentially uneven intervals. Finally, we also demonstrate how variations in the frequency of detected changepoints may be utilized to detect a significant modification to the underlying model parameters by utilizing the Lorenz-63 dynamical system.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Elucidating the Role of Electric Fields in Fe Oxidation via an Environmental Atom Probe

Abstract We quantify the effects of intensely applied electric fields on the Fe oxidation mechanism. The specimen are pristine Fe single crystals exposing a variety of surface structures identified by field ion microscopy. These crystals are simultaneously exposed to low pressures of pure oxygen gas, on the order of 10 −7 mbar, while applying intense electric fields on their surface of several tens of volts per nanometer. The local composition of the different surface structures is probed directly and in real time using an Environmental Atom Probe and successfully compared with first principles‐based models. We found that rough Fe{244} and Fe{112} facets are more reactive toward oxygen than compact Fe{024} and Fe{011} facets. Results demonstrate that the influence of an electric field on the oxidation kinetics depends on the timescales that are involved as the system evolves toward equilibrium. The initial oxidation kinetics show that strong increases in electric fields facilitate the formation of an oxide. However, as one approaches equilibrium, high field values mitigate this formation. Ultimately, this study elucidates how high externally applied electric fields can be used to dynamically exploit reaction dynamics at the nanoscale towards desired products in a catalytic reaction at mild reaction conditions.

Lambeets, Sten V. [Physical and Computational Scie↗
DOE OSTI2024

A novel open-source cultivation system helps establish the first full cycle chemosynthetic symbiosis model system involving the giant ciliate Zoothamnium niveum

Symbiotic interactions drive species evolution, with nutritional symbioses playing vital roles across ecosystems. Chemosynthetic symbioses are globally distributed and ecologically significant, yet the lack of model systems has hindered research progress. The giant ciliate Zoothamnium niveum and its sulfur-oxidizing symbionts represent the only known chemosynthetic symbiosis with a short life span that has been transiently cultivated in the laboratory. While it is experimentally tractable and presents a promising model system, it currently lacks an open-source, simple, and standardized cultivation setup. Following the FABricated Ecosystems (EcoFABs) model, we leveraged 3D printing and polydimethylsiloxane (PDMS) casting to develop simple flow-through cultivation chambers that can be produced and adopted by any laboratory. The streamlined manufacturing process reduces production time by 86% and cuts cost by tenfold compared to the previous system. Benchmarking using previously established optimal growth conditions, the new open-source cultivation system proves stable, efficient, more autonomous, and promotes a more prolific growth of the symbiosis. For the first time, starting from single cells, we successfully cultivated the symbiosis in flow-through chambers for 20 days, spanning multiple generations of colonies that remained symbiotic. They were transferred from chamber to chamber enabling long-term cultivation and eliminating the need for continuous field sampling. The chambers, optimized for live imaging, allowed detailed observation of the synchronized growth between the host and symbiont. Highlighting the benefit of this new system, we here describe a new step in the first hours of development where the host pauses growth, expels a coat, before resuming growth, hinting at a putative symbiont selection mechanism early in the colony life cycle. With this simple, open-source, cultivation setup, Z. niveum holds promises for comparative studies, standardization of research and wide adoption by the symbiosis research community.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

All-Atom Modeling and Simulation of Biopolymer Interface: Dual Role of Antifouling Polymer Brushes

Antifouling polymer brushes are well-known for their exceptional resistance to unwanted protein adsorption. While experimental studies have extensively characterized protein–polymer brush interactions, computational investigations remain limited, largely due to the challenges in accurately modeling and integrating these complex, multicomponent systems without resorting to oversimplification. To address this challenge, this study presents one of the most comprehensive and realistic model systems to date, comprising the substrate, grafted polymers, and proteins. Our work interprets the interactions between polymer brush and protein based on realistic modeling without simplification. In particular, this study utilizes molecular modeling and simulation of polycationic and polyzwitterionic brushes─poly(dimethylaminoethyl methacrylate) (PDMAEMA), poly(2-(N-oxide-N,N-dimethylamino)ethyl methacrylate) (PNOMA), and poly(2-(N-3-sulfopropyl-N,N-dimethylammonium)ethyl methacrylate) (PSBMA)─grafted onto α-quartz substrates via polymerization initiator linkers. The brush models were developed to closely replicate experimentally synthesized samples and to provide detailed insights into structural and dynamical changes at the molecular level during protein adsorption. Using steered molecular dynamics simulations, we show that the PSBMA brush, due to its high local density, exhibits the greatest resistance to protein insertion. Cα root-mean-square deviation and interaction pattern analyses further reveal that the PSBMA brush also induces the most significant destabilization of lysozyme, while the PDMAEMA brush enhances protein stability through ion-mediated interactions. The PNOMA brush, while requiring the lowest force for protein adsorption, induces greater protein destabilization than the PDMAEMA brush, primarily due to electrostatic repulsion caused by a short carbon spacer length. Hydration analysis reveals that both the PSBMA brush and the lysozyme interacting with it exhibit the most rapid dehydration, attributed to the brush’s high local chain density, which results in the greatest lysozyme destabilization and the highest adsorption force. These findings highlight the dual role of antifouling polymer brushes: resisting protein adsorption and modulating protein structural dynamics. In conclusion, this study provides valuable insights for the rational design of next-generation antifouling materials and offers a framework for realistic model development in complex multicomponent systems.

Adsorption↗
DOE OSTI2025

Nanoscale engineering and dynamic stabilization of mesoscopic spin textures

Thermalization, while ubiquitous in physics, has traditionally been viewed as an obstacle to be mitigated. In contrast, we demonstrate here the use of thermalization in the generation, control, and readout of “shell-like” spin textures with interacting 13 C nuclear spins in diamond, wherein spins are polarized oppositely on either side of a critical radius. The textures span several nanometers and encompass many hundred spins; they are created and interrogated without manipulating the nuclear spins individually. Long-time stabilization is achieved via prethermalization to a Floquet-engineered Hamiltonian under the electronic gradient field: The texture is therefore metastable and robust against spin diffusion. This enables the state to endure over multiple minutes before it decays. Our work on spin-state engineering paves the way for applications in quantum simulation and nanoscale imaging.

42 ENGINEERING↗
DOE OSTI2020

Modeling Needs for Power Semiconductor Devices and Power Electronics Systems: Preprint

As energy systems move towards wide-spread electrification, penetration of power semiconductor devices and power electronics continues to grow at a rapid pace. This paper attempts to review the state of the art in power semiconductor modeling and the existing state of modeling in general when in it comes to design of devices and systems. The modeling needs for semiconductor devices vary depending on the end goal, and the level of abstraction needed towards model formulation also changes with the size and complexity of system to be designed. Finally, key aspects of thermal design and modeling for power electronics are also discussed.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2026

Giant Magnetostriction in Ferrimagnetic SmFe 5 As 3

Magnetostrictive materials are of interest not only from a fundamental perspective but also for their potential applications, spanning spintronics to energy harvesting. A new magnetostrictive material—SmFe 5 As 3 —reveals a complex interplay between magnetostriction, magnetic properties, and the crystal structure behavior. The ground state of SmFe 5 As 3 is ferrimagnetic, as evidenced by magnetic susceptibility data, band-structure calculations, and XANES measurements. At T m1 = 28 ± 4 K, part of the Fe sublattice reorients, transitioning into a ferromagnetic state. This is followed by an entrance into the paramagnetic state at T m2 = 76 ± 4 K. The effects observed in the magnetic measurements are accompanied by structural phase transitions. All three phases—below T m1 , between T m1 and T m2 , and above T m2 —are described by the same structural motif of the UCr 5 P 3 type (monoclinic space group P2 1 /m), differing only in the degree of deformation of the Fe–As framework. The new material exhibits giant magnetostriction of 2500 x 10 -6 . Dilatometry measurements on a SmFe 5 As 3 single crystal indicate strongly diverse behavior, exhibiting not only negative, but also zero, as well as positive thermo-elastic effects.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Visualizing the strong field–induced molecular breakup of C 60 via x-ray diffraction

Laser-driven dynamics in polyatomic molecules poses a complex many-body problem. Understanding intense light-matter interaction is crucial for steering intramolecular quantum dynamical processes. Here, we record time-resolved x-ray diffraction images of C 60 molecules during and after their interaction with intense near-infrared fields, giving direct access to structural changes of the molecules and their fragmentation in real time. Tuning the intensity of the excitation pulses, we uncover a transition from a weak-field regime of excited but stable molecules to a high-field regime dominated by Coulomb explosion. In the transition region, the molecules expand by up to 50% of their initial size within just 140 fs, with major fragmentation only setting in afterward. This work demonstrates that x-ray diffractive imaging is capable of retrieving time-resolved structural information of large molecules reshaped by intense laser fields. Laser-driven fragmentation is a first step toward observing molecular processes modified by laser fields of increasing intensity.

Schnorr, Kirsten [Paul Scherrer Inst. (PSI), Villi↗
DOE OSTI2020

Structural integrity of additively manufactured stainless steel with cold sprayed barrier coating under combined cyclic loading

Integration of metal additive manufacturing (AM) and cold spray (CS) technologies provide an unprecedented opportunity to manufacture coated material systems with complex geometrical features. The application of these material systems in functionally critical components requires adequate structural integrity, particularly in the presence of cyclic loading. This article researches the multiaxial fatigue (axial-torsional cyclic loading) behavior of a coated material system consisting of 15Cr-5Ni precipitation-hardening stainless steel (15-5 PH SS) substrate additively manufactured by direct metal laser sintering with a layer of chromium carbide nickel (CrC-Ni) barrier coating deposited by CS. The influence of AM and CS-induced residual stresses on fatigue performance of test specimens was thoroughly studied. Additionally, the effect of surface roughness and processes induced defects were considered to explain the crack growth mechanism. Stresses assessed by synchrotron X-ray diffraction indicated a substantial accumulation of residual stresses, particularly in the outer surface of the as-fabricated 155 PH SS specimens. The state of residual stress was changed notably following the deposition of CrC-Ni coating in the axial, hoop, and radial directions of the fatigue test specimen. Also, CS deposition of CrC-Ni coating caused significant improvement in the surface quality of the additively manufactured components. Fatigue test results indicated, CS deposition of CrC-Ni substantially enhances the fatigue life of the AM-produced 15-5 PH SS substrate in all loading conditions, particularly in the high cycle fatigue regime. The improvement in the fatigue life of the specimens with coating was associated with a reduction in equivalent residual stress at the substrate surface and improvement in the specimens' surface condition (i.e., reduced surface roughness). The fractographic analysis of the specimen indicated the cracks tend to initiate in the surface of both as-fabricated and cold-sprayed specimens. However, the mechanism of crack growth changed notably following the deposition of CrC-Ni coating. The cracks tended to propagate in the planes parallel or with a small deviation from the build layers of the AM-produced specimens. On the other hand, deposition of CrC-Ni coating increased the deviation of crack growth plane from the build layers of the substrate.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Measurement of Photoneutrons from Depleted Uranium and Comparison Study Using MCNPX-PoliMi

High-energy photon interrogation is a nondestructive technique that is used to detect special nuclear materials and characterize nuclear waste. The development of such systems is complex and requires Monte Carlo simulations to optimize system performance. Monte Carlo simulations rely on various scattering, absorption, and photonuclear cross-section data. While the scattering and absorption cross-section data have been extensively studied and validated with experiments, the results obtained from photonuclear simulations are often found to underpredict measured results, indicating uncertainties in the photonuclear cross sections themselves. Thus, there is a need for new measured results that can be used to quantify underpredictions in simulations using photonuclear cross-section data. In the present work, we interrogated depleted uranium with a 9-MV electron linac and detected photoneutrons with trans-stilbene organic scintillators. The measurement of photoneutrons with organic scintillators is challenging due to the presence of the intense photon flux, which causes issues such as pulse pile-up, detector saturation, and poor signal-to-background ratio. To mitigate these challenges, we used iron and polyethylene shielding of varying thicknesses around the depleted uranium target and a neural network–based digital pulse processing algorithm to recover neutron and photon information from piled-up events. Our goal was to compare the measured photoneutron count rate with the simulated rate obtained using the MCNPX-PoliMi transport code. For a light output window of 0.28 to 2.67 MeVee (1.66- to 6.85-MeV proton recoil energy), we found that the simulated count rate obtained using the ENDF/B-VII photonuclear cross-section library underpredicts the measured rate by 32.8% 3.2%. Additionally, we compared the simulated and measured photoneutron light output distributions. For the least thicknesses of shielding, the simulation was found to underpredict measurements in the 0.70- to 2.67-MeVee light output window. For the greatest thicknesses of shielding, the simulation was found to underpredict the measurement across the entire light output window of 0.28 to 2.67 MeVee.

98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗
DOE OSTI2020

Metatranscriptomic dynamics after Verticillium dahliae infection and root damage in Olea europaea

Background: The olive tree is of particular economic interest in the Mediterranean basin. Researchers have conducted several studies on one of the most devastating disorders affecting this tree, the Verticillium wilt, which causes substantial economic losses in numerous areas. We analyzed metatranscriptomic samples taken from a previous study conducted on leaves and roots of Olea europaea that were infected with Verticillium dahliae. In addition, we also analyzed mechanically damaged roots. The aim of our approach is to describe the dynamics of the root microbiome after severe perturbations. Results: Our results not only describe the dynamics of the microbial community associated with the disturbance, but also show the high complexity of these systems and explain how this can lead to a conflicting assignment of the various types of parasitism observed in a specific organism. Conclusions: Our findings indicate that this infection, although led by Verticillium, is driven not by a single species, but by a polymicrobial consortium that also includes natural endophytes of the olive tree. This community contains both biotrophic and necrotrophic organisms that alternate and live together during the infection. In addition, opportunistic organisms appear that take profit not from plant tissues, but from new emerging populations of microorganisms. Therefore, this system can be described as a complex biological system composed of different interacting communities. Notably, our work has important considerations when it comes to classifying the type of parasitism of a given species.

Verticillium dahliae↗
DOE OSTI2024

Multi-physics Modeling of Radiative Heat Transfer and Fluid Flow for the Reactor Cavity Cooling System

High-temperature gas-cooled reactors (HTGRs) are notable for their high thermal efficiency and potential for combined heat and power applications. These reactors are particularly appealing due to their advanced passive safety features. HTGRs utilize passive safety systems that function without requiring active components like pumps or compressors during emergencies. These reactor designs depend on a Reactor Cavity Cooling System (RCCS) to manage decay heat removal from the reactor pressure vessel (RPV) during accident conditions. The RCCS consists of vertical rectangular channels known as "risers" or riser ducts positioned around the RPV. These risers receive heat from the RPV through both convective and radiative heat transfer mechanisms. Understanding the interplay of multiple physical phenomena, such as fluid dynamics, heat transfer, and neutron interactions, is essential for the effective design and operation of nuclear reactors, particularly for systems like the RCCS. Multi-physics simulations provide a comprehensive approach to studying these interactions, offering detailed insights and enhancing accuracy. They are especially important in RCCS designs, where the interaction between radiative and convective heat transfer can significantly impact system performance. By leveraging multi-physics simulations, complex reactor behaviors can be modeled without compromising the fidelity of the underlying physical processes. This work aims to establish a robust methodology for coupling multiple physical processes in an air-cooled RCCS. By focusing on validating this multi-physics approach, the study involves designing test cases that simulate various conditions to verify the numerical models employed. The outcomes of this research will provide critical insights for accurately modeling and optimizing complex nuclear systems like the RCCS.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗