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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 415 records · Page 23
All sourcesNASA NTRSDOE OSTI
NASA NTRS2020

Investigating the Effect of Galaxy Interactions on the Enhancement of Active Galactic Nuclei at 0.5<z<3.0

Galaxy interactions and mergers are thought to play an important role in the evolution of galaxies. Studies in the nearby universe show a higher fraction of active galactic nuclei(AGNs)in interacting and merging galaxies than in their isolated counterparts, indicating that such interactions are important contributors to black hole growth. To investigate the evolution of this role at higher redshifts, we have compiled the largest known sample of major spectroscopic galaxy pairs(2381 withΔV<5000 km s−1)at 0.5<z<3.0 from observations in the COSMOS and CANDELS surveys. We identify X-ray and IR AGNs among this kinematic pair sample, a visually identified sample of mergers and interactions, and a mass-, redshift-, and environment-matched control sample for each in order to calculate AGN fractions and the level of AGN enhancement as a function of relative velocity, redshift, and X-ray luminosity. While we see a slight increase in AGN fraction with decreasing projected separation, overall, we find no significant enhancement relative to the control sample at any separation. In the closest projected separation bin(<25 kpc,ΔV<1000 km s−1),we find enhancements of a factor of-+0.940.160.21and-+1.000.310.58for X-ray and IR-selected AGNs, respectively. While we conclude that galaxy interactions do not significantly enhance AGN activity on average over 0.5<z<3.0 at these separations, given the errors and the small sample size at the closest projected separations, our results would be consistent with the presence of low-level AGN enhancement

Ekta A. Shah↗
NASA NTRS2019

Importance of Tree- and Species-Level Interactions With Wildfire, Climate, and Soils in Interior Alaska: Implications for Forest Change Under A Warming Climate

The boreal zone of Alaska is dominated by interactions between disturbances, vegetation, and soils. These interactions are likely to change in the future through increasing permafrost thaw, more frequent and intense wildfires, and vegetation change from drought and competition. We utilize an individual tree-based vegetation model, the University of Virginia Forest Model Enhanced (UVAFME), to estimate current and future forest conditions across sites within interior Alaska. We updated UVAFME for application within interior Alaska, including improved simulation of permafrost dynamics, litter decay, nutrient dynamics, fire mortality, and post-fire regrowth. Following these updates, UVAFME output on species-specific biomass and stem density was comparable to inventory measurements at various forest types within interior Alaska. We then simulated forest response to climate change at specific inventory locations and across the Tanana Valley River Basin on a 2 × 2 km2 grid. We derived projected temperature and precipitation from a five-model average taken from the CMIP5 archive under the RCP 4.5 and 8.5 scenarios. Results suggest that climate change and the concomitant impacts on wildfire and permafrost dynamics will result in overall decreases in biomass (particularly for spruce (Picea spp.)) within the interior Tanana Valley, despite increases in quaking aspen (Populus tremuloides) biomass, and a resulting shift towards higher deciduous fraction. Simulation results also predict increases in biomass at cold, wet locations and at high elevations, and decreases in biomass in dry locations, under both moderate (RCP 4.5) and extreme (RCP 8.5) climate change scenarios. These simulations demonstrate that a highly detailed, species interactive model can be used across a large region within Alaska to investigate interactions between vegetation, climate, wildfire, and permafrost. The vegetation changes predicted here have the capacity to feed back to broader scale climate-forest interactions in the North American boreal forest, a region which contributes significantly to the global carbon and energy budgets.

forest modeling↗
NASA NTRS2022

Cloud Adjustments From Large-Scale Smoke–Circulation Interactions Strongly Modulate the Southeastern Atlantic Stratocumulus-to-Cumulus Transition

Smoke from southern Africa blankets the southeastern Atlantic Ocean from June to October, producing strong and competing aerosol radiative effects. Smoke effects on the transition between overcast stratocumulus and scattered cumulus clouds are investigated along a Lagrangian (air-mass-following) trajectory in regional climate and large eddy simulation models. Results are compared with observations from three recent field campaigns that took place in August 2017: ObseRvations of Aerosols above CLouds and their intEractionS (ORACLES), CLouds and Aerosol Radiative Impacts and Forcing: Year 2017 (CLARIFY), and Layered Atlantic Smoke Interactions with Clouds (LASIC). The case study is set up around the joint ORACLES–CLARIFY flight that took place near Ascension Island on 18 August 2017. Smoke sampled upstream on an ORACLES flight on 15 August 2017 likely entrained into the marine boundary layer later sampled during the joint flight. The case is first simulated with the WRF-CAM5 regional climate model in three distinct setups: (1) FireOn, in which smoke emissions and any resulting smoke–cloud–radiation interactions are included; (2) FireOff, in which no smoke emissions are included; (3) RadOff, in which smoke emissions and their microphysical effects are included but aerosol does not interact directly with radiation. Over the course of the Lagrangian trajectory, differences in free tropospheric thermodynamic properties between FireOn and FireOff are nearly identical to those between FireOn and RadOff, showing that aerosol–radiation interactions are primarily responsible for the free tropospheric effects. These effects are non-intuitive: in addition to the expected heating within the core of the smoke plume, there is also a “banding” effect of cooler temperature (∼1–2 K) and greatly enhanced moisture (>2 g kg−1) at the plume top. This banding effect is caused by a vertical displacement of the former continental boundary layer in the free troposphere in the FireOn simulation resulting from anomalous diabatic heating due to smoke absorption of sunlight that manifests primarily as a few hundred meters per day reduction in large-scale subsidence over the ocean. A large eddy simulation (LES) is then forced with free tropospheric fields taken from the outputs for the WRF-CAM5 FireOn and FireOff runs. Cases are run by selectively perturbing one variable (e.g., aerosol number concentration, temperature, moisture, vertical velocity) at a time to better understand the contributions from different indirect (microphysical), “large-scale” semi-direct (above-cloud thermodynamic and subsidence changes), and “local” semi-direct (below-cloud smoke absorption) effects. Despite a more than 5-fold increase in cloud droplet number concentration when including smoke aerosol concentrations, minimal differences in cloud fraction evolution are simulated by the LES when comparing the base case with a perturbed aerosol case with identical thermodynamic and dynamic forcings. A factor of 2 decrease in background free tropospheric aerosol concentrations from the FireOff simulation shifts the cloud evolution from a classical entrainment-driven “deepening–warming” transition to trade cumulus to a precipitation-driven “drizzle-depletion” transition to open cells, however. The thermodynamic and dynamic changes caused by the WRF-simulated large-scale adjustments to smoke diabatic heating strongly influence cloud evolution in terms of both the rate of deepening (especially for changes in the inversion temperature jump and in subsidence) and in cloud fraction on the final day of the simulation (especially for the moisture “banding” effect). Such large-scale semi-direct effects would not have been possible to simulate using a small-domain LES model alone.

southeast Atlantic Ocean↗
NASA NTRS2022

Cosmological constraints on dark matter interactions with ordinary matter

Dark matter interactions with electrons or protons during the early Universe leave imprints on the cosmic microwave background and the matter power spectrum, and can be probed through cosmological and astrophysical observations. These interactions lead to momentum and heat exchange between the ordinary and dark matter components, which in turn results in a transfer of pressure from the ordinary to the dark matter. We explore these interactions using a diverse suite of data: cosmic microwave background anisotropies, baryon acoustic oscillations, the Lyman-α forest, and the abundance of Milky-Way subhalos. We derive constraints using model-independent parameterizations of the dark matter–electron and dark matter–proton interaction cross sections and map these constraints onto concrete dark matter models. Our constraints are complementary to other probes of dark matter interactions with ordinary matter, such as direct detection, big bang nucleosynthesis, various astrophysical systems, and accelerator based experiments. They exclude sufficiently large cross sections for a large range of dark matter masses, which cannot be accessed by direct-detection experiments due to the overburden from the Earth’s atmosphere or crust.

Manuel A. Buen-Abad↗
NASA NTRSDate not supplied

An Overview of Plume-Surface Interaction Testing and Research

NASA has studied rocket plume-surface interactions caused by spacecraft since the Apollo era to reduce risk to landing vehicles. The study of plume-surface interactions is a multi-discipline effort, spanning aerospace engineering to planetary science. Historical testing for Apollo and Viking produced methods, terms, and datasets that influence the field today. Research conducted over the past two decades has expanded our understanding of plume-surface interaction phenomena, but the problem remains resistant to a robust predictive capability. Contemporary experimental and modeling efforts to understand and retire strategic knowledge gaps will be discussed, with a focus on work conducted under NASA’s Plume-Surface Interaction Project and the upcoming Human Landing System Plume-Surface Interaction Risk Reduction Ground Test.

Wesley A Chambers↗
NASA NTRSDate not supplied

Plume-surface interaction testing for crewed lunar lander risk reduction

Spacecraft conducting propulsive near-surface operations such as landing or initial ascent must consider potential hazards caused by rocket exhaust interacting with planetary regolith. Gas-granular interactions can erode the surface and eject material, altering the landing site, obscuring views of the surface, and creating abrasion or impact risks. The next generation of lunar landers under development for NASA’s Human Landing System program will push us outside Apollo flight experience for plume-surface interaction. Strategic knowledge gaps and poorly constrained flight data inhibit our ability to accurately and precisely predict the plume-surface interaction environment for a given flight vehicle. We present an overview of a lunar relevant, supersonic plume-surface interaction test that will be conducted in 2024 to improve our understanding of lunar PSI and reduce associated risks to the HLS program.

Wesley A. Chambers↗
NASA NTRS2023

Exploring Interactive Visuals for Orbital Debris Report

NASA often produces reports or memos that include complex data and these findings can often be most effectively communicated using dynamic or interactive visualizations. While newsrooms, such as the New York Times, and academic journals, such as Distill, have demonstrated the power of interactivity within a prose context (i.e., not dashboards), NASA is still lagging in this area. A shift towards more interactive NASA publications will require new technology and expertise. In this presentation, we begin to explore the avenues that the Office of Technology, Policy, and Strategy are using to make its reports interactive by using results from the “Cost and benefit Analysis of Orbital Debris Remediation” as initial examples. We share our current findings and aim to start a discussion with other members of the NASA analytics community interested in or currently adding interactivity to Agency products.

data visualization↗
DOE OSTI2024

Analysis and Mitigation of Cascading Outages Using an Interaction Graph Addressing Transient Stability

Cascading outages of power systems pose great threats to system security and reliability, potentially leading to large-scale blackouts. For analysis and mitigation of cascading outages, this paper proposes a transient stability-incorporated interaction graph. This graph statistically quantifies the interactions among line outages and instabilities of generators, which can model propagation paths and patterns of cascading outages. Compared with an interaction graph that only models line outages, this new interaction graph provides important insights on how transient instability occurs along with cascading outages. It also offers more effective strategies for mitigating outage propagation. The proposed interaction graph can be constructed from datasets of historical or simulated cascading events. It is demonstrated on an NPCC 140-bus system with mitigation strategies.

Guo, Zhenping↗
DOE OSTI2025

Selection Algorithm for electron neutrino charged current interactions in SBND

The Short Baseline Neutrino (SBN) program at Fermilab is a joint proposal by three experimental collaborations primarily for the investigation of the cause behind the low-energy electron-like event excess observed by the MiniBoone experiment. This dissertation focuses on the near detector of the project, named the Short Baseline Near Detector (SBND), a Liquid Argon Time Projection Chamber apparatus which will conduct searches for sterile neutrinos in the mass range of 1 ${eV}^2/{c}^4$, as well as provide cross-section measurements for neutrino interactions in argon and perform other beyond the standard model studies.\\ \indent As is the case for all detectors in the program, the SBND will use the Booster Neutrino Beam as its source, which will provide it with both muon and electron neutrinos. Given that the ability to discern between the neutrino flavors will be crucial to the fulfillment of the detector's physics goals, the objective of this work is to provide the collaboration with a tool capable of doing so. As such, we here present the development process for an inclusive selection algorithm for the identification of electron neutrino charged current (CC) events regardless of their interaction channel. This is done through a combination of traditional techniques, such as the implementation of cuts on the reconstructed interaction properties, with the use of the Convolutional Visual Network, a machine learning algorithm capable of classifying particle interactions through the analysis of the topology of their final states. With this approach, we have developed a selection process that is capable of identifying $\nu_e$ CC interactions across a wide range of topologies with 34.4\% efficiency, as well as a purity of 91.2\%, making it especially promising for use in cross section studies.

Freire, Hector Moya [ABC Federal U.] (ORCID:000900↗
DOE OSTI2026

Measuring the neutrino-oxygen neutral current quasielastic cross section using the accelerator neutrino neutron interaction experiment

The Accelerator Neutrino Neutron Interaction Experiment (ANNIE) is a 26-ton gadolinium-doped water Cherenkov detector located on-axis to Fermilab’s Booster Neutrino Beam (BNB). ANNIE is uniquely positioned to perform high-statistics measurements of neutrino-nucleus interactions in water, benefiting from a large neutrino flux due to a short (100-meter) baseline. A central focus of ANNIE’s physics program is the measurement of both charged current (CC) and neutral current (NC) cross sections on water, including neutral current quasielastic (NCQE) and CC-inclusive channels. The NCQE measurement is particularly critical for constraining uncertainties in rare-event searches such as the Diffuse Supernova Neutrino Background (DSNB), where atmospheric $\nu$NCQE interactions constitute a significant and poorly constrained background. This dissertation presents a measurement of the flux-averaged neutrino-oxygen neutral current quasielastic ($\nu$NCQE) cross section using $2.573 \times 10^{20}$~POT of BNB exposure from the 2022 and 2023 beam years. The $\nu$NCQE interaction is identified through the primary $\gamma$-rays produced by nuclear de-excitation of the residual $^{15}$N$^*$ or $^{15}$O$^*$ nucleus following nucleon knockout from $^{16}$O. A dedicated Monte Carlo (MC) re-tuning campaign was conducted using an americium-beryllium (AmBe) calibration source, Michel electrons from stopped muons, and throughgoing dirt muons originating upstream of the detector. This multi-sample approach provided a wide-ranging $\mathcal{O}(\text{MeV})$--$\mathcal{O}(\text{GeV})$ dataset for tuning the simulated detector response, which was subsequently validated against AmBe neutron and Michel electron data for use in the $\nu$NCQE analysis. A dedicated laser calibration campaign was carried out to reduce timing uncertainties across the PMT system, enabling reconstruction of the BNB bunch substructure with sufficient resolution to serve as a background rejection tool. By selecting events in-time with individual neutrino bunches, beam-correlated $\nu$NCQE events are separated from diffuse and accelerator-induced backgrounds, notably skyshine neutrons and externally-originating events, that would otherwise dominate traditional charge-based selections within a small-scale, surface-level, short-baseline detector. A data-driven estimation of the skyshine neutron and external background rates was performed and incorporated into the systematic uncertainty budget. The flux-averaged $\nu$NCQE cross section on oxygen is measured to be $1.57 \pm 0.06\,(\text{stat.})$ $^{+0.91}_{-0.67}\,(\text{syst.})$ $\times 10^{-38}\ \text{cm}^{2}$. A full systematic budget is constructed by propagating uncertainties in the secondary hadronic interaction modeling, background cross section normalizations, detector response, neutrino flux, and the primary $\gamma$-ray emission probabilities from oxygen nuclear de-excitation. An idealized de-excitation model, constructed from existing measurements in the literature is developed to benchmark the predictions of the \textsc{GENIE} event generator. A comparison reveals that \textsc{GENIE} systematically overpredicts the primary $\gamma$-ray emission probability from oxygen de-excitation by a factor of $1.49\times$ for $E_\gamma > 6$~MeV and $3.07\times$ in the $3$--$6$~MeV band. This comparison motivates the dominant systematic uncertainty in this analysis, where a conservative uncertainty of $^{+39.9\%}_{-0\%}$ on the primary $\gamma$-ray signal prediction is assigned. The ANNIE result is consistent with and complementary to existing flux-averaged $\nu$NCQE cross section measurements from T2K and Super-Kamiokande, providing an independent measurement with a different detector, neutrino beam, and analysis methodology. Looking ahead, an upgrade to the ANNIE DAQ infrastructure enabling continuous extended readout will allow a complementary $\nu$NCQE neutron multiplicity measurement, directly relevant to constraining the NCQE background in DSNB searches, competitive with the recent T2K measurement at SK-Gd. The planned Super-SANDI upgrade, deploying a large Water-based Liquid Scintillator (WbLS) volume, will further extend ANNIE's reach to hadronic final states and exclusive NC channels, and enable joint measurements with liquid argon detectors sharing the BNB beamline ahead of DUNE and Hyper-Kamiokande.

Doran, Steven [Iowa State U.]↗
DOE OSTI2026

Pre-Equilibrium De-Excitations for Neutrino-Nucleus Interactions

The Deep Underground Neutrino Experiment (DUNE) is sensitive to MeV-scale energy depositions from low-energy astrophysical neutrinos, including those from core-collapse supernovae. Interpreting these detector signals requires accurate modeling of the nuclear de-excitation that follows from the neutrino-nucleus interaction. The MARLEY (Model of Argon Reaction Low-Energy Yields) event generator specializes in the low-energy regime. MARLEY currently assumes the residual nucleus equilibrates immediately after the primary interaction. This omits the intermediate pre-equilibrium stage in which energy redistributes among nucleons until statistical equilibrium is reached. While pre-equilibrium effects are well established for nucleon-induced reactions, they have not previously been studied for neutrino-nucleus interactions. This work addresses that gap by implementing a two-component exciton model, which is the first dedicated treatment of pre-equilibrium de-excitation for neutrino-nucleus interactions, restructured around MARLEY's existing class hierarchy to prepare for direct integration, including particle-hole state densities, internal transition rates, and pre-equilibrium particle emission. The calculations show encouraging agreement with the TALYS-2.2 nuclear reaction code for neutron-nucleus interactions. We further propose a concrete integration path into the full MARLEY event generator, including derived class structure and an extended event record for pre-equilibrium vertices in support of future reweighting. Remaining work focuses on refining the emission width calculation, adding $\gamma$-ray emission, and completing this integration to quantify the impact of pre-equilibrium effects on the expected low-energy neutrino signals in DUNE and similar experiments.

Visser, Erin [Michigan State U., East Lansing (mai↗
DOE OSTI2026

Investigating Interference Term in DUNE And SBND Neutrino Interactions with ACHILLES

Understanding neutrino-nucleus interactions is critical for conducting precise neutrino oscillation ex- periments. However, uncertainties in neutrino-nucleus cross section measurements and our incomplete understanding of nuclear effects remain a significant challenge in neutrino physics. In this paper, we investigate contributions from quantum interference between one-body and two-body interactions in charged-current quasi-elastic (CCQE) neutrino scattering amplitudes, using the ACHILLES event gen- erator. Simulations are performed using muon neutrino flux from Fermilab’s Booster Neutrino Beam (BNB), as well as Long-Baseline Neutrino Facility (LBNF) flux. We observe the neutrino flux interact- ing with Argon nuclei as detected by the Short Baseline Near Detector (SBND) and DUNE Near Detector (DUNE-ND), both Liquid Argon Time Projection Chambers (LArTPC). We focus on one muon and one proton final states with cascade interactions. We analyze multiple experimental observables including outgoing kinematic variables, energy-momentum transfer variables, and Transverse Kinematic Imbalance (TKI) variables. In this study, we also investigate the effects of PRISM (a method of sampling flux from multiple off-axis angles which creates different neutrino energy spectra). We find that the ratio of in- terference to quasi-elastic contributions gives a non-flat distribution across a 0-3.5 GeV energy range, indicating that effects of interference vary with the neutrino energy sampled. Our ultimate goal is to reduce systematic uncertainties from neutrino interactions when conducting oscillation experiments by working to disentangle the effects of quantum interference from the quasi-elastic signature.

Serumaga, Peera [Fermilab; UC, San Diego] (ORCID:0↗
DOE OSTI2025

Lassa virus protein–protein interactions as mediators of Lassa fever pathogenesis

Viral hemorrhagic Lassa fever (LF), caused by Lassa virus (LASV), is a significant public health concern endemic in West Africa with high morbidity and mortality rates, limited treatment options, and potential for international spread. Despite advances in interrogating its epidemiology and clinical manifestations, the molecular mechanisms driving pathogenesis of LASV and other arenaviruses remain incompletely understood. This review synthesizes current knowledge regarding the role of LASV host-virus interactions in mediating the pathogenesis of LF, with emphasis on interactions between viral and host proteins. Through investigation of these critical protein–protein interactions, we identify potential therapeutic targets and discuss their implications for development of medical countermeasures including antiviral drugs. This review provides an update in recent literature of significant LASV host-virus interactions important in informing the development of targeted therapies and improving clinical outcomes for LF patients. Knowledge gaps are highlighted as opportunities for future research efforts that would advance the field of LASV and arenavirus pathogenesis.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2024

Fast Oxygen Redox Kinetics Induced by CoO 6 Octahedron With π –Interaction in P2–Type Sodium Oxides

Enhancing the kinetics of lattice oxygen redox (LOR) in P2-type layered sodium oxide cathodes is crucial for the advancement of sodium-ion batteries (SIBs) with superior energy and power densities. Electronic structure regulation stands out as a highly effective approach to address the inherent limitations of P2-type layered oxides with LOR, including sluggish kinetics, phase transitions, voltage hysteresis, and local structural distortion. In this work, a strategy involving the introduction of CoO 6 octahedra with π-interaction into Na 0.6 Li 0.1 Fe 0.3–x Co x Mn 0.6 O 2 (x = 0, 0.15, 0.3) cathodes to facilitate Na-ion transport is proposed. Furthermore, the impact of FeO 6 octahedra with σ-interaction in P2-type cathodes on electrochemical performance is comprehensively investigated. Through multimodal in-situ and ex-situ characterization techniques, it is revealed that Co–O with π-interaction effectively mitigates P2-OP4 phase transitions by strengthening Na–O, reduces voltage hysteresis, and stabilizes the local structure. Consequently, Na 0.6 Li 0.1 Co 0.3 Mn 0.6 O 2 demonstrates enhanced Na-ion diffusion kinetics, leading to improved rate performance and a reversible capacity of 55 mAh g –1 at 10 C, significantly outperforming cathodes with Fe–O σ-interaction. Moreover, when coupled with hard carbon, the full cell achieves a remarkable energy density of 395 Wh kg –1 (on cathode) at 0.1 C, with a capacity retention of 75% over 100 cycles at 1 C.

25 ENERGY STORAGE↗
DOE OSTI2025

Empirical evidence that glucan-interacting amino acid side chains within the transmembrane channel collectively facilitate cellulose synthase function

The fundamental mechanism of cellulose synthesis is widely conserved across Kingdoms and depends on cellulose synthases, which are processive, dual-function, family 2 glycosyltransferases (GT-2). These enzymes polymerize glucose on the cytoplasmic side of the plasma membrane and export the glucan chain to the cell surface through an integral transmembrane (TM) channel. Structural studies of active plant cellulose synthases (CESAs) have revealed interactions between the nascent glucan chain and the side chains of polar, charged, and aromatic amino acid residues that line the TM channel. However, the functional consequences of modifying these side chains have not been tested in vivo in CESAs or other processive GT-2s. To test this, we used an established in vivo assay based on genetic complementation of CESA5 in the moss, Physcomitrium patens. For accurate prediction of glucan-interacting amino acid residues, we generated a complete homotrimeric molecular model of PpCESA5 using a combination of homology and de novo modeling. All-atom molecular dynamics-based analyses of contact metrics and interaction energy identified 23 amino acid residues with high propensity to interact with the nascent glucan chain within the TM channel or on the apoplastic surface of PpCESA5. Mutating any one of 18 of these amino acid residues to alanine, thereby removing their side chains, abolished or impaired CESA function, with the strongest effects observed upon the loss of charged amino acid side chains. This provides direct evidence to support the hypothesis that multiple amino acid residues collectively maintain a smooth energy landscape within the TM channel to facilitate glucan translocation.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Chemical interaction and compatibility of uranium mononitride and alumina forming austenitic stainless steel

Uranium mononitride (UN) and alumina forming austenitic (AFA) stainless steel are a potential fuel-cladding combination for the lead-cooled fast reactor (LFR). Chemical compatibility between UN and AFA steel needs to be verified before implementation in a nuclear reactor. Diffusion couple experiments at 823 K and 1023 K were conducted for nonirradiated UN samples in contact with as-cast (no thermally grown Al 2 O 3 ) and preoxidized (with thermally grown Al 2 O 3 ) AFA for 500 and 1000 h in an inert environment. Preoxidized AFA exhibited little to no interaction with all UN samples tested at both 823 K and 1023 K, displaying the stability and capability of the Al 2 O 3 layer to prevent chemical interaction and inter-diffusion with UN. Chemical interaction occurs between UN and as-cast AFA. At 1023 K, an aluminum and nitrogen rich phase (likely AlN) formed along the interface of as-cast AFA and UN samples. At 823 K the AlN phase was not prominently observed due to the reduced diffusivity of aluminum through AFA. The aluminum and nitrogen-enriched phase was also observed in a high temperature pressure-assisted test sample of UN and as-cast AFA thermally treated at 1373 K. Finally, in UN samples doped with a low weight percent of UO 2 (< 3 wt%), AlN was not detected along the interface at either temperatures, and an Al 2 O 3 layer likely formed along the interface and prevented further chemical interaction between UN and as-cast AFA.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Effect of TiN coating on suppressing Ce-Fe interaction under irradiation

Advanced cladding is critical for fast reactors with the adequate thermal conductivity, mechanical stability and radiation tolerance of the cladding base material, corrosion resistance and high temperature coolant compatibility of the cladding surface, and chemical stability of the cladding inner wall against fuel cladding chemical interaction (FCCI). The preliminary results of recent ion irradiation studies of two diffusion-couple samples of cerium (Ce)/oxide-dispersion strengthened steel (ODS) and Ce/TiN/ODS, irradiated with 80 MeV xenon (Xe) ions to 100 displacements per atom (dpa) at 500°C, are summarized. Significant Ce-Fe interaction occurred in the Ce/ODS sample, and no noticeable Ce-Fe interaction was found in the Ce/TiN/ODS sample. It shows the effectiveness of 1-µm TiN diffusion barrier coated by the pulsed laser deposition on suppressing Ce-Fe interaction, a major contributor to FCCI in cladding. Here, density function theory (DFT) calculations of the impurity diffusivities of Ce and Fe within the Ti sublattice of TiN were performed to assist a mechanistic understanding of the experimental results.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2025

COCOMO2: A Coarse-Grained Model for Interacting Folded and Disordered Proteins

Biomolecular interactions are essential in many biological processes, including complex formation and phase separation processes. Coarse-grained computational models are especially valuable for studying such processes via simulation. Here, we present COCOMO2, an updated residue-based coarse-grained model that extends its applicability from intrinsically disordered peptides to folded proteins. This is accomplished with the introduction of a surface exposure scaling factor, which adjusts interaction strengths based on solvent accessibility, to enable the more realistic modeling of interactions involving folded domains without additional computational costs. COCOMO2 was parametrized directly with solubility and phase separation data to improve its performance on predicting concentration-dependent phase separation for a broader range of biomolecular systems compared to the original version. COCOMO2 enables new applications including the study of condensates that involve IDPs together with folded domains and the study of complex assembly processes. COCOMO2 also provides an expanded foundation for the development of multiscale approaches for modeling biomolecular interactions that span from residue-level to atomistic resolution.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗