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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 91 records · Page 5
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

A Multi-Region SEIR Model Incorporating Inter-County Mobility and Time-Dependent Transmission Dynamics: Application to COVID-19 Disease Outbreak Data in North Carolina.

Classical infectious disease compartmental models typically do not incorporate spatial heterogeneity or mobility. We develop a multi-region susceptible-exposed-infected-recovered (SEIR) model in which disease dynamics are coupled via inter-region mobility and the transmission rate is both region and time dependent. We calibrate the model using rolling averages of daily COVID-19 data in all 100 North Carolina counties. Mobility parameters are prescribed using daily inter-county commuter data. The number of transmission rate parameters is substantially reduced by hypothesizing that the dynamics correlate with county-level population density. Parameter estimation is carried out using several objective functions with error terms at different scales. An additive combination of least squares error at the county-level and the state-level, along with a quadratic transmission rate polynomial, yields the lowest overall error at both spatial scales. The calibrated model is used to simulate regional effects of perturbing disease transmission rates in adjacent counties and to illustrate effects of the state’s mobility infrastructure on disease dynamics and spread for a new disease outbreak.

COVID-19 modeling↗
DOE OSTI2025

An integrated integral projection model ( IPM 2 ) to disentangle size‐structured harvest and natural mortality

Abstract Body size is one of the most important traits governing individual‐level demographic rates and modulating population‐level processes. Multiple size‐dependent demographic rates can simultaneously change population structure, so distinguishing their individual contributions to overall population dynamics remains a challenge. Disentangling size‐dependent harvest rates from other demographic rates is critical for assessing the impact of removal on populations of invasive species. Inference about invasive populations can be difficult, however, as observations are often collected opportunistically as part of removal programs, rather than experimentally designed. Yet accurate inference is essential for understanding the feasibility of population suppression and optimising management decisions. We develop an integrated integral projection model (IPM 2 ) that leverages the strengths of the integrated population model and integral projection model to enable inference about complex, size‐structured demographic rates from imperfect observations. We apply the IPM 2 in the context of invasive European green crab ( Carcinus maenas ), a species for which individual body size strongly regulates both the observation‐generating process and latent, population dynamics. The IPM 2 facilitates the distinct estimation of green crab size‐structured harvest and natural mortality rates, parameters for which no explicit data is collected and that are unidentifiable in component datasets of the integrated population model. The model represents how the green crab population changes over time, providing the first estimates of size‐structured abundance of this high‐priority species. By forecasting the stable size distribution and equilibrium population size under varying removal efforts, we demonstrate that extremely high levels of removal effort can reduce the equilibrium green crab population size. Yet these high mortality rates also shift the stable size distribution and increase the equilibrium abundance of smaller crabs, since size‐selective removal alters intraspecific interactions. The ecological outcome of this shift in size structure will be variable, as green crab size modulates only some of its interactions with other species. These results highlight the value of the IPM 2 framework for inferring complex population dynamics with information needs that outpace information in individual observational datasets, providing a path forward for accurate assessment of conservation programs.

Keller, Abigail G. [Department of Environment Scie↗
DOE OSTI2025

Strain-associated nanoscale fluctuating lithium transport within single-crystalline LiNi 1/3 Mn 1/3 Co 1/3 O 2 cathode particles

Solid-state lithium diffusion dynamics are critical for the rate capability and longevity of Li-ion batteries. Conventionally, nanoscale lithium diffusion within individual battery particles has been simplified as being primarily driven by concentration gradients, despite the associated processes inducing local lattice expansion, contraction, and strain fields. Using operando scanning transmission soft X-ray microscopy with high spatial resolution and chemical sensitivity to track nanoscale intraparticle lithium transport, and post-cycling Bragg coherent diffraction X-ray imaging to directly reveal three-dimensional intraparticle strain fields, we uncover strain-associated lithium transport dynamics within single-crystalline LiNi 1/3 Mn 1/3 Co 1/3 O 2 (scNMC) particles during cycling. Contrary to the expected thermodynamic solid-solution behavior of scNMC, our observations reveal near-uniform but fluctuating regions of lithium-dense and lithium-dilute areas during cycling. These fluctuations suggest that nanoscale lithium diffusion can proceed counter to concentration gradients. Additionally, we demonstrate that an increased presence of lithium-dilute regions near the surface enhances lithium surface insertion kinetics, emphasizing the importance of controlling surface lithium distribution to improve rate performance. Our study provides insights into nanoscale solid-state ion transport, with potential applications in batteries, solid-state fuel cells, and memristors.

Lee, Danwon [Seoul National Univ. (Korea, Republic↗
DOE OSTI2024

Influence of high-strain-rate compression and subsequent heat treatment on (TiNbZr) 89 (AlTa) 11 refractory high-entropy alloys: Dynamic-mechanical behavior and microstructural changes

This study explored the dynamic-mechanical behavior of a novel low-density (TiNbZr) 89 (AlTa) 11 refractory high-entropy alloy (RHEA) across strain rates ranging from 1.0×10 3 to 3.5×10 3 s –1 . A significant increase in the yield and ultimate compressive strengths with rising strain rates up to 3.0×10 3 s –1 was observed and attributed to enhanced dislocation activities and stress-induced microstructural transformations. The formation of the B2 phase and Zr 5 Al 3 precipitates was found to be crucial in bolstering the alloy strength at high strain rates. Beyond strain rates of 3.0×10 3 s –1 , a decrease in strength occurred due to thermal softening and strain localization. Microstructural analyses at 3.5×10 3 s –1 revealed grain refinement, the development of micro shear bands, and dislocation tangles, which were indicative of dynamic recrystallization. Besides, the findings also revealed that the post-dynamic compression heat treatment further enhanced the hardness and microstructural stability of the alloy. These results highlight the potential of the (TiNbZr) 89 (AlTa) 11 RHEA for applications requiring materials with high strength-to-weight ratios, particularly in dynamically loaded environments. It is expected that the results of this study will further advance our fundamental understanding of the behavior of RHEAs under extreme conditions, thereby opening new avenues for material innovation.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Cavity Controlled Upconversion in CdSe Nanoplatelet Polaritons

Exciton-polaritons provide a versatile platform for investigating quantum electrodynamics effects in chemical systems, such as polariton-altered chemical reactivity. However, using polaritons in chemical contexts will require a better understanding of their photophysical properties under ambient conditions, where chemistry is typically performed. Here, we used cavity quality factor to control strong light–matter interactions and in particular the excited state dynamics of colloidal CdSe nanoplatelets (NPLs) coupled to a Fabry– Pérot optical cavity. With increasing cavity quality factor, we observe significant population of the upper polariton (UP) state, exemplified by the rare observation of substantial UP photoluminescence (PL). Excitation of the lower polariton (LP) states results in upconverted PL emission from the UP branch due to efficient exchange of population between the LP, UP and the reservoir of dark states present in collectively coupled polaritonic systems. In addition, we measure time scales for polariton dynamics ~100 ps, implying great potential for NPL based polariton systems to affect photochemical reaction rates. State-of-the-art quantum dynamical simulations show outstanding quantitative agreement with experiments, and thus provide important insight into polariton photophysical dynamics of collectively coupled nanocrystal-based systems. These findings represent a significant step toward the development of practical polariton photochemistry platforms.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2026

California Price Response Potential Study

California's energy landscape is undergoing a significant transformation, driven by the increasing integration of renewable energy sources, the increased adoption of distributed energy resources, the electrification of end-use loads, and the growing need for grid efficiency. To address these challenges, recent revisions to the State’s Load Management Standards (LMS) require all of California’s large utilities and community choice aggregators (CCAs) to offer dynamic electricity pricing options to customers by 2027. Dynamic pricing, which involves varying electricity rates based on real-time supply and demand conditions, offers a promising solution for optimizing grid operations, reducing costs, and incentivizing efficient use of grid capacity. Effective implementation of dynamic pricing requires understanding the potential impacts on customer bills, system load, and the cost-effectiveness of automation technologies. This study aims to evaluate the load response of various end-use devices to hourly dynamic prices. The end-uses studied here are space cooling, space heating, water heating, crop irrigation, pool and spa pumps, and electric vehicle (EV) charging, all for both residential and commercial applications, except for crop irrigation. In 2030, these end uses are forecasted to account for 18% of annual electricity demand in the state, but 40% of demand in the peak net load hour. By modeling possible price-responsive load dispatch algorithms and assessing the resulting impacts on both individual bills and the overall grid, we seek to inform policymakers and utilities about the potential benefits and challenges associated with dynamic pricing, and considerations for the design of dynamic pricing tariffs. Additionally, we will explore the cost effectiveness of adopting automation technologies to enable devices to respond more effectively to real-time price signals. This study considers a range of price profiles, accounting for differences across utilities and customer classes, and presents scenarios for dynamic price design via variation in the percentage of total customer electric costs that are allocated dynamically (versus constituting a fixed portion of the hourly volumetric price). We present results focused primarily on 2030, forecasting electricity prices under both low and high-cost scenarios, to inform longer-term tariff design considerations. We design tariffs by starting with 2019 prices that were calculated according to CalFUSE guidance (CPUC, 2022) and that have been used in recent studies; these prices are all-in volumetric rates that vary by utility and are revenue-neutral to each customer class. They are developed by considering six electricity cost components that are allocated hourly based on system load indicators (gross and net load, and wholesale prices). These prices are forecasted to 2030 for low and high cost scenarios, considering recent trends in total electricity costs with and without years of substantial wildfire mitigation investments. These tariffs, which allocate all costs on an hourly basis, are considered our “Full” dynamic tariff design scenario, while two additional scenarios explore allocating a portion of costs as a flat volumetric charge: the “Medium” scenario allocates 50% of revenue dynamically (and keeps 50% flat), while the “Mild” scenario allocates 20% of revenue dynamically. The 20% dynamic allocation on the Mild scenario aims to represent a case where only the marginal operating costs of the grid are included in the dynamic price.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2025

Fuel recycling and impurity characteristics in long-pulse H-mode plasmas with full metal and dynamically coated walls on EAST

We report the basic behaviors of fuel recycling and impurity accumulation during >100 s long-pulse H-mode plasma under full metal wall conditions on EAST. Significant fuel recycling and impurity rising, particularly from heavy impurities, have been observed when operating with a bare metal wall or a deteriorate real-time coated wall, which severely limits the duration of H-mode discharges. To address this issue, a novel dynamic wall coating technique combining feedforward and feedback controls has been successfully developed. The feedforward control presets the Li powder injection rate based on prior experimental observations, whereas the feedback control dynamically modulates the Li injection rate in response to real-time Li-II line emission measurements. Using this approach, a 605 s H-mode plasma has been achieved with fuel recycling and impurity level maintained stable. This result extends the previous record of a 403 s long-pulse H-mode plasma Gong et al (2024 Nucl. Fusion 64 112013) by over 200 s. It demonstrates the effectiveness of the dynamic powder injection technique in controlling fuel recycling and impurities accumulation, while prolonging plasma duration. These findings offer valuable insights into potential applications of other low-Z powder, such as boron, in ITER.

fuel recycling↗
DOE OSTI2025

Spin-on deposition of amorphous zeolitic imidazolate framework films for lithography applications

Amorphous zeolitic imidazolate framework (aZIF) films have been recently introduced as resists for electron beam and extreme ultraviolet lithography. aZIFs are also being considered for separation applications, including thin film membranes. However, the reported methods for aZIF deposition are currently based on highly empirical trial-and-error approaches that hinder control of film composition, thickness and uniformity as well as scale-up and transferability to different coating geometries. This work presents a method for depositing aZIF films with controllable thickness using dilute precursors mixed immediately before encountering the substrate. Importantly, the method is amenable to quantitative analysis by computational fluid dynamics to extract intrinsic deposition rates and limiting reactant transport diffusivities, enabling predictive physics-based modeling of the deposition process. This allows the deposition method to be adapted for spin coating on silicon wafers to prepare high-quality aZIF films with consistently controlled thickness. Using this approach, high-resolution resist performance and wafer-scale use for beyond extreme-ultraviolet lithography of aZIF films is demonstrated.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2025

Chemical templates of the Central Molecular Zone

Context . The Central Molecular Zone (CMZ) of the Milky Way exhibits extreme conditions, including high gas densities, elevated temperatures, enhanced cosmic-ray ionization rates, and large-scale dynamics. This makes it a perfect laboratory for astrochemical studies. With large-scale molecular surveys revealing increasing chemical and physical complexity in the CMZ, it is essential to develop robust methods to decode the chemical information embedded in this extreme region. Aims . A key step to interpreting the molecular richness found in the CMZ is building chemical templates tailored to its diverse conditions. In particular, understanding how CMZ environments affect shock and protostellar chemistry is crucial. The combined impact of high ionization, elevated temperatures, and dense gas remains insufficiently explored for observable tracers. Methods . For this study, we utilized UCLCHEM , a gas-grain time-dependent chemical model, to link physical conditions with their corresponding molecular signatures and identify key tracers of temperature, density, ionization, and shock activity. To achieve this, we ran a grid of models of shocks and protostellar objects representative of typical CMZ conditions, focusing on 24 species, including complex organic molecules. Results . Shocked and protostellar environments show distinct evolutionary timescales (≲10 4 vs. ≳10 4 years); 300 K emerges as a key temperature threshold for chemical differentiation. We find that cosmic-ray ionization and temperature are the main drivers of chemical trends. HCO + , H 2 CO, and CH 3 SH trace ionization, while HCO, HCO + , CH 3 SH, CH 3 NCO, and HCOOCH 3 show consistent abundance contrasts between shocks and protostellar regions over similar temperature ranges. Conclusions . We characterized the behavior of 24 species in protostellar and shock-related environments. While our models underpredict some complex organics in shocks, they reproduce observed trends for most species, supporting scenarios involving a need for recurring shocks in Galactic Center clouds and enhanced ionization toward Sgr B2(N2). Future work should assess the role of shock recurrence and metallicity in shaping chemistry.

Galaxy: center↗
DOE OSTI2026

Versatile High-Gain Low-Noise Readout ASIC for Silicon Microstrip Tracking Detectors

This work presents Turpial, a custom-designed low- power front-end readout ASIC for microstrip silicon sensors. Implemented in 130 nm CMOS technology, the chip integrates 64 identical readout channels, each including a configurable charge-sensitive amplifier, a bipolar pulse shaper, a 32-sample 50 Msps analog memory, and a 12-bit RC-hybrid SAR ADC operating at 1 Msps. To satisfy the target power budget of 5 mW per channel, the architecture employs a time-decoupled readout scheme in which fast transient signals are first captured in the analog memory and subsequently digitized at a lower rate. Turpial supports a wide dynamic range from 1 kℎ+ to 1 Mℎ+ while maintaining low noise performance, targeting an equivalent noise charge (ENC) below 200 𝑒−including the sensor, and providing a maximum gain of 1500 mV/fC. A digital block manages slow control, data acquisition, and data serialization through dual CML 300 Mb/s serializers. In addition, an on-chip reference circuit, based on a sub-1 V bandgap reference and an integrated LDO regulator, eliminates the need for external reference circuitry. Experimental results demonstrate that both the individual building blocks and the fully integrated ASIC meet the design specifications.

Hernandez, Hugo [Stanford University] (ORCID:00000↗
DOE OSTI2024

The Transactive Energy Network Template Metamodel

While transactive energy, which is defined as an allocation of electricity based on dynamically discovered values or prices, has been extensively studied, its uptake and use has been slow. This report describes a tool, the transactive network template, which should hasten the creation and uptake of transactive energy networks. Some basic principles of transactive energy are familiar from existing wholesale electricity markets. Locational prices are calculated today for zones within bulk electric transmission systems. Locational prices differ while accounting for the locational costs of electricity generation and the losses and constraints incurred when electricity is transmitted from generators and distributed to consumers. A transactive energy network might include these transmission zones. However, current research strives to apply transactive energy also in electricity distribution circuits, buildings, and even for individual generating and consuming devices. At the same time, researchers explore how to apply transactive energy in real time during increasingly shorter time intervals. Automated computational agents become necessary as transactive energy becomes applied to smaller circuit zones and at faster dynamic timescales. A transactive energy network is an example of a multi-agent system. Each zone in the network is represented by its transactive agent, which makes decisions for and acts on behalf of a business entity that is responsible for and manages one of the circuit regions. A transactive energy network is also an example of a decentralized, distributed control system. Control decisions and responsibilities are distributed among the network’s transactive agents. The transactive agents are independent; that is, there typically is no centralized authority or oversight function. Instead, transactive agents exchange transactive signals and thereby negotiate the prices and quantities of electricity that they will exchange. Initially, the circuit regions and responsibilities of transactive agents appear to be very dissimilar. Each circuit region may comprise transmission, distribution, or building-level circuits. Each has a unique position and electrical connectivity within the transactive energy network. Each possesses unique assets that either generate or consume electricity, and these (e.g., renewable energy generator, diesel generator, aggregate utility load, building load, space conditioning, refrigerator, etc.) may further differ in their price flexibility and in their strategies for responding to dynamic electricity prices. Given such diversity, an implementer’s first inclination might be to start from scratch to define all these devices and to engineer their seemingly unique interactions. Given that each implementer’s perspective may be narrow within a transactive energy network, it is unlikely that uniquely engineered systems would interact well. This is where the transactive network template is applicable. The transactive network template is a metamodel that has been developed to guide implementers as they configure their own transactive agent within a network of such agents. The object-oriented design of the transactive network template provides basic code object types that may be used and extended by implementers to represent each of the assets in their circuit region. These objects further facilitate the transactive agent’s necessary computations, which are divided among responsibilities to schedule power usage, balance electric supply and demand, and coordinate the exchange of electricity with the other transactive agents. This report addresses the conceptual transactive network template design. Implementers are directed to more formal design documents and reference implementations. A Python™-based1 reference implementation of the transactive network template has been coded, and three implementations have been configured to represent a national laboratory and two university campuses. Version 2 of the transactive node template generalizes the market class and its methods to facilitate multiple, and more diverse market coordination mechanisms than were facilitated by and demonstrated using Version 1. Version 3 includes new Appendix B, which addresses the designs of methods that would make dynamic prices track approved electricity rates. In the future, the author wishes to make the transactive network template more generally applicable to networks that require more accurate power flow. Development of the transactive network template is jointly funded by the U.S. Department of Energy (DOE) Energy Efficiency and Renewable Energy and the DOE Office of Electricity. In late 2015, one of the first projects to be funded by the DOE Grid Laboratory Modernization Laboratory Consortium was the Clean Energy and Transactive Campus project, led by Pacific Northwest National Laboratory. DOE funds were matched by an investment by the Washington Department of Commerce through its Clean Energy Fund. The transactive network template was developed to guide the implementation of transactive energy networks within this project’s scope.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2024

A Model for Pair Production Limit Cycles in Pulsar Magnetospheres

Abstract It was recently proposed that the electric field oscillation as a result of self-consistent e ± pair production may be the source of coherent radio emission from pulsars. Direct particle-in-cell simulations of this process have shown that the screening of the parallel electric field by this pair cascade manifests as a limit cycle, as the parallel electric field is recurrently induced when pairs produced in the cascade escape from the gap region. In this work, we develop a simplified time-dependent kinetic model of e ± pair cascades in pulsar magnetospheres that can reproduce the limit-cycle behavior of pair production and electric field screening. This model includes the effects of a magnetospheric current, the escape of e ± , as well as the dynamic dependence of pair production rate on the plasma density and energy. Using this simple theoretical model, we show that the power spectrum of electric field oscillations averaged over many limit cycles is compatible with the observed pulsar radio spectrum.

Astronomy & Astrophysics↗
DOE OSTI2025

Pressure-Modulated Energy Transfer Dynamics in Mn 2+ -Doped CdS/ZnS Core/Shell Quantum Dots

Transition metal doping in semiconductor quantum dots (QDs) significantly impacts their optical properties, thus expanding the range of their potential optoelectronic applications. This study investigates the pressure-dependent energy transfer dynamics in Mn 2+ -doped CdS/ZnS core/shell QDs, focusing on how external hydrostatic pressure modulates these dynamics and optical properties. By synthesizing Mn 2+ -doped QDs with varying Mn 2+ doping concentrations, we explore the effects of the pressure on photoluminescence (PL) spectra and energy transfer efficiency. Our study reveals that increasing pressure induces a blueshift in the QD host bandgap PL and a redshift in the Mn 2+ dopant PL. The pressure-induced shifts highlight a unique modulation mechanism where the energy transfer efficiency decreases with pressure due to reduced wave function overlap between host excitons and Mn 2+ dopants. Detailed analysis of the PL quantum yields and energy transfer rate constants provides insights into these dynamics, suggesting that the pressure can effectively and reversibly regulate the energy transfer efficiencies and rates. In conclusion, these results have implications for developing pressure-sensitive configurable devices and exploring pressure-induced phenomena in doped nanomaterials.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Unravelling Microstructure Selection in an Additively Manufactured Eutectic High‐Entropy Alloy

High-entropy alloys (HEAs) are promising candidates for advanced structural applications due to their excellent mechanical properties. Additive manufacturing (AM), with its rapid solidification conditions, enables the creation of unique nonequilibrium microstructures. To fully leverage the synergy between AM and HEAs, understanding how processing affects structure and properties is essential. Here, how solidification rate influences microstructure evolution and phase transformation pathway in laser additively manufactured AlCrFe2Ni2 eutectic HEAs is investigated. By increasing the laser scan speed and hence the solidification rate, distinct solidification modes evolving from coupled eutectic to anomalous eutectic and eventually to single-phase solidification are revealed. These transitions result in distinct microstructures and a wide range of mechanical properties. Thermodynamic modeling and molecular dynamics simulations reveal that low cooling rates allow for sufficient atomic diffusion and phase separation, facilitating coupled eutectic growth. In contrast, rapid cooling suppresses diffusion and destabilizes the solid–liquid interface, promoting anomalous or single-phase solidification. This integrated experimental and computational approach provides a multiscale understanding of solidification mechanisms in HEAs and underscores how kinetic effects can over-ride thermodynamic predictions under nonequilibrium conditions. Furthermore, these results demonstrate that AM can serve as a powerful tool to design HEAs with tailored microstructures and properties.

36 MATERIALS SCIENCE↗
DOE OSTI2024

A Self-Healing, Flowable, Yet Solid Electrolyte Suppresses Li-Metal Morphological Instabilities

In this article, lithium metal (Li 0 ) solid-state batteries encounter implementation challenges due to dendrite formation, side reactions, and movement of the electrode–electrolyte interface in cycling. Notably, voids and cracks formed during battery fabrication/operation are hot spots for failure. Here, a self-healing, flowable yet solid electrolyte composed of mobile ceramic crystals embedded in a reconfigurable polymer network is reported. This electrolyte can auto-repair voids and cracks through a two-step self-healing process that occurs at a fast rate of 5.6 µm h -1 . A dynamical phase diagram is generated, showing the material can switch between liquid and solid forms in response to external strain rates. The flowability of the electrolyte allows it to accommodate the electrode volume change during Li 0 stripping. Simultaneously, the electrolyte maintains a solid form with high tensile strength (0.28 MPa), facilitating the regulation of mossy Li 0 deposition. The chemistries and kinetics are studied by operando synchrotron X-ray and in situ transmission electron microscopy (TEM). Solid-state NMR reveals a dual-phase ion conduction pathway and rapid Li + diffusion through the stable polymer-ceramic interphase. This designed electrolyte exhibits extended cycling life in Li 0 –Li 0 cells, reaching 12 000 h at 0.2 mA cm -2 and 5000 h at 0.5 mA cm -2 . Furthermore, owing to its high critical current density of 9 mA cm -2 , the Li 0 –LiNi 0.8 Mn 0.1 Co 0.1 O 2 (NMC811) full cell demonstrates stable cycling at 5 mA cm -2 for 1100 cycles, retaining 88% of its capacity, even under near-zero stack pressure conditions.

25 ENERGY STORAGE↗
DOE OSTI2026

Explainable tokamak-agnostic forecasting of fusion plasma instability via megahertz turbulent fluctuations

Scientific applications of artificial intelligence (AI) often remain limited by device-specific training and unexplained “black-box” approaches, creating fundamental barriers to cross-system generalization. This challenge is critical for nuclear fusion, where future reactors will have limited operational data for AI training. Here, we demonstrate that our neural network, trained solely on megahertz-scale turbulence measurements from one machine (DIII-D), forecasts Type-I edge localized mode (ELM) onsets in a different tokamak (KSTAR) through zero-shot weight transfer following physics-consistent preprocessing without device-specific retraining. Through an explainable AI framework combining gradient-weighted class activation mapping with physics validation, we reveal that our network can internalize physics relationships governing the ELM instabilities rather than memorizing device-specific patterns. The network perceives spatiotemporal features that correlate consistently with independently calculated instability growth rates, magnetohydrodynamic stability limits, and pedestal structure dynamics. Statistical analyses of dimensionally-reduced saliency features reveal the identical triangular features between the saliency representations, instability growth rates, and prediction probability across tokamaks, providing evidence that our forecasting system can show tokamak-agnostic generalization. This work contributes to a foundation for explainable scientific AI systems, where cross-system developments are essential for transcending traditional domain-specific constraints.

AI↗
DOE OSTI2025

Impact of nutritional history, prey quality, and quantity on grazing and photophysiological responses in the mixoplanktonic dinoflagellate Karenia brevis

The mixotrophic toxic dinoflagellate Karenia brevis forms red tides almost annually along Florida's Gulf coast. We hypothesize that the nutritional status and abundance of its prey, the picocyanobacterium Synechococcus , will affect its feeding rates and growth responses, with implications for bloom dynamics. This study investigated how prey nutritional quality and quantity (absolute and relative) impact grazing rates by K. brevis initially exponentially growing and in nitrogen (N)-limited conditions, and how grazing, in turn, affects the photophysiological responses of predator and prey. Prey quality was manipulated by providing Synechococcus grown under different ratios of N : phosphorus (P). Synechococcus quality did not significantly affect ingestion rates (measured as prey death rate) but grazing rates increased with increasing prey : grazer ratios (R 2 = 0.7). Compared to control, the growth of exponentially growing grazers doubled when Synechococcus was provided, whereas there was no growth enhancement when Synechococcus of varying qualities was provided to N-limited, chemostat-seeded grazers. Despite this doubled growth, 15 N labeling of the prey and nanoscale secondary ion mass spectrometry (nanoSIMS) detected low Synechococcus -N transfer into grazer biomass after 3 d (< 1% on a cell basis). This suggests the potential of grazers benefiting from alternative N sources (e.g., microbiome-N) or other constituents (e.g., vitamins or metals) not measured in this study. Prey photosynthetic efficiency declined under grazing conditions, demonstrating that grazers can directly affect prey abundance through grazing and indirectly affect prey photophysiology, potentially via allelopathy, supporting previous findings of an inverse relationship between grazers and prey along the Florida Gulf Coast.

Ahn, So Hyun [Univ. of Maryland, Cambridge, MD (Un↗
DOE OSTI2024

Dynamic Behavior of Pt Multimetallic Alloys for Active and Stable Propane Dehydrogenation Catalysts

Improving the use of platinum in propane dehydrogenation catalysts is a crucial aspect to increasing the efficiency and sustainability of propylene production. A known and practiced strategy involves incorporating more abundant metals in supported platinum catalysts, increasing its activity and stability while decreasing the overall loading. Here, using colloidal techniques to control the size and composition of the active phase, we show that Pt/Cu alloy nanoparticles supported on alumina (Pt/Cu/Al 2 O 3 ) displayed elevated rates for propane dehydrogenation at low temperature compared to a monometallic Pt/Al 2 O 3 catalyst. We demonstrate that the enhanced catalytic activity is correlated with a higher surface Cu content and formation of a Pt-rich core and Cu-rich shell that isolates Pt sites and increases their intrinsic activity. However, rates declined on stream because of dynamic metal diffusion processes that led to a more uniform alloy structure. This transformation was only partially inhibited by adding excess hydrogen to the feed stream. Instead, cobalt was introduced to provide trimetallic Pt/Cu/Co catalysts with stabilized surface structure and stable activity and higher rates than the original Pt/Cu system. In conclusion, the structure–activity relationship insights in this work offer improved knowledge of propane dehydrogenation catalyst development featuring reduced Pt loadings and notable thermal stability for propylene production.

Alloys↗