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DOE OSTI2026

Concerted Electron-Ion Transport by Polyacrylonitrile Elucidated with Reactive Deep Learning Potentials

Charge transport in polymers, such as polyacrylonitrile (PAN), is crucial for electronics and energy storage. For instance, PAN can transport cations e.g., Li + , by facilitating dynamic cation-nitrile coordination in batteries. However, little is known regarding the underlying role of complex reactive polymer configurations. Herein, we develop a deep-learning potential, trained on ab initio energies and forces of nonequilibrium reactive PAN configurations, to unravel the kinetics of PAN cyclization initiated by a nucleophile (OH – dissociated from LiOH) attacking the terminal nitrile carbon. We find, based on the reaction free-energetics, rates, and charge analysis, that the nucleophile attack producing the first ring is the rate-limiting step, which subsequently triggers Li + -coupled electron transfer along the PAN backbone, causing ∼10 4 times faster sequential ring-formation of the remaining nitriles. PAN’s extended configurations, where dipolar and H-bonding interactions are minimal, enable such rapid kinetics. By validating our computational findings with IR and NMR experiments, we establish a pathway for designing reactive polymers with enhanced charge transport for energy applications.

Chahal-Crockett, Rajni [Oak Ridge National Laborat↗

DOE OSTI2021

Mitigating Catastrophic Forgetting in Deep Learning in a Streaming Setting Using Historical Summary

Recent advancements in scientific equipment and the adaptation of electronics and the Internet of Things (IoT) in our everyday lives resulted in large and complex data production at a high rate. Making meaningful and timely knowledge discovery at a modest cost from this big data is difficult for computing power and storage limitations. Training deep learning models incrementally in a streaming setting can help us with overcoming these limitations. However, in a well-known phenomenon named catastrophic forgetting, incrementally trained models increasingly perform poorly on the past data. To mitigate catastrophic forgetting in training in a streaming setting, we propose constructing a historical summary over time and use the summary with newly arrived data during incremental training. We propose various data summarization techniques such as random sampling, micro clustering, coreset computation, and Auto Encoders to counteract catastrophic forgetting. We built a pipeline for incremental training with a historical summary for training deep learning models for streaming data. We demonstrate the effectiveness of historical summary in mitigating catastrophic forgetting using three case studies involving three different deep learning applications: an Artificial Neural Network (ANN) for classification task on MNIST dataset, a language model (RNN-LM) on the WikiText2 dataset, and a Convolutional Neural Network (CNN), ResNet50 to classify the ImageNet dataset. Through the training of the models, we observe that catastrophic forgetting is evident in ANN and CNN but not in an RNN. For the first task, our method recovers up to 47.9% lost accuracy due to catastrophic forgetting. For the third task, the historical summary recovers classification accuracy by up to 25%. For the second task, though there is not proof of catastrophic forgetting, the training performance (PPL) improves by up to 26% with historical summary.

Dash, Sajal↗

DOE OSTI2021

Real-time Simulation Framework for Hardware-in-the-Loop Testing of Multi-port Autonomous Reconfigurable Solar Power Plant (MARS)

Multiport autonomous reconfigurable solar power plant (MARS) has been proposed for integrated development of photovoltaic (PV) and energy storage system (ESS) that can connect to high-voltage direct current (HVdc) and alternating current (ac) transmission grid. To de-risk the development of this complex integrated system that consists of hundreds to thousands of power electronics modules, a controller hardware-in-the-loop (cHIL) test setup will be extremely beneficial. The cHIL testing can be used for evaluation of modules as well as the hierarchical control system in MARS. With the unique configuration of power electronics modules in MARS, it becomes necessary to develop custom-designed real-time simulation models in the cHIL setup in absence of off-the-shelf models. In this paper, high-fidelity dynamic model of MARS, control algorithms at the lower level, and required communication algorithms are developed and optimized for real-time performance in the cHIL setup. Real-time experimental results from the cHIL are provided.

Dong, Zerui↗

DOE OSTI2022

Power Electronic Hardware-in-the-Loop (PE-HIL): Testing Individual Controllers in Large-Scale Power Electronics Systems

Large power electronics systems like multi-port autonomous reconfigurable solar power plant (MARS) are increasingly being researched upon to integrate emerging energy sources. MARS connects photovoltaic (PV) systems and energy storage systems (ESSs) to high-voltage direct current (HVdc) links/grids and high-voltage alternating current (ac) transmission grids. As these large power electronics systems incorporate complex hierarchical control systems that are close-by and communicate fast, the control systems require an unique power electronic hardware-in-the-loop (PE-HIL) real-time architecture to evaluate individual controllers. In this paper, a PE-HIL real-time architecture is proposed to evaluate one of the hundreds to thousands of digital signal processors (DSPs) that are a part of the complex hierarchical control system. The DSP connects to a central processing unit (CPU) and a field programmable gate array (FPGA) that form a part of the upper levels of the control system. The DSP is part of the lower level of the control system. The proposed PE-HIL architecture is tested and evaluated. Preliminary test results are presented to showcase the concept.

Debnath, Suman↗

DOE OSTI2025

Heating effects on jack pine pyrogenic organic matter properties from a pyrocosm study in 2022

This dataset contains data associated with the preprint “Fire removes preexisting pyrogenic organic matter from the ecosystem through the mechanisms of both direct combustion and increasing mineralizability” (Luo et al., 2025b), which is the complementary study to the published paper “Reburning pyrogenic organic matter: a laboratory method for dosing dynamic heat fluxes from above” (Luo et al., 2025a). We designed a full-factorial experiment with different burial depths of jack pine (Pinus banksiana Lamb) pyrogenic organic matter (PyOM) (Surface, 1 cm, and 5 cm) and different heat-flux profiles (High, Low, and Control) to examine how subsequent fires affect the properties of preexisting PyOM. We measured total carbon (C), pH, dissolved organic carbon (DOC), dissolved inorganic carbon (DIC), and mineralized C (as CO₂-C, from a 12-week incubation).We found that high heat flux and/or surface placement resulted in substantial direct C losses through combustion. Intermediate heat exposure produced both combustion losses and increases in DOC and mineralizability, which may have complex long-term implications: an increased dissolved fraction of PyOM may promote downward transport into mineral soils and potentially contribute to deeper, longer-term C storage, but it may also make PyOM more susceptible to microbial decomposition. Under the lowest heat flux and deepest burial, most PyOM was retained, and changes in DOC and C mineralization were minimal. Finally, PyOM pH, an important chemical property, decreased under low-temperature heating but increased under higher temperatures.We uploaded pH data for all samples (“pH_of_all_samples.csv”); pH and temperature-related data (peak temperature and degree hours) for samples in High and Low heat-flux treatments (“pH_vs_peakT_and_degree_hours_only_for_heated_samples.csv”); total C data (“CN_pct_C_stock_C_loss_in_samples.csv”); DOC and DIC data (“doc_dic.csv”); and mineralized C (CO₂-C) data (“CO2-C_all_original.csv”). Additional details can be found in the Methods & Sampling section.All datasets uploaded to ESS-DIVE are clearly labeled, cleaned, and include both raw and derived data, ready for reuse in other analyses. All analysis code and raw datasets are also available on GitHub: https://github.com/MengmengLuo/Fire-removes-preexisting-pyrogenic-organic-matter-from-the-ecosystem.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2024

Accelerator Physics at NSLS-II: Research Accomplishments in 2024

NSLS-II accelerator physicists advanced the operational performance and scientific capabilities of NSLS-II, providing regular lattice characterization and correction, injec tion optimization, vertical emittance control, and beam dynamics reports with corre lation analysis. We further developed advanced lattice characterization techniques and studies on impedance, beam-induced heating, and higher-harmonic RF cavity effects to support NSLS-II and its high-brightness upgrade. The assessment of free-electron laser options for the NSLS-II upgrade has been completed. We carried out comprehensive studies focused on complex bend magnets and novel efficient injection schemes for next-generation low-emittance synchrotrons. We contributed to the Electron-Ion Collider project, including Electron Storage Ring lattice design, beam diagnostics, and injector studies. The physicists participated in international collaborations, including the development of Python-based Middle Layer software, and participated in key accel erator physics workshops and scientific meetings. The main research accomplishments achieved in 2024 are summarized in this report.

43 PARTICLE ACCELERATORS↗

NASA NTRS1972

Electronic switching circuit uses complementary non-linear components

Inherent switching properties of saturable inductors and storage diodes are combined to perform large variety of electronic functions, such as pulse shaping, gating, and multiplexing. Passive elements replace active switching devices in generation of complex waveforms.

Zucker, O. S.↗

NASA NTRS1973

Integrated Digital Flight Control System for the Space Shuttle Orbiter

The objectives of the integrated digital flight control system (DFCS) is to provide rotational and translational control of the space shuttle orbiter in all phases of flight: from launch ascent through orbit to entry and touchdown, and during powered horizontal flights. The program provides a versatile control system structure while maintaining uniform communications with other programs, sensors, and control effectors by using an executive routine/functional subroutine format. The program reads all external variables at a single point, copies them into its dedicated storage, and then calls the required subroutines in the proper sequence. As a result, the flight control program is largely independent of other programs in the computer complex and is equally insensitive to characteristics of the processor configuration. The integrated structure is described of the control system and the DFCS executive routine which embodies that structure. The input and output, including jet selection are included. Specific estimation and control algorithm are shown for the various mission phases: cruise (including horizontal powered flight), entry, on-orbit, and boost. Attitude maneuver routines that interface with the DFCS are included.

Source record↗

NASA NTRS1983

Application of a space station to communications satellites

The economic benefits of a space station relative to communications satellites are discussed in terms of technology experiments, spacecraft checkout, repair, servicing, and refurbishment (RSR), and mating an OTV with satellites for boost to GEO. The zero gravity, vacuum conditions, and atmosphere free long ranges are environmental features that can be used for testing large, flexible antennas and laser communications devices. Some resistance might be encountered to checkout in LEO due to the substantial success of launches to GEO without LEO checkout. However, new generations of larger, more complex satellites may warrant the presence of a space station to verify performance of new spacecraft. One RSR positive aspect for a space station is as a storage site for propellant, as well as for reusable OTV booster engines. Also, the space station can serve as a base for manned or unmanned repair spacecraft which will travel to GEO to fix malfunctions in geostationary satellites.

Ramler, J. R.↗

NASA NTRS2011

Integrated Systems Health Management for Intelligent Systems

The implementation of an integrated system health management (ISHM) capability is fundamentally linked to the management of data, information, and knowledge (DIaK) with the purposeful objective of determining the health of a system. Management implies storage, distribution, sharing, maintenance, processing, reasoning, and presentation. ISHM is akin to having a team of experts who are all individually and collectively observing and analyzing a complex system, and communicating effectively with each other in order to arrive at an accurate and reliable assessment of its health. In this chapter, concepts, procedures, and approaches are presented as a foundation for implementing an ISHM capability relevant to intelligent systems. The capability stresses integration of DIaK from all elements of a system, emphasizing an advance toward an on-board, autonomous capability. Both ground-based and on-board ISHM capabilities are addressed. The information presented is the result of many years of research, development, and maturation of technologies, and of prototype implementations in operational systems.

Figueroa, Fernando↗

NASA NTRS2011

Issues of Long-Term Cryogenic Propellant Storage in Microgravity

Modern multi-layer insulation (MLI) allows to sharply reduce the heat leak into cryogenic propellant storage tanks through the tank surface and, as a consequence, significantly extend the storage duration. In this situation the MLI penetrations, such as support struts, feed lines, etc., become one of the most significant challenges of the tanks heat management. This problem is especially acute for liquid hydrogen (LH2) storage, since currently no efficient cryocoolers exist that operate at very low LH2 temperatures (20K). Even small heat leaks under microgravity conditions and over the period of many months give rise to a complex slowly-developing, large-scale spatiotemporal physical phenomena in a multi-phase liquid-vapor mixture. These phenomena are not well-understood nor can be easily controlled. They can be of a potentially hazardous nature for long-term on-orbital cryogenic torage, propellant loading, tank chilldown, engine restart, and other in-space cryogenic fluid management operations. To support the engineering design solutions that would mitigate these effects a detailed physics-based analysis of heat transfer, vapor bubble formation, growth, motion, coalescence and collapse is required in the presence of stirring jets of different configurations and passive cooling devices such as MLI, thermodynamic vent system, and vapor-cooled shield. To develop physics-based models and correlations reliable for microgravity conditions and long-time scales there is a need for new fundamental data to be collected from on-orbit cryogenic storage experiments. Our report discusses some of these physical phenomena and the design requirements and future studies necessary for their mitigation. Special attention is payed to the phenomena occurring near MLI penetrations.

Muratov, C. B.↗

DOE OSTI2025

Proteomic insights into the physiology and metabolism of oleaginous yeasts and filamentous fungi

Fungi are vital to the bioeconomy, serving as key producers of food, beverages, biofuels, and medicines, while also acting as essential resource recyclers in ecosystem management. For nearly a century, oleaginous yeast and filamentous fungi have been explored for their proficiency in oleochemicals production and carbon storage. Lipogenesis is one of the most well-studied fungal processes, with substantial progress having been made through reductionist biochemical approaches; however, the physiology and metabolism of fungal systems operating under different conditions arise from the functions of thousands of proteins, for which very little is known outside of model yeast. In this review, we discuss how proteomics provides a valuable analytical approach to contextualize lipogenesis within a complex biological system, where lipid accumulation is fundamentally governed by changes in proteins of multiple pathways. In the past two decades, proteomics has been applied to study stress response to nutrient limitations, metabolism of various carbon and nitrogen sources, the lipid droplet hub of carbon storage, protein post-translational modifications and signaling pathways, as well as oleochemical biosynthesis, thereby advancing our understanding of the oleaginous phenotype. Over 40 studies are reviewed herein to evaluate the impact, critically assess the utility, and propose future applications of proteomics. In the coming years, large systems-level proteomics studies will lay a foundation for marrying modeling and metabolic engineering strategies to optimize oleochemicals production in oleaginous fungi.

Lipid production↗

DOE OSTI2025

Quantifying Groundwater Response and Uncertainty in Beaver‐Influenced Mountainous Floodplains Using Machine Learning‐Based Model Calibration

Abstract Beavers ( Castor canadensis ) alter river corridor hydrology by creating ponds and inundating floodplains, and thereby improving surface water storage. However, the impact of inundation on groundwater, particularly in mountainous alluvial floodplains with permeable gravel/cobble layers overlain by a soil layer, remains uncertain. Numerical modeling across various floodplain structures considers topographic and sediment complexity and multidirectional flow, linking inundation to groundwater response. This study develops a model‐data integration workflow to address uncertainty in groundwater response to beaver‐induced inundations in a mountainous alluvial floodplain in the Upper Colorado River Basin. Uncertain factors include seasonal hydrologic dynamics, hydraulic conductivities, floodplain structures, and meteorological forcings. We employed an ensemble of groundwater models, based on geophysical and hydrologic data, with machine learning‐based calibration using a neural density estimator. This allowed us to quantify the vertical flux from the soil layer to the permeable gravel bed, the down‐valley underflow within the gravel bed, and their ratios. Results show a significant increase in the vertical flux relative to down‐valley underflow, from 2 during dry pond periods to 20 during wet periods, serving as an analogy for conditions without and with beaver ponds. The study highlights the influence of floodplain structure on groundwater storage, water balance, and water quality impacted by beaver ponds. A thick gravel bed layer, with a large down‐valley underflow, minimizes the effect of beaver‐induced inundation on water quality. We emphasize the need for field‐scale measurements of floodplain structure and improved characterization of evapotranspiration changes to reduce uncertainty in groundwater response. Plain Language Summary Beavers change the flow of water in river corridors by creating ponds, expanding wetlands, and flooding floodplains. This increases surface water area, promotes plant growth, and enhances biodiversity. However, the impact of this flooding on groundwater flow is not well understood, especially in mountainous areas with gravel layers where water moves easily beneath soil. In this study, we used numerical modeling to investigate how beaver ponds influence groundwater in a mountainous floodplain of the Upper Colorado River Basin. We adapted a machine learning method to validate our numerical models using multiple field data sets. Our findings show that beaver ponds significantly increase vertical water flow from the soil to the gravel during wet periods, compared to when the ponds are fully drained. The study also highlights the importance of floodplain structure in controlling both water flow in gravel layers along the river direction and vertical flow from the soil to the gravel with the presence of beavers. To reduce uncertainty in groundwater response, we emphasize the need for more field‐scale measurements of floodplain structure, hydraulic properties, and evapotranspiration changes. Key Points Floodplain structures and hydraulic conductivities are important for groundwater response with beaver ponds in mountainous floodplains Large down‐valley underflow in permeability‐stratified floodplains reduces beaver‐induced impacts on groundwater storage and water quality Machine learning‐based model calibration methods are effective for estimating posterior distributions of groundwater model parameters

Wang, Lijing↗

DOE OSTI2020

Biogeochemical Cycling of Redox-Sensitive Elements in Permafrost-Affected Ecosystems

Northern high latitudes are experiencing rapid changes in climate that drive permafrost thaw and shifts in hydrology and soil saturation. These factors regulate redox conditions across permafrost-affected landscapes, potentially altering carbon storage in soils and exacerbating climate change through accelerated decomposition of soil organic matter. Redox conditions impact soil carbon storage directly by influencing rates and pathways of organic matter decomposition, and indirectly by moderating the bioavailability of organic molecules and nutrients. Indeed, the ability of increased plant growth to offset C losses in permafrost regions will be regulated by nutrient availability (e.g., N, P) that varies across redox gradients. The purpose of this review is to examine how redox conditions shape biogeochemical cycling of ecologically important elements (P, N, S, Fe) in permafrost-affected ecosystems. Although carbon cycling in these regions continues to be widely studied, relatively little information is available on the elements that regulate C cycling. We discuss the complex feedbacks between climate change, hydrology, and landscape change that control redox conditions, then examine how these factors regulate biogeochemical cycles. We identify key gaps in our understanding of how changing climate may alter biogeochemical cycles and carbon storage in northern high-latitude ecosystems.

Herndon, Elizabeth↗

DOE OSTI2020

Three-Dimensional Imaging and Quantification of Gas Storativity in Nanoporous Media via X-rays Computed Tomography

This study provides the engineering science underpinnings for improved characterization and quantification of the interplay of gases with kerogen and minerals in shale. Natural nanoporous media such as shale (i.e., mudstone) often present with low permeability and dual porosity, making them difficult to characterize given the complex structural and chemical features across multiple scales. These structures give nanoporous solids a large surface area for gas to sorb. In oil and gas applications, full understanding of these media and their sorption characteristics are critical for evaluating gas reserves, flow, and storage for enhanced recovery and CO 2 sequestration potential. Other applications include CO 2 capture from industrial plants, hydrogen storage on sorbent surfaces, and heterogeneous catalysis in ammonia synthesis. Therefore, high-resolution experimental procedures are demanded to better understand the gas–solid behavior. In this study, CT imaging was applied on the sub-millimeter scale to shale samples (Eagle Ford and Wolfcamp) to improve quantitative agreement between CT-derived and pulse decay (mass balance) derived results. Improved CT imaging formulations are presented that better match mass balance results, highlighting the significance of gas sorption in complex nanoporous media. The proposed CT routine implemented on the Eagle Ford sample demonstrated a 17% error reduction (22% to 5%) when compared to the conventional CT procedure. These observations are consistent in the Wolfcamp sample, emphasizing the reliability of this technique for broader implementation of digital adsorption studies in nanoporous geomaterials.

42 ENGINEERING↗

DOE OSTI2021

From material properties to multiscale modeling to improve lithium-ion energy storage safety

Energy storage using lithium-ion cells dominates consumer electronics and is rapidly becoming predominant in electric vehicles and grid-scale energy storage, but the high energy densities attained lead to the potential for release of this stored chemical energy. This article introduces some of the paths by which this energy might be unintentionally released, relating cell material properties to the physical processes associated with this potential release. The selected paths focus on the anode–electrolyte and cathode–electrolyte interactions that are of typical concern for current and near-future systems. Relevant material processes include bulk phase transformations, bulk diffusion, surface reactions, transport limitations across insulating passivation layers, and the potential for more complex material structures to enhance safety. We also discuss the development, parameterization, and application of predictive models for this energy release and give examples of the application of these models to gain further insight into the development of safer energy storage systems.

25 ENERGY STORAGE↗

DOE OSTI2022

Conservative solute transport processes and associated transient storage mechanisms: Comparing streams with contrasting channel morphologies, land use and land cover

Abstract Land use within a watershed impacts stream channel morphology and hydrology and, therefore, in‐stream solute transport processes and associated transient storage mechanisms. This study evaluated transport processes in two contrasting stream sites where channel morphology was influenced by the surrounding land use, land cover, climate and geologic controls: Como Creek, CO, a relatively undisturbed, high gradient, forested stream with a gravel bed and complex channel morphology, and Clear Creek, IA, an incised, low‐gradient stream with low‐permeability substrate draining an agricultural landscape. We performed conservative stream tracer injections at these sites to address the following questions: (1) How does solute transport vary between streams with differing morphologies? and (2) How does solute transport at each stream site change as a function of discharge? We analysed in‐stream tracer time series data and compared results quantifying solute attenuation in surface and subsurface transient storage zones. Significant trends were observed in these metrics with varying discharge conditions at the forested site but not at the agricultural site. There was a broad range of transport mechanisms and evidence of substantial exchange with both surface and hyporheic transient storage in the relatively undisturbed, forested stream. Changing discharge conditions activated or deactivated different solute transport mechanisms in the forested site and greatly impacted advective travel time. Conversely in the simplified agricultural stream, there was a narrow range of solute transport behaviour across flows and predominantly surface transient storage at all measured discharge conditions. These results demonstrate how channel simplification inhibits available solute transport mechanisms across varying discharge conditions.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2022

Effect of Local Structural Distortions on Antiferroelectric–Ferroelectric Phase Transition in Dilute Solid Solutions of K x Na 1– x NbO 3

The fundamental principles that govern antiferroelectric (AFE)–ferroelectric (FE) transitions are not well understood for many solid solutions of perovskite compounds. For example, crystal chemical considerations based on the average Goldschmidt tolerance factor or ionic polarizability do not precisely predict the boundary between the AFE and FE phases in dilute solid solutions of alkali niobates, such as K x Na 1– x NbO 3 ( x ≤ 0.02). Here, based on detailed structural analysis from neutron total scattering experiments, we provide insights about how the relative local distortions around the A- and B-sites of the ABO 3 perovskite structure affect the AFE/FE order of the average crystallographic phases in K x Na 1– x NbO 3 . Specifically, we show that a higher (lower) ratio of B-site-centered distortions over A-site-centered distortions drives transition toward a long-range FE (AFE) phase, which is based on a competition between the long-range polarizing field of the Nb–O dipoles and the disordering effect of local distortions around the A-site. Our study provides a predictive tool for designing complex solid-solution perovskites with tunable (anti)ferroelectric polarization properties, which can be of interest for various energy-related applications such as high-density energy storage and solid-state cooling.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗