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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
DOE OSTI2023

Mass spectrometry and spectroscopic characterization of a tetrameric photosystem I supercomplex from Leptolyngbya ohadii , a desiccation-tolerant cyanobacterium

Cyanobacteria inhabiting desert biological soil crusts face the harsh conditions of the desert. They evolved a suite of strategies toward desiccation-hydration cycles mixed with high light irradiations, etc. In this study we purified and characterized the structure and function of Photosystem I (PSI) from Leptolyngbya ohadii, a desiccation-tolerant desert cyanobacterium. We discovered that PSI forms tetrameric (PSI-Tet) aggregate. We investigated it by using sucrose density gradient centrifugation, clear native PAGE, high performance liquid chromatography, mass spectrometry (MS), time-resolved fluorescence (TRF) and time-resolved transient absorption (TA) spectroscopy. MS analysis identified the presence of two PsaB and two PsaL proteins in PSI-Tet and uniquely revealed that PsaLs are N-terminally acetylated in contrast to non-modified PsaL in the trimeric PSI from Synechocystis sp. PCC 6803. Chlorophyll (Chl) a fluorescence decay profiles of the PSI-Tet performed at 77 K revealed two emission bands at ∼690 nm and 725 nm with the former appearing only at early delay time. The main fluorescence emission peak, associated with emission from the low energy Chls a, decays within a few nanoseconds. TA studies demonstrated that the 725 nm emission band is associated with low energy Chls a with absorption band clearly resolved at ∼710 nm at 77 K. As a result, our work suggests that the heterogenous composition of PsaBs and PsaL in PSI-Tet is related with the adaptation mechanisms needed to cope with stressful conditions under which this bacterium naturally grows.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Genotype-dependent contribution of CBF transcription factors to long-term acclimation to high light and cool temperature

When grown under cool temperature, winter annuals upregulate photosynthetic capacity as well as freezing tolerance. Here, the role of three cold-induced C-repeat-binding factor (CBF1–3) transcription factors in photosynthetic upregulation and freezing tolerance was examined in two Arabidopsis thaliana ecotypes originating from Italy (IT) or Sweden (SW), and their corresponding CBF1–3-deficient mutant lines it: cbf123 and sw: cbf123 . Photosynthetic, morphological and freezing-tolerance phenotypes, as well as gene expression profiles, were characterized in plants grown from the seedling stage under different combinations of light level and temperature. Under high light and cool (HLC) growth temperature, a greater role of CBF1–3 in IT versus SW was evident from both phenotypic and transcriptomic data, especially with respect to photosynthetic upregulation and freezing tolerance of whole plants. Overall, features of SW were consistent with a different approach to HLC acclimation than seen in IT, and an ability of SW to reach the new homeostasis through the involvement of transcriptional controls other than CBF1–3. These results provide tools and direction for further mechanistic analysis of the transcriptional control of approaches to cold acclimation suitable for either persistence through brief cold spells or for maximisation of productivity in environments with continuous low temperatures.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2026

Surface-Functionalized, Two-Dimensional Polymer Electrochromic Layers as Ultrafast, Multi-State Infrared Optical Gates

Electrochromic devices have widespread application potential, but the currently available switching speeds limit broad real-world implementation of this technology. Here, we report surface-engineered two-dimensional polymers with ionophilic pores that offer unprecedented switching speeds in solid-state, two-terminal, electrochromic devices. In particular, we demonstrate that a crystalline donor–acceptor 2DP functionalized with ethylene glycol oligomers exhibits multistate infrared absorption that is 4× faster (t c = 320 ms) with 3× coloration efficiency (491 cm 2 C –1 ) compared to an alkyl functionalized 2DP constructed from the same chromophores. The functionalized nanoporous surfaces enable rapid switching in these materials under either oxidative or reductive conditions, allowing us to access a range of robust, stable optical responses in a single electrochromic layer. These attributes led us to leverage surface-functionalized 2DPs as multistate infrared logic gates. Collectively, this work demonstrates that surface engineering of nanoporous crystalline lattices is a promising approach to co-optimize the electronic and ionic conductivities required to achieve rapidly switchable electrochromic layers. Beyond speed and efficiency, the demonstration of multistate infrared characteristics shows that electrochromic frameworks are useful in integrated optoelectronic circuits. This positions surface-engineered 2DPs as improved electrochromic coatings and a new material platform for photonic information processing and adaptive devices.

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

Phycobilisome core architecture influences photoprotective quenching by the Orange Carotenoid Protein

Photosynthetic organisms rely on sophisticated photoprotective mechanisms to prevent oxidative damage under high or fluctuating solar illumination. Cyanobacteria, which have evolved a unique, water-soluble light-harvesting complex—the phycobilisome—achieve photoprotection through a photoactivatable quencher called the Orange Carotenoid Protein (OCP). Phycobilisomes are highly symmetric and modular, formed by hierarchical assembly of conserved subunits into diverse geometries ranging from simple bundles to elaborate fan- or bouquet-like macromolecular architectures. Although OCP is known to provide photoprotection across species of cyanobacteria with different phycobilisome structures, it is not known whether or how these structural variations relate to changes in the photoprotective function of OCP. For example, OCP was recently discovered to bind as a dimer at two specific instances of an abundant structural motif on the tricylindrical phycobilisome of Synechocystis sp. PCC 6803, yet these sites are sterically inaccessible on a more common pentacylindrical phycobilisome ( Anabaena sp. PCC 7120). To understand how structural modularity and binding specificity contribute to conservation of OCP binding sites and function across different phycobilisome architectures, here we compare experimentally measured photophysical states accessible to these prototypical tricylindrical and pentacylindrical phycobilisomes, with and without OCP, at the single-molecule level. Together with Monte Carlo simulations of exciton transfer in OCP-quenched phycobilisomes, our results suggest that OCP binds at distinct and specific sites in each type of phycobilisome, yet provides nearly identical quenching strength to both phycobilisomes. Our findings highlight the utility of modular phycobilisome structures in balancing robust conservation of photoprotective function with adaptability of site-specific binding across species.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

An Integrated Energy Systems Prototype Human-System Interface for a Steam Extraction Loop System to Support Joint Electricity-Hydrogen Flexible Operations

Due to increasing economic competition from renewables and combined-cycle natural gas plants, nuclear power plants are looking toward flexible operations to enhance their cost competitiveness. The Integrated Energy Systems project under the Light Water Reactor Sustainability program of the U.S. Department of Energy focuses on joint electricity-hydrogen flexible operations. Joint electricity-hydrogen flexible operations entail the nuclear power plant diverting thermal energy via main steam to a hydrogen production plant located nearby. The steam serves to enhance the efficiency of the hydrogen production. Furthermore, high temperature electrolysis requires a large amount of electricity, which the plant can also provide. The plant provides steam and electricity to the hydrogen plant throughout the day, but during peak demand hours the nuclear power plant returns to solely providing electricity to meet the high demand. Through this flexible concept of operations, the plant can optimize the thermal energy it produces without having to maneuver the power of the plant. This report documents the human factors process to design and develop a prototype human-system interface for the steam extraction loop that serves as the conduit between the nuclear power plant and the adjacent hydrogen plant. The design process followed the human factors guidelines set by NUREG-0711, Human Factors Engineering Program Review Model (O’Hara, Higgins, & Fleger, 2012), and expanded upon by the Guideline for Operational Nuclear Usability and Knowledge Elicitation (GONUKE; Boring, Ulrich, Joe, & Lew, 2015; Boring, Lew, & Ulrich, 2016). The design process entailed operator interviews to determine the concept of operations for the steam extraction loop, a review and adaptation of digital interface design concepts developed by the team in prior projects, an iterative design process, and reviews conducted by both operators and human factors experts. Several versions of the prototype human-system interface were developed. Operators were interviewed to determine what design features they found useful and would like to see in the interface. The design underwent a review by human factors experts against NUREG-0700, Human Interface Design Review Guidelines (U.S. Nuclear Regulatory Commission, 2019), to ensure compliance with the latest human factors standards for digital interfaces in nuclear applications. The design was then prototyped as a functional windows-based application integrated with the Generic Pressurized Water Reactor simulator modified to include the steam extraction loop. The simulation is supported by the Human Systems Simulation Laboratory at Idaho National Laboratory, which supports operator-in-the-loop testing. This is an ongoing project and the next phase of the project entails performing an operator-in-the-loop usability study to evaluate the interface and examine the proposed concept of operations to extraction steam from the nuclear power plant for delivery to the coupled hydrogen production plant.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2025

FPGA-accelerated SpeckleNN with SNL for real-time X-ray single-particle imaging

We present the implementation of a specialized version of our previously published unified embedding model, SpeckleNN, for real-time speckle pattern classification in X-ray Single-Particle Imaging (SPI), using the SLAC Neural Network Library (SNL) on an FPGA platform. This hardware realization transitions SpeckleNN from a prototypic model into a practical edge solution, optimized for running inference near the detector in high-throughput X-ray free-electron laser (XFEL) facilities, such as those found at the Linac Coherent Light Source (LCLS). To address the resource constraints inherent in FPGAs, we developed a more specialized version of SpeckleNN. The original model, which was designed for broader classification across multiple biological samples, comprised ~5.6 million parameters. The new implementation, while reducing the parameter count to 64.6K (a 98.8% reduction), focuses on maintaining the model's essential functionality for real-time operation, achieving an accuracy of 90%. Furthermore, we compressed the latent space from 128 to 50 dimensions. This implementation was demonstrated on the KCU1500 FPGA board, utilizing 71% of available DSPs, 75% of LUTs, and 48% of FFs, with an average power consumption of 9.4W according to the Vivado post-implementation report. The FPGA performed inference on a single image with a latency of 45.015 microseconds at a 200 MHz clock rate. In comparison, running the same inference on an NVIDIA A100 GPU resulted in an average power consumption of ~73W and an image processing latency of around 400 microseconds. Our FPGA-accelerated version of SpeckleNN demonstrated significant improvements, achieving an 8.9 × speedup and a 7.8 × reduction in power consumption compared to the GPU implementation. Key advancements include model specialization and dynamic weight loading through SNL, which eliminates the need for time-consuming FPGA design re-synthesis, allowing fast and continuous deployment of models (re)trained online. These innovations enable real-time adaptive classification and efficient vetoing of speckle patterns, making SpeckleNN more suited for deployment in XFEL facilities. This implementation has the potential to significantly accelerate SPI experiments and enhance adaptability to evolving experimental conditions.

47 OTHER INSTRUMENTATION↗
DOE OSTI2023

Flash NanoPrecipitation as an Agrochemical Nanocarrier Formulation Platform: Phloem Uptake and Translocation after Foliar Administration

The increasing severity of pathogenic and environmental stressors that negatively affect plant health has led to interest in developing next-generation agrochemical delivery systems capable of precisely transporting active agents to specific sites within plants. In this work, we adapt Flash NanoPrecipitation (FNP), a scalable nanocarrier (NC) formulation technology used in the pharmaceutical industry, to prepare organic core–shell NCs and study their efficacy as foliar or root delivery vehicles. NCs ranging in diameter from 55 to 200 nm, with surface zeta potentials from -40 to +40 mV, and with seven different shell material properties were prepared and studied. Shell materials included synthetic polymers poly(acrylic acid), poly(ethylene glycol), and poly(2-(dimethylamino)ethyl methacrylate), naturally occurring compounds fish gelatin and soybean lecithin, and semisynthetic hydroxypropyl methylcellulose acetate succinate (HPMCAS). NC cores contained a gadolinium tracer for tracking by mass spectrometry, a fluorescent dye for tracking by confocal microscopy, and model hydrophobic compounds (alpha tocopherol acetate and polystyrene) that could be replaced by agrochemical payloads in subsequent applications. After foliar application onto tomato plants with Silwet L-77 surfactant, internalization efficiencies of up to 85% and NC translocation efficiencies of up to 32% were observed. Significant NC trafficking to the stem and roots suggests a high degree of phloem loading for some of these formulations. Results were corroborated by confocal microscopy and synchrotron X-ray fluorescence mapping. NCs stabilized by cellulosic HPMCAS exhibited the highest degree of translocation, followed by formulations with a significant surface charge. The results from this work indicate that biocompatible materials like HPMCAS are promising agrochemical delivery vehicles in an industrially viable pharmaceutical nanoformulation process (FNP) and shed light on the optimal properties of organic NCs for efficient foliar uptake, translocation, and delivery.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Community Structure and Microbial Associations in Sediment-Free Methanotrophic Enrichment Cultures from a Marine Methane Seep

We report Syntrophic consortia of anaerobic methanotrophic archaea (ANME) and sulfate-reducing bacteria (SRB) consume large amounts of methane and serve as the foundational microorganisms in marine methane seeps. Despite their importance in the carbon cycle, research on the physiology of ANME-SRB consortia has been hampered by the slow growth and complex physicochemical environment the consortia inhabit. Here, we report successful sediment-free enrichment of ANME-SRB consortia from deep-sea methane seep sediments in the Santa Monica Basin, California. Anoxic Percoll density gradients and size-selective filtration were used to separate ANME-SRB consortia from sediment particles and single cells to accelerate the cultivation process. Over a 3-year period, a subset of the sediment-associated ANME and SRB lineages, predominantly comprised of ANME-2a/2b (“Candidatus Methanocomedenaceae”) and their syntrophic bacterial partners, SEEP-SRB1/2, adapted and grew under defined laboratory conditions. Metagenome-assembled genomes from several enrichments revealed that ANME-2a, SEEP-SRB1, and Methanococcoides in different enrichments from the same inoculum represented distinct species, whereas other coenriched microorganisms were closely related at the species level. This suggests that ANME, SRB, and Methanococcoides are more genetically diverse than other members in methane seeps. Flow cytometry sorting and sequencing of cell aggregates revealed that Methanococcoides, Anaerolineales, and SEEP-SRB1 were overrepresented in multiple ANME-2a cell aggregates relative to the bulk metagenomes, suggesting they were physically associated and possibly interacting. Overall, this study represents a successful case of selective cultivation of anaerobic slow-growing microorganisms from sediments based on their physical characteristics, introducing new opportunities for detailed genomic, physiological, biochemical, and ecological analyses. Biological anaerobic oxidation of methane (AOM) coupled with sulfate reduction represents a large methane sink in global ocean sediments. Methane consumption is carried out by syntrophic archaeal-bacterial consortia and fuels a unique ecosystem, yet the interactions in these slow-growing syntrophic consortia and with other associated community members remain poorly understood. The significance of this study is the establishment of sediment-free enrichment cultures of anaerobic methanotrophic archaea and sulfate-reducing bacteria performing AOM with sulfate using selective cultivation approaches based on size, density, and metabolism. By reconstructing microbial genomes and analyzing community composition of the enrichment cultures and cell aggregates, we shed light on the diversity of microorganisms physically associated with AOM consortia beyond the core syntrophic partners. These enrichment cultures offer simplified model systems to extend our understanding of the diversity of microbial interactions within marine methane seeps.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Data-Driven Strategies for Accelerated Materials Design

The ongoing revolution of the natural sciences by the advent of machine learning and artificial intelligence sparked significant interest in the material science community in recent years. The intrinsically high dimensionality of the space of realizable materials makes traditional approaches ineffective for large-scale explorations. Modern data science and machine learning tools developed for increasingly complicated problems are an attractive alternative. An imminent climate catastrophe calls for a clean energy transformation by overhauling current technologies within only several years of possible action available. Tackling this crisis requires the development of new materials at an unprecedented pace and scale. For example, organic photovoltaics have the potential to replace existing silicon-based materials to a large extent and open up new fields of application. In recent years, organic light-emitting diodes have emerged as state-of-the-art technology for digital screens and portable devices and are enabling new applications with flexible displays. Reticular frameworks allow the atom-precise synthesis of nanomaterials and promise to revolutionize the field by the potential to realize multifunctional nanoparticles with applications from gas storage, gas separation, and electrochemical energy storage to nanomedicine. In the recent decade, significant advances in all these fields have been facilitated by the comprehensive application of simulation and machine learning for property prediction, property optimization, and chemical space exploration enabled by considerable advances in computing power and algorithmic efficiency. In this Account, we review the most recent contributions of our group in this thriving field of machine learning for material science. We start with a summary of the most important material classes our group has been involved in, focusing on small molecules as organic electronic materials and crystalline materials. Specifically, we highlight the data-driven approaches we employed to speed up discovery and derive material design strategies. Subsequently, our focus lies on the data-driven methodologies our group has developed and employed, elaborating on high-throughput virtual screening, inverse molecular design, Bayesian optimization, and supervised learning. We discuss the general ideas, their working principles, and their use cases with examples of successful implementations in data-driven material discovery and design efforts. Furthermore, we elaborate on potential pitfalls and remaining challenges of these methods. Finally, we provide a brief outlook for the field as we foresee increasing adaptation and implementation of large scale data-driven approaches in material discovery and design campaigns.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Enamel nanocrystal misorientation increased with meat-eating and agriculture

Enamel covers teeth, is the hardest tissue in the vertebrate body and has a complex multiscale structure from nanometres to millimetres. The structure comprises thin, long hydroxyapatite (Ca 5 (PO 4 ) 3 OH) nanocrystals, 50–70 nm wide, many micrometres long, parallel and bundled into approximately 5-µm-wide rods. The rods undulate and cross into a microscale ‘decussation pattern’ that toughens enamel by deflecting cracks. However, the crystallographic orientation of enamel nanocrystals is poorly understood. Here we show that the misorientation angle of adjacent nanocrystals varies markedly across 12 primate teeth spanning 9 species, 17.8 million years of evolution and diverse diets. Using a method called Polarization Enabled Large Input of Crystal Angles at the Nanoscale (PELICAN), we compare nanocrystals in the same (pre)molar locations and show that misorientation increases with food hardness in extant and fossil non-human apes and monkeys. We compare misorientation across three major dietary shifts in human evolution: the transition to meat-eating about 2.0–1.5 million years before present, to agriculture (about 12,000 years before present), and the Industrial Revolution (about 250 years before present). We show that over the past 1.6 million years, in the human lineage misorientation increased with time, especially when meat and stone-ground grains were introduced into human diets, but not with the Industrial Revolution. Thus, besides macro-changes, teeth adapted to dietary change at the nanoscale and crystallographically. This observation suggests that misorientation may contribute to enamel’s resilience; thus, bioinspired materials may consider small misorientation angles for added resilience.

biomaterials↗
DOE OSTI2021

National Virtual Biotechnology Laboratory: Report on Rapid R&D Solutions to the COVID-19 Crisis

With funding from the CARES Act, the U.S Department of Energy (DOE) established the National Virtual Biotechnology Laboratory (NVBL) in March 2020 to address key challenges associated with the COVID-19 crisis. NVBL brought together the broad scientific and technical expertise and resources of DOE’s 17 national laboratories to help tackle medical supply short ages, discover potential drugs to fight the virus, develop and validate COVID-19 testing methods, model disease spread and impact across the nation, and understand virus transport in buildings and the environment. National laboratory resources leveraged for this effort include a suite of world-leading user facilities broadly available to the research community, such as light and neutron sources, nanoscale science research centers, sequencing and biocharacterization facilities, and high-performance computing facilities. Within months, NVBL teams produced innovations in materials and advanced manufacturing that mitigated shortages in test kits and personal protective equipment (PPE), creating nearly 1,000 new jobs. They used DOE’s high-performance computers and light and neutron sources to identify promising candidates for antibodies and antivirals that universities and drug companies are now evaluating. NVBL researchers also developed new diagnostic targets and sample collection approaches, and supported U.S. Food and Drug Administration (FDA), Centers for Disease Control and Prevention (CDC), and U.S. Department of Defense (DoD) efforts to establish national guidelines used in administering millions of tests. Researchers used artificial intelligence and high-performance computing to produce near-real-time data analysis to forecast disease transmission, stress on public health infrastructure, and economic impact, which supported decision-makers at the local, state, and national levels. NVBL teams also studied how to control indoor virus movement to minimize uptake and protect human health. NVBL’s accomplishments demonstrate not only the powerful resource represented by DOE’s national laboratories working together to meet national needs, but also the effectiveness of the integrated NVBL framework for rapidly responding to emergencies with research and development (R&D) solutions. As the fight against COVID continues, sustained efforts are needed to confront this pandemic as well as future threats. Examples include: 1) Establishing “supply chains on demand” to meet emergency production needs by leveraging the materials and manufacturing expertise of DOE national laboratories and developing advances in electronics, sensing, robotics, and automation capabilities; 2) Improving the speed and robustness of drug discovery by integrating experimental platforms with DOE’s computational and experimental user facilities, which provide unique resources to support the discovery of high-potential therapeutic agents; 3) Protecting public, environmental, and animal health by developing new testing protocols and instrumentation adaptable to diverse sample types (both physiological and environmental) to quickly detect a wide range of pathogens and monitor other biorisks; 4) Supporting near-real-time data needs of decision-makers at the local, regional, state, and national levels by advancing data curation, analysis, and modeling using artificial intelligence and new data science tools for managing and evaluating large diverse datasets; 5) Harnessing DOE’s expertise in environmental modeling to design rooms and air handling for offices, classrooms, restaurants, and other structures to minimize biorisk transmissions. Going forward, NVBL is poised to apply the unique capabilities and expertise of the national laboratory complex to future national and international emergencies, both natural and engineered. Through this framework, the Office of Science will continue to be an integral component of agency wide efforts to prepare for and respond to biorisks and other crises.

42 ENGINEERING↗
DOE OSTI2025

Advanced Fuels Campaign Execution Plan

The Advanced Fuels Campaign (AFC) Execution Plan details the strategy, mission, scope, and goals—both near-term and long-term—along with the structure and organization of nuclear fuels and materials research, development, and demonstration (RD&D) activities within the Fuel Cycle Technologies (FCT) program. The FCT program, tasked by the U.S. Department of Energy (DOE), employs a science-based approach to advance fuel technologies. This approach integrates theory, experiments, and multi-scale modeling and simulation (M&S) to develop a predictive understanding of fuel fabrication processes and fuel/cladding performance under irradiation, moving beyond traditional empirical methods. The long-term goals of the AFC are guided by the AFC Strategic Plan and align with the DOE Office of Nuclear Energy (NE) Roadmap [1], which outlines a multi-decade vision for demonstrating and qualifying advanced fuel forms to support diverse fuel cycle options. Near-term goals focus on enhancing accident tolerant fuels (ATF) for Light Water Reactors (LWR), a significant challenge that demands balancing immediate objectives with ongoing progress toward advanced reactor missions. Accelerating the traditional fuel qualification process to meet ATF objectives is another critical challenge. A detailed set of 5-year goals, summarized below, has been developed in line with the overarching science-based fuel development approach: • Advanced LWR Fuel Technologies: By 2027, support the development of advanced LWR fuel technologies with improved performance and enhanced accident tolerance. This includes high burnup (HBu), low enriched uranium (LEU)+, coated cladding, and doped fuel, aimed at complementing industry-led significant LWR uprates and plant refurbishments. • Tristructural Isotropic (TRISO) Fuel: Achieve qualification by 2028 and develop improved designs for emerging markets. • Metal Fuel: Achieve qualification by 2028 and develop improved designs for emerging markets. • Molten Salt Fuel: By 2027, deploy a robust program that enables fuel salt qualification technologies needed to support fuel salt research and development (R&D), focusing on emergent needs to derisk fuel salt production and utilization in advanced reactors. • Long-Term ATF: Develop fuel technologies that enable significant power uprates (~50%) in refurbished or new LWRs while optimizing fissile material utilization and waste disposal. The 5-year milestones in the AFC Execution Plan are contingent on an assumed budget. This Execution Plan will be updated annually to reflect actual funding profiles as budget guidance becomes available, ensuring milestones are adjusted accordingly. In summary, the AFC Execution Plan presents a comprehensive strategy to advance nuclear fuel technologies through a science-based approach, addressing both near-term and long-term goals while adapting to funding realities.

11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2025

Self-supervised physics-informed generative networks for phase retrieval from a single X-ray hologram

X-ray phase contrast imaging significantly improves the visualization of structures with weak or uniform absorption, broadening its applications across a wide range of scientific disciplines. Propagation-based phase contrast is particularly suitable for time- or dose-critical in vivo/in situ/operando (tomography) experiments because it requires only a single intensity measurement. However, the phase information of the wave field is lost during the measurement and must be recovered. Conventional algebraic and iterative methods often rely on specific approximations or boundary conditions that may not be met by many samples or experimental setups. In addition, they require manual tuning of reconstruction parameters by experts, making them less adaptable for complex or variable conditions. Here we present a self-learning approach for solving the inverse problem of phase retrieval in the near-field regime of Fresnel theory using a single intensity measurement (hologram). A physics-informed generative adversarial network is employed to reconstruct both the phase and absorbance of the unpropagated wave field in the sample plane from a single hologram. Unlike most state-of-the-art deep learning approaches for phase retrieval, our approach does not require paired, unpaired, or simulated training data. This significantly broadens the applicability of our approach, as acquiring or generating suitable training data remains a major challenge due to the wide variability in sample types and experimental configurations. The algorithm demonstrates robust and consistent performance across diverse imaging conditions and sample types, delivering quantitative, high-quality reconstructions for both simulated data and experimental datasets acquired at beamline P05 at PETRA III (DESY, Hamburg), operated by Helmholtz-Zentrum Hereon. Furthermore, it enables the simultaneous retrieval of both phase and absorption information.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Genomic characterization of three marine fungi, including Emericellopsis atlantica sp. nov. with signatures of a generalist lifestyle and marine biomass degradation

ABSTRACT Marine fungi remain poorly covered in global genome sequencing campaigns; the 1000 fungal genomes (1KFG) project attempts to shed light on the diversity, ecology and potential industrial use of overlooked and poorly resolved fungal taxa. This study characterizes the genomes of three marine fungi: Emericellopsis sp. TS7, wood-associated Amylocarpus encephaloides and algae-associated Calycina marina. These species were genome sequenced to study their genomic features, biosynthetic potential and phylogenetic placement using multilocus data. Amylocarpus encephaloides and C. marina were placed in the Helotiaceae and Pezizellaceae (Helotiales) , respectively, based on a 15-gene phylogenetic analysis. These two genomes had fewer biosynthetic gene clusters (BGCs) and carbohydrate active enzymes (CAZymes) than Emericellopsis sp. TS7 isolate. Emericellopsis sp. TS7 ( Hypocreales , Ascomycota ) was isolated from the sponge Stelletta normani . A six-gene phylogenetic analysis placed the isolate in the marine Emericellopsis clade and morphological examination confirmed that the isolate represents a new species, which is described here as E. atlantica . Analysis of its CAZyme repertoire and a culturing experiment on three marine and one terrestrial substrates indicated that E. atlantica is a psychrotrophic generalist fungus that is able to degrade several types of marine biomass. FungiSMASH analysis revealed the presence of 35 BGCs including, eight non-ribosomal peptide synthases (NRPSs), six NRPS-like, six polyketide synthases, nine terpenes and six hybrid, mixed or other clusters. Of these BGCs, only five were homologous with characterized BGCs. The presence of unknown BGCs sets and large CAZyme repertoire set stage for further investigations of E. atlantica . The Pezizellaceae genome and the genome of the monotypic Amylocarpus genus represent the first published genomes of filamentous fungi that are restricted in their occurrence to the marine habitat and form thus a valuable resource for the community that can be used in studying ecological adaptions of fungi using comparative genomics.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Implementation of a Mesh refinement algorithm into the quasi-static PIC code QuickPIC

Plasma-based acceleration (PBA) has emerged as a promising candidate for the accelerator technology used to build a future linear collider and/or an advanced light source. In PBA, a trailing or witness particle beam is accelerated in the plasma wave wakefield (WF) created by a laser or particle beam driver. The WF is often nonlinear and involves the crossing of plasma particle trajectories in real space and thus particle-in-cell methods are used. The distance over which the drive beam evolves is several orders of magnitude larger than the wake wavelength. This large disparity in length scales is amenable to the quasi-static approach. Three-dimensional (3D), quasi-static (QS), particle-in-cell (PIC) codes, e.g., QuickPIC, have been shown to provide high fidelity simulation capability with 2-4 orders of magnitude speedup over 3D fully explicit PIC codes. In PBA, the witness beam needs to be matched to the focusing forces of the WF to reduce the emittance growth. In some linear collider designs, the matched spot size of the witness beam can be 2 to 3 orders of magnitude smaller than the spot size (and wavelength) of the wakefield. Such an additional disparity in length scales is ideal for mesh refinement where the WF within the witness beam is described on a finer mesh than the rest of the WF. A mesh refinement scheme is described that has been implemented into the 3D QS PIC code, QuickPIC. Very fine (high) resolution is used in a small spatial region that includes the witness beam and progressively coarser resolutions in the rest of the simulation domain. A fast multigrid Poisson solver has been implemented for the field solve on the refined meshes and a Fast Fourier Transform (FFT) based Poisson solver is used for the coarse mesh. The code has been parallelized with both MPI and OpenMP, and the parallel scalability has also been improved by using pipelining. A preliminary adaptive mesh refinement technique is described to optimize the computational time for simulations with an evolving witness beam size. Several test problems are used to verify that the mesh refinement algorithm provides accurate results. Additionally, the results are benchmarked against highly resolved simulations exhibiting near-azimuthal symmetry, performed using QPAD—a novel hybrid QS PIC code that uses a PIC description in the coordinates (r, ct – z) and a gridless description in the azimuthal angle, Φ.

Linear collider↗
DOE OSTI2024

Digitalization mapping and assessment process supporting ION strategic transformation activities

The existing fleet of commercial nuclear power plants (NPPs) are an important asset in the nation’s portfolio of electrical generating resources. Their continued safe and reliable operation are critical to providing a large source of carbon-free electricity to power the nation’s economy. The United States Department of Energy’s (DOE) Light Water Reactor Sustainability (LWRS) Program develops the scientific bases, methods, and tools, for the continued safe and economical operation of the nation's commercial NPPs. The Plant Modernization Pathway within LWRS Program focuses on providing guidance to industry on the full-scale implementation of modernization solutions for NPPs that significantly reduce the technical and financial risks associated with modernization. This research is focused on helping the nuclear industry understand how to digitize and digitalize their NPPs so that they can design their modernization solutions to be scalable, sustainable, and integrated both laterally and horizontally within their organization. That is, this research creates a digital transformation in NPPs by reshaping cultural mindsets and by identifying business efficiencies. In partnership with industry, and using four previously established guiding principles for digitalization, this research supported NPP modernization through assessing readiness for digitalization as a means to achieve integrated operations for nuclear. Specifically, this research created an assessment to review an entire organization’s work processes to gather information about the digitalization health of the plant. The assessment tools were administered to plant employees, and the results were used to develop a digitalization plan. The survey assessment identified the optimal candidate processes that would most benefit from a digitalization initiative which were revealed through analytical frameworks. One analysis calculated mean digitalization health indicator scores for all endorsed activities which allowed the researchers to rank and color code the results for easy identification. Individual health indicator scores are also provided, should our industry partner wish to understand these findings according to their own organizational priorities, business considerations and desired end-state. The results were also analyzed from the perspective that organizations are comprised of different types of innovators (e.g., generators, optimizers, conceptualizers, and implementers), which differentially affects the organization’s ability to comprehend and adapt to change (i.e., opportunities to innovate). Understanding the relative composition of innovator types at an NPP allows them to gather insights into the strengths and weaknesses they have in innovating how work is performed. For the utility that partnered with this research team, the results showed that implementers make up the largest portion of respondents and conceptualizers the smallest portion. Knowing the proportion of innovator types gave this organization insights on how they can effectively implement their innovation solutions. Additionally, the results were analyzed from a technical, economic, and risk perspective to identify and quantify work reduction opportunities (WROs). Recognizing that not all cost-saving opportunities are the same, a Technical, Economic and Risk Assessment (TERA) was performed to evaluate WROs to identify areas of greatest potential and lowest risk. The key results from TERA included a digitalization opportunity score for each activity, and a calculation of potential cost savings. These two outputs formed the bases for calculating a priority index and rank for the activities/processes assessed. From the prioritization calculations, TERA can then help the utility 1) decide what digitalization priorities to invest money in implementing and then 2) calculates how much should be invested in the digitalization initiatives selected to achieve cost savings and/or an acceptable return on investment. Last, onsite interviews revealed several inefficiencies in the standard work processes that occur cross-departmentally that are due to the absence of digitized and digitalized processes. Examples of these include time spent scanning paper documents and then uploading the documents electronically, obtaining signatures, and searching for desired information. This represents a digital but not digitalized process. Over 15 opportunities to improve work processes were identified through this multi-method digitalization assessment. The various analytical assessments used (e.g., TERA, digitalization health indicator scores), as well as discussions with the utility partner, corroborated that all the opportunities identified had a strong potential to make work processes more efficient and to improve overall performance of the NPP.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2026

Toward scalable quantum computations of atomic nuclei

We solve the nuclear two-body and three-body bound states via quantum simulations of pionless effective field theory on a lattice in position space. While the employed lattice remains small, the usage of local Hamiltonians including two- and three-body forces ensures that the number of Pauli terms scales linearly with increasing numbers of lattice sites. We use an adaptive ansatz grown from unitary coupled cluster theory to parametrize the ground states of the deuteron and 3 He, compute their corresponding energies, and analyze the scaling of the required computational resources. Our quantum simulations reproduce exact benchmarks for 2 H and 3 He within 100 keV, requiring at most 30 layers in the ansatz and thus resulting in modest circuit depths. Additionally, we find the number of shots required to reach a given precision scales linearly in the lattice size and more mildly in the system size. Furthermore, based on the agreement with exact benchmarks and mild scaling, we conclude that this can be an efficient, scalable approach for quantum computations of nuclear ground states, particularly to prepare initial states for quantum phase estimation or other filtering algorithms.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2022

Metagenomics-resolved genomics provides novel insights into chitin turnover, metabolic specialization, and niche partitioning in the octocoral microbiome

Abstract Background The role of bacterial symbionts that populate octocorals (Cnidaria, Octocorallia) is still poorly understood. To shed light on their metabolic capacities, we examined 66 high-quality metagenome-assembled genomes (MAGs) spanning 30 prokaryotic species, retrieved from microbial metagenomes of three octocoral species and seawater. Results Symbionts of healthy octocorals were affiliated with the taxa Endozoicomonadaceae , Candidatus Thioglobaceae , Metamycoplasmataceae , unclassified Pseudomonadales , Rhodobacteraceae , unclassified Alphaproteobacteria and Ca. Rhabdochlamydiaceae . Phylogenomics inference revealed that the Endozoicomonadaceae symbionts uncovered here represent two species of a novel genus unique to temperate octocorals, here denoted Ca. Gorgonimonas eunicellae and Ca. Gorgonimonas leptogorgiae . Their genomes revealed metabolic capacities to thrive under suboxic conditions and high gene copy numbers of serine-threonine protein kinases, type 3-secretion system, type-4 pili, and ankyrin-repeat proteins, suggesting excellent capabilities to colonize, aggregate, and persist inside their host. Contrarily, MAGs obtained from seawater frequently lacked symbiosis-related genes. All Endozoicomonadaceae symbionts harbored endo-chitinase and chitin-binging protein-encoding genes, indicating that they can hydrolyze the most abundant polysaccharide in the oceans. Other symbionts, including Metamycoplasmataceae and Ca. Thioglobaceae , may assimilate the smaller chitin oligosaccharides resulting from chitin breakdown and engage in chitin deacetylation, respectively, suggesting possibilities for substrate cross-feeding and a role for the coral microbiome in overall chitin turnover. We also observed sharp differences in secondary metabolite production potential between symbiotic lineages. Specific Proteobacteria taxa may specialize in chemical defense and guard other symbionts, including Endozoicomonadaceae , which lack such capacity. Conclusion This is the first study to recover MAGs from dominant symbionts of octocorals, including those of so-far unculturable Endozoicomonadaceae , Ca. Thioglobaceae and Metamycoplasmataceae symbionts. We identify a thus-far unanticipated, global role for Endozoicomonadaceae symbionts of corals in the processing of chitin, the most abundant natural polysaccharide in the oceans and major component of the natural zoo- and phytoplankton feed of octocorals. We conclude that niche partitioning, metabolic specialization, and adaptation to low oxygen conditions among prokaryotic symbionts likely contribute to the plasticity and adaptability of the octocoral holobiont in changing marine environments. These findings bear implications not only for our understanding of symbiotic relationships in the marine realm but also for the functioning of benthic ecosystems at large.

59 BASIC BIOLOGICAL SCIENCES↗