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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 667 records · Page 37
All sourcesNASA NTRSDOE OSTI
DOE OSTI2019

Robust control of the current profile and plasma energy in EAST

Integrated control of the toroidal current density profile, or alternatively the q-profile, and plasma stored energy is essential to achieve advanced plasma scenarios characterized by high plasma confinement, magnetohydrodynamics stability, and noninductively driven plasma current. The q-profile evolution is closely related to the evolution of the poloidal magnetic flux profile, whose dynamics is modeled by a nonlinear partial differential equation (PDE) referred to as the magnetic-flux diffusion equation (MDE). The MDE prediction depends heavily on the chosen models for the electron temperature, plasma resistivity, and non-inductive current drives. To aid control synthesis, control-oriented models for these plasma quantities are necessary to make the problem tractable. However, a relatively large deviation between the predictions by these control-oriented models and experimental data is not uncommon. For this reason, the electron temperature, plasma resistivity, and non-inductive current drives are modeled for control synthesis in this work as the product of an “uncertain” reference profile and a nonlinear function of the different auxiliary heating and current-drive (H&CD) source powers and the total plasma current. The uncertainties are quantified in such a way that the family of models arising from the modeling process is able to capture the q-profile and plasma stored energy dynamics from a typical EAST shot. A control-oriented nonlinear PDE model is developed by combining the MDE with the “uncertain” models for the electron temperature, plasma resistivity, and non-inductive current drives. This model is then rewritten into a control framework to design a controller that is robust against the modeled uncertainties. The resulting controller utilizes EAST's H&CD powers and total plasma current to regulate the q profile and plasma stored energy even when mismatches between modeled and actual dynamics are present. The effectiveness of the controller is demonstrated through nonlinear simulations.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2018

Oxygenated commodity chemicals from chemo-catalytic conversion of biomass derived heterocycles

Biomass is an abundant source of renewable carbon, which could form the basis for sustainable fuels and chemicals to replace those derived from fossil fuel resources. During the past decade there have been multiple large projects focused on producing renewable fuels from biomass. These pioneer processes have often struggled to reach commercialization due to operational challenges, scale up challenges, and the low margins and high product volumes required for economic viability. The production of oxygenated chemicals from biomass offers several advantages compared to production of biofuels including: (1) chemicals are higher value, allowing for profitability at moderate scale (10–30 kton/yr) and sometimes even small scale (<1 kton/yr); (2) oxygenated chemicals require less deoxygenation, and therefore less hydrogen input and higher product mass yields compared to completely deoxygenated fuels; and, (3) target chemicals use the inherent functionalities (e.g., alcohols, cyclic ethers, C = C and C = O bonds, chiral centers) present in biomass. Furthermore bio-based chemicals can also be coproduced with biofuels thereby improving the economics of bio-refineries. Synergies between bio-refineries and conventional refineries (e.g., utilizing hydrogen surplus for hydrogenation; integrating refinery waste heat) could further improve economic viability.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

ZMPY3D: accelerating protein structure volume analysis through vectorized 3D Zernike moments and Python-based GPU integration

Abstract Motivation Volumetric 3D object analyses are being applied in research fields such as structural bioinformatics, biophysics, and structural biology, with potential integration of artificial intelligence/machine learning (AI/ML) techniques. One such method, 3D Zernike moments, has proven valuable in analyzing protein structures (e.g., protein fold classification, protein–protein interaction analysis, and molecular dynamics simulations). Their compactness and efficiency make them amenable to large-scale analyses. Established methods for deriving 3D Zernike moments, however, can be inefficient, particularly when higher order terms are required, hindering broader applications. As the volume of experimental and computationally-predicted protein structure information continues to increase, structural biology has become a “big data” science requiring more efficient analysis tools. Results This application note presents a Python-based software package, ZMPY3D, to accelerate computation of 3D Zernike moments by vectorizing the mathematical formulae and using graphical processing units (GPUs). The package offers popular GPU-supported libraries such as CuPy and TensorFlow together with NumPy implementations, aiming to improve computational efficiency, adaptability, and flexibility in future algorithm development. The ZMPY3D package can be installed via PyPI, and the source code is available from GitHub. Volumetric-based protein 3D structural similarity scores and transform matrix of superposition functionalities have both been implemented, creating a powerful computational tool that will allow the research community to amalgamate 3D Zernike moments with existing AI/ML tools, to advance research and education in protein structure bioinformatics. Availability and implementation ZMPY3D, implemented in Python, is available on GitHub (https://github.com/tawssie/ZMPY3D) and PyPI, released under the GPL License.

Lai, Jhih-Siang (ORCID:0000000156775890)↗
DOE OSTI2017

Evaluation of Story Maps to Enhance Public Engagement and Communication at Legacy Management Sites - 17334

The US Department of Energy's Office of Legacy Management's (LM) mission is to fulfill the department's post-closure responsibilities and to ensure protection of human health and the environment. Accomplishing that mission currently requires managing 91 legacy sites across the country by performing efficient long-term surveillance and maintenance activities, preserving and making accessible historic site records, and identifying opportunities for beneficial reuse. Integral to the success of these activities is connecting and effectively communicating with the public, governments, and other interested parties. Relationships with such entities are so important that the Office of Legacy Management has elevated such engagement to one of its strategic goals for the next 10 years. Several public engagement efforts are currently supported, including stakeholder meetings, interpretive visitor centers, hard-copy documents, and Internet-based information sources. The tools available to communicate with the public via the Internet are continually improving, and LM proactively evaluates these tools to enhance public engagement. The use of ESRI Story Maps to effectively and more succinctly communicate LM's long-term surveillance and maintenance practices is one tool currently being evaluated. Story Maps can utilize multiple types of content to engage users through site narratives, illustrations of change over time, photos, videos, and embedded links to external sources of information. The ability to illustrate site complexities via graphics and geo-spatial data is particularly useful for staff as well as communicating to stakeholders. Staff with a variety of expertise and functions in the organization can be empowered to respond to stakeholder questions using this tool. In addition, Story Maps can be easily initiated and managed in real time by LM site managers, an efficiency that would be invaluable to them as immediate site communication needs arise. A series of test Story Maps for several sites were developed to explore the capabilities of the tool. The test Story Maps included pages that described site description and overview, historical conditions and use, cleanup conditions, current monitoring data if applicable, and institutional controls. Links to existing communications tools were also incorporated in Story Maps, such as existing web sites that currently store environmental reports and the Geo-spatial Environmental Mapping System (GEMS), where stakeholders can download monitoring data. As with any tool, many things must be taken into consideration, such as: 1) Can the current IT infrastructure support the tool? 2) What data quality protocols need to be established? 2) What resources will be needed to maintain this tool? 3) What type of information should be shared? 4) Who will be responsible for information updates? This paper explores potential approaches for developing and deploying this tool for the public. (authors)

61 RADIATION PROTECTION AND DOSIMETRY↗
DOE OSTI2026

Test of Harmonic Coil Accuracy Using a Multi Vertex Probe

Magnets are integral components of particle accelerators, with different multipoles used to perform various beam conditioning functions, like steering and focusing. Testing accelerator magnets to ensure compliance with specification is a crucial step of fabrication. One of the most popular techniques for verifying magnetic field strength and integrity is the harmonic coil probe. Harmonic coil probes are comprised of passive loops that are rotated around the aperture of a magnet and are used to measure magnetic flux. Oftentimes the measurements of the harmonic coil probe are affected by transverse vibrations along the axis of rotation and torsional vibrations of the position closure sensor, both causing spurious harmonics. To make matters challenging, it is difficult to distinguish between the real harmonics of the magnet and the spurious harmonics during analysis. This research explores the use of a novel configuration of harmonic coil probe, Multi-Vertex Probe (MVP), to address multiple factors that affect the accuracy and repeatability of harmonic coil probe measurement. Most of the results are based on simulation data, in which artificial torsional distortions are introduced and removed with the proposed processing method. In addition to implementing torsional vibration removal in simulation, laboratory analysis regarding the source of vibrations was performed using a pre-fabricated MVP. More specifically, various mechanical conditions were used to explore the standard deviation of main harmonic’s flux amplitude. The conditions included: coupling type (rigid or soft), rotation speed, probe starting position within magnetic field, and cabling location inside the magnetic field. Along with this, the MVP’s measured noise floor in and outside a magnetic field was quantified.

Lofquist, Claire [Northern Illinois U.]↗
DOE OSTI2024

The hidden roots of wetland methane emissions

Abstract Wetlands are the largest natural source of methane (CH 4 ) globally. Climate and land use change are expected to alter CH 4 emissions but current and future wetland CH 4 budgets remain uncertain. One important predictor of wetland CH 4 flux, plants, play an important role in providing substrates for CH 4 ‐producing microbes, increasing CH 4 consumption by oxygenating the rhizosphere, and transporting CH 4 from soils to the atmosphere. Yet, there remain various mechanistic knowledge gaps regarding the extent to which plant root systems and their traits influence wetland CH 4 emissions. Here, we present a novel conceptual framework of the relationships between a range of root traits and CH 4 processes in wetlands. Based on a literature review, we propose four main CH 4 ‐relevant categories of root function: gas transport, carbon substrate provision, physicochemical influences and root system architecture. Within these categories, we discuss how individual root traits influence CH 4 production, consumption, and transport (PCT). Our findings reveal knowledge gaps concerning trait functions in physicochemical influences, and the role of mycorrhizae and temporal root dynamics in PCT. We also identify priority research needs such as integrating trait measurements from different root function categories, measuring root‐CH 4 linkages along environmental gradients, and following standardized root ecology protocols and vocabularies. Thus, our conceptual framework identifies relevant belowground plant traits that will help improve wetland CH 4 predictions and reduce uncertainties in current and future wetland CH 4 budgets.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2016

Above and belowground connections and species interactions: Controls over ecosystem fluxes

The ultimate goal of this work was to quantify soil and volatile organic compound fluxes as a function of tree species and associated mycorrhizal associations in an intact forest, but also to describe the physical and biological factors that control these emissions. The results of this research lay the foundation toward an improved mechanistic understanding of carbon pathways, fluxes, and ecosystem function, ultimately improving the representation of forest ecosystems in Earth System models. To this end, a multidisciplinary approach was necessary to fill a critical gap in our understanding of how soil and root processes may influence whole-ecosystem carbon-based volatile fluxes in the face of a rapidly changing climate. We developed a series of novel sampling protocols and coupled a variety of advanced analytical techniques, resulting in findings relevant across disciplines. Furthermore, we leveraged existing infrastructure, research sites, and datasets to design a low-cost exploratory project that links belowground processes, soil volatile emissions, and total ecosystem carbon budgets. Measurements from soil collars installed across a species/mycorrhizal gradient at the DOE-supported Moran Monroe State Forest Ameriflux tower site suggest that leaf litter is the primary source of belowground and forest floor volatile emissions, but the strength of this source is significantly affected not only by leaf litter type, but the strength of the soil as a sink. Results suggest that the strength of the sink is influenced by tree species-specific associated microbial communities that change throughout the season as a function of temperature, soil moisture, leaf litter inputs, and phenology. The magnitude of the observed volatile fluxes from the forest floor is small relative to total aboveground ecosystem flux, but the contribution of these emissions to volatile-mediated ecological interactions and soil processes (e.g. nitrification) varies substantially across the growing season. This research lays the foundation to answer important questions regarding the impacts of seasonality and forest composition on belowground volatile source-sink dynamics in mediating nutrient cycling and biogeochemistry dynamics—critical components of overall ecosystem functioning. In collaboration with the Environmental Simulations Unit (EUS) at the Helmholtz Zentrum in Munich, Germany (headed by Prof. Dr. Joerg-Peter Schinitzler), we investigated carbon investment in above and belowground plant volatile compounds in response to environmental conditions and mycorrhizal associations. Using the sophisticated phytotron facility and on-line trace gas instruments, we conducted controlled laboratory experiments that showed that biotic stresses, such as herbivore feeding, can alter the magnitude of belowground volatile emissions as well as carbon allocation towards these volatiles. We saw no effect of mycorrhizae on any induced response, suggesting that microbial effects were unrelated to source-sink dynamics driving terpene emissions. Furthermore, the results suggest that even though enzyme activity responsible for root volatile synthesis is up-regulated following herbivory, the sink strength of the soil can significantly impact what is measured at the soil/atmosphere interface and thereby what enters the atmosphere. This is important as scientists may be underestimating the magnitude of belowground volatile emissions and their influence on belowground interactions due to limitations associated with current sampling techniques. These key findings are being integrated with results from a hydroxyl radical reactivity-VOC campaign and a late season litter removal experiment to offer a comprehensive mechanistic understanding of the sources and controls over soil volatile emissions, particularly during times of the year when vegetative aboveground emissions are low (leaf senescence). Ultimately, these coupled field and laboratory experiments offer insights into seasonal dynamics of volatile emissions and the mechanisms that control carbon allocation to these compounds with an eye towards improving carbon budgets, nutrient cycling, and terrestrial ecosystem models.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Advanced Reactor Designs Security Analysis, Risk, and Recommendations: Risks, Consequences, and Possible by-Design Mitigation Approaches Associated with Select Advanced Reactors

Next-generation advanced reactors (ARs) incorporate enhanced safety systems, have smaller source terms, and feature compact modular designs, which should lessen their collective risk profiles. However, to fully evaluate risk, security needs to be a part of the equation. Without taking security into consideration, safety systems and components in the new ARs may be vulnerable to sabotage. These base attributes, coupled with enhanced security features specific to AR design through sound engineering and security-by-design (SeBD), should provide developers and operators with lower inherent security risk profiles. Building security early into the AR design may remove or passively secure potential critical targets from an adversary’s reach , thereby increasing overall safety and security. An integrated approach and diverse design team that includes engineering, operations, and security experts are fundamental to building security into the design without sacrificing fundamental operational efficiencies and principles. The objective of this project was to evaluate the security and safety interfaces for five classes of reactors, identify potential security vulnerabilities of structures, systems, and components (SSC), and underscore the need to consider security alongside safety in the design o f these concepts. The five reactor classes evaluated in this project and presented in this report are molten-salt reactors (MSR), high temperature gas reactors (HTGR), sodium-fast reactors (SFR), advanced light-water reactors (ALWR), and microreactors. These designs were selected because they reflect the concepts that are closest to market deployment and have received significant resource investments from the public and private sector. This project assesses the inherent security risks posed by common classes of ARs, provides a methodology and framework to assess security along with safety, and offers an analysis of potential mitigation strategies that could be incorporated. For each AR technology, the SSCs that relate to radionuclide source safety functions are discussed to understand the SSC contribution to safety and relative importance in the protective strategy for the design. The assumptions that went into evaluating each reactor concept originated from generic publicly available nonproprietary information and should not directly be used to qualify an absolute risk profile nor to rank specific AR designs. Instead, the purpose of the analysis is to understand and compare the generic inherent security risks of different AR technologies.

98 - NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL↗
DOE OSTI2018

Rock-welding materials development for deep borehole nuclear waste disposal

We report that various versions of deep borehole nuclear waste disposal have been proposed in the past in which effective sealing of a borehole after waste emplacement is generally required. In a high temperature disposal mode, the sealing function will be fulfilled by melting the ambient granitic rock with waste decay heat or an external heating source, creating a melt that will encapsulate waste containers or plug a portion of the borehole above a stack of the containers. However, there are certain drawbacks associated with natural materials, such as high melting temperatures, inefficient consolidation, slow crystallization kinetics, the resulting sealing materials generally being porous with low mechanical strength, insufficient adhesion to waste container surface, and lack of flexibility for engineering controls. In this study, we showed that natural granitic materials can be purposefully engineered through chemical modifications to enhance the sealing capability of the materials for deep borehole disposal. The present work systematically explores the effect of chemical modification and crystallinity (amorphous vs. crystalline) on the melting and crystallization processes of a granitic rock system. The approach can be applied to modify granites excavated from different geological sites. Several engineered granitic materials have been explored which possess significantly lower processing and densification temperatures than natural granites. Finally, those new materials consolidate more efficiently by viscous flow and accelerated recrystallization without compromising their mechanical integrity and properties.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2016

Design of Distributed Controllers Seeking Optimal Power Flow Solutions Under Communication Constraints

This paper focuses on power distribution networks featuring inverter-interfaced distributed energy resources (DERs), and develops feedback controllers that drive the DER output powers to solutions of time-varying AC optimal power flow (OPF) problems. Control synthesis is grounded on primal-dual-type methods for regularized Lagrangian functions, as well as linear approximations of the AC power-flow equations. Convergence and OPF-solution-tracking capabilities are established while acknowledging: i) communication-packet losses, and ii) partial updates of control signals. The latter case is particularly relevant since it enables asynchronous operation of the controllers where DER setpoints are updated at a fast time scale based on local voltage measurements, and information on the network state is utilized if and when available, based on communication constraints. As an application, the paper considers distribution systems with high photovoltaic integration, and demonstrates that the proposed framework provides fast voltage-regulation capabilities, while enabling the near real-time pursuit of solutions of AC OPF problems.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2023

Assessing variation in faecal glucocorticoid concentrations in gray whales exposed to anthropogenic stressors

Understanding how individual animals respond to stressors behaviourally and physiologically is a critical step towards quantifying long-term population consequences and informing management efforts. Glucocorticoid (GC) metabolite accumulation in various matrices provides an integrated measure of adrenal activation in baleen whales and could thus be used to investigate physiological changes following exposure to stressors. In this study, we measured GC concentrations in faecal samples of Pacific Coast Feeding Group (PCFG) gray whales (Eschrichtius robustus) collected over seven consecutive years to assess the association between GC content and metrics of exposure to sound levels and vessel traffic at different temporal scales, while controlling for contextual variables such as sex, reproductive status, age, body condition, year, time of year and location. We develop a Bayesian Generalized Additive Modelling approach that accommodates the many complexities of these data, including non-linear variation in hormone concentrations, missing covariate values, repeated samples, sampling variability and some hormone concentrations below the limit of detection. Estimated relationships showed large variability, but emerging patterns indicate a strong context-dependency of physiological variation, depending on sex, body condition and proximity to a port. Our results highlight the need to control for baseline hormone variation related to context, which otherwise can obscure the functional relationship between faecal GCs and stressor exposure. Therefore, extensive data collection to determine sources of baseline variation in well-studied populations, such as PCFG gray whales, could shed light on cetacean stress physiology and be used to extend applicability to less-well-studied taxa. GC analyses may offer greatest utility when employed as part of a suite of markers that, in aggregate, provide a multivariate measure of physiological status, better informing estimates of individuals’ health and ultimately the consequences of anthropogenic stressors on populations.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Specialization Restricts the Evolutionary Paths Available to Yeast Sugar Transporters

Functional innovation at the protein level is a key source of evolutionary novelties. The constraints on functional innovations are likely to be highly specific in different proteins, which are shaped by their unique histories and the extent of global epistasis that arises from their structures and biochemistries. These contextual nuances in the sequence–function relationship have implications both for a basic understanding of the evolutionary process and for engineering proteins with desirable properties. Here, we have investigated the molecular basis of novel function in a model member of an ancient, conserved, and biotechnologically relevant protein family. These Major Facilitator Superfamily sugar porters are a functionally diverse group of proteins that are thought to be highly plastic and evolvable. By dissecting a recent evolutionary innovation in an α-glucoside transporter from the yeast Saccharomyces eubayanus, we show that the ability to transport a novel substrate requires high-order interactions between many protein regions and numerous specific residues proximal to the transport channel. To reconcile the functional diversity of this family with the constrained evolution of this model protein, we generated new, state-of-the-art genome annotations for 332 Saccharomycotina yeast species spanning ~400 My of evolution. By integrating phylogenetic and phenotypic analyses across these species, we show that the model yeast α-glucoside transporters likely evolved from a multifunctional ancestor and became subfunctionalized. The accumulation of additive and epistatic substitutions likely entrenched this subfunction, which made the simultaneous acquisition of multiple interacting substitutions the only reasonably accessible path to novelty.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2017

Search for heavy Majorana neutrinos in pp collisions at √s = 8 TeV with the CMS detector & photodetector and calorimeter R&D for particle colliders

This thesis contains both physics analysis and hardware studies. It consists of two primary sections: the results of a search for heavy Majorana mass neutrinos, using the event signature of same (like) sign charged electron pairs ($e^{\pm} e^{\pm}$ ) and two jets, and the results of studies to upgrade the Hadronic Forward (HF) and Hadronic Endcap (HE) subdetectors in the Compact Muon Solenoid (CMS) detector in response to the high intensity proton-proton collisions generated at the Large Hadron Collider (LHC) at European Organization for Nuclear Research (CERN, Conseil Europ\'{e}en pour la Recherche Nucl\'{e}aire). In this search for Majorana mass neutrinos, same sign dielectron ($e^{\pm} e^{\pm}$) + dijet events in the final state have been considered as a signature for neutrino particles. The analyzed data corresponds to an integrated luminosity of 19.7 fb\textsuperscript{-1} of proton-proton collisions at a center of mass energy of $\sqrt{s} = 8 \text{TeV}$, collected using the CMS detector during the 2012 operation at the LHC. Monte Carlo simulations accounting for the theoretical expectations of the Standard Model (SM) and the detector limitations are used to prototype the experiment and to test proposed analysis steps. No excess of events is observed in the data beyond the expected SM background. Upper limits are set on the mixing element squared, $|{V}_{eN}|^{2}$, of the heavy Majorana neutrino with standard model neutrinos, as a function of Majorana neutrino mass for masses in the range of 40-500 $GeV/c^2$. The detector upgrade search comprises three sections of this thesis. The first section describes the test results of 1785 multianode Hamamatsu R7600U-200-M4 photomultiplier tubes (PMT) in numerous parameters such as gain, dark current, and timing characteristics, which provide insights on the expected performance of the upgraded CMS-HF detector. These PMTs replaced the previous single anode R7525 PMTs because the glass windows of previous PMTs are the source of Cherenkov radiation, which causes a background noise in the experiment. The second section reports characterization results of two types of PMTs in a novel operation mode for Secondary Emission (SE) Ionization Calorimetry, which is a novel technique to measure electromagnetic shower particles in extreme radiation environments. The third section presents the test results of novel scintillating materials for CMS experiment in specific and future particle accelerators in general. These materials are Polyethylene Naphthalate (PEN), Polyethylene Terephthalate (PET), high efficiency mirror (HEM) and quartz plates with various organic and inorganic coating materials such as p-Terphenyl (pTp), Anthracene and Gallium-doped Zinc Oxide (ZnO:Ga). We have investigated them for radiation hardness, light yield, timing characteristics, and scintillation and transmission properties.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2025

MOOSE ProbML: Parallelizable Probabilistic Machine Learning and Uncertainty Quantification Capabilities

The Multiphysics Object Oriented Simulation Environment (MOOSE) is a widely used open- source finite element software for performing multiphysics multiscale simulations in a massively parallel fashion. Recently, the computational team at Idaho National Laboratory (INL) has implemented Probabilistic Machine Learning (ProbML) capabilities in MOOSE—in a parallelized fashion—and enable active learning with large-scale computational models for tasks such as surrogate model development, scale bridging, forward/inverse uncertainty quantification (UQ), Bayesian optimization, etc. This presentation summarizes these developments in MOOSE along with demonstrations on several real applications relevant to nuclear energy. At the fundamental level, samplers like Monte Carlo/Latin Hypercube, variance reduction, parallelized Markov Chain Monte Carlo (MCMC) support uncertainty propagation in both forward and inverse settings. These samplers can be integrated with the Gaussian processes (GP) suite in MOOSE, which offer several variants like scalar GPs, multi-output GPs, and deep GPs, to enable active learning. These GPs can be tuned using gradient-based optimization methods like Adam and its variants or gradient-free methods like the elliptical slice sampler (a variant of MCMC adept under Gaussian settings) for more complex covariance kernels or likelihoods whose gradient computations can be cumbersome. A variety of batch acquisition functions permit parallelized evaluation of the computational model and support different learning objectives with high efficiency like Bayesian inference, global surrogate development, optimization, etc. Furthermore, libtorch integration supports training, evaluation, and re-training of neural networks and other complex machine learning models in active learning settings. The impacts of these developments are shown on several real applications: (1) nuclear fuel inverse UQ and model inadequacy assessment using the Kennedy O’Hagan framework; (2) uncertainty aware surrogate modeling for additive manufacturing to predict field quantities; (3) nuclear reactor rare events analysis; and (4) complex fluid flow prediction using a global surrogate with quantified prediction uncertainty. Finally, the outlook of MOOSE ProbML is discussed for both outer-loop and inner-loop computations in the broad view to accelerate fuels and materials qualification, address gaps in knowledge and data, and assess new reactor/fuel systems.

11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2018

Qiita: rapid, web-enabled microbiome meta-analysis

Multi-omic insights into microbiome function and composition typically advance one study at a time. However, in order for relationships across studies to be fully understood, data must be aggregated into meta-analyses. This makes it possible to generate new hypotheses by finding features that are reproducible across biospecimens and data layers. Qiita dramatically accelerates such integration tasks in a web-based microbiome-comparison platform, which we demonstrate with Human Microbiome Project and Integrative Human Microbiome Project (iHMP) data.

microbiome, bioinformatics software, open source s↗
DOE OSTI2016

Conversion of lignin into value-added materials and chemicals via laccase-assisted copolymerization

With today’s environmental concerns and the diminishing supply of the world’s petroleum-based chemicals and materials, much focus has been directed toward alternative sources. Woody biomass presents a promising option due to its sheer abundance, renewability, and biodegradability. Lignin, a highly irregular polyphenolic compound, is one of the major chemical constituents of woody biomass and is the second most abundant biopolymer on Earth, surpassed only by cellulose. The pulp and paper and cellulosic ethanol industries produce lignin on the scale of millions of tons each year as a by-product. Traditionally, lignin has been viewed as a waste material and burned as an inefficient fuel. However, in recent decades, research has focused on more economical ways to convert lignin into value-added commodities, such as biofuels, biomaterials, and biochemicals, thus developing and strengthening the concept of fully integrated biorefineries. Owing to the phenolic structure of lignin, it is possible to enzymatically graft molecules onto its surface using laccases (benzenediol:oxygen oxidoreductases, EC 1.10.3.2) to create exciting novel biomaterials. These environmentally friendly enzymes use oxygen as their only co-substrate and produce water as their sole by-product, and have thus found great industrial application. Furthermore, this mini-review highlights recent advances in the field of laccase-facilitated functionalization of lignin as well as promising future directions for lignin-based polymers.

09 BIOMASS FUELS↗
DOE OSTI2020

Global root traits (GRooT) database

Motivation: Trait data are fundamental to the quantitative description of plant form and function. Although root traits capture key dimensions related to plant responses to changing environmental conditions and effects on ecosystem processes, they have rarely been included in large-scale comparative studies and global models. For instance, root traits remain absent from nearly all studies that define the global spectrum of plant form and function. Thus, to overcome conceptual and methodological roadblocks preventing a widespread integration of root trait data into large-scale analyses we created the Global Root Trait (GRooT) Database. GRooT provides readyto- use data by combining the expertise of root ecologists with data mobilization and curation. Specifically, we (a) determined a set of core root traits relevant to the description of plant form and function based on an assessment by experts, (b) maximized species coverage through data standardization within and among traits, and (c) implemented data quality checks. Main types of variables contained: GRooT contains 114,222 trait records on 38 continuous root traits. Spatial location and grain: Global coverage with data from arid, continental, polar, temperate and tropical biomes. Data on root traits were derived from experimental studies and field studies. Time period and grain: Data were recorded between 1911 and 2019. Major taxa and level of measurement: GRooT includes root trait data for which taxonomic information is available. Trait records vary in their taxonomic resolution, with subspecies or varieties being the highest and genera the lowest taxonomic resolution available. It contains information for 184 subspecies or varieties, 6,214 species, 1,967 genera and 254 families. Owing to variation in data sources, trait records in the database include both individual observations and mean values. Software format: GRooT includes two csv files. A GitHub repository contains the csv files and a script in R to query the database.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Climate adaptation and sustainability in switchgrass: exploring plant-microbe-soil interactions across continental scale environmental gradients

Less carbon-intensive energy sources are needed to reduce greenhouse gas emissions and their predicted role in climate change. There is growing interest in the potential of biofuels for meeting this need. A critical question is whether large-scale biofuel production can be sustainable over the time scales needed to mitigate our carbon debt from fossil fuel consumption. The carbon balance and ultimately the sustainability of biofuel feedstock production is the result of complex climate-coupled interactions between carbon fixation, sequestration, and release through combustion. Similarly, the long-term productivity of biofuels depends on the environmental factors limiting plant growth. These factors are often related to soil resources which involve complex interactions at the plant-microbe-soil interface impacting their availability and cycling. Our collaborative project addressed sustainable switchgrass (Panicum virgatum) production by exploring Plant Systems, Plant-Microbiome Interactions, and Ecosystem Processes through the integrating lens of Multi-Scale Modeling. Our research was based on detailed characterization of genetically diverse switchgrass genotypes planted in common gardens across a continental latitudinal gradient. The underlying theme of our Plant Systems research was the use of locally adapted plant material to explore plant function, to understand the mechanistic basis of environmental interactions, and to discover the plant genes important for adaptation and sustainability in the face of climate change. Our Plant-Microbiome Interaction project characterized the microbial communities associated with switchgrass using genomic tools. Our Ecosystem Processes research focused on carbon cycle responses at the ecosystem level using stand level plantings. Finally, our Multi-Scale Modeling helped to define conditions of a sustainable biofuel system and identify key tradeoffs between genetic diversity, productivity, and ecosystem services. Genome-wide association analyses were used to identify alleles that contribute to successful establishment and biomass production across North America. Together, our work provided a baseline analyses of the potential of switchgrass as a biofuel feedstock. Our project resulted in a number of successful outcomes. First, we were successful in collecting switchgrass germplasm across the species range, propagating the material, and establishing common garden experiments across the species range. In collaboration with DOE JGI, we successfully assembled the first tetraploid switchgrass genome and published this resource with an analyses of the genetic basis local adaptation from our gardens (Lowry et al. 2019, Lovell et al. 2021). The gardens were used to characterize the genetic architecture for a number of important plant phenotypes. Our project also conducted extensive sampling and sequencing to characterize the bacterial and fungal associates of switchgrass roots and leaves. We showed that host genotype, location, and harvesting practices can play a role in microbiome assembly (Singer et al. 2019 & 2022, Van Wallendael et al. 2020 & 2022, Edwards et al. 2023). Our ecosystem processes work created baseline dataset of carbon and nutrient cycling in realistic stand plantings of switchgrass. Data from this experiment provided new insight into the role of plant traits, phenology, and local environments in ecosystem processes like soil respiration, net-ecosystem exchange, and dynamics of soil and plant nutrients (Ricketts et al. 2023). Finally, our crop modelling experiments help to characterize the sensitivity of common modeling frameworks to parameters, identify key limiters of productivity across large geographic scales, and leverage patterns of local adaptation in prediction. Ultimately, these studies help to identify critical plant-microbe-soil traits that may be manipulated, through breeding or agronomic management, to improve the sustainability of biofuel feedstocks.

09 BIOMASS FUELS↗