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At least 145 records · Page 8

Autonomous sensor suite for evaluating fish-turbine interactions and environmental impacts in marine renewable energy and hydropower

Marine renewable energy (MRE) harnesses ocean-based resources such as waves, tides, currents, and thermal or salinity gradients for sustainable power generation. It has the potential to complement existing renewable resources, support remote communities, and contribute to decarbonization efforts. However, understanding the hydrodynamic forces created by MRE devices and their impacts on marine life is critical for responsible deployment. Here, to address these concerns, advanced sensor devices, including the Marine Sensor Fish (MSF), Sensor Fish Mini (SF Mini), and Flexible Sensor Fish (FSF), were developed to measure interactions between aquatic organisms and MRE systems. This paper details the design, manufacturing, calibration, and field deployment of these sensor suites, highlighting their ability to capture key physical stressors such as shear forces, pressure changes, and collision impacts. The MSF successfully evaluated turbine interactions at a tidal turbine in the Salish Sea, capturing data on turbulence, collision impact, and pressure gradients. The SF Mini validated hydrodynamic conditions in scaled hydraulic models, supporting computational fluid dynamics simulations. The FSF, with its flexible silicone body, measured species-specific impacts in turbulent environments. This research demonstrates the potential of Sensor Fish technology to advance sustainable marine energy systems by reducing biological impacts and informing environmentally sustainable designs.

Ecological impacts↗

Spectroscopic Investigation into P(NDI2OD-T2) Charge Localization

P(NDI2OD-T2), commonly referred to as N2200, stands out as a promising electron-transporting (n-type) polymer for low-cost, flexible (photo)electrochemical applications due to its reversible two-electron reduction and high electron mobility. UV–vis spectroelectrochemistry in the tetrabutyl ammonium hexafluorophosphate/acetonitrile electrolyte shows two sets of chemically reversible redox signals in the cyclic voltammetry corresponding to the reduction of the neutral polymer film to polaronic and bipolaronic species. These electrochemical signatures suggest a distinct electronic reorganization upon reduction (polaron/bipolaron formation), highlighting the need for molecular-level insights into how charges are accommodated within the polymer backbone. While it has been previously hypothesized that charge predominantly localizes on the naphthalene diimide (NDI) unit during reductive charging, specific changes in atomic environments that confirm this localization have not been characterized in n-type polymers. Herein, we use near-edge X-ray absorption fine structure (NEXAFS) spectroscopy to probe electronic transitions in an electrochemically charged polymer to deduce charge localization. The O K-edge (1s) spectra exhibit two distinct π* peaks; the intensity of the lower-energy π* a peak that corresponds to an excitation to a largely localized carbonyl state decreases with reductive potentials relative to the higher-energy π* b peak. We corroborate this with Raman spectroscopy at different potentials, which shows a decrease in intensity on the C–C/C═C and C═O stretching bands of NDI as well as a red shift of the carbonyl band due to the formation of a polaron on the NDI. Additionally, new Raman active NDI signals associated with elongated C═O and C═C bonds are observed at lower energy during the formation of charged states. Together with theoretical calculations, these findings show that the injected charge spatially localizes on the NDI units and is dominantly distributed on the carbonyl groups. In conclusion, the combination of NEXAFS, optical and vibrational spectroscopies, and theoretical calculations is generalizable to other pi-conjugated polymers and can identify charge localization for the further development of organic semiconductors.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Hemicellulose Modulates Nanoscale Lignin Architecture in Synthetic Plant Cell Walls

Cellulose, hemicellulose, and lignin─the most abundant biopolymers on Earth─compose the structural matrix of plant biomass, providing renewable resources critical to bioenergy and sustainable materials. Despite their importance, the nanoscale mechanochemical processes underlying lignocellulose assembly during plant secondary cell wall formation remain poorly understood, hindering advancements in biomass conversion technologies. Here, in this study, we synthesize a biomimetic model system comprising cellulose–hemicellulose nanofibrils (CHN) to examine guaiacyl lignin polymerization in a physiologically relevant context. Using advanced nanocharacterization─scattering-type scanning near-field optical microscopy (s-SNOM) with infrared nanospectroscopy coupled to solid-state nuclear magnetic resonance (NMR)─we reveal that hemicellulose presence considerably modulates lignin deposition and alters its interunit bond distribution. Specifically, hemicellulose-rich environments dramatically reduce lignin deposition by approximately 50% and yield highly condensed lignin structures characterized by severely reduced β–O–4′ linkages (<2%) and suppressed β–β′ linkages. Conversely, cellulose-alone scaffolds support notably higher β–O–4′ content (∼10%), resulting in a more uniform nanoscale lignin coating. Our work helps explain how accessible hemicellulose sites, both sterically and chemically, direct radical coupling during lignification, fundamentally reshaping lignin’s nanoscale architecture. These findings deepen our mechanistic understanding of plant cell wall biosynthesis and inform strategies aimed at enhancing biomass deconstruction efficiency for sustainable bioenergy applications.

NMR↗

Maternal provisioning interacts with incubation temperature to affect hatchling mercury exposure in an oviparous reptile

The thermal environment experienced by developing embryos can influence the utilization of maternally provisioned resources. Despite being particularly consequential for oviparous ectotherms, these dynamics are largely unexplored within ecotoxicological frameworks. Here, we test if incubation temperature interacts with maternally transferred mercury to affect subsequent body burdens and tissue distributions of mercury in hatchling American alligators (Alligator mississippiensis). Nine clutches of alligator eggs were collected from a mercury-contaminated reservoir and incubated at either female- or male-promoting temperatures. Total mercury (THg) concentration was measured in egg yolk collected during incubation and in a suite of tissues collected from hatchlings. THg concentrations in residual yolk and blood were higher in hatchlings incubated at cooler, female-promoting temperatures compared to the warmer, male-promoting temperatures. THg concentrations in most tissues were positively correlated with THg concentrations in blood and dermis, and egg yolk THg concentration was the best predictor of THg concentration in many resultant tissues. Furthermore, our results highlight a hereto unknown role of the developmental environment in mediating tissue specific uptake of contaminants in an oviparous reptile.

59 BASIC BIOLOGICAL SCIENCES↗

Experimental evaluation of respiratory droplet spread to rooms connected by a central ventilation system

This article presents results from an experimental study to ascertain the transmissibility of the SARS-CoV-2 virus between rooms in a building that are connected by a central ventilation system. Respiratory droplet surrogates made of mucus and virus mimics were released in one room in a test building and measurements of concentration levels were made in other rooms connected via the ventilation system. The paper presents experimental results for different ventilation system configurations, including ventilation rate, filtration level (up to MERV-13), and fractional outdoor air intake. The most important finding is that respiratory droplets can and do transit through central ventilation systems, suggesting a mechanism for viral transmission (and COVID-19 specifically) within the built environment in reasonable agreement with well-mixed models. We also find the deposition of these droplets on room walls to be negligibly small. Furthermore, the energy use impact of the different configuration settings is also quantified to help inform intelligent building operation that can simultaneously address energy use and occupant health.

60 APPLIED LIFE SCIENCES↗

NNSA/CEA Workflow (Workshop Report)

This report, prepared by the NNSA/CEA Workflows Working Group, briefly summarizes the presentations in the areas of domain specific workflows, end user environments, data management, job and resource management, and infrastructure, and then identifies six broad areas for potential collaboration. A key finding is that users could benefit from greater interoperability, compatibility, and composability of the workflow technologies under development and that point-to-point collaboration opportunities should be identified to explore these aspects.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗

NNSA/CEA Workflow Workshop Report 2021

Researchers from three NNSA labs plus CEA recently met for a half-day workshop on scientific and engineering workflows in March of 2021. Tools, projects and use cases from each institution were described. A wide range of unique capabilities and requirements were represented. The workshop highlights the fact that the CEA/NNSA workflows space mirrors the broader open science workflows community, with multiple technologies under development in a number of science domains and under a number of funding streams, with differing capabilities and focuses. Despite the number of tools, presentations and discussions have shown that these tools cover specific mission spaces at the four labs, each with distinctive capabilities that do not completely overlap with each other. We believe there is a strong interest in the short term for sharing lessons learned and collaborating on benchmarks and site evaluation of projects. This report, prepared by the NNSA/CEA Workflows Working Group, briefly summarizes the presentations in the areas of domain specific workflows, end user environments, data management, job and resource management, and infrastructure, and then identifies six broad areas for potential collaboration. A key finding is that users could benefit from greater interoperability, compatibility, and composability of the workflow technologies under development and that point-to-point collaboration opportunities should be identified to explore these aspects.

97 MATHEMATICS AND COMPUTING↗

Harnessing Carbon: A Review of Current Technologies for Transform-ing Methane into Value-added Products

The concern over greenhouse gases, methane (CH 4 ) and carbon dioxide (CO 2 ), is increasing rapidly. There have been strides to find solutions to this global issue but there is not a clear path to a successful end goal. The concentration of CH 4 and CO 2 in the atmosphere has increased significantly over the last 60 years, methane is a great source of concern due to its ability to trap a high amount of heat in the atmosphere. These greenhouse gases contribute to global warming which has caused changes in the environment, including the melting of ice caps, and altered weather patterns. This review investigates biotechnology that has promising potential to aid in the mitigation of the negative effects methane has on the environment by exploring microorganisms, specifically methanotrophs, for their ability to convert methane into secondary value-added products that can be used for a wide range of applications. Methane as a feedstock could provide financial benefits due to the vast amount of methane available from sources like landfills, wastewater treatment plants, and agricultural sites. Furthermore, this review will look at the prospects of bioreactor technology and the potential for more environmentally friendly plastics, such as polyhydroxyalkanoate (PHA), to shy away from traditional petroleum-based plastics. The continuous advancement of bioreactor technology is crucial to mitigating greenhouse gas emissions.

36 MATERIALS SCIENCE↗

MAPSTER: Automated Geospatial Data Sharing – Version 1.4.0

The US Department of Energy’s (DOE) Oak Ridge National Laboratory (ORNL) developed MAPSTER which is a geospatial data management tool that aggregates, organizes, and shares data from dispersed sources such as unmanned aerial systems (UAS). Built specifically for use in environments where communications may be limited, MAPSTER utilizes two key technologies to effectively manage data in the field and enable easy data sharing with authorized partners: Observer and Checkpoint. Observer is a lightweight software package on an edge device, such as a laptop, that automatically detects newly processed UAS data and sends to a central server called Checkpoint. Checkpoint is a centralized server at ORNL that receives and manages data from all Observer instances. Even in a very low bandwidth environment, Observer can still send information about the UAS data product almost instantly as it generates its own metadata package on the size of KB (kilobytes). MAPSTER is not only for UAS data but for any geospatial data collected at the austere edge and dispersed sources.

97 MATHEMATICS AND COMPUTING↗

Hardware-in-the-loop Laboratory Performance Verification of Flexible Building Equipment in a Typical Commercial Building

This project aims to develop high-resolution equipment performance and occupant data that quantifies demand flexibility in typical commercial buildings. The dataset documented in this report includes comprehensive time-series measurements from hardware-in-the-loop (HIL) experiments conducted across multiple testbeds designed to simulate realistic operational environments for HVAC systems. Specifically, it captures minute-by-minute high-resolution data on the performance of various typical HVAC systems, including a variable-air-volume (VAV) air handling unit (AHU) system with chillers and an ice tank in the Intelligent Building Agents Laboratory (IBAL) at the National Institute of Standards and Technology (NIST), a two-stage air-source heat pump (ASHP) at the NIST, and a water-source heat pump (WSHP) at Texas A&M University (TAMU). The data were generated under a range of controlled conditions reflecting different grid scenarios and climatic influences, as well as various control strategies, building types, occupancy patterns, and occupant behaviors. This dataset provides DE-EE0009153 Final Report 5 detailed insights into the demand flexibility of these systems, including their response to grid signals, occupant behaviors, energy consumption patterns, and operational efficiency under different conditions.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Development of Multimaterial Graded Structure from Superalloys to Refractory Alloys

This research focused on developing hybrid microstructures for extreme environments where zone-specific performance is essential. Traditional structural applications rely on single alloy compositions, often requiring compromises in cost, corrosion resistance, or high-temperature stability, while dissimilar welding leads to abrupt material transitions and potential mechanical weaknesses. By employing a combinatorial approach, this study enabled a gradual transition of chemistries across components, allowing site-specific tailoring of microstructures. Leveraging additive manufacturing’s flexibility, this concept facilitated multi-material alloying and optimized fabrication strategies, unlocking new capabilities in high-performance applications while reducing manufacturing costs.

36 MATERIALS SCIENCE↗

Systemic Drivers of Electric-Grid-Caused Catastrophic Wildfires: Implications for Resilience in the United States

Wildfires are projected to increase in severity and frequency due to climate change, and the electric grid is both a cause of wildfires and is vulnerable to wildfires. Equipment from the electric grid accounts for 10% of fires burned in California and 3% of fires nationally. Recent catastrophic wildfires, such as the Lahaina Fire, Camp Fire, Marshall Fire, and Smokehouse Creek fires, were all started by electrical equipment and show how devastating these events can be because they threaten lives and structures. Vegetation structure, weather and winds, climate and vegetation response, land use, and human activities all impact the likelihood of severe wildfires. We explore the relationship between the built environment, electric grid infrastructure specifically, and its role in causing catastrophic wildfires to find lessons learned for increasing resilience. Electric grid utility companies currently employ multiple methods to mitigate fire, including (1) early detection, (2) grid hardening, (3) vegetation management, and (4) pre-emptive shutoffs. Utility companies need to consider the conditions for wildfire and the impact that each mitigation strategy has on drivers of wildfire behavior, as a single solution will not be adequate. Utility companies need to work with stakeholders to develop a holistic strategy to reduce ignition likelihood and spread likelihood to reduce catastrophic wildfires and improve resiliency.

Eagleston, Holly (ORCID:0000000178175116)↗

Genomic comparisons of a bacterial lineage that inhabits both marine and terrestrial deep subsurface systems

It is generally accepted that diverse, poorly characterized microorganisms reside deep within Earth’s crust. One such lineage of deep subsurface-dwelling Bacteria is an uncultivated member of the Firmicutes phylum that can dominate molecular surveys from both marine and continental rock fracture fluids, sometimes forming the sole member of a single-species microbiome. Here, we reconstructed a genome from basalt-hosted fluids of the deep subseafloor along the eastern Juan de Fuca Ridge flank and used a phylogenomic analysis to show that, despite vast differences in geographic origin and habitat, it forms a monophyletic clade with the terrestrial deep subsurface genome of “ Candidatus Desulforudis audaxviator” MP104C. While a limited number of differences were observed between the marine genome of “ Candidatus Desulfopertinax cowenii” modA32 and its terrestrial relative that may be of potential adaptive importance, here it is revealed that the two are remarkably similar thermophiles possessing the genetic capacity for motility, sporulation, hydrogenotrophy, chemoorganotrophy, dissimilatory sulfate reduction, and the ability to fix inorganic carbon via the Wood-Ljungdahl pathway for chemoautotrophic growth. Our results provide insights into the genetic repertoire within marine and terrestrial members of a bacterial lineage that is widespread in the global deep subsurface biosphere, and provides a natural means to investigate adaptations specific to these two environments.

Jungbluth, Sean P.↗

Price equation captures the role of drug interactions and collateral effects in the evolution of multidrug resistance

Bacterial adaptation to antibiotic combinations depends on the joint inhibitory effects of the two drugs (drug interaction [DI]) and how resistance to one drug impacts resistance to the other (collateral effects [CE]). Here we model these evolutionary dynamics on two-dimensional phenotype spaces that leverage scaling relations between the drug-response surfaces of drug-sensitive (ancestral) and drug-resistant (mutant) populations. We show that evolved resistance to the component drugs – and in turn, the adaptation of growth rate – is governed by a Price equation whose covariance terms encode geometric features of both the two-drug-response surface (DI) in ancestral cells and the correlations between resistance levels to those drugs (CE). Within this framework, mean evolutionary trajectories reduce to a type of weighted gradient dynamics, with the drug interaction dictating the shape of the underlying landscape and the collateral effects constraining the motion on those landscapes. We also demonstrate how constraints on available mutational pathways can be incorporated into the framework, adding a third key driver of evolution. Our results clarify the complex relationship between drug interactions and collateral effects in multidrug environments and illustrate how specific dosage combinations can shift the weighting of these two effects, leading to different and temporally explicit selective outcomes.

Gjini, Erida↗

Structure of diopside, enstatite, and magnesium aluminosilicate glasses: A joint approach using neutron and x-ray diffraction and solid-state NMR

Neutron diffraction with magnesium isotope substitution, high energy x-ray diffraction, and 29 Si, 27 Al, and 25 Mg solid-state nuclear magnetic resonance (NMR) spectroscopy were used to measure the structure of glassy diopside (CaMgSi 2 O 6 ), enstatite (MgSiO 3 ), and four (MgO) x (Al 2 O 3 ) y (SiO 2 ) 1–x–y glasses, with x = 0.375 or 0.25 along the 50 mol. % silica tie-line (1 – x – y = 0.5) or with x = 0.3 or 0.2 along the 60 mol. % silica tie-line (1 – x – y = 0.6). The bound coherent neutron scattering length of the isotope 25 Mg was remeasured, and the value of 3.720(12) fm was obtained from a Rietveld refinement of the powder diffraction patterns measured for crystalline 25 MgO. The diffraction results for the glasses show a broad asymmetric distribution of Mg–O nearest-neighbors with a coordination number of 4.40(4) and 4.46(4) for the diopside and enstatite glasses, respectively. As magnesia is replaced by alumina along a tie-line with 50 or 60 mol. % silica, the Mg–O coordination number increases with the weighted bond distance as less Mg 2+ ions adopt a network-modifying role and more of these ions adopt a predominantly charge-compensating role. 25 Mg magic angle spinning (MAS) NMR results could not resolve the different coordination environments of Mg 2+ under the employed field strength (14.1 T) and spinning rate (20 kHz). The results emphasize the power of neutron diffraction with isotope substitution to provide unambiguous site-specific information on the coordination environment of magnesium in disordered materials.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Impact of Grazing Duration and Environment on Soil Carbon in Reclaimed Uranium Mines Tailings: A Region Specific Study

ABSTRACT Grassland ecosystems, which cover over one‐third of the Earth's land area, store 10%–30% of global soil carbon (C). However, these ecosystems face substantial impacts from human activities, including mining. This study investigates the spatial distribution of soil C and related environmental factors in reclaimed grasslands on former uranium mine sites in Wyoming. We hypothesized that grazing duration and environmental factors would influence soil C levels. Interactions between topography, vegetation diversity, soil properties, and soil C in the context of grazing management in both natural and reclaimed grasslands from a wide range of periods from 1 year to 100 years were analyzed using geographically weighted regression models. Data collected from 2022 to 2023 showed that total carbon was consistently higher in natural grasslands (1.2%–4.9%) than in reclaimed grasslands (0.8%–1.3%). Additionally, soil C was significantly higher in natural grasslands grazed for 1 year compared to those grazed for 100 years. In contrast, reclaimed grasslands had lower soil C in areas grazed for 1 year compared to those grazed for 7 or 14 years. The absolute values of coefficients from environmental covariates indicated that areas grazed for a shorter duration (~1 year) were more influenced by biotic and abiotic factors than areas grazed for longer periods (> 7 years). Our findings show moderate grazing increases the resiliency of grassland ecosystems when grazed 7 years or longer and acknowledge the roles of topographic, soil, and vegetative factors in enhancing soil C concentration and developing sustainable land management practices in rangeland conditions.

Shilpakar, Chandan [Department of Plant Sciences U↗

Advancing \textit{otsdaq}: Enhancements for Usability, Accuracy, and Robustness

High-energy physics (HEP) experiments require data acquisition (DAQ) systems that can orchestrate complex detector operations, high data throughput, and responsive, real-time feedback to operators. Traditional DAQ stacks, which are often bespoke, command-line driven and highly specific, impose large learning curves on users. The Off-The-Shelf Data Acquisition (\textit{otsdaq}) framework was created to address these issues by offering a highly customizable and scalable browser-based ’desktop’ environment, in which experiment-specific control and monitoring applications can be easily deployed and integrated. Although the initial development of the \textit{otsdaq} software was aimed at the Fermilab Test Beam Facility, \textit{otsdaq} is now being leveraged for broader deployment, including the upcoming Mu2e experiment, where real-time monitoring of field-programmable gate array (FPGA)-based Data Transfer Controllers (DTCs), Clock and Fanout (CFO) boards, and several other subsystems are critical. We contribute a set of targeted improvements to \textit{otsdaq}: bitmap visualization functionality for configured data, improved and corrected delta-based DTC throughput metrics, version control (VC)-backed source navigation for console messages, custom navigation hooks to eliminate disruptive user interface glitches, and copy-to-clipboard support for macro execution history. These changes improve usability, reduce debugging time, and increase accuracy in performance data as Mu2e moves toward commissioning.

Mohammed, A. [Unlisted, US]↗

DRAS: Deep Reinforcement Learning for Cluster Scheduling in High Performance Computing

Cluster schedulers are crucial in high-performance computing (HPC). They determine when and which user jobs should be allocated to available system resources. Existing cluster scheduling heuristics are developed by human experts based on their experience with specific HPC systems and workloads. However, the increasing complexity of computing systems and the highly dynamic nature of application workloads have placed tremendous burden on manually designed and tuned scheduling heuristics. More aggressive optimization and automation are needed for cluster scheduling in HPC. In this work, we present an automated HPC scheduling agent named DRAS (Deep Reinforcement Agent for Scheduling) by leveraging deep reinforcement learning. DRAS is built on a hierarchical neural network incorporating special HPC scheduling features such as resource reservation and backfilling. An efficient training strategy is presented to enable DRAS to rapidly learn the target environment. Once being provided a specific scheduling objective given by the system manager, DRAS automatically learns to improve its policy through interaction with the scheduling environment and dynamically adjusts its policy as workload changes. We implement DRAS into a HPC scheduling platform called CQGym. CQGym provides a common platform allowing users to flexibly evaluate DRAS and other scheduling methods such as heuristic and optimization methods. Furthermore, the experiments using CQGym with different production workloads demonstrate that DRAS outperforms the existing heuristic and optimization approaches by up to 50%.

97 MATHEMATICS AND COMPUTING↗