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DOE OSTI2021

Nitrate, ammonium, and DON mass time series output for East River stream, vadose zone and groundwater subwatersheds from HAN-SoMo model

There is a growing understanding of the role that bedrock weathering can play as a source of nitrogen (N) to soils, groundwater and river systems. The significance is particularly apparent in mountainous environments where weathering fluxes can be large. However, our understanding of the relative contributions of rock-derived, or geogenic, N to the total N supply of mountainous watersheds remains poorly understood. This dataset contains model output from the High-Altitude Nitrogen Suite of Models (HAN-SoMo), a watershed-scale ensemble of process-based models to quantify the relative sources, transformations, and sinks of geogenic and atmospheric N through a mountain watershed. Our study is based in the East River Watershed (ERW) in the Upper Colorado River Basin. The East River is a near-pristine headwater watershed underlain primarily by an N-rich Mancos Shale bedrock, enabling the timing and magnitude of geogenic and atmospheric contributions to watershed scale dissolved N-exports to be quantified. Six calibration scenarios were developed to explore equifinality using >1600 N concentration measurements from streams, groundwater, and vadose zone samples collected over the course of four years across the watershed, from 2014-2018. The files in this dataset are named according to which calibration scenario they represent (1, 2, 3, NM1, NM2, and NC), and include daily time series model output of nitrate, ammonium and dissolved organic nitrogen concentrations for all six calibration scenarios described in Maavara et al., 2021, "Modeling geogenic and atmospheric nitrogen through the East River Watershed, Colorado Rocky Mountains," PLOS One (in press), for the stream, vadose zone, and groundwater in the five discretized subwatersheds: Rustlers Gulch, Copper Creek, East above Quigley (EAQ), the Middle East River (ME), and Lower Triangle (LT) from Gothic to the Pumphouse. The READ_ME.txt file includes details on units and naming conventions in each of these files. Model files are in .mat format, to be opened in MATLAB.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2023

PiCAM: A Raspberry Pi-based open-source, low-power camera system for monitoring plant phenology in Arctic environments

Time-lapse cameras have been widely used as a tool to monitor the timing of seasonal vegetation growth. These simple, relatively inexpensive systems can provide high-frequency observations of leaf development and demography which are critical data sets needed to characterize plant phenology from species to landscapes. This is important for understanding how plants are responding to global changes, as well as for validating satellite-derived phenology products. However, in remote regions including the high-latitude Arctic, deploying time-lapse cameras could be challenging. The remoteness and lack of widespread power and telecommunications infrastructure limit options for the installation, maintenance and retrieval of data and equipment, and make it difficult for cameras to survive in extreme weather (e.g. long cold winters). To improve our understanding of Arctic phenology, new technologies are required to address these challenges. Here, we present a novel, low-power, compact, lightweight time-lapse camera system, called power-interval camera automation module (PiCAM). The PiCAM was designed with explicit consideration to simplify deployment (i.e. without a need for external power supplies) of camera systems and to address the challenges of camera survival in harsh Arctic environments. In this paper, we describe the design, setup and technical details of the PiCAM and provide a roadmap for how to build and operate these systems. As proof of concept, we deployed 26 PiCAMs at three low-Arctic tundra sites on the Seward Peninsula, Alaska in early August 2021 for characterizing Arctic plant phenology. Of the 26 PiCAMs, 70% remained active at the point of our revisit in late July 2022 despite the extreme winter temperatures they experienced (< –30°C, heavy snow cover). We extracted key plant phenology metrics from the PiCAMs and captured strong differences across key Arctic plant species. We showed that the PiCAM has the potential to be widely used for monitoring plant phenology across the broader Arctic region, addressing the need for ground-based understanding of Arctic phenological diversity to develop knowledge of plant response to climate change and to validate remote sensing products.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2026

Framework for X-ray mirror surface shape fitting

For accurate characterization of grazing-incidence X-ray mirrors, we present a comprehensive framework to fit measured surface shapes (either slope or height) of X-ray mirrors used in synchrotron radiation and free-electron laser facilities. We summarize the closed-form expressions of some typical surface shapes of X-ray mirrors including elliptic cylinders, hyperbolic cylinders, ellipsoids, hyperboloids, and diaboloids. This framework is composed of four layers: definition of standard shapes with closed-form expressions, generation of theoretical surface with pose parameters (six degrees of freedom defining an object's position and orientation relative to a coordinate system), parameter optimization with the ability to select which parameters are fit and which are held constant, and the development of user-friendly fitting function wrappers for particular fitting tasks. A few practical fitting examples are demonstrated to verify the effectiveness of the proposed fitting framework. We discuss the physical meanings of the fitting parameters, and provide several examples using the elliptic cylinder and ellipsoid shapes to highlight some features of the framework. Moreover, we provide the presented framework as open-source codes (MATLAB and Python codes available at https://github.com/nsls2omf/xmf) to the community to encourage academic collaboration and further improvements.

36 MATERIALS SCIENCE↗

DOE OSTI2018

Dual-source evaporation of silver bismuth iodide films for planar junction solar cells

Non-toxic and air-stable silver bismuth iodide semiconductors are promising light absorber candidates for photovoltaic applications owing to a suitable band gap for multi- or single-junction solar cells. Recently, solution-based film fabrication approaches for several silver bismuth iodide stoichiometries have been investigated. The current work reports on a facile and reproducible two-step coevaporation/annealing approach to deposit compact and pinhole-free films of AgBi 2 I 7 , AgBiI 4 and Ag 2 BiI 5 . X-ray diffraction (XRD) in combination with scanning electron microscopy (SEM)/energy-dispersive X-ray spectroscopy (EDX) analysis reveals formation of pure cubic (Fd$\bar{3}$m) with combining macron]m) phase AgBi 2 I 7 , cubic (Fd$\bar{3}$m) or rhombohedra (R$\bar{3}$m with combining macron]m) phase AgBiI 4 , each with >3 μm average grain size, or the rhombohedral phase (R$\bar{3}$m) Ag 2 BiI 5 with >200 nm average grain size. A phase transition from rhombohedral to cubic structure is investigated via temperature-dependent X-ray diffraction (TD-XRD). Planar-junction photovoltaic (PV) devices are prepared based on the coevaporated rhombohedral AgBiI 4 films, with titanium dioxide (TiO 2 ) and poly(3-hexylthiophene) (P3HT) as electron- and hole-transport layers, respectively. Finally, the best-performing device exhibited a power conversion efficiency (PCE) of as high as 0.9% with open-circuit voltage (VOC) > 0.8 V in the reverse scan direction (with significant hysteresis).

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2019

WBS 4.2.1.31 Integrated Life Cycle Sustainability Analysis

The main objective of this project (following the 2017 BETO Program Peer-Review) is to provide BETO with a coherent methodology and modeling framework based on life cycle (LCA) and economic input-output analysis, tested and vetted with stakeholders, to better understand the effects of an expanding U.S. bioeconomy at specific levels including economic dimensions such as jobs, gross domestic product (value added), and environmental criteria such as air pollutant emissions, water and land use, ecotoxicity, and others. This supports a 2019 milestone in the BETO MYP and simultaneously addresses a gap previously identified in the BETO program and highlighted, e.g., by BETO Program Peer Reviewers in 2015 and 2017. To fill in this gap, NREL started collaborating with developers of the national level U.S. Environmentally-Extended Input-Output (USEEIO) model in FY18. This peer-reviewed, open source model is based on publicly available data, and developed and maintained by U.S. EPA where it has been the basis for EPA's Sustainable Material Management analyses and program. Also, USEEIO was initially designed for use with EPA's Tool for the Reduction and Assessment of Chemicals and Other Environmental Impacts (TRACI). It aligns well with similar efforts including the Federal LCA Commons and the Sustainable Acquisition Program at the Department of Defense (DoD). In FY18, NREL convened stakeholders from federal agencies, universities, and private sector entities to identify and form a common understanding of (1) models describing the U.S. economy and how to build off of them, (2) a bioeconomy definition for the next modeling steps, (3) the (sub)sectors that can/should be used in the framework, and (4) opportunities for collaboration and data sharing. NREL then created a first order model by disaggregating, i.e., separating the economic activities associated with and attributed to a selected product of the bioeconomy: corn ethanol. Corn ethanol is well studied and has a significant amount of public, validated economic industry information. This is important as disaggregation is a critical step in creating a representative and accurate framework. Corn ethanol served as a validation test case for the method and framework. By the end of FY18, the team was able to generate several scenarios for corn ethanol on national and selected regional levels providing results on the absolute and relative (Megajoule) effects in several environmental and economic impact categories. A second objective of the project is to inform BETO's strategic decision making, specifically its sustainability research portfolio, by engaging in, evaluating, and synthesizing selected global multi-year activities from the perspectives of a variety of complex multilateral and multi-stakeholder processes that pertain to bioenergy. This helps to (1) identify gaps, barriers, and critical areas for future BETO bioenergy and sustainability assessments; (2) identify opportunities and challenges to a sustainable U.S. bioeconomy; and (3) contribute to and disseminate BETO information to and from major global bioenergy and sustainability efforts. This project's work with multilateral organizations ensures that U.S. science-based viewpoints are considered and helps to balance the influence of the large number of countries with the same centralized philosophy. This engagement builds a more solid foundation for sustainable biomass and bioenergy systems in the U.S. and in the world. Working with multi-lateral, international platforms including IEA Bioenergy, Global Bio-Energy Partnership (GBEP), and their partner organizations also allows engagement with important stakeholders including policy makers, industry, NGOs, and academia.

09 BIOMASS FUELS↗

DOE OSTI2024

Data and Scripts associated with “Lambda-PFLOTRAN: Workflow for Incorporating Organic Matter Chemistry Informed by Ultra High Resolution Mass Spectrometry into Biogeochemical Modeling.”

This data package is associated with the publication “Lambda-PFLOTRAN: Workflow for Incorporating Organic Matter Chemistry Informed by Ultra High Resolution Mass Spectrometry into Biogeochemical Modeling” submitted to Geoscientific Model Development (Muller et al., 2024). In this manuscript, organic matter chemistry and thermodynamics are directly connected to reactive transport simulators through the newly developed Lambda-PFLOTRAN (Parallel Reactive Flow and Transport model) workflow tool that succinctly incorporates organic matter chemistry data generated from Fourier transform ion cyclotron resonance mass spectrometry (FTICR-MS) into reaction networks to simulate aerobic respiration of the organic matter and the resulting biogeochemistry. Lambda-PFLOTRAN is a python-based workflow, executed through a Jupyter Notebook interface, that digests raw FTICR-MS data, develops a representative reaction network based on substrate-explicit thermodynamic modeling (also termed lambda modeling due to its key thermodynamic parameter λ used therein), and completes a biogeochemical simulation with the open source, reactive flow, and transport code PFLOTRAN. This data package contains Jupyter Notebook based workflows for two test cases for running biogeochemical simulations of organic matter oxidation identified by FTICR-MS. It contains four primary folders (workflow, data, src, and analysis), a file-level metadata file (Muller_2024_Lambda_PFLOTRAN_Manuscript_Data_Package_flmd.csv) that lists all the files contained in this data package with a short description of each, and a data dictionary (Muller_2024_Lambda_PFLOTRAN_Manuscript_Data_Package_dd.csv) file that describes the tabular column headers. The ‘workflow’ folder contains the Jupyter Notebook based workflows for running the lambda analysis, PFLOTRAN simulation, sensitivity analysis and parameter estimation. The ‘data’ folder contains the FTICR-MS data, initial conditions, and incubation data for test cases 1 and 2 in folders titled ‘WHONDRS’ and ‘Colloids’, respectively. The data folder also has a ‘Database’ folder containing a reaction network for bulk organic matter (assumed to be CH2O) and a general database for PFLOTRAN (hanford_rxn_network). The CH2O reaction network defines bulk organic matter oxidation. Biogeochemical simulations are completed for both the lambda binned organic matter and bulk organic matter reaction networks. The ‘hanford_rxn_network’ database includes information required for PFLTORAN simulations including ion size, molar mass, and charge of the aqueous species, gases, and minerals phases. The ‘src’ folder contains python source codes for performing lambda analysis, PFLOTRAN simulation, sensitivity analysis and parameter estimation. The ‘analysis’ folder contains outputs from the test cases 1 and 2 including lambda analysis, PFLOTRAN runs and the calibration results.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2020

UQpy: A general purpose Python package and development environment for uncertainty quantification

In this paper, we present the UQpy software toolbox, an open-source Python package for general uncertainty quantification (UQ) in mathematical and physical systems. The software serves as both a user-ready toolbox that includes many of the latest methods for UQ in computational modeling and a convenient development environment for Python programmers advancing the field of UQ. The paper presents an introduction to the software's architecture and existing capabilities, divided in the code in a set of modules centered around different UQ tasks such as sampling methods, generation of random processes and random fields, probabilistic inverse modeling, reliability analysis, surrogate modeling, and active learning. The paper also highlights the importance of the RunModel module, which is used to drive simulations in the uncertainty analyses performed in UQpy. This module conveniently allows the user to define computational models directly in Python, or to run simulations from a third-party software in serial or in parallel. To illustrate the various capabilities, two examples are tracked throughout the paper and analyzed repeatedly for various UQ tasks. The first is a Python model solving a nonlinear structural dynamics problem, used to illustrate UQpy's capabilities in sampling and forward propagation of high dimensional random vectors (stochastic processes), and probabilistic inference. The second model is a third-party Abaqus finite element model solving the thermomechanical response of a beam structure. This example is used to illustrate UQpy's capabilities in variance reduction sampling techniques, reliability analysis, surrogate modeling and active learning techniques.

97 MATHEMATICS AND COMPUTING↗

NASA NTRS2014

Enhancement of the Earth Science and Remote Sensing Group's Website and Related Projects

The major problem addressed throughout the term was the need to update the group's current website, as it was outdated and required streamlining and modernization. The old Gateway to Astronaut Photography of the Earth website had multiple components, many of which involved searches through expansive databases. The amount of work required to update the website was large and due to a desired release date, assistance was needed to help build new pages and to transfer old information. Additionally, one of the tools listed on the website called Image Detective had been underutilized in the past. It was important to address why the public was not using the tool and how it could potentially become more of a resource for the team. In order to help with updating the website, it was necessary to first learn HTML. After assisting with small edits, I began creating new pages. I utilized the "view page source" and "developer" tools in the internet browser to observe how other websites created their features and to test changes without editing the code. I then edited the code to create an interactive feature on the new page. For the Image Detective Page I began an evaluation of the current page. I also asked my fellow interns and friends at my University to offer their input. I took all of the opinions into account and wrote up a document regarding my recommendations. The recommendations will be considered as I help to improve the Image Detective page for the updated website. In addition to the website, other projects included the need for additional, and updated image collections, along with various project requests. The image collections have been used by educators in the classroom and the impact crater collection was highly requested. The glaciers collection focused mostly on South American glaciers and needed to include more of the earth's many glaciers. The collections had not been updated or created due to the fact that related imagery had not been catalogued. The process of cataloging involves identifying the center point location of the image and feature identification. Other project needs included collecting night images of India in for publishing. Again, many of the images were not catalogued and the database was lacking in night time imagery for that region. The last project was to calculate the size of mega fans in South Africa. Calculating the fan sizes involved several steps. To expedite the study, calculations needed to be made after the base maps had been created. Using data files that included an outline of the mega fans on a topographic map, I opened the file in Photoshop, determined the number of pixels within the outlined area, created a one degree squared box, determined the pixels within the box, converted the pixels within the box to kilometers, and then calculated the fan size using this information. Overall, the internship has been a learning experience for me. I have learned how to use new programs and I developed new skills. These These skills can help me as I enter into the next phase of my career. Learning Photoshop and HTML in addition to coding in Dreamweaver are highly sought after skills that are used in a variety of fields. Additionally, the exposure to different aspects of the team and working with different people helped me to gain a broader set of skills and allowed me to work with people with different experiences. The various projects I have worked on this summer have directly benefitted the team whether it was completing projects they did not have the time to do, or by helping the team reach deadlines sooner. The new website will be the best place to see all of my work as it will include the newly designed pages and will feature my updates to collections.

Coffin, Ashley↗

DOE OSTI2026

Assessing Cloud and Precipitation Properties on Temporal and Spatial Scales Using LASSO Simulations over ENA

Low clouds and precipitation representation remain a major source of uncertainty in Earth System Models (ESMs), particularly due to challenges in representing their sub-grid variability and scale-dependent sampling. This study evaluates the performance of preliminary simulations from the Large-Eddy Simulation (LES) ARM Symbiotic Simulation and Observation (LASSO) project over the Eastern North Atlantic (ENA), with a focus on liquid water path (LWP), ice water path (IWP), cloud fraction (CF), and surface precipitation simulated across closed-cell, open-cell, and transitional cloud regimes. Using LES (100 m horizontal grid spacing) driven by ERA5 and MERRA-2 reanalyses, we assess the representativeness of ground-based point observations by analyzing their correspondence to model-resolved spatial and temporal means. Results suggest that observational sampling of at least 6 hours is required to achieve consistency with domain-scale averages, in particular for observations that exhibit pronounced sub-grid heterogeneity, such as precipitation. ERA5-forced simulations exhibit improved spatial coherence and agreement with domain-averaged quantities when compared to MERRA-2 runs, with performance discrepancies largest for convective cloud conditions due to differences in forcing fidelity and temporal resolution. These findings highlight the importance of regime-aware model evaluation strategies and potentially demonstrate how LES can inform observation-model comparison practices and the development of cloud and precipitation parameterizations in ESMs.

Liang, Jiakun [University of Hawai'i at Manoa] (OR↗

DOE OSTI2023

Influence of urban extent discrepancy on the estimation of surface urban heat island intensity: A global-scale assessment in 892 cities

The estimation of surface urban heat island intensity (SUHII) is crucial for studying the urban thermal environment, which is influenced not only by the commonly known definition of rural reference but also by the delineation of urban extent. Existing studies relies on various urban extent products defined in different ways, and the influence of urban extent discrepancy (UED) on SUHII estimates still remains unclear. In this study, we collected five open-source global urban extent products (GUEPs) for the year 2015 and corresponding daily land surface temperature (LST) observations (MYD11A1). Based on these products, we quantified the UED-induced uncertainty in SUHII estimates by comparing absolute difference (ΔSUHII AD ) and relative difference (ΔSUHII RD ) in SUHII among GUEPs across 892 global cities. Additionally, we introduced an ISF-constrained (ISF–C) method to reduce SUHII differences among GUEPs by constraining the impervious surface fraction (ISF) within urban and rural extents. The results show that urban extents delineated by different GUEPs are not consistent, leading to their difference in ISF as well as LST, which in turn causes uncertainties in the estimated SUHII. On average for global cities, the annual daytime and nighttime ΔSUHII AD are 0.46 ± 0.02 °C (mean ± 95% confidence interval) and 0.24 ± 0.01 °C, with corresponding ΔSUHII RD of 42.0 ± 2.7% and 35.2 ± 2.3%, respectively. The UED-induced uncertainty in SUHII estimates varies among climate zones, and the annual daytime ΔSUHII RD averaged for cities located in the arid zone reaches up to 60.8 ± 6.6%, which is nearly twice as high as that in other climate zones. More importantly, both ΔSUHII AD and ΔSUHII RD show lower values when using the ISF-C method, implying the effectiveness of this method. This study highlights the non-negligible impact of UED on the estimation of SUHII, which requires more attention due to the inconsistency of urban extents among current products.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2023

Rewiring cell-free metabolic flux in E. coli lysates using a block—push—pull approach

Abstract Cell-free systems can expedite the design and implementation of biomanufacturing processes by bypassing troublesome requirements associated with the use of live cells. In particular, the lack of survival objectives and the open nature of cell-free reactions afford engineering approaches that allow purposeful direction of metabolic flux. The use of lysate-based systems to produce desired small molecules can result in competitive titers and productivities when compared to their cell-based counterparts. However, pathway crosstalk within endogenous lysate metabolism can compromise conversion yields by diverting carbon flow away from desired products. Here, the ‘block—push—pull’ concept of conventional cell-based metabolic engineering was adapted to develop a cell-free approach that efficiently directs carbon flow in lysates from glucose and toward endogenous ethanol synthesis. The approach is readily adaptable, is relatively rapid and allows for the manipulation of central metabolism in cell extracts. In implementing this approach, a block strategy is first optimized, enabling selective enzyme removal from the lysate to the point of eliminating by-product-forming activity while channeling flux through the target pathway. This is complemented with cell-free metabolic engineering methods that manipulate the lysate proteome and reaction environment to push through bottlenecks and pull flux toward ethanol. The approach incorporating these block, push and pull strategies maximized the glucose-to-ethanol conversion in an Escherichia coli lysate that initially had low ethanologenic potential. A 10-fold improvement in the percent yield is demonstrated. To our knowledge, this is the first report of successfully rewiring lysate carbon flux without source strain optimization and completely transforming the consumed input substrate to a desired output product in a lysate-based, cell-free system.

59 BASIC BIOLOGICAL SCIENCES↗

NASA NTRS2009

T-Slide Linear Actuators

T-slide linear actuators use gear bearing differential epicyclical transmissions (GBDETs) to directly drive a linear rack, which, in turn, performs the actuation. Conventional systems use a rotary power source in conjunction with a nut and screw to provide linear motion. Non-back-drive properties of GBDETs make the new actuator more direct and simpler. Versions of this approach will serve as a long-stroke, ultra-precision, position actuator for NASA science instruments, and as a rugged, linear actuator for NASA deployment duties. The T slide can operate effectively in the presence of side forces and torques. Versions of the actuator can perform ultra-precision positioning. A basic T-slide actuator is a long-stroke, rack-and-pinion linear actuator that, typically, consists of a T-slide, several idlers, a transmission to drive the slide (powered by an electric motor) and a housing that holds the entire assembly. The actuator is driven by gear action on its top surface, and is guided and constrained by gear-bearing idlers on its other two parallel surfaces. The geometry, implemented with gear-bearing technology, is particularly effective. An electronic motor operating through a GBDET can directly drive the T slide against large loads, as a rack and pinion linear actuator, with no break and no danger of back driving. The actuator drives the slide into position and stops. The slide holes position with power off and no brake, regardless of load. With the T slide configuration, this GBDET has an entire T-gear surface on which to operate. The GB idlers coupling the other two T slide parallel surfaces to their housing counterpart surfaces provide constraints in five degrees-of-freedom and rolling friction in the direction of actuation. Multiple GB idlers provide roller bearing strength sufficient to support efficient, rolling friction movement, even in the presence of large, resisting forces. T-slide actuators can be controlled using the combination of an off-the-shelf, electric servomotor, a motor angle resolution sensor (typically an encoder or resolver), and microprocessor-based intelligent software. In applications requiring precision positioning, it may be necessary to add strain gauges to the T-slide housing. Existing sensory- interactive motion control art will work for T slides. For open-loop positioning, a stepping motor emulation technique can be used.

Vranish, John↗

DOE OSTI2021

Effects of marine organic aerosols as sources of immersion-mode ice-nucleating particles on high-latitude mixed-phase clouds

Mixed-phase clouds are frequently observed in high-latitude regions and have important impacts on the surface energy budget and regional climate. Marine organic aerosol (MOA), a natural source of aerosol emitted over ~70 % of Earth's surface, may significantly modify the properties and radiative forcing of mixed-phase clouds. However, the relative importance of MOA as a source of ice-nucleating particles (INPs) in comparison to mineral dust, and MOA's effects as cloud condensation nuclei (CCN) and INPs on mixed-phase clouds are still open questions. In this study, we implement MOA as a new aerosol species into the Community Atmosphere Model version 6 (CAM6), the atmosphere component of the Community Earth System Model version 2 (CESM2), and allow the treatment of aerosol–cloud interactions of MOA via droplet activation and ice nucleation. CAM6 reproduces observed seasonal cycles of marine organic matter at Mace Head and Amsterdam Island when the MOA fraction of sea spray aerosol in the model is assumed to depend on sea spray biology but fails when this fraction is assumed to be constant. Model results indicate that marine INPs dominate primary ice nucleation below 400 hPa over the Southern Ocean and Arctic boundary layer, while dust INPs are more abundant elsewhere. By acting as CCN, MOA exerts a shortwave cloud forcing change of -2.78 W m-2 over the Southern Ocean in the austral summer. By acting as INPs, MOA enhances the longwave cloud forcing by 0.35 W m-2 over the Southern Ocean in the austral winter. The annual global mean net cloud forcing changes due to CCN and INPs of MOA are -0.35 and 0.016 W m-2, respectively. These findings highlight the vital importance for Earth system models to consider MOA as an important aerosol species for the interactions of biogeochemistry, hydrological cycle, and climate change.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2020

Physical drivers facilitating a toxigenic cyanobacterial bloom in a major Great Lakes tributary

The Maumee River is the primary source for nutrients fueling seasonal Microcystis -dominated blooms in western Lake Erie's open waters though such blooms in the river are infrequent. The river also serves as source water for multiple public water systems and a large food services facility in northwest Ohio. On 20 September 2017, an unprecedented bloom was reported in the Maumee River estuary within the Toledo metropolitan area, which triggered a recreational water advisory. Here we (1) explore physical drivers likely contributing to the bloom's occurrence, and (2) describe the toxin concentration and bacterioplankton taxonomic composition. A historical analysis using 10-years of seasonal river discharge, water level, and local wind data identified two instances when high-retention conditions occurred over ≥ 10 d in the Maumee River estuary: in 2016 and during the 2017 bloom. Observation by remote sensing imagery supported the advection of cyanobacterial cells into the estuary from the lake during 2017 and the lack of an estuary bloom in 2016 due to a weak cyanobacterial bloom in the lake. A rapid-response survey during the 2017 bloom determined levels of the cyanotoxins, specifically microcystins, in excess of recreational contact limits at sites within the lower 20 km of the river while amplicon sequencing found these sites were dominated by Microcystis . These results highlight the need to broaden our understanding of physical drivers of cyanobacterial blooms within the interface between riverine and lacustrine systems, particularly as such blooms are expected to become more prominent in response to a changing climate.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2023

Criterion validity of wrist accelerometry for assessing energy intake via the intake-balance technique

Background: Intake-balance assessments measure energy intake (EI) by summing energy expenditure (EE) with concurrent change in energy storage (ΔES). Prior work has not examined the validity of such calculations when EE is estimated via open-source techniques for research-grade accelerometry devices. The purpose of this study was to test the criterion validity of accelerometry-based intake-balance methods for a wrist-worn ActiGraph device. Methods: Healthy adults (n = 24) completed two 14-day measurement periods while wearing an ActiGraph accelerometer on the non-dominant wrist. During each period, criterion values of EI were determined based on ΔES measured by dual X-ray absorptiometry and EE measured by doubly labeled water. A total of 11 prediction methods were tested, 8 derived from the accelerometer and 3 from non-accelerometry methods (e.g., diet recall; included for comparison). Group-level validity was assessed through mean bias, while individual-level validity was assessed through mean absolute error, mean absolute percentage error, and Bland–Altman analysis. Results: Mean bias for the three best accelerometry-based methods ranged from -167 to 124 kcal/day, versus -104 to 134 kcal/day for the non-accelerometry-based methods. The same three accelerometry-based methods had mean absolute error of 323–362 kcal/day and mean absolute percentage error of 18.1-19.3%, versus 353–464 kcal/day and 19.5-24.4% for the non-accelerometry-based methods. All 11 methods demonstrated systematic bias in the Bland–Altman analysis. Conclusions: Accelerometry-based intake-balance methods have promise for advancing EI assessment, but ongoing refinement is necessary. We provide an R package to facilitate implementation and refinement of accelerometry-based methods in future research (see paulhibbing.com/IntakeBalance).

60 APPLIED LIFE SCIENCES↗

DOE OSTI2026

Quantum defects in carbon nanotubes as single-photon sources

Single-photon emitters are essential components of emerging quantum technologies, including secure communication and quantum computing. Single-walled carbon nanotubes (SWCNTs) have emerged as a promising platform for quantum light sources due to their quasi-one-dimensional excitonic host structure and compatibility with telecom photonic systems. Recent advances in deterministic defect engineering—most notably the development of organic color centers (OCCs)—have enabled stable, chemically controllable, and spectrally tunable single-photon emission. OCC-based emitters have demonstrated single-photon purity exceeding 99% and, more recently, room-temperature photon indistinguishability, placing them among the few solid-state systems with quantum-grade performance under ambient conditions. This review surveys progress in the field from three complementary perspectives: chemical synthesis and quantum defect engineering, computational studies of structure-property relationships and excitonic behavior, and experimental investigations of quantum optical properties. We also discuss alternative approaches, including air-suspended SWCNTs and hybrid van der Waals heterostructures, highlighting opportunities and open challenges for scalable integration into quantum photonic platforms.

36 MATERIALS SCIENCE↗

DOE OSTI2020

Fire, dust, air and water: Improving aerosol biogeochemistry interactions in ACME. Final report

Aerosol-biogeochemistry interactions will have important consequences for human health, ecosystem services, and climate feedbacks over the next several decades. In this proposal we seek to link how human activities on land, including direct industrial emissions and landscape fires, impact the atmosphere and the biogeochemistry of the ocean and land. Our overall goal was to complement existing work at DOE labs to improve the capability and performance of the E3SM model in short-term, high-resolution projections of climate. Projections of ocean uptake of anthropogenic carbon are highly dependent on the details of the ocean physical and biogeochemistry parameterizations. Potentially equally important are the estimates of increases in iron and soluble nitrogen deposition in aerosols to the open ocean, but there are substantial uncertainties in these feedbacks. The E3SM land model simulates natural and anthropogenic fires, but improvement is needed to more accurately simulate fire responses to climate variability as well as fire contributions to terrestrial climate feedbacks. This proposal addressed four of the six priorities within the ACME/E3SM call by improving the representation of fire, industrial combustion sources, and desert dust and adding iron and soluble iron to the atmospheric chemistry (1). Our work focused on improving ocean biogeochemistry and the response of the oceans to anthropogenic atmospheric iron and nitrogen (3). We also improved the representation of land disturbance on fires and fire mediated carbon cycle feedbacks in the land model (4). Finally we had planned to couple the land, atmosphere and ocean biogeochemical systems (6) and explore how this coupling changes the feedbacks in the climate system. Our work under this proposal was separated into the following 5 tasks: i) improve representation of fire dynamics in both boreal and tropical ecosystems, ii) improve estimates of industrial emissions of iron and phosphorus, iii) improve representation of atmospheric iron, phosphorus and nitrogen transport, chemistry and deposition, iv) improve representation of iron, phosphorus and nitrogen deposition impacts on ocean biogeochemistry, and v) couple emissions into atmosphere, to deposition onto land and ocean biogeochemistry. For all 5 tasks, we conducted offline experiments of the historical period to enable comparison with available aerosol and land surface observations. We had planned to conduct fully coupled simulations, however, these will be conducted as part of the coupling in version 3 and 4 of the E3SM model, and thus have not been completed.

54 ENVIRONMENTAL SCIENCES↗

NASA NTRS2013

Small Radioisotope Power System Testing at NASA Glenn Research Center

In April 2009, NASA Glenn Research Center (GRC) formed an integrated product team (IPT) to develop a Small Radioisotope Power System (SRPS) utilizing a single Advanced Stirling Convertor (ASC) with passive balancer. A single ASC produces approximately 80 We making this system advantageous for small distributed lunar science stations. The IPT consists of Sunpower, Inc., to provide the single ASC with a passive balancer, The Johns Hopkins University Applied Physics Laboratory (JHUAPL) to design an engineering model Single Convertor Controller (SCC) for an ASC with a passive balancer, and NASA GRC to provide technical support to these tasks and to develop a simulated lunar lander test stand. The single ASC with a passive balancer, simulated lunar lander test stand, and SCC were delivered to GRC and were tested as a system. The testing sequence at GRC included SCC fault tolerance, integration, electromagnetic interference (EMI), vibration, and extended operation testing. The SCC fault tolerance test characterized the SCCs ability to handle various fault conditions, including high or low bus power consumption, total open load or short circuit, and replacing a failed SCC card while the backup maintains control of the ASC. The integrated test characterized the behavior of the system across a range of operating conditions, including variations in cold-end temperature and piston amplitude, including the emitted vibration to both the sensors on the lunar lander and the lunar surface. The EMI test characterized the AC and DC magnetic and electric fields emitted by the SCC and single ASC. The vibration test confirms the SCCs ability to control the single ASC during launch. The extended operation test allows data to be collected over a period of thousands of hours to obtain long term performance data of the ASC with a passive balancer and the SCC. This paper will discuss the results of each of these tests.

Vibration↗