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At least 523 records · Page 29

Simulations With the Marine Biogeochemistry Library (MARBL)

Abstract The Marine Biogeochemistry Library (MARBL) is a prognostic ocean biogeochemistry model that simulates marine ecosystem dynamics and the coupled cycles of carbon, nitrogen, phosphorus, iron, silicon, and oxygen. MARBL is a component of the Community Earth System Model (CESM); it supports flexible ecosystem configuration of multiple phytoplankton and zooplankton functional types; it is also portable, designed to interface with multiple ocean circulation models. Here, we present scientific documentation of MARBL, describe its configuration in CESM2 experiments included in the Coupled Model Intercomparison Project version 6 (CMIP6), and evaluate its performance against a number of observational data sets. The model simulates present‐day air‐sea CO 2 flux and many aspects of the carbon cycle in good agreement with observations. However, the simulated integrated uptake of anthropogenic CO 2 is weak, which we link to poor thermocline ventilation, a feature evident in simulated chlorofluorocarbon distributions. This also contributes to larger‐than‐observed oxygen minimum zones. Moreover, radiocarbon distributions show that the simulated circulation in the deep North Pacific is extremely sluggish, yielding extensive oxygen depletion and nutrient trapping at depth. Surface macronutrient biases are generally positive at low latitudes and negative at high latitudes. CESM2 simulates globally integrated net primary production (NPP) of 48 Pg C yr −1 and particulate export flux at 100 m of 7.1 Pg C yr −1 . The impacts of climate change include an increase in globally integrated NPP, but substantial declines in the North Atlantic. Particulate export is projected to decline globally, attributable to decreasing export efficiency associated with changes in phytoplankton community composition.

Meteorology & Atmospheric Sciences↗

libEnsemble: A complete Python toolkit for dynamic ensembles of calculations

Almost all science and engineering applications eventually stop scaling: their runtime no longer decreases as available computational resources increase. Therefore, many applications will struggle to efficiently use emerging extreme-scale high-performance, parallel, and distributed systems. libEnsemble is a complete Python toolkit and workflow system for intelligently driving ensembles of experiments or simulations at massive scales. It enables and encourages multidisciplinary design, decision, and inference studies portably running on laptops, clusters, and supercomputers.

97 MATHEMATICS AND COMPUTING↗

Evaluating Portable Parallelization Strategies for Heterogeneous Architectures in High Energy Physics

High-energy physics (HEP) experiments have developed millions of lines of code over decades that are optimized to run on traditional x86 CPU systems. However, we are seeing a rapidly increasing fraction of floating point computing power in leadership-class computing facilities and traditional data centers coming from new accelerator architectures, such as GPUs. HEP experiments are now faced with the untenable prospect of rewriting millions of lines of x86 CPU code, for the increasingly dominant architectures found in these computational accelerators. This task is made more challenging by the architecture-specific languages and APIs promoted by manufacturers such as NVIDIA, Intel and AMD. Producing multiple, architecture-specific implementations is not a viable scenario, given the available person power and code maintenance issues. The Portable Parallelization Strategies team of the HEP Center for Computational Excellence is investigating the use of Kokkos, SYCL, OpenMP, std::execution::parallel and alpaka as potential portability solutions that promise to execute on multiple architectures from the same source code, using representative use cases from major HEP experiments, including the DUNE experiment of the Long Baseline Neutrino Facility, and the ATLAS and CMS experiments of the Large Hadron Collider. This cross-cutting evaluation of portability solutions using real applications will help inform and guide the HEP community when choosing their software and hardware suites for the next generation of experimental frameworks. We present the outcomes of our studies, including performance metrics, porting challenges, API evaluations, and build system integration.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

High Temperature Polymer Electrolyte Membrane Fuel Cell Electrode Composition: Durable Fuel Cell Power under Anhydrous Conditions

Innovators/Researchers at Los Alamos National Laboratory have developed an electrode composition that improves fuel cell performance under anhydrous conditions above 100°C. It has demonstrated great durability in humidified conditions under 100°C as well. It holds promise for use in fuel cells for heavy duty vehicles while retaining utility for portable and stationary power applications. In coming years this flexibility may be a breakthrough improvement over conventional compositions.

25 ENERGY STORAGE↗

Design of a graphical user interface for few-shot machine learning classification of electron microscopy data

The recent growth in data generation by modern electron microscopes requires rapid, scalable, and flexible approaches to image segmentation and analysis. Few-shot machine learning, which can richly classify images from a handful of user-provided examples, is a promising route to high-throughput analysis. However, current command-line implementations of such approaches can be slow and unintuitive to use, lacking the real-time feedback necessary to perform effective classification. Here we report on the development of a Python-based graphical user interface that enables end users to easily conduct and visualize the output of few-shot learning models. This interface is portable and can be hosted locally or on the web, providing the opportunity to reproducibly conduct, share, and crowd-source few-shot analyses.

97 MATHEMATICS AND COMPUTING↗

Measuring nonlinearities of a cantilever beam using a low-cost efficient wireless intelligent sensor for strain (LEWIS-S)

In the context of experimental vibration data, strain gauges can obtain linear and nonlinear dynamic measurements. However, measuring strain can be disincentivizing and expensive due to the complexity of data acquisition systems, lack of portability, and high costs. This research introduces the use of a low-cost efficient wireless intelligent sensor for strain (LEWIS-S) that is based on a portable-sensor-design platform that streamlines strain sensing. Additionally, the softening behavior of a cantilever beam with geometric and inertial nonlinearities is characterized by the LEWIS-S based on high force level inputs. Two experiments were performed on a nonlinear cantilever beam with measurements obtained by the LEWIS-S sensor and an accelerometer. First, a sine sweep test was performed through the fundamental resonance of the system, then a ring-down test was performed from a large initial static deformation. Good agreement was revealed in quantities of interest such as frequency response functions, the continuous wavelet transforms, and softening behavior in the backbone curves.

42 ENGINEERING↗

Miniaturized Scanning Electrical Mobility Sizer (mSEMS) Instrument Handbook – Airborne Version

The miniaturized scanning electrical mobility sizer (mSEMS), as shown in Figure 1, represents an advancement in particle size measurement technology. Designed for portability, this compact instrument is engineered to deliver precise and accurate assessments of particle size distributions. The mSEMS uses scanning electrical mobility sizing technology to analyze aerosol particles within a specified size range. Its miniaturized design does not compromise on performance, making it ideal for a myriad of applications across laboratory research, environmental monitoring, and industrial settings. The user friendly interface simplifies operation, while the instrument's robust construction ensures reliability in various conditions. Researchers and professionals can rely on the mSEMS to provide invaluable insights into aerosol dynamics, contributing to advancements in aerosol science.

54 ENVIRONMENTAL SCIENCES↗

Solid-State Mixed-Potential Electrochemical Sensors for Natural Gas Leak Detection and Quality Control (Final Technical Report)

Mitigation of methane emissions are a critical factor to limiting the impact of the natural gas industry on global climate change. Throughout the period of 2020-2024, the University of New Mexico and its commercialization partner and subcontractor, SensorComm Technologies, Inc. (SCT), have worked together to develop a low-cost Artificial Intelligence (AI)-driven Internet of Things (IoT)-based multi-gas sensor platform for methane emissions detection. In the final year of the project, we extended this work to include hydrogen detection in support of a transition to a hydrogen economy where hydrogen could be transported through existing natural gas infrastructure. Mixed potential electrochemical sensors were first prototyped by ceramic additive manufacturing and then transitioned to conventional ceramic manufacturing tape casting and screen-printing technologies in preparation for mass production. Demonstrated limits of detection of 5 ppm of methane in natural gas and 1 ppm of hydrogen were measured. These limits of detection are among the lowest of solid-state electrochemical sensors that have been reported in the literature or available in the industry. Machine learning algorithms were developed to identify natural gas mixtures with > 98% accuracy level and quantify methane concentrations at 97% accuracy. The presence of hydrogen could also be identified, and its concentration quantified at these accuracy levels. These algorithms were optimized for running on portable computing hardware which enabled > 1 Hz processing rates. A portable packaged IoT system was integrated with the electrochemical sensor in collaboration with SCT. The package consists of readout electronics with < 1 mV resolution, sensor temperature control, and data transmission over cellular wireless and/or Wi-Fi networks. Field testing was performed in two rounds at Colorado State University’s Methane Emissions Technology Evaluation Center (CSU METEC). The first round of testing demonstrated successful measurements of methane from an underground natural gas leak of 20 standard liters per minute (SLPM), which agreed with previously published literature using more sophisticated and expensive analytical equipment. The second round of testing showed that an above ground leak of 2 SLPM of hydrogen could be detected at 32 ft. This project has resulted in six published peer reviewed journal articles, over ten presentations at professional conferences, and one full patent application filed in 2023. Future work on this project includes increased sensitivity, higher production yields, and applications in the hydrogen safety and flare emissions monitoring spaces.

03 NATURAL GAS↗

Titanium Niobium Oxide: From Discovery to Application in Fast-Charging Lithium-Ion Batteries

Lithium-ion batteries are essential for portable technology and are now poised to disrupt a century of combustion-based transportation. The electrification revolution could eliminate our reliance on fossil fuels and enable a clean energy future; advanced batteries would facilitate this transition. However, owing to the demanding performance, cost, and safety requirements, it is challenging to translate new materials from laboratory prototypes to industrial-scale products. This Perspective describes that journey for a new lithium-ion battery anode material, TiNb 2 O 7 (TNO). TNO is intended as an alternative to graphite or Li 4 Ti 5 O 12 with better rate and safety characteristics than the former and higher energy density than the latter. The high capacity of TNO stems from the multielectron redox of Nb 5+ to Nb 3+ , its operating voltage window well above the Li + /Li reduction potential prevents lithium dendrite formation, and its open crystal structure leads to high-power performance. Nevertheless, the creation of a practical TNO anode was nonlinear and nontrivial. Its history is built on 30 years of fundamental science that preceded its application as a battery anode, and its battery development included a nearly 30-year gap. The insights and lessons contained in this Perspective, many of them acquired firsthand, serve two purposes: (i) to unite the disparate studies of TiNb 2 O 7 into a coherent modern understanding relevant to its application as a battery material and (ii) to highlight briefly some of the challenges faced when scaling up a new material that affect TiNb 2 O 7 as well as new electrode candidates more generally.

25 ENERGY STORAGE↗

Translating a Material Discovery into a Commercial Product in the Modern Lithium-ion Battery Market

Lithium-ion batteries are essential for portable technology and are now poised to disrupt a century of combustion-based transportation. The electrification revolution could eliminate our reliance on fossil fuels and enable a clean energy future; advanced batteries would facilitate this transition. However, owing to the demanding performance, cost, and safety requirements, it is challenging to translate new materials from laboratory prototypes to commercial products. This Perspective describes that journey toward commercialization for a new lithium-ion battery anode material, TiNb2O7 (TNO). TNO is intended as an alternative to graphite or Li4Ti5O12 with better rate and safety characteristics than the former, and higher energy density than the latter. The high capacity of TNO stems from multielectron redox of Nb5+ to Nb3+, its operating voltage window well above Li+/Li reduction potential prevents lithium dendrite formation, and its open crystal structure leads to high-power performance. Nevertheless, the creation of a practical TNO anode was non-linear and non-trivial. Its history is built on 30 years on fundamental science that preceded its application as a battery, and its battery development included a nearly 30-year gap. The insights and lessons 2 contained in this Perspective, many of them acquired firsthand, serve two purposes: (i) to unite the disparate studies of TiNb2O7 into a coherent modern understanding relevant to its application as a battery material and (ii) to highlight some of the considerations of commercializing a new material that affect TiNb2O7 as well as new electrode candidates more generally.

Griffith, Kent J.↗

Operation of Layered LiCoO 2 to Higher Voltages with a Localized Saturated Electrolyte

The commercialization of lithium-ion batteries started with the layered LiCoO 2 (LCO) cathode for portable electronics, but only 50% of its theoretical capacity can be used in practical cells due to detrimental surface and bulk degradations when charged to high voltages. Here we demonstrate here that the stability of electrolyte plays a critical role in the performance of LCO at high voltages by employing a localized saturated electrolyte (LSE). With a cutoff voltage of 4.5 V, LCO achieves an initial 1C discharge capacity of 176 mA h g -1 and a capacity retention of 80% over 230 cycles. Even with a cutoff voltage of 4.6 V, LCO with 2% aluminum doping displays an initial discharge capacity of 189 mA h g -1 at 1C rate with 80% capacity retention over 137 cycles. With extensive analytical characterization, we show that the improved cycling stability stems from a suppression of the O3 to H1-3 phase transition as well as a robust inorganic-rich cathode-electrolyte interphase (CEI) facilitated by the LSE. This work highlights the importance of protecting the surface as well as the bulk with appropriate electrolytes for the high-voltage, higher-energy-density operation of LCO.

25 ENERGY STORAGE↗

A Computational Review of Privacy-Preserving Mechanisms for the Smart Grid

Smart grid technologies have rapidly become one of the largest and most comprehensive sources of data for the modern utility. For the most part, data streams are seen as an essential tool that enable utilities to carry their day-to-day business operations, but they also create the need for efficient and secure data management strategies. In the context of the smart grid, ensuring data privacy is becoming an increasing concern due to a combination of factors that range from shifts in operational paradigms and rapid technology evolution to changes in legislation. Furthermore, researchers have highlighted the risks associated with improperly protected energy records. For example, energy consumption data from homes could be used to infer the behaviors and habits of home occupants through activity recognition or user profiling (Fan, 2017), which may lead to unfair service pricing, targeted advertising, or other personal security violations. Similarly, Electric Vehicles’ (EVs) charging metadata could be used to reveal private information about the owner such as their payment methods, preferred charging stations, and other locational and timing information that could be used to reconstruct the vehicle owner’s behaviors. The privacy of user data, even when used for statistical analysis or machine learning training processes, also needs to be carefully considered, as an individual’s private traits may still be vulnerable if their inclusion/exclusion greatly impacts the result or could be linked to a public dataset through cross-reference. The breach of user privacy also has severe impacts for organizations that store, transmit, or work on the data in the form of diminishing the public’s trust in them while potentially incurring legal consequences (e.g., fines and suspensions under the European Union General Data Protection Regulation, Health Insurance Portability and Accountability Act, etc.). Because of these risks, several privacy-preserving mechanisms are available to help organizations comply with privacy legislations and prevent the unauthorized and malicious use of user data. In light of these concerns, this report focuses on performing a computational review of privacy-preserving mechanisms that have received a significant amount of interest in literature. It specifically focuses on 1) homomorphic encryption, 2) zero-knowledge proofs, 3) differential privacy, and 4) federated learning. It is worth noting that although many of the methods presented in this document rely on cryptographic primitives, their intent is not to provide perfect secrecy, but rather to enable users to maintain privacy, and thus they shall not be compared or equated to other constructs that are aimed to address cybersecurity constructs.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Surface Structure of Reacting Solid Ramjet Fuels

Solid fuel ramjets are a developing technology that will enable extended range for supersonic vehicles. The simplicity of the system in terms of moving parts results in the performance being dictated by the solid fuel combustion processes. The physics near the surface, particularly in the fuel-rich recirculation zone, are challenging to resolve due to flow opacity. Here, regression rate measurements of hydroxyl-terminated polybutadiene from a miniature, portable slab burner are reported. Mass-averaged regression rates agree with correlations from the literature, suggesting that the proper physics in the burner are captured. Synchrotron-based phase-contrast imaging is used to quantify local surface features, including a multiphase froth layer, molten polymer transport, and local regression rate measurements in the recirculation zone. Regression rates near the inlet are less than the mass-averaged values, whereas near the reattachment point the local value exceeds the mass-averaged values. Further, the observed froth layer is as large as 2 mm near the inlet and decreases to sub-millimeter thicknesses near the reattachment point. An analytical heat transfer model is used to quantify the influence of the surface froth layer on the regression rates. Results indicate that the froth layer has an insulating effect and will reduce the local regression rate.

33 ADVANCED PROPULSION SYSTEMS↗

SPRUCE Photosynthesis and Respiration of Picea mariana and Larix laricina in SPRUCE Experimental Plots, 2016-2017

This dataset contains empirical physiological, morphological, and chemical data collected on two dominant conifer species, Picea mariana and Larix laricina, between May 2016 and August 2017 at the SPRUCE (Spruce and Peatland Responses Under Changing Environments) experimental site within the Marcell Experimental Forest in northern Minnesota, USA. Analyses assessed the response of conifers to whole-ecosystem warming and elevated atmospheric carbon dioxide (CO2) concentrations. Measurements include light-saturated net photosynthesis and dark respiration at ambient atmospheric carbon dioxide (CO2) concentration (2016), CO2 response curves of light-saturated net photosynthesis (2017), leaf morphology (leaf mass per unit leaf area) and nitrogen content (on both mass and area basis). Leaf photosynthesis and respiration were measured with portable photosynthesis systems (LI6400XT, LI6800, LI-COR Biosciences, USA). In 2016, photosynthesis and respiration were measured at a common temperature of 25 ˚C to assess thermal acclimation, and at growth temperatures (for each of the five treatment temperatures) to assess field performance. In 2017, CO2 response curves of net photosynthesis (so-called A-Ci curves) were conducted at different leaf temperatures (15, 25, 32.5, 40 and 45 ˚C) for assessment of biochemical parameters and their temperature sensitivity. In addition, dark respiration measurements at different leaf temperatures (10, 15, 20, 25, 30, 35, 40, and 45 ºC) were also taken. This dataset contains one data file in comma-separate values (*.csv) and Microsoft Excel (*.xlsx) format. Additional metadata are provided: a data dictionary and a file-level metadata file in comma-separate values (.csv) format and a user guide in PDF (*.pdf) format.

54 ENVIRONMENTAL SCIENCES↗

Portable diagnostic package for Thomson scattering and optical emission spectroscopy on Princeton field-reversed configuration 2 (PFRC 2)

An Advanced Research Projects Agency-Energy funded diagnostic system has been deployed to the Princeton field-reversed configuration 2 (PFRC-2) device, located at Princeton Plasma Physics Laboratory. The Portable Diagnostic Package (PDP), designed at Oak Ridge National Laboratory, allows for the measurement of Thomson Scattering (TS) for electron density and temperature and Optical Emission Spectroscopy (OES) for ion temperature, impurity density, and ion velocity. A tunable spectrometer on the PDP with three gratings provides the flexibility to measure low (1 eV) and high (1000 eV) electron temperature ranges from TS. Additionally, using a second spectrometer, the OES diagnostic can survey light emission from various ion excitation levels for wide wavelength ranges. The electron density (<2 × 10 19 m –3 ) of plasmas generated in PFRC-2 has been below the PDP TS discrimination threshold, which has made TS signal detection challenging against a high-background of laser stray light. The laser stray light was iteratively reduced by making modifications to the entrance and exit geometry on PFRC-2. Rayleigh scattering experiments on PFRC have yielded the TS discrimination sensitivity to be >1 × 10 20 m –3 for the PDP. A recently implemented narrow-band notch spectral filter that masks the second harmonic 532 nm Nd:YAG laser wavelength has increased the system’s TS light discrimination sensitivity 65 times compared to the instance when the notch filter was not implemented. The hardware implementation including design changes to the flight tubes and Brewster windows will be discussed, along with results from Rayleigh and rotational Raman scattering sensitivity analyses, which were used to establish a quantitative figure of merit on the system performance. Further, the Raman scattering calibration with the notch filter has improved the PDP electron density threshold to 1 ± 0.5 × 10 18 m –3 .

47 OTHER INSTRUMENTATION↗

Development of a field-deployable qPCR assay for real-time pest monitoring in algal cultivation systems

Outdoor cultivation is commonly used to produce algal biomass for a variety of bioproducts including food, feed, fuel, pharmaceuticals, and nutraceuticals. Outdoor cultivation ponds are highly susceptible to pest pressures that may lead to periods of low productivity or even entire loss of the algal crop. Consequently, there is a need for rapid, real-time tracking of pests for early intervention to mitigate crop loss. In this work, we describe the development of a field deployable, low-cost qPCR assay for detecting both known and novel pests of a farmed eukaryotic alga species, Nannochloropsis sp. We performed a proximity guided metagenome deconvolution approach (ProxiMeta™) to discover novel pests that temporally correspond to periods of reduced pond productivity. This approach provided high-quality metagenome assemblies that were used to design qPCR probes to detect specific pests of interest. The portable qPCR assay, designed to be deployed at remote field locations, enables low-cost surveillance with a rapid (2 h) turn-around time. Frequent sampling allows for early detection and prompts intervention strategies to remedy infected ponds to minimize crop loss. The qPCR assay was used to successfully detect a known predatory bacterium within the order Bdellovibrionales both in the lab and at a remote field location. Furthermore, we assembled the genome of two novel, site-specific pests in the Saprospiraceae family and successfully designed qPCR probes that differentially detected their presence in two different pond locations. Ultimately, this assay has the potential to monitor multiple pests simultaneously and tailor targets to match likely pest infections that differ across geographical locations, helping to mitigate crop loss on a large scale.

59 BASIC BIOLOGICAL SCIENCES↗

Simple Bioparticle Filtration Device Based on an Ultralow-Fouling Zwitterionic Polyurethane Membrane for Rapid Large-Volume Separation of Plasma and Viruses from Whole Blood

Plasma separation from whole blood is oftent required as an essential first step when performing blood tests with a viral assay. However, developing a point-of-care plasma extraction device with a large output and high virus recovery remains a significant obstacle to the success of on-site viral load tests. Here, we report a portable, easy-to-use, cost-efficient, membrane-filtration-based plasma separation device that enables rapid large-volume plasma extraction from whole blood, designed for point-of-care virus assays. The plasma separation is realized by a low-fouling zwitterionic polyurethane-modified cellulose acetate (PCBU-CA) membrane. The zwitterionic coating on the cellulose acetate membrane can decrease surface protein adsorption by 60% and increase plasma permeation by 46% compared with a pristine membrane. The PCBU-CA membrane, with its ultralow-fouling properties, enables rapid plasma separation. The device can yield a total of 1.33 mL plasma from 10 mL whole blood in 10 min. The extracted plasma is cell-free and exhibits a low hemoglobin level. In addition, our device demonstrated a 57.8% T7 phage recovery in the separated plasma. The results of real-time polymerase chain reaction analysis confirmed that the nucleic acid amplification curve of the plasma extracted by our device is comparable to that obtained by centrifugation. With its high plasma yield and good phage recovery, our plasma separation device provides an excellent replacement for traditional plasma separation protocols for point-of-care virus assays and a broad spectrum of clinical tests.

36 MATERIALS SCIENCE↗

Efficient phase-space generation for hadron collider event simulation

We present a simple yet efficient algorithm for phase-space integration at hadron colliders. Individual mappings consist of a single t-channel combined with any number of s-channel decays, and are constructed using diagrammatic information. The factorial growth in the number of channels is tamed by providing an option to limit the number of s-channel topologies. We provide a publicly available, parallelized code in C++ and test its performance in typical LHC scenarios.

47 OTHER INSTRUMENTATION↗