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At least 469 records · Page 26

Top 13 Blendstocks Derived from Biomass for Mixing-Controlled Compression-Ignition (Diesel) Engines: Bioblendstocks with Potential for Decreased Emissions and Improved Operability

Reducing the impacts of medium- and heavy-duty (MD/HD) ground transportation can be enabled by fuel-engine combinations that use lower compression ignition liquid fuels and reduce criteria pollutant emissions. Fuels and blendstocks combined with advanced engine technologies could reduce the cost of ownership and the emission of pollutants, including soot, nitrogen oxides (NOx) and greenhouse gases (GHGs), from MD/HD vehicles. This report describes the evaluation and screening of MD/HD mixing-controlled compression ignition (MCCI) biofuel candidates for further development and commercialization. The report is aimed at 1) biofuel researchers looking to better understand options to reduce criteria pollutant and GHG emissions while maintaining efficiency and meeting requirements for engine operability and 2) engine researchers who want to evaluate biofuels that meet diesel fuel properties for their impact on conventional and advanced diesel combustion strategies.

09 BIOMASS FUELS↗

A deep redox proteome profiling workflow and its application to skeletal muscle of a Duchenne Muscular Dystrophy model

Perturbation to the redox state accompanies many diseases and its effects are viewed through oxidation of biomolecules, including proteins, lipids, and nucleic acids. The thiol groups of protein cysteine residues undergo an array of redox post-translational modifications (PTMs) that are important for regulation of protein and pathway function. To better understand what proteins are redox regulated following a perturbation, it is important to be able to comprehensively profile protein thiol oxidation at the proteome level. Herein, we report a deep redox proteome profiling workflow and demonstrate its application in measuring the changes in thiol oxidation along with global protein expression in skeletal muscle from mdx mice, a model of Duchenne Muscular Dystrophy (DMD). In depth coverage of the thiol proteome was achieved with >18,000 Cys sites from 5608 proteins in muscle being quantified. Compared to the control group, mdx mice exhibit markedly increased thiol oxidation, where ~2% shift in the median oxidation occupancy was observed. Further, pathway analysis for the redox data revealed that coagulation system and immune-related pathways were among the most susceptible to increased thiol oxidation in mdx mice, whereas protein abundance changes were more enriched in pathways associated with bioenergetics. This study illustrates the importance of deep redox profiling in gaining greater insight into oxidative stress regulation and pathways/processes that are perturbed in an oxidizing environment.

60 APPLIED LIFE SCIENCES↗

Enhancing Network Anomaly Detection Using Graph Neural Networks

In the world of Internet of Things (IoT) networks, where devices are constantly communicating, keeping them secure from cyber threats is critical. This paper introduces a novel approach to detecting unusual and potentially harmful activities in these networks using graph neural networks (GNNs). We combine two specific types of GNNs-GraphSAGE and graph attention networks (GAT)-to create a model that understands and represents the behaviors and interactions in a network. GraphSAGE creates an embedding of network activities by examining local data interactions, while GAT directs the model's focus to the most critical interactions. By integrating these two methods in a single model that considers different types of interactions (both host and flow nodes), we aim to create a system that accurately represents the current state of a network and can also spot anomalies effectively while reducing false positives and negatives. Our innovative approach has demonstrated promising results, achieving an accuracy of 98% on the UNSW-NB15 dataset, significantly outperforming standalone GraphSAGE and GAT models. This underscores its potential as a robust framework for securing IoT networks against cyber threats and anomalies.

Marfo, William↗

Recent Advances for Improving the Accuracy, Transferability, and Efficiency of Reactive Force Fields

Reactive force fields provide an affordable model for simulating chemical reactions at a fraction of the cost of quantum mechanical approaches. However, classically accounting for chemical reactivity often comes at the expense of accuracy and transferability, while computational cost is still large relative to nonreactive force fields. Here, we summarize recent efforts for improving the performance of reactive force fields in these three areas with a focus on the ReaxFF theoretical model. To improve accuracy, we describe recent reformulations of charge equilibration schemes to overcome unphysical long-range charge transfer, new ReaxFF models that account for explicit electrons, and corrections for energy conservation issues of the ReaxFF model. To enhance transferability we also highlight new advances to include explicit treatment of electrons in the ReaxFF and hybrid nonreactive/reactive simulations that make it possible to model charge transfer, redox chemistry, and large systems such as reverse micelles within the framework of a reactive force field. To address the computational cost, we review recent work in extended Lagrangian schemes and matrix preconditioners for accelerating the charge equilibration method component of ReaxFF and improvements in its software performance in LAMMPS.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Thermodynamics of Uranium Tri-Iodide from Density-Functional Theory

Density-functional theory (DFT) is employed to investigate the thermodynamic and ground-state properties of bulk uranium tri-iodide, UI3. The theory is fully relativistic and electron correlations, beyond the DFT and generalized gradient approximation, are addressed with orbital polarization. The electronic structure indicates anti-ferromagnetism, in agreement with neutron diffraction, with band gaps and a non-metallic system. Furthermore, the formation energy, atomic volume, crystal structure, and heat capacity are calculated in reasonable agreement with experiments, whereas for the elastic constants experimental data are unavailable for comparison. The thermodynamical properties are modeled within a quasi-harmonic approximation and the heat capacity and Gibbs free energy as functions of temperature agree with available calculation of phase diagram (CALPHAD) thermodynamic assessment of the experimental data.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Role of Intact Hydrogen-Bond Networks in Multiproton-Coupled Electron Transfer

The essential role of a well-defined hydrogen-bond network in achieving chemically reversible multiproton translocations triggered by one-electron electrochemical oxidation/reduction is investigated by using pyridylbenzimidazole–phenol models. The two molecular architectures designed for these studies differ with respect to the position of the N atom on the pyridyl ring. In one of the structures, a hydrogen-bond network extends uninterrupted across the molecule from the phenol to the pyridyl group. Experimental and theoretical evidence indicates that an overall chemically reversible two-protoncoupled electron-transfer process (E2PT) takes place upon electrochemical oxidation of the phenol. This E2PT process yields the pyridinium cation and is observed regardless of the cyclic voltammogram scan rate. In contrast, when the hydrogen-bond network is disrupted, as seen in the isomer, at high scan rates (~1000 mV s –1 ) a chemically reversible process is observed with an E 1/2 characteristic of a one-proton-coupled electron-transfer process (E1PT). At slow cyclic voltammetric scan rates (<1000 mV s –1 ) oxidation of the phenol results in an overall chemically irreversible two-proton-coupled electron-transfer process in which the second proton-transfer step yields the pyridinium cation detected by infrared spectroelectrochemistry. In this case, we postulate an initial intramolecular proton-coupled electron-transfer step yielding the E1PT product followed by a slow, likely intermolecular chemical step involving a second proton transfer to give the E2PT product. Insights into the electrochemical behavior of these systems are provided by theoretical calculations of the electrostatic potentials and electric fields at the site of the transferring protons for the forward and reverse processes. Furthermore, this work addresses a fundamental design principle for constructing molecular wires where protons are translocated over varied distances by a Grotthuss-type mechanism.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

URBANopt™ District Energy Systems HVAC Measures (DES_HVAC) [SWR-21-30]

DES_HVAC is a repository of a Parametric Analysis Tool (PAT) project and for scripts related to modeling of different HVAC systems for buildings in a district served by a district thermal energy system. The Measures directory contains the new measures developed to extract data from the simulations. Update these measures and not the measures in the Test Suite measures directory. PAT should be used to update the measures in the Test Suite project. The Test directory contains a PAT project for testing the functionality of the measures. The PAT project is named HVAC_Test and can be opened in PAT > 3.x.

Allen, Amy↗

Picoflow Liquid Chromatography–Mass Spectrometry for Ultrasensitive Bottom-Up Proteomics Using 2-μm-i.d. Open Tubular Columns

In many areas of applications key objectives of chemical separations and analysis are to minimize the sample quantity while maximizing the chemical information obtained. Increasing measurement sensitivity is especially critical for proteomics research, especially when processing trace samples and where multiple measurements are desired. A rich collection of technologies has been developed, but the resulting sensitivity remains insufficient for achieving in-depth coverage of proteomic samples as small as single cells. In this paper, we combine picoliter-scale liquid chromatography (picoLC) with mass spectrometry (MS) to address this issue. The picoLC employs 2-µm-i.d. open tubular column to reduce the sample input needed to greatly increase the sensitivity achieved using electrospray ionization (ESI) with MS. With this picoLC-MS system, we show that we can identify ~1000 proteins reliably using only 30 pg of tryptic peptides, representing a 10–100-fold sensitivity improvement compared with the state-of-the-art liquid chromatography (LC) or capillary electrophoresis (CE)-MS methods. PicoLC-MS extends the limit of separation science and is expected to be a powerful tool for single cell proteomics.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Saturn's Weather‐Driven Aurorae Modulate Oscillations in the Magnetic Field and Radio Emissions

Abstract The Cassini spacecraft revealed that Saturn's magnetic field displayed oscillations at a period originally thought to match the planetary rotation rate but later found not to. One of many proposed theories predicts that a polar twin‐cell neutral weather system drives this variation, producing observable differences in flows within Saturn's ionosphere. Here, using spectral observations of auroral emission lines taken by the Keck Observatory's Near Infrared Echelle Spectrograph (Keck‐NIRSPEC) in 2017, we derive ion line‐of‐sight velocity maps after grouping spectra into rotational quadrants matching phases of the planetary magnetic field. We measure 0.5 km s −1 wind systems in the ionosphere consistent with predicted neutral twin‐vortex flow patterns. These findings demonstrate that neutral winds in Saturn's polar regions cause the rotational period, as determined via the magnetic field, to exhibit differences and time variabilities relative to the planet's true period of rotation in a process never before seen within planetary atmospheres.

Chowdhury, M. N.↗

Assessment of Flow-Enhanced Electrochemical Sensor Testing and Deployments for MSRs

This report serves as the deliverable for Milestone M3RS-23AN0401061 that is part of Work Package RS-23AN040106 (Flow Enhanced Sensors for MSRs – ANL). The goal of this milestone was to determine performance of the flow enhanced electrochemical sensor (FEES) and modular flow instrumentation testbed (MFIT) in safeguards relevant scenarios. Flow enhanced electrochemical sensors are a type of electroanalytical sensor that has been developed at Argonne National Laboratory to be installed directly into MSR flow conduits to make measurements of the salt composition. These sensors represent a significant improvement in capabilities compared to earlier electroanalytical sensors that instead can only be operated in quiescent conditions. Previous work has focused on testing of the FEES in flowing conditions provided by the MFIT to assess the accuracy and precision of the sensor measurements. To further improve this capability, in FY23 we undertook a campaign of safeguards relevant scenarios in molten salt containing a range of uranium chloride concentrations (0 to 3 wt%). All the testing carried out in FY23 was aided by a control system designed to automatically actuate flow conditions and collect data. This new automation system is estimated to have increased experimental throughput by a factor of four and enabled testing in a variety of complex conditions. The advancements in throughput and repeatability led to improved quantification of actinide concentrations using the in-flow sensors, with a reduction of the mean absolute relative error from 5.6% in FY22 to 3.1% in FY23. In addition to safeguards scenarios run in the MFIT, FY23 work included deployment of a FEES at a partner institution where it will be tested in a flowing salt loop. The FEES was successfully integrated into that loop and is being tested prior to loop startup. In FY23, work also continued on the smaller flow system that we have named the mini-MFIT. This smaller system is capable of rapid prototyping of new sensor designs prior to installation in the larger MFIT radiological flow system. Work was carried out to test this new system in non-radiological molten salts in a separate glovebox. This work is helping us to enhance the accuracy of our salt monitoring capabilities through the integration of multiple types of sensors. The high degree of accuracy required by 10 CFR 74 represents a significant challenge, and further design evolution and integration of the sensors into multimodal sensing frameworks will be needed to further push the measurement accuracy to the needed level.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

MRCI Subtask 2.1: Defining Sub-Regional Carbon Storage Systems Final Technical Summary Report

In order to assess the regional and subregional geologic framework of the MRCI area and expand carbon dioxide (CO2) storage characterization efforts in this larger region, the current state of geologic knowledge relative to carbon storage (CS) has been summarized by compiling available geologic data and interpretive results into a centralized resource under Subtask 2.1. The MRCI region is a large area, which includes (1) part of the Forest City Basin and Western Arches, (2) Illinois Basin, (3) Upper Mississippi Embayment, (4) Michigan Basin, (5) Central Arches, (6) Appalachian Basin, and (7) Atlantic Coastal Plain and West Atlantic basins. Basins and arches are subdivided into areas of similar geology based on geologic structures and state-specific stratigraphic nomenclature. A concerted effort was made to present the current understanding of rock-unit stratigraphy in the subsurface of each basin and arch region (and subdivisions therein). Rock units are characterized based on their relative CS potential (saline reservoirs, confining intervals, etc.) within CS systems. CS systems are defined by regional confining units (usually thick, widespread shales), and contain all reservoirs and strata between the regional confining units. Report Authors – Steve Greb and Tom Sparks (Kentucky Geological Survey), Mark Kelley, Sanjay Mawalkar, John Hershberger, Priya Ravi Ganesh, Derrick James, and Stuart Skopec (Battelle), Charles Bopp, Yaghoob Lasemi and Hannes Leetaru (deceased) (Illinois State Geological Survey), Kristin Carter (Pennsylvania Geological Survey), William Harrison (Michigan Geological Repository for Research and Education – Michigan Geological Survey), Susan Pool (West Virginia Geological and Economic Survey), James McDonald (Ohio Geological Survey), John Schmelz (Rutgers University), Ryan Clark (Iowa Geological Survey). Other Technical Contributors – Seth Carpenter and John Hickman (Kentucky Geological Survey), Jessica Moore, Eric Lewis, Philip Dinterman, Timothy Vance, and Gary Daft (West Virginia Geological and Economic Survey), Michele Cooney, Robin Anthony, Cheyenne Woodward, and Katherine Schmid (Pennsylvania Geological Survey), Autumn Haagsma and Amber Conner (Michigan Geological Repository for Research and Education – Michigan Geological Survey), Kenneth Miller (Rutgers University), Ashley Douds and Valerie Beckham-Feller (Indiana Geological & Water Survey), Michael Solis (Ohio Geological Survey).

Appalachian,Arches,Forest City,Illinois,MRCI,Michi↗

Improved PARE (Pressurized Airborne Release Equipment) for Damage Ratio, Airborne Release Fraction and Respirable Fraction Testing (Version 4)

This paper describes an improved version of the PARE (Pressurized Airborne Release Equipment) system (Sutter 1983a and Sutter 1983b and Ballinger et al 1987) for powder venting testing. This effort seeks to improve the accuracy of risk estimation for the venting of pressurized powders and the venting of gases through pressurized powders. This includes experimental measurement for estimating DR (damage ratio), ARF (airborne release fraction) and RF (respirable fraction) quantities. The present study was performed to address previously indicated problematic factors (i.e. noted gaps) (US DOE 1994).

42 ENGINEERING↗

Net Zero World 2024 Achievements

Net Zero World, launched at COP26, aims to expedite the transition to clean energy systems worldwide. This report details Net Zero World's achievements in 2024. Leveraging expertise from ten U.S. Department of Energy national laboratories and nine federal agencies, Net Zero World has provided specialized technical support and energy modeling to eight partner countries: Argentina, Chile, Egypt, Indonesia, Nigeria, Singapore, Thailand, and Ukraine.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Economic and environmental performance of biomass gasification for renewable natural gas production in the context of the U.S. natural gas supply

Bioenergy technologies offer potential for reducing greenhouse gas (GHG) emissions. One such promising technology is biomass gasification, which is the conversion of biomass into renewable natural gas (RNG) for use with a natural gas combined-cycle power generation system. However, the associated economic and emission effects need to be better understood to enable optimal decision-making and avoid missed opportunities for enhancing efficiency and increasing system circularity. This analysis explores opportunities to (1) decarbonize natural-gas-based systems and (2) leverage the extensive US natural gas infrastructure to mobilize biomass resources to achieve environmental and economic benefits. Here, in this analysis, the research team used a spatially explicit biomass logistics model (integrated with relevant biomass availability, technoeconomic analysis, and life cycle assessment information) to simulate economically optimal biomass allocation for RNG production and use for decarbonization in the United States. Results show that the United States has the potential to produce 9203 million GJ of RNG within the expected range of $\$$12–30/GJ. Further analyses tested the overall RNG production system's sensitivity to economic and emissions parameters of nine different processes. The sensitivity analysis results indicate that the median carbon abatement cost of RNG is most sensitive to changes in emissions associated with conversion processes and land use changes. These findings provide a deeper understanding of RNG's economic and emission potential for decision-making and guiding future research.

09 BIOMASS FUELS↗

Critical design load case fatigue and ultimate failure simulation for a 10-m H-type vertical-axis wind turbine

While previous studies investigating critical VAWT design load cases have focused on large and relatively flexible Darrieus designs, the bulk of current commercial products seeking certification fall in the relatively small, stiff, and H-type configuration, such as the XFlow Energy Corporation turbine that this study compares against. Understanding the critical design load case impacts for both fatigue and ultimate failure for this size and type of VAWT are imperative for certification. The abil

Brownstein, Ian↗

Condition monitoring and anomaly detection in cyber-physical systems

The modern industrial environment is equipping myriads of smart manufacturing machines where the state of each device can be monitored continuously. Such monitoring can help identify possible future failures and develop a cost-effective maintenance plan. However, it is a daunting task to perform early detection with low false positives and negatives from the huge volume of collected data. This requires developing a holistic machine learning framework to address the issues in condition monitoring of high priority components and develop efficient techniques to detect anomalies that can detect and possibly localize the faulty components. This paper presents a comparative analysis of recent machine learning approaches for robust, cost-effective anomaly detection in cyber-physical systems. While detection has been extensively studied, very few researchers have analyzed the localization of the anomalies. We show that supervised learning outperforms unsupervised algorithms. For supervised cases, we achieve near-perfect accuracy of 98% (specifically for tree-based algorithms). In contrast, the best-case accuracy in the unsupervised cases was 63%—the area under the receiver operating characteristic curve (AUC) exhibits similar outcomes as an additional metric.

Marfo, William↗

ReSpike: A Co-Design Framework for Evaluating SNNs on ReRAM-Based Neuromorphic Processors

With Moore’s law approaching its end, traditional von Neumann architectures are struggling to keep up with the exceeding performance and memory requirements of artificial intelligence and machine learning algorithms. Unconventional computing approaches such as neuromorphic computing that leverage spiking neural networks (SNNs) to perform computation are gaining traction and seek the paradigm shift necessary to sustain the increasing demands of modern applications. Novel memory technologies, such as resistive RAM (ReRAM), employ a crossbar architecture that possesses the inherent capability of efficiently computing vector-matrix multiplication—a dominant operation in SNNs. The prospect of naturally mapping SNNs to the crossbar structures provides a unique opportunity for achieving a high-performance, power-efficient neuromorphic system. In this work, we present ReSpike, which is a new framework, behavioral simulator, and architectural design based on ReRAM crossbar architectures, enabling modeling and co-design to achieve efficient execution of SNNs. We drive this co-design forward by quantifying the impact that ReRAM cell nonidealities have on the corresponding accuracy of an SNN application.

Asifuzzaman, Kazi [ORNL] (ORCID:0000000240044791)↗

Flowback Test Analyses at the Utah Frontier Observatory for Research in Geothermal Energy (FORGE) Site

Abstract In 2017 and 2019, injection testing was carried out in three zones in a vertical well in granite at the Frontier Observatory for Research in Geothermal Energy site near Milford, Utah, USA. In several injection cycles, flowback was implemented rather than shut-in. The goal was to explore an alternative to prolonged shut-in periods for inferring closure stress, formation compressibility, and formation permeability (permeability thickness product). The flowback procedures involved a cyclic flowback/shut-in, while pressure decreased. The flowback data are presented, and analyses are shown. The inferred closure stress(es) from flowback analyses are lower than for equivalent injection cycles that were strictly shut-in. Relatively high formation compressibility obtained from the flowback analyses indicates an extensive, fractured system. This study also includes numerical simulation of the flowback events. The numerical model shows that the rebound pressure is not necessarily the lower bound of the minimum principal stress. The signature of stiffness change can be identified as the process when the depletion mainly transitions from hydraulic fracture to natural fractures from numerical analysis. Overall, flowback potentially has advantages over shut-in because of the reduced time to closure.

15 GEOTHERMAL ENERGY↗