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At least 937 records · Page 52

Direct observations and characterization of crack closure during microstructurally small fatigue crack growth via in-situ high-energy X-ray characterization

This study provides direct observation of the crack closure mechanism of a naturally occurring, tortuous, 3D microstructurally small fatigue crack (SFC) in additively manufactured Inconel 718. In-situ non-destructive characterization is performed using high-energy X-ray diffraction techniques to capture the evolution of the 3D microstructure and micromechanical response in the vicinity of the crack front. Based on the stress state of twelve grains analyzed at the crack tip, the crack closure events of the SFC front was found to be spatially heterogeneous with respect to loading progression governed by the local stress state of the grains (specifically the stress reversal from compression to tension). From this analysis, three grains that displayed different degrees of crack closure were further investigated, based on the orientation of the crack relative to the grains and the associated modality of crack growth. The stress normal to the crack plane and the associated degree of Mode I crack behavior were correlated with events of the crack opening earlier during the loading cycle. This was further corroborated by diffraction spot spreading analysis that quantified the crystallographic lattice distortion caused by the opening crack. Additionally, the detailed characterization of the opening behavior of the grains located at the crack tip and their associated states of stress elucidates the mechanism governing crack closure and will inform future modeling efforts of this phenomenon.

36 MATERIALS SCIENCE↗

Mining Air for Fuels and Fine Chemicals

The Intergovernmental Panel on Climate Change’s 2021 report underscores that Direct Air Capture (DAC) is an essential component to limiting global warming to 2 °C, yet separating CO 2 from air and its subsequent concentration for conversion into carbon neutral fuels/chemicals or permanent storage remains energy intensive and costly. Further, most DAC technologies rely on repetitive capture and release cycles that reduces the amount of time the DAC materials are able to collect CO 2 and increases wear and tear. Moisture swing (MS) sorption within anion exchange materials utilizes differences in relative humidity to capture and concentrate CO 2 up to 500-fold with negligible energy inputs and low-cost sorbents. Molecular modeling predicts that membranes with a dry and wet side would actively transport CO 2 from its dry side to its wet side against a counter flow of H 2 O evaporating on the dry side, however, existing MS materials are too brittle to be processed into membranes to test this hypothesis. This project brought together experts in DAC materials and design, techno-economic analysis and project management at Arizona State University (ASU), polymer processing at University of Texas at Austin (UTA) and modeling gas transport and exchange at Norther Arizona University (NAU) to develop hollow fiber membranes that use energy from water evaporation to continuously pump CO 2 from air against a concentration gradient to the membranes interior and requiring significantly less energy than current DAC technologies. While this project did not meet its ultimate objectives of demonstrating an active CO 2 pumping membrane, a number of key accomplishments were made in developing low-cost, flexible anion exchange membranes (AEM) at 3.5 m 2 scale, characterizing the ionic and molecular transport within MS materials, and developing several analytical and mathematical models of the MS and pumping process leading to new fundamental knowledge about key rate limiting steps of CO 2 flux in anion exchange membranes at low water activity. Technoeconomic models show that if CO 2 fluxes ≥ 25 µmol CO 2 m -2 s -1 (membrane surface area) are achieved that cost ≤ $\$$100/tonne CO 2 captured, purified and compressed to pipeline quality is possible. The knowledge gained in this research will guide future research in developing new materials toward overcoming these rate limiting steps that in turn could enable transformative and disruptive DAC technologies needed for capturing gigatons of CO 2 per year needed to limiting global warming to 2 °C.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

The role of current and emerging technologies in meeting Japan’s mid- to long-term carbon reduction goals

Using Japan as a proxy for a developed nation, we investigated the role of existing and nascent technologies in curbing carbon emissions. We simulated possible pathways to meeting 2030 and 2050 emission targets within the Japanese electricity supply sector using a single-region model in The Integrated MARKAL-EFOM System (TIMES). Critically, our simulations incorporate novel technologies like hydrogen electrolysers, carbon capture, photochemical water splitting, and emerging photovoltaic cells, assess long-term impacts up to the year 2100, and include life-cycle emissions and learning curves for parameters such as investment cost, efficiency, and emission coefficients. Results indicate that a hybrid approach, using nuclear power and hydrogen from renewable energy-based electrolysis, is cost-effective and provides long-term emission reduction along with energy security. Finally, nuclear, wind, solar, and hydrogen from renewables emerge as key emission reduction technologies, while natural gas with carbon capture plays a minor role in achieving emission reduction targets.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Optical Properties of the Infinite-Layer La 1-x Sr x NiO 2 and Hidden Hund's Physics

We investigate the optical properties of the normal state of the infinite-layer La 1-x Sr x NiO 2 using density functional theory plus dynamical mean-field theory. We find a correlated metal which exhibits substantial transfer of spectral weight to high energies relative to the density functional theory. The correlations are not due to Mott physics, which would suppress the charge fluctuations and the integrated optical spectral weight as we approach a putative insulating state. Instead, we find the unusual situation, that the integrated optical spectral weight decreases with doping and increases with increasing temperature. We contrast this with the coherent component of the optical conductivity, which decreases with increasing temperature as a result of a coherence-incoherence crossover. Our studies reveal that the effective crystal field splitting is dynamical and increases strongly at low frequency. This leads to a picture of a Hund's metallic state, where dynamical orbital fluctuations are visible at intermediate energies, while at low energies a Fermi surface with primarily d x 2 -y 2 character emerges. The infinite-layer nickelates are thus in an intermediate position between the iron based high temperature superconductors where multiorbital Hund's physics dominates and a one-band system such as the cuprates. To capture this physics we propose a low-energy two-band model with atom centered e g states.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

A reinforcement learning approach to long-horizon operations, health, and maintenance supervisory control of advanced energy systems

In this work, we develop a Reinforcement Learning (RL) approach to the supervisory control problem for advanced energy systems, such as novel nuclear reactors and other demand-driven, mission-critical, and component-health-sensitive energy plants. The inclusive problem landscape considered captures the stochastic confluence of plant performance, component health evolution, power demand from the grid, diverse maintenance actions, and operator-defined goals and constraints, all considered over meaningfully long-enough reasoning horizons. Key aspects of the proposed approach are a receding horizon control-inspired technique dictating time- or event-triggered supervisory policy (re-)constructions, as well as additional capability-enabling contributions such as timescale compression, to handle long reasoning horizons and uncertainty in parts of the problem, and practical yet demonstrably-effective handling of hybrid action spaces with continuous and discrete decision variables. The resulting algorithm consists of a simulation-based RL agent constructing stochastic supervisory control policies over nontrivial action spaces and for long horizons, applying the learned policy to the system for a much shorter interval, and perpetually repeating, to construct the next long-horizon policy. That next policy will only be applied, again, for a short interval, yet originally far-in-time events move progressively closer, their associated uncertainty decreases, and new events and aspects enter the reasoning horizon. The proposed methodology bridges fundamental receding horizon concepts with the unequivocally stronger and more scalable reasoning of contemporary RL. Numerical examples using Soft Actor–Critic Deep RL illustrate the operation and efficacy of the proposed technique for a power plant tasked with health-aware load following missions in a dynamic electricity market landscape.

97 MATHEMATICS AND COMPUTING↗

Pseudo-viscous modeling of transport in dense granular flows for thermal energy storage applications

Dense, granular flows were examined to effectively capture and model bulk viscous properties in thin packed beds. A modified Couette cell with particle image velocimetry was used to experimentally determine pseudo-viscosity properties of four particulate media with varying morphologies: (1) iron oxide-coated SiO 2 particles, (2) CARBOBEAD CP30-60 particles, (3) CARBOBEAD CP40-100 particles, and (4) Al 2 O 3 beads. The pseudo-viscosity functions were fitted using a power law to correlate the measured shear stress as a function of measured shear rate. The pseudo-viscous functions were used as inputs to computation fluid dynamics models for a single-phase viscous fluid to predict granular flow profiles. Steady-state free surface velocity profiles at angular velocities <7 rad/s predicted by the model were in good agreement with the experimental particle image velocimetry measurements, resulting in Pearson correlation coefficients of 0.97 for iron-oxide coated SiO 2 particles and 0.95 for CP30-60 particles. As a result, this alternative approach to measuring pseudo-viscous properties under shearing and modeling bulk transport behavior of granular flow using computation fluid dynamics model offered significant reduction in computational load compared to discrete element methods.

14 SOLAR ENERGY↗

Global assessment of the carbon–water tradeoff of dry cooling for thermal power generation

Water scarcity and climate change are dual challenges that could potentially threaten energy security. Yet, integrated water–carbon management frameworks coupling diverse water- and carbon-mitigation technologies at high spatial heterogeneity are largely underdeveloped. Here we build a global unit-level framework to investigate the CO 2 emission and energy penalty due to the deployment of dry cooling—a critical water mitigation strategy—together with alternative water sourcing and carbon capture and storage under climate scenarios. We find that CO 2 emission and energy penalty for dry cooling units are location and climate specific (for example, 1–15% of power output), often demonstrating notably faster efficiency losses than rising temperature, especially under the high climate change scenario. Despite energy and CO 2 penalties associated with alternative water treatment and carbon capture and storage utilization, increasing wastewater and brine water accessibility provide potential alternatives to dry cooling for water scarcity alleviation, whereas CO 2 storage can help to mitigate dry cooling-associated CO 2 emission tradeoffs when alternative water supply is insufficient. By demonstrating an integrative planning framework, our study highlights the importance of integrated power sector planning under interconnected dual water–carbon challenges.

42 ENGINEERING↗

Efficient Synthetic Natural Gas Production from Direct Air Capture Using Titania-Based Dual Function Materials

Converting atmospheric CO2 into methane offers a compelling pathway to store intermittent renewable electricity and enhance energy security using existing natural gas infrastructure. However, current CO2 utilization approaches remain energy- and capital-intensive, largely due to the need for separate capture, purification, and conversion steps. Integrating CO2 capture with catalytic methanation represents a transformative strategy for process intensification on both the unit operation and molecular levels. We report a series of Ru-Na/TiO2 dual function materials (DFMs) for a reactive carbon capture (RCC) process consisting of simulated direct air capture and subsequent CO2 methanation (DACM). Superior methane desorption purity was observed on TiO2-based DFMs (>94 %) relative to state-of-the-art Al2O3-supported DFMs (77 %). Modifying the process to begin CO2 adsorption immediately following the methanation stage, rather than beginning adsorption near ambient temperature, resulted in >97 % methane desorption purity, suitable for injection into the natural gas pipeline without additional CO2 separation steps.

organic↗

INL Intern Poster Session

Characterization of off-gas constituents from nuclear fuel reprocessing can be measured using a residual gas analyzer. Characterization of this off-gas is important in a closed fuel cycle, where gasses such as Nox, Kr, I, and C-14 need to be removed from reprocessing plants to meet regulatory requirements. Both Kr and Xe have low chemical reactivity, making capture and separation difficult. Solid sorbents can be used to capture these gases as an alternative to cryogenic distillation, which is energy intensive and hazardous. AgZ-PAN and HZ-PAN are two solid sorbents that have demonstrated selective capture of Xe and Kr. A residual gas analyzer can be used to obtain breakthrough curves that demonstrate how well this adsorption and separation occur. The breakthrough curve is dependent on packing density, column size, and flow rate. Data obtained from the RGA was verified with a gas chromatographer.

11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Detection of MeV-Scale Gammas from Pion/Muon Nuclear Capture With the LArIAT Liquid Argon TPC

LArIAT (Liquid Argon In A Testbeam) is a LArTPC experiment at Fermilab which aims to understand and characterize interactions of neutrino final-state products with Argon. Tracks for pions and muons in LArTPCs are difficult to differentiate since both particles exhibit very similar ionization densities. We are exploring unique new particle discrimination capabilities for pions and muons by exploiting information from small, isolated ionization depositions, referred to as "blips", reconstructed near the endpoint of stopping tracks. These blips are formed by gammas emitted when an at-rest pion or muon captures on the argon nucleus. The relatively low beam energy provided by LArIAT makes it uniquely suited for performing this demonstration. In this talk, an overview of event candidate selection and reconstruct blips corresponding to our signal of interest, nuclear captures of pions and muons at rest inside LArIAT's TPC, and how we estimate and subtract backgrounds from these capture-at-rest blip signals.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Local reduced-order modeling for electrostatic plasmas by physics-informed solution manifold decomposition

Despite advancements in high-performance computing and modern numerical algorithms, computational cost remains prohibitive for multi-query kinetic plasma simulations. Here, in this work, we develop data-driven reduced-order models (ROMs) for collisionless electrostatic plasma dynamics, based on the kinetic Vlasov-Poisson equation. Our ROM approach projects the equation onto a linear subspace defined by the proper orthogonal decomposition (POD) modes. We introduce an efficient tensorial method to update the nonlinear term using a precomputed third-order tensor. We capture multiscale behavior with a minimal number of POD modes by decomposing the solution manifold into multiple time windows and creating temporally local ROMs. We consider two strategies for decomposition: one based on the physical time and the other based on the electric field energy. Applied to the 1D1V Vlasov–Poisson simulations, that is, prescribed E-field, Landau damping, and two-stream instability, we demonstrate that our ROMs accurately capture the total energy of the system both for parametric and time extrapolation cases. The temporally local ROMs are more efficient and accurate than the single ROM. In addition, in the two-stream instability case, we show that the energy-windowing reduced-order model (EW-ROM) is more efficient and accurate than the time-windowing reduced-order model (TW-ROM). With the tensorial approach, EW-ROM solves the equation approximately 90 times faster than Eulerian simulations while maintaining a maximum relative error of 7.5% for the training data and 11% for the testing data.

Electrostatic plasmas↗

Technoeconomic analysis and life cycle assessment of purification processes for captured CO 2 streams

Captured carbon dioxide (CO 2 ) streams contain impurities that must be removed to meet specifications for safe transport, storage, and utilization. Among these impurities, oxygen poses challenges due to its high reactivity and potential to cause corrosion, motivating stringent purity limits below 10 ppmv. Building on recent experimental demonstrations of catalytic oxygen removal using hydrogen (H 2 ), carbon monoxide (CO), methanol (CH 3 OH), and methane (CH 4 ) as reducing agents, this study presents a technoeconomic (TEA) and life cycle assessment (LCA) of these four catalytic purification pathways. Process flowsheets were developed and simulated in Aspen Plus for CO 2 streams representative of both low-temperature and high-temperature capture processes, with integrated heat recovery and energy optimization. Results showed that total purification costs were dominated by feedstock procurement and electricity consumption. Among the studied reducing agents, the CH 4 -assisted route achieved the lowest purification cost and highest CO 2 recovery. Sensitivity analyses showed that the H 2 route became competitive at H 2 prices below $\$$0.56/kg to $\$$0.84/kg, depending on the CO 2 feed temperature conditions. In conclusion, environmental impacts were primarily driven by indirect CO 2 emissions from raw material production and utility consumption.

CO2 pipeline specifications↗

Synthesis and processing of lithium-loaded plastic scintillators on the kilogram scale

Plastic scintillators that can discriminate between gamma rays, fast neutrons, and thermal neutrons were synthesized and characterized while considering the performance at the kilogram scale. The synthesis and processing of these plastic scintillators on the kilogram scale required examination of several factors. The examination of these factors was necessitated by the inclusion of 0.1 wt.% lithium-6 to enable detection of thermal neutrons. First, methacrylic acid was used as an additive to solubilize salts of lithium-6, which allow for a thermal-neutron capture reaction that produces scintillation light following energy transfer. Second, a trade-off between scintillation performance and processability was considered because the increasing content of the methacrylic acid that aided processability resulted in a sharp decrease in the light output. The use of small amounts of methacrylic acid (≤3 wt.%) resulted in better performance but required high processing temperatures. At large scales, these high temperatures could initiate exothermic polymerization that results in premature curing and/or defects. Additionally, the deleterious effects of the methacrylic acid may be mitigated by using m-terphenyl as a primary dye rather than 2,5-diphenyloxazole (PPO), which has been traditionally used in organic scintillators. Finally, the curing environment was controlled to avoid defects like cracking and discolouration​ while maintaining solubility of dopants during curing. For scintillators that were produced from kilogram-scale batches of precursors, the effective attenuation of scintillation light was characterized.

36 MATERIALS SCIENCE↗

Integrated Ion-Exchange Membrane Resin Wafer Assemblies for Aromatic Organic Acid Separations Using Electrodeionization

Aromatic acids, such as p-coumaric acid, are valuable chemical intermediates that are used in the specialty chemical industries because they are precursors to phenylpropanoid compounds. The separation of p-coumaric acid from fermentation broths is a critical step in the biochemical production process and more broadly the circular carbon economy. Electrodeionization (EDI) has been applied toward separations of low-carbon chain acids, but purifying p-coumaric acid has been challenging due to fouling and irreversible binding with ion-exchange membranes and resins. Here, we report a new membrane wafer assembly (MWA) consisting of laminated ion exchange membranes to porous ionomer-binder resin wafers for EDI. The MWAs in an EDI stack showed a 7-fold increase in p-coumaric acid capture while also using 70% less specific energy consumption when benchmarked against state-of-the-art resin wafer EDI modules. The more efficient p-coumaric acid recovery was ascribed to (i) the 38% reduction in interfacial transport resistance between the membrane and resin wafer and (ii) using imidazolium anion exchange membranes and ionomer binders in the MWA. MD simulations revealed enhanced transport rates for p-coumarate in imidazolium ionomers through π–π interactions. As a result, adopting the new MWA significantly reduced the amount of ion-exchange membranes in EDI and may lead to drastic capital cost savings.

42 ENGINEERING↗

The Illumination of Thunderclouds by Lightning: 3. Retrieving Optical Source Altitude

Abstract Optical space‐based lightning sensors such as the Geostationary Lightning Mapper (GLM) detect and geolocate lightning by recording rapid changes in cloud top illumination. While lightning locations can be determined to within a pixel on the GLM imaging array, these instruments are not individually able to natively report lightning altitude. It has previously been shown that thunderclouds are illuminated differently based on the altitude of the optical source. In this study, we examine how altitude information can be extracted from the spatial distributions of GLM energy recorded from each optical pulse. We match GLM “groups” with Lightning Mapping Array (LMA) source data that accurately report the 3‐D positions of coincident Radio‐Frequency (RF) emitters. We then use machine learning methods to predict the mean LMA source altitudes matched to GLM groups using metrics from the optical data that describe the amplitude, breadth, and texture of the group spatial energy distribution. The resulting model can predict the LMA mean source altitude from GLM group data with a median absolute error of <1.5 km, which is sufficient to determine the location of the charge layer where the optical energy originated. This model is able to capture changes to the source altitude distribution in response to convective processes in the thunderstorm, and the GLM predictions can reveal the vertical structure of individual flashes ‐ enabling 3‐D flash geolocation with GLM for the first time. Future work will account for differences in thunderstorm charge/precipitation structures and viewing angle across the GLM Field of View.

54 ENVIRONMENTAL SCIENCES↗

Plasma electron acceleration driven by a long-wave-infrared laser

Laser-driven plasma accelerators provide tabletop sources of relativistic electron bunches and femtosecond x-ray pulses, but usually require petawatt-class solid-state-laser pulses of wavelength λ L ~ 1 μm. Longer-λ L lasers can potentially accelerate higher-quality bunches, since they require less power to drive larger wakes in less dense plasma. Here, we report on a self-injecting plasma accelerator driven by a long-wave-infrared laser: a chirped-pulse-amplified CO 2 laser (λ L ≈ 10 μm). Through optical scattering experiments, we observed wakes that 4-ps CO 2 pulses with < 1/2 terawatt (TW) peak power drove in hydrogen plasma of electron density down to 4 × 10 17 cm –3 (1/100 atmospheric density) via a self-modulation (SM) instability. Shorter, more powerful CO 2 pulses drove wakes in plasma down to 3 × 10 16 cm –3 that captured and accelerated plasma electrons to relativistic energy. Collimated quasi-monoenergetic features in the electron output marked the onset of a transition from SM to bubble-regime acceleration, portending future higher-quality accelerators driven by yet shorter, more powerful pulses.

43 PARTICLE ACCELERATORS↗

Structure of a biohybrid photosystem I-platinum nanoparticle solar fuel catalyst

Biohybrid solar fuel catalysts leverage natural light-driven enzymes to produce valuable fuel products. One useful biological platform for such a system is photosystem I, a pigment-protein complex that captures sunlight and converts it into chemical energy with near unity quantum efficiency, which generates low potential reducing equivalents for metabolism. Realizing and understanding the molecular basis for an approach that utilizes those electrons and stores solar energy as a fuel is therefore appealing. Here, we report the 2.27-Å global resolution cryo-EM structure of a photosystem I complex with bound platinum nanoparticles that catalyzes light-driven H 2 production. The platinum nanoparticle binding sites and possible stabilizing interactions are described. Overall, the investigation reveals a direct structural look at a photon-to-fuels photosynthetic biohybrid system.

59 BASIC BIOLOGICAL SCIENCES↗

Design and evaluation of a cyber‐physical testbed for improving attack resilience of power systems

Abstract A power system is a complex cyber‐physical system whose security is critical to its function. A major challenge is to model, analyse and visualise the communication backbone of the power systems concerning cyber threats. To achieve this, the design and evaluation of a cyber‐physical power system (CPPS) testbed called Resilient Energy Systems Lab (RESLab) are presented to capture realistic cyber, physical, and protection system features. RESLab is architected to be a fundamental platform for studying and improving the resilience of complex CPPS to cyber threats. The cyber network is emulated using Common Open Research Emulator (CORE), which acts as a gateway for the physical and protection devices to communicate. The physical grid is simulated in the dynamic time frame using Power World Dynamic Studio (PWDS). The protection components are modelled with both PWDS and physical devices including the SEL Real‐Time Automation Controller (RTAC). Distributed Network Protocol 3 (DNP3) is used to monitor and control the grid. Then, the design is exemplified and the tools are validated. This work presents four case studies on cyberattack and defence using RESLab, where we demonstrate false data and command injection using Man‐in‐the‐Middle and Denial of Service attacks and validate them on a large‐scale synthetic electric grid.

Sahu, Abhijeet↗