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DOE OSTI2024

Do not forget the electrons: Extending moderately-sized nuclear networks for multidimensional hydrodynamic codes

Context.Nuclear networks are widely used coupled with hydrodynamical simulations of explosive scenarios to account for the change of nuclear species and energy generation rate due to nuclear reactions. In this way, there is a feedback mechanism between the hydrodynamical state and the nuclear processes. Unfortunately, the timescale of nuclear reactions is orders of magnitude smaller than the dynamical timescale that drives hydrodynamical simulations. Therefore, these nuclear networks are usually very small, reduced in most cases to a dozen elements, especially when simulations are carried out in more than one dimension. Aims.We present here an extended nuclear network, with 90 species, designed for being coupled with hydrodynamic simulations, which includes neutrons, protons, electrons, positrons, and the corresponding neutrino and anti-neutrino emission. This network is also coupled with temperature, making it extremely robust and, together with its size, unique of its kind. The inclusion of electron captures on free protons makes the network very appropriate for multidimensional studies of Type Ia supernova explosions, especially when the exploding object is a massive white dwarf. Methods.We perform several tests that are relevant to simulate explosive scenarios, such as Type Ia supernovae and core-collapse supernovae. We compare the results of the 90 nuclei network with a standardα-chain network with 14 elements to evaluate the differences in the energy generation rate. We also evaluate the relevance of including the electrons in the network in terms of generated yields and how it affects the pressure of a degenerate fluid such as that of white dwarfs. The results obtained with the 90-nuclei network have been verified with a much larger 2000-nuclei network built from REACLIB (WinNet), in terms of nuclear energy generation rate, pressure, and produced yields. Results.The results obtained with the proposed medium-sized network compare fairly well, to a few percent, with those computed withWinNetin scenarios reproducing the gross physical conditions of current Type Ia supernova explosion models. In those cases where the carbon and oxygen fuel ignites at high density, the high-temperature plateau typical of the nuclear statistical equilibrium regime is well defined and stable, allowing large integration time steps. We show that the inclusion of electron captures on free protons substantially improves the estimation of the electron fraction of the mixture. Therefore, the pressure is better determined than in networks where electron captures are excluded, which will ultimately lead to more reliable hydrodynamic models. Explosive combustion of helium at low density, occurring near the surface layer of a white dwarf, is also better described with the proposed network, which gives nuclear energy generation rates much closer toWinNetthan typical reduced alpha networks. Conclusions.A nuclear network withN= 90 species, including electrons, aimed at multidimensional calculations of supernova explosions is described and verified. The proposed network is suitable for the study of Type Ia supernova explosions because it provides better values of pressure and electron abundance than other existing networks with smaller or even a similar size but without including electron capture processes.

Astronomy & Astrophysics↗

DOE OSTI2024

A high fidelity and user-friendly equation-oriented optimization model for carbon capture using a novel water-lean solvent

Research Triangle Institute (RTI) International and SLB have developed a novel water-lean solvent technology for carbon capture, demonstrating low specific reboiler duty (SRD) values at capture rates exceeding 90%. At the Technology Centre Mongstad (TCM) pilot plant, the technology achieved an SRD of 2.55 GJ/t-CO2 at 95% capture, utilizing an intercooler and a 5°C temperature approach in the lean/rich solvent cross exchanger. To meet varying carbon capture targets for Front End Engineering and Design (FEED) studies and to enable real-time optimization and advanced process control, an efficient optimization model is required. This model needs to minimize energy demand for a given capture rate and determine optimal operating parameters in response to fluctuating flue gas conditions. While an existing Aspen Plus simulation model, developed by RTI and SLB, accurately matches TCM plant data, its sequential modular (SM) strategy is too slow for real-time applications due to recycle streams and tight heat integration inherent in solvent-based carbon capture processes. Although an equation-oriented (EO) modeling strategy is more suitable for optimizing these processes, its adoption has been limited by several factors: feature limitations in Aspen Plus EO mode (e.g., lack of balance block support), a less user-friendly interface for variable identification and loop solving, complex troubleshooting of convergence issues, and the necessity for accurate initial values.

carbon capture↗

DOE OSTI2023

Denitrification and the challenge of scaling microsite knowledge to the globe

Here, our knowledge of microbial processes—who is responsible for what, the rates at which they occur, and the substrates consumed and products produced—is imperfect for many if not most taxa, but even less is known about how microsite processes scale to the ecosystem and thence the globe. In both natural and managed environments, scaling links fundamental knowledge to application and also allows for global assessments of the importance of microbial processes. But rarely is scaling straightforward: More often than not, process rates in situ are distributed in a highly skewed fashion, under the influence of multiple interacting controls, and thus often difficult to sample, quantify, and predict. To date, quantitative models of many important processes fail to capture daily, seasonal, and annual fluxes with the precision needed to effect meaningful management outcomes. Nitrogen cycle processes are a case in point, and denitrification is a prime example. Statistical models based on machine learning can improve predictability and identify the best environmental predictors but are—by themselves—insufficient for revealing process-level knowledge gaps or predicting outcomes under novel environmental conditions. Hybrid models that incorporate well-calibrated process models as predictors for machine learning algorithms can provide both improved understanding and more reliable forecasts under environmental conditions not yet experienced. Incorporating trait-based models into such efforts promises to improve predictions and understanding still further, but much more development is needed.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2025

Experimental and fuel-surrogates modeling study of the high-pressure pyrolysis of specialty cetane number fuels: implications for fall-off in ethylene unimolecular dissociation

Single pulse shock tube experiments were conducted at 50 atm nominal pressure and 4 ms nominal reaction time over a temperature range of 900–1800 K, to study the pyrolysis speciation of a multi-component jet fuel, F-24, and six cetane number (CN) specialty fuels - CN30, CN35, CN40, CN45, CN50, and CN55. Gas chromatography (GC) was used to qualitatively and quantitatively analyze the post shock gases. The relationship between the formation of key pyrolysis species and the chemically controlled combustion propensity as reflected by the cetane number of each fuel was examined. A surrogate-based mechanism from the CRECK Modelling Group and chemical-functional group based optimized surrogates (CFGO) were used to simulate the pyrolysis speciation results. The model was able to capture the chemistry of most species except two important pyrolysis intermediates – ethylene and acetylene. Chemical kinetic analyses were performed to identify the important reactions which affect the chemistry of these species; however, the rate parameters of critical reactions were found to be unsuitable for simulating the present high-pressure studies. Here, to address this unsuitability, a theory-based fall-off analysis for three reactions representing the decomposition of ethylene and subsequent formation of acetylene was performed, and these are included in an updated version of the CRECK mechanism. This update resolves discrepancies between the experimental results and simulations for ethylene and acetylene. Reaction flux analyses using the updated surrogate model were also performed to identify the important reaction pathways responsible for the formation of crucial species and to provide an analysis of the chemistry of complex multi-component fuel systems. The fundamental reactions responsible for driving pyrolysis chemistry were greatly influenced by the chemical functional groups present in these fuels. In addition to updating the rate parameters of specific reactions to improve modeling, this study also emphasizes the effectiveness of the fuel-surrogate approach, where surrogates representing the chemical functional group composition of the parent fuel serve as a valuable tool for predicting the combustion chemistry of novel fuels.

Chemical Kinetics↗

DOE OSTI2026

Integrating Carbon Capture, Utilization, & Sequestration into Chemical Pulp Mills

The U.S. pulp and paper industry presents a unique and largely untapped opportunity for large- scale carbon dioxide removal (CDR). Unlike most industrial sectors, pulp mills rely heavily on biomass, meaning that much of their carbon emissions originate from atmospheric CO₂ that was recently captured by plants. If this biogenic CO₂ can be captured and permanently stored, pulp mills can be transformed from carbon emitters into net carbon removal facilities. This project was motivated by that opportunity and aimed to develop and evaluate integrated, low-cost strategies for capturing, utilizing, and sequestering CO₂ within existing chemical pulping operations. The scope of this work focused on four complementary innovations designed to integrate seamlessly into kraft pulp mill infrastructure: (1) in situ CO₂ capture within the recovery cycle, (2) oxy-fuel retrofitting of the rotary lime kiln to produce a high-purity CO₂ stream, (3) ex situ CO₂ capture and mineralization using pulp mill residues (dregs, grits, and lime mud), and (4) beneficial reuse of these residues as mineral carbonate fertilizers. The project combined process modeling, laboratory experimentation, life cycle assessment (LCA), and field trials to evaluate the technical feasibility, economic viability, and environmental impact of these approaches. The results demonstrate that pulp mills can serve as effective platforms for carbon removal when equipped with integrated carbon capture systems. Process modeling showed that combining sodium spiking with oxy-fuel calcination significantly enhances CO₂ capture efficiency while reducing costs by up to 31% compared to conventional configurations. Experimental work further revealed that calcination behavior in high-CO₂ environments differs substantially from traditional systems, leading to the development of a new kinetic model that predicts reaction rates under these conditions. This model provides essential design guidance for next-generation decarbonized lime kilns. In parallel, the project demonstrated that alkaline mineral residues generated during pulping operations can be repurposed as a sustainable alternative to agricultural lime. Across a wide range of soils in the southeastern United States, these materials performed equivalently to commercial lime in adjusting soil pH while offering lower greenhouse gas emissions and reduced cost. Field and greenhouse studies confirmed that crop and tree growth responses were comparable, supporting their viability as a drop-in replacement. This co-product pathway provides a practical utilization strategy that offsets costs and improves overall system economics. A major contribution of this project is the first comprehensive life cycle assessment of carbon removal in pulp and paper systems across multiple system boundaries. Results show that retrofitted mills can achieve carbon removal efficiencies ranging from 12% to 92%, depending on how the system is defined. This finding highlights a critical issue in carbon accounting: reported performance is highly sensitive to methodological choices. By explicitly quantifying these differences, this work provides valuable guidance for policymakers, carbon registries, and project developers working to standardize carbon removal metrics. From a commercialization perspective, the technologies investigated in this project are well- aligned with existing industrial infrastructure, minimizing the need for entirely new facilities. 3 DE-EE0009413 Industry engagement throughout the project—including collaboration with pulp and paper companies, equipment manufacturers, and carbon removal developers—has accelerated the transition from research to deployment. Notably, a commercial developer is actively pursuing carbon capture projects at pulp mills in the southeastern United States and has cited this research as a contributing foundation. The emergence of voluntary carbon markets and long-term offtake agreements further strengthens the business case for implementation. The broader public benefits of this work are significant. By enabling large-scale carbon removal using existing industrial systems, this approach offers a near-term pathway to reduce atmospheric CO₂ concentrations while supporting domestic manufacturing and rural economies. The reuse of industrial residues as fertilizers reduces reliance on mined materials, lowers costs for farmers, and decreases environmental impacts associated with conventional lime production. In addition, the project has supported workforce development by training graduate students and researchers in carbon capture technologies, helping to build capacity in a critical area of national interest. In conclusion, this project demonstrates that integrated carbon capture, utilization, and sequestration in pulp mills is both technically feasible and economically promising. By combining process innovation, experimental validation, and systems-level analysis, the work advances the understanding of how biomass-based industries can contribute to climate mitigation. The findings provide a strong foundation for commercial deployment and offer a scalable solution for transforming a major U.S. industry into a source of durable carbon removal.

09 BIOMASS FUELS↗

DOE OSTI2025

An Atomistic Study of Reactivity in Solid-State Electrolyte Interphase Formation for Li/Li7P3S11

Lithium metal batteries offer superior volumetric and gravimetric specific capacities compared to those based on traditional graphite anodes. Although advancements in solid-state electrolytes address safety concerns, challenges remain, particularly regarding interphase formation in lithium metal anodes. This work presents a computational framework based on high-throughput first-principles density functional theory and machine-learning interatomic potentials (MLIPs) including automated iterative, active learning to enable robust computational exploration of interphase formation between lithium metal anodes and an inorganic solid-state electrolyte. As a demonstration, we apply the framework to a Li/Li7P3S11 interface and find that it accurately identifies the experimentally observed, thermodynamically stable interphase products as well as their overall spatial arrangement within a heterogeneous, amorphous layered structure, with Li2S domains of nanocrystallinity. Our simulations show two stages, a fast and slow diffusion reaction regime, that corroborate the relative phase formation rate of Li x P, Li2S, and Li3P. Using the Onsager transport theory, we capture time-dependent ionic diffusion within the reacting interface, including cross-correlation effects. We found that cross-correlation effects between Li-P and P-S ionic motion significantly influence P-ion diffusion, making it highly sensitive to the local environment and potentially leading to "kinetic trapping" of Li-P phases. The passivation of the interface is shown as the ionic fluxes all approach zero, effectively halting interphase growth.

Diffusion↗

DOE OSTI2020

An Eulerian multimaterial framework for simulating high-explosive aquarium tests

Aquarium tests of cylindrical high-explosive charges provide optical data of the detonation front velocity and shape, propagation of the shock wave in the surrounding water, and expansion rates of the detonation products behind the front. Data from aquarium experiments is often used for calibration of reactive burn models based on phenomenological equations of state (EOS) and reaction rate laws. This paper presents a multimaterial numerical modeling framework to solve the 2D axisymmetric reactive Euler equations for high-explosive aquarium tests, in particular for ammonium nitrate - fuel oil (ANFO) explosives. An extension of the Ghost Fluid Method (GFM) is used to handle the dynamic material interfaces for the ANFO explosion products, the charge-confining material (polymethyl methacrylate PMMA), and the surrounding water. This study analyzes the sensitivity of calculations (both computational efficiency and numerical accuracy) to different algorithms for the material interface models including the original GFM versus Riemann solver-based strategies. A novel method for defining the left and right states in the interfacial Riemann problem eliminates the need for sorting or nodal interpolation during the projection along the material interface. Numerical tests indicate that populating the interface node values using the Riemann solution mitigate the overheating error observed in steady-state calculations. Solution convergence and computational efficiency are explored as a function of the spatial and temporal order of the schemes. Results from the computational model with analytical equations of state and fitted reaction rate parameters show very good quantitative agreement with experimentally observed detonation front velocity, reaction products expansion, and shock wave propagation in the surrounding water for a cylindrical ANFO charge encased in PMMA. Finally, the proposed modeling framework, in conjunction with experimental tests, provides a reliable tool to assess equations of state and reaction rate expressions for reactive burn models of confined high explosives.

42 ENGINEERING↗

DOE OSTI2025

Multiscale electro-chemo-mechanical model of high-capacity amorphous silicon anode material in sodium-ion batteries

The growing interest in sodium-ion batteries (SIBs) is fueled by their abundant resources and environmentally friendly nature, with amorphous silicon (a-Si) emerging as a promising anode material for enhancing capacity. However, the key challenge lies in sustaining reversible capacity during cycling. Here, in this work, we developed a multiscale electrochemical model incorporating an a-Si anode to elucidate the performance parameters of SIBs. Additionally, we integrated an electro-chemo-mechanical model at the particle level to capture stress generation, an essential factor in the degradation of high-capacity electrodes. Unlike existing models, our approach accounts for large-deformation chemo-mechanics at the particle scale and includes simulations under varying charge rates to explore multiscale behavior. The results reveal that coupled sodiation significantly prolongs complete cycling times and influences discharge dynamics, indicating that neglecting this coupling leads to an underestimation of actual capacity. Furthermore, we observed pronounced polarization effects at higher charge rates, resulting in heterogeneous stress distributions across the anode. With the identification of critical failure parameters for both active particles and binder materials, offering novel insights for mitigating degradation in high-capacity electrode systems.

Amorphous silicon anode↗

DOE OSTI2024

Phase transition kinetics revealed by in situ x-ray diffraction in laser-heated dynamic diamond anvil cells

We report successful coupling of dynamic loading in a diamond anvil cell and stable laser heating, which enables compression rates up to 500 GPa/s along high-temperature isotherms. Dynamic loading in a diamond-anvil cell allows exploration of a wider range of pathways in the pressure-temperature space compared to conventional dynamic compression techniques. By x-ray diffraction, we are able to characterize and monitor the structural transitions with the appropriate time resolution i.e., millisecond timescales. Using this method, we investigate the γ − ε phase transition of iron under dynamic compression, reaching compression rates of hundreds of GPa/s and temperatures of 2000 K. Our results demonstrate a distinct response of the γ − ε and α − ε transitions to the high compression rates achieved, possibly due to the different transition mechanisms. These findings open up new avenues to study tailored dynamic compression pathways in the pressure-temperature space and highlight the potential of this platform to capture kinetic effects (over ms time scales) in a diamond anvil cell. Published by the American Physical Society 2024

Ricks, Matthew (ORCID:000000015315612X)↗

DOE OSTI2026

Rolling Root Mean Square Based Multimodal Anomaly Detection for Real Time Monitoring of Smart Grid

Reliable real-time monitoring is valuable for maintaining the operational integrity of modern electrical smart grids. Deployment of heterogeneous sensing technologies in substations has enabled high-resolution, multichannel waveform monitoring, but also introduces challenges for anomaly detection due to noise, baseline drift, and modality-dependent signal characteristics. In this work, we present a computationally efficient unsupervised method for multimodal event detection based on Rolling Root Mean Square based Event Detection (RRMSED). The method is developed using in-house, field deployed sensors collecting data at a utility substation. The sensing system comprises voltage and current sensors, triaxial accelerometers, and magnetometers, collectively capturing electrical, vibrational, and magnetic waveform measurements at high temporal resolution. RRMSED operates by extracting rolling RMS energy features and their first-order temporal differences from consecutive waveform segments for each channel and then applying channel-specific statistical thresholds learned from historical data. A persistence-based exceedance logic is employed to robustly identify transient events while suppressing impulsive noise, and to provide precise temporal localization with high resolution. The framework is designed for continuous server-side operation and can be deployed in real time without requiring complex models. Experiments on simulated waveform data with known ground truth demonstrate low false positive (FP) and false negative (FN) rates. Application to real substation data shows RRMSED to identify events that are not captured by conventional monitoring indicators including fast transient detection algorithm currently deployed in the system. These results indicate that rolling RMS based features provide an effective and practical basis for real-time multimodal event detection in smart-grid substations.

Mukherjee, Subrata [ORNL] (ORCID:0000000309930338)↗

DOE OSTI2022

BISON validation of FeCrAl cladding mechanical failure during simulated reactivity-initiated accident conditions*

Here, a reactivity-initiated accident (RIA) is a postulated design basis accident in light water reactors (LWRs) in which a rapid reactivity insertion induces a fission rate increase and a fuel pellet temperature rise. During RIA, the fuel pellet thermally expands and may cause pellet-cladding mechanical interaction (PCMI). Separate effects PCMI tests were performed on C26M FeCrAl cladding tube samples, introducing biaxial stress via a well understood modified burst test (MBT) system. A high-speed camera in the MBT system captured the projections, covering a 360° view of the cladding deformation and enabling a digital image correlation (DIC) method to quantify the surface strains with high fidelity. Representative hot zero-power RIA mechanical loading conditions were applied to the sample, and the test duration ranged from 20 to 500 ms at an average temperature of 573 K. BISON finite element–based fuel performance code modeling was performed against the high-fidelity DIC data produced from the MBTs. Validation calculations were conducted with 2D models and systematically compared with test data of the burst time, burst pressure, burst hoop strains, and hoop strain rates. Based on the behaviors from the separate effects test, BISON calculations satisfactorily predicted the cladding deformation behaviors. Sensitivity analysis was conducted to identify highly influential mechanical properties responsible for the cladding failure behavior during the MBT experiments. The results highlight the significance of the cladding's mechanical strength in governing cladding strain, followed by the significance of the mechanical interactions between the pellet and the cladding.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2024

Fast neutron irradiation capability in existing thermal test reactors

In today’s nuclear industry, momentum towards the design, licensing, and construction of advanced nuclear demonstration plants, including fast reactors, is at a remarkably high level. However, there are currently no dedicated fast spectrum irradiation test facilities in the United States to support the development of fast spectrum technologies. As a result, a unique situation is developing where most of these plants will likely be designed by leveraging historic nuclear material technologies, but where the further optimization and advancement is impeded by the lack of fast neutron irradiation test facilities. While these circumstances present a challenge, there are some near-term opportunities that, if seized, can still help develop advanced fast reactor materials to a meaningful level of readiness to support future commercial fast reactors. Here, in this paper, we assess the feasibility of using thermal neutron filtering materials in existing experiment positions in the Advanced Test Reactor (ATR) at Idaho National Laboratory and the High Flux Isotope Reactor (HFIR) at Oak Ridge National Laboratory to simulate fast reactor test environments for nonfuel test specimens. Items investigated include the incident neutron flux (both fast and thermal), the total neutron fluence and cumulative atom displacements, helium production rate due to thermal neutron capture in nickel, and the potential impact that the thermal neutron filter material has on the cycle length of a given reactor. It is concluded that while HFIR provides the highest fast flux of all the options investigated, it is limited in the amount of thermal neutron filtering material that can be introduced into an experiment position without significantly affecting the operation of the reactor. Irradiation in Outboard-A positions in the ATR was found to be the most realistic near-term experiment avenue due to having ample space for several capsules in a moderately fast flux.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2020

Nonfuel antineutrino contributions in the ORNL High Flux Isotope Reactor (HFIR)

Reactor neutrino experiments have seen major improvements in precision in recent years. With the experimental uncertainties becoming lower than those from theory, carefully considering all sources of $\bar{ν}$ e is important when making theoretical predictions. One source of νe that is often neglected arises from the irradiation of the nonfuel materials in reactors. The $\bar{ν}$ e rates and energies from these sources vary widely based on the reactor type, configuration, and sampling stage during the reactor cycle and have to be carefully considered for each experiment independently. In this article, we present a formalism for selecting the possible $\bar{ν}$ e sources arising from the neutron captures on reactor and target materials. We apply this formalism to the High Flux Isotope Reactor (HFIR) at Oak Ridge National Laboratory, the $\bar{ν}$ e source for the the Precision Reactor Oscillation and Spectrum Measurement (PROSPECT) experiment. Overall, we observe that the nonfuel $\bar{ν}$ e contributions from HFIR to PROSPECT amount to 1% above the inverse beta decay threshold with a maximum contribution of 9% in the 1.8–2.0 MeV range. Nonfuel contributions can be particularly high for research reactors like HFIR because of the choice of structural and reflector material in addition to the intentional irradiation of target material for isotope production. We show that typical commercial pressurized water reactors fueled with low-enriched uranium will have significantly smaller nonfuel $\bar{ν}$ e contribution.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

DOE OSTI2020

Parameterizing Perennial Bioenergy Crops in Version 5 of the Community Land Model Based on Site‐Level Observations in the Central Midwestern United States

Abstract With projected expansion of biofuel production at a global scale, there is a pressing need to develop adequate representation of bioenergy crops in land surface models to help effectively quantify the biogeophysical and biogeochemical effects of its associated land use changes. This study implements two new perennial bioenergy crops, Miscanthus and switchgrass, into the Community Land Model Version 5 based on site‐level observations from the midwestern United States by modifying parameters associated with photosynthesis, phenology, allocation, decomposition, and carbon cost of nitrogen uptake and integrating concomitantly land management practices. Sensitivity analyses indicate that carbon and energy fluxes of the perennial crops are most sensitive to photosynthesis and phenology parameters. Validation of simulated fluxes against site‐level measurements demonstrates that the model is capable of capturing the overall patterns of energy and carbon fluxes, as well as physiological transitions from leaf emergence to senescence. Compared to annual crops, perennial crops feature longer growing season, greater leaf areas, and higher productivity, leading to increased transpiration, lower annual runoff, and larger carbon uptake. The model simulations suggest that with higher CO 2 assimilation rates and lower demands for nutrients and water, high‐yielding perennial crops are promising alternatives of bioenergy feedstocks compared to traditional annual crops not only for mitigating climate change but also for environmental conservation purposes by reducing fertilizer application and therefore alleviating surface‐ and ground‐water contaminations. Although the local‐scale simulations shed light on potential benefits of using perennial grasses as bioenergy feedstocks, quantifying consequences of their plantations at larger scales warrants additional investigation.

Cheng, Yanyan↗

DOE OSTI2020

Evaluating the Influence of Hemorheological Parameters on Circulating Tumor Cell Trajectory and Simulation Time

Extravasation of circulating tumor cells (CTCs) occurs primarily in the microvasculature, where flow and cell interactions significantly affect the blood rheology. Capturing cell trajectory at this scale requires the coupling of several interaction models, leading to increased computational cost that scales as more cells are added or the domain size is increased. In this work, we focus on micro-scale vessels and study the influence of certain hemorheological factors, including the presence of red blood cell aggregation, hematocrit level, microvessel size, and shear rate, on the trajectory of a circulating tumor cell. We determine which of the aforementioned factors significantly affect CTC motion and identify those which can potentially be disregarded, thus reducing simulation time. We measure the effect of these elements by studying the radial CTC movement and runtime at various combinations of these hemorheological parameters. To accurately capture blood flow dynamics and single cell movement, we perform high-fidelity hemodynamic simulations at a sub-micron resolution using our in-house fluid dynamics solver, HARVEY. We find that increasing hematocrit increases the likelihood of tumor cell margination, which is exacerbated by the presence of red blood cell aggregation. As microvessel diameter increases, there is no major CTC movement towards the wall; however, including aggregation causes the CTC to marginate quicker as the vessel size increases. Finally, as the shear rate is increased, the presence of aggregation has a diminished effect on tumor cell margination.

Roychowdhury, Sayan↗

DOE OSTI2022

High‐Resolution Electron Tomography of Ultrathin Boerdijk–Coxeter–Bernal Nanowire Enabled by Superthin Metal Surface Coating

Abstract The rapid advancement of transmission electron microscopy has resulted in revolutions in a variety of fields, including physics, chemistry, and materials science. With single‐atom resolution, 3D information of each atom in nanoparticles is revealed, while 4D electron tomography is shown to capture the atomic structural kinetics in metal nanoparticles after phase transformation. Quantitative measurements of physical and chemical properties such as chemical coordination, defects, dislocation, and local strain have been made. However, due to the incompatibility of high dose rate with other ultrathin morphologies, such as nanowires, atomic electron tomography has been primarily limited to quasi‐spherical nanoparticles. Herein, the 3D atomic structure of a complex core–shell nanowire composed of an ultrathin Boerdijk–Coxeter–Bernal (BCB) core nanowire and a noble metal thin layer shell deposited on the BCB nanowire surface is discovered. Furthermore, it is demonstrated that a new superthin noble metal layer deposition on an ultrathin BCB nanowire could mitigate electron beam damage using an in situ transmission electron microscope and atomic resolution electron tomography. The colloidal coating method developed for electron tomography can be broadly applied to protect the ultrathin nanomaterials from electron beam damage, benefiting both the advanced material characterizations and enabling fundamental in situ mechanistic studies.

Song, Xiaohui↗

DOE OSTI2021

Picosecond laser generated plasma as a source of singly charged ions for external injection into an EBIS

The focus of this paper is on practical aspects of ion generation by picosecond lasers as a source of low charge state ions for external injection of ions into an electron beam ion source (EBIS). For a ps-laser, compared to a ns-laser currently used at Relativistic Heavy Ion Collier Electron Beam Ion Source (RHIC EBIS), the influence of heat conductivity in the solid target is almost negligible, which results in a lower target consumption rate and less vacuum pressure rise. By using a laser with high repetition rate, it is possible to produce quasi continuous 1+ ion beams for periods of tens of milliseconds, making it possible to take advantage of the ability of the EBIS to accumulate ions in the “slow” injection capture mode. Producing such an ion pulse train is now feasible since ps-lasers with pulse energy up to 10 mJ and rep-rate up to 10 kHz have recently become commercially available. The advantages of this lower current accumulation scheme include: (1) easier beam transport due to lower space charge of lower beam currents required compared to the present single pulse fast injection scheme, (2) better EBIS pulse to pulse ion output stability since pulse to pulse ion variations of the laser source are averaged over a long train of laser pulses, and (3) the possible addition of an isotope separator in which rare beams could be produced and selected at run time from less expensive (unenriched) targets. We studied the properties of plasmas generated by a ps-laser with 1.27 mJ energy within an 8 ps pulse and a repetition rate up to 400 Hz at Argonne National Laboratory to investigate feasibility and specify parameters for a laser ion source for RHIC EBIS using a “slow” injection mode. Al, Ti, Cu, Nb, and Ta targets were tested with various target translation speeds. Here, we demonstrated that a both “slow” and “fast” injection modes are accessible with a single ion source geometry and single injection line, providing the most attractive option for an ion source for external injection into RHIC EBIS trap based on a ps-laser.

43 PARTICLE ACCELERATORS↗

DOE OSTI2024

Abstract for CRADA between Capture6 CORP and NETL

The National Energy Technology Laboratory (NETL) and Capture6 CORP (Participant) will collaborate to refine Capture6’s transformative air contactor design for optimal direct air capture (DAC) under an awarded project from the Department of Energy’s Direct Air Capture Pre-Commercialization Technology Prize. Current cooling tower designs require exponentially more resources as the concentration of CO 2 in the gas phase decreases, resulting in a low conversion rate of carbonates, a large physical footprint, and high evaporation of water, which consequently limits the energy and water benefits that a DAC process can create. Capture6’s innovative tower design AURA (Absorption Unit Reactor for Ambient air) seeks to improve the mass transfer characteristics of legacy cooling towers and reduces total energy demand by: (1) introducing laminar and turbulent flow to increase mass transfer, (2) generating a solvent gradient to improve CO 2 absorption, (3) leveraging venturi and packed towers to increase the surface for the mass-transfer process, (4) adding charged/cool plates to reduce overall water loss in the system, and (5) utilizing surfactant additives to increase mass transfer. The collaboration will facilitate the deployment of technologies that reduce the total energy required and carbon footprint of solvent-based carbon dioxide removal (CDR) technologies. The anticipated results support NETL’s goal of fostering rapid development and commercialization pathways for technologies that remove CO 2 from the atmosphere.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗