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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 451 records · Page 25
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Thermal Infrared Detectors: expanding performance limits using ultrafast electron microscopy

This project aimed to identify the performance-limiting mechanisms in mid- to far infrared (IR) sensors by probing photogenerated free carrier dynamics in model detector materials using scanning ultrafast electron microscopy (SUEM). SUEM is a recently developed method based on using ultrafast electron pulses in combination with optical excitations in a pump- probe configuration to examine charge dynamics with high spatial and temporal resolution and without the need for microfabrication. Five material systems were examined using SUEM in this project: polycrystalline lead zirconium titanate (a pyroelectric), polycrystalline vanadium dioxide (a bolometric material), GaAs (near IR), InAs (mid IR), and Si/SiO 2 system as a prototypical system for interface charge dynamics. The report provides detailed results for the Si/SiO 2 and the lead zirconium titanate systems.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Filling data analysis gaps in time-resolved crystallography by machine learning

There is a growing understanding of the structural dynamics of biological molecules fueled by x-ray crystallography experiments. Time-resolved serial femtosecond crystallography (TR-SFX) with x-ray Free Electron Lasers allows the measurement of ultrafast structural changes in proteins. Nevertheless, this technique comes with some limitations. One major challenge is the quality of data from TR-SFX measurements, which often faces issues like data sparsity, partial recording of Bragg reflections, timing errors, and pixel noise. To overcome these difficulties, conventionally, large volumes of data are collected and grouped into a few temporal bins. The data in each bin are then averaged and paired with the mean of their corresponding jittered timestamps. This procedure provides one structure per bin, resulting in a limited number of averaged structures for the entire time interval spanned by the experiment. Therefore, the information on ultrafast structural dynamics at high temporal resolution is lost. This has initiated research for advanced methods of analyzing experimental TR-SFX data beyond the standard binning and averaging method. To address this problem, we use a machine learning algorithm called Nonlinear Laplacian Spectral Analysis (NLSA), which has emerged as a promising technique for studying the dynamics of complex systems. In this work, we demonstrate the power of this algorithm using synthetic x-ray diffraction snapshots from a protein with significant data incompleteness, timing uncertainties, and noise. Our study confirms that NLSA is a suitable approach that effectively mitigates the effects of these artifacts in TR-SFX data and recovers accurate structural dynamics information hidden in such data.

Trujillo, Justin (ORCID:0000000285505360)↗
DOE OSTI2022

UrbanPop: A spatial microsimulation framework for exploring demographic influences on human dynamics

Ensuring the social equity of planning measures in social systems requires an understanding of human dynamics, particularly how individual relationships, activities, and interactions intersect with individual needs. Spatial microsimulation models (SMSMs) support planning for human security goals by representing human dynamics through realistic, georeferenced synthetic populations, that a) provide a complete representation of social systems while b) also protecting individual privacy. In this paper, we present UrbanPop, an open and reproducible SMSM framework for analysis of human dynamics with high spatial, temporal, and demographic resolution. UrbanPop creates synthetic populations of demographically detailed worker and student agents, positioning them first at probable nighttime locations (home), then moving them to probable daytime locations (work/school). Summary aggregations of these populations match the granular detail available at the census block group level in the American Community Survey Summary File (SF), providing realistic approximations of the actual population. UrbanPop users can select particular demographic traits important in their application, resulting in a highly tailored agent population. We first lay out UrbanPop's baseline methodology, including population synthesis, activity modeling, and diagnostics, then demonstrate these capabilities by developing case studies of shifting population distributions and high-risk populations in Knox County, TN during the global COVID-19 pandemic.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2026

Diffusion and Solvation Dynamics of Ions in Water: Beyond the Brownian Approximation

The coupled dynamics of ions and water molecules in their first hydration shell impact a variety of processes including ion diffusion, selective ion transport in water-filled nanopores, and the kinetics of ion-pairing, ion adsorption, and metal-ligand binding reactions. In this work, we study these coupled dynamics for alkali metals (Li, Na, K, Rb, Cs), alkaline Earth metals (Mg, Ca, Sr, Ba), and chloride through the lens of their dependence on ion isotopic mass. Results are validated against previous measurements of the isotopic mass-dependence of ion diffusion coefficients in water and previous ab initio calculations of ion high-frequency dynamics in water. We find that the vibrational power spectra of ions in water consistently exhibit either two or three peaks, i.e., ions have several rattling frequencies within their solvations shells as previously reported for a subset of the species examined here. These frequencies have different sensititivies to isotopic mass that may serve as signatures of ion solvation processes (such as the tendency of ions to orient their first-shell water molecules) and that also may relate to Hofmeister-like effects including the relative affinity of different metals for ribonucleic acid (RNA).

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Assessment of Dynamic Fracture in Ultra-High Performance Concrete Using Synchrotron X-ray Source

Ultra-high-performance concretes (UHPCs) retain higher ultimate (compressive) strengths and greater durability relative to traditional concrete materials. As a result, they are enabling construction materials for blast resistant structures, where a higher capacity for energy absorption is required. In past investigations, the strength of UHPCs was shown to retain a dependency on strain rate. Still, the failure mechanisms which govern this rate dependency have yet to be completely elucidated. In the current study, the dynamic fracture behavior of Cor-tuf UHPC was assessed, in-situ, using a Synchrotron X-ray source in phase contrast imaging (PCI) mode. Prior to testing, the material’s morphology was characterized using X-ray computed tomography (CT) and scanning electron microscopy (SEM). A polychromatic pulsed X-ray source, high-speed camera and Kolsky bar apparatus were used in tandem, to observe the transient failure modes. A pin was placed at the end of the incident bar to control the location of damage initiation, and tests were performed at a constant velocity of ~6 m/s. These test conditions were observed to yield cracks with median and/or cone like geometries. Despite the variation in the crack paths, a significant difference in peak load was not observed. The failure mode was also observed to depend on the microstructure of the concrete samples.

Kolsky bar↗
DOE OSTI2025

Complementing Dynamical Downscaling With Super‐Resolution Convolutional Neural Networks

Despite advancements in Artificial Intelligence (AI) methods for climate downscaling, significant challenges remain for their practicality in climate research. Current AI-methods exhibit notable limitations, such as limited application in downscaling Global Climate Models (GCMs), and accurately representing extremes. To address these challenges, we implement an AI-based methodology using super-resolution convolutional neural networks (SRCNN), trained and evaluated on 40 years of daily precipitation data from a reanalysis and a high-resolution dynamically downscaled counterpart. The dynamical downscaled simulations, constrained using spectral nudging, enable the replication of historical events at a higher resolution. This allows the SRCNN to emulate dynamical downscaling effectively. Modifications, such as incorporating elevation data and data pre-processing enhances overall model performance, while using exponential and quantile loss functions improve the simulation of extremes. Our findings show SRCNN models efficiently and skillfully downscale precipitation from GCMs. Future work will expand this methodology to downscale additional variables for future climate projections.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Milestone report for MRT 8479: High Yield Xray Imager Preliminary Design Review

The High Yield Xray Imager (HYXI) is a new NIF target diagnostic system currently under development. The goal of HYXI is to provide high-fidelity, high temporal resolution x-ray imaging capability on high yield NIF implosions at 10MJ and above. The HYXI instrument design concept is based on the combination of two technologies that have been successfully utilized at the NIF on previous instruments, electron pulse-dilation and hybrid-CMOS sensor imaging. The combination of these two techniques will give HYXI sufficient data quality to ascertain differences in hot spot formation dynamics between high and low yield implosions. This information will highlight the critical hot spot conditions needed for ignition and burn. The HYXI design leverages the successful operation of the PDIXI x-ray imager at the NIF on multi-MJ yield shots. Also, a new radiation tolerance CMOS imaging array is being developed to eliminate the significant background noise which limits the data quality of PDIXI. The HYXI Preliminary Design Review was completed at the end of Q4 FY23. The HYXI project is a multi-year effort with a phased approach to be bring up system functionality over time in parallel with the development and fabrication effort of the new CMOS imaging array. Initial time integrated NIF data will be collected in Q2 FY25, first time resolved imaging with Daedalus starting in Q2 FY26 and the final performance qualification of the complete HYXI system is scheduled for Q2 FY27.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2024

High Yield Xray Imager Final Design Review

The High Yield Xray Imager (HYXI) is a new NIF target diagnostic system currently under development. The goal of HYXI is to provide high-fidelity, high temporal resolution x-ray imaging capability on high yield NIF implosions at 10MJ and above. The HYXI instrument design concept is based on the combination of two technologies that have been successfully utilized at the NIF on previous instruments, electron pulse-dilation and hybrid-CMOS sensor imaging. The combination of these two techniques will give HYXI sufficient data quality to ascertain differences in hot spot formation dynamics between high and low yield implosions. This information will highlight the critical hot spot conditions needed for ignition and burn. The HYXI design leverages the successful operation of the PDIXI x-ray imager at the NIF on multi MJ yield shots. A new radiation tolerant CMOS imaging array (HYPERION) is being developed to eliminate the significant background noise which limits the data quality of PDIXI. We successfully placed the contract with Advanced hCMOS Systems (AHS) to develop the HYPERION sensor, which fulfils our criteria to place long lead time item procurements by end of FY24. The HYXI Final Design Review was completed at the end of Q4 FY24 (Sep 24 th and Sep 30 th ). The HYXI project is a multi-year effort with a phased approach to be bring up system functionality over time in parallel with the development and fabrication effort of the HYPERION CMOS imaging array. In Phase 1, time-integrated x-ray images on NIF DT experiments will be collected starting in Q3 FY25. In Phase 2 of the project, time-resolved imaging with HYXI utilizing a spare microchannel plate detector back-end will begin in Q3 FY26. Phase 3 concludes the project with the installation of the HYPERION sensor array and the final performance qualification of the HYXI instrument which is scheduled for Q3 FY27 as discussed in the PDR and MRT report on this project in FY23.

42 ENGINEERING↗
DOE OSTI2020

Giant electron–phonon coupling of the breathing plane oxygen phonons in the dynamic stripe phase of $\hbox {La}_{1.67}\hbox {Sr}_{0.33}\hbox {NiO}_4$

Doped antiferromagnets host a vast array of physical properties and learning how to control them is one of the biggest challenges of condensed matter physics. La 1.67 Sr 0.33 NiO 4 (LSNO) is a classic example of such a material. At low temperatures holes introduced via substitution of La by Sr segregate into lines to form boundaries between magnetically ordered domains in the form of stripes. The stripes become dynamic at high temperatures, but LSNO remains insulating presumably because an interplay between magnetic correlations and electron–phonon coupling localizes charge carriers. Magnetic degrees of freedom have been extensively investigated in this system, but phonons are almost completely unexplored. We searched for electron–phonon anomalies in LSNO by inelastic neutron scattering. Giant renormalization of plane Ni–O bond-stretching modes that modulate the volume around Ni appears on entering the dynamic charge stripe phase. Other phonons are a lot less sensitive to stripe melting. Dramatic overdamping of the breathing modes indicates that dynamic stripe phase may host small polarons. We argue that this feature sets electron–phonon coupling in nickelates apart from that in cuprates where breathing phonons are not overdamped and point out remarkable similarities with the colossal magnetoresistance manganites.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2022

Quantifying Dynamic Signal Spread in Real-Time High-Energy X-ray Diffraction

Abstract Measured intensity in high-energy monochromatic X-ray diffraction (HEXD) experiments provides information regarding the microstructure of the crystalline material under study. The location of intensity on an areal detector is determined by the lattice spacing and orientation of crystals so that changes in the heterogeneity of these quantities are reflected in the spreading of diffraction peaks over time. High temporal resolution of such dynamics can now be experimentally observed using technologies such as the mixed-mode pixel array detector (MM-PAD) which facilitates in situ dynamic HEXD experiments to study plasticity and its underlying mechanisms. In this paper, we define and demonstrate a feature computed directly from such diffraction time series data quantifying signal spread in a manner that is correlated with plastic deformation of the sample. A distinguishing characteristic of the analysis is the capability to describe the evolution from the distinct diffraction peaks of an undeformed alloy sample through to the non-uniform Debye–Scherrer rings developed upon significant plastic deformation. We build on our previous work modeling data using an overcomplete dictionary by treating temporal measurements jointly to improve signal spread recovery. We demonstrate our approach in simulations and on experimental HEXD measurements captured using the MM-PAD. Our method for characterizing the temporal evolution of signal spread is shown to provide an informative means of data analysis that adds to the capabilities of existing methods. Our work draws on ideas from convolutional sparse coding and requires solving a coupled convex optimization problem based on the alternating direction method of multipliers.

Engineering↗
DOE OSTI2024

Impulse-driven release of gas-encapsulated drops

Gas-encapsulated drops, much like antibubbles, are drops enclosed in a bubble within a liquid. They show potential as payload carriers in fluid transport and mixing techniques where sound waves can be leveraged to induce the collapse of the gas core and the subsequent release of the drop. Here, the interaction of millimetre-sized gas-encapsulated drops with impulsive laser-induced shock waves is investigated to gain fundamental insights into the release process. Experimental synchrotron X-ray phase contrast imaging, which allows the drop dynamics to be visualised inside the encapsulating bubble, is complemented by numerical simulations to study the intricate physics at play. Three drop dynamical release regimes are discovered, namely the drop impact , partial deposition and jet impact regimes. The regime type is mainly dependent on the shape of the bubble interface impacting the drop and the associated Weber and Reynolds numbers. The drop dynamics of the drop impact and partial deposition regimes show similarities with the canonical configuration of drops impacting flat liquid surfaces, whereas the jet impact regime resembles binary drop collisions, which allows existing scaling laws to be applied to describe the underlying processes. The release of the drop is investigated numerically. The time evolution of the drop dissemination within the surrounding liquid discloses enhanced mixing for dynamics involving high Weber and Reynolds numbers such as the drop impact and jet impact regimes.

42 ENGINEERING↗
DOE OSTI2022

Spatial turnover of soil viral populations and genotypes overlain by cohesive responses to moisture in grasslands

Viruses shape microbial communities, food web dynamics, and carbon and nutrient cycling in diverse ecosystems. However, little is known about the patterns and drivers of viral community composition, particularly in soil, precluding a predictive understanding of viral impacts on terrestrial habitats. To investigate soil viral community assembly processes, here we analyzed 43 soil viromes from a rainfall manipulation experiment in a Mediterranean grassland in California. We identified 5,315 viral populations (viral operational taxonomic units [vOTUs] with a representative sequence ≥10 kbp) and found that viral community composition exhibited a highly significant distance–decay relationship within the 200-m 2 field site. This pattern was recapitulated by the intrapopulation microheterogeneity trends of prevalent vOTUs (detected in ≥90% of the viromes), which tended to exhibit negative correlations between spatial distance and the genomic similarity of their predominant allelic variants. Although significant spatial structuring was also observed in the bacterial and archaeal communities, the signal was dampened relative to the viromes, suggesting differences in local assembly drivers for viruses and prokaryotes and/or differences in the temporal scales captured by viromes and total DNA. Despite the overwhelming spatial signal, evidence for environmental filtering was revealed in a protein-sharing network analysis, wherein a group of related vOTUs predicted to infect actinobacteria was shown to be significantly enriched in low-moisture samples distributed throughout the field. Overall, our results indicate a highly diverse, dynamic, active, and spatially structured soil virosphere capable of rapid responses to changing environmental conditions.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Spin-filter tunneling detection of antiferromagnetic resonance with electrically tunable damping

Antiferromagnetic spintronics offers the potential for higher-frequency operations and improved insensitivity to magnetic fields compared to ferromagnetic spintronics. However, previous electrical techniques to detect antiferromagnetic dynamics have utilized large, millimeter-scale bulk crystals. In this work, we demonstrate direct electrical detection of antiferromagnetic resonance in structures on the few-micrometer scale using spin-filter tunneling in platinum ditelluride (PtTe 2 )/bilayer chromium sulfide bromide (CrSBr)/graphite junctions in which the tunnel barrier is the van der Waals antiferromagnet CrSBr. This sample geometry allows not only efficient detection but also electrical control of the antiferromagnetic resonance through spin-orbit torque from the PtTe 2 electrode. The ability to efficiently detect and control antiferromagnetic resonance enables detailed studies of the physics governing these high-frequency dynamics.

Cham, Thow Min Jerald [Cornell University, Ithaca,↗
DOE OSTI2020

Direct observations of shock-induced melting in a porous solid using time-resolved x-ray diffraction

Here in this work we provide direct evidence of shock-induced melting and associated kinetics in a porous solid (aluminum powder) using time-resolved x-ray diffraction. Unambiguous evidence of melting in 50% porous aluminum (Al) powder samples, shocked to peak pressures between ~13 - 19 GPa, was provided by the broadening of the Debye-Scherrer ring corresponding to the (111) peak. Shocked Al powder did not melt completely in any of our experiments within the durations of measurement. Incomplete (partial) melting of the powder, even after several hundreds of nanoseconds of shock loading, provides insights into thermal transport with Al powder particles under high-pressure dynamic loading. Such insights are quite valuable for developing well-constrained melting models and thermodynamic equations of state for porous Al and other porous solids relevant to planetary and materials science.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Characterization of Contaminants and Mobility in WMA A-AX Boreholes D0006 and D0008

This study was initiated to determine if subsurface contaminants in the A-AX vadose zone at the Hanford site (boreholes D0006 and D0008) caused corrosion of nearby stainless steel well casings (299-E-24-19, 299-E25-46, and 299-E25-236) and, based on the type and distribution of contaminants, determine if contaminants are from one or more sources including a) the A-104 and/or A-105 tanks, b) the 242A evaporator, and c) the 200-E-286 ditch. A tiered approach was used for characterizing contaminants in vadose zone sediments starting with mobile and total contaminant concentrations (Tier 1), characterizing contaminant speciation (Tier 2), and measuring contaminant leaching (Tier 3). Total and mobile contaminant measurements at seven depths showed elevated sulfate and nitrate in all samples (130 to 280 ft depth), elevated chloride in five depths, and no elevated radionuclides except I-129 in D0006 at 206 to 208 ft depth. If these contaminants were initially acidic, stainless-steel corrosion would occur. However, because sediments likely have a high acid neutralization capacity, an acidic spill would have been neutralized within tens of feet, so casing corrosion would likely occur in shallow sediments. GEL labs data also shows low (but above natural) chromate from shallow to 170 ft depth, then higher chromate to 280 ft, suggesting a surface Cr spill or casing corrosion. GEL labs data also showed evidence of more than one plume, with deep nitrate, sulfate, and chloride migration, but only shallow tritium migration. Tritium should migrate nearly unretarded in the subsurface like nitrate and chloride. Elevated aqueous cations and anions in the D0006 206 to 208' depth pore water (SO 4 2- , NO 3 - , Na + , K + , Ca 2+ , Mg 2+ , Si) could be the result of acid disposal and calcite dissolution at shallow depth, with deeper migration of SO 4 2- , NO 3 - from acids and Ca 2+ and Mg 2+ from calcite. Elevated Si (160 mg/L) indicates dissolution of clays or other silicates, which can also occur in acids. Acid extractable metals did show elevated Cr (but not Fe, Ni, Mo, and Mn) above natural levels, which may indicate stainless-steel well corrosion or transport of metals from a shallow spill. The elevated I-129 in D0006 at 206 to 208' depth was low with 0.34 μg/g in pore water and 1.5 μg/g total extractable I-129 in the sediment, which indicates significant fraction of I-129 was bound in one or more precipitates. Although total I-129 was below detection limits in most extractions due to high molybdate interference, I-127 analysis provided some insight into potential precipitate phases. Total I-127 was mainly extracted by acetate or acetic acid (67%), which may be iodine in calcite. Inorganic carbon measurement identified 1.65% calcite, and total organic carbon (TOC) was below detection limits, so iodine was not associated with organic matter. Nearly all the I-127 was present as iodide. In 1-D leach experiments, I-127 as iodide leached from the sediment within 2 pore volumes. Due to high and dynamic molybdate leaching from the sediment and interference with I-129 analysis, there were few quantifiable I-129 measurements. The calculated molybdate release rates from the sediment suggested Mo was being released from the same precipitate phase, such as molybdate incorporated into calcite. Overall, because there was little radioactive contamination measured in D0006 and D0008 boreholes, potential releases from A-104 and A-105 did not reach this location south of the A tank farm. Elevated cations and anions found in D0006 and D0008 at depth as the result of acidic disposal could cause shallow stainless steel casing corrosion. The nearby 242A evaporator generally contained alkaline waste and tritium, but the nearby 200-E-286 ditch generally contained high Cl - liquid effluent, so these are unlikely to be acidic sources.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2025

Future Intensity‐Duration‐Frequency Curves of Extreme Precipitation in the Midwest United States From Convection‐Permitting Modeling

Abstract During the last four decades, global warming has statistically significant intensified extreme precipitation events in the Midwestern United States (defined here as the region covering Illinois, Indiana, Ohio, and Kentucky), leading to increased risks to human life, property, and infrastructure. To enable climate change adaptation and resilience across various economic and social sectors in this region, updated information about future climate changes, specifically at finer spatial scales, is essential. Leveraging a new 150‐year dynamical downscaling data set at convection‐permitting resolution, this study introduces a framework to construct the projected future intensity‐duration‐frequency (IDF) curves of heavy precipitation, which are prominent tools for infrastructure design and water resources management. This framework generates IDF curves at both sub‐daily and multi‐day duration utilizing hourly in situ observations as well as quantile‐based statistical techniques in bias‐correction and return levels selection. The assumption of non‐stationarity in the distribution parameter fitting process is also implemented in this workflow. Compared to historical IDF curves for 1980–2022, future projected IDF curves for 2058–2100 under Representative Concentration Pathway (RCP) 4.5 and RCP 8.5 scenarios indicate an average intensity increase of approximately 15% and 25%, respectively, across 74 stations, considering both annual and seasonal timescales. Future projections suggest that extreme precipitation events may become more severe across six investigated return periods, with longer return periods showing a greater increase. The frequency of future extreme precipitation events in the Midwest region is also projected to double. Furthermore, current results reveal spatial heterogeneity of future trends across stations owing to the high‐resolution input data set. Plain Language Summary This study investigates the evolving nature of extreme precipitation events in the Midwestern United States under a changing climate. By leveraging a high‐resolution dynamical downscaling data set, we construct projected intensity‐duration‐frequency (IDF) curves for future extreme rainfall events. These curves serve as vital tools for infrastructure planning and water resource management. Our analysis reveals a significant increase in both the intensity and frequency of extreme precipitation events in the region. Future projected IDF curves for the late century indicate an average intensity increase of approximately 15%–25% compared to historical values. Moreover, the frequency of such events is expected to double. Spatial heterogeneity in future trends is observed across different stations within the Midwest, highlighting the importance of high‐resolution modeling in capturing localized climate variability. These findings underscore the urgent need for climate adaptation strategies to mitigate the increasing risks associated with extreme precipitation events in the region. Key Points This study introduces a workflow to construct future intensity‐duration‐frequency (IDF) curves over the Midwest United States using a new convection‐permitting modeling data set The current IDF construction workflow reproduces well the historical observed IDF 30 curves in summer months with median relative errors of 2.4% among 74 stations and 6 investigated durations The projected IDF curves show diverse future trends of extreme precipitation across stations, with intensity increases of approximately 15% and 25% under RCP4.5 and RCP8.5 climate scenarios, respectively, and a doubling of frequency on average

Nguyen, Trung↗
DOE OSTI2022

A high-dimensional neural network potential for molecular dynamics simulations of condensed phase nickel and phase transitions

A high-dimensional neural network interatomic potential was developed and used in molecular dynamics simulations of condensed phase Ni and Ni systems with liquid–solid phase coexistence. The reference data set was generated by sampling the potential energy surface over a broad temperature-pressure domain using ab initio MD simulations to train a unified potential. Excellent agreement was achieved between bulk face-centered cubic nickel thermal expansion simulations and relevant experimental data. The same potential also yields accurate structures and diffusivities in the liquid state. The phase transition between liquid and solid phases was simulated using the two-phase interface method. The predicted melting point temperature is within a few kelvins of the literature value. Here, the general methodology could be applied to describe crystals with much more complex phase behaviors.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2022

Mesoflow: An Open-Source Reacting Flow Solver for Catalysis at Mesoscale

We present the capabilities and software performance metrics of our open-source continuum solver for catalysis, Mesoflow, developed specifically for modeling transport and chemistry at the mesoscale. Our solver utilizes Cartesian block-structured adaptive mesh refinement to resolve complex catalyst surface morphologies directly obtained from X-ray tomography data. An immersed boundary based formulation enables rapid representation of complex geometries prevalent in most mesoporous catalyst interfaces. The solver is developed on top of open-source performance portable library, AMReX, providing parallel execution capabilities on current and upcoming high-performance-computing (HPC) architectures. Our flexible software framework enables integration of complex chemical mechanisms at heterogenous interfaces and time-split algorithms for circumventing highly disparate reaction and flow time-scales. Our current studies indicate a ten-fold performance gain by using graphics-processing-units (GPUs) compared to a single processor for representative problem sizes (2 million cell mesh). We will also present a brief introduction on how to build and use this software for application problems pertaining to catalytic upgrading and gas transport within porous catalyst particles.

adaptive meshing↗