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At least 649 records · Page 36
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Characterization of Mk-IV and EBR-II X441A Metallic Fuel Pins for the THOR-C-2 and THOR-M-TOP-1 Experiments: Results from Post-Transient Neutron Tomography of THOR-C-2 Capsule and Pre-transient Non-Destructive and Destructive Examination of DP 36 and DP 40 (Rev.1)

Current interest in sodium-cooled fast reactor designs, such as TerraPower’s Natrium Reactor, has highlighted the need for advanced-reactor fuel technology development. A Fuel Safety Research and Development (FSRD) program for metallic fast reactor fuels has been created to achieve comprehensive safety testing within the re-commissioned Transient Reactor Test (TREAT) facility at the Idaho National Laboratory. Despite over 60 years of metallic fuel irradiation, uncertainties exist in the performance of the fuel system, particularly under anticipated operational occurrences and severe accident scenarios. Throughout historical testing within the Experimental Breeder Reactor (EBR)-II and the Fast Flux Test Facility, fuel behavior has demonstrated benign response to transient reactor conditions; however, accurate predictions of failure thresholds rely heavily on fuel composition and irradiation history. In advancing the FSRD program, two planned transient heating experiments are at various stages of completion. The Temperature Heat sink Overpower Response (THOR)-C-2, fueled with an unirradiated Mk IV U-10Zr pin, has undergone transient irradiation in TREAT and post-transient three-dimensional neutron tomography. Additionally, pre-transient characterization of test and sibling U-19Pu-10Zr pins for THOR-M-TOP-1 was evaluated by both non-destructive and destructive methods. The test and sibling pins were selected from previously irradiated EBR-II experiment X441A. Both pins underwent visual examination, precise gamma spectrometry, two-dimensional neutron radiography, and element contact profilometry while the sibling pin was additionally subjected to sectioning and optical microscopy. THOR-C-2 radiography captured the fuel and cladding relocation during the intermediate transient at the top and bottom of the THOR capsule, allowing key features to be linked to the pin’s measured thermal response. For THOR M TOP 1, a solid baseline for steady-state behavior has been established. No anomalous features were identified in either the test or sibling pin. Defining characteristics and features were recorded for further comparisons.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2024

Iron Impurity Impairs the CO 2 Capture Performance of MgO: Insights from Microscopy and Machine Learning Molecular Dynamics

Magnesium oxide (MgO) is a promising sorbent for direct air capture (DAC) of carbon dioxide. Iron (Fe) is a common impurity in naturally occurring MgO and minerals used to produce MgO, yet a molecular-scale understanding of Fe-doping effects on carbonation is lacking. Here, in this study, we observed reduced carbonation performance in Fe-doped MgO experimentally. The energetics of adsorbing a (bi)carbonate ion on pristine and Fe-doped MgO(001) surfaces were further investigated using ab initio and machine learning potential molecular dynamics coupled with metadynamics simulations. Both pristine and Fe-doped surfaces exhibited a basic (OH – ) hydration layer, where the (bi)carbonate ion adsorption is thermodynamically favorable. However, the dissolution of surface Fe had smaller energy barriers and was more favorable than Mg. Leached Fe likely neutralized the near-surface basicity, yielding reduced reactivity on Fe-doped MgO. Our observations offer critical insights for material selection and emphasize the importance of evaluating the geologic origin of earth materials used for DAC.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Optimizing Alabama’s CO 2 Storage in Shelby County (Project OASIS), Task 5.0 Deliverable: Infrastructure Assessment Report

The “Optimizing Alabama’s CO 2 Storage in Shelby County: Project OASIS” CarbonSAFE Phase II Project seeks to build on regional data sets that demonstrate that the subsurface within Shelby County, Alabama has the potential to store commercial volumes of CO 2 safely, permanently, and economically. This work builds on the initiatives of the Southeast Regional Carbon Utilization and Storage Acceleration Partnership (SECARB-USA, DE-FE0031830) that identified nearly 500 million metric tonnes of CO 2 emitted on an annual basis that is not collocated with prospective storage geology (the Coastal Plain of the Southeastern U.S. in this context). This observation suggests costly investments in connective infrastructure (e.g., pipelines) or exploratory well drilling campaigns to identify CO 2 storage opportunities in under explored areas. While not traditionally thought of for saline storage, these studies suggest that storage prospects in the Valley and Ridge Province occur in relatively flat lying structural panels between thrust faults. For the Project OASIS region, available geologic studies related to hydrocarbon exploration suggest that Cambro-Ordovician carbonates and Cambrian clastic units offer multiple potential storage intervals, and that regional confining systems are present, such as the tectonically thickened Floyd-Parkwood Shale. The Project OASIS surface property is owned by a timber and land stewardship company, The Westervelt Company, Inc., who worked with the Project Team to select and prepare adequate sites for geologic assessment.

20 FOSSIL-FUELED POWER PLANTS↗
DOE OSTI2020

Molecularly engineering polymeric membranes for H 2 / CO 2 separation at 100–300 °C

Over the last two decades, polymers with superior H 2 /CO 2 separation properties at 100–300 °C have gathered significant interest for H 2 purification and CO 2 capture. This timely review presents various strategies adopted to molecularly engineer polymers for this application. We first elucidate the Robeson's upper bound at elevated temperatures for H 2 /CO 2 separation and the advantages of high-temperature operation (such as improved solubility selectivity and absence of CO 2 plasticization), compared with conventional membrane gas separations at ~35 °C. Second, we describe commercially relevant membranes for the separation and highlight materials with free volumes tuned to discriminate H 2 and CO 2 , including functional polymers (such as polybenzimidazole) and engineered polymers by cross-linking, blending, thermal treatment, thermal rearrangement, and carbonization. Third, we succinctly discuss mixed matrix materials containing size-sieving or H 2 -sorptive nanofillers with attractive H 2 /CO 2 separation properties.

42 ENGINEERING↗
DOE OSTI2022

Machine learning-based ethylene concentration estimation, real-time optimization and feedback control of an experimental electrochemical reactor

With the increase in electricity supply from clean energy sources, electrochemical reduction of carbon dioxide (CO 2 ) has received increasing attention as an alternative source of carbon-based fuels. As CO 2 reduction is becoming a stronger alternative for the clean production of chemicals, the need to model, optimize and control the electrochemical reduction of the CO 2 process becomes inevitable. However, on one hand, a first-principles model to represent the electrochemical CO 2 reduction has not been fully developed yet because of the complexity of its reaction mechanism, which makes it challenging to define a precise state-space model for the control system. On the other hand, the unavailability of efficient concentration measurement sensors continues to challenge our ability to develop feedback control systems. Gas chromatography (GC) is the most common equipment for monitoring the gas product composition, but it requires a period of time to analyze the sample, which means that GC can provide only delayed measurements during the operation. Moreover, the electrochemical CO 2 reduction process is catalyzed by a fast-deactivating copper catalyst and undergoes a selectivity shift from the product-of-interest at the later stages of experiments, which can pose a challenge for conventional control methods. To this end, machine learning (ML) techniques provide a potential approach to overcome those difficulties due to their demonstrated ability to capture the dynamic behavior of a chemical process from data. Motivated by the above considerations, we propose a machine learning-based modeling methodology that integrates support vector regression and first-principles modeling to capture the dynamic behavior of an experimental electrochemical reactor; this model, together with limited gas chromatography measurements, is employed to predict the evolution of gas-phase ethylene concentration. The model prediction is directly used in a proportional-integral (PI) controller that manipulates the applied potential to regulate the gas-phase ethylene concentration at energy-optimal set-point values computed by a real-time process optimizer (RTO). Specifically, the RTO calculates the operation set-point by solving an optimization problem to maximize the economic benefit of the reactor. Finally, suitable compensation methods are introduced to further account for the experimental uncertainties and handle catalyst deactivation. The proposed modeling, optimization, and control approaches are the first demonstration of active control for a CO 2 electrolyzer and contribute to the automation and scale-up efforts for electrified manufacturing of fuels and chemicals starting from CO 2 .

42 ENGINEERING↗
DOE OSTI2022

Sorghum Association Panel whole‐genome sequencing establishes cornerstone resource for dissecting genomic diversity

SUMMARY Association mapping panels represent foundational resources for understanding the genetic basis of phenotypic diversity and serve to advance plant breeding by exploring genetic variation across diverse accessions. We report the whole‐genome sequencing (WGS) of 400 sorghum ( Sorghum bicolor (L.) Moench) accessions from the Sorghum Association Panel (SAP) at an average coverage of 38× (25–72×), enabling the development of a high‐density genomic marker set of 43 983 694 variants including single‐nucleotide polymorphisms (approximately 38 million), insertions/deletions (indels) (approximately 5 million), and copy number variants (CNVs) (approximately 170 000). We observe slightly more deletions among indels and a much higher prevalence of deletions among CNVs compared to insertions. This new marker set enabled the identification of several novel putative genomic associations for plant height and tannin content, which were not identified when using previous lower‐density marker sets. WGS identified and scored variants in 5‐kb bins where available genotyping‐by‐sequencing (GBS) data captured no variants, with half of all bins in the genome falling into this category. The predictive ability of genomic best unbiased linear predictor (GBLUP) models was increased by an average of 30% by using WGS markers rather than GBS markers. We identified 18 selection peaks across subpopulations that formed due to evolutionary divergence during domestication, and we found six F st peaks resulting from comparisons between converted lines and breeding lines within the SAP that were distinct from the peaks associated with historic selection. This population has served and continues to serve as a significant public resource for sorghum research and demonstrates the value of improving upon existing genomic resources.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2026

Development of a pattern recognition algorithm for reconstructing multi-particle events in the Mu2e detector

Mu2e is an upcoming experiment at Fermilab and its main goal is to search for the Charged Lepton Flavor Violation (CLFV) in the coherent transition of a muon into an electron on an Al target. In Mu2e, multi-particle events can occur simultaneously within the same time region and it is crucial to accurately identify each particle track, including signals, to improve the robustness of track finding methods and enhance reconstruction efficiency. ¯p annihilation is one of the background events and produces multiple particles that can mimic signal events. Additionally, photons from radiative pion captures can produce a γ → $e+e−$ pair, which can be used to calibrate the Mu2e momentum scale and the resolution. The Mu2e track reconstruction sequence begins by grouping hits produced in the tracker based on time and z coordinate information, called TimeCluster, and selected hits are processed to reconstruct helices and determine their momentum. The current pattern recognition algorithms identify a single helix per TimeCluster for single track events. A new pattern recognition algorithm is being developed to reconstruct multi-particle events and its features for finding multiple tracks and the current evaluation results are reported.

Kitagawa, H. [Pisa U.]↗
DOE OSTI2024

Integrated Process for Direct Air Capture of CO 2 and Electrochemical Conversion to Ethanol

This Cooperative Research and Development Agreement (CRADA) between UT-Battelle, LLC and Reactwell, L.L.C. aimed to facilitate the development of an energy-efficient and cost-effective technology that captures carbon dioxide (CO 2 ) from ambient air and converts it electrochemically to ethanol. Direct air capture (DAC) of CO 2 offers the prospect of permanently lowering the atmospheric CO 2 concentration, providing economic and energy-efficient technologies can be developed and deployed at a large scale. DAC has the potential for high-capacity atmospheric CO 2 capture, the flexibility of placement anywhere on earth, and the generation of high-purity CO 2 streams. The most significant technical challenge with DAC is the very low atmospheric concentration of CO 2 , thereby requiring sorbents that bind CO 2 quickly, strongly, and selectively against other components in the air. Integrating DAC with CO 2 conversion into useful chemicals, fuels, or materials can provide an economically feasible solution for mitigating climate change. As long as the carbon contained in these products is taken from the atmosphere and no additional carbon emissions result from their production, processing, and transportation, they can be considered carbon-neutral products. This CRADA facilitated the development of a new net-zero emission technology that closes the carbon cycle by combining DAC with the catalytic electrochemical conversion of CO 2 into ethanol.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Methods for ultraviolet excitation microscopy of biological surfaces

Microscopy with Ultraviolet Surface Excitation (MUSE) for use in the classroom to enhance life sciences education and curricula, or for other applications, including without limtiation the operating room, other medical environments, research environments, and low resource environments. MUSE's suitability is based on multiple key factors including its simplicity of use, the incorporation of inexpensive hardware including LED illumination, and very basic tissue preparation. The ultraviolet excitation acts as passive optical sectioning confining the generated fluorescence signal to only a few micrometers below the tissue surface thus eliminating the out of focus signals. This facilitates image capture of tissue microstructure and organization from specimens at the intact or sliced surface arising from varying fluorophore concentration within the different cellular compartments. Although just the tissue auto fluorescence maybe used, image quality is enhanced with brief application of nontoxic fluorescent dyes to selectively highlight cellular compartments. Sample preparation is safe, efficient and familiar to students with basic chemistry or biology lab experience. Mixed-dye powders may be used to simplify translation of this method for educational, medical, research, low resource, and other settings.

Demos, Stavros G.↗
DOE OSTI2022

Mass Transport Limitations and Kinetic Consequences of Corn Stover Deacetylation

Alkaline pretreatment of herbaceous feedstocks such as corn stover prior to mechanical refining and enzymatic saccharification improves downstream sugar yields by removing acetyl moieties from hemicellulose. However, the relationship between transport phenomena and deacetylation kinetics is virtually unknown for such feedstocks and this pretreatment process. Here, we report the development of an experimentally validated reaction–diffusion model for the deacetylation of corn stover. A tissue-specific transport model is used to estimate transport-independent kinetic rate constants for the reactive extraction of acetate, hemicellulose and lignin from corn stover under representative alkaline conditions (5–7 g L -1 NaOH, 10 wt% solids loadings) and at low to mild temperatures (4–70°C) selected to attenuate individual component extraction rates under differential kinetic regimes. The underlying transport model is based on microstructural characteristics of corn stover derived from statistically meaningful geometric particle and pore measurements. These physical descriptors are incorporated into distinct particle models of the three major anatomical fractions (cobs, husks and stalks) alongside an unsorted, aggregate corn stover particle, capturing average Feret lengths of 917–1239 μm and length-to-width aspect ratios of 1.8–2.9 for this highly heterogeneous feedstock. Individual reaction–diffusion models and their resulting particle model ensembles are used to validate and predict anatomically-specific and bulk feedstock performance under kinetic-controlled vs. diffusion-controlled regimes. In general, deacetylation kinetics and mass transfer processes are predicted to compete on similar time and length scales, emphasizing the significance of intraparticle transport phenomena. Critically, we predict that typical corn stover particles as small as ~2.3 mm in length are entirely diffusion-limited for acetate extraction, with experimental effectiveness factors calculated to be 0.50 for such processes. Debilitatingly low effectiveness factors of 0.021–0.054 are uncovered for cobs—implying that intraparticle mass transfer resistances may impair observable kinetic measurements of this anatomical fraction by up to 98%. These first-reported quantitative maps of reaction vs. diffusion control link fundamental insights into corn stover anatomy, biopolymer composition, practical size reduction thresholds and their kinetic consequences. These results offer a guidepost for industrial deacetylation reactor design, scale-up and feedstock selection, further establishing deacetylation as a viable biorefinery pretreatment for the conversion of lignocellulosics into value-added fuels and chemicals.

09 BIOMASS FUELS↗
DOE OSTI2021

Harnessing Peptide Binding to Capture and Reclaim Phosphate

With rising consumer demands, society is tapping into wastewater as an innovative source to recycle depleting resources. Novel reclamation technologies have been recently explored for this purpose, including several that optimize natural biological processes for targeted reclamation. However, this emerging field has a noticeable dearth of synthetic material technologies that are programmed to capture, release, and recycle specified targets; and of the novel materials that do exist, synthetic platforms incorporating biologically inspired mechanisms are rare. We present here a prototype of a materials platform utilizing peptide amphiphiles that has been molecularly engineered to sequester, release, and reclaim phosphate through a stimuli-responsive pH trigger, exploiting a protein-inspired binding mechanism that is incorporated directly into the self-assembled material network. This material is able to harvest and controllably release phosphate for multiple cycles of reuse, and it is selective over nitrate and nitrite. We have determined by simulations that the binding conformation of the peptide becomes constrained in the dense micelle corona at high pH such that phosphate is expelled when it otherwise would be preferentially bound. However, at neutral pH, this dense structure conversely employs multichain binding to further stabilize phosphate when it would otherwise be unbound, opening opportunities for higher-order conformational binding design to be engineered into this controllably packed corona. With this work, we are pioneering a new platform to be readily altered to capture other valuable targets, presenting a new class of capture and release materials for recycling resources on the nanoscale.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Field evaluation of zone temperature response to control actions in cooling systems of small and medium-sized office buildings

The response of zone temperature to control actions in heating, ventilation, and air conditioning (HVAC) systems, known as zone temperature response, has been a central focus of building control research owing to its crucial role in determining control performance. However, existing studies often overlook the representativeness of the buildings being studied, resulting in unclear generalizations. In addition, those studies tend to focus on a single aspect of the response. Furthermore, this paper provides the first comprehensive characterization of zone temperature response applicable to a clearly defined building sector—small and medium-sized office (SMO) buildings (<5000 m 2 ) in the US. Specifically, two representative SMO buildings, selected based on the US Department of Energy’s commercial prototype buildings, were studied. Field tests were conducted over a 2-month period during summer, and the collected data were analyzed with two key metrics—delay time and nonlinearity index—to quantify zone temperature response, capturing both short- and long-term patterns. Beyond this quantitative characterization, the analysis reveals that the HVAC system type, rather than factors like floor area or zone location, is the primary determinant of the zone temperature response. Drawing on the field test results, we recommend that building control strategies monitor zone temperatures at intervals shorter than 10 minutes, configure controls independently for VAV- and RTU-served zones, and implement nonlinear methods at the zone level—particularly for VAV zones—rather than across the entire building.

Building control↗
DOE OSTI2022

In-Use Passenger Vessel Emission Rates of Black Carbon and Nitrogen Oxides

This study quantified emission factors of black carbon (BC) and nitrogen oxides (NO x ) from 21 engines on in-use excursion vessels and ferries operating in California's San Francisco Bay, including EPA uncertified and Tier 1-4 engines and across engine operating modes. On average, ~60 fuel-based emission factors per engine were measured using a novel combination of exhaust plume capture combined with GPS location and speed data that can be more readily deployed than common portable emissions measurement systems. Here, BC and NO x emission factors (g kg -1 ) were lowest and least variable during fast cruising and highest during maneuvering and docked operation. Selective catalytic reduction (SCR) reduced NO x emissions by ~80% when functional. However, elevated NO x emissions that exceeded corresponding exhaust standards were measured on most Tier 3 and Tier 4 engines sampled, which can be attributed to inactive SCR during frequent low engine load operation. In contrast, BC emissions exceeded the PM emission standard for only one engine, and SCR systems employed as a NO x reduction technology also reduced emitted BC. Using these measured emission factors to compare commuting options, we show that the CO 2 -equivalent emissions per passenger-kilometer are comparable when commuting by car and ferry, but BC and NO x emissions can be several to more than ten times larger when commuting by ferry.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Minimal cyclic behavior in sheared amorphous solids

Although jammed packings of soft spheres exist in potential energy landscapes with a vast number of minima, when subjected to cyclic shear they may revisit the same configurations repeatedly. Simple hysteretic spin models, in which particle rearrangements are represented by interacting spin flips called hysterons, capture many features of this periodic behavior. Yet it has been unclear to what extent individual rearrangements can be described by such binary objects and how such objects interact with one another. Using a particularly sensitive algorithm, we identify rearrangements in simulated jammed packings and select pairs of rearrangements that undo one another to create periodic cyclic behavior. We find that the rearrangement pairs surprisingly persist down to the smallest increments in strain, even in the smallest systems we can study. We explore the statistics of these rearrangement pairs and find that there is a relation between the amount of hysteresis and the energy drop and mean-square displacement of the particles; these results are inconsistent with the scaling found in models that treat rearrangements as localized buckling events. Finally, our analysis shows that there is no clean distinction between the particle motions that represent the identity of a single, individual rearrangement and the particle motions that lead to interactions between separated rearrangements or hysterons. These results offer insight into how complex systems such as amorphous solids can reach a limit cycle.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2021

Measurement of Deformation Heterogeneity During Shale Swelling Using Digital Image Correlation

Abstract Rock-fluid interactions in shale formations are one of the main sources of wellbore instability issues and inadequate stimulation performance. For better planning of fracturing operations and optimizing production from these reservoirs, it is important to understand the mechanisms behind these interactions. These issues are especially prevalent in clay-rich shales, such as Tuscaloosa Marine Shale, which is the subject of this study. Conventional techniques to quantify these shale-fluid interactions comprise of measuring swelling in powdered rock grains or measurement of deformation in the whole pieces of the core using a linear variable differential transformer and strain gages. However, the contribution from individual laminae to overall deformation cannot be evaluated using these methods. In this study, we developed an experimental setup to evaluate the spatial deformation in shale during interaction with water using digital image correlation (DIC). Deformation of two shale samples, with 34 wt% to 51 wt% clay content, was studied. White paint was used to generate a random speckle pattern on the specimen and then immersed in deionized water. The deformation process was captured using a digital camera and images were analyzed using DIC to quantify the deformation. The implementation of the DIC technique enables the visualization and quantification of spatial deformation in the specimen during interacting with water. The results show the localization of large strains in select laminations. The results provide a better understanding of shale deformation when interacting with water in comparison to traditional measurements that can provide only an average strain value.

Energy & Fuels↗
DOE OSTI2025

Planar Collisionless Shock Simulations with the Semi-implicit Particle-in-cell Model FLEKS

This study investigates the applicability of the semi-implicit particle-in-cell code FLexible Exascale Kinetic Simulator (FLEKS) to heliospheric shock simulations. We examine one- and two-dimensional local planar shock simulations, initialized using MHD states with upstream conditions representative of plasmas in the hypersonic, β ∼ 1 regime, for both quasi-perpendicular and quasi-parallel configurations. The refined algorithm in FLEKS proves robust, enabling accurate shock simulations with a grid resolution on the order of the electron inertial length d e . Our simulations successfully capture key shock features, including shock structures (foot, ramp, overshoot, and undershoot), upstream and downstream waves (fast magnetosonic, whistler, Alfvén ion-cyclotron, and mirror modes), and non-Maxwellian particle distributions. Crucially, we find that at least two spatial dimensions are critical for accurately reproducing downstream-wave physics in quasi-perpendicular shocks and capturing the complex dynamics of quasi-parallel shocks, including surface rippling, shocklets, short, large-amplitude magnetic structures, magnetic reconnection, and jets. Furthermore, our parameter studies demonstrate the impact of mass ratio and grid resolution on shock physics. This work provides valuable guidance for selecting appropriate physical and numerical parameters for shock simulations using a semi-implicit PIC method, paving the way for incorporating kinetic shock processes into large-scale collisionless plasma simulations with the MHD-AEPIC model.

plasma astrophysics↗
DOE OSTI2025

A bi-level spatiotemporal clustering approach and its application to drought extraction

We present a novel flexible bi-level spatiotemporal clustering algorithm to extract events based on their intensity and spatiotemporal structures. Our algorithm consists of using (i) a novel space-time k-means clustering to obtain spatiotemporally coherent intensity clusters, and (ii) a density-based spatial clustering of applications with noise (DBSCAN) to spatiotemporally section the intensity clusters into individual events. We discuss the development of the algorithm, the selection, tuning and meaning of the parameters within each step, as well as its validation. Finally, we apply the algorithm to a spatiotemporal drought index, standardized vapor pressure deficit drought index (SVDI), over the continental United States (US) from 1980–2021 and show that it captures historical drought events over the continental United States and their spatiotemporal extents.

17 WIND ENERGY↗
DOE OSTI2024

Carbon Capture through Membranes - Leveraging Multiphysics Modeling, Dimensional Analysis and Machine Learning to Scale up and Optimize Devices and Processes for Decarbonization

We study the separation performance using membrane modules through dimensional analysis (DA). We formulate the main process equations to identify relevant dimensionless numbers inherent in the physics. In particular, we identify that the critical step in the separation process is mass transfer through the selective layer. Remarkably, the dimensionless feed flow (DFfeed) emerges as a crucial factor in describing this process. Not only does DFfeed directly appear in the governing equations, but it also holds a physical significance associated with the time scales for the mass transfer across the feed side and through the selective layer. Regarding the output performance variables, we consider the recovery, stage cut, productivity and purity. In this context, we profit from experimental data and CFD simulations to evaluate the separation performance of the modules when varying the input flowrate, the scale of the module, and the CO2 permeance. These datasets enable us to establish correlations between performance metrics and the dimensionless feed flow (DFfeed). Using simple power functions of DFfeed, we obtain R2 coefficients exceeding 0.99, indicating the accuracy of the correlations built in the present work. In the future, we wish to use DA to understand key transport mechanisms, predict and control module performance, and challenge the universality of these findings by testing various gas separations across different membrane modules beyond our case study.

Pedrozo, Hector A.↗