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A conceptual design of a carbon capture cyber-physical system (CC-CPS) is proposed to provide an opportunity to accelerate co-design of carbon capture technologies in integrated energy systems.
A novel reactive technology is being investigated that electrochemically converts CO2 into valuable chemicals, particularly formic acid. This work focuses on identifying the optimal design and operation of an integrated membrane-based CO2 capture unit with the electrochemical conversion process. In this setup, the CO2 in the flue gas permeates through a CO2-selective membrane and enters an electrolyzer to produce formic acid, creating an integrated reaction module. To refine the chemical product, gas products from the electrolyzer are directed to a pressure swing adsorption unit, while the liquid product undergoes refinement to achieve commercial-grade formic acid using reactive distillation. A membrane CO2 capture model and an electrochemical conversion model have been developed using the IDAES Integrated Platform (Institute for the Design of Advanced Energy System), facilitating rigorous flowsheet modeling and process design and optimization.
Radioiodine is one of the radionuclides of concern when considering reprocessing of used nuclear fuel (UNF). It is expected to be released primarily in the dissolver off-gas (DOG) stream. Sorbents that target I 2 removal from a UNF processing off gas must perform efficiently under elevated temperatures in the presence of water vapor and nitrogen oxide gasses (NOx). Many studies have been conducted that examine the adsorption of iodine species in the presence of NOx gases through reduced silver-exchanged mordenite (Ag 0 Z), a zeolite mineral. This study characterizes the effects of iodine, water vapor, and nitrogen dioxide on the adsorption of I 2 by Ag 0 Z at lower temperatures suitable for comparison with novel Cu- and Bi- bearing sorbents which offer a non-RCRA alternative. When exposed to ‘harsh’ conditions such as I 2 , H 2 O, and NO 2 vapors carried by air, Cu 2 S-polyacrylonitrile (PAN) is more efficient than Ag 0 Z and all other novel sorbents, providing with 11% I capture efficiency. However, under ‘ideal’ conditions in which I 2 is carried by dry air), Ag 0 Z is more efficient than Cu 2 S-PAN and other novel sorbents, providing 74% I capture efficiency. To investigate this result and the overall performance of all sorbents tested, several characterization techniques were employed, including thermal gravimetric analysis, scanning electron microscopy – electron dispersion X-Ray spectroscopy, powder X-ray diffraction, and X-ray photoelectron spectroscopy. These techniques are discussed within this report. This document also includes a design and test plan update from Idaho National Laboratory as the next step in testing the high performing sorbents from thin-bed tests carried out by Oak Ridge National Laboratory.
Carbon Capture, Utilization, and Storage (CCUS) is a critical strategy for reducing CO₂ emissions and mitigating climate change. However, its widespread deployment faces numerous challenges across the capture, transport, and storage phases. These challenges include the technical complexity of predicting subsurface behaviors during CO₂ injection, ensuring long-term storage integrity, optimizing transportation networks, and balancing the economic and environmental trade-offs. Addressing these issues requires an integrated approach combining advanced subsurface modeling with system-level analyses to assess costs, risks, and benefits. This presentation provides an overview of studies conducted by the National Energy Technology Laboratory (NETL) to tackle these challenges. NETL’s efforts encompass cutting-edge research in subsurface fluid behavior machine learning predictions, alongside the development of innovative tools for system optimization and economic evaluation. By bridging technical expertise and strategic analysis, NETL aims to advance the deployment of CCUS technologies to support global decarbonization efforts. Presented at the Carnegie Mellon University CEE IESS Student Seminar October 4, 2024.
Polar Bear™ is a patented technology developed by the Energy & Environmental Research Center (EERC) to capture storage tank vapors and eliminate methane emissions from upstream oil- and gas-producing facilities. Sparked by early commercial investment, the EERC licensed the technology and extended the intellectual property to storage tanks. Polar Bear™ is uniquely engineered and adapted to individual lower-producing facilities where there is otherwise no economic alternative for capturing tank vapors. A high number of small producing oil and gas wells are distributed across the country. The aggregate contributes to a significant volume of emissions. Because of the lack of economy of scale, gas volumes from these facilities are typically not recovered and contribute to methane emissions. Polar Bear™ provides a fit-for-purpose compression solution that addresses cost by reducing complexity with respect to conventional vapor recovery units and eliminating oil changes. Unique to Polar Bear™ is the capability to separate oxygenated gas from storage tank vapors. Storage tanks are designed to “breathe,” allowing gas to enter and escape during internal level and temperature changes. This infiltration of air into the tank headspace imparts undesirable oxygen content with respect to pipeline gathering. Polar Bear™ separates the vapor stream, allowing oxygen-rich gas to be used as fuel on-site while recovering the liquids-rich portion of the gas where oxygen content is minimized. A prototype system was tested to verify process models, evaluate operational performance, and advance the technology readiness level from 5 to 6. Results provide a good match between experimental measurements and process models, indicating the models are useful for future scale-up and field design. Various mixtures of nitrogen and liquefied petroleum gas were tested to understand the mass balance of nitrogen and how it relates to the potential control of oxygen content. Findings indicate that less than 2000 ppm of oxygen is likely to remain in the liquid portion of the gas in field applications. The research and development prepare the technology for field implementation to eliminate routine and fugitive methane emissions from storage tanks.
Securing and protecting critical infrastructure in an increasingly digital world is vital but it is all too often an afterthought. It is especially important that students become aware of internet safety and security at an early age. However, the availability of interactive and educational cybersecurity material targeted toward students is minimal in the United States. Here we show an example of interactive cyber security educational material that an educator can use in their classroom to encourage students to think about the interaction between real-world physical objects, cyber security, and information security. By putting together a “capture-the-flag” exercise, students can see in real time how hackers and cybercriminals exploit vulnerabilities and gain access information. The students try to “capture” the “flag” (i.e., information) in the wind farm by looking for oddities in the code or by taking advantage of weaknesses in everyday protocols. Students can also see how cybersecurity interacts with the power grid through the wind farm project scenario and how a hacker could cause serious problems to a critical infrastructure sector. Our goal for the project is getting students interested in cybersecurity and help them develop an awareness of how important having robust security systems is. We also hope that this project demonstrates the importance of introducing these concepts early and inspires others to create similar projects geared toward students.
This project advanced the development of a novel wind-driven direct air capture (WEDAC) system for removing carbon dioxide (CO 2 ) from the atmosphere. Our research focused on combining passive air contact with electrothermal desorption using specially designed carbon fiber modules, aiming to provide a scalable, low-cost, and energy-efficient alternative to conventional carbon capture systems.
The release of radioiodine, one of several radionuclides of concern when recycling used nuclear fuel (UNF), is an important consideration in the fuel cycle. In this study, two sorbent materials, Cu 0 -polyacrylonitrile (PAN) and Bi 0 -PAN, were tested as solid sorbent candidates for iodine capture. Experiments using a thin bed of sorbent material were exposed to vaporized iodine for over 300 hours (~2 weeks) under varied conditions in a dynamic flow environment. The overall performance was monitored in real-time using thermogravimetric analysis, and the materials were subsequently characterized for surface and bulk analysis using scanning electron microscopy – energy-dispersive spectroscopy (SEM-EDS) and powder x-ray diffraction (pXRD), respectively. Iodine (in the form of I 2 ) is expected to be released primarily in the dissolver off-gas (DOG) stream; therefore, this study demonstrates the effects of elemental iodine (I 2 ), water vapor (H 2 O), and nitrogen dioxide (NO 2 ). When exposed to ‘ideal’ conditions (in which I 2 is carried by dry air), Cu 0 -PAN and Bi 0 -PAN behave differently, with TGA analysis indicating that Cu 0 sorption performance is higher than that of Bi 0 , as evidenced by a larger mass change. Under ‘harsh’ conditions—such as a gaseous feed containing I 2 , H 2 O, and NO 2 vapors carried by air,—iodine capture performance for both Cu 0 - and Bi 0 -PAN are affected. SEM-EDS and pXRD analysis of these materials is discussed herein.
In light water reactors, fuel vendors are investigating the use of dopants to modify the properties of UO 2 pellets, with the goal of improving pellet-cladding mechanical interactions during operation. Dopants are expected to ‘soften’ the pellets; that is, the doped pellets have higher plastic deformation than conventional UO 2 . This leads to a reduction in the severity of mechanical pellet-cladding interactions, helping to reduce the hoop strain on the cladding. By minimizing the strain exerted by the pellet on the cladding, it is anticipated that cladding performance under accident conditions can be enhanced (i.e., lowering the risk of burst during a LOCA). Dopants such as chromium (Cr) promote grain growth during pellet fabrication, leading to larger grains; therefore, understanding the link between chemistry, microstructure and mechanical deformation (enhanced creep rates) behavior of UO 2 is critical to helping operators further substantiate the benefits of doping UO 2 . Historically, the nuclear energy industry has relied on empirical models to make assessments of performance. Compared to empirical models, mechanistic physics-based models provide benefits, such as, fewer data points for validation and better extrapolation where experimental data is scarce or non-existent. In this report, Bayesian inference techniques have been applied to a previously developed lower length-scale-informed diffusional creep model. The objective is to i) infer lower-length-scale parameter distributions from available experiment and then ii) determine the uncertainties in the measurable quantity (in this case creep rates) after propagating the inferred lower length scale parameter uncertainties. The approach requires many evaluations of the model, which becomes computationally insurmountable; therefore, a neural-network model is trained to data obtained by sampling the full model over the most important parameters. This neural-network is then used in the Bayesian inference approach to determine probability distributions in the parameter values that represent the uncertainty in the model given what is known from the experiments (posterior). A significant reduction compared to conservative initial (prior) uncertainties is achieved through inference against the experimental data, demonstrating the efficacy of this approach. Furthermore, by accounting for uncertainties in the experimental conditions and sample non-stoichiometry, it is possible to resolve apparent discrepancies in experimental measurements within a self-consistent grain boundary (Coble) creep model that is sensitive to chemistry. This work has been written up and submitted to Nuclear Technology for a special issue on accelerated fuel qualification (AFQ). This uncertainty quantification (UQ) work not only improves the diffusional model, while accounting for uncertainty, but also establishes a framework which can readily be applied to the mechanistic models of dislocation deformation developed in this study. The most likely values from the Bayesian analysis are incorporated into our UO 2 diffusional creep model and a lower length scale-informed irradiation UO 2 creep mechanistic model to generate a dataset. This dataset has been provided to our INL collaborators for training an artificial neural network surrogate model, which will be implemented in the BISON fuel performance code to assess how the results differ from those currently obtained using a fully empirical model and that of using the nominal (uncalibrated) atomic scale parameters in our mechanistic model. Plastic deformation (creep and glide) in UO 2 is a complex phenomenon, governed by multiple underlying processes such as local defect concentrations, applied stresses, and microstructural characteristics. Consequently, there is a need for a meso-scale model with polycrystalline resolution capable of extrapolating to large grain sizes applicable to doped UO 2 , where data is limited and the model can help bridge the knowledge gap. By integrating atomistic data into the polycrystal LApx code, it becomes possible to predict dislocation climb and glide plasticity that simple analytical models cannot accurately represent. The application of atomic-scale data within LApx demonstrated the importance of climb and glide mechanisms in reproducing high-stress UO 2 behavior. Behaviors such as this are crucial to capture and implement in BISON, as parts of the fuel pellet can reach temperatures where glide can occur before pellet cracking. This model which captures dislocation based mechanisms for UO 2 is then used to stand up the doped model accounting for larger grain sizes. It was found that larger grain sizes can lead to enhanced deformation rates in the glide regime, and therefore can help with the pellet cladding mechanical interaction. Therefore if the fuel pellet reaches conditions (stress/temperature) where glide is active, the enhanced creep rates for larger grains in the glide regime (doped UO 2 ) can help with pellet cladding mechanical interactions. Plastic deformation in UO 2 involves multiple mechanisms, including diffusional creep, dislocation climb, and glide. This milestone contains two parts: (1) UQ of a pre-existing lower length scale informed mechanistic diffusional creep model, and (2) development of a new LApx based model for dislocation-mediated creep mechanisms in UO 2 , with application to large-grain doped UO 2 .
As part of the Next-Gen Profiles (NGP) project, the profile capture and analysis of production electric vehicles undergoing high-power charging (HPC) is conducted over a wide range of conditions to explore variance and performance. Charge session parameters are collected from both the electric vehicle (EV) and electric vehicle supply equipment (EVSE) at a rate of 10Hz and entered into a time-series database for analysis. These charge profiles are captured under nominal and off-nominal conditions, exploring the impact of starting battery state of charge (SOC), battery temperature, vehicle condition, smart charge management (SCM), EVSE limitations and charging adapter usage. Nominal conditions are defined as ideal conditions that should transfer the maximum allowable energy in the minimum possible amount of time. Nominal condition profiles are compared across EVs to characterize state-of-the-art EV charging performance against one another. Off-nominal condition profiles are compared against their nominal condition profile counterparts to highlight the variance across less desirable starting conditions within a single EV.
This project pioneered a groundbreaking reactor design to produce green methanol by harnessing the electrochemical CO 2 reduction reaction (eCO 2 RR), a cornerstone of power-to-fuels technology. The effort integrated three innovative technologies to achieve carbon-neutral methanol production at a target cost of under $\$$800/ton: 1. Direct Air Capture (DAC): Using a cutting-edge sorbent material developed at Holocene, scalable models were developed to integrate captured atmospheric CO₂ into the reactor system. 2. Intermediate-Temperature CO 2 Electrolyzer: Developed by the University of Tennessee (UTK), this electrolyzer utilizes a cost-effective, proton-conducting solid acid electrolyte (CsH 2 PO 4 , CDP) and a mixed-metal oxide cathode. It achieves high faradaic efficiencies (>98%) by effectively suppressing hydrogen evolution at high current densities, converting CO 2 to CO with remarkable selectivity. 3. Catalysis and Reactor Engineering: Oak Ridge National Laboratory (ORNL) contributed world-class expertise in heterogeneous catalysis and reactor design. Their advanced ASPEN modeling drove systems integration and supported techno-economic and life cycle analyses. This effort was further bolstered by partnerships with industry leaders Air Company and Plug Power, who provided critical guidance on scaling, systems engineering, and the integration of water electrolyzers into large-scale operations. During Phase 1, the team focused on modeling and validating a lab-scale reactor demonstrating the feasibility of the integrated approach. Key accomplishments include a 52% increase in current density at 0.8 V while maintaining >98% CO faradaic efficiency, successful 10× scale-up of the electrolyzer with performance within 5% of coin-cell results, best-in-class durability (168-hour test at 0.6 V with 0.14 mA/cm 2 -h degradation), validated TEA confirming the $\$$800/ton methanol target, and completed preliminary LCA showing potential for net-negative GHG emissions under renewable energy scenarios.
The Mu2e experiment at Fermilab will search for the charged lepton flavor violating (CLFV) process of a neutrinoless muon-to-electron conversion in the field of an aluminum nucleus. Reaching the experiment’s target sensitivity requires precise normalization of the physics signal through accurate monitoring of the muon capture rate on the stopping target. For this purpose, the Calorimeter Precise High-Resolution Intensity detector (CAPHRI) has been developed. The detector is composed of four LYSO crystals installed in the upstream disk of the Mu2e calorimeter and read out with the standard calorimeter readout. CAPHRI measures the muon capture rate by detecting the characteristic 1.8~MeV gamma emission line of the $^{27}Al(\mu^−, \nu n \gamma) ^{26}Mg$ nuclear reaction. The fast, precise response enables injection-by-injection monitoring of proton beam intensity fluctuations. We report on the commissioning and performance characterization of CAPHRI. The response of each channel is calibrated at two SiPM overvoltages using both the intrinsic self-emission of the LYSO crystals and cosmic ray signals. In parallel, Monte Carlo simulations are used to evaluate the detector acceptance and the expected signal-to-background ratio under realistic running conditions. Preliminary results show a crystal light yield consistent with expectations and a channel inter-calibration at the 2--4% level. Simulation studies indicate that the detector acceptance and background rejection satisfy the requirements for physics operations, with about 1000 detected events per beam injection at a beam power of 1.5~kW. These results demonstrate that CAPHRI is an effective tool for beam monitoring and signal normalization in Mu2e.
Environmental microbial diversity is often investigated from a molecular perspective using 16S ribosomal RNA (rRNA) gene amplicons and shotgun metagenomics. While amplicon methods are fast, low-cost, and have curated reference databases, they can suffer from amplification bias and are limited in genomic scope. In contrast, shotgun metagenomic methods sample more genomic regions with fewer sequence acquisition biases, but are much more expensive (even with moderate sequencing depth) and computationally challenging. Here, we develop a set of 16S rRNA sequence capture baits that offer a potential middle ground with the advantages from both approaches for investigating microbial communities. These baits cover the diversity of all 16S rRNA sequences available in the Greengenes (v. 13.5) database, with no sequence having <78% sequence identity to at least one bait for all segments of 16S. The use of our baits provide comparable results to 16S amplicon libraries and shotgun metagenomic libraries when assigning taxonomic units from 16S sequences within the metagenomic reads. We demonstrate that 16S rRNA capture baits can be used on a range of microbial samples (i.e., mock communities and rodent fecal samples) to increase the proportion of 16S rRNA sequences (average > 400-fold) and decrease analysis time to obtain consistent community assessments. Furthermore, our study reveals that bioinformatic methods used to analyze sequencing data may have a greater influence on estimates of community composition than library preparation method used, likely due in part to the extent and curation of the reference databases considered. Thus, enriching existing aliquots of shotgun metagenomic libraries and obtaining modest numbers of reads from them offers an efficient orthogonal method for assessment of bacterial community composition.
Molten salt reactor operation will necessitate circulation of a cover gas to remove certain evolved fission products and maintain an inert atmosphere. The cover gas leaving the reactor core is expected to contain both noble and non-noble gases, aerosols, volatile species, tritium, and radionuclides and their daughters. To remove these radioactive gases, it is necessary to develop a robust off-gas system, along with novel sensors to monitor the gas stream and the treatment system performance. In this study, a metal organic framework (MOF) was engineered for the capture of Xe, a major contributor to the off-gas source term. The engineered MOF column was tested with a laser-induced breakdown spectroscopy (LIBS) sensor for noble gas monitoring. The LIBS sensor was used to monitor breakthrough tests with various Xe, Kr, and Ar mixtures to determine the Xe selectivity of the MOF column. This study offers an initial demonstration of the feasibility of monitoring off-gas treatment systems using a LIBS sensor to aid in the development of new capture systems for molten salt reactors.
The design and synthesis of porous carbons for CO 2 adsorption have attracted tremendous interest owing to the ever-soaring concerns regarding climate change and global warming. Herein, for the first time, nitrogen-rich porous carbon was prepared with chemical activation (KOH) of commercial melamine formaldehyde resin (MF) in a single step. It has been shown that the porosity parameters of the as-prepared carbons were successfully tuned by controlling the activating temperature and adjusting the amount of KOH. Thus, as-prepared N-rich porous carbon shows a large surface area of 1658 m 2 /g and a high N content of 16.07 wt%. Benefiting from the unique physical and textural features, the optimal sample depicted a CO 2 uptake of up to 4.95 and 3.30 mmol/g at 0 and 25 °C under 1 bar of pressure. More importantly, as-prepared adsorbents show great CO 2 selectivity over N 2 and outstanding recyclability, which was prominently important for CO 2 capture from the flue gases in practical application. An in-depth analysis illustrated that the synergetic effect of textural properties and surface nitrogen decoration mainly determined the CO 2 capture performance. However, the textural properties of carbons play a more important role than surface functionalities in deciding CO 2 uptake. In view of cost-effective synthesis, outstanding textural activity, and the high adsorption capacity together with good selectivity, this advanced approach becomes valid and convenient in fabricating a unique highly efficient N-rich carbon adsorbent for CO 2 uptake and separation from flue gases.
Reversible oxidative modifications on protein thiols have recently emerged as important mediators of cellular function. Herein we describe the detailed procedure of a quantitative redox proteomics method that utilizes resin-assisted capture (RAC) in combination with tandem mass tag (TMT) isobaric labeling and liquid chromatography-tandem mass spectrometry (LC-MS/MS) to allow multiplexed stochiometric quantification of oxidized protein thiols at the proteome level. The site-specific quantitative information on oxidized cysteine residues provides additional insight into the functional impacts of such modifications. The workflow is adaptable across many sample types including cultured cells (e.g. mammalian, prokaryotic) and whole tissues (e.g. heart, lung, muscle) which are initially lysed/homogenized with free thiols being alkylated to prevent artificial oxidation. The oxidized protein thiols are then reduced and captured by a thiol affinity resin which streamlines and simplifies the workflow steps by allowing the proceeding digestion, labeling, and washing procedures to be performed without additional transfer of proteins/peptides. Finally, labeled peptides are eluted and analyzed by LC-MS/MS to reveal comprehensive stoichiometric changes related to thiol oxidation across the entire proteome. This method greatly improves our understanding of the role of redox dependent regulation under physiological and pathophysiological states related to protein thiol oxidation.
We study dust capture by vortices and its long-term consequences in global two-fluid inviscid disk simulations using a new polar grid code RoSSBi. We perform the longest integrations so far, several hundred disk orbits, at the highest resolution attainable in global disk simulations with dust, namely, 2048 × 4096 grid points. We vary a wide range of dust parameters, most notably the initial dust-to-gas ratio ϵ varies in the range of 10{sup −4}–10{sup −2}. Irrespective of the value of ϵ , we find rapid concentration of the dust inside vortices, reaching dust-to-gas ratios of the order of unity inside the vortex. We present an analytical model that describes this dust capture process very well, finding consistent results for all dust parameters. A vortex streaming instability develops, which invariably causes vortex destruction. After vortex dissipation large-scale dust rings encompassing a disk annulus form in most cases, which sustain very high dust concentration, approaching ratios of the order of unity; they persist as long as the duration of the simulations. They are sustained by a streaming instability, which manifests itself in high-density dust clumps at various scales. When vortices are particularly long-lived, rings do not form but dust clumps inside vortices can survive a long time and would likely undergo collapse by gravitational instability. Rings encompass almost an Earth mass of solid material, while even larger masses of dust do accumulate inside vortices in the earlier stage. We argue that rapid planetesimal formation would occur in the dust clumps inside the vortices as well as in the post-vortex rings.
Abstract This study probes the chemical abundances of the neutron-capture elements cerium and neodymium in the inner Milky Way from an analysis of a sample of ∼2000 stars in the Galactic bulge bar spatially contained within ∣X Gal ∣ < 5 kpc, ∣Y Gal ∣ < 3.5 kpc, and ∣Z Gal ∣ < 1 kpc, and spanning metallicities between −2.0 ≲ [Fe/H] ≲ +0.5. We classify the sample stars into low- or high-[Mg/Fe] populations and find that, in general, values of [Ce/Fe] and [Nd/Fe] increase as the metallicity decreases for the low- and high-[Mg/Fe] populations. Ce abundances show a more complex variation across the metallicity range of our bulge-bar sample when compared to Nd, with ther-process dominating the production of neutron-capture elements in the high-[Mg/Fe] population ([Ce/Nd] < 0.0). We find a spatial chemical dependence of Ce and Nd abundances for our sample of bulge-bar stars, with low- and high-[Mg/Fe] populations displaying a distinct abundance distribution. In the region close to the center of the MW, the low-[Mg/Fe] population is dominated by stars with low [Ce/Fe], [Ce/Mg], [Nd/Mg], [Nd/Fe], and [Ce/Nd] ratios. The low [Ce/Nd] ratio indicates a significant contribution in this central region fromr-process yields for the low-[Mg/Fe] population. The chemical pattern of the most metal-poor stars in our sample suggests an early chemical enrichment of the bulge dominated by yields from core-collapse supernovae andr-process astrophysical sites, such as magnetorotational supernovae.