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Consequence Analysis of Residual Water in a Storage Canister (Preliminary Report)

The objective of this work is to examine the consequences of a residual water on change in condition of cladding and SNF during dry storage. Small amounts of residual water may remain in SNF dry storage canisters after the fuel assemblies are transferred to the canister in the spent fuel pool (SFP), the canister is removed from the SFP and drained or pumped, vacuum dried in several pressure reducing steps, and backfilled with helium. This residual water from incomplete drying could degrade fuel rod cladding, oxidize exposed fuel pellets, and cause cladding failure resulting in SNF fines’ release in canister cavity. If residual water content is high enough, it could corrode internal components inside the canister, e.g., fuel basket, and neutron absorber plates, but CNWRA work indicated that corrosion of the internal component is expected to be negligible even with 55 moles of residual water. Considering this, focus of this work to determine partitioning of residual water towards fuel and cladding oxidation. Residual water will decompose by radiolysis and create reactive oxygen species, which, at sufficient high temperatures will oxidize cladding, and UO 2 exposed by clad breaches. If a significant fraction of UO 2 in a fuel rod is oxidized to U 3 O 8 , swelling of the fuel pellets will rupture the cladding and release fuel particles, contaminating the inside of the canister and complicating retrieval of fuel assemblies, transport and ultimate disposal. The report describes an evaluation of the potential cladding and exposed SNF pellets due to residual water. An integrated quantitative approach was used to estimate the effects. The approach consisted of (i) the evolution of environmental conditions, i.e., temperature and radiation field, in the cask, (ii) the physicochemical processes that affect degradation of the materials within the cask, and (iii) the potential damage states that may result from these conditions and processes. The assessment considers the following set of cask environmental conditions: (i) the quantity of residual water after drying, (ii) internal temperature fields and their intensity decrease over time, and (iii) the strength of the internal radiation field. The quantity of residual water will affect the mass of cladding, SNF, and other components that are degraded by oxidation. Temperature controls the rate of the oxidation reactions, the phase composition of water, and, to a lesser extent, the rate at which water vapor is radiolyzed. The strength of the radiation field controls the radiolysis rate of residual water. These processes, i.e., time evolution of temperature fields and their effects on radiolysis of residual water, fuel and cladding oxidations, were modeled using the integrated approach.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

A novel strategy for producing compost with enhanced biopesticide properties through solid-state fermentation of biowaste and inoculation with Bacillus thuringiensis

Highlights: • Bacillus thuringiensis (Bt) growth on non-sterile OFMSW has been demonstrated. • Bt-enriched compost can be produced from non-sterile biowaste. • Non-sterile OFMSW can be valorized through semi-continuous SSF and Bt inoculation. • The self-sustained inoculation procedure proposed will enhance process economics. - Abstract: In the framework of a circular economy, organic solid wastes are considered to be resources useful for obtaining value-added products. Among other potential uses, biodegradable wastes from agricultural, industrial, and domestic sources are being studied to obtain biopesticides through solid-state fermentation (SSF), mainly at the laboratory scale. The suitability of biowaste (source-selected organic fraction of municipal solid waste) for use as a substrate for Bacillus thuringiensis (Bt) growth under non-sterile conditions in a 10 L SSF reactor was determined in this study. An operational strategy for setting up a semi-continuous process yielding a stabilised organic compost-like material enriched with Bt suitable for use as a soil amendment was developed. Concentrations of 1.7·10{sup 7}–2.2·10{sup 7} and 1.3·10{sup 7}–2.1·10{sup 7} CFU g{sup −1} DM for Bt viable cells and spores, respectively, were obtained in the final material. As the results confirmed, Bt-enriched compost-like material with potential biopesticide properties can be produced from non-sterile biowaste.

09 BIOMASS FUELS↗

CVEVOLVE

CVEvolve is an agentic AI system for autonomous algorithm discovery for scientific data processing. It creates workflows where large language model agents freely set up and configure development environments and evaluation harnesses, develop and improve data processing algorithms with designed exploration-exploitation balancing mechanisms, log history and findings in a structured database, and run holdout testing to ensure algorithm generalizability. CVEvolve offers a zero-code interface and does not require users to provide structured data and evaluation scripts.

Cherukara, MatthewJoseph [Argonne National Laborat↗

Application of Electromagnetic Methods for Reservoir Monitoring with Emphasis on Carbon Capture, Utilization, and Storage

The Controlled-Source ElectroMagnetic (CSEM) method provides crucial information about reservoir fluids and their spatial distribution. Carbon dioxide (CO2) storage, enhanced oil recovery (EOR), geothermal exploration, and lithium exploration are ideal applications for the CSEM method. The versatility of CSEM permits its customization to specific reservoir objectives by selecting the appropriate components of a multi-component system. To effectively tailor the CSEM approach, it is essential to determine whether the primary target reservoir is resistive or conductive. This task is relatively straightforward in CO2 monitoring, where the injected fluid is resistive. However, for scenarios involving brine-saturated (water-wet) or oil-wet (carbon capture, utilization, and storage—CCUS) reservoirs, consideration must also be given to conductive reservoir components. The optimization of data acquisition before the survey involves analyzing target parameters and the sensitivity of multi-component CSEM. This optimization process typically includes on-site noise measurements and 3D anisotropic modeling. Based on our experience, subsequent surveys tend to proceed smoothly, yielding robust measurements that align with scientific objectives. Other critical aspects to be considered are using magnetotelluric (MT) measurements to define the overall background resistivities and integrating real-time quality assurance during data acquisition with 3D modeling. This integration allows the fine tuning of acquisition parameters such as acquisition time and necessary repeats. As a result, data can be examined in real-time to assess subsurface information content while the acquisition is ongoing. Consequently, high-quality data sets are usually obtained for subsequent processing and initial interpretation with minimal user intervention. The implementation of sensitivity analysis during the inversion process plays a pivotal role in ensuring that the acquired data accurately respond to the target reservoirs’ expected depth range. To elucidate these concepts, we present an illustrative example from a CO2 storage site in North Dakota, USA, wherein the long-offset transient electromagnetic method (LOTEM), a variation of the CSEM method, and the MT method were utilized. This example showcases how surface measurements attain appropriately upscaled log-scale sensitivity. Furthermore, the sensitivity of the CSEM and MT methods was examined in other case histories, where the target reservoirs exhibited conductive properties, such as those encountered in enhanced oil recovery (EOR), geothermal, and lithium exploration applications. The same equipment specifications were utilized for CSEM and MT surveys across all case studies.

Barajas-Olalde, César↗

High-Throughput Microstructural Characterization and Process Correlation Using Automated Electron Backscatter Diffraction

The need to optimize the processing conditions of additively manufactured (AM) metals and alloys has driven advances in throughput capabilities for material property measurements such as tensile strength or hardness. High-throughput (HT) characterization of AM metal microstructure has fallen significantly behind the pace of property measurements due to intrinsic bottlenecks associated with the artisan and labor-intensive preparation methods required to produce highly polished surfaces. This inequality in data throughput has led to a reliance on heuristics to connect process to structure or structure to properties for AM structural materials. In this study, we show a transformative approach to achieve laser powder bed fusion (LPBF) printing, HT preparation using dry electropolishing and HT electron backscatter diffraction (EBSD). This approach was used to construct a library of > 600 experimental EBSD sample sets spanning a diverse range of LPBF process conditions for AM Kovar. This vast library is far more expansive in parameter space than most state-of-the-art studies, yet it required only approximately 10 labor hours to acquire. Build geometries, surface preparation methods, and microscopy details, as well as the entire library of >600 EBSD data sets over the two sample design versions, have been shared with intent for the materials community to leverage the data and further advance the approach. Using this library, we investigated process–structure relationships and uncovered an unexpected, strong dependence of microstructure on location within the build, when varied, using otherwise identical laser parameters.

Characterization and Analytical Technique↗

INVESTIGATING THE MASS SEGREGATION PROCESS IN GLOBULAR CLUSTERS WITH BLUE STRAGGLER STARS: THE IMPACT OF DARK REMNANTS

We present the results of a set of N -body simulations aimed at exploring how the process of mass segregation (as traced by the spatial distribution of blue straggler stars, BSSs) is affected by the presence of a population of heavy dark remnants (as neutron stars and black holes (BHs)). To this end, clusters characterized by different initial concentrations and different fractions of dark remnants have been modeled. We find that an increasing fraction of stellar-mass BHs significantly delay the mass segregation of BSSs and the visible stellar component. In order to trace the evolution of BSS segregation, we introduce a new parameter ( A {sup +}), which can be easily measured when the cumulative radial distribution of these stars and a reference population are available. Our simulations show that A {sup +} might also be used as an approximate indicator of the time remaining to the core collapse of the visible component.

79 ASTRONOMY AND ASTROPHYSICS↗

Self-consistent integrated modeling of combined hybrid discharge-laser produced plasma devices for extreme ultraviolet metrology

Discharge- and laser-produced plasma (DLPP) devices are being used as light sources for extreme ultraviolet (EUV) generation. A key challenge for both, DPP and LPP, is achieving sufficient brightness to support the throughput requirements of nanometrology tools. To simulate the environment of a hybrid DLPP device and optimize the EUV output, we have developed an integrated HEIGHTS-DLPP computer simulation package. The package integrates simulation of two evolving plasmas (DPP and LPP) and includes modeling of a set of integrated self-consistent processes: external power source and plasma energy balance, plasma resistive magnetohydrodynamics, plasma heat conduction, detailed radiation transport (RT), and laser absorption and refraction. We simulated and optimized DLPP devices using Xe gas as a target material. We synchronized the external circuit parameters, chamber gas parameters, and laser beam temporal and spatial profiles to achieve maximum EUV output. The full 3D Monte Carlo scheme was integrated for detailed RT and EUV output calculations in Xe using more than 3600 spectral groups. The modeling results are in good agreement with Julich Forschungszentrum experimental data. Theoretical models, developed and integrated into the HEIGHTS package, showed wide capabilities and flexibility. In conclusion, the models and package can be used for optimization of the experimental parameters and settings, investigation of DLPP devices with complex design, analyzing the impact of integrated spatial effects and working timeline arrangement on the final EUV output, and EUV source size, shape, and angular distribution.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

A proteome-wide assessment of the oxidative stress paradigm for metal and metal-oxide nanomaterials in human macrophages

Responsible implementation of engineered nanomaterials (ENMs) into commercial applications is an important societal issue, driving demand for new approaches for rapid and comprehensive evaluation of their bioactivity and safety. An essential part of any research focused on identifying potential hazard of ENMs is the appropriate selection of biological endpoints to evaluate. Herein, we use a tiered strategy employing both targeted biological assays and untargeted quantitative proteomics to elucidate the biological responses of human macrophages across a library of metal/metal oxide ENMs, raised as priority ENMs for investigation by NIEHS’s Nanomaterial Health Implications Research (NHIR) program. Our results show that quantitative cellular proteome profiles readily distinguish ENM types based on their cytotoxic potential according to induction of biological processes and pathways involved in the cellular antioxidant response, TCA cycle, oxidative stress, endoplasmic reticulum stress, and immune responses as major processes impacted. Interestingly, pathway analysis of differentially abundant proteins also revealed new cell processes that were influenced by all ENMs independent of cytotoxic potential. These included pathways previously implicated as cellular adaptive mechanisms to low levels of oxidative stress, including cell adhesion, protein translation and protein targeting pathways. Unsupervised clustering of all data revealed the most striking proteome changes that differentiated ENM classes involved a small subset of proteins involved in the oxidative stess response (HMOX1), protein chaperone functions (HS71B, DNJB1), and autophagy (SQSTM), providing a potential new panel of markers of ENM-induced cell stress. To our knowledge, the results represent the most comprehensive profiling of the biological responses to a library of ENMs conducted using quantitative mass spectrometry-based proteomics. The results provide a basis to identify the patterns of a diverse set of cellular pathways and cell processes impacted by ENM exposure in an important immune cell type, laying the foundation for multivariate, pathway-level structure activity assessments of ENMs in the future.

36 MATERIALS SCIENCE↗

Data Transferability and Collection Consistency in Marine Renewable Energy

Concerns about the potential effects of tidal turbines and wave energy devices on the marine environment continue to slow siting and permitting/consenting of single devices and arrays worldwide. While research studies and early results from post-installation monitoring over the past decade have informed interactions between marine renewable energy (MRE) devices, marine animals, and habitats, regulators still demonstrate considerable reluctance to accelerate the permitting/consenting process for devices and arrays. Furthermore, the MRE industry is struggling with the high costs of baseline assessments and post-installation monitoring, as well as long timelines for obtaining permits, which leads to uncertainty and risk related to project financing. Regulators require assessment and monitoring information to allow them to carry out the necessary analyses to describe, permit/consent, and manage the environmental risks associated with new MRE technologies and new uses of ocean space. One way to reduce risks to the industry and the environment and to allow for acceleration of the permitting/consenting process could be to transfer learning, analyses, and data sets from one country to another, among projects, and across jurisdictional boundaries. In addition, data are collected around early-stage MRE devices using many different methods, instruments, and measurement scales. If similar parameters and accessible methods of data collection were used for baseline assessments and post-installation monitoring around all early-stage devices and MRE developments, the results would be more readily comparable. This comparability would lead to a decrease in scientific uncertainty and support a common understanding of the risk of MRE devices to the marine environment. This in turn would facilitate more efficient and shorter permitting/consenting processes, which would decrease the financial risk for MRE project development. As a means of addressing the concept of transferring data (information, learning, analyses, and data sets) among projects and collecting data consistently, Annex IV has developed a data transferability process that has been socialized with the MRE community, which includes regulators, industry, developers, consultants, and researchers. The data transferability process consists of five components: 1. A Data Transferability Framework brings together data sets in an organized fashion, compares the applicability of each data set for use on other projects, and guides the process of data transfer 2. A Data Collection Consistency Table provides preferred measurement methods or processes, reporting units, and the most common methods of analysis or interpretation and use of data 3. A Monitoring Data Sets Discoverability Matrix allows a practitioner to discover data sets based on the approach presented in the Framework 4. Best Management Practices (BMPs) include five BMPs related to data transferability and collection consistency 5. An Implementation Plan presents an approach for implementing and applying the data transferability process. This report documents the background and development of the data transferability process and associated components and summarizes the next steps needed to successfully implement and apply the data transferability process.

16 TIDAL AND WAVE POWER↗

Pele: An Exascale-Ready Suite of Combustion Codes

High fidelity simulations of realistic combustion devices are extremely demanding computationally because of the requirements to capture complex fuel chemical decomposition, its intricate interactions with turbulent, often multiphase, flows, and the wide separation of space and time scales between the thin flame and the device boundaries. Software required to carry out such computations tends to be extremely complex, particularly when designed to exploit hardware accelerators, and can be difficult to port and maintain. We present Pele, a performance portable suite of tools for the simulation of combustion systems, including codes to evolve reactive multiphase configurations in the low Mach number and compressible flow regimes, along with a set of inter-compatible post processing and in situ analysis tools. The Pele suite of tools is built on top of the AMReX framework for block-structured adaptive mesh refinement, which provides efficient data structures and algorithms that enable the development of a wide variety of efficient mesh and particle based PDE integration schemes. A hierarchical MPI+X parallelism scheme supports CPU-only and accelerated architectures, where X can be OpenMP, CUDA, and HIP based approaches for intra-node computational work distribution. The algorithms and data structures underlying the Pele simulation and analysis tools are highly scalable and performant across a wide variety of high-performance computing platforms, including DOEs newest exascale-class machines, Frontier and Aurora. The simulation and analysis tools are fully documented and freely distributed as open source via GitHub. We present key algorithmic and software challenges, solution strategies, performance and resulting set of capabilities.

AMReX↗

PIMS: Memristor-Based Processing-in-Memory-and-Storage.

Continued progress in computing has augmented the quest for higher performance with a new quest for higher energy efficiency. This has led to the re-emergence of Processing-In-Memory (PIM) ar- chitectures that offer higher density and performance with some boost in energy efficiency. Past PIM work either integrated a standard CPU with a conventional DRAM to improve the CPU- memory link, or used a bit-level processor with Single Instruction Multiple Data (SIMD) control, but neither matched the energy consumption of the memory to the computation. We originally proposed to develop a new architecture derived from PIM that more effectively addressed energy efficiency for high performance scientific, data analytics, and neuromorphic applications. We also originally planned to implement a von Neumann architecture with arithmetic/logic units (ALUs) that matched the power consumption of an advanced storage array to maximize energy efficiency. Implementing this architecture in storage was our original idea, since by augmenting storage (in- stead of memory), the system could address both in-memory computation and applications that accessed larger data sets directly from storage, hence Processing-in-Memory-and-Storage (PIMS). However, as our research matured, we discovered several things that changed our original direc- tion, the most important being that a PIM that implements a standard von Neumann-type archi- tecture results in significant energy efficiency improvement, but only about a O(10) performance improvement. In addition to this, the emergence of new memory technologies moved us to propos- ing a non-von Neumann architecture, called Superstrider, implemented not in storage, but in a new DRAM technology called High Bandwidth Memory (HBM). HBM is a stacked DRAM tech- nology that includes a logic layer where an architecture such as Superstrider could potentially be implemented.

97 MATHEMATICS AND COMPUTING↗

Adsorption Equilibrium, Kinetics, and Column Breakthrough Data for Aqueous Solutions of Binary-Acid and Ternary-Acid Mixtures of Acetic Acid, Butyric Acid, and Lactic Acid on IRN-78 Ion-Exchange Resin at Initial pH Levels of ∼3–7 and at 25–55 °C

This work is part of an effort to develop thermophysical property data and models supporting adsorptive process development for organic acid separation from a dilute aqueous solution of fermentation broth. It presents systematic experimental measurements for aqueous-phase adsorption equilibrium, kinetics, and column breakthrough for three binary-acid aqueous mixtures (acetic acid + lactic acid, butyric acid + lactic acid, and acetic acid + butyric acid) and one ternary-acid aqueous mixture (acetic acid + butyric acid + lactic acid) on Amberlite IRN-78 ion-exchange resin. The equilibrium measurements covered broad ranges of the initial acid concentration (100–400 mmol/L), initial pH (∼3–7), and temperature (25–55 °C). The equilibrium data for the binary-acid and ternary-acid aqueous mixtures indicate selective adsorption of lactic acid at initial pH levels of ∼3 and 4, while acetic acid and butyric acid are selectively adsorbed at initial pH levels of 5, 6, and 7. The subsequent kinetics and column breakthrough experiments were performed at 200 mmol/L with equimolar ratios, an initial pH of 6, and 25 °C. In conclusion, the measurements provide essential data sets for rigorous thermodynamic modeling and process simulation of adsorptive separation processes for organic acid separation from fermentation broth.

Adsorption↗

Detailed Modeling of Physical Processes in Electron Sources for Accelerator Applications

At present, electron sources are essential in a wide range of applications – from common technical use to exploring the nature of matter. Depending on the application requirements, different methods and materials are used to generate electrons. State of-the-art accelerator applications set a number of often-contradicting requirements for electron sources (e.g., high quantum efficiency vs. high spin-polarization, high current density vs. long lifetime, etc). Development of advanced electron sources includes modeling and design of cathodes, material growth, fabrication of cathodes, and cathode testing. The detailed simulation and modeling of physical processes are required in order to shed light on the exact mechanisms of electron emission and to develop new-generation electron sources with optimized efficiency. The purpose of the present work is to study physical processes in prominent electron sources and to develop scientific tools that could be used to predict electron emission from novel nano-structured materials. In particular, the Monte Carlo model has been implemented and used to study photoemission from Negative Electron Affinity (NEA) GaAs widely used to provide spin-polarized electron beams for many accelerator facilities, including Thomas Jefferson National Accelerator Facility. According to our best knowledge, this is the first to date scientific tool to simulate the complete from-excitation-to-emission-into-vacuum photoemission of spin-polarized electrons from NEA GaAs based on the details of material band structure. Moreover, an effective image-processing algorithm has been developed and used to study field emission properties of Nitrogen-incorporated UltraNanoCrystalline Diamond ((N)UNCD) films. The algorithm processes large sets of image micrographs representing field emission sites formed on the anode plate and therefore provides significant information about the field emission area and the current density. The field emission model from convenient semiconductors has been modified and used to study the influence of the space-charge region and the electric-field-dependent electron mobility on the field emission characteristics of (N)UNCD field emitters.

Chubenko, Oksana↗

A High-Fidelity Molecular Model of the Cu(111) Repeating Unit

Dynamic processes at surfaces are central to heterogeneous catalysis, but their atomistic mechanism(s) can prove difficult to elucidate due to variations in material structure and the corresponding impact on reactivity. Moreover, disparities between reaction conditions and those employed for spectroscopic characterization at surfaces can inhibit detailed understanding of catalysis-relevant chemistries. Herein, we substantiate the so-called “cluster-surface” analogy by leveraging a low-valent tricopper architecture ( 1 ) as a model system for small molecule activation at Cu(111). Two reaction classes are explored: the adsorption of carbon monoxide (CO) and the dissociative adsorption of dihydrogen (H 2 ). These processes serve as an ideal testbed to compare the reactivity of a molecular cluster ( 1 ) to that of a heterogeneous surface, as both reactions have empirical data from measurements performed on crystalline Cu(111). Cluster 1 reversibly binds CO. Variable temperature NMR analysis with 13 CO reveals a favorable enthalpy but large negative entropy (−5.1 kcal × mol –1 and −22.9 cal × mol –1 × K –1 , respectively) for CO binding, affording a process that is marginally endergonic at room temperature (ΔG ads (298.15 K) = 1.7 ± 0.5 kcal × mol –1 ). Similarly, analogous to a Cu(111) surface, 1 is shown to oxidatively add (chemisorb) H 2 . Kinetic parameters were determined for this process and the activation enthalpy (8.4 ± 0.5 kcal × mol –1 ) closely mirrors that established for H 2 binding at the Cu(111) facet (6.0 to 12.4 kcal × mol –1 ). Together, these results showcase that a trinuclear cluster can reproduce the small molecule binding and activation energetics of a bulk crystalline surface, setting the stage for studying less-defined surface processes in an atomically precise molecular setting.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Emissions mitigation technology for advanced water-lean solvent-based CO 2 capture processes

This technical final report submitted to DOE/NETL presents all the research activities performed during the entirety of DE-FE0031660 project-Emissions Mitigation Technology for Advanced Water-Lean Solvent-Based CO 2 Capture Processes which spans from October 2018 through March 2022. RTI International has been conducting studies from fundamental and operational aspects to reduce the overall amine emissions from the advanced Water-Lean Solvent (WLS) systems, specifically RTI’s Non-Aqueous Solvent (NAS). This technical final report will highlight the key findings from project which align closely to the project objectives which are: Identify the contribution of vapor loss, entrainment, and aerosols to the overall emissions of water-lean systems; Determine the significance of CO 2 capture system operating parameters to the amine emissions; Develop an emissions model based on critical operating parameters; Evaluate the effectiveness of emissions mitigation devices to reduce the amine emissions to <1 ppm under flue coal-fired flue gas; and, Determine the contribution of the ECTs to the overall CO 2 capture cost. The following are the key findings based on numerous tests using both lab-scale setups and parametric testing performed at RTI’s Bench-scale Gas Absorption System (BsGAS). During the BP1, the aerosol generation system and monitoring equipment were installed at BsGAS to produce and determine the aerosol characteristics during the NAS CO 2 capture process. The aerosol produced by this setup produced aerosols with the peak diameter and concentration of 50 micron and 1.2E10 7 cm -3 , respectively. These particle sizes and concentrations are matched to those observed in the actual coal-fired power plant flue gases and expected to be found at the absorber inlet of the CO 2 capture system. Over 1,300 hours of parametric testing have been conducted to evaluate the impact of the aerosols and operating conditions during the CO 2 capture with NAS on the overall amine emissions in the treated flue gas. At the worse condition tested, the presence of the aerosols in the flue gas could increase the overall emissions by 10X compared to the baseline emissions from NAS’s vapor pressure. CO 2 capture rate was found to be a main factor impacting the overall emissions as well as aerosol size and concentrations in the absorber off-gas. The higher CO 2 capture rate, the higher amine emissions in the treated gas. The temperature difference between the temperature bulge seen in the absorber and the water wash temperature also impacts the particle growth where the larger the temperature difference, the more amine emissions from aerosols in the treated gas. The majority of the aerosols did not grow substantially in the system, and the particle concentrations remained nearly constant between the absorber inlet and wash outlet. Only a small portion of the particles were found to grow significantly. The high efficiency demister with mesh size of 5-10 micron can be installed to remove a portion of the aerosols from the gas stream leaving the water wash. Overall, these results from parametric testing have established the emission baseline and validate our assumption on the need of emission control technologies (ECT) in order to minimize the emissions from the baseline NAS CO 2 capture process. Over 2,000 of BsGAS operating hours was used to investigate a handful of process improvements which led to a selection of the vital few changes that effectively control the amine emissions. These process improvements are lime-coated-filters for absorber gas inlet, advanced demister at the top of the absorber, a second water wash with amine recovery unit were designed, installed, and tested at BsGAS at the end of BP1. The result showed that the NAS CO 2 capture process with these additional emission control devices could lower the amine emission in the treated gas to about 1 ppm using a simulated coal-fire flue gas stream. The main contributor in lowering the amine emission came from the second water wash with amine recovery unit where the amine concentration in the scrubbing water was kept below 2 wt% through a continuous amine removal via an adsorbent bed, resulting in a low amine vapor pressure. The adsorbent bed was regenerated via a direct steam regeneration and the recover amine was returned to the absorber to minimize wastewater and makeup amine. A flue gas generation system was designed and installed during the first half of BP2 to support the emission testing using a real coal-derived flue gas. The system is capable of generating both coal- and natural gas- derived flue gases with the composition of the gaseous species highly resemble to that of the power plant flue gases. The particulates detected in the coal-derived flue gas showed the mean diameter of 1 micron. The CO 2 capture operating was then proceed using the real coal-derived flue gas where the amine emission was controlled to be about 0-3 ppm for the total run time of about 200 hours. Similar testing was conducted with natural gas-derived flue gas and the result showed a highly amine emission of 30 ppm under the total run time of 200 hours. The Principal Component Analysis (PCA) and the Partial Least Squares Projection to Latent Structures (PLS) techniques were applied to the parametric testing data to derive a multivariate statistical model. The model was validated and trained with half of the data collected, and the predictive ability of the model was evaluated using the remaining half of the data. The resulting empirical model was capable of predicting the overall emissions from the NAS process without the ECTs with ±15% accuracy (average absolute deviation, AAD) in BP1. As more emission data were obtained under the real coal-flue gas in the BP2, the model incorporated these new set of data to reflect the final process configuration, operating parameters, and amine emission. This results in the updated empirical model predicting the amine emission from the NAS CO 2 capture process with 84% goodness-of-fit (R 2 ), 85% predictability (Q 2 ), and 15% AAD. The study evaluates the use of RTI’s Non-Aqueous Solvent technology for 90% CO 2 capture from a net 650 MWe pulverized coal power plant, downstream of the flue-gas desulfurization unit. The captured CO 2 has a purity of > 95% CO 2 , and is dried, compressed to 15.3 MPa (2,215 psia), ready for sequestration. The analysis uses Case B12B from the DOE Baseline study on Bituminous Coal, Revision 4 where the Cansolv CO 2 capture plant is replaced by the RTI CO 2 Capture plant. The CO 2 capture plant has been sized to capture >90% CO 2 from flue gas derived from a net 650 MWe supercritical pulverized coal power plant. The CO 2 capture plant is equipped with emission control technologies that limits the amine emissions to < 1 ppm. Two different cases were evaluated for the technoeconomic study. The key difference between the two cases is the regenerator pressure. In Case 1, the regenerator operates at 0.195 MPa (28.3 psia), whereas in Case 2, the regenerator pressure is 0.44 MPa (64 psia) thus removing the need for the first stage of compression of the eight-stage compression train. Results from the TEA are compared against the DOE reference cases for SCPC plant with and without CO 2 Capture (Case B12A and Case B12B of the DOE Baseline study, respectively). Case 2 with CO 2 regeneration at higher pressure results in the lower cost of CO 2 capture. The total capital cost of the capture process has been estimated using 2018 dollars in Aspen Process Economic Analyzer and was estimated to be $579 MM. The capture plant operation leads to a total parasitic power loss rate of 96 MWe, resulting in a decrease in pulverized coal power plant efficiency of 7.8% points. The resulting cost of electric power increases from 64.4 mills/kWh, for no capture, to 97.5 mills/kWh, with 90% capture, an increase of 51% in the COE. The cost of capturing 90% CO 2 was estimated to be $38.2/tonne-CO 2 , and meets the DOE target of $40/t-CO 2 . Emission control technologies (ECT) investigated in this project includes a second water wash with use of activated carbon beds for removal of amine from the wash water prior to recirculation in the water wash. These ECT allow operation of the CO 2 capture plant with < 1 ppm amine emissions with the treated flue gas and contributes to $2.4/t-CO 2 captured. Amine emissions derived from thermal and oxidative degradations were investigated under this project along with the emissions derived from aerosols for the NAS system. The thermally degraded of the lean NAS showed less than 4% decreased of the original total amine content in the NAS at 150 °C while the result obtained at 120 °C showed no drop in total amine content, suggesting that thermal degradation of the NAS is minimal. These results also suggested that the thermally degraded species are not likely formed and contributed to the emissions due to the low regeneration temperature of the NAS at 90-105 °C. The oxidative degradation, on the other hand, could become problematic as some of these oxidative degraded species were observed during the NAS-5 testing at National Carbon Capture Center (NCCC) and SINTEF in our previous project. The rapid screening of selected inhibitors suggested that oxidative degradation of NAS can be suppressed using thiol containing compounds in amounts of at least 1 mol%. The detailed mechanistic degradation pathway was conceived for a specific amine used in NAS formulation during BP2. he reduction of the nitrosamines caused by the NO x present in the flue gas was also examined. The study suggested that the thermo-chemical treatment of the NAS solvent would be a more effective and economically viable compared to removing NO x at the DCC.

01 COAL, LIGNITE, AND PEAT↗

MAPPRAISER: A massively parallel map-making framework for multi-kilo pixel CMB experiments

Forthcoming cosmic microwave background (CMB) polarized anisotropy experiments have the potential to revolutionize our understanding of the Universe and fundamental physics. The sought-after, tale-telling signatures will be however distributed over voluminous data sets which these experiments will collect. These data sets will need to be efficiently processed and unwanted contributions due to astrophysical, environmental, and instrumental effects characterized and efficiently mitigated in order to uncover the signatures. This poses a significant challenge to data analysis methods, techniques, and software tools which will not only have to be able to cope with huge volumes of data but to do so with unprecedented precision driven by the demanding science goals posed for the new experiments. A keystone of efficient CMB data analysis is solvers of very large linear systems of equations. Such systems appear in very diverse contexts throughout CMB data analysis pipelines, however they typically display similar algebraic structures and can therefore be solved using similar numerical techniques. Linear systems arising in the so-called map-making problem are one of the most prominent and common ones. In this work we present a massively parallel, flexible and extensible framework, comprised of a numerical library, MIDAPACK, and a high level code, MAPPRAISER, which provide tools for solving efficiently such systems. Here, the framework implements iterative solvers based on conjugate gradient techniques: enlarged and preconditioned using different preconditioners. We demonstrate the framework on simulated examples reflecting basic characteristics of the forthcoming data sets issued by ground-based and satellite-borne instruments, executing it on as many as 16,384 compute cores. The software is developed as an open source project freely available to the community at: https://github.com/B3Dcmb/midapack.

79 ASTRONOMY AND ASTROPHYSICS↗

Perspectives on Polyolefin Catalysis in Microfluidics for High-Throughput Screening: A Minireview

Polyolefins are the largest produced plastics in the world which traditionally employ continuous stirred tank reactors and fluidized bed reactors for commercial production. The operating condition, reaction kinetics, and molecular interactions inside the reactor strongly affect the polyolefin properties, which require stringent process control in conventional procedures. Understanding the catalytic pathway, behavior of polymer particles and effect of reactor conditions are essential for designing specific polymer properties, namely the molecular weight, chain length, polydispersity, etc. Microfluidics can play a significant role in designing polymers tailored to the user needs. Smaller channel dimensions help obtain uniform reaction conditions over the length of the microfluidic reactor in a controlled environment. With real-time monitoring techniques in microfluidics, even single particle growth of polymer can be studied to understand the parameters affecting the polymer properties. High throughput microfluidics can help catalyst screening in a short duration with less consumption of reagents generating less waste. When supplemented with efficient machine learning algorithms, automated high throughput microfluidics has the potential to rapidly optimize the process and develop new knowledge even with a limited data set. When trained on data sets generated using microfluidic experiments that are designed efficiently with working knowledge of the process, machine learning algorithms can provide the relationship between the multivariable parameters space and polymer properties, which is not possible with the traditional statistical methods and interpolation techniques. Here, the rise in the utilization of microfluidics, with the advancement of machine learning algorithms, for polyolefin catalysis, highlights the importance of microfluidics for catalyst discovery, parameter optimization, and understanding reaction pathway for producing polymers with specific properties for specialized applications.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Trends and Drivers of Terrestrial Sources and Sinks of Carbon Dioxide: An Overview of the TRENDY Project

The terrestrial biosphere plays a major role in the global carbon cycle, and there is a recognized need for regularly updated estimates of land-atmosphere exchange at regional and global scales. An international ensemble of Dynamic Global Vegetation Models (DGVMs), known as the “Trends and drivers of the regional scale terrestrial sources and sinks of carbon dioxide” (TRENDY) project, quantifies land biophysical exchange processes and biogeochemistry cycles in support of the annual Global Carbon Budget assessments and the REgional Carbon Cycle Assessment and Processes, phase 2 project. DGVMs use a common protocol and set of driving data sets. A set of factorial simulations allows attribution of spatio-temporal changes in land surface processes to three primary global change drivers: changes in atmospheric CO 2 , climate change and variability, and Land Use and Land Cover Changes (LULCC). Here, we describe the TRENDY project, benchmark DGVM performance using remote-sensing and other observational data, and present results for the contemporary period. Simulation results show a large global carbon sink in natural vegetation over 2012–2021, attributed to the CO 2 fertilization effect (3.8 ± 0.8 PgC/yr) and climate (–0.58 ± 0.54 PgC/yr). Forests and semi-arid ecosystems contribute approximately equally to the mean and trend in the natural land sink, and semi-arid ecosystems continue to dominate interannual variability. The natural sink is offset by net emissions from LULCC (–1.6 ± 0.5 PgC/yr), with a net land sink of 1.7 ± 0.6 PgC/yr. Despite the largest gross fluxes being in the tropics, the largest net land-atmosphere exchange is simulated in the extratropical regions.

58 GEOSCIENCES↗