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Here, atmospheric CO 2 removal through direct air capture (DAC) may help restore CO 2 concentrations to optimal levels, but slow CO 2 uptake rates remain a major impediment. Now, an intensified DAC process has been demonstrated, involving enhanced CO 2 capture rates and reactive K 2 CO 3 crystallization at the interface of ultraconcentrated KOH solutions with air.
During fissionable material processing, all normal and credible abnormal conditions must remain safely subcritical. Nuclear Criticality Safety (NCS) uses a number of methods to determine subcriticality, one of which is the use of neutron transport codes such as MCNP6. In order to create models for use with MCNP6, both the geometry and materials in fissionable material processes must be known, or assumptions must be made and quantified for the impact to bias. One of the systems with a significant amount of bias due to material modeling assumptions is in the area of aqueous plutonium processing. These solutions are typically plutonium nitrate solutions or plutonium chloride solutions, which are modeled as fictitious plutonium metal-water mixtures because little is known about the actual density of the solution and there is no current predictive capability approved for use at Los Alamos National Laboratory (LANL) for modeling them. This research is currently underway to fill the gap and develop an algorithm for use with MCNP6 to model the density of plutonium chloride solutions. The method is to be validated with experimental data for density, and also validated with critical experiments using MCNP6. Note that the Chlorine Worth Study (CWS) was performed in December 2021 to help bridge the gap in chlorine data for critical experiments, and is currently awaiting International Criticality Safety Benchmark Evaluation Project (ICSBEP) review. This study was performed by LANL at the National Criticality Experiments Research Center (NCERC) at the Nevada National Security Site (NNSS). Additional information regarding this experiment may currently be found in LA-UR- 22-29180. Additionally, the Chemistry-Actinide Analytical Chemistry (C-AAC) at LANL has performed a number of solution density measurements for PuCl 3 -HC 1 -H 2 O, allowing for such data be used to create a semi-empirical density via the Pitzer method. The published dataset for the measurements is documented in LA-UR-22-25454. This method has already been tested successfully for aqueous plutonium nitrate solutions in SCALE. Current solution density measurements exist of plutonium concentrations of 0-~142g/L, all at 2M HC1, at temperatures 20-40°C. Additional data was taken for HC1-corrected density values, which essentially mimics the data for a pure PuCl x -water solution. The calculations in this report aim to support the current research by demonstrating the difference in system reactivity for the current modeling method when compared to the new proposed modeling with a density law implementation, which is being written as a Python tool to be used with MCNP6.
In this study, we discuss a hybrid system combining a membrane reactor (MR) and an adsorptive reactor (AR), with the MR's reject stream serving as the AR's feed. We apply this system for the water gas shift (WGS) reaction for H 2 generation and simultaneous CO 2 capture in the context of the Integrated Gas Combined Cycle (IGCC) process for power generation from coal and biomass. This MR-AR system attains a high conversion exceeding equilibrium, produces a pure H 2 product for power generation, and delivers a high-pressure CO 2 stream ready for sequestration. Specifically, in our study we use carbon molecular sieve membranes (CMSMs) and a commercial sour-shift WGS catalyst. Lab experiments were carried-out to determine the membrane characteristics, and the MR performance under IGCC-relevant conditions, i.e., for temperatures up to 250 °C and pressures up to 25 bar, employing a model coal gasifier syngas. The CMSM and the catalyst have displayed robust and stable performance during a long-term run (~750 h of syngas exposure). We evaluated the MR-AR system in multi-cycle runs and it has demonstrated superior performance to that of a conventional packed-bed reactor, producing a high-purity H 2 product directly useable in a turbine for power generation. We conclude from the study, that the CMSM-based MR-AR system is a good candidate technology for environmentally-benign power generation. We are currently constructing a pilot-scale system for field demonstration of the technology.
Natural systems drive the high-energy reactions of photosynthesis with efficient and broadband energy capture. Transition-metal photocatalysts similarly convert light into chemical reactivity, and yet suffer from light-limited operation and require blue-to-UV excitation. In photosynthesis, both light capture and reactivity have been optimized by separation into distinct sites. In this work, inspired by this modular architecture, we synthesized a biohybrid photocatalyst by covalent attachment of the photosynthetic light-harvesting protein R-phycoerythrin (RPE) to the transition-metal photocatalyst tris(2,2'-bipyridine)ruthenium(II) ([Ru(bpy) 3 ] 2+ ). Spectroscopic investigation found that absorbed photoenergy was efficiently funneled from RPE to [Ru(bpy) 3 ] 2+ . The utility of the biohybrid photocatalyst was demonstrated via an increase in yields for a thiol-ene coupling reaction and a cysteinyl-desulfurization reaction, including recovered reactivity at red wavelengths where [Ru(bpy) 3 ] 2+ alone does not absorb.
Sensitivity coefficients calculated with Monte Carlo codes are widely used for nuclear data uncertainty quantification in the modeling and simulation of complex 3D reactor systems. This study systematically compares sensitivity coefficients and associated statistical uncertainties for the multiplication factor and fuel temperature reactivity across multiple Monte Carlo codes (SCALE/KENO, SCALE/Shift, MCNP, and Serpent) using simple models representing light-water reactors and advanced reactor concepts. For multiplication factor sensitivities, statistical uncertainties are generally acceptable, although scattering sensitivities show significantly larger statistical uncertainties than, for example, fission and capture reactions. Fuel temperature reactivity sensitivities show significantly larger statistical uncertainties across all reactions. Elastic scattering sensitivities are the most problematic: all Monte Carlo codes fail to resolve energy-dependent coefficients, and they produce dramatically different energy-collapsed values. Critically, the use of these sensitivity coefficients in nuclear data uncertainty propagation leads to reduced statistical uncertainties in individual uncertainty contributions. This can lead to the masking of unusable sensitivity coefficients and producing misleading uncertainty results. The findings of this study show that new or enhanced methods are needed to improve Monte Carlo elastic scattering sensitivity calculations. Additionally, this study shows the relevance of verifying sensitivity coefficients through direct perturbation calculations for individual nuclide reactions, instead of only for total cross sections as commonly done.
Understanding and mitigating lithium plating remains one of the most pressing challenges in advancing the safety and longevity of lithium-ion batteries (LIBs). Here, we present a novel integrative framework that combines in-operando swelling force measurements with a physics-based electro-chemo-mechanical model to uncover previously inaccessible insights into lithium plating dynamics under mechanical constraints. Unlike existing approaches that focus primarily on electrochemical signatures, our approach captures the coupled mechanical responses of commercial pouch cells during cycling, revealing how mechanical constraints fundamentally alter degradation pathways. We demonstrate that the use of a moderate stacking pressure suppresses lithium plating and enhances lithium stripping. This mechanically driven structural effect, coupled with the electrochemical process, significantly extends the linear aging regime in LIBs. Intriguingly, intermittent capacity recovery events that were observed during the battery cycling suggest dynamic lithium reactivation, a phenomenon rarely captured in real-time. This study pioneers a stress-aware methodology for diagnosing and managing lithium plating, establishing a new paradigm for real-time battery health monitoring. The findings offer transformative implications for the design of durable, high-performance LIB systems, opening new avenues for intelligent control strategies in battery management systems.
The Intentional Forensics (IF) project seeks to design a suite of tagging materials that can be used to unobtrusively “barcode” nuclear fuel. The idea being that, if the fuel leaves institutional controls and is later recovered, the “barcode” can be used to determine the provenance of the fuel. The IF project is investigating several schemes for this “barcode” and taggants with tailored isotopic compositions are once leading concept. Recently 18 O was suggested as a potential taggant [IF2023]. This report assesses the quality of 16,17,18 O evaluations in the ENDF/B-VIII.0 library [ENDF8.0]. In a neutron-rich environment such as a nuclear reactor, we are interested in two main processes – neutron scattering and neutron absorption (or capture). For the typical neutron energies encountered in a reactor, absorption is determined exclusively by the neutron radiative capture cross section (in which a neutron is absorbed, and the residual nucleus emits one or more gamma rays). The capture cross sections are described by and can be completely determined from R-matrix parameters in the ENDF evaluations. Therefore, it is sufficient to consider the quality of the neutron resonance part of these evaluations. Neutron scattering is determined mainly by the elastic scattering cross section which is very similar for all oxygen isotopes and is essentially constant until around 100 keV. The cross section varies from 3-4 barns, depending on the isotope, and 16 O has the largest elastic cross section of all isotopes. Therefore, we expect that significant amounts of 17 O and 18 O could diminish the moderating role of oxygen in fuel. We note that, in traditional power reactor, the hydrogen in the coolant water provides the vast majority of the moderation in the reactor, so the impact of 17 O and 18 O in any taggant would be minimal. At higher energies, neutron resonances start to play a role and the R-matrix parameters determine the cross sections. Fig. 1 shows the mass region near stable oxygen isotopes. As nuclei capture neutrons, they transmute into a different isotope, one unit to the right. In particular, 16 O transmutes to 17 O, 17 O transmutes to 18 O and 18 O transmutes to 19 O. 19 O, being unstable, beta decays in 27 s to 19 F. So, even if the 18 O neutron capture data is good, the fact that it transmutes into 19 F may be problematic and needs investigation. Fig. 2 from [NuDat] shows the thermal neutron capture cross sections for all nuclei in the ENDF/B-VII.1 library [ENDF7.1]. Clearly oxygen thermal capture values are quite small compared to other nuclei. Note, there is no 18 O evaluation in the ENDF/B-VII.1 library. In any event, given that neutron capture events lower the reactor reactivity and potentially induce chemical changes in the fuel, we will focus our attention on the capture part of the neutron resonances.
Abstract A physical understanding of the progression from flow‐driven (quasi‐static) poromechanical deformation to dynamic fault rupture is critical to the resilient operations of several engineering systems. These processes are bridged by a progression from fault reactivation to the spontaneous nucleation of unstable sliding. Toward addressing this challenge, novel automatic time step size control methods are developed to enable accurate and efficient simulation of these dynamics and transitions from the first principles. The controllers combine local models for discretization error and Coulomb failure conditions to automatically adjust the time step size across several orders of magnitude. The methods do not require additional empirical or theoretical input and can resolve the pre‐rupture, interseismic, and seismic periods to the allowed accuracy. The computational results reveal that the proposed methods automatically capture the onset of reactivation and nucleation for homogeneous and heterogeneous fields. Hydrodynamic and structural heterogeneity lead to disparate critical nucleation sizes compared to those predicted by theory. The results highlight its potential in predicting induced seismicity in realistic subsurface engineering systems and at practical scales.
Propanol and butanol isomers have received significant research attention as promising fuel additives or neat biofuels. Robust chemical kinetic models are needed that can provide accurate and efficient predictions of combustion performance across a wide range of engine relevant conditions. Herein, this study seeks to improve the understanding of ignition and combustion behavior of pure C3-C4 linear and iso-alcohols, and their blends with gasoline at engine-relevant conditions. In this work, a kinetic model with improved thermochemistry and reaction kinetics was developed based on recent theoretical calculations of H-atom abstraction and peroxy radical reaction rates. Kinetic model validations are reported, and the current model reproduces the ignition delay times of the C3 and C4 alcohols well. Variations in reactivity over a wide range of temperatures and other operating conditions are also well predicted by the current model. Recent ignition delay time measurements from a rapid compression machine of neat iso-propanol and iso-butanol [Cheng et al., Proc. Combust Inst. (2020)] and blends with a research grade gasoline [Goldsborough et al., Proc. Combust Inst. (2020)] at elevated pressure (20–40 bar) and intermediate temperatures (780–950 K) were used to demonstrate the accuracy of the current kinetic model at conditions relevant to boosted spark-ignition engines. The effects of alcohol blending with gasoline on the autoignition behavior are discussed. The current model captures the suppression of reactivity in the low-temperature and negative-temperature-coefficient (NTC) region when either isopropanol and isobutanol are added to a research grade gasoline. Sensitivity and reaction flux analysis were performed to provide insights into the relevant fuel chemistry of the C3-C4 alcohols.
The formation of defect-free two-dimensional nanocrystal (NC) superstructures remains a challenge as persistent defects hinder charge delocalization and related device performance. Understanding defect formation is an important step toward developing strategies to mitigate their formation. However, specific mechanisms of defect formation are difficult to determine, as superlattice phase transformations that occur during fabrication are quite complex and there are a variety of factors influencing the disorder in the final structure. Here, we use Molecular Dynamics (MD) and electron microscopy in concert to investigate the nucleation of the epitaxial attachment of lead chalcogenide (PbX, where X = S, Se) NC assemblies. We use an updated implementation of an existing reactive force field in an MD framework to investigate how initial orientational (mis)alignment of the constituent building blocks impacts the final structure of the epitaxially connected superlattice. This Simple Molecular Reactive Force Field (SMRFF) captures both short-range covalent forces and long-range electrostatic forces and allows us to follow orientational and translational changes of NCs during superlattice transformation. Our simulations reveal how robust the oriented attachment is with regard to the initial configuration of the NCs, measuring its sensitivity to both in-plane and out-of-plane misorientation. We show that oriented attachment nucleates through the initial formation of dimers, which corroborate experimentally observed structures. We present high-resolution structural analysis of dimers at early stages of the superlattice transformation and rationalize their contribution to the formation of defects in the final superlattice. Collectively, the simulations and experiments presented in this paper provide insights into the nucleation of NC oriented attachment, the impact of the initial configuration of NCs on the structural fidelity of the final epitaxially connected superlattice, and the propensity to form commonly observed defects, such as missing bridges and atomic misalignment in the superlattice due to the formation of dimers. Here, we present potential strategies to mitigate the formation of superlattice defects.
Fine-tuning of protein-protein interactions occurs naturally through coevolution, but this process is difficult to recapitulate in the laboratory. We describe a platform for synthetic protein-protein coevolution that can isolate matched pairs of interacting muteins from complex libraries. This large dataset of coevolved complexes drove a systems-level analysis of molecular recognition between Z domain–affibody pairs spanning a wide range of structures, affinities, cross-reactivities, and orthogonalities, and captured a broad spectrum of coevolutionary networks. Furthermore, we harnessed pretrained protein language models to expand, in silico, the amino acid diversity of our coevolution screen, predicting remodeled interfaces beyond the reach of the experimental library. Further, the integration of these approaches provides a means of simulating protein coevolution and generating protein complexes with diverse molecular recognition properties for biotechnology and synthetic biology.
Milestone 4 is given in the SOPO as being due in quarter 5 (ending 9/11/2020) and is described thus: Milestone 4: Enhanced Simulation Testbed Validated with Experimental Data (UM, Mathieu). Simulation testbed validated with data obtained from experimental testbed, specifically, nonlinear load behaviors and communication network issues observed in the experimental testbed will be modeled in the simulation testbed. The simulation testbed should accurately capture TCL real and reactive power consumption (including during extreme events associated with nonlinear behaviors and communication network failures) to within 5% RMSE error with respect to data obtained from the experimental testbed. The Tasks comprising the work to achieve Milestone 4 are outlined here.
This project will investigate and utilize the basicity and enhanced reactivity of CO2 chemically captured in PNNL’s CO2BOLs carbon capture solvents to perform the first direct carboxylation of the aromatic rings (substituted phenols) in lignin and lignite. This project aims to develop a deep decarbonization approach that can sequester millions of tonnes of CO2 annually by reacting with two large-volume products, lignin, and lignite, to enable their use as composite fillers. The goal is to demonstrate that CO2-containing composites have comparable properties to conventional synthetic materials, meeting international building codes (IBC) while being able to sequester millions of tonnes of CO2 per year.
Milestone 4 is given in the SOPO as being due in quarter 5 (ending 9/11/2020) and is described thus: Milestone 4: Enhanced Simulation Testbed Validated with Experimental Data (UM, Mathieu) Simulation testbed validated with data obtained from experimental testbed, specifically, nonlinear load behaviors and communication network issues observed in the experimental testbed will be modeled in the simulation testbed. The simulation testbed should accurately capture TCL real and reactive power consumption (including during extreme events associated with nonlinear behaviors and communication network failures) to within 5% RMSE error with respect to data obtained from the experimental testbed.
A many times heard mantra of solvent degradation management in amine-based post combustion capture is “keep the solvent clean” to minimize solvent consumption. It is assumed that the amine losses would decrease by the removal of metals, degradation products, and reactive trace components which are captured from the flue gas, like NO 2 (as potentially driving components of the amine degradation besides dissolved O 2 ). However, this theoretical hypothesis – based on results from laboratory experiments typically generated with fresh amines – disregards the complexity of the solvent matrix, interaction of potential metal catalysts with degradation products and oxidizing agents, and specific chemical requirements which must be fulfilled before a degradation mechanism can proceed. Degradation of the solvent CESAR1 (aqueous solution of 3.0 molar 2-amino-2-methylpropan-1-ol (AMP) and 1.5 molar piperazine (PZ)) is investigated in a unique long-time test campaign (testing time up to now 40 months; 24/7 operation) without replacement of the solvent inventory at the capture pilot plant at the lignite-fired power plant in Niederaussem. Three solvent management strategies with different effect mechanisms are investigated and evaluated: (a) removal of only anionic compounds and trace elements (within 75 days solvent inventory treated two times) and anionic as well as cationic compounds and trace elements (114 days, inventory treated four times) from the solvent by ion exchange, (b) adsorptive removal of trace elements from the solvent by active carbon in 35% of the operating time, and (c) removal of >80% NO 2 by flue gas pretreatment with thiosulfate/sulfite solution (dosing for 2,000 h). The results of the testing program clearly show that “solvent cleanliness” is not a well-defined parameter and that results from laboratory tests, tests without fully representative industrial flue gasses, and short-term testing of monoethanolamine cannot be generalized for other solvents and industrial application. Furthermore, these results showcase that specific degradation management considering solvent, capture plant and flue gas quality is reasonable. Overshooting efforts for solvent management are contra-productive and produce unnecessary waste streams, efficiency losses and costs.
Investigations of coupled multiphysics processes in rivers and hyporheic zones have extensively used numerical models. Most existing models use a sequential, one-way coupling between the surface and subsurface domains. Such one-way coupling potentially introduces error. To overcome this, a fully coupled model, hyporheicFoam, was developed using the open-source computational platform OpenFOAM. It captures the coupled flow and multicomponent reactive transport processes within both surface and subsurface domains and across their interface. The coupling between two domains is implemented by mapping conservative flux boundary conditions at the interface through an iterative algorithm. Reactive transport is enabled by specifying a reaction network. To start, we have implemented reaction kinetics following the double Monod-type model with inhibition. The model capability is illustrated through modeling of both conservative and reactive hyporheic flow and transport through dune bedforms. With the novel coupled model, it is now possible to quantify reactions wherein the reactants and products are constantly exchanging between domains and have feedbacks. hyporheicFoam can simulate large, three-dimensional cases owing to the computational flexibility and power offered by the code structure and parallel design of OpenFOAM.
The gapstick is a high explosive (HE) sensitivity test recently developed at Los Alamos. The experiment design was motivated by the traditional gap test and consists of a series of HE and inert pellets in a rate stick configuration. The inert pellets are made increasingly longer so that eventually the attenuated shock is unable to initiate the next HE pellet. While the gapstick is a mechanically simple experiment it poses several challenges for numerical simulation. In particular, accurately modeling the HE initiation and detonation phenomena requires a reactive burn model with sufficient mesh resolution to capture the reaction scales. In this work, the Scaled Uniform Reactive Front (SURF) and Arrhenius Wescott-Stewart-Davis (AWSD) burn models are used for simulations of a PBX 9501 (95 wt% HMX, 5% binder) gapstick. Furthermore, the material model for the inert pellet material, Polyvinylidene Fluoride (PVDF), has a direct influence on the shock propagation and a new equation of state (EOS) calibration for PVDF is developed using available Hugoniot data. Despite some challenges, the simulations are able to reasonably predict shock transit velocities and detonation failure in the gapstick.
In this work, we report on a combined experimental and theoretical study of the wetting and reactivity of water-lean carbon capture solvents on the surface of common column packing materials. Paradoxically, we find that these solvents are equally able to wet hydrophobic and hydrophilic surfaces. The solvents are amphiphilic and are able to adapt to any interfacial environment due to their inherent heterogeneous molecular structure. Ab initio molecular dynamics indicates that these structures enable the formation of a strong adlayer on the surface of hydrophilic surfaces like oxidized steel which promotes solvent decomposition akin to hydrolysis from surface oxides and hydroxides. This decomposition passivates the surface, making it effectively hydrophobic, and the decomposed solvent promotes leaching of the iron into the bulk fluid. This study links the wetting behavior to the observed corrosion of the steels via decomposition of solvent at steel interfaces. The overall affect is strongly dependent on the chemical composition of the solvent, in that amines are stable, whereas imines and alcohols are not. We also observed that plastic packing shows little to no solvent degradation, but an equal degree of wetting.