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At least 1,351 records · Page 75

Towards predictive control of reversible nanoparticle assembly with solid-binding proteins

Although a broad range of ligand-functionalized nanoparticles and physico-chemical triggers have been exploited to create stimuli-responsive colloidal systems, little attention has been paid to the reversible assembly of unmodified nanoparticles with non-covalently bound proteins. Previously, we reported that a derivative of green fluorescent protein engineered with oppositely located silica-binding peptides mediates the repeated assembly and disassembly of 10-nm silica nanoparticles when pH is toggled between 7.5 and 8.5. We captured the subtle interplay between interparticle electrostatic repulsion and their protein-mediated short-range attraction with a multiscale model energetically benchmarked to collective system behavior captured by scattering experiments. Here, in this work, we show that both solution conditions (pH and ionic strength) and protein engineering (sequence and position of engineered silica-binding peptides) provide pathways for reversible control over growth and fragmentation, leading to clusters ranging in size from 25 nm protein-coated particles to micrometer-size aggregate. We further find that the higher electrolyte environment associated with successive cycles of base addition eventually eliminates reversibility. Our model accurately predicts these multiple length scales phenomena. The underpinning concepts provide design principles for the dynamic control of other protein- and particle-based nanocomposites.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Blowing Snow at McMurdo Station, Antarctica During the AWARE Field Campaign: Surface and Ceilometer Observations

Blowing snow (BLSN) is an impactful process in cold climates, affecting regional thermodynamics, radiation properties, and the surface mass balance of snow. Though it has significant climatic impacts, the process is still poorly understood and not widely included in weather and climate models. In 2016, the AWARE Field Campaign saw the deployment of a large suite of in situ and remote sensing instruments to McMurdo Station, Antarctica allowing for investigation of BLSN. A ceilometer–based BLSN detection algorithm used elsewhere in Antarctica is applied to data from AWARE, yielding a BLSN frequency of 14.1% compared to 8.2% as detected by human observers. To increase confidence in detections, the algorithm is updated to have shorter temporal averaging and to include a variety of meteorological thresholds to limit false detections due to fog. Efforts to incorporate a laser disdrometer into the algorithm were unsuccessful. An unphysical dependence of particle size distributions on wind speed is found suggesting observations are problematic at wind speeds greater than 10 m s –1 . The revised algorithm detected a BLSN frequency of 7.4%, increasing agreement with human observations and confidence that the process is actively occurring at the observation site. Furthermore, these observations are put into context of a climatology of human observations of BLSN at McMurdo station from 2002–2018. An annual average of 8.0%–14.0% is estimated, with a total annual range of 3.4%–21.3%. Regardless of whether BLSN is observed by humans or instrument, the majority of cases at this location are associated with ongoing precipitation.

54 ENVIRONMENTAL SCIENCES↗

Resistive wall mode stability and resonant field amplification in MAST high beta plasma

The n=1 (n is the toroidal mode number) resistive wall mode (RWM) instability and the resonant field amplification (RFA) due to a stable RWM response are numerically investigated for a MAST high-pressure plasma scenario, utilizing the MARS-F (Liu Y.Q. et al 2000 Phys. Plasmas 7 3681) and MARS-K (Liu Y.Q. et al 2008 Phys. Plasmas 15 112503) codes, for the purpose of understanding the potential RWM behavior in MAST-U plasmas. Ideal kink stability analysis identifies a target plasma, with parameters similar to that of the reference equilibrium reconstructed from a MAST high-pressure discharge, that accesses the RWM regime. The unstable n=1 RWM for the target equilibrium is subject to strong damping by the plasma toroidal flow and/or the drift kinetic effects from thermal particles. As a result, the mode is found to be stable under the experimental flow conditions, or even without flow stabilization if drift kinetic stabilization is included. The stability prediction is robust against variation of the assumed resistive wall minor radius. Active magneto-hydrodynamic (MHD) spectroscopy modeling, using the magnetic coils designed for controlling the edge localized modes (ELMs) in MAST-U as the antenna, shows strong resonant field amplification due to a stable RWM response in the target plasma. Maximal amplification, of 6-7 times larger than the applied vacuum field within the plasma, is obtained assuming a coil phasing of 120-180 degrees between the upper and lower rows of the ELM control coils. The MHD-kinetic hybrid model predicts generally higher RFA than the fluid model, in particular near the low-field and high-field sides of the plasma boundary surface. Furthermore, the MARS-F/K modeling thus shows that the RWM in MAST-U is subject to strong flow and kinetic stabilization, but can nevertheless be detected by active MHD spectroscopy.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Transport and confinement physics: Chapter 2 of the special issue: on the path to tokamak burning plasma operation

Progress in physics understanding and theoretical model development of plasma transport and confinement (TC) in the ITPA TC Topical Group since the publication of the ITER Physics Basis (IPB) document (Doyle et al 2007 Nucl. Fusion 47 S18) was summarized focusing on the contributions to ITER and burning plasma prediction and control. This paper provides a general and streamlined overview on the advances that were mainly led by the ITPA TC joint experiments and joint activities for the last 15 years (see JEX/JA table in appendix). This paper starts with the scientific strategy and scope of the ITPA TC Topical group and overall picture of the major progress, followed by the progress of each research field: particle transport, impurity transport, ion and electron thermal turbulent transport, momentum transport, impact of 3D magnetic fields on transport, confinement mode transitions, global confinement, and reduced transport modeling. Cross references with other Topical Groups are given in order to highlight overlapped topics, such as the 3D effect on the plasma transport in the edge and L-H transition physics. The increasing overlap between the topical groups is a reflection of the progress on integrating the known physics into comprehensive models that are better and better able to reproduce the plasma transport. In recent years, such integration has become increasingly prevalent when considering transport from the SOL, through the edge pedestal, and into the plasma core. In the near future, increased collaboration also with the magneto-hydrodynamic and energetic particles community will be important as we approach burning plasma conditions in next-step fusion devices. A summary of remaining challenges and next steps for each research field is given in the Summary section.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Active Control of Alfvén Eigenmodes by Externally Applied 3D Magnetic Perturbations

The suppression and excitation of Alfvén eigenmodes have been experimentally obtained, for the first time, by means of externally applied 3D perturbative fields with different spatial spectra in a tokamak plasma. The applied perturbation causes an internal fast-ion redistribution that modifies the phase-space gradients responsible for driving the modes, determining, ultimately their existence. Hybrid kinetic-magnetohydrodynamic simulations reveal an edge resonant transport layer activated by the 3D perturbative field as the responsible mechanism for the fast-ion redistribution. Finally, the results presented here may help to control fast-ion driven Alfvénic instabilities in future burning plasmas with a significant fusion born alpha particle population.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Simulations of short-term exposure to NO 2 and PM 2.5 to inform capture efficiency standards

The California building code requires all new or renovated residential dwelling units to have kitchen exhaust ventilation to manage air pollutants and moisture generated during cooking. Current performance requirements are specified as a minimum airflow and maximum sound level. This report presents an analysis to support consideration of adding a capture efficiency requirement to the code. The analysis uses a physics-based simulation model to calculate air pollutant concentrations in homes that result from cooking and the inflow of outdoor air, mediated by loss and removal process including deposition, dwelling unit ventilation, and the use of a range hood with varying levels of capture efficiency. Calculated pollutant concentrations are compared to relevant, health-based guidelines. The analysis considers the highest 1-hour concentration of nitrogen dioxide (NO 2 ), which is a product of natural gas combustion and the highest 24-hour concentrations of fine particulate matter (PM 2.5 ) which is emitted in substantial quantities from frying, broiling and grilling among other cooking activities. For NO 2 , the analysis considers cooking of a dinner for 3-4 persons consisting of pasta, meat sauce, a par-boiled vegetable, and baked garlic bread. For PM 2.5 , the analysis considers a day in which breakfast emitted particles at the 80th percentile and lunch and dinner entailed particle emissions at the 50th percentile of cooking emission events reported in the literature. Model simulations were performed to determine the level of range hood capture efficiency that will allow these cooking scenarios to occur in the vast majority (>99%) of new homes being built in California while maintaining pollutant concentrations below the health-based guidelines, if the range hood is used throughout cooking. All homes were assumed to have dwelling unit ventilation at the rate required in the building code. Simulation model input parameters were specified using a Monte Carlo approach to represent a range of housing characteristics, outdoor conditions, and indoor pollutant dynamics. Simulation results suggest that requiring a minimum capture efficiency of at least 70% is needed to avoid unacceptably high NO 2 (1-h average concentration of 100 ppb or higher) and at least 60% to avoid unacceptably high PM 2.5 (24-h average of 25 μg/m³ or higher). These results were driven by multi-family homes, which have a smaller volume of air to dilute any pollutants not captured and removed at the cooking area, resulting in higher concentrations.

54 ENVIRONMENTAL SCIENCES↗

Fast Dissipation of Colliding Alfvén Waves in a Magnetically Dominated Plasma

Magnetic energy around compact objects often dominates over plasma rest mass, and its dissipation can power the object's luminosity. We describe a dissipation mechanism that works faster than magnetic reconnection. The mechanism involves two strong Alfvén waves with anti-aligned magnetic fields B 1 and B 2 that propagate in opposite directions along the background magnetic field B 0 and collide. The collision forms a thin current sheet perpendicular to B 0 , which absorbs the incoming waves. The current sheet is sustained by an electric field E breaking the magnetohydrodynamic condition E < B and accelerating particles to high energies. We demonstrate this mechanism with kinetic plasma simulations using a simple setup of two symmetric plane waves with amplitude A = B 1 / B 0 = B 2 /B 0 propagating in a uniform B 0 . The mechanism is activated when A > 1/2. It dissipates a large fraction of the wave energy, † = (2A - 1)/A 2 , reaching 100% when A = 1. The plane geometry allows one to see the dissipation process in a one-dimensional simulation. We also perform two-dimensional simulations, enabling spontaneous breaking of the plane symmetry by the tearing instability of the current sheet. At moderate A of main interest, the tearing instability is suppressed. Dissipation transitions to normal, slower, magnetic reconnection at A $\gg$ 1. The fast dissipation described in this paper may occur in various objects with perturbed magnetic fields, including magnetars, jets from accreting black holes, and pulsar wind nebulae.

79 ASTRONOMY AND ASTROPHYSICS↗

Gamma-Ray Emission from Galaxies Hosting Molecular Outflows

Many star-forming galaxies and those hosting active galactic nuclei show evidence of massive outflows of material in a variety of phases including ionized, neutral atomic, and molecular. Molecular outflows in particular have been the focus of recent interest as they may be responsible for removing gas from the galaxy, thereby suppressing star formation. As material is ejected from the cores of galaxies, interactions of the outflowing material with the interstellar medium can accelerate cosmic rays and produce high-energy gamma rays. In this work, we search for gamma-ray emission from a sample of local galaxies known to host molecular outflows using data collected by the Fermi Large Area Telescope. We employ a stacking technique in order to search for and characterize the average gamma-ray emission properties of the sample. Gamma-ray emission is detected from the galaxies in our sample at the 4.4σ level with a power-law photon index of Γ ≈ 2 in the 1–800 GeV energy range. The emission is found to correlate with tracers of star formation activity, namely the 8–1000 μm infrared luminosity. We also find that the observed signal can be predominantly attributed to H II galaxies hosting energy-driven outflows. While we do not find evidence suggesting that the outflows are accelerating charged particles directly, galaxies with molecular outflows may produce more gamma rays than galaxies without outflows. In particular, the set consisting of gamma-ray-detected galaxies with molecular outflows are nearly perfect calorimeters and may be future targets for searches of high-energy neutrinos.

79 ASTRONOMY AND ASTROPHYSICS↗

Analysis of MINERvA tunings of GENIE based on Hadron Multiplicity using Machine Learning

Scientists with the MINERvA neutrino interaction experiment have long studied distributions of hadrons (protons and pions) to improve the models for these reactions. Until now, most work has relied on easy to find, energetic, and well tracked hadrons. But in order to take full advantage of MINERνA data it is necessary to develop an efficient enough tool to recognize hadron tracks with lower energy, more transverse angle and more challenging patterns of activity. In this analysis, a Machine Learning tool based on Convolutional Neural Network and Transfer Learning has been developed to tackle that issue. It is found to be extremely capable of recognizing hadron activities especially when there are few and not very energetic hadrons, the accuracy is 76%. But it is also found that this network is very reluctant to classify too many hadrons. The classification is also affected by the presence of other particles in the event such photons, hadrons below a threshold or neutrons. This network is used to compare hadron multiplicity of data to the MC models and distinguish between different MC tunes. Some MINERνA tunes are explored in this analysis, but none of them described the data very well, especially not for all different hadrons multiplicities at once. Four combinations of those tunes were more successful, but none of them could be recognized as the best one. Nevertheless, this analysis develops an ML network that sets the basis of further exploration of hadron multiplicity as a tool to analyze MC tunes at MINERνA and beyond.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Evaluation of HPK n + - p planar pixel sensors for the CMS Phase-2 upgrade

To cope with the challenging environment of the planned high luminosity upgrade of the Large Hadron Collider (HL-LHC), scheduled to start operation in 2029, CMS will replace its entire tracking system. The requirements for the tracker are largely determined by the long operation time of 10 years with an instantaneous peak luminosity of up to 7.5 × 10 34 cm –2 s –1 in the ultimate performance scenario. Depending on the radial distance from the interaction point, the silicon sensors will receive a particle fluence corresponding to a non-ionizing energy loss of up to $\Phi_{\text {eq}}$ = 3.5 × 10 16 cm –2 . Here this paper focuses on planar pixel sensor design and qualification up to a fluence of $\Phi_{\text {eq}}$ = 1.4 × 10 16 cm –2 . For the development of appropriate planar pixel sensors an R&D program was initiated, which includes $n^+ -p$ sensors on 150 mm (6”) wafers with an active thickness of 150 μm with pixel sizes of 100 × 25 μm 2 and 50 × 50 μm 2 manufactured by Hamamatsu. Single chip modules with ROC4Sens and RD53A readout chips were made. Irradiation with protons and neutrons, as well was an extensive test beam campaign at DESY were carried out. This paper presents the investigation of various assemblies mainly with ROC4Sens readout chips. It demonstrates that multiple designs fulfill the requirements in terms of breakdown voltage, leakage current and efficiency. The single point resolution for 50 × 50 μm 2 pixels is measured as 4.0 μm for non-irradiated samples, and 6.3 μm after irradiation to $\Phi_{\text {eq}}$ = 7.2 × 10 15 cm –2 .

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Letter of Intent for a Drell-Yan experiment with a polarized proton target

It is well known that the proton is a spin-1/2 particle, but how the constituents (quarks and gluons) assemble to this quantized spin is still a mystery. There is a worldwide effort to map out the individual contributions to the proton spin. It is established that the quark spins contribute around 30%, while the gluon intrinsic angular momentum is still under active investigation at the Relativistic Heavy Ion Collider. Fully resolving the proton spin puzzle requires information on the orbital angular momentum (OAM) of both quarks and gluons. Recent studies have shown that the so-called transverse momentum dependent parton distribution functions (TMDs) can inform us about the OAM of the partons.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Unsupervised learning for identifying events in active target experiments

This article presents novel applications of unsupervised machine learning methods to the problem of event separation in an active target detector, the Active-Target Time Projection Chamber (AT-TPC). The overarching goal is to group similar events in the early stages of the data analysis, thereby improving efficiency by limiting the computationally expensive processing of unnecessary events. The application of unsupervised clustering algorithms to the analysis of two-dimensional projections of particle tracks from a resonant proton scattering experiment on 46 Ar is introduced. We explore the performance of autoencoder neural networks and a pre-trained VGG16 Simonyan and Zisserman (2015) convolutional neural network. We study clustering performance on both data from a simulated 46 Ar experiment, and real events from the AT-TPC detector. We find that a -means algorithm applied to simulated data in the VGG16 latent space forms almost perfect clusters. Additionally, the VGG16+-means approach finds high purity clusters of proton events for real experimental data. Here, we also explore the application of clustering the latent space of autoencoder neural networks for event separation. While these networks show strong performance, they suffer from high variability in their results.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Permeability-Engineered Compartmentalization Enables In Vitro Reconstitution of Sustained Synthetic Biology Systems

In nature, biological compartments such as cells rely on dynamically controlled permeability for matter exchange and complex cellular activities. Likewise, the ability to engineer compartment permeability is crucial for in vitro systems to gain sustainability, robustness, and complexity. However, rendering in vitro compartments such a capability is challenging. Here, a facile strategy is presented to build permeability-configurable compartments, and marked advantages of such compartmentalization are shown in reconstituting sustained synthetic biology systems in vitro. Through microfluidics, the strategy produces micrometer-sized layered microgels whose shell layer serves as a sieving structure for biomolecules and particles. In this configuration, the transport of DNAs, proteins, and bacteriophages across the compartments can be controlled an guided by a physical model. Through permeability engineering, a compartmentalized cell-free protein synthesis system sustains multicycle protein production; ≈100 000 compartments are repeatedly used in a five-cycle synthesis, featuring a yield of 2.2 mg mL -1 . Further, the engineered bacteria-enclosing compartments possess near-perfect phage resistance and enhanced environmental fitness. In a complex river silt environment, compartmentalized whole-cell biosensors show maintained activity throughout the 32 h pollutant monitoring. It is anticipated that permeability-engineered compartmentalization should pave the way for practical synthetic biology applications such as green bioproduction, environmental sensing, and bacteria-based therapeutics.

59 BASIC BIOLOGICAL SCIENCES↗

Impact of Particle Size on the Vapor-Phase Oxidative Coupling of Methanol and Dimethylamine over Palladium–Gold Nanoparticles

Oxidative coupling of methanol and dimethylamine in the presence of O 2 in the vapor phase over dilute Pd in Au bimetallic catalysts occurs via the dissociation of O 2 on Pd and selective oxidation of methanol on Au. Here, we synthesize a series of silica-supported PdAu alloy nanoparticle catalysts of varied Pd:Au ratios with ~5 nm particle diameter and show that these catalysts have increased selectivity to dimethylformamide across all Pd:Au ratios (~95%), distinct from observations over larger PdAu nanoparticles (~15–25 nm diameter) of similar Pd:Au ratios. Small monometallic Pd particles are more selective than large monometallic Pd particles, and small Au nanoparticles are reactive and selective for oxidative coupling (while large Au nanoparticles are inactive). Rates per surface metal atom were similar over PdAu nanoparticles of all sizes and increased monotonically with increasing Pd content for the small nanoparticles. Further, apparent reaction kinetics demonstrate distinct apparent methanol reaction order and apparent activation energy relative to those reported over larger nanoparticles of similar Pd:Au ratios. Unlike larger PdAu nanoparticles, the rate of dimethylformamide formation is not promoted by cofed water over small PdAu nanoparticles. The results of the kinetic studies are used to propose a series of elementary steps, derive a plausible rate expression, and regress rate and equilibrium constants. These results suggest high coverages of surface methoxy species and low coverages of adsorbates derived from dimethylamine. Taken together, these results demonstrate the sensitivity of the rates, selectivities, and kinetics of oxidative coupling reactions to the size of bimetallic nanoparticles.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Stability and Control of Burning Tokamak Plasmas with Resistive Walls (Final Report)

This research has focused on quantitative prediction of the stability, control, and equilibrium state evolution in toroidal burning plasmas. The stability of long pulse burning plasmas is highly sensitive to the physics of resonant layers in the plasma, sources of momentum and flow, kinetic effects of energetic particles, and boundary conditions at the wall, including feedback control and error fields. In ITER in particular, the low toroidal flow equilibrium state, sustained primarily by energetic alpha particles from fusion reactions, will require the consideration of all of these key elements to predict quantitatively the stability and evolution. The principal investigators on this proposal are leading experts in the relevant theoretical and computational areas, and aimed to perform computations guided by analytic modeling, to address this physics in realistic configurations. The overall goal is to understand the key physics mechanisms that describe resistive toroidal burning plasmas, surrounded by a resistive wall, under active feedback control. With the physics of the energetic ions, resonant layers, resistive wall, and toroidal momentum transport included, this study will extend from recent publications in theory and simulation of individual effects and move toward predictive modeling for burning plasmas.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

A Review of the Resuspension of Radioactively Contaminated Particles by Vehicle and Pedestrian Traffic—Current Theory, Practice, Gaps, and Needs

Here, the resuspension of radioactively contaminated particles in a built environment, such as from urban surfaces like foliage, building exteriors, and roadways, is described empirically by current plume and dosimetry models used for hazard assessment and long-term risk purposes. When applying these models to radiological contamination emergencies affecting urban areas, the accuracy of the results for recent contamination deposition is impacted in two main ways. First, the data supporting the underlying resuspension equations was acquired for open, quiescent conditions with no vehicle traffic or human activities, so it is not necessarily representative of the urban environment. Second, mechanical disturbance by winds in urban canyons and during emergency operations caused by vehicle traffic and human activities are not directly considered by the equations. Accordingly, plume and dosimetry models allow the user to input certain compensating values, but the models do not necessarily supply users instructions on what values to use. This manuscript reviews the available literature to comprehensively and consistently pool data for resuspension due to mechanically induced resuspension applicable to urban contamination. Because there are few studies that directly measured radioactive resuspension due to vehicles and pedestrians, this review novelly draws on a range of other studies involving non-radioactive particles, ranging from outdoor air pollution emissions to indoor allergen transport. The results lead to tabulated, recommended values for specific conditions in the emergency phase to help users of plume and dosimetry models maintain the conservativeness needed to properly capture the potential radiation dose posed by mechanically induced resuspension. These values are of benefit to model users until better data are available. The results also suggest the types of data that may result in improved plume and dose modeling.

61 RADIATION PROTECTION AND DOSIMETRY↗

An indirect approach to optimize the reaction rates of thermal NO formation for diesel engines

With stringent emission regulations, it has become more important for modern diesel engine manufacturers to accurately predict engine-out nitrogen oxide (NO x ) emissions across a wide range of operating conditions. Thermal NO is the major source of engine-out NO x in modern diesel engines. For thermal NO formation, several earlier studies have recommended the forward and reverse reaction rate coefficients of the rate-limiting reaction (O + N 2 ⇌ NO + N). However, due to deficiencies in sub-models and inadequacies of reduced chemical mechanisms to represent diesel combustion, these recommended values more often than not need to be adjusted in reduced order combustion models to accurately predict engine-out NO x . Hence, in this work a systematic and computationally efficient approach has been proposed to streamline the process of determining the optimum reaction rate coefficients. Here, to develop the optimization approach, four different production diesel engines with different operating conditions in terms of speed, load, and exhaust-gas recirculation have been considered. Numerical simulations have been performed using a detailed zero-dimensional velocity-composition-frequency transported probability density function (0D-VCF-tPDF) model that uses hundreds of notional particles to capture in-cylinder stratification. Four different combinations of hydrocarbon and NO x chemical mechanisms were used to represent chemistry. It was found that for the rate-limiting reaction, the pre-exponent factors (A f1 , A r1 ) and activation energies (E A,f1 , E A,r1 ) of the forward and reverse reaction rates follow a linear band in A f1 - E A,f1 and A r1 - E A,r1 space where predicted engine-out NO x match the measured values closely. By encompassing such bands from different engines and considering constraints on activation energies, a reduced search domain of pre-exponent factors and activation energies was constructed that is expected to be applicable to any diesel engine. Eventually, computationally efficient three-line and one-line search approaches were proposed to determine the optimum values of the pre-exponent factors and activation energies that led to a minimum error between measured and predicted engine-out NO x . Finally, these three-line and one-line NO x optimization approaches were applied to a fifth production diesel engine for which the 0D-VCF-tPDF model showed a very good predictive performance in terms of predicting peak pressure, 50% burn rate, and engine-out NO x when compared to measured and 3D-CFD values.

33 ADVANCED PROPULSION SYSTEMS↗

Catalyzed oxidation of nuclear graphite by simulated fission products Sr, Eu, and I

The influence of three fission products Sr, Eu, and I on the oxidation of IG-110 nuclear graphite was studied in the temperature range of 400 to 1000 °C. Sr and Eu were introduced as chlorides, and I was introduced as NaI. The temperature dependence of both CO 2 and CO production during the graphite oxidation measured with mass spectroscopy and infrared spectrometry shows that the introduction of these three compounds to graphite significantly decreases the onset temperature for the oxidation of graphite. Among the three compounds, NaI is the most active towards the oxidation reaction, characterized by a significant decrease of the onset temperature from approximately 650 to 400 °C before and after its introduction to graphite. Separate measurements of CO 2 and CO concentration at varying temperatures enable the calculation of the activation energy for the formation of CO 2 and CO. The activation energies for the oxidation of pure and fission product-impregnated graphite samples decrease in the following order: standard IG-110 graphite, EuCl 3 -impregnated IG-110, SrCl 2 -impregnated IG-110, and NaI-impregnated IG-110. This trend indicates that the three compounds catalyze the oxidation of graphite at temperatures relevant to the operation of high-temperature gas-cooled reactors. Furthermore, it is found that the three compounds can also affect the molar ratio of reaction products CO 2 and CO, and the rates of the graphite oxidation. At temperatures higher than about 850 °C, the impregnated samples exhibit lower CO 2 : CO ratios than the pure graphite. Different from EuCl 3 and NaI, the introduction of SrCl 2 decreases the graphite oxidation rates at temperatures higher than about 770 °C. Their catalytic mechanism can be understood based on a redox cycle of the intermediate active species, promoting the dissociation of molecular oxygen and transfer to the carbon.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗