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At least 235 records · Page 13

Dynamics modeling of molten salt reactor with reduced and expanded representations of delayed neutron precursors

Molten salt reactors (MSRs) present unique challenges in dynamic behavior due to the mobility of their fuel. In these reactors, delayed neutron precursors (DNPs) drift with the fuel circulation through the primary loop. As a result, a fraction of DNPs decays outside the core, effectively reducing the available delayed neutron population for reactivity control. Consequently, precise modeling of the distribution and behavior of DNPs is critical for accurate reactor dynamics simulations. In this study, the System Dynamics Analysis Tool (SDAT) was used to simulate a thermal-spectrum MSR under steady-state conditions and following transients. The effects of using reduced and expanded representations of DNPs with fewer or more groups than the conventional 6-group model were investigated. Their impact on the simulated distribution of precursors in the primary loop, reactivity loss value, and reactor response to transients was analyzed. Simulation results showed that reduced models lead to the loss of the actual DNPs distribution data, resulting in less accurate estimates of reactivity loss. Reactor power predictions using these reduced models showed significant deviations compared to those using the conventional 6-group model in transient simulations. Expanded models offered a more accurate representation of the distribution of DNPs and reactivity loss estimates. Reactor power predictions using expanded models showed minimal deviation from the conventional 6-group model during the simulated transients.

analysis↗

Investigating Kinetic Mechanisms of Soot Formation in Plasma Pyrolysis of Methane via Active Learning (Final Technical Report)

Plasma pyrolysis of methane is an effective route for zero-carbon hydrogen production. Yet, soot generated from pyrolysis of hydrocarbons is detrimental to the climate and human health. There is ample experimental and theoretical evidence that suggests polycyclic aromatic hydrocarbons (PAHs) are the molecular precursors to soot particles. The reaction pathways of PAH formation are intricately dependent on a multitude of process parameters, whose kinetic mechanisms are not well-understood in plasma pyrolysis. This project aims to leverage advances in the kinetic modeling of soot formation in combustion, as well as in surrogate modeling and active learning, to systematically investigate the effects of process parameter on the kinetics of PAH formation in plasma pyrolysis of methane. To this end, we propose to use the PAH formation kinetics model developed by the PPPL/PU group based on the well-established ABF and HACA mechanisms, coupled with low-temperature plasma models. We will develop an active learning (AL) framework based on Bayesian optimization to systematically and data-efficiently explore the complex and multivariable parameter space of plasma pyrolysis in order to quantify the effects of plasma and feed parameters on the ABF and HACA kinetic pathways. AL is the branch of machine learning concerned with systematically querying samples from a system (experimental or computational) to train a data-driven model that maps design parameters to a performance criterion. We will use the data generated via AL to perform global sensitivity analysis, combined with uncertainty quantification, to elucidate the impact of different reaction pathways on minimizing formation of soot precursors. This study will result in an improved understanding of kinetics of PAH formation in plasma pyrolysis and can pave the way for more advanced mechanistic studies (e.g., soot nucleation mechanisms). Additionally, the findings will be useful for establishing practical strategies for increasing the pyrolysis efficiency and producing high-grade carbon for synthesis of nanomaterials.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

In situ Synchrotron X‐ray Metrology Boosted by Automated Data Analysis for Real‐time Monitoring of Cathode Calcination

Abstract Synchrotron X‐ray‐based in situ metrology is advantageous for monitoring the synthesis of battery materials, offering high throughput, high spatial and temporal resolution, and chemical sensitivity. However, the rapid generation of massive data poses a challenge to on‐site, on‐the‐fly analysis needed for real‐time process monitoring. Here, a weighted lagged cross‐correlation (WLCC) similarity approach is presented for automated data analysis, which merges with in situ synchrotron X‐ray diffraction metrology to monitor the calcination process of the archetypal nickel‐based cathode, LiNiO 2 . The WLCC approach, incorporating variables that account for peak shifts and width changes associated with structural transformations, enables rapid extraction of phase progression within 10 seconds from tens of diffraction patterns. Details are captured, from initial precursors to intermediates and the final layered LiNiO 2 , providing information for agile on‐site adjustments during experiments and complementing post hoc diffraction analysis by offering insights into early‐stage phase nucleation and growth. Expanding this data‐powered platform paves the way for real time calcination process monitoring and control, which is pivotal to quality control in battery cathode manufacturing.

36 MATERIALS SCIENCE↗

Analysis of Atmospheric Conditions Responsible for an Ozone Exceedance Event in Southeast Virginia on June 15, 2022

On June 15, 2022, the Virginia Department of Environmental Quality monitoring site at Suffolk/Holland, a rural site in southeast Virginia, recorded its first ozone exceedance since 2016. An ozone exceedance day occurs when the daily maximum 8-hour average surface ozone concentration is greater than 70 ppb. On this day, it was 75 ppb. This event is also noteworthy due to the rapid increase in surface ozone between 6 am and 9 am EDT as well as the hourly maximum ozone concentration of 82 ppb that was measured at 1 pm EDT. In this analysis, we utilize various observational and model data to determine the atmospheric conditions responsible for this ozone exceedance event. The analysis is conducted in two parts: (1) an evaluation of the accuracy of the GEOS-CF and WRF-Chem model forecasts and (2) an investigation of the mechanisms responsible for the high surface ozone at the Virginia DEQ Suffolk/Holland monitoring site. Comparisons of model forecasted ozone time-height cross sections with measured ozone by lidars from the Tropospheric Ozone Lidar Network (TOLNet) at NASA Langley and NASA Goddard reveal that both models forecasted ozone reasonably well near the surface. Model and observational data reveal that an upper-level ridge was present over much of the eastern United States, with a broad anticyclonic circulation near the surface, resulting in north-northeasterly flow over southeast Virginia. Back trajectory calculations using the Hybrid Single-Particle Lagrangian Integrated Trajectory model (HYSPLIT) and model data suggest that a low-level plume rich in ozone and precursor species originating from the New York City and New Jersey region was transported along the east coast between June 14 and June 15, arriving in southeast Virginia around 6 am EDT on June 15. In the early morning hours, this plume mixed down to the surface, elevating the background ozone mixing ratio as well as the mixing ratios of several precursor species. Other potential contributions are also explored and discussed. Lastly, the authors note that this work represents the analysis of the authors and not the Virginia Department of Environmental Quality.

Daniel B Phoenix↗

Computationally guided synthesis of carbon coated mesoporous silica materials

Mesoporous silica materials (MSMs) are well-suited for biomedical applications due to their unique features, including a large surface area and tunable pore size. To enhance their durability, the small pores in MSMs are filled with carbon precursors and then carbonized to prevent them from interacting with unreacted silicic acid. Here, in this study, we synthesized and healed MSMs using a combination of non-reactive and reactive molecular dynamics (MD) simulations. The non-reactive MD simulation revealed that the self-assembly of Pluronic® L64 polymers in water resulted in nearly 80 % hydrogen bonds between the hydrophilic sections of the micelle and water. In the bond-boosted ReaxFF MD simulations, silicic acid precursors were condensed on the micelle surface, with over 60 % of them leading to the creation of periodic mesoporous silica within the system. Condensation of silicic acid precursors at 300 K with bond-boosting and at 1500 K without it both significantly promoted the polymerization of Si(OH) 4 , with the latter doubling the rate compared to the former. Subsequently, we healed the MSM surface by carbonizing carbon precursors inside an MSM pore. Polyethylene (PE) and high-rank lignite were identified as the most suitable precursors due to their ability to form turbostratic graphene structures. High-rank lignite exhibited the highest carbon conversion ratio to 6-membered rings, closely followed by PE, in the carbon ring formation analysis. Additionally, the production of gases, such as H 2 , increased significantly for PE at both 2200 K and 2600 K, indicating the conversion of a considerable portion of carbon into graphitic or turbostratic structures. The carbonization of PE primarily led to the formation of planar (sp 2 ) structures, while sucrose yielded the least planar structures. Finally, we studied the protective blocking of unreacted silicic acid precursor by considering a PET turbostratic graphene structure in a silica mesopore formed at 2600 K. The trajectory analysis showed that the surface of the silica was effectively coated with PET tar, preventing unreacted silicic acid from interacting with the inner silica pore surface. These findings offer valuable insights into the synthesis and carbonization-based healing processes of MSMs, enhancing their potential for various biomedical applications.

36 MATERIALS SCIENCE↗

Zn‐Doped P‐Type InAs Nanocrystal Quantum Dots

Abstract Doped heavy metal‐free III–V semiconductor nanocrystal quantum dots (QDs) are of great interest both from the fundamental aspects of doping in highly confined structures, and from the applicative side of utilizing such building blocks in the fabrication of p–n homojunction devices. InAs nanocrystals (NCs), that are of particular relevance for short‐wave IR detection and emission applications, manifest heavy n‐type character poising a challenge for their transition to p‐type behavior. The p‐type doping of InAs NCs is presented with Zn – enabling control over the charge carrier type in InAs QDs field effect transistors. The post‐synthesis doping reaction mechanism is studied for Zn precursors with varying reactivity. Successful p‐type doping is achieved by the more reactive precursor, diethylzinc. Substitutional doping by Zn 2+ replacing In 3+ is established by X‐ray absorption spectroscopy analysis. Furthermore, enhanced near infrared photoluminescence is observed due to surface passivation by Zn as indicated from elemental mapping utilizing high‐resolution electron microscopy corroborated by X‐ray photoelectron spectroscopy study. The demonstrated ability to control the carrier type, along with the improved emission characteristics, paves the way towards fabrication of optoelectronic devices active in the short‐wave infrared region utilizing heavy‐metal free nanocrystal building blocks.

77 NANOSCIENCE AND NANOTECHNOLOGY↗

Isolation of a Cyclopentasilane from Magnesium Reduction of a Linear Hexasilane

The reductive cyclization of two linear hexasilanes is contrasted, where a methylated precursor yielded a cyclohexasilane while the tert-butyl-functionalized analog unexpectedly yielded a cyclopentasilane. A comprehensive analysis using X-ray diffraction, IR, HR, HRMS, and multinuclear (1H, 13C and 29Si) 1D and 2D NMR spectroscopy identified the 1,2-dihydrodisilane tBuPhHSi–SiHPhtBu as an additional product, which was interpreted as supportive of a mechanism involving silylene elimination. Here, the results of this study may prove informative about substituent effects in the practice of complex organosilicon molecular synthesis.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Nanosized Organo-Silica Particles with “Built-In” Surface-Initiated Atom Transfer Radical Polymerization Capability as a Platform for Brush Particle Synthesis

A facile synthetic method was developed to prepare sub-5 nm organo-silica (oSiO 2 ) nanoparticles through the self-condensation of ATRP-initiator-containing silica precursors. The obtained oSiO 2 nanoparticles were characterized by a combination of nuclear magnetic resonance (NMR), thermogravimetric analysis (TGA), transmission electron microscopy (TEM), dynamic light scattering (DLS) and small-angle neutron scattering (SANS). The accessibility of the surface -Br initiating sites was evaluated by the polymerization of poly(methyl methacrylate) (PMMA) ligands from the surface of the oSiO 2 nanoparticles using surface-initiated atom transfer radical polymerization (SI-ATRP). Here, the ultra-small size, tunable composition and ease of surface modification may render these organosilica nanoparticle systems with built-in SI-ATRP capability an interesting alternative to conventional silica nanoparticles for functional material design.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

FY22 Progress Report: SRNL Analysis of ICCWR LCM and WAMS Data for Corrosion and Cracking

Algorithms for machine learning and data analysis for the 3013 Surveillance Program are being developed in an ongoing collaborative effort by the Savannah River National Laboratory (SRNL) and the University of South Carolina (USC). To detect the presence of corrosion and cracking, data is collected from large binary files generated by a Laser Confocal Microscope (LCM) or Wide Area 3D Measurement System (WAMS). Software is being developed to use the physical attributes in the data files (e.g., height, color, and grayscale values; all as functions of a location in a plane projection) to detect the presence of surface corrosion and cracking. A user-friendly Matlab Graphical User Interface (GUI) that reads data from either LCM or WAMS files was developed to integrate input data with software developed for processing and evaluation. The GUI can selectively download binary data, interrogate data attributes, label data for training ML algorithms, flag significant features, execute Machine Learning (ML) algorithms, output parameters from trained ML algorithms, report ML model accuracy with respect to labeled data, and generate graphical representations for various analyses. Surface defects can be called out by setting user-specified thresholds, feature based analysis or machine learning algorithms. Enhancements to data labeling capability have been developed to address this essential precursor to application of ML routines. Efficient labeling is particularly important in view of the very large volume of data required to train ML algorithms.

3013 Corrosion↗

Organic molecules as chemical fossils - The molecular fossil record

The study of biochemical clues to the early earth and the origin of life is discussed. The methods used in such investigation are described, including the extraction, fractionation, and analysis of geolipids and the analysis of kerogen. The occurrence of molecular fossils in the geological record is examined, discussing proposed precursor-product relationships and the molecular assessment of deep sea sediments, ancient sediments, and crude petroleums. Alterations in the molecular record due to diagenesis and catagenesis are considered, and the use of microbial lipids as molecular fossils is discussed. The results of searches for molecular fossils in Precambrian sediments are assessed.

Eglinton, G.↗

Synthesis, Characterization and Decomposition Studies of Tris(N,N-dibenzyldithiocarbamato) Indium(III): Chemical Spray Deposition of Polycrystalline CuInS2 on Copper Films

Tris(bis(phenylmethyl)carbamodithioato-S,S ), commonly referred to as tris(N,Ndibenzyldithiocarbamato) indium(III), In(S2CNBz2)3, was synthesized and characterized by single crystal X-ray crystallography. The compound crystallizes in the triclinic space group P1 bar with two molecules per unit cell. The material was further characterized using a novel analytical system employing the combined powers of thermogravimetric analysis, gas chromatography/mass spectrometry and Fourier-Transform infrared spectroscopy to investigate its potential use as a precursor for the chemical vapor deposition (CVD) of thin film materials for photovoltaic applications. Upon heating, the material thermally decomposes to release CS2 and benzyl moieties in to the gas phase, resulting in bulk In2S3. Preliminary spray CVD experiments indicate that In(S2CNBz2)3 decomposed on a Cu substrate reacts to produce stoichiometric CuInS2 films.

Hehemann, David G.↗

COUPLED GRIFFIN AND PRONGHORN SIMULATION OF THE MOLTEN SALT FAST REACTOR (MSFR) FOR THE VIRTUAL TEST BED

The Virtual Test Bed (VTB) repository hosts a wide range of challenge problems to showcase modeling and simulation capabilities to support advanced reactor demonstration. An overview of a coupled multiphysics model for Molten Salt Reactors (MSR) is presented here. The analysis leverages MOOSE-based tools (notably Griffin and Pronghorn) for neutronic and thermal hydraulic simulation. Neutron precursor drifting capability is showcased, along with some initial turbulence models. Both steady-state and transient coupled multiphysics results for an MSR concept are discussed.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Exploring the fragmentation efficiency of proteins analyzed by MALDI-TOF-TOF tandem mass spectrometry using computational and statistical analyses

Matrix-assisted laser desorption/ionization time-of-flight-time-of-flight (MALDI-TOF-TOF) tandem mass spectrometry (MS/MS) is a rapid technique for identifying intact proteins from unfractionated mixtures by top-down proteomic analysis. MS/MS allows isolation of specific intact protein ions prior to fragmentation, allowing fragment ion attribution to a specific precursor ion. However, the fragmentation efficiency of mature, intact protein ions by MS/MS post-source decay (PSD) varies widely, and the biochemical and structural factors of the protein that contribute to it are poorly understood. With the advent of protein structure prediction algorithms such as Alphafold2, we have wider access to protein structures for which no crystal structure exists. In this work, we use a statistical approach to explore the properties of bacterial proteins that can affect their gas phase dissociation via PSD. We extract various protein properties from Alphafold2 predictions and analyze their effect on fragmentation efficiency. Our results show that the fragmentation efficiency from cleavage of the polypeptide backbone on the C-terminal side of glutamic acid (E) and asparagine (N) residues were nearly equal. In addition, we found that the rearrangement and cleavage on the C-terminal side of aspartic acid (D) residues that result from the aspartic acid effect (AAE) were higher than for E- and N-residues. From residue interaction network analysis, we identified several local centrality measures and discussed their implications regarding the AAE. We also confirmed the selective cleavage of the backbone at D-proline bonds in proteins and further extend it to N-proline bonds. Finally, we note an enhancement of the AAE mechanism when the residue on the C-terminal side of D-, E- and N-residues is glycine. To the best of our knowledge, this is the first report of this phenomenon. Our study demonstrates the value of using statistical analyses of protein sequences and their predicted structures to better understand the fragmentation of the intact protein ions in the gas phase.

59 BASIC BIOLOGICAL SCIENCES↗

Transcriptomic Analysis Reveals Novel Regulators of the Scots Pine Stilbene Pathway

Stilbenes accumulate in Scots pine heartwood where they have important roles in protecting wood from decaying fungi. They are also part of active defense responses, and their production is induced by different (a)biotic stressors. The specific transcriptional regulators as well as the enzyme responsible for activating the stilbene precursor cinnamate in the pathway are still unknown. UV-C radiation was the first discovered artificial stress activator of the pathway. Here, we describe a large-scale transcriptomic analysis of pine needles in response to UV-C and treatment with translational inhibitors, both activating the transcription of stilbene pathway genes. We used the data to identify putative candidates for the missing CoA ligase and for pathway regulators. We further showed that the pathway is transcriptionally activated by phosphatase inhibitor, ethylene and jasmonate treatments, as in grapevine, and that the stilbene synthase promoter retains its inducibility in some of the tested conditions in Arabidopsis, a species that normally does not synthesize stilbenes. Shared features between gymnosperm and angiosperm regulation and partially retained inducibility in Arabidopsis suggest that pathway regulation occurs not only via ancient stress-response pathway(s) but also via species-specific regulators. Understanding which genes control the biosynthesis of stilbenes in Scots pine aids breeding of more resistant trees.

4-Coumarate-CoA ligase↗

Toward a tunable fabrication of multifunctional iron-aluminum spinels via solution combustion synthesis: The effects of fuel, heating mode, and Fe:Al precursor ratio

The solid solutions of iron and aluminum spinels (hercynite, maghemite, magnetite, and γ-alumina) are promising materials for emerging technologies such as solar thermochemical fuel production and clean dehydrogenation of fossil fuels. Solution combustion synthesis (SCS) is an attractive technique for the fabrication of these materials as it has been used for synthesis of many nanoscale oxides. However, the design space of SCS is large with many synthesis parameters affecting the properties of the combustion products. To optimize the SCS of these materials, it is important to determine which parameters yield the best properties. In the present work, FeAlO x nanocomposites were obtained by SCS using iron nitrate and aluminum nitrate as precursors and oxidizers. Two fuels (citric acid and glycine), three Fe:Al molar ratios (1:2, 1:1, and 2:1) in the precursors, and three heating modes (hotplate, muffle furnace, and microwave oven) were compared. The products were characterized by X-ray diffraction analysis, scanning electron microscopy, Brunauer-Emmett-Teller surface area analysis, and laser diffraction particle size analysis. The fuel used had the largest impact on the combustion behavior and hence the material properties. The high combustion temperature of glycine allowed for the formation of an FeAl 2 O 4 /Fe 3 O 4 solid solution, while the lower-temperature combustion of citric acid yielded Al-substituted γ-Fe 2 O 3 with high amorphous content. With citric acid, the specific surface area as high as 200 m 2 /g was achieved. The effect of Fe:Al precursor ratio was clearly seen in variations of the lattice parameter, which demonstrated the ability to tune the phase composition. The heating mode had minor effects on material properties, but some differences were observed. As a result, all products obtained by SCS in a microwave oven had low specific surface areas compared to those obtained with a hotplate and a muffle furnace.

Alumina↗

An Approach for Defining IASMS Services, Functions, and Capabilities

Assuring safety in the NAS with the inclusion of new entrants, such as Advanced Air Mobility (AAM), will require overcoming unique safety challenges that result from combining innovative technologies with novel airspace concepts for moving people and cargo using autonomous vehicles. The focus of the In-time Aviation Safety Management System (IASMS) is to overcome AAM’s safety assurance challenges. The IASMS Concept of Operations (ConOps) describes an interconnected set of services, functions, and capabilities (SFCs) designed to manage operational risks, identify unknown risks, and inform system designs. This paper describes an approach for defining SFCs based on technology trends in research, assessment of known and unknown risks in voluntary safety reports, and causal and contributing factors in aviation accidents and incidents. This approach would identify potential SFCs that further expand the Monitor, Assess, and Mitigate (M-A-M) functionality that represents the enabling framework of the IASMS. Safety implications that will result from integration of AAM in the transformation of the National Airspace System (NAS) were addressed in National Academies committees reports on AAM and IASMS. Development of a ConOps for IASMS was a top recommendation and can be represented as a reframing of safety assurance that builds on real-time alerting such as the Traffic Alert and Collision Avoidance System, and adds the more encompassing in-time temporal parameter in recognition of the different timelines for collecting and assessing safety data for risk mitigations. For example, mining for safety trends from data sources such as the Aviation Safety Information Analysis and Sharing system occurs over a longer time period. Research on AAM operations poses that SFCs can be designed to monitor the safety margin appropriate for AAM including with regards to the distance between current flight parameters and nominal ideal conditions. These in-time comparisons will become more complex as the density of operations increases at least in certain areas and can include planned and actual 4D trajectory, and in-time comparisons having implications on conflict modeling and prediction including expected and actual departure time, fix/waypoint crossing times, and arrival time. These comparisons would be integrated as part of SFCs that redefine and inform new safety margin. An increased safety margin improves management of operational risks while reducing the potential for anomalies. An increased safety margin also has implications for operator confidence in the certainty of its operations and trust in automation. Technology trends in research could be used to refine existing SFCs and define needs for additional SFCs that provide safety improvements to the design and operation of vehicles, airspace design, and operator performance requirements. NASA is developing innovative approaches to safeguard against major accidents and incidents that have occurred in the NAS and those anticipated with the inclusion of envisioned AAM operations. The innovations use operational performance data to monitor, detect, and predict flight variations exceeding safe nominal patterns, such as would be caused by navigational error, severe weather complications, or hijacking of UAS controls. These innovative approaches have high potential to prevent accidents and incidents in the new AAM era. It is anticipated that elements of the innovations will evolve into SFCs for the IASMS. Voluntary safety reports can be monitored to identify anomalies related to design or operational performance risks. Reports could be periodically monitored and assessed for specific topics. Reports might serve as weak signals or precursors indicative of emergent risk such as when combined with other safety information. The architecture could include SFCs that are based on voluntary safety reports recognizing the periodic temporal nature of data analysis. As previously mentioned, aviation accidents with their causal and contributing precursors can inform the need for SFCs in the IASMS. Accidents and incidents at San Francisco International Airport such as Asiana 214 and Air Canada 759 illustrate how combinations of different factors lead to increased risk. These types of precursors and different factors have implications on the types of SFCs that could be needed to monitor and manage different sources and types of design and operational risk. Continuing to assure the safety of AAM as designs and operations gain in complexity can be accompanied by defining SFCs that also increase in complexity. These SFCs can leverage information from findings and recommendations synthesized across on-going research, voluntary safety reports, and accident and incident reports. These SFCs can serve to refine accuracy of algorithms and resolve limitations with current practices. The IASMS architecture represents the framework for the SFCs and their critical role in safety assurance.

In-Time Aviation Safety Management System↗

Equatorial waves triggering extreme rainfall and floods in southwest Sulawesi, Indonesia

On the basis of detailed analysis of a case study and long-term climatology, it is shown that equatorial waves and their interactions serve as precursors for extreme rain and flood events in the central Maritime Continent region of southwest Sulawesi, Indonesia. Meteorological conditions on January 22, 2019, leading to heavy rainfall and devastating flooding in this area were studied. It is shown that a convectively coupled Kelvin wave (CCKW) and a convectively coupled Rossby wave (CCERW) embedded within the larger-scale envelope of the Madden-Julian Oscillation (MJO) enhanced convective phase, contributed to the onset of a mesoscale convective system which developed over the Java Sea. Low-Level convergence from the CCKW forced mesoscale convective organization and orographic ascent of moist air over the slopes of southwest Sulawesi. Climatological analysis shows that 92 % of December-January-February floods and 76% of extreme rain events in this region were immediately preceded by positive low-level westerly wind anomalies. It is estimated that both CCKWs and CCERWs propagating over Sulawesi double the chance of floods and extreme rain event development, which the probability of such hazardous events occurring during their combined activity is eight times greater than on a random day. While the MJO is a key component shaping tropical atmospheric variability, it is shown that its usefulness as a single factor for extreme weather-driven hazard prediction is limited.

Latos, Beata↗

Laser-Induced Thermal Decomposition of Uranium Coordination Compounds with Non-oxidic Ligands to Produce Nitride and Carbide Materials

The production of ceramics from uranium coordination compounds can be achieved through thermal processing if an excess amount of the desired atoms (i.e., C or N), or reactive gaseous products (e.g., methane or nitrogen oxide) is made available to the reactive uranium metal core via decomposition/fragmentation of the surrounding ligand groups. Here, computational thermodynamic approaches were utilized to identify the temperatures necessary to produce uranium metal from some starting compounds—UI 4 (TMEDA) 2 , UCl 4 (TMEDA) 2 , UCl 3 (pyridine) x , and UI 3 (pyridine) 4 . Experimentally, precursors were irradiated by a laser under various gaseous environments (argon, nitrogen, and methane) creating extreme reaction conditions (i.e., fast heating, high temperature profile >2000 °C, and rapid cooling). Despite the fast dynamics associated with laser irradiation, the central uranium atom reacted with the thermal decomposition products of the ligands yielding uranium ceramics. Residual gas analysis identified vaporized products from the laser irradiation, and the final ceramic products were characterized by powder X-ray diffraction. The composition of the uranium precursor as well as the gaseous environment had a direct impact on the production of the final phases.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗