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DOE OSTI2024

Fungi rather than bacteria drive early mass loss from fungal necromass regardless of particle size

Microbial necromass is increasingly recognized as an important fast-cycling component of the long-term carbon present in soils. To better understand how fungi and bacteria individually contribute to the decomposition of fungal necromass, three particle sizes (>500, 250–500, and <250 μm) of Hyaloscypha bicolor necromass were incubated in laboratory microcosms inoculated with individual strains of two fungi and two bacteria. Decomposition was assessed after 15 and 28 days via necromass loss, microbial respiration, and changes in necromass pH, water content, and chemistry. To examine how fungal–bacterial interactions impact microbial growth on necromass, single and paired cultures of bacteria and fungi were grown in microplates containing necromass-infused media. Microbial growth was measured after 5 days through quantitative PCR. Regardless of particle size, necromass colonized by fungi had higher mass loss and respiration than both bacteria and uninoculated controls. Fungal colonization increased necromass pH, water content, and altered chemistry, while necromass colonized by bacteria remained mostly unaltered. Bacteria grew significantly more when co-cultured with a fungus, while fungal growth was not significantly affected by bacteria. Collectively, our results suggest that fungi act as key early decomposers of fungal necromass and that bacteria may require the presence of fungi to actively participate in necromass decomposition.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2025

Microbiome Adaptation Could Amplify Modeled Projections of Global Soil Carbon Loss With Climate Warming

Warming alters soil microbial traits through ecological and evolutionary processes, directly influencing the decomposition of organic matter, which significantly affects global soil carbon emissions. Yet, soil carbon models largely ignore these processes and their implications for global responses to warming. Here, we incorporate eco-evolutionary theory into a mechanistic model describing microbial soil carbon decomposition to address the question of whether such processes could have consequential effects on climate carbon feedbacks globally. We assume that a key trait of microbes, their resource allocation to production of exoenzymes (which facilitate decomposition of organic matter)—is optimized to environmental temperatures by natural selection. We find that eco-evolutionary optimization results in microbes allocating more resources to enzyme production under warming. When applied at the global scale, eco-evolutionary optimization enhances the biological realism of soil carbon models and significantly amplifies global soil carbon loss by 2100. Our results highlight the significant potential of microbial eco-evolutionary responses to influence carbon cycle feedbacks to climate change, and motivate an urgent need for more comprehensive data to accurately quantify the adaptive potential of microbiomes in response to climate change.

Biodiversity & Conservation↗

DOE OSTI2025

Wildfire‐Induced Losses of Soil Particulate and Mineral‐Associated Organic Carbon Persist for Over 4 Years in a Chaparral Ecosystem

ABSTRACT Wildfires can lower soil carbon (C) stocks directly through combustion, but also indirectly during post‐fire recovery if microbial C demands outpace photosynthetic C inputs. However, how much C is respired by soil microorganisms post‐fire may depend on wildfire effects on particulate organic carbon (POC; mostly plant material accessible to microbes) and/or mineral‐associated organic carbon (MAOC; considered C protected by minerals from decomposers), meaning assessment of wildfire impacts on these pools is necessary to predict microbial decomposition rates and, thus, the fate of soil C. Here, we measured POC, MAOC, pyrogenic organic matter C, plant cover, extracellular enzyme activity (EEA), and microbial community abundance and composition 17 days, and 1, 3, and 4 years after the Holy Fire burned 94 km 2 of fire‐adapted chaparral. The wildfire immediately decreased POC by 50% (from 51 ± 21 to 26 ± 6 g C kg −1 ) and MAOC by 33% (from 9.3 ± 0.9 to 6.3 ± 0.9 g C kg −1 ), consistent with MAOC being less vulnerable to loss than POC. POC decreased by another 38% 1 year post‐fire, consistent with increases in microbial abundance and EEA suggesting increased microbial decomposition. Between 1 and 4 years after the fire, cover of the dominant shrub (Arctostaphylos glandulosa) increased from 3.9% ± 1.6% to 16% ± 5.4% (compared to 58% ± 4.6% in unburned plots), marking the end of net soil C losses. Still, soil C did not increase between 1 and 4 years post‐fire, suggesting plant C inputs did not outpace microbial respiration, a finding consistent with isotopically heavier C from microorganisms raising bulk soil δ 13 C values. As global changes favor increases in wildfire frequency and severity, C losses via combustion and decomposition may outpace plant C inputs during the first 4 years post‐fire in chaparral, slowing the replenishment of soil C stocks.

Biodiversity & Conservation↗

DOE OSTI2026

ChatMPI: LLM-Driven MPI Code Generation for HPC Workloads

The Message Passing Interface (MPI) standard plays a crucial role in enabling scientific applications for parallel computing and is an essential component in high-performance computing (HPC). However, implementing MPI code manually—especially applying a proper domain decomposition and communication pattern—is a challenging and error-prone task. We present ChatMPI, an AI assistant for MPI parallelization of sequential C codes. In our analysis, we focus on testing six essential HPC workloads, which are based on Basic Linear Algebra Subprograms levels 1, 2, and 3 as well as sparse, stencil, and iterative operations. We analyze the process of creating ChatMPI by using the ChatHPC library. This lightweight large language model (LLM)–based infrastructure enables HPC experts to efficiently create and supervise trustworthy AI capabilities for critical HPC software tasks. We study the data required for training (fine-tuning) ChatMPI to generate parallel codes that not only use MPI syntax correctly but also apply HPC techniques to reduce memory communication and maximize performance by using proper work decomposition. With a relatively small training dataset composed of a few dozen prompts and fewer than 15 minutes of fine-tuning on one node equipped with two NVIDIA H100 GPUs, ChatMPI elevates trustworthiness for MPI code generation of current LLMs (e.g., Code Llama, ChatGPT-4o and ChatGPT 5). Additionally, we evaluate the performance of the MPI codes generated by ChatMPI in comparison with the ones generated by ChatGPT-4o and ChatGPT-5. The codes generated by ChatMPI provide up to a 4 × boost in performance by using better problem decomposition, communication patterns, and HPC techniques (e.g., communication avoiding).

Valero Lara, Pedro [ORNL] (ORCID:0000000214794310)↗

DOE OSTI2026

BoBa

BoBa is a C++ software library for working with large matrices, tensors, and tensor decompositions. The library provides tools for dense matrix and tensor operations, tensor decompositions, and tensor decomposition methods that support modern CPU and GPU architectures. It includes portable abstractions for linear algebra, tensor algebra, and multidimensional computation. BoBa is intended for scientific computing applications that involve large multidimensional data sets or high dimensional mathematical models. Its capabilities support tasks such as data compression, linear algebra, efficient numerical computation, and the development of scalable algorithms for heterogeneous hardware. Tutorials, tests, and example applications are included to help users learn and apply the library.

Yao, Jin [Lawrence Livermore National Laboratory (↗

DOE OSTI2025

TRISO Particle Isolation and Graphite Removal Using SRNL Vapor Digestion Technology

Tri-structural isotropic fueled reactors are planned to come online in the next decade, but there is not currently a widely agreed upon disposition pathway for this new fuel stream. For long term used nuclear fuel storage, there would be a significant benefit if the waste volume could be reduced or mitigated. Most of the volume from used TRISO fuel contains graphite. SRNL currently has an active patent which describes one pathway to digest the graphite. One benefit in the utilization of this pathway is that multiple cylindrical pieces can be stacked end-to-end in a reaction tube, then nitric acid and water vapor can be flowed through the tube, and the weight change of the individual cores can provide both a reaction profile and overall oxidant use efficiency. The reaction of nitric acid and graphite passes through a series of intermediate products – NO 2 , NO, and N 2 O – from reaction and decomposition to eventually form N2. The data shows that NO2 grows in with increasing temperature between 500-600°C and then decreases by way of either reaction with graphite or decomposition. Nitric oxide, a reaction and thermal decomposition product of NO 2 , exhibits a consistent decline as a function of temperature, which is consistent with the literature. Similarly, the concentrations of N 2 O and N 2 increase as a function of temperature as their reactions with graphite become more favorable.

Advanced Reactors↗

DOE OSTI2026

Blodgett 13C–labeled litter incubation 2016-2019

The dataset is from 13C-labelled (stable isotope of carbon) root-litter in-situ field incubation experiment based on the whole-soil warming experiment at the Blodgett Forest Research Station, CA, USA. The files are in both ".csv" and ".xlsx" versions, and can be opened in "maCOS numbers", and "Microsoft Excel". The files includes several sheets with all the data published in the paper: Sun, B., Zosso, C., Wiesenberg, G. L. B., Pegoraro, E., Torn, M. S., and Schmidt, M. W. I.: Warming accelerates the decomposition of root-derived hydrolysable lipids in a temperate forest and is depth- and compound class-dependent, SOIL, 11, 1077–1093, https://doi.org/10.5194/soil-11-1077-2025, 2025. This dataset includes bulk soil carbon, nitrogen, delta 13C values, the normalized concentration (to organic carbon) of hydrolysable lipids identified, the absolute concentration (normalized to bulk soil) of hydrolysable lipids, hydrolysable lipids recovery, and weighted 13C-excess of bulk soil carbon, and weighted 13C-excess of each compound class in hydrolysable lipids. These data aim to answer two research questions: 1) How will warming affect the decomposition of 13C-labelled root-litter at different depth? 2) Will the decomposition of root-derived hydrolysable lipids under warming differ among different compound classes? The experiment sites located on the foothills of the Sierra Nevada near Georgetown, CA (120°3904000W; 38°5404300 N) at 1370m above see level. The Blodgett Forest is a mixed-coniferous forest. The site has a Mediterranean climate with a mean annual air temperature of 12.5 °C and a mean annual precipitation of 1774mm.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2026

Microwave-Assisted Hydrogen Generation from Hydrocarbon-Bearing Reservoir Rocks: Stage-Dependent Thermal Runaway and In-Situ Carbonate Engineering

Microwave-assisted hydrogen generation from hydrocarbon-bearing reservoir rocks is strongly influenced by mineralogy, methane activation, carbonate reactions, and thermal runaway behavior. This study investigates a new approach in which carbonate phases are generated in-situ through the reaction of internally produced CO2 with Ca(OH)2 under microwave heating conditions. The objective is to evaluate how rock mineralogy, methane injection, and Ca(OH)2 addition influence hydrogen generation, carbon redistribution, and stage-dependent reaction pathways during microwave exposure. Microwave heating experiments were conducted using Permian Basin reservoir rocks under three experimental conditions: rock-only experiments under Ar atmosphere, CH4–Ar experiments without additive, and CH4–Ar experiments containing 5 wt% Ca(OH)2. Methane-assisted experiments were performed under continuous injection of 30 standard cubic centimeters per minute (sccm) CH4 and 30 sccm Ar. Based on thermal runaway behavior, each experiment was divided into three operational stages: Before Thermal Runaway (BR), After Thermal Runaway–Decrease in Microwave Power (ARD), and After Thermal Runaway– Increase in Microwave Power (ARI). Temperature and gas composition were continuously monitored throughout the experiments. The rock-only experiments demonstrated that hydrogen generation can occur intrinsically from hydrocarbon-bearing rocks under microwave heating, even without externally injected methane. However, hydrogen production did not correlate solely with kerogen content, indicating that mineralogy strongly influences hydrogen-generation pathways. Correlation analyses suggested that kerogen decomposition initially generated CH4, CO, and CO2, followed by secondary hydrocarbon reactions associated with H2 and C2 hydrocarbon formation. Methane-assisted experiments substantially increased hydrogen production; however, identical methane injection rates produced significantly different hydrogen yields among the rock samples, confirming that mineralogical composition controls methaneconversion behavior under microwave heating conditions. The addition of Ca(OH)2 significantly altered carbon evolution behavior in a stage-dependent manner. During the BR stage, Ca(OH)2 reduced gas-phase CO2 production, particularly in carbonate-rich rocks, indicating favorable conditions for in-situ carbonation and carbonate deposition prior to extensive thermal decomposition. The suppression of CO2 during BR became more pronounced with increasing carbonate content of the rock system. After thermal runaway, carbonate-containing systems exhibited enhanced hydrogen generation behavior, suggesting that carbonatederived mineral transformations and carbonate-mediated reactions contribute to high-temperature hydrogen-generation pathways. In carbonate-poor rocks, Ca(OH)2 addition enabled simultaneous URTeC 4493775 2 enhancement of hydrogen production and partial suppression of CO2 release during the post-runaway stages. Overall, the results demonstrate that microwave-assisted hydrogen generation is governed by dynamically evolving interactions among kerogen decomposition, methane activation, mineral transformations, carbonate formation/decomposition, and thermal runaway behavior. This work introduces in-situ carbonate engineering with Ca(OH)2 as a strategy for coupling hydrogen generation with partial insitu carbon management under microwave heating conditions.

03 NATURAL GAS↗

DOE OSTI2024

Exploration of signal processing methods for superconducting magnet and quench data

Quenching is the phenomenon of a superconducting magnetic material carrying current transitioning into a regular conducting material. This may cause severe and irreparable damage to the superconductor due to Joule heating. The Magnet Department at Fermi National Accelerator Laboratory (FNAL) has acquired experimental data through quench antenna arrays that are recorded when the quench is detected. These data are in terms of voltage signals that are sampled at 100kHz for several minutes. There are multiple channels and each channel provides a data set of more than 20 million observations, while there is one channel, called the trigger channel which shows the time when quench is detected. Despite some advancements that were made including machine learning, data complexity still shadows the progress. In this work, we studied a multi-resolution analysis of the quench antenna data through the Haar wavelet transform. In particular, we applied the maximally overlapped discrete w avelet transform (MODWT) of a suitable level L to the given data and then projected it onto the wavelet basis. This decomposes a given signal (Original data) $x ϵ \mathbb{R}^N$ into $L + 1$ subspaces of $\mathbb{R}^N$. One of the subspaces called the approximation, captures the trend of the signal, and the others, called the details, capture the fluctuations at different frequency bands. This decomposition provides a clear trend of the data at a suitable level and also various activities (spikes) are seen in the details of the decomposition at every level. These spikes might reveal some information about the quench under investigation but in any case, give information about magnet behavior. Also, this decomposition is seen to be very useful in removing noise present in the data due to the source or mechanism of the experiment.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2024

Simultaneous Thermal Analysis of Anion and Cation Exchange Resins

The decomposition reactions of one anion exchange resin (Bio-Rad AG MP-1) and one cerium-loaded cation exchange resin (DOWEX 50W-X8), both in nitrate form, were analyzed using simultaneous thermal analysis methods. Thermogravimetric analysis, dynamic scanning calorimetry, and evolved gas analysis were deployed in combination to probe the temperature profiles, reaction enthalpies, and off-gases from these resins under process-relevant temperature ranges. Analysis indicates that both resins undergo three clear phases during heating. The first is a dehydration step with prominent off-gassing of water, the second is a decomposition step with evolution of several gaseous species, and lastly is a combustion step with a large release of CO 2 . The temperature at which combustion ends varies slightly between AG MP-1 and DOWEX 50W: combustion completed at ~690°C and ~810°C, respectively. For the DOWEX cation resin, the combustion reaction showed greater sensitivity to the availability of oxygen under the test conditions. Both resins displayed broad exotherms during the combustion step of the decomposition, but the DOWEX cation resin demonstrated a 4.5 times higher specific enthalpy than that of the AG MP-1.

36 MATERIALS SCIENCE↗

DOE OSTI2025

A Review of Tank 48H Treatment of Tetraphenylborate with Permanganate

Tank 48H contains roughly 270,000 gallons of radioactive waste material. The waste stored in this tank was to be processed in multiple stages utilizing facilities at the Savannah River Site (SRS) almost 30 years ago. The In-Tank Precipitation Process (ITP) was initiated in Tank 48H, which precipitated highly radioactive cesium-137 using sodium tetraphenylborate (NaTPB). While the process succeeded in precipitating the Cs, Sr, and other actinides, it also generated an unexpectedly large amount of benzene. The evolved benzene created a safety concern and made the waste incompatible with further downstream processing. This halted the ITP, and a new method of treatment was required to continue processing the legacy waste contained in Tank 48H. A myriad of treatment options have been proposed with multiple teams of researchers assembled to work on this highly complex issue over the last few decades. This review investigated one potentially viable treatment option, in-tank oxidation with sodium permanganate. Permanganate has been well known in literature as a strong oxidizing agent for organic compounds, as well as being utilized at the Savannah River Site (SRS) in other processes. A small number of studies have been conducted utilizing waste simulants to evaluate the use of permanganate as an oxidant for tetraphenylborate (TPB). A search of the literature and data from these studies indicates that permanganate could be a viable treatment for destruction of TPB in Tank 48H. While the scoping studies had a small number of individual experiments and nonideal conditions, the permanganate decomposed up to 90% of the TPB. A free hydroxide concentration above 1.0 M is required for tank corrosion control. Simulant studies indicate no decrease in TPB decomposition by permanganate until pH 14. The simulant studies show an increase in TPB decomposition as the temperature of the solution is increased to 40 °C. The post-reaction analysis of previous simulant tests did not look at all of the organic degradation products. Investigations into what these organic products are and in what quantity will help guide determinations as to whether the downstream processing facilities are able to handle the material that will be generated. Study on the time frame for the reaction between permanganate and TPB should be investigated as the literature reports only extend out to two weeks reaction time. The permanganate treatment conditions indicate no corrosion control concerns and a longer timescale reaction may be needed for in-tank treatment. In addition, further study would be useful to identify a lower boundary condition for the ratio of TPB and oxidant. The simulant tests applied large excesses of permanganate, and this may be unnecessary. The size constraint of the tank means that there will be practical limitations on the amount of sodium permanganate that can be added to the tank. The amount of permanganate should be minimized as much as possible while still ensuring decomposition of the TPB to minimize the amount of manganese dioxide solids generated.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

DOE OSTI2025

Replace Human Intelligence with Fast and Smart Geometric Reasoning and Graph Neural Network to Accelerate Next Gen ModSim Workflows

We present an agent-guided approach to CAD geometry decomposition that automates hex/hybrid meshing with graph neural networks (GNNs) to accelerate next-generation ModSim workflows. Our end-to-end pipeline (i) reduces 3D boundary-representation (B-Rep) models to a 2D chordal axis skeleton (CAT) and then to a 1D bipartite graph of surface and curve nodes, (ii) assigns per node labels as Cubit® WebCut actions, (iii) trains a multi-action GNN under supervised learning, and (iv) predicts five surface-node and three curve-node actions on out-of-distribution test geometries. Each graph node carries geometric, topological, and meshing attributes drawn from the B-Rep “skin” and CAT “skeleton,” with two-way mappings across 3D↔2D↔1D representations to maintain traceability back to 3D CAD. The supervised learning model exhibits stable convergence of the binary cross-entropy loss and achieves 98.7% accuracy on unseen lattice models. To operationalize decision-making, we rank predicted commands by geometric significance and prototyped the agent-guided workflow through the Cubit® Meshing PowerTool GUI. As a stretch goal, we explore reinforcement learning (RL) to reduce or remove label requirements and to learn policies for action sequences that maximize total reward (e.g., size of hex-meshable regions and resulting hex mesh quality). When all-hex meshing is not feasible, the agent assists in producing hybrid meshes—prioritizing hex in critical regions and transitioning to tetrahedral elements (tets) elsewhere—maintaining fidelity while ensuring robustness. The overarching objective is to replace manual, heuristics-based decomposition with data-driven, reproducible automation, cutting meshing turnaround time by orders of magnitude. We anticipate direct impact on simulation workflows through intelligent, scalable decomposition of complex CAD models into hex-meshable subdomains.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2025

Closing the Loop between In Situ Stress Complexity and EGS Fracture Complexity

42 ENGINEERING↗

DOE OSTI2025

Fabrication, oxidation, and combustion of nanoscale magnesium diboride and tetraboride

The difficult ignition of boron decreases the combustion efficiency of boron-loaded, fuel-rich propellants. One approach to solving this problem involves the use of magnesium diboride (MgB2), which ignites easier than boron. Magnesium tetraboride (MgB4) offers greater energy density owing to its higher boron content. However, the effect of B/Mg ratio on the ignition and combustion is unknown. Additionally, while nanoscale MgB₂ particles and quasi-2D structures were recently recognized as promising energetic additives, the oxidation and combustion properties of nanoscale MgB₄ have not been explored. The objectives of the present work included synthesis, purification, and high-energy ball milling of MgB2 and MgB4 powders as well as investigation of their thermal decomposition, oxidation, and combustion. The MgB2 and MgB4 powders were fabricated by combustion synthesis in the chemical oven mode and by heating Mg/B mixtures in a tube furnace. The latter method was superior in the synthesis of MgB4. Oxide impurities in the synthesized powders were removed by acid leaching. Nanoscale powders were obtained by high-energy ball milling. Thermal decomposition and oxidation of the obtained MgB₂ and MgB₄ powders were investigated by conducting non-isothermal thermogravimetric analysis (TGA) at temperatures up to 1550 °C in argon and oxygen flows. Combustion of B, MgB₂, and MgB₄ powders with oxygen at atmospheric pressure was studied in a windowed chamber using laser ignition and high-speed video recording. The TGA has shown multi-step decomposition of both magnesium borides in an argon environment. The maximum oxidation rate of MgB4 in oxygen was observed at a much lower temperature than in the case of MgB2. In the combustion experiments, both magnesium borides burned much faster than submicron boron. Ball milling of the borides further increased their burning rates. It has been concluded that nanoscale magnesium tetraboride is a promising ingredient for fuel-rich propellants owing to its high energy density, efficient oxidation, and rapid combustion.

Molina, Andre [The University of Texas at El Paso]↗

DOE OSTI2026

The Poisson tensor completion parametric estimator

We introduce the Poisson tensor completion (PTC) estimator that exploits inter-sample relationships to compute a low-rank Poisson tensor decomposition of the frequency histogram for samples of a multivariate distribution. Our crucial observation is that the histogram bins are an instance of a space partitioning of counts and thus can be identified with a spatial non-homogeneous Poisson process. The Poisson tensor decomposition leads to a completion of the mean measure over all bins—including those containing few to no samples—and leads to our proposed estimator. A Poisson tensor decomposition models the underlying distribution of the count data and guarantees non-negative estimated values obviating the need for additional constraints to ensure non-negativity. Furthermore, we demonstrate that our PTC estimator is a substantial improvement over standard histogram-based estimators for sub-Gaussian probability distributions because of the concentration of norm phenomenon.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2025

Fabrication and characterization of nanoscale magnesium diboride and tetraboride for propulsion and hydrogen storage applications

Abstract: Boron-loaded propellants have the potential to dramatically increase the performance of solid fuel ramjets, ducted rockets, and hybrid rocket engines. However, difficult ignition of boron decreases the combustion efficiency of these propellants. One approach to solving this problem involves the use of magnesium diboride, MgB2, which ignites easier than boron. Magnesium tetraboride, MgB4, potentially offers greater energetic performance as B has a higher energy density than Mg. However, the effect of the higher boron/metal ratio on the ignition and combustion is unclear. Nanoscale MgB2 particles and quasi 2D structures are promising propellant ingredients, but the oxidation and combustion properties of nanoscale MgB4 remain unknown. Nanoscale magnesium borides are also of interest as precursors for the synthesis of magnesium borohydride, Mg(BH4)2, a promising hydrogen storage material, but hydrogenation of MgB4 has not been studied yet. The objectives of the present work included synthesis, purification, and high-energy ball milling of MgB2 and MgB4 powders as well as investigation of their hydrogen uptake, thermal decomposition, oxidation, and combustion. The powders were fabricated by combustion synthesis and by heating in a tube furnace. The latter method was superior in the synthesis of MgB4. Oxide impurities in the synthesized powders were removed by acid leaching. Nanoscale powders were obtained by ball-mill exfoliation. The hydrogen intake of the obtained magnesium borides was examined at 700 bar and 300 ℃ and did not reveal any advantage of MgB4 over MgB2. Their thermal decomposition and oxidation were investigated with thermogravimetric analysis (TGA), while their combustion was studied using laser ignition and high-speed video recording. TGA has confirmed prior observations of multistep decomposition of magnesium borides, where each step involves formation of a boride with a higher B/Mg ratio and evaporation of formed magnesium. The oxidation rates of the borides are much higher than that of boron at temperatures over 1200 °C for MgB2 and over 900 °C for MgB4. The burning rates of non-milled MgB₂ and MgB₄ powders were much higher than for the used submicron boron. Milling the MgB₂ and MgB₄ powders further increased their burning rates. The milled MgB4 burned 7.5 times faster than submicron boron.

Combustion of metals, Solid fuels, Propellants, Hy↗

DOE OSTI2024

Synthesis of cerium precursors with alkoxide ligands for degradation to cerium oxide nanoparticles

Lanthanide oxide and sulfide nanoparticles present intriguing theoretical questions regarding their electronic structures, alongside numerous potential applications in material science and catalysis. Although these materials can be formed through hydrolysis, their synthesis via thermolysis is crucial for nanoscale materials and practical applications. This research aims to enhance our understanding of the decomposition mechanisms by focusing on cerium compounds, which are analogous to those studied previously. Currently, our knowledge of the decomposition mechanisms of cerium alkoxide precursors is limited. The objective of this project is to develop a mechanistic understanding of the formation of cerium oxide nanoparticles from cerium alkoxide precursors, employing a variety of techniques. These techniques include collision-induced dissociation in an ion-trap mass spectrometer, nuclear magnetic resonance (NMR) spectroscopy, thermogravimetric analysis coupled with differential scanning calorimetry (TGA-DSC), and gas chromatography-mass spectrometry (GC-MS) to investigate the decomposition mechanisms of the synthesized precursors.

37 - INORGANIC, ORGANIC, PHYSICAL AND ANALYTICAL C↗

DOE OSTI2026

A Scalable Reduced‐Order Model for the Steady Navier–Stokes Equations

Scaling up new scientific technologies from laboratory to industry often involves demonstrating performance on a larger scale. Computer simulations can accelerate design and predictions in the deployment process, though traditional numerical methods are computationally intractable even for intermediate pilot plant scales. Recently, the component reduced order modeling method has been developed to tackle this challenge by combining projection reduced order modeling and discontinuous Galerkin domain decomposition. However, while many scientific or engineering applications involve nonlinear physics, this method has only been demonstrated for various linear systems. In this work, the component reduced order modeling method is extended to steady Navier–Stokes flow, with application to general nonlinear physics in view. The large‐scale, global domain is decomposed into a combination of small‐scale unit component. Linear subspaces for flow velocity and pressure are identified via proper orthogonal decomposition over sample snapshots collected from each small‐scale unit component. Velocity bases are augmented with a pressure supremizer to satisfy the inf–sup condition for stable pressure prediction. Two different nonlinear reduced order modeling methods are employed and compared for efficient evaluation of nonlinear advection: A third‐order tensor projection operator and the empirical quadrature procedure. The proposed method is demonstrated on the flow over arrays of five different unit objects, achieving a 23‐fold speedup with less than 4% relative error in domains up to 256 times larger than the unit components. Furthermore, a numerical experiment with the pressure supremizer strongly indicates the need for a supremizer for stable pressure prediction. A comparison between the tensorial approach and the empirical quadrature procedure revealed a slight advantage of the empirical quadrature procedure. The framework is compared with an alternating Schwarz‐based reduced‐order approach, demonstrating improved efficiency and robustness for the DG‐based global solver while retaining flexibility for sub‐scale iterative solvers. The method is further extended to a coupled advection–diffusion and Navier–Stokes system, illustrating its applicability to multi‐physics problems and its potential for more general, inter‐coupled nonlinear systems.

42 ENGINEERING↗