Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “SYNTHESIS”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 19 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Laser-heated diamond anvil cell synthesis and recovery of metastable MnSb 2 and YbZn 2 for post-synthesis transport studies

The creation and exploration of new materials under extreme pressure–temperature conditions has become increasingly reliant on laser-heated diamond anvil cell (LHDAC) techniques, which provide direct access to previously unexplored regions of multinary phase diagrams. Whereas numerous high-pressure phases have been identified in situ, systematic recovery and post-synthesis physical property characterization of these materials remain significant challenges. In this work, we describe the setup and implementation of an LHDAC-based synthesis and recovery workflow and demonstrate its application to metastable MnSb 2 and YbZn 2 phases. Synchrotron x-ray diffraction and spatial mapping confirm dominant formation of the targeted phases, whereas laboratory-based refinement quantifies phase fractions despite intrinsic microstrain and minor secondary phases. High-pressure transport measurements on recovered samples reveal pressure-tunable electronic instabilities in both systems. In MnSb 2 , pressure suppresses two high-temperature magnetic ordering anomalies, observed in transport, by ∼5 GPa and, for higher pressures, induces a new low-temperature feature that increases with further pressure increase. In hexagonal high-pressure YbZn 2 , an electronic reconstruction emerges at ∼11 GPa, characterized by semiconducting-like behavior from ∼30 to 300 K and a broad low-temperature coherence crossover near 30 K. Our results establish LHDAC synthesis not only as a structural discovery tool but also as an experimental platform for investigating correlated quantum states stabilized far from equilibrium thermodynamic conditions.

Huyan, S. [Iowa State University, Ames, IA (United↗
DOE OSTI2026

Ammonia Synthesis by a Supported Iron-Lithium Hydride Precatalyst: Silicon Nitride Support Enabled Synthesis and Nitrogen Reservoir Dynamics

Amorphous silicon nitride (Si 3 N 4 ) is an unconventional support for the chemisorption of organometallic complexes and offers potential improvements in active site stability and reactivity through enhanced metal-nitrogen covalency and orbital overlap in bonding interactions with the nitride framework. Here, we show that silicon nitride-supported iron mesityl complexes display divergent reactivity compared to their silica-supported homologues, resisting metallic particle formation under reducing pretreatment conditions (exposure to excess organolithium reagents) and maintaining active iron/lithium speciation under ammonia synthesis conditions that is absent on the oxide support. When the organometallic iron complex on silicon nitride is exposed to excess n-butyllithium, iron remains isolated, catalyzing the conversion of butyllithium to lithium hydride, resulting in a divalent iron site in a polyhydride environment. In contrast, the silica-supported complex is converted to reduced iron clusters without forming persistent isolated hydrides. These structural differences lead to markedly different catalytic behaviors under ammonia synthesis conditions. The Li/Fe/Si 3 N 4 catalyst is highly active (7.5 mol NH 3 /mol Fe/h at 300 °C, 10 bar, or 46 mol NH 3 /mol Fe/h at 400 °C, 10 bar), while both the silica-supported analog and the nonlithiated Si 3 N 4 -supported species are inactive. Notably, this activity is enhanced relative to previously reported iron-lithium hydride composite catalysts (0.43–4.1 mol NH 3 /mol Fe/h at 300 °C, 10 bar) and relative to the industrial benchmark promoted iron catalyst KM1 (3.0 mol NH 3 /mol Fe/h at 400 °C, 10 bar). The catalyst activation and LiH/LiNH x nitrogen reservoir dynamics for Li/Fe/Si 3 N 4 are studied by X-ray Absorption, Mössbauer, and in situ DRIFT spectroscopies and isotopic exchange kinetics.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Microwave-assisted pyrolysis of liquid hydrocarbons using iron-based alumina catalysts obtained by solution combustion synthesis: The effect of synthesis parameters

The microwave-absorbing and catalytic properties of iron-based alumina (FeAl x O y ) materials have enabled their use as catalysts for the microwave-assisted generation of hydrogen and carbon via pyrolysis of hydrocarbons. Solution combustion synthesis (SCS) is a promising method to fabricate these materials, but the pyrolysis performance still needs to be improved. The present work investigated how altering the SCS parameters affects the pyrolysis of diesel fuel, gasoline, and crude oil. Two fuels (citric acid and glycine), four Fe:Al molar ratios, and two heating modes (hotplate and furnace) were tested. Fe/γ-Al 2 O 3 and Fe/β-SiC catalysts were prepared via incipient wetness impregnation for comparison. Among the three fossil fuels tested, diesel fuel yielded the highest amounts of H 2 and least amounts of CO x . The choice of fuel for the SCS process and the Fe/Al ratio strongly affected pyrolysis performance as they influence properties important for both catalysis and microwave absorption. The use of glycine resulted in catalysts that exhibited high H 2 yield and low CO 2 generation, which is explained by the revealed structural differences. The increase in the Fe:Al molar ratio accelerated microwave heating by adding more magnetic loss but also increased the amount of CO x . When the optimal SCS parameters were used, FeAl x O y catalysts outperformed Fe/γ-Al 2 O 3 and Fe/β-SiC. The high H 2 generation efficiency of the SCS catalysts is explained by their enhanced microwave-absorption properties. Scanning electron microscopy and energy dispersive X-ray spectroscopy revealed the formation of large-diameter CNTs via the tip-growth mechanism. The regeneration of SCS catalysts was demonstrated via the Boudouard reaction.

Carbon nanotubes↗
DOE OSTI2026

Synthesis of ARM User Facility Surface Rainfall Datasets to Construct a Best Estimate Value Added Product (PrecipBE)

Surface precipitation measurements are essential for Earth system model (ESM) evaluation and understanding cloud processes. An ever-growing need for robust, temporally evolving, and easy-to-use statistical datasets provides motivation for a baseline ground-based precipitation properties data product. The U.S. Department of Energy Atmospheric Radiation Measurement (ARM) user facility operates an extensive suite of precipitation instruments with various sensitivities and operating mechanisms, which render the decision of which instrument to use based on one or more fixed thresholds challenging and prone to errors and bias. Using a long-term instrument inter-comparison from a unique per-precipitation event perspective, rather than instantaneous sample comparison, we demonstrate that ARM rainfall-measuring instruments are generally consistent with each other at the statistical level. Inter-instrument deviations at the single event level can be large, especially for specific rainfall event properties such as maximum precipitation rates. A machine-learning (ML) analysis using a random forest regressor indicates that in some cases, depending on instrument, local site climatology, and/or specific deployment configuration, certain atmospheric state variables influence the measured quantities in an unpredictable manner. Thus, a-priori weighting of different instruments does not necessarily lead to more accurate and less biased synthesis of instrument data. These results motivate the design of the ARM precipitation best-estimate (PrecipBE) value-added product, which incorporates all valid precipitation data while considering data quality and other instrument limitations. PrecipBE consists of time series and tabular statistics datasets in an easy-to-use and insightful per-precipitation event format. It provides a large set of precipitation event properties supplemented with ancillary data from ARM datasets that correspond to the detected precipitation events. We describe the PrecipBE algorithm and demonstrate its use via the examination of a single-day output as well as a long-term trend analysis of precipitation events at the ARM Southern Great Plains (SGP) site, covering more than 30 years of data. The trend analysis tentatively suggests a long-term temporal tendency for mainly shorter and less intense precipitation events at the SGP site, but a long-term increase in annual rainfall by more than 36 mm (5 %) per decade. This rainfall trend is catalyzed primarily by more extreme event properties of relatively rare, intense precipitation events, with event total and 1 min maximum precipitation rate at a 1 year timeframe increasing up to 5 mm and 9 mm h −1 (several percent) per decade, respectively. While the currently available PrecipBE datasets (at https://adc.arm.gov/discovery/, last access: 8 December 2025) cover rainfall from multiple ARM deployments up to March 2025, PrecipBE is planned to be expanded to include solid-phase precipitation and will soon become an operational product with a several-day lag from real-time. We invite the ARM user community to leverage this new product and welcome user feedback to further enhance the dataset.

Silber, Israel [Pacific Northwest National Laborat↗
DOE OSTI2024

UZrCN Synthesis via Arc Melting - A Novel Synthesis Study

The next generation of nuclear reactors for both power production and space nuclear propulsion require fuel that is more durable, thermally stable, and more thermally conductive to support rapid heat transfer. High temperature gas reactors (HTGR), advanced gas reactors (AGR), and space-based nuclear thermal propulsion (NTP) are advanced reactor concepts that require a fuel type that can withstand high temperatures (1000-2900K) and flow of corrosive gas coolants such as helium, hydrogen, and carbon dioxide. One fuel with the potential to meet these demanding requirements is uranium-zirconium-carbonitride (UZrCN). UZrCN has many favorable fuel qualities compared to other eligible fuel forms such as uranium dioxide (UO2) and uranium mononitride (UN) that could support the aforementioned reactor concepts. UZrCN has an exceptionally high operating temperature and thermal conductivity which are highly desirable to improve reactor economics and safety. It far exceeds the properties of UO2 which is the most common fuel form in the United States. UZrCN also surpasses UN in terms of thermal conductivity and operating temperature by eliminating the dissociation problem UN has at 1700K. UZrCN could improve gas reactor performance and enable NTP technologies; however, it is an under-researched fuel that lacks rigorous scientific study. In recent efforts by the Idaho National Laboratory, a variety of novel methods to produce this fuel composition have been explored. One such method is via arc melting of uranium, zirconium, and carbon under a nitrogen atmosphere. Alloy fabrication using arc melting has been utilized for close to 150 years now and is well-understood as a method for rapid alloy prototyping. This process will be used to perform in-situ nitriding to form UZrCN.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Carbon Negative Synthesis of Amino Acids Using a Cell-Free-Based Biocatalyst

Biological systems can directly upgrade carbon dioxide (CO 2 ) into chemicals. The CO 2 fixation rate of autotrophic organisms, however, is too slow for industrial utility, and the breadth of engineered metabolic pathways for the synthesis of value-added chemicals is too limited. Biotechnology workhorse organisms with extensively engineered metabolic pathways have recently been engineered for CO 2 fixation. Yet, their low carbon fixation rate, compounded by the fact that living organisms split their carbon between cell growth and chemical synthesis, has led to only cell growth with no chemical synthesis achieved to date. Here, we engineer a lysate-based cell-free expression (CFE)-based multienzyme biocatalyst for the carbon negative synthesis of the industrially relevant amino acids glycine and serine from CO 2 equivalents–formate and bicarbonate–and ammonia. The formate-to-serine biocatalyst leverages tetrahydrofolate (THF)-dependent formate fixation, reductive glycine synthesis, serine synthesis, and phosphite dehydrogenase-dependent NAD(P)H regeneration to convert 30% of formate into serine and glycine, surpassing the previous 22% conversion using a purified enzyme system. We find that (1) the CFE-based biocatalyst is active even after 200-fold dilution, enabling higher substrate loading and product synthesis without incurring additional cell lysate cost, (2) NAD(P)H regeneration is pivotal to driving forward reactions close to thermodynamic equilibrium, (3) balancing the ratio of the formate-to-serine pathway genes added to the CFE is key to improving amino acid synthesis, and (4) efficient THF recycling enables lowering the loading of this cofactor, reducing the cost of the CFE-based biocatalyst. To our knowledge, this is the first synthesis of amino acids that can capture CO 2 equivalents for the carbon negative synthesis of amino acids using a CFE-based biocatalyst. Looking ahead, the CFE-based biocatalyst process could be extended beyond serine to pyruvate, a key intermediate, to access a variety of chemicals from aromatics and terpenes to alcohols and polymers.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Assessment of the Impact of Realistic Sensor Physics and the Integration of Ex-Core Sensors on Reactor Power Synthesis

In the work documented in this report, a weighting function–based core power synthesis method was applied to multiple Monte Carlo N-Particle (MCNP) reactor models, which are informed based on simulated self-powered neutron detector (SPND) responses. The weighting function method used has been coined the point-based iterative (PBI) method. The goal of this application is to assess the impact of considering realistic sensor physics in the generation of the simulated SPND outputs as well as to consider how the synthesis is impacted based on the inclusion of ex-core detectors in the model. The NuScale small modular reactor (SMR) and Westinghouse AP1000 pressurized water reactor (PWR) are the models that served as the testbeds for the assessment of realistic sensor physics; this was achieved by using Geant4 SPND models in comparison with analytical models, such that the effect of electron transport in realistic SPND geometries in the Geant4 model can be understood in terms of synthesis error and convergence time. The comparison was considered for fuel burnup–induced perturbations, for a range of sensor string densities and synthesized power distribution axial fidelities. The Texas A&M Testing, Research, Isotopes, General Atomics Reactor (TAMU TRIGA) reactor MCNP model was used to assess the impact of ex-core sensors; this was done by performing synthesis with and without the ex-core detectors and by quantifying the synthesis error and number of iterations associated with Gaussian-type perturbations in many locations in the core. The TAMU TRIGA model was particularly pertinent for this study because of the interest in future experimental tests with SPNDs in this reactor, as well as the ease of modifying the MCNP model to include ex-core detectors with heterogeneously described response functions. Results from the comparison between the Geant4 and analytical SPND models indicate that similar average and maximum synthesis errors were obtained for burnup-induced perturbations in both the NuScale SMR and the AP1000. This was true for a range of sensor string densities and axial fidelities. However, there were marked differences between both the Geant4 and analytically informed models in terms of the iterations required to converge on the synthesized power distribution. Namely, the Geant4-informed models tended to lead to fewer iterations, except for a few sensor–core configurations that had particularly numerous iterations. Results from the ex-core sensor assessment with the TAMU TRIGA model indicate that the inclusion of ex-core sensors drastically reduces the synthesis error of Gaussian-type perturbations close to the edge of the core, and it slightly reduces synthesis errors for perturbations closer to the center of the core. This was achieved with a minimal increase in computational cost—that is, the number of iterations required for convergence. The errors were identified to be in the same location as the perturbation in the core, indicating that the methodology remains robust for unperturbed regions of the core. A secondary result from this study with the TAMU TRIGA was yielded by analysis of the neutron flux levels in the in-core and ex-core sensor locations of the core; these flux levels indicate that SPNDs could be used as both in-core and ex-core sensors, so long as the emitter material is sensitive to thermal neutrons. The results from these studies provide a quantitative understanding of the importance of considering realistic sensor physics and including ex-core sensors to perform accurate and timely power distribution synthesis of a reactor core.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2025

Synthesis Roadmap for Actinide Chloride Salts

Molten salt reactors (MSRs) are among the main advanced nuclear reactor types at the forefront of development by industry, with the support of the US government, for the next fleet of nuclear reactors to support the demand for energy in the coming decades. MSRs are highly unique because they are cooled and typically also fueled by molten salt. This quality brings about safety benefits such as low-pressure operation and self-stabilization of the neutron flux, operational benefits such as high-temperature operation and the ability for online refueling, and fuel and waste management benefits thanks to the flexibility of post-processing of molten salts and reprocessing options that involve removal of fission products and actinide separation. In fact, domestic deployment of molten salt (or molten salt–cooled) reactors is an approaching reality: a handful of molten salt reactor developers are planning to operate demonstration-scale reactors, as a step toward commercial-scale power reactors, within the decade. For example, Natura Resources received a construction permit in September 2024 for the deployment of MSR-1, which is a graphite-moderated thermal spectrum reactor, at Abilene Christian University. Also, TerraPower, in a collaborative effort with Southern Company and Idaho National Laboratory (INL), received approval from DOE in 2023 to proceed with the construction of the Molten Chloride Reactor Experiment (MCRE), a homogeneous chloride fast reactor at INL, and has begun assembly of system components. There are several other examples of developers at different stages of development of their own unique MSR designs (Jenet et al., 2025). As developers are in the process of obtaining approvals for their designs, deploying demonstration-scale reactors, and planning for their commercial-scale power reactors, there is a critical supply chain need for the synthesis of fuel for these reactors that must be addressed. The challenge generally is three-fold: (1) the quantity of fueled salt needed for these reactors is extraordinarily high (>100s of kilograms), but demonstrations of scaled-up techniques for fueled salt synthesis are significantly more limited than demonstrations of lab-scale syntheses; (2) each developer has a unique reactor design, which means different actinide halide elements in different carrier salts must be synthesized; and (3) there is a need for particularly high-purity salt so as to ensure the long-term operability of these reactors with minimal degradation to salt-wetted components, which necessitates synthesis techniques with high levels of quality control, repeatability, and well-characterized precursor and reactant materials. It is crucial that this supply chain challenge be addressed by demonstrating synthesis techniques that are scalable, de-risked, and well-documented so that these technologies may be adopted and utilized by industry to support the fueling needs of MSRs that are to come online within the next 10 years. With this supply chain challenge clearly defined for the developing MSR industry, it is important to consider that addressing such a challenge is oftentimes complex and context-dependent. There is not necessarily a single synthesis technique that can be scaled up and adopted to address the needs of all MSR developers; the synthesis approach that may be viable for producing a desired fuel salt will be entirely dependent on the exact salt composition needed, the quantity needed, purity needed, the refueling and waste plans, and the availability of a carrier salt for the fuel. Therefore, it is important to consider more broadly what synthesis techniques are available and have been demonstrated to understand the benefits, challenges, and general nuances that should be considered when evaluating a particular route for efficient production of high-purity fuel salts at scale.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2025

Cell-Free-Based Thermophilic Biocatalyst for the Synthesis of Amino Acids from One-Carbon Feedstocks

Bioproduction from one-carbon compounds, such as formate, is an attractive prospect due to reduced energy requirements and the possibility for using CO 2 as a sustainable feedstock. Formate-fixing pathways engineered using Escherichia coli lysate-based cell-free expression (CFE) biocatalysts have the potential to route 100% of feedstock carbon toward chemical synthesis but are undermined by siphoning of in-pathway metabolites and cofactors by the CFE background metabolism. To address this limitation, we engineer a CFE-based thermophilic multienzyme biocatalyst for the synthesis of serine and glycine from formate, bicarbonate, and ammonia. After expression of the thermophilic formate-to-serine pathway in a one-pot reaction, the mesophilic E. coli CFE background machinery is removed by simple heat denaturation, eliminating the siphoning of cofactors, inpathway metabolites, and products. After bioprocess optimization, including pathway gene expression duration and chemical synthesis temperature, we achieve near stoichiometric conversion of formate and bicarbonate to serine and glycine, reaching 97% of stoichiometric yield. The use of a moderately thermophilic biocatalyst allowed chemical synthesis to take place at mesophilic temperatures, enabling the balance of optimal enzyme activity with minimal metabolite/cofactor thermal degradation. In a fed-batch experiment, the biocatalyst shows sustained chemical synthesis rates for 8 h, paving the way toward a continuous bioprocess. Finally, a sensitivity analysis of cofactor usage revealed that the most expensive cofactors, THF and NADPH, can be reduced by 5-fold without significantly lowering product yields. To the best of our knowledge, this is the first instance of expressing a thermophilic pathway in an E. coli lysate-based CFE system to generate a thermophilic biocatalyst for use at mesophilic temperatures. The CFEbased thermophilic formate-to-serine biocatalyst triples the combined serine and glycine yield previously obtained by a CFE-based mesophilic formate-to-serine biocatalyst (30%), and quadruple the yield obtained by a purified enzyme system (22%). Ultimately, this work opens the door to using E. coli lysate-based CFE for thermophilic biocatalyst generation to achieve high chemical synthesis yields.

bacteria↗
DOE OSTI2024

Interzeolite Transformation through Cross-Nucleation: A Molecular Mechanism for Seed-Assisted Synthesis

Polymorph selection and efficient crystallization are central goals in zeolite synthesis. Crystalline seeds are used for both purposes. While it has been proposed that zeolite seeds induce interzeolite transformation by dissolving into structural units that promote nucleation of the daughter crystal, the seed’s structural elements do not always match those of the target zeolite. This discrepancy raises the question of how the seed promotes the daughter phase. Here, we present the first molecularly resolved investigation of seed-assisted zeolite synthesis. Using molecular simulations, we reproduce the experimental finding that a parent zeolite can promote the nucleation of a daughter zeolite even when it lacks common composite building units (CBUs) or crystal planes. Modeling the seed-assisted synthesis of an AFI-type zeolite using zeolite CHA, our simulations indicate that stand-alone CBUs from the parent seed do not facilitate daughter crystal formation. However, introducing the intact seed significantly reduces the synthesis time, supporting that seed integrity is key to increased efficiency. This reduction arises from the cross-nucleation of the AFI-type zeolite on the CHA (001) face. We find that parent and daughter zeolites are connected by an interfacial transition layer with an order distinct from that of both zeolites. Simulations reveal that cross-nucleation occurs over a broad range of synthesis conditions. We argue that cross-nucleation would be most favorable for zeolite pairs that share crystalline planes such as those forming intergrowths. In conclusion, our findings suggest that the prevalence of intergrowths with a common lattice plane in zeolite synthesis is likely a kinetic effect of accelerated cross-nucleation.

Crystallization↗
DOE OSTI2025

Rapid Oxidation of Uranium Steel Alloys: Combustion Synthesis

This project explored the use of combustion synthesis as a rapid, high-temperature method for oxidizing uranium-bearing steel alloys. Traditional laboratory-scale synthesis methods often fail to replicate the thermal and kinetic conditions experienced by real-world particulates, particularly those formed under rapid quenching or high-temperature scenarios. Combustion synthesis offers a promising alternative by enabling fast, localized heating and flexible precursor selection. A series of targeted experiments were conducted using a U 2 NiCrFe 4 alloy as the precursor. The alloy was oxidized using combustion synthesis reactions fueled by uranyl nitrate and glycine, achieving peak temperatures exceeding 1,200 °C. Postreaction analysis using scanning electron microscopy (SEM), elemental mapping, and Raman spectroscopy revealed the formation of iron-based oxides, with limited but detectable evidence of uranium oxide phases such as UO 2 . The results indicate that under the rapid reaction and cooling conditions of combustion synthesis, iron oxides form preferentially, but uranium oxide formation is kinetically limited. These findings validate combustion synthesis as a viable method for simulating the oxidation behavior of uranium steels in extreme environments and lay the groundwork for future studies aimed at enhancing uranium oxide formation through higher temperatures or modified precursor compositions.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Impact of Time Dependent Reactor and Sensor Physics on Core Power Synthesis

Online synthesis of the power distribution is critical in the operation and control of nuclear power reactors to ensure that the core is operating within safety margins, and to provide essential knowledge associated with the burnup of the fuel. In light water reactors (LWRs), power synthesis is achieved by using some a priori knowledge of the state of the reactor core and updating based on the signals coming from in-core sensors—namely, self-powered neutron detectors (SPNDs). This report aims to study the effects of fuel burnup and sensor degradation on the ability to accurately synthesize the power distribution in a LWR. Several modeling tools were used to simulate power synthesis based on the responses of SPNDs, with emitters made out of Rh or V. A representative pressurized water reactor low-enriched uranium (LEU) core was modeled using the Polaris/Purdue Advanced Reactor Core Simulator (PARCS) approach. The Monte Carlo N-Particle Transport 6 (MCNP6) code was used, as well, to calculate response functions between different segments of fuel to individual SPNDs; this is a crucial parameter for power synthesis. The Oak Ridge Isotope GENeration (ORIGEN) package in the Standardized Computer Analyses for Licensing Evaluation (SCALE) code was used to model the time-dependent isotopic transmutation in the SPND emitters. All these data were fed into a custom code that enacted the point-based iterative (PBI) method to simulate power synthesis. Developmental work was also performed on high-fidelity SPND models in the GEometry ANd Tracking 4 (Geant4) code, which enables higher-accuracy modeling of the current responses from SPNDs. In this work, five sets of time-dependent power synthesis test cases were conducted. In these test cases, systematic changes in the input conditions enabled an analysis of the effect of (1) slightly inaccurate a priori power distribution assumptions with respect to fuel burnup, (2) highly inaccurate a priori assumptions with respect to fuel burnup (such that burnup is not included in the a priori assumed distribution), and (3) differences between Rh and V SPNDs in terms of downstream consequences of the transmutation in the emitters. The authors discovered that one may permissibly have slightly inaccurate a priori assumptions of the fuel burnup (such that the level of burnup may be slightly under- or over-approximated by the accumulated burnup in approximately 9.3 full power days), but to not account for burnup at all in the a priori assumption leads to severe levels of error, approaching 25% at maximum. The authors also discovered that V SPNDs are extraordinarily robust in the low-enriched uranium fuel cycle considered in this modeling work, whereas Rh SPNDs undergo significant transmutation that can result in large errors in the synthesized power distribution.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2026

Impact of Time-Dependent Reactor and Sensor Physics on Core Power Synthesis (Rev.1)

Online synthesis of power distribution is critical in the operation and control of nuclear power reactors to ensure that the core is operating within safety margins and to provide essential knowledge associated with the burnup of the fuel. In light-water reactors, power synthesis is achieved by using some a priori knowledge of the state of the reactor core and updating based on the signals coming from in-core sensors—namely, self-powered neutron detectors (SPNDs). This report examines the effects of fuel burnup and sensor degradation on the ability to accurately synthesize the power distribution in a pressurized water reactor (PWR), considering the typical low-enriched uranium (LEU, 3%-5% enrichment) fuel cycle as well as the higher enrichment LEU+ (5%-8% enrichment) fuel cycle. Several modeling tools were used to simulate power synthesis based on the responses of SPNDs, with emitters made out of Rh or V. A representative PWR LEU core was modeled using the Polaris/Purdue Advanced Reactor Core Simulator (PARCS) approach. The Monte Carlo N-Particle Transport 6 (MCNP6) code was used as well to calculate response functions between different segments of fuel to individual SPNDs; this is a crucial parameter for power synthesis. The Oak Ridge Isotope GENeration (ORIGEN) package in the Standardized Computer Analyses for Licensing Evaluation (SCALE) code was used to model the time-dependent isotopic transmutation in the SPND emitters. All these data were fed into a custom code that enacted the point-based iterative method to simulate power synthesis. Developmental work was also performed on high-fidelity SPND models in the GEometry ANd Tracking 4 (Geant4) code, which enables higher-accuracy modeling of the current responses from SPNDs. In this work, five sets of time-dependent power synthesis test cases were conducted. In these test cases, systematic changes in the input conditions enabled an analysis of the effect of (1) slightly inaccurate a priori power distribution assumptions with respect to fuel burnup, (2) highly inaccurate a priori power distribution assumptions with respect to fuel burnup (such that burnup is not included in the a priori assumed distribution), and (3) differences between Rh and V SPNDs in terms of downstream consequences of the transmutation in the emitters and the extended nature of the LEU+ fuel cycle in comparison with LEU. The authors discovered that one may permissibly have slightly inaccurate a priori assumptions of the fuel burnup (such that the level of burnup may be slightly underapproximated or overapproximated by the accumulated burnup in approximately 9.3 full power days), but to not account for burnup at all in the a priori assumptions leads to severe levels of error, approaching 25% at maximum (for LEU). The authors also discovered that V SPNDs are extraordinarily robust in both the LEU and LEU+ fuel cycles considered in this modeling work, whereas Rh SPNDs undergo significant transmutation that can result in large errors in the synthesized power distribution.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2025

AI‐Driven Robot Enables Synthesis‐Property Relation Prediction for Metal Halide Perovskites in Humid Atmosphere

Materials Acceleration Platforms (MAPs) – also known as self-driving laboratories– present a new paradigm for materials science and promise an order of magnitude accelerated materials discovery compared to the traditional trial-and-error approach. Metal halide perovskites (MHPs) are an emerging class of materials for optoelectronic applications but are plagued by irreproducible optoelectronic quality, particularly for films fabricated in a humid atmosphere. Here, in this work, a machine learning (ML)-guided closed-loop platform is developed with a multimodal data fusion approach to predict synthesis–property relations for the optical quality of MHP thin films in relative humidities (RHs) ranging from 5–55%. The efficiency of this approach is confirmed by the fast-dropping learning rate to 2% after experimentally sampling less than 1% of the possible 5,000+ combinations. The prediction of synthesis–property relations is done by optical and imaging characterizations. In situ photoluminescence characterization revealed the origin of thin film quality variation at different RH. These insights provide an avenue for controlling the MHP crystallization by fine-tuning the synthesis parameters and RH for a given chemistry, thus lifting the need for stringent atmosphere control. The MAP enables an accelerated screening and understanding of the synthesis design space, facilitating rational synthesis recipe choice for a wide range of materials.

AI-driven robot↗
DOE OSTI2025

Autonomous Nanoparticle Synthesis Guided by In Situ Multiscale Structural Characterization

Autonomous synthesis platforms promise rapid exploration of vast parameter spaces; yet, integrating in situ structural characterization in closed-loop synthesis optimization remains challenging. We demonstrate a realization of such a closed-loop platform coupled with a droplet-flow microreactor, in situ X-ray scattering methods (SAXS/WAXS), and Gaussian process optimization to synthesize citrate-reduced Au nanoparticles with targeted characteristics. The system efficiently explored ∼19,000 synthesis recipes through 365 experiments, achieving precise control over size (4–60 nm) and polydispersity (σ < 0.11) across large citrate/gold ratios, exceeding traditional synthesis boundaries (1–10). Beyond confirming classical Turkevich–Frens trends, partial-dependence analysis revealed strong nonlinear coupling among precursor, citrate, and pH effects. Combining quantitative SAXS/WAXS analysis with electron microscopy characterization, we uncovered that crystallite size (d c ) and particle size (d) follow d c = 0.18d + β, where synthesis chemistry controls the intercept β while maintaining a universal slope. This parallel-band structure enables independent tuning of crystallite domain size at fixed particle diameter through a combination of chloride, gold precursor, citrate, and pH contributions (cross-validated Spearman ρ = 0.7 ± 0.1). High-resolution electron microscopy shows multiple lattice-fringe orientations within single particles, directly confirming polycrystalline domains and the ability to tune d c at the fixed d. The platform’s validation includes indistinguishable static versus flowing measurements, stable droplet transport at 100 °C, and <5% run-to-run variation, establishing a robust framework for mapping and controlling multiscale nanoparticle structure across expansive chemical spaces. In conclusion, the developed closed-loop platform can be applied to a borad range of nanosyntheis processes.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2024

Target of 1 Rapamycin kinase is a positive regulator of plant fatty acid 2 and lipid synthesis

In eukaryotes, Target of Rapamycin (TOR), a conserved protein sensor kinase, integrates a diverse set of environmental cues, including growth factor signals, energy availability, and nutritional status, to direct cell growth. In plants, TOR is activated by light and sugars and regulates a wide range of cellular processes, including protein synthesis and metabolism. Fatty acid synthesis is key to membrane biogenesis that in turn, is required for cell growth. To elucidate the primary regulatory role(s) of TOR in lipid metabolism, we followed fatty acid and lipid changes in plants with altered TOR protein levels or activity for short durations, using Nicotiana benthamiana leaves, Arabidopsis seedlings and Brassica napus cell suspension cultures. Transient expression of TOR significantly elevated the levels of total fatty acids in Nicotiana benthamiana leaves, while treatment of Arabidopsis seedlings with Torin 2, a TOR specific inhibitor, for one day, caused significant reductions in fatty acids and membrane lipids. Similarly, incubating oil-producing Brassica napus suspension culture cells with Torin 2 for eight hours led to significant decreases in the levels of TFA and TAG. Taken together the results from three independent systems presented here establishes that TOR positively regulates lipid synthesis in plants, consistent with its role in animals. Furthermore, RNA-seq analysis of Torin 2-treated Arabidopsis seedlings showed that TOR promotes the upregulation of a number of genes involved in de novo fatty acid synthesis while downregulating genes involved in lipid turnover, which we propose as a mechanistic explanation for its promotion of lipid synthesis and accumulation.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Design, Synthesis, and Evaluation of Noble Metal Nanoparticles and In Situ-Decorated Carbon-Supported Nanoparticle Electrocatalysts Using Hypergolic Reactions

Here, we report the first synthesis of metal nanoparticles and supported metal nanoparticles on carbon by using hypergolic reactions. Specifically, we report the synthesis of noble metal nanoparticles (Pt, Ag, and Au) using sodium hydride (NaH) as both an ignition trigger and a reducing agent for the corresponding metal salt precursors. In addition, we report the one-step, in situ synthesis of Pt nanoparticles supported on carbon by adding sucrose as the carbon source. The hypergolically synthesized nanoparticles display elliptical morphology and are more crystalline compared with those conventionally synthesized in solution using sodium borohydride (NaBH 4 ). When tested as electrocatalysts, the hypergolic Pt nanoparticles exhibit more than 2 times higher specific electrochemical active surface area (ECSA) and a higher half-wave potential (E 1/2 ) of 0.94 V vs the reversible hydrogen electrode (RHE) compared to the conventionally synthesized ones. In addition, the electrocatalyst based on the in situ synthesized carbon that was decorated with the Pt nanoparticles synthesized hypergolically outperforms an analogous, state of the art, commercial PtC system. For example, the former shows an attractive E 1/2 (0.94 V) compared with 0.9 V for the commercial PtC. Accelerated durability tests (ADT) in an alkaline environment add another advantage. After 10 000 cycles, the hypergolically synthesized system shows a smaller reduction of E 1/2 and less degradation compared to the commercial PtC (10 mV compared to ∼30 mV). The work described here represents the first reported synthesis using hypergolic reactions of metal nanoparticles as well as supported metal nanoparticles. The properties of the resulting electrocatalysts demonstrate the versatility and promise of the new approach in materials synthesis and open new avenues for further investigation as electrocatalysts.

Chalmpes, Nikolaos↗