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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.

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At least 181 records · Page 10
All sourcesNASA NTRSDOE OSTI
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 OSTI2023

Structural evolution during solution-based synthesis of Li 7 P 3 S 11 solid electrolyte by synchrotron X-ray total scattering

Solution-based synthesis has emerged as a promising approach for scalable and efficient synthesis of solid electrolytes (SEs). However, the ionic conductivity of solution-synthesized SEs is much lower than that of SEs synthesized by solid state approaches. The structural evolution during the synthesis of SEs is crucial to explaining the decreased ionic conductivities but has not been well understood. Here, in this work, we use synchrotron X-ray total scattering combined with pair distribution function (PDF) analysis to understand the structural evolution during annealing of the solution-processed precursor for the synthesis of Li 7 P 3 S 11 SEs. Combining Bragg diffraction and diffuse scattering, X-ray total scattering enables detection of structural information including phase transition and crystallinity. The results show that the formation of Li 7 P 3 S 11 glass-ceramic starts at 230 °C. Increasing the annealing temperature helps to improve the crystallinity, but the degree of crystallization is still lower than 70.3% even after annealing at 290 °C when thermal decomposition of Li 7 P 3 S 11 to Li 4 P 2 S 6 has occurred. PDF analysis also revealed the existence of acetonitrile used in the solution-based synthesis in the SEs after annealing at high temperatures. The results rationalize the synthesis–property relationship, explain why annealing at 290 °C provides the highest ionic conductivity at the studied temperatures due to an optimal balance for achieving a high crystallinity while suppressing severe decomposition of Li 7 P 3 S 11 , and provide novel insights to develop approaches for synthesizing superior Li 7 P 3 S 11 SEs on a large scale.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Reoptimization of Quantum Circuits via Hierarchical Synthesis

The current phase of quantum computing is in the Noisy Intermediate-Scale Quantum (NISQ) era. On NISQ devices, two-qubit gates such as CNOTs are much noisier than single-qubit gates, so it is essential to minimize their count. Quantum circuit synthesis is a process of decomposing an arbitrary unitary into a sequence of quantum gates, and can be used as an optimization tool to produce shorter circuits to improve overall circuit fidelity. However, the time-to-solution of synthesis grows exponentially with the number of qubits. As a result, synthesis is intractable for circuits on a large qubit scale. In this paper, we propose a hierarchical, block-by-block opti-mization framework, QGo, for quantum circuit optimization. Our approach allows an exponential cost optimization to scale to large circuits. QGo uses a combination of partitioning and synthesis: 1) partition the circuit into a sequence of independent circuit blocks; 2) re-generate and optimize each block using quantum synthesis; and 3) re-compose the final circuit by stitching all the blocks together. We perform our analysis and show the fidelity improvements in three different regimes: small-size circuits on real devices, medium-size circuits on noisy simulations, and large-size circuits on analytical models. Our technique can be applied after existing optimizations to achieve higher circuit fidelity. Further, using a set of NISQ benchmarks, we show that QGo can reduce the number of CNOT gates by 29.9% on average and up to 50% when compared with industrial compiler optimizations such as t|ket). When executed on the IBM Athens system, shorter depth leads to higher circuit fidelity. We also demonstrate the scalability of our QGo technique to optimize circuits of 60+ qubits, Our technique is the first demonstration of successfully employing and scaling synthesis in the compilation tool chain for large circuits. Overall, our approach is robust for direct incorporation in production compiler toolchains to further improve the circuit fidelity.

97 MATHEMATICS AND COMPUTING↗
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 OSTI2022

Synthesis of Hydrophilic Derivative Surfactants From Algae-Derived Unsaponifiable Lipids

In the context of decarbonizing the economy, the utilization of biologically sourced feedstocks to produce replacements for petroleum-derived materials is becoming more urgent. Improving renewable biomass production and utilization is imperative for commercializing future biorefineries. Algae-derived biomass is a particularly promising feedstock thanks to its attractive oil content and composition; specifically, the high-value products in the unsaponifiable lipids have not been included in a conversion process. Here we demonstrate surfactant synthesis from a complex oil fraction as the hydrophobic donor moieties, yielding products that are similar to commercially available surfactants such as the linear alkyl benzene sulfonates. Unsaponifiable lipids extracted from algae were derivatized to non-ionic surfactants using a green chemical synthesis route based on a double esterification with succinic acid and polyethylene glycol. The in-depth molecular and structural surfactant characterization is included and indicates that the resulting properties fall between those of pure cholesterol and phytol used as surrogates for the reaction synthesis demonstration. This is the first demonstration of an effective and potentially high-value synthesis of functional surfactants with properties that can be tailored based on the relative composition of the resulting hydrocarbon alcohol components in the mixture. This novel green chemistry synthesis approach provides a route to high-value product synthesis from algae.

09 BIOMASS FUELS↗
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 OSTI2021

Visualization of Solid-State Synthesis for Chalcogenide Na Superionic Conductors by in-situ Neutron Diffraction

Chalcogenide superionic sodium (Na) conductors are great potential as solid electrolytes (SEs) in all-solid-state Na batteries with advantages of high energy density and safety, and cost effectiveness. For solid Na-ion conductors, their crystal structures and ionically conductive properties are strongly influenced by the synthetic approaches and processing parameters. Thus, understanding the synthesis process is essential to control the structures and phases and thereby yields to Na-ion conductors with desirable properties. Thanks to the high-flux and deep-penetrating time-of-flight neutron diffraction (ND), we employed in situ experiments to track real-time structural changes of two chalcogenide SEs (Na 3 SbS 4 and Na 3 SbS 3.5 Se 0.5 ) during the solid-state synthesis. For these two conductors, the ND results reveal a fast one-step reaction for the synthesis and the molten process when heating up, and the recrystallization as well as the cubic-to-tetragonal phase transition up on cooling. Moreover, Se-doping is found to influence the reaction temperatures, lattice parameter and structure stability based on neutron experimental observations and theoretical simulation. This work presents a detailed structural study using in situ neutron diffraction technology for the solid synthesis process of chalcogenide Na-ion conductors, beneficial for the design and synthesis of new solid-state conductors.

25 ENERGY STORAGE↗
DOE OSTI2020

Mechanisms of mechanochemical synthesis of cesium lead halides: pathways toward stabilization of α-CsPbI 3

Cesium lead iodide with cubic perovskite structure (α-CsPbI 3 ) is gaining significant interest in photovoltaic applications due to its excellent absorbance of the visible solar light and other attractive optoelectronic properties. However, the synthesis of stable α-CsPbI 3 poses a significant challenge. Mechanochemical synthesis is emerging as a suitable method for the preparation of cesium lead halides. This work investigates the ball milling-induced synthesis of cesium lead halides perovskite phase using halide mixing or doping approaches. The synthesis in the CsI + PbI 2 , CsBr + PbBr 2 , CsBr + PbI 2 , and CsI + PbI 2 + NdI 3 mixtures and halide exchange reactions in the CsPbBr 3 + 3KI and CsBr + PbBr 2 + 3KI systems are investigated to elucidate the mechanism of this process. Then, CsPb(I 1–x Br x ) 3 and CsPb( 1–y )Nd y I 3 materials with different x and y ratios are prepared, and their stability is probed in the air using light absorption spectroscopy. These results suggest that Nd doping is more efficient in the stabilization of the perovskite structure than partial replacement of iodine with bromine. Microstructure observations reveal the existence of two different product formation mechanisms depending on the mechanical properties of reactants. The results reveal that the milling temperature has a significant impact on the reaction kinetics. Here, the produced particles nucleate and grow at the reactant interface and retard the synthesis reaction by creating a diffusion barrier. Extended milling reduces the product particle size and creates fresh contact between reactants, thus facilitating reaction completion.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Alkaline Ethanol Oxidation Reaction on Carbon Supported Ternary PdNiBi Nanocatalyst using Modified Instant Reduction Synthesis Method

Direct ethanol fuel cells (DEFC) still lack active and efficient electrocatalysts for the alkaline ethanol oxidation reaction (EOR). In this work, a new instant reduction synthesis method was developed to prepare carbon supported ternary PdNiBi nanocatalysts with improved EOR activity. Synthesized catalysts were characterized with a variety of structural and compositional analysis techniques in order to correlate their morphology and surface chemistry with electrochemical performance. The modified instant reduction synthesis results in well-dispersed, spherical Pd85Ni10Bi5 nanoparticles on Vulcan XC72R support (Pd85Ni10Bi5/C(II-III)), with sizes ranging from 3.7 +/- 0.8 to 4.7 +/- 0.7 nm. On the other hand, the common instant reduction synthesis method leads to significantly agglomerated nanoparticles (Pd85Ni10Bi5/C-(I)). EOR activity and stability of these three different carbon supported PdNiBi anode catalysts with a nominal atomic ratio of 85:10:5 were probed via cyclic voltammetry and chronoamperometry using the rotating disk electrode method. Pd85Ni10Bi5/C-(II) showed the highest electrocatalytic activity (150 mA.cm(-2); 2678 mA.mg(-1)) with low onset potential (0.207 V) for EOR in alkaline medium, as compared to a commercial Pd/C and to the other synthesized ternary nanocatalysts Pd85Ni10Bi5/C-(I) and Pd85Ni10Bi5/C-(III). This new synthesis approach provides a new avenue to developing efficient, carbon supported ternary nanocatalysts for future energy conversion devices. The modified instant reduction method for synthesis of ternary Pd85Ni10Bi5/C-(II) nanocatalyst using Vulcan XC72R as carbon support initiates an agglomeration reduction, provides low average particle size, and enables enhanced activity for the alkaline ethanol oxidation reaction (EOR) compared to the common instant reduction method and to a commercial Pd/C catalyst.

Alkaline direct ethanol fuel cell↗
DOE OSTI2022

Continuum Modeling of Porous Electrodes for Electrochemical Synthesis

Electrochemical synthesis possesses substantial promise to utilize renewable energy sources to power the conversion of abundant feedstocks to value-added commodity chemicals and fuels. Of the potential system architectures for these processes, only systems employing 3-D structured porous electrodes have the capacity to achieve the high rates of conversion necessary for industrial scale. However, the phenomena and environments in these systems are not well understood and are challenging to probe experimentally. Fortunately, continuum modeling is well-suited to rationalize the observed behavior in electrochemical synthesis, as well as to ultimately provide recommendations for guiding the design of next-generation devices and components. In this review, we begin by presenting an historical review of modeling of porous electrode systems, with the aim of showing how past knowledge of macroscale modeling can contribute to the rising challenge of electrochemical synthesis. We then present a detailed overview of the governing physics and assumptions required to simulate porous electrode systems for electrochemical synthesis. Here, leveraging the developed understanding of porous-electrode theory, we survey and discuss the present literature reports on simulating multiscale phenomena in porous electrodes in order to demonstrate their relevance to understanding and improving the performance of devices for electrochemical synthesis. Lastly, we provide our perspectives regarding future directions in the development of models that can most accurately describe and predict the performance of such devices and discuss the best potential applications of future models.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Facile and Scalable Synthesis of Metal- and Nitrogen-Doped Carbon Nanotubes for Efficient Electrochemical CO 2 Reduction

Metal- and nitrogen-doped carbon (M–N–C) is a promising material to catalyze electrochemical CO 2 reduction reaction (CO 2 RR). However, most M–N–C catalysts in the literature require complicated synthesis procedures and produce small quantities per batch, limiting the commercialization potential. In this work, we developed a simple and scalable synthesis method to convert metal-impurity-containing commercial carbon nanotubes (CNTs) and nitrogen-containing organic precursors into M–N–C via one-step moderate-temperature (650 °C) pyrolysis without any other treatment nor the need to add metal precursors. Batches of catalysts in varied mass up to 10 g (150 mL in volume) per batch were synthesized, and repeatable catalytic performances were demonstrated. To the best of our knowledge, the 10 g batch is one of the largest batches of CO2RR catalysts synthesized in the literature while requiring minimal synthesis steps. The catalyst possessed single-atomic iron–nitrogen (Fe–N) sites, enabling a high performance of >95% CO product selectivity at a high current density of 400 mA/cm 2 and high stability for 45 h at 100 mA/cm 2 in a flow cell testing. The catalyst outperformed a benchmark noble-metal nanoparticle catalyst and achieved longer stability than many other reported M–N–C catalysts in the literature. The scalable and cost-effective synthesis developed in this work paves a pathway toward practical CO 2 RR applications. The direct utilization of metal impurities from raw CNTs for efficient catalyst synthesis with minimal treatment is a green and sustainable engineering approach.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
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 OSTI2022

Text-mined dataset of gold nanoparticle synthesis procedures, morphologies, and size entities

Abstract Gold nanoparticles are highly desired for a range of technological applications due to their tunable properties, which are dictated by the size and shape of the constituent particles. Many heuristic methods for controlling the morphological characteristics of gold nanoparticles are well known. However, the underlying mechanisms controlling their size and shape remain poorly understood, partly due to the immense range of possible combinations of synthesis parameters. Data-driven methods can offer insight to help guide understanding of these underlying mechanisms, so long as sufficient synthesis data are available. To facilitate data mining in this direction, we have constructed and made publicly available a dataset of codified gold nanoparticle synthesis protocols and outcomes extracted directly from the nanoparticle materials science literature using natural language processing and text-mining techniques. This dataset contains 5,154 data records, each representing a single gold nanoparticle synthesis article, filtered from a database of 4,973,165 publications. Each record contains codified synthesis protocols and extracted morphological information from a total of 7,608 experimental and 12,519 characterization paragraphs.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
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

Selective CW Laser Synthesis of MoS2 and Mixture of MoS2 and MoO2 from (NH4)2MoS4 Film

Very recently, the synthesis of 2D MoS2 and WS2 through pulsed laser-directed thermolysis can achieve wafer-scale and large-area structures, in ambient conditions. In this paper, we report the synthesis of MoS2 and MoS2 oxides from (NH4)2MoS4 film using a visible continuous-wave (CW) laser at 532 nm, instead of the infrared pulsed laser for the laser-directed thermolysis. The (NH4)2MoS4 film is prepared by dissolving its crystal powder in DI water, sonicating the solution, and dip-coating onto a glass slide. We observed a laser intensity threshold for the laser synthesis of MoS2, however, it occurred in a narrow laser intensity range. Above that range, a mixture of MoS2 and MoO2 is formed, which can be used for a memristor device, as demonstrated by other research groups. We did not observe a mixture of MoS2 and MoO3 in the laser thermolysis of (NH4)2MoS4. The laser synthesis of MoS2 in a line pattern is also achieved through laser scanning. Due to of the ease of CW beam steering and the fine control of laser intensities, this study can lead toward the CW laser-directed thermolysis of (NH4)2MoS4 film for the fast, non-vacuum, patternable, and wafer-scale synthesis of 2D MoS2.

(NH4)2MoS4↗
DOE OSTI2020

Carbohydrate‐binding domains facilitate efficient oligosaccharides synthesis by enhancing mutant catalytic domain transglycosylation activity

Abstract Chemoenzymatic approaches using carbohydrate‐active enzymes (CAZymes) offer a promising avenue for the synthesis of glycans like oligosaccharides. Here, we report a novel chemoenzymatic route for cellodextrins synthesis employed by chimeric CAZymes, akin to native glycosyltransferases, involving the unprecedented participation of a “non‐catalytic” lectin‐like domain or carbohydrate‐binding modules (CBMs) in the catalytic step for glycosidic bond synthesis using β‐cellobiosyl donor sugars as activated substrates. CBMs are often thought to play a passive substrate targeting role in enzymatic glycosylation reactions mostly via overcoming substrate diffusion limitations for tethered catalytic domains (CDs) but are not known to participate directly in any nucleophilic substitution mechanisms that impact the actual glycosyl transfer step. This study provides evidence for the direct participation of CBMs in the catalytic reaction step for β‐glucan glycosidic bonds synthesis enhancing activity for CBM‐based CAZyme chimeras by >140‐fold over CDs alone. Dynamic intradomain interactions that facilitate this poorly understood reaction mechanism were further revealed by small‐angle X‐ray scattering structural analysis along with detailed mutagenesis studies to shed light on our current limited understanding of similar transglycosylation‐type reaction mechanisms. In summary, our study provides a novel strategy for engineering similar CBM‐based CAZyme chimeras for the synthesis of bespoke oligosaccharides using simple activated sugar monomers.

Bandi, Chandra Kanth↗