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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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All sourcesNASA NTRSDOE OSTI
DOE OSTI2019

Semi-supervised machine-learning classification of materials synthesis procedures

Digitizing large collections of scientific literature can enable new informatics approaches for scientific analysis and meta-analysis. However, most content in the scientific literature is locked-up in written natural language, which is difficult to parse into databases using explicitly hard-coded classification rules. In this work, we demonstrate a semi-supervised machine-learning method to classify inorganic materials synthesis procedures from written natural language. Without any human input, latent Dirichlet allocation can cluster keywords into topics corresponding to specific experimental materials synthesis steps, such as “grinding” and “heating”, “dissolving” and “centrifuging”, etc. Guided by a modest amount of annotation, a random forest classifier can then associate these steps with different categories of materials synthesis, such as solid-state or hydrothermal synthesis. Finally, we show that a Markov chain representation of the order of experimental steps accurately reconstructs a flowchart of possible synthesis procedures. Our machine-learning approach enables a scalable approach to unlock the large amount of inorganic materials synthesis information from the literature and to process it into a standardized, machine-readable database.

36 MATERIALS SCIENCE↗
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 OSTI2012

ON THE RELIABILITY OF POLARIZATION ESTIMATION USING ROTATION MEASURE SYNTHESIS

We benchmark the reliability of the rotation measure (RM) synthesis algorithm using the 1005 Centaurus A field sources of Feain et al. The RM synthesis solutions are compared with estimates of the polarization parameters using traditional methods. This analysis provides verification of the reliability of RM synthesis estimates. We show that estimates of the polarization parameters can be made at lower signal-to-noise ratio (S/N) if the range of RMs is bounded, but reliable estimates of individual sources with unusual RMs require unconstrained solutions and higher S/N. We derive from first principles the statistical properties of the polarization amplitude associated with RM synthesis in the presence of noise. The amplitude distribution depends explicitly on the amplitude of the underlying (intrinsic) polarization signal. Hence, it is necessary to model the underlying polarization signal distribution in order to estimate the reliability and errors in polarization parameter estimates. We introduce a Bayesian method to derive the distribution of intrinsic amplitudes based on the distribution of measured amplitudes. The theoretically derived distribution is compared with the empirical data to provide quantitative estimates of the probability that an RM synthesis solution is correct as a function of S/N. We provide quantitative estimates of the probability that any given RM synthesis solution is correct as a function of measured polarized amplitude and the intrinsic polarization amplitude compared to the noise.

79 ASTRONOMY AND ASTROPHYSICS↗
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 OSTI2019

Accumulation-Driven Surfactant-Free Synthesis of Architectured Immiscible Metallic Nanoalloys with Enhanced Catalysis

Accumulation-mediated chemical reactions are a ubiquitous phenomenon in nature. In this work, we explore microbubble-induced accumulation of precursor ions to achieve surfactant-free synthesis of immiscible metallic nanoalloys and simultaneously pattern the nanoalloys into targeted architectures for their enhanced catalytic applications. Additionally, our unified spatiotemporal synthesis and structuring (US3) strategy, whereby millisecond-scale accumulation of the ions takes place in a highly confined laser-mediated microbubble trap (MBT), drives ultrafast alloy synthesis in sync with the structuring process. As a case in point, we employ the US3 strategy for the in situ surfactant-free synthesis and patterning of traditionally immiscible rhodium-gold (RhAu) nanoalloys. Stochastic random walk simulations justify the millisecond-scale accumulation process, leading to a 3-order reduction in synthesis time. The catalytic activity and structure-property relationship were evaluated using the reduction of p-nitrophenol with NaBH4. Our in situ synthesis and structuring strategy can be translated for high-throughput production and screening of multimetallic systems with tailored catalytic, optoelectronic, and magnetic functions.

36 MATERIALS SCIENCE↗
DOE OSTI2016

Basic Research Needs Workshop on Synthesis Science for Energy Relevant Technology

The technology that lies at our fingertips becomes more powerful each day. Smartphones connect us instantly to family, friends, and co-workers around the globe; give us access to a limitless stream of information; control the heating in our homes; and serve as our cameras, calculators, flashlights, music players, boarding passes and, on occasion, our phones. Cars are ever more fuel-efficient, safer, semi-autonomous, and have more computing power than the systems that guided humankind to the moon. LED lighting and solar panels are becoming commonplace, replacing less efficient technologies and expanding the energy options available worldwide. Novel polymers and nanoparticles are playing a crucial role in enhanced oil recovery. None of these advances would have been possible without the discovery and development of, and ability to create, new materials and chemical processes. Now imagine what our world would be like if we could accelerate those discoveries a thousandfold. What if the only limit to synthesizing new forms of matter were the imagination? We could build complex assemblies of atoms and molecules with architectures and capabilities far exceeding those of materials found in nature—for example, develop catalysts that turn garbage into fuels, design solar cells to power our homes directly from sunlight, make batteries with the energy density of gasoline, and create one- and two-dimensional solids that transport charge hundreds of times faster than silicon or allow us to build quantum bits based on the spins of electrons or photons to realize the promise of “beyond Moore’s law” computing. Advances in synthesis science are required to bring about this future—we not only must know how to design new molecules and materials with desired functions and properties through theory and computational techniques; we also must be able to make the materials we envision. New approaches to discovering as yet unimagined matter require a sea change in the way we think about the science of synthesis. Chemical and materials sciences have traditionally focused on understanding structure–function relationships with the goal of predicting where the atoms should be placed to achieve a targeted property or process. Much less effort has been directed toward a predictive science of synthesis—understanding how to get the atoms where they need to go to achieve the desired structure. This report, which is the result of the Basic Energy Sciences Workshop on Basic Research Needs for Synthesis Science for Energy Technologies, lays out the scientific challenges and opportunities in synthesis science. The workshop was attended by more than 100 leading national and international scientific experts. Its five topical and two crosscutting panels identified four priority research directions (PRDs) for realizing the vision of predictive, science-directed synthesis.

99 GENERAL AND MISCELLANEOUS↗
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↗
NASA NTRS1999

The Effects of Gravity on Combustion and Structure Formation During Synthesis of Advanced Materials

Combustion in a variety of heterogeneous systems, leading to the synthesis of advanced materials, is characterized by high temperatures (2000-3500 K) and heating rates (up to 10(exp 6) K/s) at and ahead of the reaction front. These high temperatures generate liquids and gases which are subject to gravity-driven flow. The removal of such gravitational effects is likely to provide increased control of the reaction front, with a consequent improvement in control of the microstructure of the synthesized products. Thus, microgravity experiments can lead to major advances in the understanding of fundamental aspects of combustion and structure formation under the extreme conditions of the combustion synthesis wave. In addition, the specific features of microgravity environment allow one to produce unique materials, which cannot be obtained under terrestrial conditions. The general goals of the current research are: 1) to improve the understanding of fundamental phenomena taking place during combustion of heterogeneous systems, 2) to use low-gravity experiments for insight into the physics and chemistry of materials synthesis processes, and 3) based on the obtained knowledge, to optimize processing conditions for synthesis of advanced materials with desired microstructures and properties. This research follows logically from the results of investigations we have conducted in the framework of our previous grant on gravity influence on combustion synthesis (CS) of gasless systems. Prior work, by others and by us, has clearly demonstrated that gravity plays an important role during combustion synthesis of materials. The immediate tasks for the future are to quantitatively identify the nature of observed effects, and to create accurate local kinetic models of the processes, which can lead to a control of the microstructure and properties of the synthesized materials. In summary, this is the value of the proposed research. Based on our prior work, we focus on the fundamental aspects of combustion and structure formation under the unique condition of microgravity.

Varma, A.↗
DOE OSTI2015

Recent progress in the synthesis of metal–organic frameworks

Metal–organic frameworks (MOFs) have attracted considerable attention for various applications due to their tunable structure, porosity and functionality. In general, MOFs have been synthesized from isolated metal ions and organic linkers under hydrothermal or solvothermal conditions via one-spot reactions. The emerging precursor approach and kinetically tuned dimensional augmentation strategy add more diversity to this field. In addition, to speed up the crystallization process and create uniform crystals with reduced size, many alternative synthesis routes have been explored. Recent advances in microwave-assisted synthesis and electrochemical synthesis are presented in this review. In recent years, post-synthetic approaches have been shown to be powerful tools to synthesize MOFs with modified functionality, which cannot be attained via de novo synthesis. In this study, some current accomplishments of post-synthetic modification (PSM) based on covalent transformations and coordinative interactions as well as post-synthetic exchange (PSE) in robust MOFs are provided.

36 MATERIALS SCIENCE↗
DOE OSTI2016

Scope and Limitations of Fmoc Chemistry SPPS-Based Approaches to the Total Synthesis of Insulin Lispro via Ester Insulin

We have systematically explored three approaches based on 9-fluorenylmethoxycarbonyl (Fmoc) chemistry solid phase peptide synthesis (SPPS) for the total chemical synthesis of the key depsipeptide intermediate for the efficient total chemical synthesis of insulin. The approaches used were: stepwise Fmoc chemistry SPPS; the “hybrid method”, in which maximally protected peptide segments made by Fmoc chemistry SPPS are condensed in solution; and, native chemical ligation using peptide-thioester segments generated by Fmoc chemistry SPPS. A key building block in all three approaches was a Glu[O-β-(Thr)] ester-linked dipeptide equipped with a set of orthogonal protecting groups compatible with Fmoc chemistry SPPS. We report the most effective method for the preparation of the 51 residue ester-linked polypeptide chain of ester insulin was the use of unprotected peptide-thioester segments, prepared from peptide-hydrazides synthesized by Fmoc chemistry SPPS, and condensed by native chemical ligation. High-resolution X-ray crystallography confirmed the disulfide pairings and three-dimensional structure of synthetic insulin lispro prepared from ester insulin lispro by this route. Further optimization of these pilot studies could yield an efficient total chemical synthesis of insulin lispro (Humalog) based on peptide synthesis by Fmoc chemistry SPPS.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2011

Insight into methanol synthesis from CO2 hydrogenation on Cu(111): Complex reaction network and the effects of H2O

Methanol synthesis from CO2 hydrogenation on supported Cu catalysts is of considerable importance in the chemical and energy industries. Although extensive experimental and theoretical efforts have been carried out in the past decades, the most fundamental questions such as the reaction mechanisms and the key reaction intermediates are still in debate. In the present work, a comprehensive reaction network for CO2 hydrogenation to methanol on Cu(111) was studied using periodic density functional theory (DFT) calculations. All of the elementary reaction steps in the reaction network were identified in an unbiased way with the dimer method. Our calculation results show that methanol synthesis from direct hydrogenation of formate on Cu(111) is not feasible due to the high activation barriers for some of the elementary steps. Instead, we find that CO2 hydrogenation to hydrocarboxyl (trans-COOH) is kinetically more favorable than formate in the presence of H2O via a unique proton transfer mechanism. The trans-COOH is then converted into hydroxymethylidyne (COH) via dihydroxycarbene (COHOH) intermediates, followed by three consecutive hydrogenation steps to form hydroxymethylene (HCOH), hydroxymethyl (H2COH), and methanol. This is consistent with recent experimental observations [1], which indicate that direct hydrogenation of formate will not produce methanol under dry hydrogen conditions. Thus, both experiment and computational modeling clearly demonstrate the important role of trace amounts of water in methanol synthesis from CO2 hydrogenation on Cu catalysts. The proposed methanol synthesis route on Cu(111) not only provides new insights into methanol synthesis chemistry, but also demonstrates again that spectroscopically observed surface species are often not critical reaction intermediates but rather spectator species. Pacific Northwest National Laboratory is operated by Battelle for the US Department of Energy.

08 HYDROGEN↗
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 OSTI2019

Synthesis of Nickel-Doped Ceria Catalysts for Selective Acetylene Hydrogenation

Metallic nickel is known to be an active, but not a selective hydrogenation catalyst for conversion of alkynes to alkenes. On the other hand, nickel oxide is not active. Recently, we have demonstrated that nickel doped into ceria provides an inexpensive catalyst for selective hydrogenation of acetylene in the presence of ethylene. Here, we evaluate various synthesis methods to achieve optimal selective hydrogenation performance. We examined incipient wetness impregnation, coprecipitation, solution combustion, and sol-gel synthesis to study how the method of preparation affects catalytic structure and behavior. Sol-gel synthesis, coprecipitation, and solution combustion synthesis methods favor nickel incorporation into the ceria lattice, while incipient wetness impregnation creates segregated nickel species on the ceria surface. For hydrogenation of acetylene, these nickel surface species lead to poor ethylene selectivity due to ethane and oligomer formation. However, when nickel is incorporated into the ceria lattice, ethane formation is prevented even while achieving 100 % conversion of acetylene. Coke formation is also significantly reduced on these catalysts compared to conventional nanoparticle counterparts. Finally, we conclude that sol-gel synthesis provides the optimal method for creating a uniform dopant distribution within the high surface area ceria.

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