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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 361 records · Page 20
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Workshop on Addressing Rigor and Reproducibility in Thermal, Heterogeneous Catalysis

Heterogeneous catalysis has long served as the bedrock of the manufacturing of energy carriers, fuels and chemicals, and various technologies for pollution abatement. The significant complexity and variability spanning the entire breadth of catalyst material properties, synthesis methods, characterization techniques, and evaluation procedures, has focused attention on the need to establish community-accepted best practices for ensuring high-quality, benchmarked, and reproducible data. In addition, increased societal urgency to transition to clean energy and reduce greenhouse gas concentrations has incentivized interdisciplinary, convergent, and translational approaches to catalysis research in recent years. Research engineers and scientists with expertise cutting broadly across materials science, chemical synthesis, interfacial science, spectroscopy, and methods of data science and computational simulation, all bring diverse and important perspectives to catalysis research, but often with little awareness of the complexity of catalytic systems, especially in their working environment. As has already occurred in other scientific fields, there has been growing recognition and consensus in the heterogeneous catalysis research community that mechanisms are needed to improve the rigor and reproducibility (R&R) of experimental measurements, to ensure alignment of the broader research community with a common core of best practices specific to the realization of high-quality catalysis research. Similarly, the field is moving rapidly toward computationally informed and data science-driven catalyst design, but the success of implementing such predictive tools hinges on model training and validation rooted in rigorously obtained and reproducible experimental data that are benchmarked to common specifications. As such, this workshop was convened to prepare a report summarizing best practices for reporting data and performing experiments that researchers can use to benchmark, validate, and reproduce data in specific sub-fields of thermal, heterogeneous catalysis. Additionally, we discussed recommendations for future actions that may improve R&R in this field. The workshop organizers and participants include a diverse range of catalysis researchers from various employment sectors (e.g., academia, industry, national laboratory), institutional mission and resources (e.g., PhD-granting research universities, non-PhD-granting teaching universities), career stage (e.g., early, mid and late-career), technical expertise, and demographic background. This diverse group was involved in the discussion of workshop agenda items, writing this report, and discussing possible future action items for the community to consider, which helped ensure that a broad range of perspectives were captured in the description of the problems at hand and the creation of actionable solutions that may be effectively adopted by the diverse practitioners in catalysis research. Importantly, this group of workshop participants also included very early career researchers (e.g., senior PhD students, postdoctoral scholars) who will become the next generation of scientific leaders in various sectors, thus capturing emerging perspectives of newcomers to the field to shape its future while positively impacting the development of its future workforce. We envision that this effort will help advance the field of catalysis science by improving the rigor and reproducibility of experimental data collected by current researchers and future newcomers to the field, which is of broad importance to health and vitality of any scientific discipline. Therefore, best practices identified in this endeavor for thermal heterogeneous catalysis can be translated to such efforts in other areas of catalysis and other scientific fields involving the study of materials, and vice versa. We also envision this to be an ongoing effort, with future workshops that are convened to discuss issues of rigor and reproducibility on technical topics that were unable to be covered in this workshop due to its scope limitations, and as emerging methods and materials become more prevalent in the research community.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Synthesis of Ln II ‐in‐Cryptand Complexes by Chemical Reduction of Ln III ‐in‐Cryptand Precursors: Isolation of a Nd II ‐in‐Cryptand Complex

Abstract Lanthanide triflates have been used to incorporate Nd III and Sm III ions into the 2.2.2‐cryptand ligand (crypt) to explore their reductive chemistry. The Ln(OTf) 3 complexes (Ln=Nd, Sm; OTf=SO 3 CF 3 ) react with crypt in THF to form the THF‐soluble complexes [Ln III (crypt)(OTf) 2 ][OTf] with two triflates bound to the metal encapsulated in the crypt. Reduction of these Ln III ‐in‐crypt complexes using KC 8 in THF forms the neutral Ln II ‐in‐crypt triflate complexes [Ln II (crypt)(OTf) 2 ]. DFT calculations on [Nd II (crypt)] 2+ ], the first Nd II cryptand complex, assign a 4f 4 electron configuration to this ion.

Huh, Daniel N.↗
DOE OSTI2022

Designing Sites in Heterogeneous Catalysis: Are We Reaching Selectivities Competitive With Those of Homogeneous Catalysts?

A critical review of different prominent nanotechnologies adapted to catalysis is provided, with focus on how they contribute to the improvement of selectivity in heterogeneous catalysis. Ways to modify catalytic sites range from the use of the reversible or irreversible adsorption of molecular modifiers to the immobilization or tethering of homogeneous catalysts and the development of well-defined catalytic sites on solid surfaces. The latter covers methods for the dispersion of single-atom sites within solid supports as well as the use of complex nanostructures, and it includes the post-modification of materials via processes such as silylation and atomic layer deposition. All these methodologies exhibit both advantages and limitations, but all offer new avenues for the design of catalysts for specific applications. Because of the high cost of most nanotechnologies and the fact that the resulting materials may exhibit limited thermal or chemical stability, they may be best aimed at improving the selective synthesis of high value-added chemicals, to be incorporated in organic synthesis schemes, but other applications are being explored as well to address problems in energy production, for instance, and to design greener chemical processes. Finally, the details of each of these approaches are discussed, and representative examples are provided. We conclude with some general remarks on the future of this field.

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

Multistep catalytic abiotic CO2 conversion to sugars through C1 intermediates

Carbon dioxide (CO2) to multicarbon (Cn) upgrading for commodity chemicals, fuel production, or artificial food synthesis using renewable energy input is a golden target for researchers in sustainable carbon emission reduction. Here, we explore and analyze a flexible modular roadmap for the task, utilizing sequential electro-, photo-, and organocatalysis to develop a strategy for CO2 conversion using the key and elusive formaldehyde precursor of interest for sugar generation. We study the electrochemical carbon dioxide reduction reaction to methanol in a flow cell and its discontinuous photooxidation to formaldehyde (PMOR) with excellent selectivity. Utilizing a highly active N-heterocyclic carbene catalyst enables tunable generation of C4-C6 aldoses without undesirable byproducts, with carbon conversion yield reaching 60 to 80% for desired pentose, tetrose, and triose product mixtures and over 20% for hexose. This approach presents a roadmap for CO2 valorization, aiming to bridge carbon waste streams with sustainable sugar synthesis and opening broad avenues for green chemical production.

CO2 valorization↗
DOE OSTI2022

Graphene nanoribbons initiated from molecularly derived seeds

Abstract Semiconducting graphene nanoribbons are promising materials for nanoelectronics but are held back by synthesis challenges. Here we report that molecular-scale carbon seeds can be exploited to initiate the chemical vapor deposition (CVD) synthesis of graphene to generate one-dimensional graphene nanoribbons narrower than 5 nm when coupled with growth phenomena that selectively extend seeds along a single direction. This concept is demonstrated by subliming graphene-like polycyclic aromatic hydrocarbon molecules onto a Ge(001) catalyst surface and then anisotropically evolving size-controlled nanoribbons from the seeds along $$\left\langle 110\right\rangle$$ 110 of Ge(001) via CH 4 CVD. Armchair nanoribbons with mean normalized standard deviation as small as 11% (3 times smaller than nanoribbons nucleated without seeds), aspect ratio as large as 30, and width as narrow as 2.6 nm (tunable via CH 4 exposure time) are realized. Two populations of nanoribbons are compared in field-effect transistors (FETs), with off-current differing by 150 times because of the nanoribbons’ different widths.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Intense Reactivity in Sulfur–Hydrogen Mixtures at High Pressure under X-ray Irradiation

Superconductivity near room temperature in the sulfur–hydrogen system arises from a sequence of reactions at high pressures, with X-ray diffraction experiments playing a central role in understanding these chemical–structural transformations and the corresponding S:H stoichiometry. Here we document X-ray irradiation acting as both a probe and as a driver of chemical reaction in this dense hydride system. We observe a reaction between molecular hydrogen (H 2 ) and elemental sulfur (S 8 ) under high pressure, induced directly by X-ray illumination, at photon energies of 12 keV using a free electron laser. The rapid synthesis of hydrogen sulfide (H 2 S) at 0.3 GPa was confirmed by optical observations, spectroscopic measurements, and microstructural changes detected by X-ray diffraction. These results document X-ray induced chemical synthesis of superconductor-forming dense hydrides, revealing an alternative production strategy and confirming the disruptive nature of X-ray exposure in studies on high-pressure hydrogen chalcogenides, from water to high-temperature superconductors.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2025

Machine-Learned Force Field for Molecular Dynamics Simulations of Nonequilibrium Ammonia Synthesis on Iron Catalysts

Ammonia (NH 3 ) is one of the most important industrial chemicals. The conventional NH 3 synthesis method-the Haber–Bosch process-converts atmospheric nitrogen (N 2 ) into NH 3 using H 2 with an iron (Fe) catalyst. However, this process requires high pressures (100–200 atm) and temperatures (700–800 K) near thermal equilibrium. Recently, Fe-based nanocatalysts have been reported to produce promising NH 3 yields under atmospheric pressures and temperature-modulated nonequilibrium conditions. Understanding the mechanism of nonequilibrium catalysis with programmed temperature variation could help to optimize this fully electrified and less energy-intensive process. Although reactive molecular dynamics (RMD) simulations can be a useful tool to model nonequilibrium catalytic processes, they require the development of accurate force fields (i.e., interatomic potentials). Here, we present a machine-learned (ML) force field within the Deep Potential MD (DPMD) framework, trained using periodic density functional theory (DFT) calculations, to model NH 3 synthesis on Fe catalysts with various surface adsorbates such as *N, *H, *N 2 , *H 2 , *NH, *NH 2 , and *NH 3 . Here, we generated the DFT data from static models of elementary reactions on the most stable (110) surface of body-centered cubic Fe, which then were augmented by data from constant number of particles–volume–temperature (NVT) DFT-MD trajectories at various temperatures. Finally, we utilized the fully optimized ML force field to investigate reaction dynamics at an Fe(110) surface at linearly increasing temperatures using NVT-DPMD simulations. Our simulations indicate that pulsed temperature ramping could prove favorable for NH3 synthesis. For example, we conducted ramping under multiple sets of conditions: (i) from 900 to 1200 K over periods of 0.1–0.3 ns for Fe surfaces precovered with N or NH along with H; and (ii) from 300 to 600 K over 0.1–0.3 ns for Fe surfaces precovered with NH 3 . While our simulations so far are limited to short time scales (very rapid heating), these observations shed light on the mechanism of the high NH 3 synthesis rate achieved in a novel temperature-modulated nonequilibrium catalytic reactor using pulsed heating and cooling.

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

Graph-Based Approaches for Predicting Solvation Energy in Multiple Solvents: Open Datasets and Machine Learning Models

The solvation properties of molecules, often estimated using quantum chemical simulations, are important in the synthesis of energy storage materials, drugs, and industrial chemicals. Here, we develop machine learning models of solvation energies to replace expensive quantum chemistry calculations with inexpensive-to-compute message-passing neural network models that require only the molecular graph as inputs. Our models are trained on a new database of solvation energies for 130,258 molecules taken from the QM9 dataset computed in five solvents (acetone, ethanol, acetonitrile, dimethyl sulfoxide, and water) via an implicit solvent model. Our best model achieves a mean absolute error of 0.5 kcal/mol for molecules with nine or fewer non-hydrogen atoms and 1 kcal/mol for molecules with between 10 and 14 non-hydrogen atoms. We make the entire dataset of 651,290 computed entries openly available and provide simple web and programmatic interfaces to enable others to run our solvation energy model on new molecules. This model calculates the solvation energies for molecules using only the SMILES string and also provides an estimate of whether each molecule is within the domain of applicability of our model. We envision that the dataset and models will provide the functionality needed for the rapid screening of large chemical spaces to discover improved molecules for many applications.

25 ENERGY STORAGE↗
DOE OSTI2020

Programming Amphiphilic Peptoid Oligomers for Hierarchical Assembly and Inorganic Crystallization

Natural organisms make a wide variety of exquisitely complex, nano-, micro-, and macroscale structured materials in an energy-efficient and highly reproducible manner. During these processes, the information-carrying biomolecules (e.g., proteins, peptides, and carbohydrates) enable (1) hierarchical organization to assemble scaffold materials and execute high-level functions and (2) exquisite control over inorganic materials synthesis, generating biominerals whose properties are optimized for their functions. Inspired by nature, significant efforts have been devoted to developing functional materials that can rival those natural molecules by mimicking in vivo functions using engineered proteins, peptides, DNAs, sequence-defined synthetic molecules (e.g., peptoids), and other biomimetic polymers. Among them, peptoids, a new type of synthetic mimetics of peptides and proteins, have received particular attention because they combine the merits of both synthetic polymers (e.g., high chemical stability and efficient synthesis) and biomolecules (e.g., sequence programmability and biocompatibility). The lack of both chirality and hydrogen bonds in their backbone results in a highly designable peptoid-based system with reduced structural complexity and side chain-chemistry-dominated properties. Here in this Account, we present our recent efforts in this field by programming amphiphilic peptoid sequences for (1) the controlled self-assembly into different hierarchically structured nanomaterials with favorable properties and (2) manipulating inorganic (nano)crystal nucleation, growth, and assembly into superstructures. First, we designed a series of amphiphilic peptoids with controlled side chain chemistries that self-assembled into 1D highly stiff and dynamic nanotubes, 2D membrane-mimetic nanosheets, hexagonally patterned nanoribbons, and 3D nanoflowers. These crystalline nanostructures exhibited sequence-dependent properties and showed promise for different applications. The corresponding peptoid self-assembly pathways and mechanisms were also investigated by leveraging in situ atomic force microscopy studies and molecular dynamics simulations, which showed precise sequence dependency. Second, inspired by peptide- and protein-controlled formation of hierarchical inorganic nanostructures in nature, we developed peptoid-based biomimetic approaches for controlled synthesis of inorganic materials (e.g., noble metals and calcite), in which we took advantage of the substantial side chain chemistry of peptoids and investigated the relationship between the peptoid sequences and the morphology and growth kinetics of inorganic materials. For example, to overcome the challenges (e.g., complexity of protein- and peptide-folding, poor thermal and chemical stabilities) facing the area of protein- and peptide-controlled synthesis of inorganic materials, we recently reported the design of sequence-defined peptoids for controlled synthesis of highly branched plasmonic gold particles. Moreover, we developed a rule of thumb for designing peptoids that predictively enabled the morphological evolution from spherical to coral-shaped gold nanoparticles (NPs). With this Account, we hope to stimulate the research interest of chemists and materials scientists and promote the predictive synthesis of functional and robust materials through the design of sequence-defined synthetic molecules.

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

Syntheses and characterization of isotopically labeled 1,3,5-triamino-2,4,6-trinitrobenzene (TATB)

Synthesis and characterization of chemical analogues of TATB, where specific atoms in the structure have been isotopically substituted, are reported. 15 N, 2 H, and 18 O have replaced the naturally occurring isotope distributions in the amino and/or the nitro attendant sites and 13 C has replaced the carbon in the ring structure. A modified wet-amination method was used to produce the analogues, and the isotopic replacements were performed by selective choice of labeled precursors. Four 15 N-labeled compounds (N replaced in the amino and nitro positions), two deuterium-labeled compounds (hydrogens replaced on the amino groups), and one 13 C-labeled compound (C in the ring substituted) were synthesized of high isotopic and chemical purity. One partially labeled 18 O-labeled compound (O in the nitro position) was a result of incomplete labeling due to exchange reactions during synthesis. The compounds were characterized by various spectroscopic methods – mass spectrometry (MS), solid-state nuclear magnetic resonance (SS-NMR), infrared (FTIR), powder x-ray diffraction (PXRD), and differential scanning calorimetry (DSC), depending upon the substitution. In conclusion, these compounds have been critical to the efforts in understanding the decomposition pathways of TATB when exposed to abnormal thermal environments.

36 MATERIALS SCIENCE↗
NASA NTRS1980

Plasma chemistry and organic synthesis

The characteristic features of chemical reactions using low temperature plasmas are described and differentiated from those seen in other reaction systems. A number of examples of applications of plasma chemistry to synthetic reactions are mentioned. The production of amino acids by discharge reactions in hydrocarbon-ammonia-water systems is discussed, and its implications for the origins of life are mentioned.

Tezuka, M.↗
DOE OSTI2024

A dynamic Bayesian optimized active recommender system for curiosity-driven partially Human-in-the-loop automated experiments

Optimization of experimental materials synthesis and characterization through active learning methods has been growing over the last decade, with examples ranging from measurements of diffraction on combinatorial alloys at synchrotrons, to searches through chemical space with automated synthesis robots for perovskites. In virtually all cases, the target property of interest for optimization is defined a priori with the ability to shift the trajectory of the optimization based on human-identified findings during the experiment is lacking. Thus, to highlight the best of both human operators and AI-driven experiments, here we present the development of a human–AI collaborated experimental workflow, via a Bayesian optimized active recommender system (BOARS), to shape targets on the fly with human real-time feedback. Here, the human guidance overpowers AI at early iteration when prior knowledge (uncertainty) is minimal (higher), while the AI overpowers the human during later iterations to accelerate the process with the human-assessed goal. We showcase examples of this framework applied to pre-acquired piezoresponse force spectroscopy of a ferroelectric thin film, and in real-time on an atomic force microscope, with human assessment to find symmetric hysteresis loops. It is found that such features appear more affected by subsurface defects than the local domain structure. This work shows the utility of human–AI approaches for curiosity driven exploration of systems across experimental domains.

36 MATERIALS SCIENCE↗