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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 325 records · Page 18
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Enhanced Guest@MOF Interaction via Stepwise Thermal Annealing: TCNQ@Cu 3 (BTC) 2

Confinement of guest molecules in porous materials such as metal organic frameworks (MOFs) promises to deliver emergent properties separate from those of the individual components. Understanding the confinement mechanism is therefore important for the development of new synthesis routes that adjust MOF properties for specific applications. In this work, we developed a new synthetic method to confine guest molecules into MOF pores through a stepwise thermal annealing process, wherein the confinement of 7,7,8,8-tetracyanoquinodimethane (TCNQ) guest molecules into Cu 3 (BTC) 2 (BTC = benzene-1,3,5-tricarboxylic acid) MOF host is used as an example of how novel materials can be created with new physical properties. The stepwise thermal annealing process includes 1) an activation process of pristine Cu 3 (BTC) 2 MOF to maximizes the TCNQ guest loading in the MOF host by effectively removing the residual solvents and 2) post-annealing of the TCNQ infiltrated MOF to enhances the interaction of the confined guest molecules with the MOF host. Obtained experimental results based on thermogravimetric analysis, N 2 gas adsorption, electron microscopy, X-ray diffraction and infrared absorption, combined with density functional theory calculations provide evidence that the use of a stepwise thermal annealing process yields enhancements in the guest loading, packing and interaction between the TCNQ guest and the MOF host. The new hybrid TCNQ@Cu 3 (BTC) 2 system is stable and shows no significant signs of structural degradation even after submersion in water. This is due to the presence of significantly stronger interactions of TCNQ with the frame-work metal ions compared to those of the water molecules competing for the same framework binding sites. It was also found that TCNQ@Cu 3 (BTC) 2 system maintains a significant CO 2 and CH 4 adsorption potential compared to the pristine MOF. The synthetic route developed in this work yields novel guest@MOF hybrid systems that will be useful for many MOF-based applications such as gas separations and chemical sensors performed under humid conditions.

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

Influence of Carbon-Nitride Dot-Emitting Species and Evolution on Fluorescence-Based Sensing and Differentiation

Carbon dots have attracted widespread interest for sensing applications based on their low cost, ease of synthesis, and robust optical properties. We investigate structure–function evolution on multiemitter fluorescence patterns for model carbon-nitride dots (CNDs) and their implications on trace-level sensing. Hydrothermally synthesized CNDs with different reaction times were used to determine how specific functionalities and their corresponding fluorescence signatures respond upon the addition of trace-level analytes. Archetype explosives molecules were chosen as a testbed due to similarities in substituent groups or inductive properties (i.e., electron withdrawing), and solution-based assays were performed using ratiometric fluorescence excitation–emission mapping (EEM). Analyte-specific quenching and enhancement responses were observed in EEM landscapes that varied with the CND reaction time. We then used self-organizing map models to examine EEM feature clustering with specific analytes. Finally, the results reveal that interactions between carbon-nitride frameworks and molecular-like species dictate response characteristics that may be harnessed to tailor sensor development for specific applications.

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

Friends or Foes: Fundamental Principles of Th-Organic Scaffold Chemistry Using Zr-Analogs as a Guide

The fundamental interest in actinide chemistry, particularly for the development of thorium-based materials, is experiencing a renaissance owing to the recent and rapidly growing attention to fuel cycle reactors, radiological daughters for nuclear medicine, and efficient nuclear stockpile development. Herein, we uncover fundamental principles of thorium chemistry on the example of Th-based extended structures such as metal–organic frameworks in comparison with the discrete systems and zirconium extended analogs, demonstrating remarkable over two-and-half-year chemical stability of Th-based frameworks as a function of metal node connectivity, amount of defects, and conformational linker rigidity through comprehensive spectroscopic and crystallographic analysis as well as theoretical modeling. Despite exceptional chemical stability, we report the first example of studies focusing on the reactivity of the most chemically stable Th-based frameworks in comparison with the discrete Th-based systems such as metal–organic complexes and a cage, contrasting multicycle recyclability and selectivity (>97%) of the extended structures in comparison with the molecular compounds. Altogether, the presented work not only establishes the conceptual foundation for evaluating the capabilities of Th-based materials but also represents a milestone for their multifaceted future and foreshadows their potential to shape the next era of actinide chemistry.

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

Complexes of Platinum Group Metals with a Conformationally Locked Scorpionate in a Metal–Organic Framework: An Unusually Close Apical Interaction of Palladium(II)

Here, we report synthetic strategies for installing platinum group metals (PGMs: Pd, Rh, Ir, and Pt) on a scorpionate-derived linker (TpmC*) within a metal–organic framework (MOF), both by room-temperature postsynthetic metalation and by direct solvothermal synthesis, with a wide range of metal loadings relevant for fundamental studies and catalysis. In-depth studies for the palladium adduct Pd(II)@Zr-TpmC* by density-functional-theory-assisted extended X-ray absorption fine structure spectroscopy reveals that the rigid MOF lattice enforces a close Pd(II)–N apical interaction between the bidentate palladium complex and the third uncoordinated pyrazole arm of the TpmC* ligand (Pd–N apical = 2.501 ± 0.067 Å), an interaction that is wholly avoided in molecular palladium scorpionates.

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

Analytical gradients for molecular-orbital-based machine learning

We report molecular-orbital-based machine learning (MOB-ML) enables the prediction of accurate correlation energies at the cost of obtaining molecular orbitals. Here, we present the derivation, implementation, and numerical demonstration of MOB-ML analytical nuclear gradients, which are formulated in a general Lagrangian framework to enforce orthogonality, localization, and Brillouin constraints on the molecular orbitals. The MOB-ML gradient framework is general with respect to the regression technique (e.g., Gaussian process regression or neural networks) and the MOB feature design. We show that MOB-ML gradients are highly accurate compared to other ML methods on the ISO17 dataset while only being trained on energies for hundreds of molecules compared to energies and gradients for hundreds of thousands of molecules for the other ML methods. The MOB-ML gradients are also shown to yield accurate optimized structures at a computational cost for the gradient evaluation that is comparable to a density-corrected density functional theory calculation.

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

Facilitating Screening of MOFs for Mixed Matrix Membranes Using Machine Learning and the Maxwell Model

Metal organic framework (MOF)-based mixedmatrix membranes (MMMs), which embed MOF particles in polymer matrices, combine the advantages of polymeric and inorganic membranes. Multiple previous studies have used the Maxwell model together with molecular simulations and machine learning (ML) to predict the performance of MOF/polymer MMMs. However, the assumption of rigid MOF frameworks in molecular simulations limited the accuracy of the data used in the predictions, particularly in predicting molecular diffusivities. We developed a novel workflow integrating ML models with consideration of MOF flexibility to predict the permeability and selectivity of 131,722 MMMs for CO 2 /CH 4 , O 2 /N 2 and He/H 2 separations. The full range of achievable MMM performance within the Maxwell model was analyzed, and several promising MOFs were identified using this workflow. This approach offers an efficient tool for screening any polymer and MOF combination in gas separation applications.

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

Self-Assembly of Helical Nanofibrous Chiral Covalent Organic Frameworks

Despite significant progress on the design and synthesis of covalent organic frameworks (COFs), precise control over microstructures of such materials remains challenging. Herein, two chiral COFs with well-defined one-handed double-helical nanofibrous morphologies were constructed via an unprecedented template-free method, capitalizing on the diastereoselective formation of aminal linkages. Detailed time-dependent experiments reveal the spontaneous transformation of initial rod-like aggregates into the double-helical microstructures. Impoirtantly, we have further demonstrated that the helical chirality and circular dichroism signal can be facilely inversed by simply adjusting the amount of acetic acid during synthesis. Moreover, by transferring chirality to achiral fluorescent molecular adsorbents, the helical COF nanostructures can effectively induce circularly polarized luminescence with the highest luminescent asymmetric factor (g lum ) up to ≈0.01.

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

MOFSimplify, machine learning models with extracted stability data of three thousand metal–organic frameworks

Abstract We report a workflow and the output of a natural language processing (NLP)-based procedure to mine the extant metal–organic framework (MOF) literature describing structurally characterized MOFs and their solvent removal and thermal stabilities. We obtain over 2,000 solvent removal stability measures from text mining and 3,000 thermal decomposition temperatures from thermogravimetric analysis data. We assess the validity of our NLP methods and the accuracy of our extracted data by comparing to a hand-labeled subset. Machine learning (ML, i.e. artificial neural network) models trained on this data using graph- and pore-geometry-based representations enable prediction of stability on new MOFs with quantified uncertainty. Our web interface, MOFSimplify, provides users access to our curated data and enables them to harness that data for predictions on new MOFs. MOFSimplify also encourages community feedback on existing data and on ML model predictions for community-based active learning for improved MOF stability models.

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

Mining for Metal–Organic Systems: Chemistry Frontiers of Th-, U-, and Zr-Materials

The conceptual framework presented in this Perspective overviews the design principles of innovative thorium-based materials that could address urgent needs of the medicinal, nuclear energy, and waste remediation sectors from the lens of zirconium and uranium analogs. We survey the intersections of Zr, Th, and U chemistry with a focus on how the intrinsic behavior of each metal translates to broader material properties, including, but not limited to, structural and topological diversity, preferential metal–ligand binding, and reactivity. On the example of several classes of materials, including organometallic complexes, polyoxometalates, and the primary focus of this Perspective, metal–organic frameworks (MOFs), the design principles that govern the preparation of Zr-, Th-, and U-compounds, including oxophilicity, variation in oxidation states, and stable coordination environments have been considered. Further, we highlight how the impact of the mentioned variables may shift throughout the progression from discrete molecular systems to extended structures. We discuss the common assumption that zirconium-organic materials are typically considered a close analog of thorium-based congeners in areas such as material design and preparation. Through consideration of fundamental chemistry principles, we shed light on the relationships between Zr-, Th-, and U-based materials and highlight how a critical analysis of their distinct properties can be used to target a desired material performance. Finally, we provide a detailed understanding of Th-based materials chemistry by anchoring their fundamental properties between two well-studied reference points, zirconium- and uranium-containing analogs.

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

Concurrent Enhancement of Acetylene Uptake Capacity and Selectivity by Progressive Core Expansion and Extra–Framework Anions in Pore–Space–Partitioned Metal–Organic Frameworks

A multi-stage core-expansion method is proposed here as one component of the integrative binding-site/extender/core-expansion (BEC) strategy. The conceptual deconstruction of the partitioning ligand into three editable parts draws our focus onto progressive core expansion and allows the optimization of both acetylene uptake and selectivity. Herein the effectiveness of this strategy is shown through a family of eight cationic pore-partitioned materials containing three different partitioning ligands and various counter anions. The optimized structure, Co 3 -cpt-tph-Cl (Hcpt=4-(p-carboxyphenyl)-1,2,4-triazole, H-tph=(2,5,8-tri-(4-pyridyl)-1,3,4,6,7,9-hexaazaphenalene) with the largest surface area and highest C 2 H 2 uptake capacity (200 cm 3 /g at 298 K), also exhibits (desirably) the lowest CO 2 uptake and hence the highest C 2 H 2 /CO 2 selectivity. The successful boost in both C 2 H 2 capacity and IAST selectivity allows Co 3 -cpt-tph-Cl to rank among the best crystalline porous materials, ionic MOFs in particular, for C 2 H 2 uptake and C 2 H 2 /CO 2 experimental breakthrough separation.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Metal–Organic Framework Nodes as a Supporting Platform for Tailoring the Activity of Metal Catalysts

Catalysis is a ubiquitous element of the modern economy, representing a cornerstone of many sectors including energy, materials, and pharmaceuticals. Within this realm, 80% of reactions are carried out by heterogeneous catalysts due to their advantageous physical and chemical characteristics. In some heterogeneous systems, the reaction rate can be optimized through rational catalyst design, in which support materials can be tailored structurally and stereoelectronically for targeted purposes to better facilitate the catalytic reaction. To this end, metal-organic frameworks (MOFs) have garnered recent attention due to their high porosity, crystallinity, and chemical tunability, which can be used to derive structure-activity relationships in the design of catalysts. In this Perspective, we survey examples of catalytically active guest metals on the inorganic nodes of MOFs. This is done with the intention of providing design guidelines for tailoring chemical reactivity and insights into the opportunities for future growth in this field. Strategies for rational design in MOF catalysis include electronic tuning of the metal node in the MOF support, installing promoter ions onto the node to effect the reactivity of grafted metals, modulation of the spatial environment around the transition metal using the metal node structure, and achieving site uniformity in supported catalysts. By highlighting these efforts, we seek to underscore the role of MOF nodes as nonspectator supports for catalytic metal complexes and provide future directions for rational catalyst design by tuning reactivity on these anchoring platforms.

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

General Strategy for Incorporation of Functional Group Handles into Covalent Organic Frameworks via the Ugi Reaction

The library of imine-linked covalent organic frameworks (COFs) has grown significantly over the last two decades, featuring a variety of morphologies, pore sizes, and applications. An array of synthetic methods has been developed to expand the scope of the COF functionalities; however, most of these methods were designed to introduce functional scaffolds tailored to a specific application. Having a general approach to diversify COFs via late-stage incorporation of functional group handles would greatly facilitate the transformation of these materials into platforms for a variety of useful applications. In this paper, we report a general strategy to introduce functional group handles in COFs via the Ugi multicomponent reaction. To demonstrate the versatility of this approach, we have synthesized two COFs with hexagonal and kagome morphologies. We then introduced azide, alkyne, and vinyl functional groups, which could be readily utilized for a variety of post-synthetic modifications. This facile approach enables the functionalization of any COFs containing imine linkages.

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

Tailoring On-Surface Molecular Reactions and Assembly through Hydrogen-Modified Synthesis: From Triarylamine Monomer to 2D Covalent Organic Framework

Relative to conventional wet-chemical synthesis techniques, on-surface synthesis of organic networks in ultrahigh vacuum has few control parameters. The molecular deposition rate and substrate temperature are typically the only synthesis variables to be adjusted dynamically. Here we demonstrate that reducing conditions in the vacuum environment can be created and controlled without dedicated sources-relying only on backfilled hydrogen gas and ion gauge filaments-and can dramatically influence the Ullmann-like on-surface reaction used for synthesizing two-dimensional covalent organic frameworks (2D COFs). Using tribromo dimethylmethylene-bridged triphenylamine ((Br 3 )DTPA) as monomer precursors, we find that atomic hydrogen (H*) blocks aryl-aryl bond formation to such an extent that we suspect this reaction may be a factor in limiting the ultimate size of 2D COFs created through on-surface synthesis. Conversely, we show that control of the relative monomer and hydrogen fluxes can be used to produce large self-assembled islands of monomers, dimers, or macrocycle hexamers, which are of interest in their own right. On-surface synthesis of oligomers, from a single precursor, circumvents potential challenges with their protracted wet-chemical synthesis and with multiple deposition sources. Using scanning tunneling microscopy and spectroscopy (STM/STS), we show that changes in the electronic states through this oligomer sequence provide an insightful view of the 2D COF (synthesized in the absence of atomic hydrogen) as the end point in an evolution of electronic structures from the monomer.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Efficient Capture and Release of the Rare-Earth Element Neodymium in Aqueous Solution by Recyclable Covalent Organic Frameworks

Rare-earth elements (REEs) are present in a broad range of critical materials. The development of solid adsorbents for REE capture could enable the cost-effective recycling of REE-containing magnets and electronics. In this context, covalent organic frameworks (COFs) are promising candidates for REE adsorption due to their exceptionally high surface area. Despite having attractive physical properties, COFs are heavily underutilized for REE capture applications due to their limited lifecycle in aqueous acidic environments, as well as synthetic challenges associated with the incorporation of ligands suitable for REE capture. Here, in this work, we show how the Ugi multicomponent reaction can be leveraged to postsynthetically modify imine-based COFs for the introduction of a diglycolic acid (DGA) moiety, an efficient scaffold for REE capture. The adsorption capacity of the DGA-functionalized COF was found to be more than 40 times higher than that of the pristine imine COF precursor and more than four times higher than that of the next-best reported DGA-functionalized solid support. This rationally designed COF has appealing characteristics of high adsorption capacity, fast and efficient capture and release of the REE ions, and reliable recyclability, making it one of the most promising adsorbents for solid–liquid REE ion extractions reported to date.

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

Electron shuttle in the MOF derived TiO 2 /CuO heterojunction boosts light driven hydrogen evolution

Metal organic frameworks (MOFs) have emerged as a novel template to develop porous photocatalytic materials for solar fuel conversion. In this work, we report the synthesis, charge separation dynamics, and photocatalytic performance of the TiO 2 /CuO heterostructure derived from mixed-phase MOFs based on Ti and Cu metal nodes, which demonstrates significantly enhanced catalytic activity for the hydrogen evolution reaction (HER) compared to metal oxides derived from single node MOFs. More importantly, using transient absorption spectroscopy, we identified the specific role each component in the heterostructure plays and unravelled the key intermediate species that is responsible for the exceptional photocatalytic activity of the heterostructure. We found that the HER is initiated with ultrafast electron transfer (<150 fs) from the molecular photosensitizer to the conduction band of TiO 2 , where TiO 2 acts as an electron mediator and shuttles the electron to the CuO cocatalyst, facilitating charge separation and ultimately boosting the HER efficiency. Overall, these results not only demonstrate the great potential of using mixed-phase MOFs as templates to synthesize mesoporous heterostructure photocatalysts but also provide important insight into the HER mechanism.

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

Big Data For Operation and Maintenance Cost Reduction

The purpose of this research is to develop a first-of-a-kind framework for integrating Big Data capability into the daily activities of our current fleet of nuclear power plants. Big Data is traditionally defined as data sets with high volume, velocity, and heterogeneity, and the existing Big Data analytics capabilities are now widely popular in fields such as finance, weather, e-commerce, healthcare and sports. In the nuclear industry, while the volume and velocity of data may present computational challenges for existing analytics capabilities, data heterogeneity are seen to present the major challenge. This research project mainly focuses on incorporating the wide range of data heterogeneities in nuclear power plants into an integrated Big Data Analytics capability. The primary end-product of this project is a Big Data framework that is capable of dealing with the large volume and heterogeneity of the data found in nuclear power plants to extract timely and valuable information on equipment performance. The framework can generate system insights that are actionable relations between measurable impacts and the corresponding maintenance action plans and enable optimization of plant operation and maintenance based on the extracted information. The developed framework is capable of handling heterogeneous data including both image data and time-series sensor data. Specifically, this developed framework includes the following components. The first component is an overarching maintenance ontology which includes system insights required by maintenance optimization. The maintenance ontology interacts with other components in the developed framework. The second component handles Piping & Instrumentation Diagram (P&ID) data. It can be used to extract system components and their relations automatically from the P&IDs. This extracted information is stored in the first component, i.e., maintenance ontology, and is also used as input to the third component, i.e., a tool for generating the fault tree for the corresponding system. The generated fault tree in turn is stored in the ontology for assessing risk that is used as a criterion in maintenance policy optimization. The fourth component is a tool for inferring the parameters in the Markov degradation model for a nuclear system. It uses basic information from the ontology. The fifth component is a tool for assessing the degradation level using sensor measurement data, for example, pressure, flowrate. This tool can be used for determining corrective maintenance actions. The results obtained from components four and five are returned to the ontology. The sixth component of the framework is a tool for optimizing the maintenance policy for a nuclear system of interest. It takes certain basic information from the ontology, e.g., costs of maintenance actions and system failures, as input, and returns the optimal maintenance policy to the ontology. This tool can be used for determining predictive maintenance actions. A set of experiments have also been conducted to verify the algorithms developed in this project for nuclear system degradation monitoring. The experiments are based on four solenoid valves, similar to the ones used in nuclear power plants. The analyses based on the experimental data using two algorithms, i.e., the Randomized Window Decomposition (RWD) algorithm and the particle filtering algorithm, and the results are introduced in the report. The Big Data framework developed in this project can be used as a support tool in daily activities of plant operation and maintenance and will reduce current costs while maintaining or improving safety levels. Overall, the project will not only benefit existing reactors, however it will open new frontiers to realize the long overdue value of Big Data Analytics in the nuclear sphere.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2024

Gas Permeation and Separation Characteristics of Microporous TpHz COF Membranes Synthesized by Substrate-Assisted Interfacial Polymerization

Microporous two-dimensional covalent organic framework (2D COF) membranes offer promise for gas separation applications, but their gas transport mechanism remains unclear. In this study, a TpHz 2D COF membrane supported on a macroporous nylon substrate is prepared by substrate-assisted interfacial polymerization under mild conditions. The formation of a continuous and dense thin (~300 nm thick) TpHz layer is confirmed by scanning electron microscopy and Fourier transform infrared spectroscopy. Characterization by X-ray diffraction, grazing incidence wide-angle X-ray scattering, and N 2 porosimetry qualitatively reveals the microstructures of the supported TpHz membranes, i.e., they comprise partially oriented 2D COF lamellar crystallites with moderate crystallinity in an eclipsed (AA) stacking geometry, centering the effective membrane pore size distribution at ~1.1 nm. Further, single gas permeation data show that the transport of common molecular gases, including H 2 , He, CH 4 , N 2 , and CO 2 , through the synthesized TpHz membranes follows the Knudsen transport mechanism, where single gas permeance decreases with an increasing molecular weight and permeation temperature. Binary gas separation results show that in the equimolar CO 2 /N 2 mixture, the presence of the CO 2 surface flow slightly hinders the N 2 flow at room temperature due to the reduced membrane channel size by the adsorbed CO 2 gas layer on TpHz’s pore wall. In contrast, permeation of the equimolar CH 4 /N 2 binary mixture does not exhibit a discernible surface flow of both gases due to their much lower gas uptake on TpHz, and their transport mechanism follows Knudsen-like behavior.

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

An AI-Enabled MODEX Framework for Improving Predictability of Subsurface Water Storage across Local and Continental Scales

Focal Area: (2) Predictive modeling through the use of AI techniques and AI-derived model components. (3) Insight gleaned from complex data using AI, big data analytics, and other advanced methods. We propose an AI-enabled model-experiment (MODEX) framework to improve the predictability of subsurface water storage (SWS) from local to conus scales in a changing environment by taking advantage of DOE’s observation and simulation capabilities, as well as to inform the model and the observation development.

54 ENVIRONMENTAL SCIENCES↗