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DOE OSTI2020

Competition between Solvation and Intramolecular Hydrogen-Bonding in Microsolvated Protonated Glycine and β-Alanine

Infrared predissociation (IRPD) spectroscopy is used to reveal and compare the microsolvation motifs of GlyH + (H 2 O) n and β-AlaH + (H 2 O) n . The chemical structure of these amino acids differ only in the length of the carbon chain connecting the amine and carboxyl terminals, which nonetheless leads to a significant difference in the strength of the intramolecular C=O···H-N hydrogen bond in the unsolvated ions. This difference makes them useful in our studies of the competition between solvation and internal hydrogen bonding interactions. Analysis of the IRPD results reveals that the sequential addition of water molecules leads to similar effects on the intramolecular interaction in both GlyH + (H 2 O) n and β-AlaH + (H 2 O) n . Solvation of the -NH 3 + group leads to a weakening of the C=O···H-N hydrogen bond, while solvation of the carboxyl -OH leads to a strengthening of this bond. Additionally, we have found that for β-AlaH + , the addition of a H 2 O to the second solvation shell can still influence the strength of the C=O···H-N hydrogen bonding interaction. Lastly because the C=O···H-N interaction in β-AlaH + is stronger than that in GlyH + , more solvent molecules are needed to sufficiently weaken the intramolecular hydrogen bond such that isomers without this bond begin to be energetically competitive; this occurs at n=5 for β-AlaH + and n=1 for GlyH + .

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2025

Chemical classification program synthesis using generative artificial intelligence

Accurately classifying chemical structures is essential for cheminformatics and bioinformatics, including tasks such as identifying bioactive compounds of interest, screening molecules for toxicity to humans, finding non-organic compounds with desirable material properties, or organizing large chemical libraries for drug discovery or environmental monitoring. However, manual classification is labor-intensive and difficult to scale to large chemical databases. Existing automated approaches either rely on manually constructed classification rules, or are deep learning methods that lack explainability. This work presents an approach that uses generative artificial intelligence to automatically write chemical classifier programs for classes in the Chemical Entities of Biological Interest (ChEBI) database. These programs can be used for efficient deterministic run-time classification of SMILES structures, with natural language explanations. The programs themselves constitute an explainable computable ontological model of chemical class nomenclature, which we call the ChEBI Chemical Class Program Ontology (C3PO). We validated our approach against the ChEBI database, and compared our results against deep learning models and a naive SMARTS pattern based classifier. C3PO outperforms the naive classifier, but does not reach the performance of state of the art deep learning methods. However, C3PO has a number of strengths that complement deep learning methods, including explainability and reduced data dependence. C3PO can be used alongside deep learning classifiers to provide an explanation of the classification, where both methods agree. The programs can be used as part of the ontology development process, and iteratively refined by expert human curators.

Artificial Intelligence↗

DOE OSTI2026

Temperature-dependent changes in gas chromatographic separation metrics for trihexyl(tetradecyl)phosphonium-based ionic liquid stationary phases and comparison to conventional polysiloxane stationary phases

Here, to assess whether the trihexyl(tetradecyl)phosphonium chloride ([P 66614 + ][Cl - ]) ionic liquid (IL), employed as a gas chromatographic stationary phase, exhibits temperature-dependent phase transitions or structural heterogeneity, retention thermodynamics for probe molecules of varied chemical structure were investigated by gas chromatography (GC) over the temperature range of 25 to 64 °C using van’t Hoff analysis. All van’t Hoff plots for n-alkanes (C8–C12) and other probe analytes were linear, indicating the absence of detectable phase-transition behavior. The [P 66614 + ][Cl - ] IL was further compared with the [P 66614 + ] bis[(trifluoromethyl)sulfonyl]imide ([P 66614 + ][NTf 2 - ]) IL and commercial polysiloxane stationary phases in terms of temperature-dependent resolution behavior and chromatographic selectivity over the temperature range of 28–52 °C. The resolution factors of analytes in mixtures obtained using gas chromatography–mass spectrometry (GC–MS) and the summation of resolution values decreased smoothly with temperature on both IL stationary phases and on the dimethylphenylcyano-substituted polymeric stationary phase (OV-1701), whereas the poly(50% diphenyl/50% dimethyl siloxane) stationary phase (SPB-50) exhibited irregularities in its temperature-dependent summation of resolution profile, showing a distinct maximum in the temperature range of 34–40 °C. Selectivity values for the IL stationary phases were largely determined by the anion, with the [P 66614 + ][Cl - ] IL providing enhanced separation between polar and aromatic analytes, while the [P 66614 + ][NTf 2 - ] IL favored dispersive and π-π interactions that resulted in a reversal of elution order for some aliphatic–aromatic and alkyne-containing analyte pairs. Capillary columns prepared using different surface activation methods and coated with identical [P 66614 + ][Cl - ] IL stationary phase showed indistinguishable temperature-dependent trends in summation of resolution value and selectivity. An evaluation of analyte-specific selectivity provides insight into the characteristic separation behavior of the stationary phases and enables identification of analyte classes that are more efficiently separated on the [P 66614 + ]-based IL stationary phases compared to conventional stationary phase materials.

Chromatographic selectivity↗

DOE OSTI2020

The Sensitivity of Joint Inversions of Seismic and Geodynamic Data to Mantle Viscosity

Seismic tomography has revealed the existence of large-scale velocity heterogeneities in the mantle. The interpretation of seismic velocity anomalies in terms of temperature and chemical composition is nonunique. We use geodynamic observations including gravity, plate motions, dynamic topography, and excess ellipticity of the core-mantle boundary combined with seismic observations to investigate the thermo-chemical structure of the mantle through joint inversions. An outstanding issue, however, is the physical connection between mantle density anomalies and the surface geodynamic observations, which requires knowledge of the mantle viscosity structure. Here we perform joint inversions assuming different viscosity profiles and examine the dependence of the results on the viscosity. We first assume that mantle heterogeneity is due to thermal variations, which places a constraint on the relation between seismic velocity and density, and we subsequently relax the constraint to allow for potential nonthermal effects. In all of our joint inversions, a nonthermal origin of density anomalies is required to explain the geodynamic data, though the amount varies with the assumed viscosity structure. A common observation is a high-density chemical signal in the center of the large low-shear-velocity provinces at the base of the mantle resulting in a near neutral or slightly dense overall buoyancy there. Using the derived density models and their corresponding viscosity profiles, we also calculate instantaneous mantle flow fields. The predicted flow fields derived from joint inversions are generally similar but are quite different from flow fields using density models derived from a posteriori scaling of pure seismic tomography models.

58 GEOSCIENCES↗

DOE OSTI2025

Probing polarity structure–function relationships in amine–water mixtures

This study investigates the relationships between chemical structure, polarity, and miscibility in solvent–water systems to elucidate the mechanisms underlying the thermoresponsive hydrophilicity of amines. By integrating complementary analyses of Kamlet–Taft parameters and relative permittivity, we reveal that hydrogen bonding and nanoscale ordering, i.e., molecular-level and mean-field, respectively, underlie amine–water interactions, which, in turn, influence the thermomorphic hydrophilicity.

Dach, Elizabeth [Columbia University, New York, NY↗

NASA NTRS1998

EOS Interdisciplinary Investigation: Observational and Modeling Studies of Radiative, Chemical, and Dynamical Interactions in the Earth's Atmosphere

A 3-dimensional model of atmospheric dynamics and photochemistry has been developed from the primitive equations in isentropic coordinates. The model extends from the upper troposphere through the middle atmosphere and is driven by observed dynamical and chemical structure in the troposphere. The model's formulation is entirely spectral: Horizontal structure is represented in terms of vector Hough functions, which explicitly partition the motion into its rotational and divergent components. This formulation enables the model's computational performance to be increased dramatically by filtering high-frequency gravity waves, which do not affect PV conservation. Vertical structure is represented in terms of eigenfunctions that follow from the primitive equations in isentropic coordinates. The model's fully spectral formulation enables scale-selective dissipation, necessary for numerical stability, to be applied at 6th order-in all 3 coordinate directions. This feature leaves all but the shortest vertical scales undamped and, consequently, allows potential vorticity and chemical tracers to be conserved quite accurately, distinctly better than in the model's layered counterpart. These dynamical features are complemented by a basic but fairly complete treatment of gas phase photochemistry, which accounts for some 48 chemical species, diurnally-varying SW absorption by O2 and O3, and LW cooling calculated via a detailed band calculation of radiative transfer. Driven by observed tropospheric structure, the 3D model reproduces observed structure in the middle atmosphere, inclusive of transport by the Brewer-Dobson circulation and accompanying chemical variations. Calculated residual motion is consistent with diabatic cooling rates, poleward transport, and descent in the polar night derived from satellite measurements of chemical tracers made from LIMS, SAGE, and UARS. The model also reproduces the observed structure of chemical species like O3, HNO3, and ClO. At the same time, it provides a respectable 3D simulation of the wintertime increase of midlatitude total ozone, as well as its geographical structure observed by Nimbus-7 TOMS. The 3D model has been used to explore the origin of diabatic upwelling in the tropical lower stratosphere, which has been related to planetary wave absorption in the winter- time stratosphere, as well as to influences from tropospheric convection at the tropical tropopause.

Salby, Murry L.↗

DOE OSTI2022

Local cation order and ferrimagnetism in compositionally complex spinel ferrites

We present an exploration of a family of compositionally complex cubic spinel ferrites featuring combinations of Mg, Fe, Co, Ni, Cu, Mn, and Zn cations, systematically investigating the average and local atomic structures, chemical short-range order, magnetic spin configurations, and magnetic properties. All compositions result in ferrimagnetic average structures with extremely similar local bonding environments; however, the samples display varying degrees of cation inversion and, therefore, differing apparent bulk magnetization. Additionally, first-order reversal curve analysis of the magnetic reversal behavior indicates varying degrees of magnetic ordering and interactions, including potentially local frustration. Finally, reverse Monte Carlo modeling of the spin orientation demonstrates a relationship between the degree of cation inversion and the spin collinearity. Collectively, these observations correlate with differences in synthesis procedures. This work provides a framework for understanding magnetic behavior reported for “high-entropy spinels,” revealing many are likely compositionally complex oxides with differing degrees of chemical short-range order—not meeting the community established criteria for high or medium entropy compounds. Moreover, this work highlights the importance of reporting complete sample processing histories and investigating local to long-range atomic arrangements when evaluating potential entropic mixing effects and assumed property correlations in high entropy materials.

36 MATERIALS SCIENCE↗

DOE OSTI2025

Generative AI for design of nanoporous materials: review and future prospects

Generative artificial intelligence (AI) is emerging as a powerful tool for advancing the design of nanoporous materials such as metal–organic frameworks, covalent–organic frameworks, and zeolites. These materials have potential application in important areas such as carbon capture, catalysis, gas storage, chemical separation, and drug delivery due to their modular, tunable structures, and their performance in these areas depends on precise control over their structure, chemical functionalities, and properties. Herein, we provide a review of generative AI algorithms that are emerging as powerful tools for the design of nanoporous materials, namely generative adversarial networks, variational autoencoders, diffusion models, genetic algorithms, reinforcement learning, and large language models. Some models are particularly good at generating diverse and high-quality designs, while others excel at exploring large design spaces or optimizing materials with desired properties. Certain algorithms also allow for efficient transitions between different designs, and some offer versatility in generating materials based on textual input. We discuss the advantages, limitations, and applications of these algorithms in porous material design and emphasize the future potential of integrating AI with experimental workflows to accelerate the development and validation of AI-generated materials.

36 MATERIALS SCIENCE↗

NASA NTRS1983

Growth, characterization, and properties of metastable and modulated semiconductor structures - Prospects for future studies

The general field of preparation and study of metastable and modulated semiconductor structures has progressed rapidly in recent years. This short overview offers an assessment of the progress and current understanding in the areas of fabrication, characterization, and utilization of these new material systems. The discussion includes the more prominent growth techniques, theoretical and experimental analysis of growth kinetics, and an overview of structural, chemical, electronic, and optical characterization. The probable application of these structures for the technological development of new device structures and concepts is considered. The discussion particularly emphasizes the prospects for future studies in view of the specific current understanding.

Grunthaner, F. J.↗

DOE OSTI2024

Spin-Controllable Dynamics in Defect-Engineered Carbon Nanotubes as Single Photon Emitters: Data-Driven Modeling and Computations

Quantum technologies, such as quantum computing and sensing, require efficient single-photon emission (SPE) sources that operate at room temperature in telecom wavelengths. While several materials can serve as SPE sources, no single platform meets all the criteria for efficiency, ambient operation, and scalability. Single-walled carbon nanotubes (SWCNTs) with covalently attached molecules offer a promising solution. Their SPE can be easily tuned via modifications of the SWCNT's diameter, chirality, and bonded molecules, enabling emission across near-IR to telecom wavelengths at ambient conditions. However, to fully realize the potential of SWCNTs and unlock their quantum capabilities, a deeper understanding of how structural defects from molecular adducts affect their emission and competing photoexcited processes is essential. To address this gap in our knowledge, this project combined quantum chemistry calculations with data-driven methods of cheminformatics (QSAR) and machine learning (ML). The developed computational approaches have provided several design strategies for covalent functionalization of SWCNTs to improve their optical response. The collaboration with Los Alamos National Lab (LANL) enabled direct comparison of computational and experimental data, facilitating method validation. This partnership was enhanced through access to LANL's Center for Integrated Nanotechnologies (CINT) utilizing User Facility Program and summer internships, which provided three NDSU graduate students with hands-on experience at LANL. The outcomes of this project included (1) Advancing the current stage of computational methods in accurate modeling of non-adiabatic spin-dependent photoexcited dynamics and its applicability to nanosystems consisting of thousands of atoms, realized as open-access codes linked to existing DFT-based software; (2) Establishing the relationship between the structure of adducts and SWCNTs and intrinsic excitonic and spin properties of defect states for guiding novel synthetic strategies and experimental probes of chemically functionalized SWCNTs as near-IR emitting materials; (3) Generating virtual libraries of hypothetical functionalized SWCNTs for virtual screening of their chemical structures and optical properties, leveraging new functionalities of SWCNTs; (4) Offering a unique experience for NDSU graduate students that prepared them for future scientific careers related to materials modeling and big data processing. These results were summarized in 12 published journal papers and 3 recently submitted papers. One of a key finding is that the position of defect sites on the SWCNT surface primarily drives the emission redshift (up to 100 meV), while the polarity of the defect-inducing molecules has a much smaller effect (~10 meV). However, the electron-donating or withdrawing properties of a molecule influence selecting reactivity of defect sites. These insights important for optimizing synthetic protocols for desired emissions in SWCNTs. We also revealed that the interaction between two defects at various positions on the SWCNT enhances the redshift and optical activity of states, favoring strong near-IR emission. This suggests that manipulations in defect concentrations is a promising strategy for controlling efficient emission. Mostly important, the defect position was found controllable by the spin states of photoexcited intermediates: Excited aromatic molecules form ortho defects with SWCNTs at their singlet states in the presence of oxygen, while oxygen-free conditions favor para defects via the triplet-state mechanism. Additionally, a heat-activated [2+2] cycloaddition reaction facilitates divalent defect formation with fewer bonding positions that narrows emission bands. These groundbreaking findings have been experimentally validated and significantly advance our understanding of defect chemistry in SWCNTs. Using a novel encoding technique and 3D-MoRSE descriptors, we developed highly accurate ML/QSAR models to predict both the 3D structure and optical properties of SWCNTs with chemical defects. This model enabled the creation of a virtual library of 125,556 structures, providing new insights into the relationship between SWCNT-defect structure and emission.

77 NANOSCIENCE AND NANOTECHNOLOGY↗

NASA NTRS1993

Viscoelastic characterization of thin-film polymers exposed to low Earth orbit

The materials made available through the Long Duration Exposure Facility (LDEF) satellite provide a set of specimens that can be well characterized and have a known exposure history with reference to atomic oxygen and ultraviolet radiation exposure. Mechanical characteristics measured from control samples and exposed samples provide a data base for predicting the behavior of polymers in low earth orbit. Samples of 1.0 mil thick low density polyethylene were exposed to the low earth orbit environment for a period of six years. These materials were not directly exposed to ram atomic oxygen and offer a unique opportunity for measuring the effect of atomic oxygen and UV radiation on mechanical properties with little concern to the effect of erosion. The viscoelastic characteristics of these materials were measured and compared to the viscoelastic characteristics of control samples. To aid in differentiating the effects of changes in crystallinity resulting from thermal cycling, from the effects of changes in chemical structure resulting from atomic oxygen/UV attack to the polymer, a second set of control specimens, annealed to increase crystallinity, were measured as well. The resulting characterization of these materials will offer insight into the impact of atomic oxygen/UV on the mechanical properties of polymeric materials. The viscoelastic properties measured for the control, annealed, and exposed specimens were the storage and loss modulus as a function of frequency and temperature. From these datum is calculated the viscoelastic master curve derived using the principle of time/temperature superposition. Using the master curve, the relaxation modulus is calculated using the method of Ninomiya and Ferry. The viscoelastic master curve and the stress relaxation modulus provide a direct measure of the changes in the chemical or morphological structure. In addition, the effect of these changes on long-term and short-term mechanical properties is known directly. It should be noted that the dependence on directionality for the polymer films was considered since these films were manufactured by a blown-film process.

Letton, Alan↗

DOE OSTI2021

Composition and Structure of Fluorescent Graphene Quantum Dots Generated by Enzymatic Degradation of Graphene Oxide

The broad applications of carbon nanomaterials (CNMs) in both materials and life sciences necessitate investigation of their metabolites due to the inevitable contact of CNMs and biological systems. Graphene oxide (GO), along with other types of CNMs, can be enzymatically degraded by myeloperoxidase (MPO), an enzyme released during the innate immune response. However, the enzymatic degradation products are neither well-defined nor well-understood. Some products generated during MPO-catalyzed degradation of GO could emit blue photoluminescence (PL) and were simply dubbed graphene quantum dots (GQDs) without further elucidating their structures. In this work, we use liquid chromatography-mass spectrometry (LC-MS) to isolate and elucidate chemical structures of the MPO-catalyzed degradation products. A general chemical formula screening workflow was developed for the GQDs, which are in the form of polyaromatic hydrocarbons (PAHs), obtained in the degradation products. Structures of the PAHs responsible for the blue PL were further proposed using density functional theory (DFT) calculations. Our results indicated that structures with several conjugated benzene rings are likely to generate the observed PL. This work provides insights into the mechanism of enzymatic degradation and open opportunities for fluorescence imaging of GO in biological systems.

composition and structure screening↗

NASA NTRS1999

Photochemistry of Pluto's Atmosphere

This work include studies of two problems: (1) Modeling thermal balance, structure. and escape processes in Pluto's upper atmosphere. This study has been completed in full. A new method, of analytic solution for the equation of hydrodynamic flow from in atmosphere been developed. It was found that the ultraviolet absorption by methane which was previously ignored is even more important in Pluto's thermal balance than the extreme ultraviolet absorption by nitrogen. Two basic models of the lower atmosphere have been suggested, with a tropopause and a planetary surface at the bottom of the stellar occultation lightcurve, respectively, Vertical profiles, of temperature, density, gas velocity, and the CH4 mixing ratio have been calculated for these two models at low, mean, and high solar activity (six models). We prove that Pluto' " s atmosphere is restricted to 3060-4500 km, which makes possible a close flyby of future spacecraft. Implication for Pluto's evolution have also been discussed. and (2) Modeling of Pluto's photochemistry. Based on the results of (1), we have made some changes in the basic continuity equation and in the boundary conditions which reflect a unique can of hydrodynamic escape and therefore have not been used in modeling of other planetary atmospheres. We model photochemistry of 44 neutral and 23 ion species. This work required solution of a set of 67 second-order nonlinear ordinary differential equations. Two models have been developed. Each model consists of the vertical profiles for 67 species, their escape and precipitation rates. These models predict the chemical structure and basic chemical processes in the current atmosphere and possible implication of these processes for evolution. This study has also been completed in full.

Krasnopolsky, Vladimir A.↗

DOE OSTI2025

Effect of Annealing on Direct Recycled NMC Cathodes

A substantial number of electric vehicle batteries are poised to reach end-of-life conditions in the next decade. Direct recycling has advantages over typical recycling processes because it preserves the chemical structure of the material. One key step of direct recycling materials like nickel manganese cobalt oxide (NMC) cathodes is relithiation, which includes replacing the depleted lithium inventory in the cathode and annealing the material to fix crystallographic degradation. This work uses multiple characterization techniques (synchrotron X-ray diffraction, Ni X-ray absorption near edge structure, scanning transmission electron microscopy) to understand the lithiation mechanism of degraded and chemically relithiated NMC 622. Despite the necessary reconstruction after relithiation being limited to the surface of the degraded NMC 622, a high annealing temperature of 720 °C is still necessary to restore the NMC 622 structure back to pristine condition after relithiation. This work also finds that treating degraded NMC 622 with an annealing step is sufficient to restore key electrochemical and structural properties, other essential features of pristine NMC 622 material such as particle porosity and morphology are largely unaffected. Understanding the effect of this annealing step has important implications on defining the degree of success of any given direct recycling strategy.

36 MATERIALS SCIENCE↗

DOE OSTI2024

Molecular Vision - Multimodal, multitask retrieval of molecular structure from measured signatures for reference-free compound identification

We are currently at risk of generating false conclusions based on limited methods to identify small molecules in biological systems and in chemical forensics. By definition, the chemical structures of novel small molecules have not been determined, let alone measured or synthesized. Currently, unambiguous structure determination of small molecules is constrained by the time and effort needed to isolate compounds and perform de novo structure elucidation using laboratory-based methods, significantly extending the time to inform mitigation strategies. To address this gap, we have developed a deep learning approach to directly map molecular structure to experimental signatures. We aim to unify measurement technologies employed in untargeted small molecule identification studies—such as infrared (IR) spectrometry, tandem mass spectrometry (MS/MS), ion mobility spectrometry-derived collision cross section (CCS)—through use of a multimodal, multitask deep learning architecture. Where existing methods require direct generation of information-rich spectra and/or properties, an inherently difficult task, we will simplify molecular signature-based identification by posing the problem as a recognition or retrieval task. The model is thus presented with relevant endpoints – structure and one or more molecular signatures – and need only determine whether they are semantically related. Thus, our approach offers the following advantages over existing techniques: (i) circumvents difficulties associated with direct generation of molecular signatures from structure and structure from signatures; (ii) incorporates multiple molecular signatures simultaneously, as available, to support identification; and (iii) enables rapid computation of structural embeddings toward broad coverage of known chemical space. Taken together, the approach removes the need to explicitly obtain or compute reference spectra, representing a powerful method for compound identification that requires only experimentally observed signatures.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2023

Nanoscale chemical imaging with structured X-ray illumination

High-resolution imaging with compositional and chemical sensitivity is crucial for a wide range of scientific and engineering disciplines. Although synchrotron X-ray imaging through spectromicroscopy has been tremendously successful and broadly applied, it encounters challenges in achieving enhanced detection sensitivity, satisfactory spatial resolution, and high experimental throughput simultaneously. In this work, based on structured illumination, we develop a single-pixel X-ray imaging approach coupled with a generative image reconstruction model for mapping the compositional heterogeneity with nanoscale resolvability. This method integrates a full-field transmission X-ray microscope with an X-ray fluorescence detector and eliminates the need for nanoscale X-ray focusing and raster scanning. We experimentally demonstrate the effectiveness of our approach by imaging a battery sample composed of mixed cathode materials and successfully retrieving the compositional variations of the imaged cathode particles. Bridging the gap between structural and chemical characterizations using X-rays, this technique opens up vast opportunities in the fields of biology, environmental, and materials science, especially for radiation-sensitive samples.

Li, Jizhou↗

DOE OSTI2023

An investigation on the structural stability of $\mathrm{ZIF}$-8 in water versus water-derived oxidative species in aqueous environment

We report the zeolitic-imidazolate-framework-8 (ZIF-8) is one of the extensively studied metal-organic frameworks (MOF) materials because of its unique structure. For its potential applicability in numerous fields, it becomes crucial to have detailed studies on the structural stability of ZIF-8, especially in aqueous environments. A number of studies have been conducted to investigate the breakdown process of the ZIF-8 structure in water; which is known as the hydrolysis of ZIF-8. However, those studies reported different opposing experimental observations on the role of water on the structural stability of ZIF-8, which created obscurity in understanding this phenomenon. This study explored the effects of different water-derived species on the structural stability of ZIF-8; specifically, examined the effects of only water and water with different oxidative species that may be generated by water molecules' dissociation under external energy or catalyst presence. To this effort, we experimentally probed the physical and chemical structural changes of ZIF-8 in DI water and three different solutions of hydrogen peroxides (H 2 O 2 ); taking H 2 O 2 as the source of oxidative species. To assess the changes in elemental compositions, chemical bonds, functional groups, crystal structure, and morphology, all the samples were analyzed by X-ray photoelectron spectroscopy (XPS), energy-dispersive x-ray (EDX) spectroscopy, Fourier Transform Infrared (FTIR) spectroscope, X-ray diffractometer (XRD), and scanning electron microscope (SEM). Significant structural changes in ZIF-8 occurred mainly in the presence of oxidative species in water. Notably, oxidative species' concentration exceeding 1 M heightened the deformation of the ZIF-8 structure.

36 MATERIALS SCIENCE↗

DOE OSTI2020

Nanoscale x-ray and electron tomography

We present that three-dimensional (3D) tomographic imaging of the structural, chemical, and physical properties of a material provides key knowledge that links the structure of a material to both its processing and structure that is central to studies across a broad spectrum of materials. For many decades, tomography using x-rays or electrons has proven to be an essential 3D characterization tool. In recent years, advances in technology have significantly pushed the envelope of these techniques in many respects, enabling new imaging capabilities at the nanometer and atomic scale. This article highlights several such developments in nanoscale x-ray and electron tomography. The five articles that appear in this issue of MRS Bulletin discuss research frontiers that include multimodal x-ray tomography at the nanoscale, x-ray spectroscopic tomography, dark-field x-ray microscopy, electron nanotomography for functional nanomaterials, and atomistic imaging by electron tomography. Lastly, these articles give a holistic view of the status of these techniques and promising future directions, as well highlighting their applications for scientific problems.

36 MATERIALS SCIENCE↗