Search NASA⌕ Search

SEARCH · Search NASA

Results for “xanes”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 109 records · Page 6

The Role of Electron Localization in Covalency and Electrochemical Properties of Lithium-Ion Battery Cathode Materials

Following the fundamental research conducted by J. B. Goodenough, the important role of electron localization induced by elemental substitution is studied. The size and electron negativity of host and substituting ions are two important factors in tuning material properties such as local structure and transition metal (TM) oxygen covalency. However, another factor, electron localization, which is widely studied in catalyst research but largely overlooked for battery materials, deserves systematic studies. A combined investigation using synchrotronbased X-ray spectroscopy and theoretical calculations is carried out on the Li-Co-Mn-O model system in which the substituting cation Mn 4+ , with its 3d 3 electronic structure, is used as a promoter for electron localization. Results indicate that electron localization greatly influences the Co - O bond by making it less covalent, which increases the delithiation voltage. It is also found that during charge/discharge, electron localization tends to make TM K-edge X-ray absorption near edge spectroscopy (XANES) spectra show a more “rigid shift” behavior while electron delocalization makes the XANES exhibit a “shape change.” It clearly explains why the K-edge XANES data of some TM oxides show no “rigid shift” while the nominal valence states changed. This work highlights the importance of electron localization with guidance for XANES interpretation.

25 ENERGY STORAGE↗

Effect of oxidation on the release of multiple metals from industrially polluted sediments and synchrotron-based evidence of Cu–S dynamic association

Disposal operations for industrially polluted sediments are usually accompanied by disturbance and resuspension, which can induce metal remobilization and secondary pollution. Evaluating the risk of metal release under various redox conditions is fundamental for predicting contaminant mobilization and guiding remediation measures. An abandoned oxidation pond, Yanjia Lake, China, was selected as a typical industrially polluted site. Re-suspension experiments were carried out by mixing polluted sediments with lake water under oxic or anoxic conditions, then investigating the effect of oxidation conditions on the release of multiple metals. Metal concentrations and aqueous chemistry in the overlying water were monitored. Synchrotron-based methods, including X-ray absorption near-edge structure (XANES) and extended X-ray absorption fine structure (EXAFS), were used to characterize oxidation states and coordination conditions of metals in sediments. The release of metals, including Cr, Co, Ni, Cu, Zn, Se, Mo, Sn, Cd, and Pb, was enhanced under oxic vs. anoxic conditions. The XANES analysis revealed that elevated Cr and Zn concentrations under oxic conditions likely resulted from the oxidation of Cr(III) and oxidizing dissolution of ZnS, respectively. K-edge Cu XANES, S XANES, and Cu EXAFS analyses reconstructed the Cu–S association, indicating that S-related oxidation promoted Cu release and Cu–O partly replaced Cu–S in the sediment after a 7-day oxic treatment. The release of most metals was promoted under oxic conditions, resulting from the oxidation of sulfides and metals as indicated by aqueous and synchrotron-based evidence. The risk of secondary pollution is greatly enhanced under oxic conditions, which suggests that measures should be taken to minimize the redox disturbance during sediment remediation. This information can guide the management of sediments in Yanjia Lake and other contaminated sites with similar properties.

54 ENVIRONMENTAL SCIENCES↗

Interpreting the Operando X-ray Absorption Near-Edge Structure of Supported Cu and CuPd Clusters in Conditions of Oxidative Dehydrogenation of Propane: Dynamic Changes in Composition and Size

Supported subnano-cluster catalysts are highly dynamic, developing true active sites only under the pressures and temperatures of reaction conditions. Operando X-ray absorption near-edge structure (XANES) spectroscopy can track changes in the oxidation state and the local environment of cluster atoms, providing insight into the development of these active sites. While bulk metal, oxide, and hydroxide standards are often used for fitting experimental XANES spectra to obtain average oxidation states, we recently showed that computed cluster standards of relevant compositions are a more suitable basis, producing more accurate fits. Here, we theoretically interpret the operando XANES of supported Cu 3 Pd and Cu 4 clusters during temperature-programmed reaction (TPRx) of oxidative dehydrogenation of propane. We use an expanded basis set including both globally optimized computed clusters and bulk standards. Not only can we track reversible composition/oxidation state change with temperature, but also the irreversible growth of the bulk fraction upon heating, which we attribute to cluster sintering. This has important implications for the mechanism of the catalyzed reaction and the nature of the available active sites. Here, we propose that operando XANES provides most significant insight into the nature of supported cluster catalysts in reaction conditions when interpreted using mixed computed cluster and bulk standards.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Harnessing Neural Networks for Elucidating X-ray Absorption Structure–Spectrum Relationships in Amorphous Carbon

Improved understanding of structural and chemical properties through local experimental probes, such as X-ray absorption near-edge structure (XANES) spectroscopy, is crucial for the understanding and design of functional materials. In recent years, significant advancements have been made in the development of data science approaches for the automated interpretation of XANES structure–spectrum relationships. However, existing studies have primarily focused on crystalline solids and small molecules, while fewer efforts have been devoted to disordered systems. Thus, in this work, we demonstrate the development of neural network models for predicting and interpreting XANES spectra of amorphous carbon (a-C) from local structural descriptors. Comparison between different structural descriptors expectedly shows that the inclusion of both bond length and bond angle information is necessary for an accurate prediction of the spectra. Among the descriptors considered in this work, we find that the local many-body tensor representation yields the highest accuracy and greatest interpretability so that it can be leveraged to understand the importance of structural motifs in determining XANES spectra. Furthermore, we also discuss performance of neural network models for predicting both local structure features, such as bond lengths and bond angles, and global chemical composition, such as the sp:sp 2 :sp 3 ratio.

36 MATERIALS SCIENCE↗

Latent Representation Learning for Structural Characterization of Catalysts

Supervised machine learning-enabled mapping of the X-ray absorption near edge structure (XANES) spectra to local structural descriptors offers new methods for understanding the structure and function of working nanocatalysts. We briefly summarize a status of XANES analysis approaches by supervised machine learning methods. We present an example of an autoencoder-based, unsupervised machine learning approach for latent representation learning of XANES spectra. This new approach produces a lower-dimensional latent representation, which retains a spectrum–structure relationship that can be eventually mapped to physicochemical properties. Furthermore, the latent space of the autoencoder also provides a pathway to interpret the information content “hidden” in the X-ray absorption coefficient. Our approach (that we named latent space analysis of spectra, or LSAS) is demonstrated for the supported Pd nanoparticle catalyst studied during the formation of Pd hydride. By employing the low-dimensional representation of Pd K-edge XANES, the LSAS method was able to isolate the key factors responsible for the observed spectral changes.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Chemical state mapping of simulant Chernobyl lava-like fuel containing material using micro-focused synchrotron X-ray spectroscopy

Uranium speciation and redox behaviour is of critical importance in the nuclear fuel cycle. X-ray absorption near-edge spectroscopy (XANES) is commonly used to probe the oxidation state and speciation of uranium, and other elements, at the macroscopic and microscopic scale, within nuclear materials. Two-dimensional (2D) speciation maps, derived from microfocus X-ray fluorescence and XANES data, provide essential information on the spatial variation and gradients of the oxidation state of redox active elements such as uranium. In the present work, we elaborate and evaluate approaches to the construction of 2D speciation maps, in an effort to maximize sensitivity to the U oxidation state at the U L 3 -edge, applied to a suite of synthetic Chernobyl lava specimens. Our analysis shows that calibration of speciation maps can be improved by determination of the normalized X-ray absorption at excitation energies selected to maximize oxidation state contrast. The maps are calibrated to the normalized absorption of U L 3 XANES spectra of relevant reference compounds, modelled using a combination of arctangent and pseudo-Voigt functions (to represent the photoelectric absorption and multiple-scattering contributions). We validate this approach by microfocus X-ray diffraction and XANES analysis of points of interest, which afford average U oxidation states in excellent agreement with those estimated from the chemical state maps. This simple and easy-to-implement approach is general and transferrable, and will assist in the future analysis of real lava-like fuel-containing materials to understand their environmental degradation, which is a source of radioactive dust production within the Chernobyl shelter.

36 MATERIALS SCIENCE↗

Sulfur Species in Zinc-Rich Condylar Zones of a Rat Temporomandibular Joint

We performed synchrotron-based micro-X-ray absorption near-edge spectroscopy (µ-XANES) coupled with micro-X-ray fluorescence (µ-XRF) for the identification of elements that included biometal zinc (Zn) and nonmetal sulfur (S) (and its species) in the condylar zones of a rat temporomandibular joint (TMJ). Zone-specific spatial localization of biometal Zn and nonmetal S from a materials viewpoint when correlated with hypoxia inducible factor-1α (HIF-1α) (a surrogate for tissue oxygenation) can provide insights into Zn-specific redox pathways at the vulnerable subchondral interface. Histologic localization of Zn, HIF-1α, and sulfur-rich proteoglycans (PGs) were mapped using an optical microscope. The µ-XRF maps coupled with site-specific micro-X-ray diffraction (µ-XRD) patterns were used to underline Zn-incorporated biological apatite in the subchondral bone and the bone of a rat TMJ condyle. Results demonstrated an association between Zn, PG, and HIF-1α histologic maps with µ-XRF, µ-XANES, and µ-XRD data and provided insights into plausible biological S species in Zn-enriched zones of a rat TMJ condyle. Spatially localized Zn and S underscore their roles in cell and tissue functions in a zone-specific manner. Elemental Zn with organic and inorganic S species at the cartilage-bone interface and the biomineral phase of Zn-enriched biological apatite from subchondral bone to condylar bone were ascertained using µ-XRF-XANES and µ-XRF-XRD. The coupled µ-XRF-XANES in situ complemented with µ-XRF-XRD in situ and immunohistochemistry provided valuable biological insights into zone-specific biological pathways in rat TMJ condyles. Based on these data, we present a workflow to reliably map and correlate S species within Zn-enriched regions of cartilage, bone, and their interface. We suggest the use of this correlative and complementary microspectroscopic spatial information for zone-specific localization of biometal Zn and nonmetal S to gain insights into plausible microanatomy-specific oxidative stress in the TMJ.

apatites↗

Soil and Water Chemistry and Trace Metal Extractability and Speciation in Wetland Soils from Illinois and South Carolina and Stream Sediments from Tennessee

Dataset revised on October 15, 2021. This revision adds sulfur and iron X-ray absorption near-edge structure spectra for the wetland soils and stream sediments from the field areas. It also renames the sample locations in a way that is more intuitive to readers of the companion paper that is under review. Finally, the data filenames and organization have been updated in their labeling to parallel the data sources in the associated paper. The abstract text and methods were also revised to reflect the data that was added to the dataset.Trace metals are essential for microbially-mediated biogeochemical processes occurring in anoxic wetland soils and stream bed sediments, such as denitrification, methanogenesis, and mercury methylation. Low availability of these elements may potentially inhibit key components of anaerobic carbon and nitrogen cycling and contaminant transformation. The solid-phase speciation of trace metals likely plays an important role in controlling their bioavailability. Metal speciation is well studied in contaminated soils and sediments as well as those naturally elevated in trace metals. However, less is known regarding the chemical forms of trace metals in systems having concentrations similar to geological background levels, the very settings where metal limitations may be most prevalent. We have investigated trace metal concentrations, extractability, and solid-phase speciation in three freshwater subsurface aquatic systems: marsh wetland soils, riparian wetland soils, and the sediments of a streambed.Data are provided for marsh wetland soils at Argonne National Laboratory, riparian wetland soils in the Tims Branch watershed at Savannah River National Laboratory, and stream bed sediments from East Fork Poplar Creek near Oak Ridge National Laboratory. Soil and sediment elemental abundances, mineralogy, and extractable nutrients as well as dissolved major elements, anions, trace metals, and nutrients in the overlying surface waters are provided. In addition, the results of sequential chemical extraction for the trace metals cobalt, nickel, copper, and zinc from the soils and sediment are reported as well as X-ray absorption near-edge structure (XANES) spectra in these materials are reported. To aid interpretation of these data, XANES spectra of sulfur in the soils and sediments as well as both XANES and extended X-ray absorption fine structure (EXAFS) spectra of iron in these materials are reported. The data package also includes the XANES spectra of reference standards and a potential interferent in the measurements. All data are provided in text-based CSV format with header sections indicating the data contained in each file and the corresponding units. Note that "u" is used in place of Greek lower case mu to indicate the micro prefix on units.

54 ENVIRONMENTAL SCIENCES↗

Deep Learning for Spectroscopic X-ray Nano-Imaging Denoising

Synchrotron transmission X-ray microscopy with absorption near edge structure (TXM-XANES) is a powerful tool for investigating the structure and composition of materials at nano- to meso-scales. It is, however, often challenged by high levels of noise that obscure critical details at the single-pixel level. To address this issue, a deep learning-based algorithm is developed for suppressing the image noise, grounded in self-supervised learning principles. In contrast to traditional image denoising methods, this approach successfully enhances the visibility of fine details while significantly reducing the noise in the X-ray images. Through this advancement, the potential of the approach for improving the accuracy and interpretability of the TXM-XANES data is demonstrated, thereby enabling more precise detection of nanoscale phenomena such as inhomogeneous cation redox and metal segregation in battery cathode materials. This technique offers an effective new avenue for harnessing the full potential of synchrotron TXM-XANES imaging, paving the way for a range of exciting new studies in materials science and beyond.

36 MATERIALS SCIENCE↗

Consistent Controls on Trace Metal Micronutrient Speciation in Wetland Soils and Stream Sediments

Trace metal are essential for microbially-mediated biogeochemical processes occurring in anoxic wetland soils and stream bed sediments, but low availability of these elements may inhibit anaerobic element cycling and transformations. Solid-phase speciation is likely a critical control on trace metal availability but has seen limited study in anoxic systems having concentrations similar to geological background levels, where metal limitations may be most prevalent. We have investigated trace metal concentrations and solid-phase speciation in three freshwater subsurface aquatic systems: marsh wetland soils, riparian wetland soils, and the sediments of a streambed. These systems displayed low solid-phase trace metal concentrations, generally at or below geological background levels, which generally followed the trend Zn > Cu ≈ Ni > Co and showed no correlation with major element compositions. All soils and sediments were dominated by quartz but varied in clay mineralogy as well as the organic matter, total sulfur, and total iron contents. X-ray absorption near-edge structure (XANES) spectroscopy shows that sulfur speciation in both wetlands is dominated by organic sulfur. Elemental sulfur and iron sulfides together made up <25% of the sulfur in the wetland soils, but the distribution between inorganic and organic forms was reversed in the stream sediments. Ferrous and ferric iron in clay minerals were common species identified by both XANES and extended X-ray absorption fine structure (EXAFS) spectroscopies at all sites. Iron(III) oxides were substantial components in all but the marsh wetland soils. Quantitative analysis of copper, nickel, and zinc XANES spectra revealed similar metal speciation across all sites. Copper speciation was dominated by sulfides, adsorbed species, and minor amounts of copper bound to organic matter; no metallic copper was detected. Nickel speciation also varied little and was dominated by nickel in clay mineral octahedral sheets and nickel sulfide, with adsorbed species also present. Zinc speciation was slightly more varied, with the marsh wetland soils and stream bed sediments containing adsorbed species, zinc associated with clay mineral structures, and zinc bound to reduced sulfur groups on organic matter, whereas the riparian wetland soils lacked clay-associated zinc but contained zinc sulfide. Trace metals bound to reduced sulfur occurred at every site, with a greater sulfur-bound fraction for copper. The fractional abundance of sulfur-bound species showed no relationship with soil or sediment total sulfur content, which varied by two orders of magnitude. More broadly, the observations in this study suggest that trace metal speciation in freshwater wetland soils and stream sediments is consistently dominated by a small set of recurring components which are distinct for each metal. Furthermore, this may represent a general geochemical phenomenon in anoxic soils and sediments containing trace metals at background concentrations (as low as 3 µg g -1 ) that was not predicted from systems that are contaminated with or naturally-enriched in copper, nickel, or zinc.

54 ENVIRONMENTAL SCIENCES↗

Size Dependence of Lattice Parameter and Electronic Structure in CeO2 Nanoparticles

Intrinsic properties of a compound (e.g. electronic structure, crystallographic structure, optical and magnetic properties) define notably its chemical and physical behavior. In the case of nanomaterials, these fundamental properties depend on the occurrence of quantum mechanical size effects and on the considerable increase of the surface to bulk ratio. However, the literature on this size-dependence and on the involved mechanisms is quite elusive and scarce. Here, we explore the size-dependence of both crystal and electronic properties of CeO2 nanoparticles (NPs) with different sizes by state-of-the art spectroscopic techniques. XRD, XPS and HERFD-XANES demonstrate that the as-synthesized NPs crystallize in the fluorite structure and they are predominantly composed of CeIV ions. The strong dependence of the lattice parameter with the NPs size was attributed to the presence of adsorbed species at the NPs surface thanks to FTIR and TGA measurements. In addition, the size-dependence of the eg level in the Ce LIII XANES spectra was experimentally observed by HERFD-XANES and confirmed by theoretical calculations.

Lanthanide, CeO2, HEFRD-XANES, Electronic structur↗

X-ray Absorption Spectroscopy Studies of a Molecular CO 2 -Reduction Catalyst Deposited on Graphitic Carbon Nitride

Metal-ligand complexes have been extensively explored as well-defined molecular catalysts in small molecule activation reactions such as carbon dioxide (CO 2 ) reduction. Many hybrid photocatalysts have been prepared by coupling such complexes with photoactive surfaces for use in solar CO 2 reduction. In this work, we employ X-ray absorption near edge structure (XANES) and extended X-ray absorption fine structure (EXAFS) spectroscopies, density functional theory (DFT) and computational XANES modeling to interrogate the structure of a hybrid photocatalyst consisting of a macrocyclic cobalt complex deposited on graphitic carbon nitride (C 3 N 4 ). Results show that the cobalt complex binds on C 3 N 4 through surface OH or NH 2 groups. By refining the local geometry and binding sites of this well-defined molecular cobalt complex on C 3 N 4 , here we established an important benchmark for modeling a large class of molecular catalysts that can be adapted to in situ/operando studies and further enhanced by applying chemometrics-based approaches and machine learning methods of XANES data analysis.

36 MATERIALS SCIENCE↗

Identification of engine oil-derived ash nanoparticles and ash formation process for a gasoline direct-injection engine

Engine oil-derived ash particles emitted from internal combustion (IC) engines are unwanted by-products, after oil is involved in in-cylinder combustion process. Since they typically come out together with particulate emissions, no detail has been reported about their early-stage particles other than agglomerated particles loaded on aftertreatment catalysts and filters. To better understand ash formation process during the combustion process, here differently formulated engine oils were dosed into a fuel system of a gasoline direct injection (GDI) engine that produces low soot mass emissions at normal operating conditions to increase the chances to find stand-alone ash particles separated from soot aggregates in the sub-20-nm size range. In addition to them, ash/soot aggregates in the larger size range were examined using scanning transmission electron microscopy (STEM)-X-ray electron dispersive spectroscopy (XEDS) to present elemental information at different sizes of particles from various oil formulations. The STEM-XEDS results showed that regardless of formulated oil type and particle size, Ca, P and C were always contained, while Zn was occasionally found on relatively large particles, suggesting that these elements get together from an early stage of particle formation. The S, Ca and P K-edge X-ray absorption near edge structure (XANES) analyses were performed for bulk soot containing raw ash. The linear combination approach & cross-checking among XANES results proposed that Ca 5 (OH)(PO 4 ) 2 , Ca 3 (PO 4 ) 2 and Zn 3 (PO 4 ) 2 are potentially major chemical compounds in raw ash particles, when combined with the STEM-XEDS results. Despite many reports that CaSO 4 is a major ash chemical when ash found in DPF/GFP systems was examined, it was observed to be rarely present in raw ashes using the S K-edge XANES analysis, suggesting ash transformation.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Revealing the chemical environment of Cr, Fe, and Ni in high temperature-ultrafine precipitate strengthened steel subjected to low fluence neutron irradiation

High-temperature ultrafine-precipitate-strengthened (HT-UPS) steel has potential applications in advanced nuclear reactors as a structural material. However, little is currently known about its response to neutron irradiation. This research provides insight into the neutron irradiation-induced physicochemical changes of the major constituents in HT-UPS steels, including Fe, Cr, and Ni, using synchrotron X-ray absorption near edge structure (XANES) and diffraction. This study is the first known investigation using XANES to characterize HT-UPS steel to analyze the evolution of the atomic level chemistry. It was found that following irradiation, nucleation, ballistic dispersion, and/or coarsening of Cr 23 C 6 precipitates occurred at very low neutron irradiation fluences, from 0.003 displacements per atom (dpa) up to 0.3 dpa, at ~600°C, which were at least an order of magnitude lower than previous studies. Calculations of the angular momentum projections, partial density of states, and the XANES spectra confirmed the experimental findings of the Cr 23 C 6 precipitate evolution. In contrast, the local atomic structure around Fe and Ni atoms demonstrated irradiation resistance.

36 MATERIALS SCIENCE↗

Calcium-organic matter fouling in nanofiltration: Synchrotron-based X-ray fluorescence and absorption near-edge structure spectroscopy for speciation

Calcium (Ca)-enhanced organic matter (OM) fouling of nanofiltration (NF) membranes leads to reduced flux during desalination and requires frequent cleaning. Fouling mechanisms are not fully understood, which limits the development of targeted fouling control methods. This study employed synchrotron-based X-ray fluorescence (XRF) and X-ray absorption near-edge structure (XANES) spectroscopy to quantify the spatial distribution and mass of Ca deposition as well as changes in the Ca coordination environment characteristic of specific fouling mechanisms, respectively. Bench-scale filtration experiments were performed using feed solutions containing Ca and ten different types of organic matter (OM), as well as the common scalants, calcium carbonate (CaCO 3 ) and calcium sulfate (CaSO 4 ). Osmotic backwash (OB) was performed at regular intervals for fouling control. Ca-OM aggregation resulted in greater flux decline and lower flux recovery during OB than Ca conditioning of membranes followed by filtration of feed solution with OM. Linear combination fitting (LCF) of XANES absorption spectra from fouled membranes indicated that Ca-OM aggregation preferentially occurred for OM types that exhibited both high carboxylic group and negative charge density. Consequently, these OM types exhibited greater deposition of Ca and TOC on the membrane surface when compared to other OM types. For the coexistence of scalants and OM, Ca speciation within the fouling layer was characteristic of both Ca bound to the membrane (i.e. potential bridging, charge screening) as well as Ca-OM aggregation and deposition mechanisms, while a range of crystal polymorphs were observed to occur simultaneously. XRF and XANES represent powerful tools for the elucidation of NF fouling mechanisms by quantification of Ca deposition as well as Ca speciation. Fouling control methods should target OM types with high carboxyl group density and negative charge to neutralize or eliminate interactions with Ca.

42 ENGINEERING↗

Robust Machine Learning Inference from X-ray Absorption Near Edge Spectra through Featurization

X-ray absorption spectroscopy (XAS) is a commonly employed technique for characterizing functional materials. In particular, X-ray absorption near edge spectra (XANES) encode local coordination and electronic information, and machine learning approaches to extract this information are of significant interest. To date, most ML approaches for XANES have primarily focused on using the raw spectral intensities as input, overlooking the potential benefits of incorporating spectral transformations and dimensionality reduction techniques into ML predictions. Here, in this work, we focused on systematically comparing the impact of different featurization methods on the performance of ML models for XAS analysis. We evaluated the classification and regression capabilities of these models on computed data sets and validated their performance on previously unseen experimental data sets. Our analysis revealed an intriguing discovery: the cumulative distribution function feature achieves both high prediction accuracy and exceptional transferability. This remarkably robust performance can be attributed to its tolerance to horizontal shifts in the spectra, which is crucial when validating models using experimental data. While this work exclusively focuses on XANES analysis, we anticipate that the methodology presented here will hold promise as a versatile asset to the broader spectroscopy community.

36 MATERIALS SCIENCE↗

Smaller Is Better: The Case for Lower-Order Iodoplumbate Species Dominating MAPbI 3 /Dimethylformamide Solutions

Here, using complementary experimental measurements and computational predictions of spectroscopic measurements (EXAFS, XANES, and UV–vis), we have determined the identity of the most stable iodoplumbate species in dilute lead halide perovskite precursor solutions. We have determined which species are most likely to be thermodynamically stable compared to others that are unstable or metastable. Condensed phase ab initio models were constructed, and the resulting ensembles were used to directly compare the computed signals to the experimental results of the EXAFS, XANES, and UV–vis spectra of PbI 2 :MAI in DMF. The results of this study suggest that only Pb 2+ , PbI + , and PbI 2 are dominant in the dilute lead perovskite precursor solutions as thermodynamically stable entities. Our interpretation of the relative stability of iodoplumbate species in solution, based on an analysis of EXAFS and XANES spectra, provides critically important new insight into the species most likely to be responsible for crystal nucleation and growth in these materials. This insight will have a significant consequence on the broad scientific community and will necessitate the reinterpretation of peaks in the UV–vis spectra of lead halide perovskite precursor solutions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Rapid Accumulation of Soil Inorganics on Plastics: Implications for Plastic Degradation and Contaminant Fate

As plastics degrade in the environment, chemical oxidation of the plastic surface enables inorganics to adsorb and form inorganic coatings, likely through a combination of adsorption of minerals and in situ mineral formation. The presence of inorganic coatings on aged plastics has negative implications for plastics fate, hindering our ability to recycle weathered plastics and increasing the potential for plastics to adsorb contaminants. Here, inorganic coatings formed on terrestrially weathered polyethylene were characterized using synchrotron spectroscopy and microscopy techniques across spatial scales including optical microscopy, nano-X-ray-fluorescence mapping (nano-XRF), nano-X-ray absorption near edge structure (nano-XANES), and high-energy resolution fluorescence detected-XANES (HERFD-XANES). Results indicate a heterogeneous elemental distribution and speciation which includes inorganics common to soil terrestrial environments including iron oxides and oxyhydroxides, aluminosilicates, and carbonates.

36 MATERIALS SCIENCE↗