Search NASA⌕ Search

SEARCH · Search NASA

Results for “ATOMIC STRUCTURE”

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 127 records · Page 7

Atomic-scale e-beam sculptor

A system and method (referred to as the system) fabricates controllable atomic assemblies in two and three dimensions. The systems identify by a non-invasive imager, a local atomic structure, distribution of vacancies, and dopant atoms and modify, by a microscopic modifier, the local atomic structure, via electron beam irradiation. The systems store, by a knowledge base, cause-and-effect relationships based on a non-invasive imaging and electron scans. The systems detect, by detectors, changes in the local atomic structure induced by the electron irradiation; and fabricate, a modified atomic structure by a beam control software and feedback.

Kalinin, Sergei V.↗

NbTaV_BCC_SolidSolution_128atoms_VASP6

We performed density functional theory (DFT) calculations for body-centered-cubic (BCC) structures with 128 lattices sites of solid solution ternary alloys niobium-tantalum-vanadium (Nb-Ta-V). The first-principle code that has been used to run the calculations is the closed-source Vienna Ab-Initio Simulation Package (VASP). The calculations have been collected by sampling chemical compositions across the entire compositional range. The chemical compositions have been sampled by progressively changing the number of atoms per constituent by 8. For each chemical composition of binaries and ternaries, the first-principle calculations have been run for 100 randomized arrangements of the constituents on the BCC lattice sites. We collected data for a total of 10,500 randomized atomic structures over 105 chemical compositions. The calculations have been collected on NERSC-Perlmutter using the VASP 6.3.2. The VASP calculations for every atomic structure have been performed in 2 main steps: 1. Starting from an ideal body-centered-cubic (BCC) structure, geometry optimization with low precision has been executed to perform a preliminary optimization of the atomic structure. The output for this calculations is available in the files 0.CONTCAR, 0.OUTCAR, rlx1.out. 2. Using the atomic structure resulting from the preliminary geometry optimization, a second geometry optimization has been performed using normal precision. The output for this calculations is available in the files CONTCAR, OUTCAR, rlx2.out, vaspout.h5, and vasprun.xml. Every chemical composition sampled across the composition range in the dataset has its own directory. The convention used to name the directories for ternary alloys is AXBYCZ, where A, B, and C refer to the constituents, and X, Y, and Z are positive integers that represent the number of atoms for each constituent and their values still sum up to 128. Each atomic structure associated with a specific chemical composition has its own sub-directory within the directory of the corresponding chemical composition. The sub-directories for each atomic structure for each chemical composition are named 'case-*', where * is a positive integer that spans all the values from 1 through 100, extremes included. The files contained in each sub-directory 'case-*' for each atomic structure are as follows: 1. INCAR: input file that contains various parameters and settings for controlling the behavior of the electronic structure calculations 2. 0.POSCAR: input file that defines the atomic structure of a system 3. 0.CONTCAR: output file that provides the atomic positions and cell parameters after the first geometry optimization has been run with the precision variable set to PREC=Low in the INCAR file 4. 0.OUTCAR: output file that contains detailed information about the progress of a calculation after the first geometry optimization has been run with the precision variable set to PREC=Low in the INCAR file 5. rlx1.out: file with diagnostic information about the execution of the first geometry optimization with precision variable set to PREC=Low in the INCAR file 6. POSCAR: input file that defines the atomic structure of a system after the first geometry optimization has been run at low precision. This represents the input for the second geometry optimization run with the precision variable set to PREC=Normal in the INCAR file 7. CONTCAR: output file that provides the atomic positions and cell parameters after the second geometry optimization has been run with the precision variable set to PREC=Normal in the INCAR file 8. OUTCARL: output file that contains detailed information about the progress of a calculation after the second geometry optimization has been run with the precision variable set to PREC=Normal in the INCAR file 9. rlx2.out: file with diagnostic information about the execution of the second geometry optimization with precision variable set to PREC=Normal in the INCAR file 10. vaspout.h5: hierarchical HDF5 file containing the inputs and outputs of a VASP calculation. To analyze the data in this file we recommend using py4vasp. This file is only produced if the VASP version used is compiled with HDF5 support 11. vasprun.xml: contains similar information to OUTCAR, but in an xml format. This research is sponsored by the Artificial Intelligence Initiative as part of the Laboratory Directed Research and Development (LDRD) Program of Oak Ridge National Laboratory, managed by UT-Battelle, LLC, for the US Department of Energy under contract DE-AC05-00OR22725. This work used resources of the Oak Ridge Leadership Computing Facility, which is supported by the Office of Science of the U.S. Department of Energy under Contract No. DE-AC05-00OR22725, under Directorate Discretionary awards MAT025 (Materials Science) and LRN026 (Machine Learning), and INCITE award MAT201. This work also used resources of the National Energy Research Scientific Computing Center, which is supported by the Office of Science of the U.S. Department of Energy under Contract No. DE-AC02-05CH11231, under award ERCAP0025216.

36 MATERIALS SCIENCE↗

Nanometer Resolution Structure‐Emission Correlation of Individual Quantum Emitters via Enhanced Cathodoluminescence in Twisted Hexagonal Boron Nitride

Understanding the atomic structure of quantum emitters, often originating from point defects or impuritie, is essential for designing and optimizing materials for quantum technologies such as quantum computing, communication, and sensing. Despite the availability of atomic-resolution scanning transmission electron microscopy and nanoscale cathodoluminescence microscopy, experimentally determining the atomic structure of individual emitters is challenging due to the conflicting needs for thick samples to generate strong cathodoluminescence signals and thin samples for structural analysis. To overcome this challenge, significantly enhanced cathodoluminescence at twisted interfaces is leveraged to achieve sub-nanometer localization precision for the first time in mapping individual quantum emitters in carbon-implanted hexagonal boron nitride. This unprecedent spatial sensitivity, together with correlative electron energy loss spectroscopy quantitative scanning transmission electron microscopy imaging, and first principles density functional theory calculations, enables the identification of the atomic structure of the 440 nm blue emitter in hexagonal boron nitride as a substituted vertical carbon dimer. Building on the atomic structure insights, nanoscale spatially precise creation of blue emitters is demonstrated by electron beam irradiation of carbon-coated hexagonal boron nitride. This advancement in correlating atomic structures with optical properties lays the foundation for a deeper understanding and precise engineering of quantum emitters, significantly advancing the development of cutting-edge quantum information technologies.

2D material↗

Spectroscopy-guided discovery of three-dimensional structures of disordered materials with diffusion models

Spectroscopy techniques such as x-ray absorption near edge structure (XANES) provide valuable insights into the atomic structures of materials, yet the inverse prediction of precise structures from spectroscopic data remains a formidable challenge. In this study, we introduce a framework that combines generative artificial intelligence models with XANES spectroscopy to predict three-dimensional atomic structures of disordered systems, using amorphous carbon (a-C) as a model system. In this work, we introduce a new framework based on the diffusion model, a recent generative machine learning method, to predict 3D structures of disordered materials from a target property. For demonstration, we apply the model to identify the atomic structures of a-C as a representative material system from the target XANES spectra. We show that conditional generation guided by XANES spectra reproduces key features of the target structures. Furthermore, we show that our model can steer the generative process to tailor atomic arrangements for a specific XANES spectrum. Finally, our generative model exhibits a remarkable scale-agnostic property, thereby enabling generation of realistic, large-scale structures through learning from a small-scale dataset (i.e. with small unit cells). Our work represents a significant stride in bridging the gap between materials characterization and atomic structure determination; in addition, it can be leveraged for materials discovery in exploring various material properties as targeted.

36 MATERIALS SCIENCE↗

Atomic-Scale Structural Mapping of Active Sites in Monolayer PGM-Free Catalysts by Low-Voltage 4D-STEM

Two-dimensional (2D) materials have attracted a large amount of attention in both basic and applied fields, and scanning transmission electron microscopy (STEM) is often uniquely well-suited for characterizing the atomic-scale structure of these materials [1-4]. As a result, STEM is poised to significantly impact progress on platinum group metal (PGM)-free catalysts, which are currently under intense development to enable low-cost, commercially viable hydrogen fuel cells [5]. While recent advancements have resulted in fuel cell performance comparable to Pt catalysts by some measures [6], cell durability remains a significant challenge, limiting practical applications [7]. Catalytically active sites in PGM-free materials are proposed to be FeN4 complexes embedded in a graphene lattice (Fig. 1b) within layered or other larger materials, but this is still under debate largely due to the range of potential actives sites predicted by computational methods and lack of methods for directly validating these models [5]. Fundamental insights into the atomic structure and resulting degradation pathways of proposed active sites are therefore needed to fully understand and control cell performance and durability [6].2D materials typically make ideal samples for STEM, but those within PGM-free catalysts present additional challenges since these materials are often defect-rich, with a high density of edges, dopant atoms, etc., which significantly increase susceptibility to beam damage at standard operating voltages. This makes analysis of potential FeN4 active sites particularly challenging, since a large proportion of Fe exists at edge sites where beam-induced atomic displacements can prohibit high-resolution structural characterization [6]. Conventional dark-field imaging compounds this problem by producing less signal for a given dose and being less sensitive to light elements than dose-efficient phase contrast imaging techniques such as those enabled by four-dimensional (4D)-STEM [8-10] (Fig. 1a). Consequently, active site structural analysis is often left to methods such as low-resolution imaging combined with quantum chemical calculations [6], which hinders accurate determination of reaction and degradation mechanisms.Here, we demonstrate direct atomic-scale structural mapping of FeN4 sites by performing low-voltage 4D-STEM on a model PGM-free catalyst system with many exposed monolayer regions. To accomplish this, we pair a 30 keV aberration-corrected probe with a fast pixelated detector that has optimal performance at low beam voltages [11]. This enables us to simultaneously image light and heavy elements with high signal-to-noise by center-of-mass analysis (Fig. 1c) while minimizing beam-induced atomic displacements at sensitive sites. The monolayer nature of these materials additionally allows for experimental validation by direct comparison with multislice simulations [12] of model structures (Fig. 1d-e). This work demonstrates how low-voltage 4D-STEM will provide new insights into the atomic-scale structure and degradation mechanisms of active sites in PGM-free catalysts, facilitating the development of low-cost hydrogen fuel cells and other energy conversion technologies in the future [13].

Zachman, Michael↗

Formation of a Ti–Cu(111) single atom alloy: Structure and CO binding

A single atom Ti–Cu(111) surface alloy can be generated by depositing small amounts of Ti onto Cu(111) at slightly elevated surface temperatures (~500 to 600 K). Here, scanning tunneling microscopy shows that small Ti-rich islands covered by a Cu single layer form preferentially on ascending step edges of Cu(111) during Ti deposition below about 400 K but that a Ti–Cu(111) alloy replaces these small islands during deposition between 500 and 600 K, producing an alloy in the brims of the steps. Larger partially Cu-covered Ti-containing islands also form on the Cu(111) terraces at temperatures between 300 and 700 K. After surface exposure to CO at low temperatures, reflection absorption infrared spectroscopy (RAIRS) reveals distinct C–O stretch bands at 2102 and 2050 cm –1 attributed to CO adsorbed on Cu-covered Ti-containing domains vs sites in the Ti–Cu(111) surface alloy. Calculations using density functional theory (DFT) suggest that the lower frequency C–O stretch band originates specifically from CO adsorbed on isolated Ti atoms in the Ti–Cu(111) surface alloy and predicts a higher C–O stretch frequency for CO adsorbed on Cu above subsurface Ti ensembles. DFT further predicts that CO preferentially adsorbs in flat-lying configurations on contiguous Ti surface structures with more than one Ti atom and thus that CO adsorbed on such structures should not be observed with RAIRS. The ability to generate a single atom Ti–Cu(111) alloy will provide future opportunities to investigate the surface chemistry promoted by a representative early transition metal dopant on a Cu(111) host surface.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Phase Transformations among TiO2 Polymorphs

Polymorphs widely exist in nature and synthetic systems and are well known to determine material properties. Understanding phase transformation mechanisms among polymorphs enables the design of structures and tuning of phases to tailor material properties. However, current understanding is limited due to the lack of direct observations that track the processes and the structural evolution is not known at atomic scale. Here, integrating (semi) in situ transmission electron microscopy and density functional theory, we report atomic structural evolutions of phase transformation from anatase (A) to rutile (R), brookite (B), R-phase, and TiO. Besides the consistent paths with previous reports, we discover several unreported paths, including a [001] direction and (020) plane of anatase to [100]A and (011)R of rutile, respectively, ( , ) and , . Density functional theory analysis elucidates atomic structural evolution during the processes and over 16% of Ti-O bonds break and reform during the processes with energy barriers of ~0.7-1.0 eV per TiO2 formula unit. Under electron-beam irradiation, anatase particles transform into TiO2-R phase or TiO at high or room temperature, respectively. We also reveal the anisotropic nature of electron-beam effect, which is seldom discussed: dependence of crystallographic orientation with respect to electron-beam irradiation direction. Understanding the atomic structural evolution sheds light on interpreting and controlling TiO2 polymorphs and interface structures for various applications. The revealed electron-beam effects in our work provide guidance for in situ transmission electron microscopy studies.

Song, Miao↗

The atomic-level structure and stability of interfaces of Pt nanoparticles in alumina: An experimental and computational evaluation

The atomic-level structure of interfaces between Pt and a transition form of Al2O3 were studied using a combination of electron microscopy and first principles calculations. A model system of Pt nanoprecipitates in Al2O3 were formed in sapphire wafers via high-energy ion implantation of Pt followed by thermal annealing at 1000 °C in air. The Pt nanoparticles took the form of tetrahedra and truncated tetrahedra primarily bound by {111}Pt facets. The high prevalence of these facets motivated the development of density functional theory (DFT) based models of (111)Pt interfaces with six different chemical terminations of ( 2 ¯ 01 ) θ-alumina. The atomic-level structure of the Pt/Al2O3 interfaces was characterized with aberration-corrected scanning transmission electron microscopy (STEM) and the experimental images were compared to STEM image simulations of the DFT models. The model interface with Pt bonded to oxygen-terminated θ-Al2O3, with the Pt located on top of the O and with an underlying layer of octahedral Al, provided the best match to the experimental images. This interfacial termination is also the most stable for the thermal annealing conditions used based on thermodynamic calculations of the interfacial energy as a function of temperature and oxygen partial pressure. This experimentally verified model provides a basis for improving models of Pt/γ-alumina interfaces.

Clauser, A L↗

Predictability as a probe of manifest and latent physics: The case of atomic scale structural, chemical, and polarization behaviors in multiferroic Sm-doped BiFeO 3

The predictability of a certain effect or phenomenon is often equated with the knowledge of relevant physical laws, typically understood as a functional or numerically derived relationship between the observations and known states of the system. Correspondingly, observations inconsistent with prior knowledge can be used to derive new knowledge on the nature of the system or indicate the presence of yet unknown mechanisms. In this work, we explore the applicability of Gaussian processes (GP) to establish predictability and uncertainty of local behaviors from multimodal observations, providing an alternative to this classical paradigm. Using atomic resolution scanning transmission electron microscopy (STEM) of multiferroic Sm-doped BiFeO 3 across a broad composition range, we directly visualize the atomic structure and structural, physical, and chemical order parameter fields for the material. GP regression is used to establish the predictability of the local polarization field from different groups of parameters, including the adjacent polarization values and several combinations of physical and chemical descriptors, including lattice parameters, column intensities, etc. We observe that certain elements of microstructure, including charged and uncharged domain walls and interfaces with the substrate, are best predicted with specific combinations of descriptors, and this predictability and associated uncertainties are consistent across the composition series. The associated generative physical mechanisms are discussed. It is also found that certain parameter combinations tend to predict the orthorhombic phase in the cases where rhombohedral phase is observed, suggesting a potential role of clamping and confinement phenomena in phase equilibrium in Sm-BiFeO 3 system close to morphotropic phase boundary. We argue that predictability and uncertainty in observational data offer a new pathway to probe the physics of condensed matter systems from multimodal local observations.

74 ATOMIC AND MOLECULAR PHYSICS↗

Characterization of the atomic-level structure of γ-alumina and (111) Pt/γ-alumina interfaces

The atomic-level structure of platinum/γ-alumina interfaces is characterized in a model system of dense γ-alumina embedded with faceted Pt NPs produced by implantation of platinum ions into sapphire followed by thermal annealing in air at 800 °C. Aberration-corrected scanning transmission electron microscopy (STEM) was used to collect atomic-resolution images, which are compared to STEM image simulations of two experimentally-based bulk models of γ-alumina by Smrčok et al. and Zhou and Snyder. A density functional theory (DFT) based model of (111) interfaces with different chemical terminations (O, Al 1 , Al 2 ) of the γ-alumina developed by Oware Sarfo et al. is also compared to experimental STEM data from Pt/γ-alumina interfaces. Further, the Smrčok γ-alumina model provides a better fit than the Zhou structure to the bulk of the γ-alumina. The oxygen-terminated Oware Sarfo model best fits the experimental data and is a very good model close to the interface. However, the fit of the interface model to the experimental data is poorer beyond the third atomic layer in the γ-alumina. This is attributed to compromises required in the design of the model to limit the cell size and computational time for DFT calculations. Understanding the accuracy and limits of the structural models of γ-alumina and Pt/γ-alumina interfaces is important to further the understanding of the structure/property relationships in this system.

36 MATERIALS SCIENCE↗

Resolving Atomic-Scale Structure and Chemical Coordination in High-Entropy Alloy Electrocatalysts for Structure–Function Relationship Elucidation

The recent breakthrough in confining five or more atomic species in nanocatalysts, referred to as high-entropy alloy nanocatalysts (HEAs), has revealed the possibilities of multielemental interactions that can surpass the limitations of binary and ternary electrocatalysts. The wide range of potential surface configurations in HEAs, however, presents a significant challenge in resolving active structural motifs, preventing the establishment of structure-function relationships for rational catalyst design and optimization. Here, we present a methodology for creating sub-5 nm HEAs using an aqueous-based peptide-directed route. Using a combination of pair distribution function and X-ray absorption spectroscopy, HEA structure models are constructed from reverse Monte Carlo modeling of experimental data sets and showcase a clear peptide-induced influence on atomic-structure and chemical miscibility. Coordination analysis of our structure models facilitated the construction of structure-function correlations applied to electrochemical methanol oxidation reactions, revealing the complex interplay between multiple metals that leads to improved catalytic properties. Our results showcase a viable strategy for elucidating structure-function relationships in HEAs, prospectively providing a pathway for future materials design.

36 MATERIALS SCIENCE↗

Electron-impact excitation data for W 2+ in support of tungsten spectroscopy and re-deposition measurements for magnetically-confined plasmas

Abstract To better understand plasma wall interactions involving tungsten, accurate atomic structure and electron-impact driven collisional processes for near-neutral ion stages of tungsten are required. Complementing existing work on neutral and singly ionised tungsten, atomic structure and collisional calculations for W 2+ electron-impact excitation have been completed. These excitation calculations are an important component of S/XB coefficients for near-neutral charge states, which may be used to spectroscopically infer re-deposition of tungsten at the plasma-solid boundary of fusion relevant devices. With W 2+ in particular having emission lines that can be observed at ultraviolet (UV) wavelengths, while higher charge states of tungsten are unlikely to have lines possible to observe outside of the vacuum UV range. The atomic structure was generated using the General-purpose Relativistic Atomic Structure Package (GRASP 0 ), implementing the Multi-configuration Dirac Fock approach. This structure was the basis for a subsequent Dirac R -matrix electron-impact excitation calculation to provide Maxwellian averaged rate coefficients. A synthetic spectrum was generated from this data using a collisional-radiative model to predict the strongest W III spectral lines and these lines were compared to emission from the Compact Toroidal Hybrid (CTH) plasma device. Several of the strongest W III lines are observed in CTH and agree well with the modelled line wavelengths and intensities, a table of these lines is provided that could be observed in other devices.

McCann, M. (ORCID:0000000215321240)↗

Atomic-Scale Structure of Chemically Distinct Surface Oxygens in Redox Reactions

During redox reactions, oxide-supported catalytic systems undergo structural and chemical changes. Improving subsequent catalytic properties requires an understanding of the atomic-scale structure with chemical state specificity under reaction conditions. For the case of 1/2 monolayer vanadia on α-TiO 2 (110), we use X-ray standing wave (XSW) excited X-ray photoelectron spectroscopy to follow the redox induced atomic positional and chemical state changes of this interface. Furthermore, while the resulting XSW 3D composite atomic maps include the Ti and O substrate atoms and V surface atoms, our focus in this report is on the previously unseen surface oxygen species with comparison to density functional theory predictions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Elucidation of a Metastable p(2 × 1) O Atom Adlayer Structure on Cu(111)

Cu-based catalysts are ubiquitous in many industrial reactions, including methanol synthesis. Under partially oxidizing conditions, Cu catalysts can have dynamic surface structures that greatly influence their reactivities. Therefore, elucidating the surface structures that are present on Cu, and looking for metastable structures, aids in the long term goal of understanding and controlling their catalytic behavior. Thin-film copper oxides such as the “29” and “44” structures have been described at length in the literature, but precursors to these thin-film oxides can be challenging to study because they exist only under certain conditions. Using a combination of experimental and computational surface science techniques, we discovered, modeled, and quantified a previously unreported O atom adlayer structure on Cu(111) with a p(2 × 1) unit cell. Here, we used scanning tunneling microscopy to visualize the striped 2 × 1 structure and density functional theory (DFT) structure optimizations to identify the thermodynamically most favorable positions of Cu and O atoms in a p(2 × 1) unit cell. Using X-ray photoelectron spectroscopy and temperature-programmed desorption, we determined the stoichiometry of the structure to be 2:1 for surface Cu atoms to O adatoms, the same stoichiometry as that modeled by DFT. This work reports a new metastable structure formed on Cu(111) at the very initial stages of oxidation and is therefore worth considering in models of catalytically relevant redox processes at Cu surfaces.

36 MATERIALS SCIENCE↗

Insights into Native Single-Atom Electrocatalyst Site Structures

Single-atom electrocatalysts consisting of metal atoms embedded in a carbon matrix are promising next-generation catalysts for green hydrogen production and utilization, CO2 reduction, low-temperature CO oxidation, ammonia production, plastic decomposition, and electrochemical energy storage. The origins of activity and stability for the single-atom sites are still debatable, however, because of constrained insights into their local structure resulting from idealized models and experiments derived from a large number of individual sites. Insights into structural variations around single atomic sites are therefore critical for the continued development of these next-generation catalysts. While electron microscopy commonly provides atomic-scale information about these materials, the beam sensitivity of individual sites makes structural determination by conventional low-voltage (60 keV) techniques challenging. Here, we introduce ultralow-voltage electron ptychography, performed at 30 keV, that enables determination of the lattice structure around individual metal sites in a well-defined single-atom electrocatalyst system while essentially eliminating knock-on structural modifications. Pairing these atomic-scale, site-specific measurements with computational methods will broaden our understanding of the activity and stability of these materials, which will accelerate the development of the next generation of catalysts.

Zachman, Michael [ORNL] (ORCID:0000000319101357)↗

Matching Crystal Structures Atom-to-Atom

Finding an optimal match between two different crystal structures underpins many important materials science problems, including describing solid-solid phase transitions and developing models for interface and grain boundary structures. Here, we formulate the matching of crystals as an optimization problem where the goal is to find the alignment and the atom-to-atom map that minimize a given cost function such as the Euclidean distance between the atoms. We construct an algorithm that directly solves this problem for large finite portions of the crystals and retrieves the periodicity of the match subsequently. We demonstrate its capacity to describe transformation pathways between known polymorphs and to reproduce experimentally realized structures of semi-coherent interfaces. Additionally, from our findings, we define a rigorous metric for measuring distances between crystal structures that can be used to properly quantify their geometric (Euclidean) closeness.

36 MATERIALS SCIENCE↗

Time-resolved Brownian tomography of single nanocrystals in liquid during oxidative etching

Colloidal nanocrystals inherently undergo structural changes during chemical reactions. The robust structure-property relationships, originating from their nanoscale dimensions, underscore the significance of comprehending the dynamic structural behavior of nanocrystals in reactive chemical media. Moreover, the complexity and heterogeneity inherent in their atomic structures require tracking of structural transitions in individual nanocrystals at three-dimensional (3D) atomic resolution. In this study, we introduce the method of time-resolved Brownian tomography to investigate the temporal evolution of the 3D atomic structures of individual nanocrystals in solution. The methodology is applied to examine the atomic-level structural transformations of Pt nanocrystals during oxidative etching. The time-resolved 3D atomic maps reveal the structural evolution of dissolving Pt nanocrystals, transitioning from a crystalline to a disordered structure. Our study demonstrates the emergence of a phase at the nanometer length scale that has received less attention in bulk thermodynamics.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗