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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 883 records · Page 49

Self-Adjusting Metal–Organic Framework for Efficient Capture of Trace Xenon and Krypton

The capture of the xenon and krypton from nuclear reprocessing off-gas is essential to the treatment of radioactive waste. Although various porous materials have been employed to capture Xe and Kr, the development of high-performance adsorbents capable of trapping Xe/Kr at very low partial pressure as in the nuclear reprocessing off-gas conditions remains challenging. Herein, we report a self-adjusting metal-organic framework based on multiple weak binding interactions to capture trace Xe and Kr from the nuclear reprocessing off-gas. The self-adjusting behavior of ATC-Cu and its mechanism have been visualized by the in-situ single-crystal X-ray diffraction studies and theoretical calculations. The self-adjusting behavior endows ATC-Cu unprecedented uptake capacities of 2.65 and 0.52 mmol g -1 for Xe and Kr respectively at 0.1 bar and 298 K, as well as the record Xe capture capability from the nuclear reprocessing off-gas. Further, our work not only provides a benchmark Xe adsorbent but proposes a new route to construct smart materials for efficient separations.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Use of shape-preserving interpolation methods in surface modeling

In many large-scale scientific computations, it is necessary to use surface models based on information provided at only a finite number of points (rather than determined everywhere via an analytic formula). As an example, an equation of state (EOS) table may provide values of pressure as a function of temperature and density for a particular material. These values, while known quite accurately, are typically known only on a rectangular (but generally quite nonuniform) mesh in (T,d)-space. Thus interpolation methods are necessary to completely determine the EOS surface. The most primitive EOS interpolation scheme is bilinear interpolation. This has the advantages of depending only on local information, so that changes in data remote from a mesh element have no effect on the surface over the element, and of preserving shape information, such as monotonicity. Most scientific calculations, however, require greater smoothness. Standard higher-order interpolation schemes, such as Coons patches or bicubic splines, while providing the requisite smoothness, tend to produce surfaces that are not physically reasonable. This means that the interpolant may have bumps or wiggles that are not supported by the data. The mathematical quantification of ideas such as physically reasonable and visually pleasing is examined.

Ftitsch, F. N.↗

Determine the coordination of Al and Si of Fe-rich fly ash: The challenge in NMR and how we probe its heterogeneity using X-ray spectromicroscopy

Scanning transmission X-ray microscopy (STXM) coupled with ptychographic imaging at Al and Si K-edge is a new probe to the microscale chemistry of heterogenous materials. Here, the combined techniques are applied to study local coordination environment of Fe-rich fly ash (FA). Ptychographic imaging at Al K- and Si K-edge highlights the fine Al- and Si-rich morphological features, respectively, at 6 nm pixel resolution. STXM visualizes the inter- and intra-particle variations in the silicate polymerization degree and two types of Al coordination environment in FA. The Si K-edge of SiO4 connected with four-fold coordinated Al is higher than SiO4 sharing oxygen with six-fold coordinated Al. The result is consistent with bulk nuclear magnetic resonance spectroscopy measurement of the Fe-rich sample which, however, is sensitive to paramagnetic Fe and time-consuming. Here, we demonstrate that the combined method has great potential in the studies of chemically heterogenous aluminosilicates.

01 COAL, LIGNITE, AND PEAT↗

Frequent Fulcrum Functions: The Basics of SCALE’s Graphical User Interface [Slides]

This tutorial introduces the Fulcrum graphical user interface and the basic functions that enhance the common activities of creating, editing, navigating, executing, and visualizing SCALE input files. This tutorial will help you become familiar with the Fulcrum input file text editor and the integrated input development environment features of autocompletion, automatic checking, cursor context, and input navigation. In addition, the Fulcrum and SCALE runtime environment will be reviewed to improve the understanding of job execution workflow. This tutorial does not cover data and geometry plotting. Please see the Advanced User Interface Capabilities tutorial for details regarding plotting data and geometry. No prior experience with SCALE is required. You can follow along using SCALE 6.2 or 6.3-beta.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Electrochemical Imaging of Precisely‐Defined Redox and Reactive Interfaces

Abstract Understanding the diverse electrochemical reactions occurring at electrode‐electrolyte interfaces (EEIs) is a critical challenge to developing more efficient energy conversion and storage technologies. Establishing a predictive molecular‐level understanding of solid electrolyte interphases (SEIs) is challenging due to the presence of multiple intertwined chemical and electrochemical processes occurring at battery electrodes. Similarly, chemical conversions in reactive electrochemical systems are often influenced by the heterogeneous distribution of active sites, surface defects, and catalyst particle sizes. In this mini review, we highlight an emerging field of interfacial science that isolates the impact of specific chemical species by preparing precisely‐defined EEIs and visualizing the reactivity of their individual components using single‐entity characterization techniques. We highlight the broad applicability and versatility of these methods, along with current state‐of‐the‐art instrumentation and future opportunities for these approaches to address key scientific challenges related to batteries, chemical separations, and fuel cells. We establish that controlled preparation of well‐defined electrodes combined with single entity characterization will be crucial to filling key knowledge gaps and advancing the theories used to describe and predict chemical and physical processes occurring at EEIs and accelerating new materials discovery for energy applications.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Learning surface molecular structures via machine vision

Recent advances in high resolution scanning transmission electron and scanning probe microscopies have allowed researchers to perform measurements of materials structural parameters and functional properties in real space with a picometre precision. In many technologically relevant atomic and/or molecular systems, however, the information of interest is distributed spatially in a non-uniform manner and may have a complex multi-dimensional nature. One of the critical issues, therefore, lies in being able to accurately identify (‘read out’) all the individual building blocks in different atomic/molecular architectures, as well as more complex patterns that these blocks may form, on a scale of hundreds and thousands of individual atomic/molecular units. Here we employ machine vision to read and recognize complex molecular assemblies on surfaces. Specifically, we combine Markov random field model and convolutional neural networks to classify structural and rotational states of all individual building blocks in molecular assembly on the metallic surface visualized in high-resolution scanning tunneling microscopy measurements. We show how the obtained full decoding of the system allows us to directly construct a pair density function—a centerpiece in analysis of disorder-property relationship paradigm—as well as to analyze spatial correlations between multiple order parameters at the nanoscale, and elucidate reaction pathway involving molecular conformation changes. Here, the method represents a significant shift in our way of analyzing atomic and/or molecular resolved microscopic images and can be applied to variety of other microscopic measurements of structural, electronic, and magnetic orders in different condensed matter systems.

36 MATERIALS SCIENCE↗

Model-Based Energy and Cost Analysis of Direct Air Capture Using ePTFE-Based Laminate-Structured Gas–Solid Contactors

Carbon dioxide removal (CDR) technologies will play a significant role in limiting global warming if implemented on a large scale. Direct air capture (DAC) is a scalable approach for removing atmospheric carbon, yet the true scope of its scalability remains unclear due to the early stage of technology development and high first plant costs. This study provides groundwork for understanding the technoeconomic trade-offs in developing DAC systems using laminate-structured gas–solid contactors, encompassing the analysis of both contactor and process design spaces. The robust mass transfer and process models outlined in this study provide tools for evaluating DAC processes and designing DAC plants based on cost and energy analysis. First, the key contactor geometrical parameters are identified to understand the CO 2 productivity–energy demand trade-offs, where geometries yielding higher mass transfer rates can achieve higher CO 2 productivities at the expense of energy consumption by fans and steam use. Next, a detailed process parametric study is conducted for DAC systems coupled with steam-assisted temperature-vacuum swing adsorption (S-TVSA) to visualize the trade-offs in the multidimensional design space. The main cost driver dramatically changes over different process conditions, but the operating cost prevailed on the Pareto front, with potential to operate as low as 150 $/tonne-CO 2 (within the cost range of 148–504 $/tonne-CO 2 in this study where the DAC system is coupled with industrial facilities for steam production).

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Direct Observation of Transient Structural Dynamics of Atomically Thin Halide Perovskite Nanowires

Halide perovskite is a unique dynamical system, whose structural and chemical processes happening across different timescales have significant impact on its physical properties and device-level performance. However, due to its intrinsic instability, real-time investigation of the structure dynamics of halide perovskite is challenging, which hinders the systematic understanding of the chemical processes in the synthesis, phase transition, and degradation of halide perovskite. Here, we show that atomically thin carbon materials can stabilize ultrathin halide perovskite nanostructures against otherwise detrimental conditions. Moreover, the protective carbon shells enable atomic-level visualization of the vibrational, rotational, and translational movement of halide perovskite unit cells. Albeit atomically thin, protected halide perovskite nanostructures can maintain their structural integrity up to an electron dose rate of 10,000 e – /Å 2 ·s while exhibiting unusual dynamical behaviors pertaining to the lattice anharmonicity and nanoscale confinement. Here, our work demonstrates an effective method to protect beam-sensitive materials during in situ observation, unlocking new solutions to study new modes of structure dynamics of nanomaterials.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Modified Energy Span Analysis of Catalytic Parallel Pathways and Selectivity

Mechanistic modeling provides vital insights into catalytic reactions. To analyze complex reaction networks with parallel pathways, we leverage the graph theory approach of the Energy Span Model (ESM) to develop a modified energy span analysis (MESA). A new method of cycle plots is proposed to perform reaction pathways analysis visually. We demonstrate this method on two published models: one describing carbon monoxide oxidation and the other simulating ethylene conversion to propanal via hydroformylation or ethane via hydrogenation. Fundamental insights explain kinetic observables, such as a reactant’s negative reaction order. General principles are revealed, such as rate-determining surface species being outside the primary reaction flux cycle and pathway selectivity being a purely kinetic property when reaction conditions are not near equilibrium. Lastly, we demonstrate MESA’s consistency with published microkinetic modeling results, highlighting this technique’s extension of the ESM to heterogeneous catalysts using collision theory to describe adsorption steps and concentration effects.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Molecular Weight Dependence of Methylcellulose Fibrillar Networks

Gelation of aqueous methylcellulose (MC) solutions upon heating has been shown to result from the formation of a network of semiflexible fibrils, with diameters of 15 ± 2 nm. Here, we investigate the impact of MC molecular weight on the elasticity and structure of aqueous gels at concentrations between 0.1 and 3 wt %. Small-amplitude oscillatory shear measurements conducted at a fixed concentration reveal that the gel modulus increases monotonically by a factor of 5 for weight-average molecular weights (M w ) between 22 and 550 kg/mol. Small-angle X-ray scattering data, fit to a semiflexible cylinder model, demonstrate that the fibril radius, Kuhn length, and volume fraction are approximately constant throughout this molecular weight range. Small-angle light scattering shows that the fibrillar-rich and fibrillar-depleted domains within the gel are associated with an essentially invariant heterogeneity correlation length. Direct visualization by cryo-TEM reveals that lower molecular weight MC forms fibrils of lower average length. The distribution of fibril lengths measured by cryo-TEM and the distribution of the polymer chain contour lengths are similar, especially for shorter chains, and these features are correlated to network connectivity. We propose that the underlying fibril structure consists of bundles of polymer chains with a preferred orientation coincident with the fibril axis, while the fibril diameter is controlled by a circumferential helical pitch associated with the single chain Kuhn length and interactions between chains.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Polymer Nanogels as Reservoirs To Inhibit Hydrophobic Drug Crystallization

Herein the effects of cross-link density and composition on the loading and in vitro dissolution of the drug phenytoin as amorphous solid dispersions in emulsion polymerized poly(N-isopropylacrylamide) (PNIPAm) and poly(N-isopropylacrylamide-co-N,N-dimethylacrylamide) nanogels were investigated near the lower critical solution temperature (LCST). Nanogel size and particle density in phosphate buffered saline were quantified by dynamic light scattering (DLS) and viscometry experiments, while drug–nanogel interactions were revealed by cross peaks in aqueous-state nuclear Overhauser effect spectroscopy measurements. Spray-dried dispersions (SDDs) of drug-loaded PNIPAm nanogel particles (R ≈ 43 nm) were directly visualized by cryogenic transmission electron microscopy and further quantified by small-angle X-ray scattering during in vitro dissolution. SDD dissolution profiles were highly dependent on the nanogel cross-link density and directly correlated with the state of dispersion of the drug-loaded nanogel particles. A balance between net particle hydrophobicity and hydrophilicity along with the distance in temperature from the LCST are shown to dictate the in vitro dissolution of the amorphous solid dispersions. Solubility enhancement mechanisms disclosed in this study provide essential guidance for the design of effective nanogels for oral drug delivery applications.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

X-ray Pump–Probe Investigation of Charge and Dissociation Dynamics in Methyl Iodine Molecule

Molecular dynamics is of fundamental interest in natural science research. The capability of investigating molecular dynamics is one of the various motivations for ultrafast optics. Here, we present our investigation of photoionization and nuclear dynamics in methyl iodine (CH 3 I) molecule with an X-ray pump X-ray probe scheme. The pump–probe experiment was realized with a two-mirror X-ray split and delay apparatus. Time-of-flight mass spectra at various pump–probe delay times were recorded to obtain the time profile for the creation of high charge states via sequential ionization and for molecular dissociation. We observed high charge states of atomic iodine up to 29+, and visualized the evolution of creating these high atomic ion charge states, including their population suppression and enhancement as the arrival time of the second X-ray pulse was varied. We also show the evolution of the kinetics of the high charge states upon the timing of their creation during the ionization-dissociation coupled dynamics. We demonstrate the implementation of X-ray pump–probe methodology for investigating X-ray induced molecular dynamics with femtosecond temporal resolution. The results indicate the footprints of ionization that lead to high charge states, probing the long-range potential curves of the high charge states.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

The Pursuit of K: Reflections on the Current State-of-the-Art in Stress Intensity Factor Solutions for Practical Aerospace Applications

The elastic stress intensity factor (SIF, commonly denoted as K) is the foundation of practical fracture mechanics (FM) analysis for aircraft structures. This single parameter describes the first-order effects of stress magnitude and distribution as well as the geometry of both structure/component and crack. Hence, the calculation of K is often the most significant step in fatigue analysis based on FM. This presentation will provide several reflections on the current state-of-the-art in SIF solution methods used for practical aerospace applications, including a brief historical perspective, descriptions of some recent and ongoing advances, and comments on some remaining challenges. Newman and Raju made significant early contributions to practical structural analysis by developing closed-form SIF equations for surface and corner cracks in simplified geometries, often based on empirical fits of finite element (FE) solutions. Those solutions (and others like them) were sometimes revised as new analyses were conducted or limitations discovered. The foundational solutions have exhibited striking longevity, despite the relatively "coarse" FE models employed many decades ago. However, in recent years, the accumulation of different generations of solutions for the same nominal geometry has led to some confusion (which solution is correct?), and steady increases in computational capabilities have facilitated the discovery of inaccuracies in some (not all!) of the legacy solutions. Some examples of problems and solutions are presented and discussed, including the challenge of maintaining consistency with legacy design applications. As computational power has increased, the prospect of calculating large numbers of SIF solutions for specific complex geometries with advanced numerical methods has grown more attractive. Fawaz and Andersson, for example, have been generating literally millions of new SIF solutions for different combinations of multiple cracks under simplified loading schemes using p-version FE methods. These data are invaluable, but questions remain about their practical use, because the tabular databases of key results needed to support practical life analysis can occupy gigabytes of storage for only a few classes of geometries. The prospect of using such advanced numerical methods to calculate in real time only those K solutions actually needed to support a specific crack growth analysis is also tempting, but the stark reality is that the computational cost is still so high that the approach is not practical except for specific, critical application problems. Some thoughts are offered about alternative paradigms. Compounding approaches are some of the earliest building blocks of SIF development for more complex geometries. These approaches are especially attractive because of their very low computational cost and their conceptual robustness; they are, in some ways, an intriguing contrast and complement to the brute-force numerical methods. In recent years, researchers at NRC-Canada have published remarkable results showing how compounding approaches can be used to generate accurate solutions for very difficult problems. Examples are provided of some successes--and some limitations--using this approach. These closed-form, tabulated numerical, and compounding approaches have typically been used for simple remote loading with simple load paths to the crack. However, many significant cracks occur in complex stress gradient fields. This is a job for weight function (WF) methods, where the arbitrary stress distribution on the crack plane in the corresponding uncracked body (typically determined using FE methods) is used to determine K. Several significant recent advances in WF methods and solutions are highlighted here. Fueled by advanced 3D numerical methods, many new solutions have been generated for classic geometries such as surface and corner cracks with wide ranges of geometrical validity. A new WF formulation has also be developed for part-through cracks considering the arbitrary stress gradients in all directions in the crack plane (so-called bivariant solutions). Basic WF methods have recently been combined with analytical expressions for crack plane stresses to develop a large family of accurate SIF solutions for corner, surface, and through cracks at internal or external notches with very wide ranges of shapes, sizes, acuities, and offsets. Finally, WF solutions are much faster than FE or boundary element solutions, but can still be much slower than simple closed-form solutions, especially for bivariant solutions that can require 2D numerical integration. Novel pre-integration and dynamic tabular methods have been developed that substantially increase the speed of these advanced WF solutions. The practical utility of advanced SIF methods, including both WF and direct numerical methods, is greatly enhanced if the FM life analysis can be directly and efficiently linked with digital models of the actual structure or component (e.g., FE models for stress analysis). Two recent advances of this type will be described. One approach directly interfaces the FM life analysis with the FE model of the uncracked component (including stress results). Through a powerful graphical user interface, simplified FM life models can be constructed (and visualized) directly on the component model, with the computer collecting the geometry and stress gradient information needed for the life calculation. An even more powerful paradigm uses expert logic to automatically build an optimum simple fracture model at any and every desired location in the component model, perform the life calculation, and even generate fatigue crack growth life contour maps, all with minimal user intervention. This paradigm has also been extended to the automatic calculation of fracture risk, considering uncertainty or variability in key input parameters such as initial crack size or location. Another new integrated approach links the engineering life analysis, the component model, and a 3D numerical fracture analysis built with the same component model to generate a table of SIF values at a specific location that can then be employed efficiently to perform the life calculation. Some attention must be given to verification and validation (V&V) issues and challenges: how good are these SIF solutions, how good is good enough, and does anyone believe the life answer? It is important to think critically about the different sources of error or uncertainty and to perform V&V in a hierarchal, building-block manner. Some accuracy issues for SIF solutions, for example, may actually involve independent material behavior issues, such as constraint loss effects for crack fronts near component surfaces, and can be a source of confusion. Recommendations are proposed for improved V&V approaches. This presentation will briefly but critically survey the range of issues and advances mentioned above, with a particular view towards assembling an integrated approach that combines different methods to create practical tools for real-world design and analysis problems. Examples will be selectively drawn from the recent literature, from recent enhancements in the NASGRO and DARWIN computer codes, and from previously unpublished research

CraigMcClung, R.↗

Disentangling Rotational Dynamics and Ordering Transitions in a System of Self-Organizing Protein Nanorods via Rotationally Invariant Latent Representations

The dynamics of complex ordering systems with active rotational degrees of freedom exemplified by protein self-assembly is explored using a machine learning workflow that combines deep learning-based semantic segmentation and rotationally invariant variational autoencoder-based analysis of orientation and shape evolution. The latter allows for disentanglement of the particle orientation from other degrees of freedom and compensates for lateral shifts. The disentangled representations in the latent space encode the rich spectrum of local transitions that can now be visualized and explored via continuous variables. The time dependence of ensemble averages allows insight into the time dynamics of the system and, in particular, illustrates the presence of the potential ordering transition. Finally, analysis of the latent variables along the single-particle trajectory allows tracing these parameters on a single-particle level. The proposed approach is expected to be universally applicable for the description of the imaging data in optical, scanning probe, and electron microscopy seeking to understand the dynamics of complex systems where rotations are a significant part of the process.

representation learning↗

Effects of Defects on Band Structure and Excitons in WS 2 Revealed by Nanoscale Photoemission Spectroscopy

Two-dimensional materials with engineered composition and structure will provide designer materials beyond conventional semiconductors. Yet, the potentials of defect engineering remain largely untapped, because it hinges on a precise understanding of electronic structure and excitonic properties, which are not yet predictable by theory alone. In this report, we use correlative, nanoscale photoemission spectroscopy to visualize how local introduction of defects modifies electronic and excitonic properties of two-dimensional materials at the nanoscale. As a model system, we study chemical vapor deposition grown monolayer WS 2 , a prototypical, direct gap, two-dimensional semiconductor. By cross-correlating nanoscale angle-resolved photoemission spectroscopy, core level spectroscopy, and photoluminescence, we unravel how local variations in defect density influence electronic structure, lateral band alignment, and excitonic phenomena in synthetic WS 2 monolayers.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Accelerating Multivariate Functional Approximation Computation with Domain Decomposition Techniques⋆

Modeling large datasets through Multivariate Functional Approximations (MFA) provide an elegant way to handle many visualization and scientific analysis workflows. The process necessitates scalable data partitioning methods to compute MFA representations efficiently without compromising the accuracy or continuity of the reconstructed solution. We propose a domain -decomposed method for computing the MFA with B -spline bases, which reduces the total work per task and uses a restricted Additive Schwarz (RAS) method to converge the control point data degrees -of -freedom along subdomain boundaries. We provide an in-depth analysis of the parallel approach with domain decomposition solvers, aiming to minimize local subdomain error residuals and recover high -order continuity at subdomain interfaces with appropriate choices of knot overlaps. The communication cost, determined by the overlap regions in the RAS implementation, is optimized to recover the numerical error profile of the single subdomain case. Our proposed method stands in contrast to previous methods, which typically only recover either C 0 or at best C 1 continuity for arbitrary B -spline degree expansions, or those that require post -processing to blend discontinuities in the reconstructed data. We demonstrate the effectiveness of our approach using analytical and real -world datasets in 1D, 2D, and 3D through both strong and weak scaling studies. The performance results indicate that the overall cost of computing the approximation is directly proportional to the underlying nearest -neighbor communication implementation, and is only weakly dependent on the overlap region size that determines the size of the messages. This finding underscores the efficiency and scalability of our proposed method, making it a promising solution for handling large datasets in scientific workflows.

additive Schwarz solvers↗

Visualizing Lithium Dendrite Formation within Solid-State Electrolytes

Solid-state electrolyte (SSE) is promising for application in allsolid-state lithium metal batteries because of its reliable safety and longevity. The failure of SSE to suppress dendrite formation of Li metal anodes has been conventionally explained by uneven Li deposition at Li/SSE interfaces and its subsequent dendritic growth. While Li deposition within SSE has been recently proposed as another key cause for SSE failure, little is known regarding the Li growth details inside the SSE itself. In this work, we performed in situ microscopic observation of Li deposition inside the SSE and obtained visualized evidence regarding the dynamic process of Li dendrite formation and growth. Here, Li is seen to directly nucleate and propagate within the SSE, leading to its structural cracking. Such behavior should be caused by the presence of P- and S-based crystalline defects in Li 3 PS 4 SSE, which is consistent with the cryo-transmission electron microscopy observations and theoretical calculations. This observation provides important insights into the growth mechanisms of Li dendrites within a working lithium battery.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Probing Ultrafast Electron (De)localization Dynamics in Mixed Valence Complexes Using Femtosecond X-ray Spectroscopy (Final Report)

The central goal of this proposal was to directly visualize and quantify how electronic correlations, vibronic couplings, and local solute-solvent interactions control intramolecular electron motion on the femtosecond time scale. The proposed research program focused on solvated Ruthenium (Ru) based mixed-valence complexes, a prototypical class of transition-metal complexes, which are of significant interest for their potential applications in photochemical energy conversion. Electron movements following photochemical excitation are closely coupled with atomic/vibrational and solvent motion. To disentangle these various components requires tools designed to directly probe electron correlations and vibronic coupling (coherently coupled motions of electronic and vibrational coordinates) on the timescale of electron motion in the solution phase.

36 MATERIALS SCIENCE↗