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Results for “characterization and analytical techniques”

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 109 records · Page 6

Machine learning for automated experimentation in scanning transmission electron microscopy

Abstract Machine learning (ML) has become critical for post-acquisition data analysis in (scanning) transmission electron microscopy, (S)TEM, imaging and spectroscopy. An emerging trend is the transition to real-time analysis and closed-loop microscope operation. The effective use of ML in electron microscopy now requires the development of strategies for microscopy-centric experiment workflow design and optimization. Here, we discuss the associated challenges with the transition to active ML, including sequential data analysis and out-of-distribution drift effects, the requirements for edge operation, local and cloud data storage, and theory in the loop operations. Specifically, we discuss the relative contributions of human scientists and ML agents in the ideation, orchestration, and execution of experimental workflows, as well as the need to develop universal hyper languages that can apply across multiple platforms. These considerations will collectively inform the operationalization of ML in next-generation experimentation.

36 MATERIALS SCIENCE↗

Integrated analysis of X-ray diffraction patterns and pair distribution functions for machine-learned phase identification

Abstract To bolster the accuracy of existing methods for automated phase identification from X-ray diffraction (XRD) patterns, we introduce a machine learning approach that uses a dual representation whereby XRD patterns are augmented with simulated pair distribution functions (PDFs). A convolutional neural network is trained directly on XRD patterns calculated using physics-informed data augmentation, which accounts for experimental artifacts such as lattice strain and crystallographic texture. A second network is trained on PDFs generated via Fourier transform of the augmented XRD patterns. At inference, these networks classify unknown samples by aggregating their predictions in a confidence-weighted sum. We show that such an integrated approach to phase identification provides enhanced accuracy by leveraging the benefits of each model’s input representation. Whereas networks trained on XRD patterns provide a reciprocal space representation and can effectively distinguish large diffraction peaks in multi-phase samples, networks trained on PDFs provide a real space representation and perform better when peaks with low intensity become important. These findings underscore the importance of using diverse input representations for machine learning models in materials science and point to new avenues for automating multi-modal characterization.

36 MATERIALS SCIENCE↗

Highly sensitive 2D X-ray absorption spectroscopy via physics informed machine learning

Abstract Improving the spatial and spectral resolution of 2D X-ray near-edge absorption structure (XANES) has been a decade-long pursuit to probe local chemical reactions at the nanoscale. However, the poor signal-to-noise ratio in the measured images poses significant challenges in quantitative analysis, especially when the element of interest is at a low concentration. In this work, we developed a post-imaging processing method using deep neural network to reliably improve the signal-to-noise ratio in the XANES images. The proposed neural network model could be trained to adapt to new datasets by incorporating the physical features inherent in the latent space of the XANES images and self-supervised to detect new features in the images and achieve self-consistency. Two examples are presented in this work to illustrate the model’s robustness in determining the valence states of Ni and Co in the LiNi x Mn y Co 1-x-y O 2 systems with high confidence.

36 MATERIALS SCIENCE↗

Revealing the growth kinetics of atmospheric corrosion pitting in aluminum via in situ microtomography

Abstract Understanding the mechanistic relationship between the environment, microstructure, and local kinetics of atmospheric corrosion damage remains a central challenge. To address this challenge, this study used laboratory-based X-ray tomography to directly observe attack in-operando over an extended period, enabling insights into the evolving growth kinetics and morphology of individual pits over months of exposure. Damage progression associated with nine pits in a 99.9% pure aluminum wire exposed to chloride salts in humid air was characterized. Most pits grew at a nominally linear rate up until pit death, which occurred within 12–24 h of nucleation. Exceptions to this were observed, with three pits exhibiting bimodal growth kinetics and growing for 40 or more hours. This was explained by secondary droplets that formed near the pits, increasing the cathode area. A corrosion-driven drying mechanism likely contributed to pit death in both cases. Pits first grew into the material followed by lateral expansion.

36 MATERIALS SCIENCE↗

Probing lithium mobility at a solid electrolyte surface

Abstract Solid-state electrolytes overcome many challenges of present-day lithium ion batteries, such as safety hazards and dendrite formation 1,2 . However, detailed understanding of the involved lithium dynamics is missing due to a lack of in operando measurements with chemical and interfacial specificity. Here we investigate a prototypical solid-state electrolyte using linear and nonlinear extreme-ultraviolet spectroscopies. Leveraging the surface sensitivity of extreme-ultraviolet-second-harmonic-generation spectroscopy, we obtained a direct spectral signature of surface lithium ions, showing a distinct blueshift relative to bulk absorption spectra. First-principles simulations attributed the shift to transitions from the lithium 1 s state to hybridized Li- s /Ti- d orbitals at the surface. Our calculations further suggest a reduction in lithium interfacial mobility due to suppressed low-frequency rattling modes, which is the fundamental origin of the large interfacial resistance in this material. Our findings pave the way for new optimization strategies to develop these electrochemical devices via interfacial engineering of lithium ions.

25 ENERGY STORAGE↗

Resolving length-scale-dependent transient disorder through an ultrafast phase transition

Abstract Material functionality can be strongly determined by structure extending only over nanoscale distances. The pair distribution function presents an opportunity for structural studies beyond idealized crystal models and to investigate structure over varying length scales. Applying this method with ultrafast time resolution has the potential to similarly disrupt the study of structural dynamics and phase transitions. Here we demonstrate such a measurement of CuIr 2 S 4 optically pumped from its low-temperature Ir-dimerized phase. Dimers are optically suppressed without spatial correlation, generating a structure whose level of disorder strongly depends on the length scale. The redevelopment of structural ordering over tens of picoseconds is directly tracked over both space and time as a transient state is approached. This measurement demonstrates the crucial role of local structure and disorder in non-equilibrium processes as well as the feasibility of accessing this information with state-of-the-art XFEL facilities.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Formation, chemical evolution and solidification of the dense liquid phase of calcium (bi)carbonate

Metal carbonates, which are ubiquitous in the near-surface mineral record, are a major product of biomineralizing organisms and serve as important targets for capturing anthropogenic CO 2 emissions. However, pathways of carbonate mineralization typically diverge from classical predictions due to the involvement of disordered precursors, such as the dense liquid phase (DLP), yet little is known about DLP formation or solidification processes. Using in situ methods we report that a highly hydrated bicarbonate DLP forms via liquid–liquid phase separation and transforms into hollow hydrated amorphous CaCO 3 particles. Acidic proteins and polymers extend DLP lifetimes while leaving the pathway and chemistry unchanged. Molecular simulations suggest that the DLP forms via direct condensation of solvated Ca 2+ •(HCO 3 – ) 2 complexes that react due to proximity effects in the confined DLP droplets. Furthermore, our findings provide insight into CaCO 3 nucleation that is mediated by liquid–liquid phase separation, advancing the ability to direct carbonate mineralization and elucidating an often-proposed complex pathway of biomineralization.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Electronic thermal transport measurement in low-dimensional materials with graphene non-local noise thermometry

In low-dimensional systems, the combination of reduced dimensionality, strong interactions and topology has led to a growing number of many-body quantum phenomena. Thermal transport, which is sensitive to all energy-carrying degrees of freedom, provides a discriminating probe of emergent excitations in quantum materials and devices. However, thermal transport measurements in low dimensions are dominated by the phonon contribution of the lattice, requiring an experimental approach to isolate the electronic thermal conductance. In this work we measured non-local voltage fluctuations in a multi-terminal device to reveal the electronic heat transported across a mesoscopic bridge made of low-dimensional materials. Using two-dimensional graphene as a noise thermometer, we measured the quantitative electronic thermal conductance of graphene and carbon nanotubes up to 70 K, achieving a precision of ~1% of the thermal conductance quantum at 5 K. Employing linear and nonlinear thermal transport, we observed signatures of energy transport mediated by long-range interactions in one-dimensional electron systems, in agreement with a theoretical model.

36 MATERIALS SCIENCE↗

Relation between interfacial shear and friction force in 2D materials

Understanding the interfacial properties between an atomic layer and its substrate is of key interest at both the fundamental and technological levels. From Fermi level pinning to strain engineering and superlubricity, the interaction between a single atomic layer and its substrate governs electronic, mechanical and chemical properties. Here, we measure the hardly accessible interfacial transverse shear modulus of an atomic layer on a substrate. By performing measurements on bulk graphite, and on epitaxial graphene films on SiC with different stacking orders and twisting, as well as in the presence of intercalated hydrogen, we find that the interfacial transverse shear modulus is critically controlled by the stacking order and the atomic layer–substrate interaction. Importantly, we demonstrate that this modulus is a pivotal measurable property to control and predict sliding friction in supported two-dimensional materials. The experiments demonstrate a reciprocal relationship between friction force per unit contact area and interfacial shear modulus. As a result, the same relationship emerges from simulations with simple friction models, where the atomic layer– substrate interaction controls the shear stiffness and therefore the resulting friction dissipation.

36 MATERIALS SCIENCE↗

Electronic response of a Mott insulator at a current-induced insulator-to-metal transition

The Mott insulator Ca 2 RuO 4 exhibits an insulator-to-metal transition induced by d.c. current. Despite the thorough examination of the structural changes associated with this transition, a comprehensive knowledge of the response of electronic degrees of freedom is still lacking. Here we demonstrate current-induced modifications of the electronic states of Ca 2 RuO 4 . Angle-resolved photoemission spectroscopy in conjunction with four-probe electrical transport (transport-ARPES) measurements reveal a clear reduction of the Mott gap and a modification in the dispersion of the Ru bands. Based on a free-energy analysis, we show that the current-induced phase is electronically distinct from the high-temperature zero-current metallic phase. Our results highlight strong interplay of lattice- and orbital-dependent electronic responses in the current-driven insulator-to-metal transition.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Observations of grain-boundary phase transformations in an elemental metal

The theory of grain boundary (the interface between crystallites, GB) structure has a long history 1 and the concept of GBs undergoing phase transformations was proposed 50 years ago 2,3 . The underlying assumption was that multiple stable and metastable states exist for different GB orientations 4,5,6 . The terminology ‘complexion’ was recently proposed to distinguish between interfacial states that differ in any equilibrium thermodynamic property 7 . Different types of complexion and transitions between complexions have been characterized, mostly in binary or multicomponent systems 8,9,10,11,12,13,14,15,16,17,18,19 . Simulations have provided insight into the phase behaviour of interfaces and shown that GB transitions can occur in many material systems 20,21,22,23,24 . However, the direct experimental observation and transformation kinetics of GBs in an elemental metal have remained elusive. In this work we demonstrate atomic-scale GB phase coexistence and transformations at symmetric and asymmetric $[11\bar{1}]$ tilt GBs in elemental copper. Atomic-resolution imaging reveals the coexistence of two different structures at Σ19b GBs (where Σ19 is the density of coincident sites and b is a GB variant), in agreement with evolutionary GB structure search and clustering analysis 21,25,26 . We also use finite-temperature molecular dynamics simulations to explore the coexistence and transformation kinetics of these GB phases. Our results demonstrate how GB phases can be kinetically trapped, enabling atomic-scale room-temperature observations. Our work paves the way for atomic-scale in situ studies of metallic GB phase transformations, which were previously detected only indirectly 9,15,27,28,29 , through their influence on abnormal grain growth, non-Arrhenius-type diffusion or liquid metal embrittlement.

36 MATERIALS SCIENCE↗

The structure of liquid carbon elucidated by in situ X-ray diffraction

Carbon has a central role in biology and organic chemistry, and its solid allotropes provide the basis of much of our modern technology. However, the liquid form of carbon remains nearly uncharted, and the structure of liquid carbon and most of its physical properties are essentially unknown. But liquid carbon is relevant for modelling planetary interiors and the atmospheres of white dwarfs, as an intermediate state for the synthesis of advanced carbon materials, inertial confinement fusion implosions, hypervelocity impact events on carbon materials and our general understanding of structured fluids at extreme conditions. Here we present a precise structure measurement of liquid carbon at pressures of around 1 million atmospheres obtained by in situ X-ray diffraction at an X-ray free-electron laser. Our results show a complex fluid with transient bonding and approximately four nearest neighbours on average, in agreement with quantum molecular dynamics simulations. The obtained data substantiate the understanding of the liquid state of one of the most abundant elements in the universe and can test models of the melting line. The demonstrated experimental abilities open the path to performing similar studies of the structure of liquids composed of light elements at extreme conditions.

74 ATOMIC AND MOLECULAR PHYSICS↗

Database of ab initio L-edge X-ray absorption near edge structure

Abstract The L-edge X-ray Absorption Near Edge Structure (XANES) is widely used in the characterization of transition metal compounds. Here, we report the development of a database of computed L-edge XANES using the multiple scattering theory-based FEFF9 code. The initial release of the database contains more than 140,000 L-edge spectra for more than 22,000 structures generated using a high-throughput computational workflow. The data is disseminated through the Materials Project and addresses a critical need for L-edge XANES spectra among the research community.

42 ENGINEERING↗

A preliminary investigation into the use of molecular oxide and hydride secondary ion relationships for improvement of the 236U/238U determination on a NanoSIMS 50L

Abstract A NanoSIMS 50L is used to investigate uranium molecular ( 235 U 16 O, 236 U 16 O, 238 U 16 O, 235 U 1 H, 238 U 1 H, 236 U 16 O 1 H, and 238 U 16 O 1 H) and elemental ( 235 U, 236 U, and 238 U) secondary ion production during sputtering of synthetic UO 2 and the NIST-610 standard to determine if: (1) the 236 U 16 O/ 238 U 16 O molecular oxide ratio performs better than the 236 U/ 238 U elemental ratio, and (2) there is co-variance between the molecular hydrides and oxides. Despite an order of magnitude greater abundance of 236 U 16 O secondary ions (compared to 236 U), the 236 U 16 O/ 238 U 16 O ratios are less accurate than the 236 U/ 238 U ratios. Further work is needed before the higher count rate of the 236 U 16 O secondary ion can be used to obtain a better 236 U/ 238 U ratio. The second objective was undertaken because correction for the interference of 235 U 1 H on the 236 U secondary ion species typically utilizes the 238 U 1 H/ 238 U ratio. This becomes problematic in samples containing 239 Pu, so our aim was to understand if the hydride formation rate can be constrained independently of having to measure the 238 U 1 H. We document correlations between the hydride ( 238 U 1 H and 238 U 16 O 1 H) and oxide ( 236 U 16 O) secondary ions, suggesting that pursuing an alternative correction regime is worthwhile.

38 RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCLEA↗