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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 667 records · Page 37

Understanding the Thermal Stability of Palladium–Platinum Core–Shell Nanocrystals by In Situ Transmission Electron Microscopy and Density Functional Theory

Core–shell nanocrystals offer many advantages for heterogeneous catalysis, including precise control over both the surface structure and composition, as well as reduction in loading for rare and costly metals. Although many catalytic processes are operated at elevated temperatures, the adverse impacts of heating on the shape and structure of core–shell nanocrystals are yet to be understood. In this work, we used ex situ heating experiments to demonstrate that Pd@Pt 4L core–shell nanoscale cubes and octahedra are promising for catalytic applications at temperatures up to 400 °C. We also used in situ transmission electron microscopy to monitor the thermal stability of the core–shell nanocrystals in real time. Our results demonstrate a facet dependence for the thermal stability in terms of shape and composition. Specifically, the cubes enclosed by {100} facets readily deform shape at a temperature 300 °C lower than that of the octahedral counterparts enclosed by {111} facets. A reversed trend is observed for composition, as alloying between the Pd core and the Pt shell of an octahedron occurs at a temperature 200 °C lower than that for the cubic counterpart. Density functional theory calculations provide atomic-level explanations for the experimentally observed behaviors, demonstrating that the barriers for edge reconstruction determine the relative ease of shape deformation for cubes compared to octahedra. Furthermore, the opposite trend for alloying of the core–shell structure can be attributed to a higher propensity for subsurface Pt vacancy formation in octahedra than in cubes.

36 MATERIALS SCIENCE↗

Experimental Determination of the Ionization Energies of MoSe 2 , WS 2 , and MoS 2 on SiO 2 Using Photoemission Electron Microscopy

Here, the values of the ionization energies of transition metal dichalcogenides (TMDs) are needed to assess their potential usefulness in semiconductor heterojunctions for high-performance optoelectronics. Here, we report on the systematic determination of ionization energies for three prototypical TMD monolayers (MoSe 2 , WS 2 , and MoS 2 ) on SiO 2 using photoemission electron microscopy with deep ultraviolet illumination. The ionization energy displays a progressive decrease from MoS 2 , to WS 2 , to MoSe 2 , in agreement with predictions of density functional theory calculations. Combined with the measured energy positions of the valence band edge at the Brillouin zone center, we deduce that, in the absence of interlayer coupling, a vertical heterojunction comprising any of the three TMD monolayers would form a staggered (type-II) band alignment. This band alignment could give rise to long-lived interlayer excitons that are potentially useful for valleytronics or efficient electron–hole separation in photovoltaics.

36 MATERIALS SCIENCE↗

Deep Learning of Atomically Resolved Scanning Transmission Electron Microscopy Images: Chemical Identification and Tracking Local Transformations

Recent advances in scanning transmission electron and scanning probe microscopies have opened unprecedented opportunities in probing the materials structural parameters and various functional properties in real space with an angstrom-level precision. This progress has been accompanied by exponential increase in the size and quality of datasets produced by microscopic and spectroscopic experimental techniques. These developments necessitate adequate methods for extracting relevant physical and chemical information from the large datasets, for which a priori information on the structures of various atomic configurations and lattice defects is limited or absent. Here we demonstrate an application of deep neural networks to extracting information from atomically resolved images including location of the atomic species and type of defects. We develop a “weakly-supervised” approach that uses information on the coordinates of all atomic species in the image, extracted via a deep neural network, to identify a rich variety of defects that are not part of an initial training set. We further apply our approach to interpret complex atomic and defect transformation, including switching between different coordination of silicon dopants in graphene as a function of time, formation of peculiar silicon dimer with mixed 3-fold and 4-fold coordination, and the motion of molecular “rotor”. In conclusion, this deep learning based approach resembles logic of a human operator, but can be scaled leading to significant shift in the way of extracting and analyzing information from raw experimental data.

36 MATERIALS SCIENCE↗

Operando Atomic Force Microscopy Reveals Mechanics of Structural Water Driven Battery-to-Pseudocapacitor Transition

The presence of structural water in tungsten oxides leads to a transition in the energy storage mechanism from battery-type intercalation (limited by solid state diffusion) to pseudocapacitance (limited by surface kinetics). Here, we demonstrate that these electrochemical mechanisms are linked to the mechanical response of the materials during intercalation of protons and present a pathway to utilize the mechanical coupling for local studies of electrochemistry. Operando atomic force microscopy dilatometry is used to measure the deformation of redox-active energy storage materials and to link the local nanoscale deformation to the electrochemical redox process. Here, this technique reveals that the local mechanical deformation of the hydrated tungsten oxide is smaller and more gradual than the anhydrous oxide and occurs without hysteresis during the intercalation and deintercalation processes. The ability of layered materials with confined structural water to minimize mechanical deformation likely contributes to their fast energy storage kinetics.

25 ENERGY STORAGE↗

In Situ Electron Microscopy Investigation of Sodiation of Titanium Disulfide Nanoflakes

Two-dimensional (2D) metal sulfides show great promises for their potential applications as electrode materials of sodium ion batteries because of the weak interlayer van der Waals interactions which allow the reversible accommodation and extraction of sodium ions. The sodiation of metal sulfides can undergo a distinct process compared to that of lithiation, which is determined by their metal and structural types. Yet, the structural and morphological evolution during its electrochemical sodiation is still unclear. In this report, we studied the sodiation reaction dynamics of TiS 2 by employing in situ transmission electron microscopy and first-principles calculations. During the sodium ion intercalation process, we observed multiple intermediate phases (phase II, phase Ib, and phase Ia), different from its lithiation counterpart, with varied sodium occupation sites and interlayer stacking sequences. Further insertion of Na ions prompted a multi-step extrusion reaction which led to the phase separation of Ti metal from the Na 2 S matrix, with its 2D morphology expanded to a 3D morphology. In contrast to regular conversion electrodes, TiS 2 still maintained a compacted structure after a full sodiation. Frist-principles calculations reveal that the as-identified phases are thermodynamically preferred at corresponding intercalation/extrusion stages compared to other possible phases. The current work provides the fundamental mechanistic understanding of the sodiation process of 2D transition metal sulfides.

25 ENERGY STORAGE↗

Insights into the Structure and Dynamics of Metal–Organic Frameworks via Transmission Electron Microscopy

Metal–organic frameworks (MOFs) are hybrid materials composed of metal ions and organic linkers featuring high porosity, crystallinity, and chemical tunability at multiple length scales. Here, a recent advancement in transmission electron microscopy (TEM) and its direct application to MOF structure–property relationships have changed how we consider rational MOF design and development. Herein, we provide a perspective on TEM studies of MOFs and highlight the utilization of state-of-the-art TEM technologies to explore dynamic MOF processes and host–guest interactions. Additionally, we provide thoughts on what the future holds for TEM in the study of MOFs.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Self-Assembly of Metallo-Supramolecules with Dissymmetrical Ligands and Characterization by Scanning Tunneling Microscopy

Asymmetrical and dissymmetrical structures are widespread and play a critical role in nature and life systems. In the field of metallo-supramolecular assemblies, it is still in its infancy for constructing artificial architectures using dissymmetrical building blocks. Herein, we report the self-assembly of supramolecular systems based on two dissymmetrical double-layered ligands. With the aid of ultra-high-vacuum, low-temperature scanning tunneling microscopy (UHV-LT-STM), we were able to investigate four isomeric structures corresponding to four types of binding modes of ligand LA with two major conformations complexes A. The distribution of isomers measured by STM and total binding energy of each isomer obtained by density functional theory (DFT) calculations suggested that the most abundant isomer could be the most stable one with highest total binding energy. Lastly, through shortening the linker between inner and outer layers and the length of arms, the arrangement of dissymmetrical ligand LB could be controlled within one binding mode corresponding to the single conformation for complexes B.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

The cryo-electron microscopy structure of human transcription factor IIH

We report human transcription factor IIH (TFIIH) is part of the general transcriptional machinery required by RNA polymerase II for the initiation of eukaryotic gene transcription. Composed of ten subunits that add up to a molecular mass of about 500 kDa, TFIIH is also essential for nucleotide excision repair. The seven-subunit TFIIH core complex formed by XPB, XPD, p62, p52, p44, p34, and p8 is competent for DNA repair, while the CDK-activating kinase subcomplex, which includes the kinase activity of CDK7 as well as the cyclin H and MAT1 subunits, is additionally required for transcription initiation. Mutations in the TFIIH subunits XPB, XPD, and p8 lead to severe premature ageing and cancer propensity in the genetic diseases xeroderma pigmentosum, Cockayne syndrome, and trichothiodystrophy, highlighting the importance of TFIIH for cellular physiology. Here we present the cryo-electron microscopy structure of human TFIIH at 4.4 Å resolution. The structure reveals the molecular architecture of the TFIIH core complex, the detailed structures of its constituent XPB and XPD ATPases, and how the core and kinase subcomplexes of TFIIH are connected. Also, our structure provides insight into the conformational dynamics of TFIIH and the regulation of its activity.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Thermoresponsive polymer assemblies via variable temperature liquid-phase transmission electron microscopy and small angle X-ray scattering

Abstract Herein, phase transitions of a class of thermally-responsive polymers, namely a homopolymer, diblock, and triblock copolymer, were studied to gain mechanistic insight into nanoscale assembly dynamics via variable temperature liquid-cell transmission electron microscopy (VT-LCTEM) correlated with variable temperature small angle X-ray scattering (VT-SAXS). We study thermoresponsive poly(diethylene glycol methyl ether methacrylate) (PDEGMA)-based block copolymers and mitigate sample damage by screening electron flux and solvent conditions during LCTEM and by evaluating polymer survival via post-mortem matrix-assisted laser desorption/ionization imaging mass spectrometry (MALDI-IMS). Our multimodal approach, utilizing VT-LCTEM with MS validation and VT-SAXS, is generalizable across polymeric systems and can be used to directly image solvated nanoscale structures and thermally-induced transitions. Our strategy of correlating VT-SAXS with VT-LCTEM provided direct insight into transient nanoscale intermediates formed during the thermally-triggered morphological transformation of a PDEGMA-based triblock. Notably, we observed the temperature-triggered formation and slow relaxation of core-shell particles with complex microphase separation in the core by both VT-SAXS and VT-LCTEM.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Observation of electron orbital signatures of single atoms within metal-phthalocyanines using atomic force microscopy

Resolving the electronic structure of a single atom within a molecule is of fundamental importance for understanding and predicting chemical and physical properties of functional molecules such as molecular catalysts. However, the observation of the orbital signature of an individual atom is challenging. We report here the direct identification of two adjacent transition-metal atoms, Fe and Co, within phthalocyanine molecules using high-resolution noncontact atomic force microscopy (HR-AFM). HR-AFM imaging reveals that the Co atom is brighter and presents four distinct lobes on the horizontal plane whereas the Fe atom displays a “square” morphology. Pico-force spectroscopy measurements show a larger repulsion force of about 5 pN on the tip exerted by Co in comparison to Fe. Our combined experimental and theoretical results demonstrate that both the distinguishable features in AFM images and the variation in the measured forces arise from Co’s higher electron orbital occupation above the molecular plane. The ability to directly observe orbital signatures using HR-AFM should provide a promising approach to characterizing the electronic structure of an individual atom in a molecular species and to understand mechanisms of certain chemical reactions.

36 MATERIALS SCIENCE↗

Demonstration of an AI-driven workflow for autonomous high-resolution scanning microscopy

Abstract Modern scanning microscopes can image materials with up to sub-atomic spatial and sub-picosecond time resolutions, but these capabilities come with large volumes of data, which can be difficult to store and analyze. We report the Fast Autonomous Scanning Toolkit (FAST) that addresses this challenge by combining a neural network, route optimization, and efficient hardware controls to enable a self-driving experiment that actively identifies and measures a sparse but representative data subset in lieu of the full dataset. FAST requires no prior information about the sample, is computationally efficient, and uses generic hardware controls with minimal experiment-specific wrapping. We test FAST in simulations and a dark-field X-ray microscopy experiment of a WSe 2 film. Our studies show that a FAST scan of <25% is sufficient to accurately image and analyze the sample. FAST is easy to adapt for any scanning microscope; its broad adoption will empower general multi-level studies of materials evolution with respect to time, temperature, or other parameters.

47 OTHER INSTRUMENTATION↗

Structural polymorphism of amyloid fibrils in ATTR amyloidosis revealed by cryo-electron microscopy

ATTR amyloidosis is caused by the deposition of transthyretin in the form of amyloid fibrils in virtually every organ of the body, including the heart. This systemic deposition leads to a phenotypic variability that has not been molecularly explained yet. In brain amyloid conditions, previous studies suggest an association between clinical phenotype and the molecular structures of their amyloid fibrils. Here we investigate whether there is such an association in ATTRv amyloidosis patients carrying the mutation I84S. Using cryo-electron microscopy, we determined the structures of cardiac fibrils extracted from three ATTR amyloidosis patients carrying the ATTRv-I84S mutation, associated with a consistent clinical phenotype. We found that in each ATTRv-I84S patient, the cardiac fibrils exhibited different local conformations, and these variations can co-exist within the same fibril. Our finding suggests that one amyloid disease may associate with multiple fibril structures in systemic amyloidoses, calling for further studies.

59 BASIC BIOLOGICAL SCIENCES↗

Differential programming enabled functional imaging with Lorentz transmission electron microscopy

Abstract Lorentz transmission electron microscopy is an advanced characterization technique that enables the simultaneous imaging of both the microstructure and functional properties of materials. Information such as magnetization and electric potentials is carried by the phase of the electron wave, and is lost during image acquisition. Various methods have been proposed to retrieve the phase of the electron wavefunction using intensities of the acquired images, most of which work only in the small defocus limit. Imaging at strong defoci not only carries more quantitative phase information, but is essential to the study of weak magnetic and electrostatic fields at the nanoscale. In this work we develop a method based on differentiable programming to solve the inverse problem of phase retrieval. We show that our method maintains a high spatial resolution and robustness against noise even at the upper defocus limit of the microscope. More importantly, our proposed method can go beyond recovering just the phase information. We demonstrate this by retrieving the electron-optical parameters of the contrast transfer function alongside the electron exit wavefunction.

97 MATHEMATICS AND COMPUTING↗

Rapid and flexible segmentation of electron microscopy data using few-shot machine learning

Abstract Automatic segmentation of key microstructural features in atomic-scale electron microscope images is critical to improved understanding of structure–property relationships in many important materials and chemical systems. However, the present paradigm involves time-intensive manual analysis that is inherently biased, error-prone, and unable to accommodate the large volumes of data produced by modern instrumentation. While more automated approaches have been proposed, many are not robust to a high variety of data, and do not generalize well to diverse microstructural features and material systems. Here, we present a flexible, semi-supervised few-shot machine learning approach for segmentation of scanning transmission electron microscopy images of three oxide material systems: (1) epitaxial heterostructures of SrTiO 3 /Ge, (2) La 0.8 Sr 0.2 FeO 3 thin films, and (3) MoO 3 nanoparticles. We demonstrate that the few-shot learning method is more robust against noise, more reconfigurable, and requires less data than conventional image analysis methods. This approach can enable rapid image classification and microstructural feature mapping needed for emerging high-throughput characterization and autonomous microscope platforms.

36 MATERIALS SCIENCE↗

Imaging atomic-scale chemistry from fused multi-modal electron microscopy

Efforts to map atomic-scale chemistry at low doses with minimal noise using electron microscopes are fundamentally limited by inelastic interactions. Here, fused multi-modal electron microscopy offers high signal-to-noise ratio (SNR) recovery of material chemistry at nano- and atomic-resolution by coupling correlated information encoded within both elastic scattering (high-angle annular dark-field (HAADF)) and inelastic spectroscopic signals (electron energy loss (EELS) or energy-dispersive x-ray (EDX)). By linking these simultaneously acquired signals, or modalities, the chemical distribution within nanomaterials can be imaged at significantly lower doses with existing detector hardware. In many cases, the dose requirements can be reduced by over one order of magnitude. This high SNR recovery of chemistry is tested against simulated and experimental atomic resolution data of heterogeneous nanomaterials.

36 MATERIALS SCIENCE↗

Uncertainty-aware particle segmentation for electron microscopy at varied length scales

Electron microscopy is indispensable for examining the morphology and composition of solid materials at the sub-micron scale. To study the powder samples that are widely used in materials development, scanning electron microscopes (SEMs) are increasingly used at the laboratory scale to generate large datasets with hundreds of images. Parsing these images to identify distinct particles and determine their morphology requires careful analysis, and automating this process remains challenging. In this work, we enhance the Mask R-CNN architecture to develop a method for automated segmentation of particles in SEM images. We address several challenges inherent to measurements, such as image blur and particle agglomeration. Moreover, our method accounts for prediction uncertainty when such issues prevent accurate segmentation of a particle. Recognizing that disparate length scales are often present in large datasets, we use this framework to create two models that are separately trained to handle images obtained at low or high magnification. By testing these models on a variety of inorganic samples, our approach to particle segmentation surpasses an established automated segmentation method and yields comparable results to the predictions of three domain experts, revealing comparable accuracy while requiring a fraction of the time. These findings highlight the potential of deep learning in advancing autonomous workflows for materials characterization.

36 MATERIALS SCIENCE↗

Uncovering multiscale structure-property correlations via active learning in scanning tunneling microscopy

Atomic arrangements and local sub-structures fundamentally influence emergent material functionalities. These structures are conventionally probed using spatially resolved studies and the property correlations are deciphered by a researcher based on sequential explorations, thereby limiting the efficiency and scope. Here we demonstrate a multi-scale Bayesian deep-learning based framework that automatically correlates material structure with its electronic properties using scanning tunneling microscopy (STM) measurements in real-time. Its predictions are used to autonomously direct exploration toward regions of the sample that optimize a given material property. This method is deployed on a low-temperature ultra-high vacuum STM to understand the structure-property relationship in a europium-based semimetal, EuZn 2 As 2 , a promising candidate relevant to magnetism-driven topological phenomena. The framework employs a sparse-sampling approach to efficiently construct the scalar-property space using minimal measurements, about 1–10% of the data required in standard hyperspectral methods. Moreover, we formulate the problem hierarchically across length scales, implementing autonomous workflow to locate mesoscopic and atomic structures that correspond to a target material property. This framework offers the choice to design scalar-property from the spectroscopic data to steer sample exploration. Our findings reveal correlations of the electronic properties unique to surface terminations, local defect density, and point defects.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

BEACON—automated aberration correction for scanning transmission electron microscopy using Bayesian optimization

Aberration correction is an important aspect of modern high-resolution scanning transmission electron microscopy. Most methods of aligning aberration correctors require specialized sample regions and are unsuitable for fine-tuning aberrations without interrupting on-going experiments. Here, we present an automated method of correcting first- and second-order aberrations called BEACON, which uses Bayesian optimization of the normalized image variance to efficiently determine the optimal corrector settings. We demonstrate its use on gold nanoparticles and a hafnium dioxide thin film showing its versatility in nano- and atomic-scale experiments. BEACON can correct all first- and second-order aberrations simultaneously to achieve an initial alignment and first- and second-order aberrations independently for fine alignment. Ptychographic reconstructions are used to demonstrate an improvement in probe shape and a reduction in the target aberration.

techniques and instrumentation↗