High-Resolution Mapping of Photocatalytic Activity by Diffusion-Based and Tunneling Modes of Photo-Scanning Electrochemical Microscopy
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37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
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Investigating the failure behavior of cast Al-11Ce-0.4Mg alloys using in-situ scanning electron microscopy tensile testing
Within the last decade, research on Al-Ce-Mg alloys has reported promising results for use in cast part applications. In this paper, the failure behavior of cast Al-11Ce-0.4Mg (wt%) was investigated experimentally with focus on the effect the matrix and intermetallic phases have on the fracture propagation behavior at failure. For the first time, in-situ SEM tensile testing was used to study the failure behavior of cast Al-Ce alloys, reporting results for uniaxial, DIC, and single edge notch tensile tests. The results of the in-situ SEM tensile testing were compared with the materials characterization experiments, which included serial sectioning, EBSD, EDS, and fractography. Analysis of EBSD and EDS mapping of cast Al-11Ce-0.4Mg showed that the cast microstructure was a hypereutectic two phase Al-Ce alloy with grains encompassing large complex colonies of laminar eutectic Al 11 Ce 3 intermetallic. The uniaxial tensile results reported the effect casting defects have on the strength and ductility of the alloy, and DIC in-situ testing showed that the eutectic colonies plastically deform less than the matrix phase. In-situ SEM single edge notch tensile testing displayed how the strength of an individual phase affected the crack propagation direction in the alloy. The results of both the materials characterization and in-situ tensile testing experiments on the failure of this alloy revealed further directions for future alloy development that can improve both the strength and fracture toughness of Al-Ce-Mg alloys.
36 MATERIALS SCIENCE↗
Disentangling Electronic Transport and Hysteresis at Individual Grain Boundaries in Hybrid Perovskites via Automated Scanning Probe Microscopy
Underlying the rapidly increasing photovoltaic efficiency and stability of metal halide perovskites (MHPs) is the advancement in the understanding of the microstructure of polycrystalline MHP thin film. Over the past decade, intense efforts have been aimed at understanding the effect of microstructures on MHP properties, including chemical heterogeneity, strain disorder, phase impurity, etc. It has been found that grain and grain boundary (GB) are tightly related to lots of microscale and nanoscale behavior in MHP thin films. Atomic force microscopy (AFM) is widely used to observe grain and boundary structures in topography and subsequently to study the correlative surface potential and conductivity of these structures. For now, most AFM measurements have been performed in imaging mode to study the static behavior; in contrast, AFM spectroscopy mode allows us to investigate the dynamic behavior of materials, e.g., conductivity under sweeping voltage. However, a major limitation of AFM spectroscopy measurements is that they require manual operation by human operators, and as such only limited data can be obtained, hindering systematic investigations of these microstructures. Here, we designed a workflow combining the conductive AFM measurement with a machine learning (ML) algorithm to systematically investigate grain boundaries in MHPs. The trained ML model can extract GBs locations from the topography image, and the workflow drives the AFM probe to each GB location to perform a current–voltage (IV) curve automatically. Then, we are able to have IV curves at all GB locations, allowing us to systematically understand the property of GBs. Using this method, we discovered that the GB junction points are less conductive, potentially more photoactive, and can play critical roles in MHP stability, while most previous works only focused on the difference between GB and grains.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
Atomic‐Scale Surface Imaging of Bulk Epitaxial CsPbBr 3 Perovskite Single Crystals on Mica Using Light Assisted Scanning Tunneling Microscopy at Low‐Temperature (80 K)
Epitaxial single-crystalline CsPbBr 3 perovskite films on mica, prepared ex situ, are explored using a low-temperature scanning tunneling microscope (STM) by probing the unoccupied electronic states of their surface in ultra-high vacuum (UHV) at 80 K. Light-assisted STM measurements under a broadband illumination with visible light were employed to enhance and stabilize surface conductivity. STM imaging across the surface of macroscopic bulk CsPbBr 3 films reveals large flat terraces characterized by a specific type of surface reconstruction, consisting of parallel rows of U-shaped atomic nanostructures. These structures are spaced by 12 Å and exhibit an internal feature size of 5.1 Å. Density functional theory (DFT) calculations reproduce the experimental observations and reveal a competition between different orthorhombic CsPbBr 3 (110) surface reconstructions: a Cs-rich structure, identified as the most energetically stable, and three alternative Pb–Br-rich reconstructions, which are slightly higher in energy yet remain consistent with the STM data. Additional analyses that explicitly account for the mica substrate exclude the cubic CsPbBr 3 phase and other orthorhombic surface orientations, while showing that variations in the mica surface termination do not alter the preferred CsPbBr 3 (110) reconstruction. In conclusion, this combined approach thereby confirms our assignment and resolves previous STM interpretations of CsPbBr 3 .
36 MATERIALS SCIENCE↗
Autonomous scanning probe microscopy investigations over WS2 and Au{111}
Abstract Individual atomic defects in 2D materials impact their macroscopic functionality. Correlating the interplay is challenging, however, intelligent hyperspectral scanning tunneling spectroscopy (STS) mapping provides a feasible solution to this technically difficult and time consuming problem. Here, dense spectroscopic volume is collected autonomously via Gaussian process regression, where convolutional neural networks are used in tandem for spectral identification. Acquired data enable defect segmentation, and a workflow is provided for machine-driven decision making during experimentation with capability for user customization. We provide a means towards autonomous experimentation for the benefit of both enhanced reproducibility and user-accessibility. Hyperspectral investigations on WS 2 sulfur vacancy sites are explored, which is combined with local density of states confirmation on the Au{111} herringbone reconstruction. Chalcogen vacancies, pristine WS 2 , Au face-centered cubic, and Au hexagonal close-packed regions are examined and detected by machine learning methods to demonstrate the potential of artificial intelligence for hyperspectral STS mapping.
36 MATERIALS SCIENCE↗
Exploring the Relationship of Microstructure and Conductivity in Metal Halide Perovskites via Active Learning-Driven Automated Scanning Probe Microscopy
Electronic transport and hysteresis in metal halide perovskites (MHPs) are key to the applications in photovoltaics, light emitting devices, and light and chemical sensors. These phenomena are strongly affected by the materials microstructure including grain boundaries, ferroic domain walls, and secondary phase inclusions. Here, we demonstrate an active machine learning framework for “driving” an automated scanning probe microscope (SPM) to discover the microstructures responsible for specific aspects of transport behavior in MHPs. In our setup, the microscope can discover the microstructural elements that maximize the onset of conduction, hysteresis, or any other characteristic that can be derived from a set of current–voltage spectra. Furthermore, this approach opens new opportunities for exploring the origins of materials functionality in complex materials by SPM and can be integrated with other characterization techniques either before (prior knowledge) or after (identification of locations of interest for detail studies) functional probing.
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A study on the creep behavior of alloy 709 using in-situ scanning electron microscopy
In this research, an experimental evaluation of creep properties of Alloy 709 in the temperature range of 750–850 °C was undertaken. Alloy 709 is a novel austenitic stainless steel with 20% Cr and 25% Ni by wt% that was developed for application in structural components of nuclear power plants. Creep rupture tests were conducted in an in-situ heating-loading and Scanning Electron Microscope (SEM) unit equipped with Electron Backscatter Diffraction (EBSD) detector and Energy Dispersive Spectroscopy (EDS). “Real-time” creep damage mechanisms of Alloy 709 at various stresses and temperatures using a flat, un-notched sample with continuously reducing cross-section is studied so that the failure and maximum creep damage occurred at the center of the sample where the in-situ SEM imaging could be focused. Accelerated creep tests at temperatures and stresses above service conditions were performed by employing multiple blocks of constant loads where the loads were increased once the sample attained constant creep rate, indicating a secondary creep regime. This technique ensures multiple data points can be obtained from the same test, saves the time required for an otherwise long-term creep test and usage of SEM. Further, Coincident Site Lattice (CSL) boundary maps were collected as control maps before testing, and the grain boundaries were observed during the creep test to understand the effect of grain boundary character on the creep damage mechanism. Void growth, grain boundary separation, and sliding were found to be the main creep mechanisms whose rate is dependent on stress and temperature. Failure mechanisms studied on the fracture surface using SEM fractography were correlated to the sample surface observations to create complementary information to better understand the underline creep mechanism of Alloy 709.
36 MATERIALS SCIENCE↗
Using Fission-Track Radiography Coupled with Scanning Electron Microscopy for Efficient Identification of Solid-Phase Uranium Mineralogy at a Former Uranium Pilot Mill (Grand Junction, Colorado)
At a former uranium pilot mill in Grand Junction, Colorado, mine tailings and some subpile sediments were excavated to various depths to meet surface radiological standards, but residual solid-phase uranium below these excavation depths still occurs at concentrations above background. The combination of fission-track radiography and scanning electron microscope energy-dispersive X-ray spectroscopy (SEM-EDS) provides a uniquely efficient and quantitative way of determining mineralogic associations of uranium that can influence uranium mobility. After the creation of sample thin sections, a mica sheet is placed on those thin sections and irradiated in a nuclear research reactor. Decay of the irradiated uranium creates fission tracks that can be viewed with a microscope. The fission-track radiography images indicate thin section sample areas with elevated uranium that are focus areas for SEM-EDS work. EDS spectra provide quantitative elemental data that indicate the mineralogy of individual grains or grain coatings associated with the fission-track identification of elevated uranium. For the site in this study, the results indicated that uranium occurred (1) with coatings of aluminum–silicon (Al/Si) gel and gypsum, (2) dispersed in the unsaturated zone associated with evaporite-type salts, and (3) sorbed onto organic carbon. The Al/Si gel likely formed when low-pH waters were precipitated during calcite buffering, which in turn retained or precipitated trace amounts of Fe, As, U, V, Ca, and S. Understanding these mechanisms can help guide future laboratory and field-scale efforts in determining long-term uranium release rates to groundwater.
58 GEOSCIENCES↗
Evidence for quantum spin liquid behaviour in single-layer 1T-TaSe 2 from scanning tunnelling microscopy
Two-dimensional triangular-lattice antiferromagnets are predicted under some conditions to exhibit a quantum spin liquid ground state with no energy barrier to create emergent, fractionalized spinon excitations that carry spin but no charge. Materials that realize this kind of spin liquid are expected to have a low-energy behaviour described by a spinon Fermi surface. Directly imaging the resulting spinons, however, is difficult due to their chargeless nature. In this work, we use scanning tunnelling spectroscopy to image density waves consistent with the predictions of spinon density modulation arising from a spinon Fermi surface instability in single-layer 1T-TaSe 2 . We confirm the existence of a triangular lattice of localized spins in this material by contacting it with a metallic 1H-TaSe 2 substrate and measuring the Kondo effect. Spectroscopic imaging of isolated single-layer 1T-TaSe 2 reveals long-wavelength super-modulations at Hubbard band energies, consistent with the predicted behaviour of itinerant spinons. These super-modulations allow the direct experimental measurement of the spinon Fermi wavevector, in good agreement with theoretical predictions for a two-dimensional quantum spin liquid.
71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
Smart Scattering Scanning Near-Field Optical Microscopy
Scattering scanning near-field optical microscopy (s-SNOM) provides spectroscopic imaging from molecular to quantum materials with few nanometer deep subdiffraction limited spatial resolution. However, in its conventional implementation s-SNOM is slow to effectively acquire a series of spatio-spectral images, especially with large fields of view. This problem is further exacerbated for weak resonance contrast or when using light sources with limited spectral irradiance. Indeed, the generally limited signal-to-noise ratio prevents sampling a weak signal at the Nyquist sampling rate. Here, we demonstrate how acquisition time and sampling rate can be significantly reduced by using compressed sampling, matrix completion, and adaptive random sampling, while maintaining or even enhancing the physical or chemical image content. We use fully sampled real data sets of molecular, biological, and quantum materials as ground-truth physical data and show how deep under-sampling with a corresponding reduction of acquisition time by 1 order of magnitude or more retains the core s-SNOM image information. We demonstrate that a sampling rate of up to 6× smaller than the Nyquist criterion can be applied, which would provide a 30-fold reduction in the data required under typical experimental conditions. Furthermore, our smart s-SNOM approach is generally applicable and provides systematic full spatio-spectral s-SNOM imaging with a large field of view at high spectral resolution and reduced acquisition time.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
Freeform Hybrid Manufacturing: Binderjet, Structured Light Scanning, Confocal Microscopy, and CNC Machining
This paper describes a hybrid manufacturing approach for silicon carbide (SiC) freeform surfaces using binder jet additive manufacturing (BJAM) to print the preform and machining to obtain the design geometry. Although additive manufacturing (AM) techniques such as BJAM allow for the fabrication of complex geometries, additional machining or grinding is often required to achieve the desired surface finish and shape. Hybrid manufacturing has been shown to provide an effective solution. However, hybrid manufacturing also has its own challenges, depending on the combination of processes. For example, when the subtractive and additive manufacturing steps are performed sequentially on separate systems, it is necessary to define a common coordinate system for part transfer. This can be difficult because AM preforms do not inherently contain features that can serve as datums. Additionally, it is important to confirm that the intended final geometry is contained within the AM preform. The approach described here addresses these challenges by using structured light scanning to create a stock model for machining. Results show that a freeform surface was machined with approximately 70 µm of maximum deviation from that which was planned.
Dvorak, Jake (ORCID:0000000260989944)↗
Qualitative assessment of uranium ore concentrates and related materials using scanning electron microscopy
Several studies have evaluated the morphology of uranium compounds produced under controlled conditions at the laboratory scale, but it is unclear whether the morphological characteristics of these materials persist in commercially produced uranium ore concentrates (UOCs). To assess the morphology in “real-world” UOCs, we qualitatively evaluated the morphological profile of secondary electron images from over 100 commercial UOCs using a previously published lexicon. We observe differences between samples with differing chemical composition and samples with similar chemical composition and differing provenance. Further, this work contextualizes morphology for commercially produced UOCs and will provide a basis for future machine learning efforts.
11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
Light-Dependent Impedance Spectra and Transient Photoconductivity in a Ruddlesden–Popper 2D Lead–Halide Perovskite Revealed by Electrical Scanned Probe Microscopy and Accompanying Theory
Electric force microscopy was used to record the light-dependent impedance spectrum and the probe transient photoconductivity of a film of butylammonium lead iodide, BA 2 PbI 4 , a 2D Ruddlesden–Popper perovskite semiconductor. The impedance spectrum of BA 2 PbI 4 showed modest changes as the illumination intensity was varied up to 1400 mW cm –2 , in contrast with the comparatively dramatic changes seen for 3D lead–halide perovskites under similar conditions. BA 2 PbI 4 ’s light-induced conductivity had a rise time and decay time of ~100 μs, 10 4 slower than expected from direct electron–hole recombination yet 10 5 faster than the conductivity-recovery times recently observed in 3D lead–halide perovskites and attributed to the relaxation of photogenerated vacancies. What sample properties are probed by electric force microscope measurements remains an open question. A Lagrangian-mechanics treatment of the electric force microscope experiment was recently introduced by Dwyer, Harrell, and Marohn which enabled the calculation of steady-state electric force microscope signals in terms of a complex sample impedance. Here this impedance treatment of the tip–sample interaction is extended, through the introduction of a time-dependent transfer function, to include time-resolved electrical scanned probe measurements. Here, it is shown that the signal in a phase-kick electric force microscope experiment, and therefore also the signal in a time-resolved electrostatic force microscope experiment, can be written explicitly in terms of the sample’s time-dependent resistance (i.e., conductivity).
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
Adaptive Scalpel Scanning Probe Microscopy for Enhanced Volumetric Sensing in Tomographic Analysis
Controlling nanoscale tip‐induced material removal is crucial for achieving atomic‐level precision in tomographic sensing with atomic force microscopy (AFM). While advances have enabled volumetric probing of conductive features with nanometer accuracy in solid‐state devices, materials, and photovoltaics, limitations in spatial resolution and volumetric sensitivity persist. This work identifies and addresses in‐plane and vertical tip‐sample junction leakage as sources of parasitic contrast in tomographic AFM, hindering real‐space 3D reconstructions. Novel strategies are proposed to overcome these limitations. First, the contrast mechanisms analyzing nanosized conductive features are explored when confining current collection purely to in‐plane transport, thus allowing reconstruction with a reduction in the overestimation of the lateral dimensions. Furthermore, an adaptive tip‐sample biasing scheme is demonstrated for the mitigation of a class of artefacts induced by the high electric field inside the thin oxide when volumetrically reduced. This significantly enhances vertical sensitivity by approaching the intrinsic limits set by quantum tunneling processes, allowing detailed depth analysis in thin dielectrics. The effectiveness of these methods is showcased in tomographic reconstructions of conductive filaments in valence change memory, highlighting the potential for application in nanoelectronics devices and bulk materials and unlocking new limits for tomographic AFM.
36 MATERIALS SCIENCE↗
Combining fission-track radiography and scanning electron microscopy to identify uranium host phases
Not provided.
Environmental Sciences & Ecology↗