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Hypothesis-learning-driven automated scanning probe microscopy allows physical discovery during experiments, where the hypothesis learning algorithm implemented on an operating microscope identifies the physical mechanism behind the material’s response
The broad adoption of machine learning (ML)-based autonomous experiments (AEs) in material characterization and synthesis requires strategies development for understanding and intervention in the experimental workflow. Here, we introduce and realize a post-experimental analysis strategy for deep kernel learning-based autonomous scanning probe microscopy. This approach yields real-time and post-experimental indicators for the progression of an active learning process interacting with an experimental system. We further illustrate how this approach can be applied to human-in-the-loop AEs, where human operators make high-level decisions at high latencies setting the policies for AEs, and the ML algorithm performs low-level, fast decisions. The proposed approach is universal and can be extended to other techniques and applications such as combinatorial library analysis.
Here, we consider theoretically extension of magnetic resonance force microscopy (MRFM) replacing a ferromagnetic probe on a cantilever tip (CT) with a paramagnetic one (PMRFM). The dynamics of the interaction between the paramagnetic probe and a local magnetic moment in a sample is analyzed, using a quasi-classical approach. We show that the application of a proper sequence of electromagnetic pulses provides a significant deflection of the CT from the initial equilibrium position. Periodic application of these sequences of pulses results in quasi-periodic CT deflections from the equilibrium, which can be used for detection of the magnetic moment in a sample.
This study directly compares the mechanical behavior of novel molecular layer deposition (MLD) and analogous interfacial polymerization (IP) polyamide thin films in environments relevant to reverse osmosis (RO) membrane operation. The elastic modulus of the films was determined using atomic force microscopy (AFM) in dry, hydrated, and chlorinated states. Surface roughness characteristics were also obtained given their potential influence on AFM modulus measurements. The much smoother MLD films demonstrated a statistically higher modulus in all states as compared to their IP counterparts. The MLD films maintained a modulus ~3X and ~5X greater than that of IP films after hydration and chlorination, respectively. Such differences in behavior may be due to the higher density and correspondingly lower void content of the MLD films. Results from this study provide a rationale for future development of MLD for fabrication of polyamide films for incorporation in RO membranes.
The advent of optical super-resolution microscopy (OSRM) over two decades ago has transformed light-mediated interrogation of systems down to the nanoscale. This innovative set of approaches to optics breaks the so-called diffraction limit of light (~200 nm), allowing for the first time to use optics in the far field to visualize behavior on nanoscopic length scales. While these visualization tools have rapidly found widespread use in biology and related fields, their implementation in materials and, more specifically, in polymer science has been far slower. To overcome possible barriers and highlight possible future directions, we present in this paper an introduction to OSRM for polymer scientists, beginning with an overview of relevant techniques and existing optical probes. We then show and examine the first examples of OSRM adaptation across major areas of polymer science, including: polymerization and structural characterization, self-assembly and solution behavior, bulk structure and behavior, crystallization, gel structure and behavior, phase transitions, and biofunctionality. We hope and anticipate that the discussions provided in this review will draw the attention of the polymer community to the capacities of these hitherto underexplored optical visualization techniques to further transform polymer science.
The subsurface dislocation content in a Ti-5Al-2.5Sn (wt%) uniaxial tension sample deformed at ambient temperature was characterized by peak streak analysis of micro-Laue diffraction patterns collected non-destructively by differential aperture X-raymicroscopy, and with focused ion beam transmission electron microscopy of material in the same volume. This comparison reveals that micro-Laue diffraction streak analysis based on an edge dislocation assumption can accurately identify the dominant dislocation slip system history (Burgers vector and plane observed by TEM), despite the fact that dislocations have predominantly screw character. As a result, other dislocations identified by TEM were not convincingly discernible from the peak streak analysis.
We report on nm-resolution imaging of charge-carrier distribution around local potential-induced degradation (PID) shunting defects using scanning capacitance microscopy. We imaged on cross sections of heavily field-degraded module areas, cored out and selected by mm-scale photoluminescence imaging. We found localized areas with abnormal carrier behavior induced by the PID defects: the apparent n-type carrier extends vertically into the absorber to ~1-2 um from the cell surface, and laterally in similar lengths; in defect-free areas, the n-type carrier extends ~0.5 um, which is consistent with the junction depth. For comparison, we also investigated areas of the same module exhibiting the least PID stress, and we found no such heavily damaged junction area. Instead, we found slightly abnormal carrier behavior, where the carrier-type inversion in the absorber did not occur, but the p-type carrier concentration changed slightly in a much smaller lateral length of ~300 nm. These nano-electrical findings may indicate a possible mechanism that the existing extended defects, which may not be significantly harmful to cell performance, can be changed by PID to heavily damaged junction areas.
Quantum-enhanced microscopes capable of probing classically inaccessible material properties have drawn increasing interest, but most proof-of-principle quantum microscopes have not surpassed classical limits. Here, we discuss the promise and obstacles associated with the use of quantum light with reduced noise (‘squeezed’ light) for quantum-enhanced atomic force microscopy, bioimaging, magneto-optical measurements, and Raman spectroscopy.
Here, electron correlation microscopy (ECM) is a way to measure structural relaxation times, τ, of liquids with nanometer-scale spatial resolution using coherent electron scattering equivalent of photon correlation spectroscopy. We have applied ECM with a 3.5 nm diameter probe to Pt 57.5 Cu 14.7 Ni 5.3 P 22.5 amorphous nanorods and Pd 40 Ni 40 P 20 bulk metallic glass (BMG) heated inside the STEM into the supercooled liquid region. These data demonstrate that the ECM technique is limited by the characteristics of the time series, which must be at least 40τ to obtain a well-converged correlation function g 2 (t), and the time per frame, which must be less than 0.1τ to obtain sufficient sampling. A high-speed direct electron camera enables fast acquisition and affords reliable g 2 (t) data even with low signal per frame.
Critical applications of spin polarized low energy electron microscopy (SPLEEM) employ this technique's vector imaging capability to resolve domain wall (DW) spin textures. Studying several thin film systems including Co/W(110), Co/Cu(001) and (Co/Ni) n /W(110), we demonstrate that an additional contrast can appear at magnetic DWs. By imaging the magnetization as a function of electron landing energy, electron energies are selected at which the magnetic domain contrast vanishes. Surprisingly, under such conditions of zero contrast between magnetic domains, we observe the appearance of magnetic contrast outlining the DWs. This DW contrast fails to depend on the DW spin texture. Instead, our measurements show that this DW contrast results from a combination of the energy-dependence of the spin reflectivity asymmetry of the magnetic film, the finite energy width of the spin polarized electron source, and the dispersion of the magnetic prism array that separates the illumination and imaging columns of the instrument. Awareness of this DW contrast mechanism is useful to aid correct interpretation of SPLEEM images.
High resolution electron backscatter diffraction (HREBSD), an SEM-based diffraction technique, may be used to measure the lattice distortion of a crystalline material and to infer the geometrically necessary dislocation content. Uncertainty in the image correlation process used to compare diffraction patterns leads to an uneven distribution of measurement noise in terms of the lattice distortion, which results in erroneous identification of dislocation type and density. This work presents a method of reducing noise in HREBSD dislocation measurements by removing the effect of the most problematic components of the measured distortion. The method is then validated by comparing with TEM analysis of dislocation pile-ups near a twin boundary in austenitic stainless steel and with ECCI analysis near a nano-indentation on a tantalum oligocrystal. Finally, the HREBSD dislocation microscopy technique is able to resolve individual dislocations visible in TEM and ECCI and correctly identify their Burgers vectors.
The development of four-dimensional (4D) scanning transmission electron microscopy (STEM) using fast detectors has opened-up new avenues for addressing some of longstanding challenges in electron imaging. One of these challenges is how to image severely distorted crystal lattices, such as at a dislocation core. Here we develop a new 4D-STEM technique, called Cepstral STEM, for imaging disordered crystals using electron diffuse scattering. In contrast to analysis based on Bragg diffraction, which measures the average and periodic scattering potential, electron diffuse scattering can detect fluctuations caused by crystal disorder. Local fluctuations of diffuse scattering are captured by scanning electron nanodiffraction (SEND) using a coherent probe. The harmonic signals in electron diffuse scattering are detected through Cepstral analysis and used for imaging. By integrating Cepstral analysis with 4D-STEM, we demonstrate that information about the distortive part of electron scattering potential can be separated and imaged at nm spatial resolution. Here, we apply the technique to the analysis of a dislocation core in SiGe and lattice distortions in a high entropy alloy.
Scanning transmission electron microscopy (STEM) has become the technique of choice for quantitative characterization of atomic structure of materials, where the minute displacements of atomic columns from high-symmetry positions can be used to map strain, polarization, octahedra tilts, and other physical and chemical order parameter fields. The latter can be used as inputs into mesoscopic and atomistic models, providing insight into the correlative relationships and generative physics of materials on the atomic level. However, these quantitative applications of STEM necessitate understanding the microscope induced image distortions and developing the pathways to compensate them both as part of a rapid calibration procedure for in situ imaging, and the post-experimental data analysis stage. Here, we explore the spatiotemporal structure of the microscopic distortions in STEM using multivariate analysis of the atomic trajectories in the image stacks. Based on the behavior of principal component analysis (PCA), we develop the Gaussian process (GP)-based regression method for quantification of the distortion function. The limitations of such an approach and possible strategies for implementation as a part of in-line data acquisition in STEM are discussed. Here, the analysis workflow is summarized in a Jupyter notebook that can be used to retrace the analysis and analyze the reader's data.
Four-dimensional scanning transmission electron microscopy (4D-STEM) is a versatile analytical tool for characterizing materials structural properties. However, extending such analysis to disordered materials is challenging, especially in technologically important samples with mixed ordered and disordered phases. Here, in this work, we present a new 4D-STEM method, called fluctuation cepstral STEM (FC-STEM), based on the fluctuation analysis of cepstral transform of diffraction patterns. The peaks in the associated transformation relate to inter-atomic distances in a thin sample. By varying the real-space range over which fluctuations are calculated, distinct ordered and disordered phases can be mapped in a diffractive image reconstruction. We demonstrate the principles of FC-STEM by characterizing a silicon anode, harvested from a cycled lithium-ion battery. A mixture of amorphous and nanocrystalline silicon, graphitic carbon, and electrolyte by-products is identified and mapped. Comparisons with conventional electron imaging and energy-dispersive X-ray spectroscopy show that FC-STEM is highly effective for the structure determination of mixed-phase amorphous materials.
The sensitivity and the precision of the Geometric Phase Analysis (GPA) method for strain characterization is a topic widely discussed in the literature and is usually difficult to quantify. Indeed, the GPA precision is intricately linked to the resolution of the strain maps defined when masking the periodic reflections in Fourier space. In this study an additional parameter, sampling, is proposed to be analyzed regarding the precision of GPA by developing the concept of a phase noise in the GPA equations. Both experimentally and theoretically, the following article demonstrates how the precision, and the sensitivity of the GPA method is improved when using a larger pixel spacing to record an electron micrograph in Scanning Transmission Electron Microscopy (STEM). In conclusion, the counterintuitive concept of increasing the field of view to improve the GPA precision results in an extension of the application of strain characterization methods in STEM towards low deformation levels.
Under illumination by a 300 keV electron beam, oxygen vacancy ordering structures are induced within cerium oxide grains. Here, our high-resolution transmission electron microscopy (HRTEM) study, supported by image simulation, reveals the evolution of these structures as vacancy concentration increases. The observed fluorite-type superlattice structures are identified as CeO 1.825 , CeO 1.75 , Ce 2 O 3 , displaying a gradient in oxygen vacancy concentration moving away from the grain surface. Correspondingly, the structural sequence transitions from Ce 2 O 3 to CeO 1.75 and then to CeO 1.825 . Without the constraints of surrounding grains, fluorite-type Ce 2 O 3 nanocrystals show a preference for transformation into an A-type trigonal structure. Notably, at temperatures up to 200°C, only the perfect fluorite structure is observed. Structural models were validated through both [110] and [001] projections. Our findings further confirm lattice expansion associated with local oxygen vacancy enrichment, which can be compensated by the formation of stacking faults, where a {111} oxygen plane is lost at defect sites.
Cells adjust their adhesive and cytoskeletal organizations according to changes in the biochemical and physical nature of their surroundings. In return, by adhering and generating forces on the extracellular matrix (ECM) cells organize their microenvironment. Integrin-dependent focal adhesions (FAs) are the converging zones integrating biochemical and biomechanical signals arising from the ECM and the actin cytoskeleton. Thus, integrin-mediated adhesion and mechanotransduction, the conversion of mechanical forces into biochemical signals, are involved in critical cellular functions such as migration, proliferation and differentiation, and their deregulation contributes to pathologies including cancer. A challenging problem is to decipher how stochastic protein movements and interactions lead to formation of dynamic architecture such as integrin-dependent adhesive structures. In this review, we will describe recent advances made possible by super-resolution microscopies and single molecule tracking approaches that provided new understanding on the organization and the dynamics of integrins and intracellular regulators at the nanoscale in living cells.
Electron microscopy (EM)-based techniques are mostly responsible for our current view of cell morphology at the subcellular level and continue to play an essential role in biological research. In cells from the immune system, such as eosinophils, EM has helped to understand how cells package and release mediators involved in immune responses. Ultrastructural investigations of human eosinophils enabled visualization of secretory processes in detail and identification of a robust, vesicular trafficking essential for the secretion of immune mediators via a non-classical secretory pathway associated with secretory (specific) granules. This vesicular system is mainly organized as large tubular-vesicular carriers (Eosinophil Sombrero Vesicles – EoSVs) actively formed in response to cell activation and provides a sophisticated structural mechanism for delivery of granule-stored mediators. In this review, we highlight the application of EM techniques to recognize pools of immune mediators at vesicular compartments and to understand the complex secretory pathway within human eosinophils involved in inflammatory and allergic responses. - Highlights: • Application of EM to understand the complex secretory pathway in human eosinophils. • EM techniques reveal an active vesicular system associated with secretory granules. • Tubular vesicles are involved in the transport of granule-derived immune mediators.