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At least 253 records · Page 14

Quantifying System Strength From Grid-Forming Resources Using Frequency Scan Approach: Preprint

Current industry practices for quantifying the system strength contribution from grid-forming (GFM) resources to ensure stability of power systems dominated by inverter-based resources (IBRs) are primarily based on iterative electromagnetic transient (EMT) time-domain simulation studies. While feasible, these approaches are resource-intensive, lack scalability and intuition, and might not evaluate the system strength contribution over the entire frequency range of interest. This paper introduces a novel, frequency-domain approach to quantify system strength support provided by a GFM resource using frequency scans. The proposed method uses transfer functions from the grid voltage magnitude (V) and phase (?), respectively, to the reactive (Q) and active power (P) output of a GFM resource for quantifying its contribution to system strength. These transfer functions provide a direct measure of the ability of a GFM resource to behave as a stiff voltage source behind a reactance over a specified frequency range, enabling robust quantification of its system strength contribution. The key innovation of this work is the development of a frequency domain system strength metric called the dynamic short-circuit ratio (dSCR) that is suitable for IBR-dominated power systems and is directly related with the familiar short circuit ratio (SCR) metric. The new metric, dSCR, enables the assessment of system strength contributions from both synchronous machines and converter-based GFM resources using a unified benchmark, which is not possible with the traditional SCR metric. The paper also demonstrates how impedance scans could identify if an unstable condition observed during weak grid conditions is a result of the lack active or reactive power support or both. By leveraging the proposed frequency-domain dSCR metric for quantifying system strength contribution from GFM IBRs, the paper demonstrates targeted mitigation strategies for weak grid instabilities without resorting to repeated, time-consuming time-domain simulations. The result is a scalable and efficient approach to remediate stability challenges in power systems with high shares of IBRs and accelerating the integration of GFM technologies for system strength support in power systems.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Probing Activities of Individual Catalytic Nanoflakes by Tunneling Mode of Scanning Electrochemical Microscopy

The tunneling mode of scanning electrochemical microscopy (SECM) was developed recently and applied to studies of charge-transfer reactions at single metal nanoparticles (NPs). When an SECM tip is brought within the tunneling distance from a conductive NP, the particle begins to act as a part of the nanoelectrode. Herein, we demonstrate the possibility of using carbon nanoelectrodes with a very thin insulating sheath for electrochemical tunneling experiments at flat samples. In this way, electrocatalytic activity, conductivity, and charging properties of and faradaic processes in layered nanomaterials can be characterized by single-nanoflake voltammetry without making direct ohmic contact with them. A broad applicability of tunneling SECM experiments is demonstrated by probing nanomaterials with different size, geometry, and electrocatalytic properties, including metallic/pseudo-metallic (1T/1T') and semiconducting (2H) MoS 2 nanoflakes, N-doped porous carbon catalyst, and MXene nanosheets. Further, the Tafel plots for the hydrogen evolution reaction (HER) and oxygen evolution reaction (OER) at individual nanoflakes are compared to analogous measurements for an ensemble of flakes attached to the surface of a macroscopic electrode. Moreover, we observed variations in catalytic activities of individual MXene flakes toward HER and OER caused by non-uniform doping.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Revealing the Chemical Bonding in Adatom Arrays via Machine Learning of Hyperspectral Scanning Tunneling Spectroscopy Data

The adatom arrays on surfaces offer an ideal playground to explore the mechanisms of chemical bonding via changes in the local electronic tunneling spectra. While this information is readily available in hyperspectral scanning tunneling spectroscopy data, its analysis has been considerably impeded by a lack of suitable analytical tools. Here we develop a machine learning based workflow combining supervised feature identification in the spatial domain and unsupervised clustering in the energy domain to reveal the details of structure-dependent changes of the electronic structure in adatom arrays on the Co 3 Sn 2 S 2 cleaved surface. This approach, in combination with first-principles calculations, provides insight for using artificial neural networks to detect adatoms and classifies each based on their local neighborhood comprised of other adatoms. These structurally classified adatoms are further spectrally deconvolved. The unexpected inhomogeneity of electronic structures among adatoms in similar configurations is unveiled using this method, suggesting there is not a single atomic species of adatoms, but rather multiple types of adatoms on the Co 3 Sn 2 S 2 surface. This is further supported by a slight contrast difference in the images (or slight size variation) of the topography of the adatoms.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Fingerprints of composite fermion Lambda levels in scanning tunneling microscopy

A composite fermion (CF) is a topological quasiparticle that emerges from a nonperturbative attachment of vortices to electrons in strongly correlated two-dimensional materials. Similar to noninteracting fermions that form Landau levels in a magnetic field, CFs can fill analogous “Lambda” levels, giving rise to the fractional quantum Hall (FQH) effect of electrons. Here, we show that Lambda levels can be directly visualized through the characteristic peak structure in the signal obtained via spectroscopy with scanning tunneling microscopy (STM) on a FQH state. Complementary to transport, which probes the low-energy properties of CFs, we show that high-energy features in STM spectra can be interpreted in terms of Lambda levels. We numerically demonstrate that STM spectra can be accurately modeled using Jain's CF theory. Our results show that STM provides a powerful tool for revealing the anatomy of FQH states and identifying physics beyond the noninteracting CF paradigm.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Detecting Symmetry Breaking in Magic Angle Graphene Using Scanning Tunneling Microscopy

A growing body of experimental work suggests that magic angle twisted bilayer graphene exhibits a "cascade" of spontaneous symmetry-breaking transitions, sparking interest in the potential relationship between symmetry breaking and superconductivity. However, it has proven difficult to find experimental probes which can unambiguously identify the nature of the symmetry breaking. Here, we show how atomically resolved scanning tunneling microscopy can be used as a fingerprint of symmetry-breaking order. Further, by analyzing the pattern of sublattice polarization and "Kekulé" distortions in small magnetic fields, order parameters for each of the most competitive symmetry-breaking states can be identified. In particular, we show that the "Kramers intervalley coherent state," which theoretical work predicts to be the ground state at even integer fillings, shows a Kekulé distortion which emerges only in a magnetic field.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Cathode Electrolyte Diagnostics Based on Scanning Probe Microscopy

Various processes lead to degradation of cathodes in lithium-ion batteries. Questions remain regarding mechanisms of many of these processes. Probe microscopy methods including scanning electrochemical microscopy (SECM) are capable of directly probing processes at the cathode/electrolyte interface. SECM uses a small electrode to perform rapid electrochemical analysis of transient species generated at an active cathode/electrolyte interface. This paper discusses the background of the SECM instrument and its application to lithium-ion battery research. We also describe the application of SECM methods to the study of cathode degradation processes observed in lithium-ion batteries. Specifically, we focus on characterizing the dissolution of manganese from LiMn2O4 (LMO) based on recent debate in the literature. We describe experiments to observe and characterize the electrochemical properties of manganese complexes emerging from degrading LMO electrode materials.

cathode/electrolyte interface↗

Basal Plane Hydrogen Evolution Activity from Mixed Metal Nitride MXenes Measured by Scanning Electrochemical Microscopy

2D early transition metal carbide and nitride MXenes have intriguing properties for electrochemical energy storage and electrocatalysis. These properties can be manipulated by modifying the basal plane chemistry. Here, mixed transition metal nitride MXenes, M-Ti 4 N 3 T x (M = V, Cr, Mo, or Mn; T x = O and/or OH), are developed by modifying pristine exfoliated Ti 4 N 3 T x MXene with V, Cr, Mo, and Mn salts using a simple solution-based method. The resulting mixed transition metal nitride MXenes contain 6–51% metal loading (cf. Ti) that exhibit rich electrochemistry including highly tunable hydrogen evolution reaction (HER) electrocatalytic activity in a 0.5 m H 2 SO 4 electrolyte as follows: V-Ti 4 N 3 T x > Cr-Ti 4 N 3 T x > Mo-Ti 4 N 3 T x > Mn-Ti 4 N 3 T x > pristine Ti 4 N 3 T x with overpotentials as low as 330 mV at -10 mA cm -2 with a charge-transfer resistance of 70 O. Scanning electrochemical microscopy (SECM) reveals the electrochemical activity of individual MXene flakes. The SECM data corroborate the bulk HER activity trend for M-Ti 4 N 3 T x as well as provide the first experimental evidence that HER results from catalysis on the MXene basal plane. These electrocatalytic results demonstrate a new pathway to tune the electrochemical properties of MXenes for water splitting and related electrochemical applications.

2D materials↗

Ionic Liquid-Mediated Scanning Probe Electro-Oxidative Lithography as a Novel Tool for Engineering Functional Oxide Micro- and Nano-Architectures

Functional oxides have extensively been investigated as a promising class of materials in a broad range of innovative applications. Harnessing the novel properties of functional oxides in micro- to nano-scale applications hinges on establishing advanced fabrication and manufacturing techniques able to synthesize these materials in an accurate and reliable manner. Oxidative scanning probe lithography (o-SPL), an atomic force microscopy (AFM) technique based on anodic oxidation at the water meniscus formed at the tip/substrate contact, not only combines the advantages of both “top-down” and “bottom-up” fabrication approaches, but also offers the possibility of fabricating oxide nanomaterials with high patterning accuracy. While the use of self-assembled monolayers (SAMs) broadened the application of o-SPL, significant challenges have emerged owing to the relatively limited number of SAM/solid surface combinations that can be employed for o-SPL, which constrains the ability to control the chemistry and structure of oxides formed by o-SPL. Here, in this work, a new o-SPL technique that utilizes room-temperature ionic liquids (RTILs) as the functionalizing material to mediate the electrochemistry at AFM tip/substrate contacts is reported. The results show that the new IL-mediated o-SPL (IL-o-SPL) approach allows sub-100 nm oxide features to be patterned on a model solid surface, namely steel, with an initiation voltage as low as -2 V. Moreover, this approach enables high tunability of both the chemical state and morphology of the patterned iron oxide structures. Owing to the high chemical compatibility of ILs, which derives from the possibility of synthesizing ILs able to adsorb on a wide variety of solid surfaces, IL-o-SPL can be extended to other material surfaces and provide the opportunity to accurately tailor the chemistry, morphology, and electronic properties within nanoscale domains, thus opening new pathways to the development of novel micro- and nano-architectures for advanced integrated devices.

36 MATERIALS SCIENCE↗

Learning and Controlling Silicon Dopant Transitions in Graphene Using Scanning Transmission Electron Microscopy

A machine learning approach is introduced to determine the transition dynamics of silicon atoms on a single layer of carbon atoms, when stimulated by the electron beam of a scanning transmission electron microscope (STEM). This method is data-centric, leveraging data collected on a STEM. The data samples are processed and filtered to produce symbolic representations, which is used to train a neural network to predict transition probabilities. These learned transition dynamics are then leveraged to guide a single silicon atom throughout the lattice to pre-determined target destinations. Empirical analyses are presented that demonstrate the efficacy and generality of the approach.

36 MATERIALS SCIENCE↗

Physics Discovery in Nanoplasmonic Systems via Autonomous Experiments in Scanning Transmission Electron Microscopy

Abstract Physics‐driven discovery in an autonomous experiment has emerged as a dream application of machine learning in physical sciences. Here, this work develops and experimentally implements a deep kernel learning (DKL) workflow combining the correlative prediction of the target functional response and its uncertainty from the structure, and physics‐based selection of acquisition function, which autonomously guides the navigation of the image space. Compared to classical Bayesian optimization (BO) methods, this approach allows to capture the complex spatial features present in the images of realistic materials, and dynamically learn structure–property relationships. In combination with the flexible scalarizer function that allows to ascribe the degree of physical interest to predicted spectra, this enables physical discovery in automated experiment. Here, this approach is illustrated for nanoplasmonic studies of nanoparticles and experimentally implemented in a truly autonomous fashion for bulk‐ and edge plasmon discovery in MnPS 3 , a lesser‐known beam‐sensitive layered 2D material. This approach is universal, can be directly used as‐is with any specimen, and is expected to be applicable to any probe‐based microscopic techniques including other STEM modalities, scanning probe microscopies, chemical, and optical imaging.

42 ENGINEERING↗

Prediction of curing kinetics of resorcinol‐added resole phenolic resins using differential scanning calorimetry for the fabrication of carbon/carbon composites

Phenolic resins are commonly used as carbon precursors for the fabrication of carbon/carbon composites due to their high carbon yield and aromatic nature. To decrease curing times, acid catalysts are generally used, but the addition of resorcinol was found to have a similar effect while being incorporated into the resin matrix with no contamination or corrosion issues. In this work, the curing kinetics of pure, 10, 20, and 30 wt% resorcinol-added phenolic resins were investigated through differential scanning calorimetry. Heating rates of 0.5, 1, 2.5, and 5°C min -1 were used with several curing models to predict isothermal curing. Averaged mean absolute error (MAE) for the isoconversional mathematical approaches namely Kissinger–Akahira–Sunose (MAE = 12.9 min), Flynn–Wall–Ozawa (15.8 min), and Vyazovkin (14 min) show that these methods provide the best predictions, attributed to their adoption of an activation energy that depends on the extent of cure (E a (α)). The Kissinger method (MAE = 36 min), which depends only on peak temperature with a constant activation energy assumption, and the data noise sensitive Friedman model (MAE = 1144.7 min) provide the least accurate results. Thermogravimetric analysis revealed that resorcinol decreases the curing times by up to 71% without lowering carbon yield.

36 MATERIALS SCIENCE↗

Nanoscale properties of lead halide perovskites by scanning tunneling microscopy

Since the introduction of lead halide perovskites, tremendous progress has been made regarding their stability, reproducibility and durability. However, one of the issues that remains is related to the interfacial atomic structure arrangement and structure-property relationship under optical and electrical stimuli. In this critical review, we highlight the recent progress using scanning tunneling microscopy (STM) to understand the nanoscale properties and dynamic processes occurring in these halide perovskite materials. STM is known to be a very challenging technique, which is reflected by the low number of relevant publications in the last years. These initial reports mirror the unique potential of STM to give Ångstrom-scale insight into the (opto)-electronic properties, morphology and underlying electronic structure and provide a path toward harnessing the full potential of these materials. However, care must be taken to understand the effects of the perturbations caused by STM and tailor the measurement conditions accordingly.

36 MATERIALS SCIENCE↗

Electron Microscopy Transfer System to Protect Atmosphere‐Sensitive Materials for Scanning Electron Microscopy Characterization

Atmosphere- and/or moisture-sensitive materials can be challenging to characterize using electron microscopy techniques due to sample preparation workflows that generally require exposure to ambient conditions. Here, we describe a novel preparation method that uses aluminum foil in combination with a commercial cryo-EM transfer system to circumvent undesired exposure to the atmosphere. First, hygroscopic MgCl 2 was used as a model material, and prepared samples (both protected and unprotected) were placed in a controlled-humidity environment (> 80% relative humidity) for various exposure lengths (circa seconds to hours). Following this, the effectiveness of the sample preparation method was determined by comparing qualitative photos and quantitative X-ray diffraction patterns between the two sample subsets. The combined results of these experiments suggest that the outlined preparation method effectively protects MgCl 2 from atmospheric contamination compared to MgCl 2 samples that had no protective measures taken. Finally, the preparation method was utilized to protect a highly hygroscopic crystalline BaO thin film for characterization via scanning electron microscopy, thereby demonstrating a functional application of the outlined preparation technique and an additional use for the commercial cryo-EM transfer system beyond its intended application.

atmosphere-sensitive materials↗

Hollow Ptychography: Toward Simultaneous 4D Scanning Transmission Electron Microscopy and Electron Energy Loss Spectroscopy

With the recent development of high-acquisition-speed pixelated detectors, 4D scanning transmission electron microscopy (4D-STEM) is becoming routinely available in high-resolution electron microscopy. 4D-STEM acts as a “universal” method that provides local information on materials that is challenging to extract from bulk techniques. It extends conventional STEM imaging to include super-resolution techniques and to provide quantitative phase-based information, such as differential phase contrast, ptychography, or Bloch wave phase retrieval. However, an important missing factor is the chemical and bonding information provided by electron energy loss spectroscopy (EELS). 4D-STEM and EELS cannot currently be acquired simultaneously due to the overlapping geometry of the detectors. Here, the feasibility of modifying the detector geometry to overcome this challenge for bulk specimens is demonstrated, and the use of a partial or defective detector for ptycholgaphic structural imaging is explored. Here, results show that structural information beyond the diffraction-limit and chemical information from the material can be extracted together, resulting in simultaneous multi-modal measurements, adding the additional dimensions of spectral information to 4D datasets.

4D-scanning transmitting electron microscopy (STEM↗

A Machine Learning Approach to Quantitative Analysis of Enamel Microstructure from Scanning Electron Microscopy Images

Dental enamel, the outermost tissue of mammalian teeth, must withstand a lifetime of wear and cyclic contact. To meet this demand, enamel possesses a combination of high hardness and resistance to fracture, properties that are typically mutually exclusive. The impressive damage tolerance has been attributed largely to decussation of the enamel rods, the principal unit of its microstructure. As such, enamel is inspiring the design of next‐generation structural materials. However, quantitative descriptions of the decussated enamel rod microstructure remain limited due to challenges encountered in applying computed tomography and in acquiring quality images appropriate for traditional digital processing methods. Here, a machine learning segmentation method is applied to images of the enamel obtained using scanning electron microscopy to support quantitative analysis of the microstructure. A pretrained convolutional neural network is used to expand the input training image dataset to allow the training of a random forest classifier, which ultimately segments the image with a very small training set ( n = 3 images). A validation of this segmentation method is presented, in addition to its application to calculate relevant microstructural parameters for images of tooth enamel from selected mammalian species. The methodology applied here is equally applicable to other hard tissues.

36 MATERIALS SCIENCE↗

High-Resolution Imaging of Cellulose Organization in Cell Walls by Field Emission Scanning Electron Microscopy

Field emission scanning electron microscopy (FESEM) is a powerful tool for analyzing surface structures of biological and nonbiological samples. However, when it is used to study fine structures of nanometer-sized microfibrils of epidermal cell walls, one often encounters tremendous challenges to acquire clear and undistorted images because of two major issues: (1) Preparation of samples suitable for high resolution imaging; due to the delicateness of some plant materials, such as onion epidermal cell walls, many things can happen during sample processing, which subsequently result in damaged samples or introduce artifacts. (2) Difficulties to acquire clear images of samples which are electron-beam sensitive and prone to charging artifacts at magnifications over 100,000×. In this chapter we described detailed procedures for sample preparation and conditions for high-resolution FESEM imaging of onion epidermal cell walls. Lastly, the methods can be readily adapted for other wall materials.

59 BASIC BIOLOGICAL SCIENCES↗

Scanning tunneling microscope tip-induced formation of Bi bilayers on Bi 2 Te 3

We report the formation of Bi(111) bilayer islands and crater structures on Bi 2 Te 3 (111) surfaces induced by voltage pulses from a scanning tunneling microscope tip. Pulses above a threshold voltage (+3 V) produce craters ∼0.5μm in diameter, similar to the size of the tip. Redeposited material self-assembles into a network of atomically ordered islands with a lattice constant identical to the underlying Bi2Te3 surface. The island size monotonically decreases over several micrometers from the pulse site, until the pristine Bi 2 Te 3 surface is recovered. We assign these islands to Bi bilayer based on atomic resolution images, analysis of step heights, and tunneling spectroscopy. Here, the dependence of bilayer formation on bias polarity and the evidence for defect diffusion together suggest a mechanism driven by the interplay of field evaporation and tunneling-current-induced Joule heating.

Bi bilayer↗

Probing individual single atom electrocatalyst sites by advanced analytical scanning transmission electron microscopy

Single atom electrocatalysts (SAEs) are promising next-generation materials for promoting a variety of important reactions, such as the oxygen reduction, nitrogen reduction, and CO 2 reduction reactions. While bulk characterization techniques such as X-ray absorption spectroscopy and Mössbauer spectroscopy have significantly enhanced our understanding of these catalysts, direct probing of individual single metal atom sites at the atomic scale is necessary to understand local variations in the properties of these sites and accelerate design and synthesis of improved SAEs. Aberration-corrected scanning transmission electron microscopy (STEM) has become a powerful tool for providing this type of atomic-scale information about SAE metal sites. These sites are typically unstable under the electron beam, however, which, in combination with conventional acquisition methods and detectors, has limited the type and quantity of information obtainable by spectroscopic STEM techniques. Here, we map multiple individual SAE metal sites in a nitrogen-doped carbon containing atomically dispersed Fe and Re (FeReNC) at the atomic scale by direct electron detection electron energy-loss spectroscopy (EELS). Direct electron detection provides an improved signal-to-noise ratio over conventional scintillator-based detectors and enables detection and real space localization of weak signals. In addition, we demonstrate an automated method for identification of metal atom positions, placement of the probe on these sites, and simultaneous EELS and energy dispersive X-ray spectroscopic (EDS) signal acquisition. This simultaneous acquisition of EELS and EDS provides access to the composition and bonding of a wide range of SAE metal sites. In this study, focusing the probe directly on the metal sites also increases the relevant data acquisition rate by more than an order of magnitude over two-dimensional mapping, enabling improved statistical measurements of site properties. The versatility, sensitivity, and speed that these techniques provide enhances our ability to probe the local elemental and chemical environment of a large number of individual SAE metal site structures at the atomic scale, enabling an improved understanding of the variations in the local properties of these electrocatalysts to be gained. As a result, significantly increased information about individual metal sites will be available to future electrochemical studies through these techniques, accelerating the development of advanced SAEs.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗