Probing Ultralow Energy Excitations at Ultrahigh Spatial Resolution with Monochromated Electron Energy Loss Spectroscopy
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Hachtel, Jordan↗
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Velocity map imaging apparatus for studying electron transfer and plasma initiation with low-energy electrons
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Smoll, Eric James↗
Electron energy loss spectroscopy database synthesis and automation of core-loss edge recognition by deep-learning neural networks
Abstract The ionization edges encoded in the electron energy loss spectroscopy (EELS) spectra enable advanced material analysis including composition analyses and elemental quantifications. The development of the parallel EELS instrument and fast, sensitive detectors have greatly improved the acquisition speed of EELS spectra. However, the traditional way of core-loss edge recognition is experience based and human labor dependent, which limits the processing speed. So far, the low signal–noise ratio and the low jump ratio of the core-loss edges on the raw EELS spectra have been challenging for the automation of edge recognition. In this work, a convolutional-bidirectional long short-term memory neural network (CNN-BiLSTM) is proposed to automate the detection and elemental identification of core-loss edges from raw spectra. An EELS spectral database is synthesized by using our forward model to assist in the training and validation of the neural network. To make the synthesized spectra resemble the real spectra, we collected a large library of experimentally acquired EELS core edges. In synthesize the training library, the edges are modeled by fitting the multi-Gaussian model to the real edges from experiments, and the noise and instrumental imperfectness are simulated and added. The well-trained CNN-BiLSTM network is tested against both the simulated spectra and real spectra collected from experiments. The high accuracy of the network, 94.9%, proves that, without complicated preprocessing of the raw spectra, the proposed CNN-BiLSTM network achieves the automation of core-loss edge recognition for EELS spectra with high accuracy.
36 MATERIALS SCIENCE↗
Atomic-Scale Behavior of Radiation-Resistant ZnO under High-Energy Electron Bombardment
Understanding the atomic structure and defect characteristics of ZnO thin films is crucial for optimizing their electronic properties and performance in advanced applications. Here, we investigate the atomic structure and defect characteristics of atomic layer deposition (ALD)-grown ZnO thin films by using aberration-corrected scanning transmission electron microscopy (STEM). Atomic-resolution imaging identifies prevalent stacking faults, dipole disorder, and various grain boundary types, which are believed to influence the electronic properties of ZnO. Additionally, real-time electron beam exposure experiments demonstrate structural transformations, including crystal growth and surface rearrangements. These findings provide insights into the growth mechanisms of ALD ZnO under high-energy electron irradiation conditions, an important finding for the use of polycrystalline ZnO wide bandgap semiconductors in space-like conditions. In conclusion, our results underscore the capability of STEM in directly visualizing and quantifying atomic-scale defects and beam-induced transformations in radiation-resistant ZnO.
Defects↗
Bypassing the Energy Functional in Density Functional Theory: Direct Calculation of Electronic Energies from Conditional Probability Densities
Density functional calculations can fail for want of an accurate exchange-correlation approximation. The energy can instead be extracted from a sequence of density functional calculations of conditional probabilities (CP DFT). Simple CP approximations yield usefully accurate results for two-electron ions, the hydrogen dimer, and the uniform gas at all temperatures. CP DFT has no self-interaction error for one electron, and correctly dissociates H2, both major challenges. For warm dense matter, classical CP DFT calculations can overcome the convergence problems of Kohn-Sham DFT.
75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
Demonstration of transmission high energy electron microscopy
Charged particle radiography with 800 MeV protons has been used for decades at LANL and developed around the world to study dynamic material properties. Recently, charged particle radiography has been demonstrated with the use of high-energy electrons. Because of the difference in the mass of the electron compared to the mass of the proton, the radiographic processes are substantially different and well suited to the study of fast dynamic processes in relatively thin systems. This presentation will show the layout required for such measurements, along with data collected from this recent demonstration performed with 14 GeV electrons generated at the SLAC National Accelerator Laboratory. The radiographic performance for flash measurements will be presented, along with the limitations of this measurement technique.
Merrill, F. E.↗
Differentiating the bonding states in calcium carbonate polymorphs by low-loss electron-energy-loss spectroscopy
Calcium carbonate is one of the important building components in organisms, especially the two most common polymorphs, calcite and aragonite. Here, to understand the difference in bonding state, the two polymorphs are characterized by valence (low-loss) electron energy loss spectroscopy. It is found that the difference in Ca M 23 edge originating from 3p to 3d states is consistent with the change of Ca-O bonds in the two studied polymorphs. Surprisingly, the measured Ca M 23 edge is in qualitative agreement with the calculated partial density of states (PDOS) of Ca-d states in contrast to their L edges (from 2p to 3d states) which are strongly influenced by atomic multiplet effect (spin-orbit coupling). This is because the atomic multiplet effect is much reduced for the Ca 3p orbital, which permits the corresponding Ca M 23 edge to be compared with the PDOS results. Our findings show insights that PDOS can potentially be used to interpret the M 23 edge of lighter 3d transition metals such as scandium, titanium, vanadium and chromium when such interpretation may not be achieved for their L edges.
36 MATERIALS SCIENCE↗
Charges on a suspended silicon nitride membrane under a high-energy electron beam
Thin silicon nitride (SiN x ) membranes are widely used in gas and liquid phase transmission electron microscopy (TEM) and as phase plates to enhance imaging contrast. SiN x contains trap sites for both positive and negative charges, which can be manipulated by high-energy electron irradiation, external potential biasing, or light exposure. Charge accumulation on the membrane can significantly affect in situ TEM processes, including chemical and electrochemical reactions, nanoparticle dynamics, and catalytic activity, or introduce unwanted phase shifts when used as a phase plate. Here, in this study, charge accumulation on suspended SiN x membranes was investigated using off-axis electron holography combined with model-free charge analysis, supported by custom finite element analysis (FEA) simulations. An average residual positive charge density of approximately 2.8 × 10 −4 C m −2 was measured. Localized and stable regions of both positive and negative charges were identified on the membrane. The global positive and localized positive/negative charges give rise to strong electric fields and electroosmotic slip velocities at the membrane surface, which are sufficient to induce non-Brownian particle behavior and directional fluid flow, offering a physical explanation for previously observed anomalies in particle dynamics, nucleation, and growth during gas and liquid phase TEM experiments. These results provide a benchmark for understanding charge behavior at SiNx interfaces in gas and liquid phase TEM. Furthermore, the FEA simulations establish a framework for future investigations into charge distribution, electrostatic potentials, and electrical double layers at solid–liquid interfaces, particularly in complex geometries and chemically dynamic environments.
Suspended silicon↗
Investigating the FLASH Effect in a Rat Brain Organotypic Model With a Novel High-Energy Electron Beam
Ultrahigh dose rate (FLASH) radiation therapy is reported to reduce normal tissue toxicity while maintaining tumor control; however, mechanism(s) remain obscure. To study FLASH mechanisms in brain tissue, we developed a novel experimental platform featuring a specialized high-energy electron linear accelerator, High Intensity Gamma Ray Source (HIGS), paired with an organotypic ex vivo brain metastasis model. We varied interpulse spacing to modulate the mean dose rate (MDR) of our unique 35 MeV electron beam, while maintaining extremely high instantaneous dose rate (IDR). We characterized dosimetry and targeting accuracy of the FLASH beam with film dosimetry. We combined this FLASH beam with an organotypic rat brain slice/breast carcinoma coculture model of brain metastasis to assess effects on normal and neoplastic tissues. Live-cell and bioluminescence imaging demonstrated cancer cell growth effects, whereas normal tissue responses and immune activation were assessed using live-cell imaging, cytokine profiles, and confocal microscopy. Here, we performed comparison experiments with 20 MeV electrons from a Varian clinical linear accelerator (VCLA) using conventional dose rates. The highest IDR of the FLASH beam to date was 20.7 ± 0.6 MGy/s, with maximum MDR of 20.7 MGy/s delivered in 1 pulse of 1 µs duration. Beam targeting was accurate to <1 mm and reproducible. HIGS-FLASH and VCLA dose rates equivalently decreased cancer cell growth. HIGS-FLASH irradiation significantly increased tumor necrosis factor α and fractalkine levels and confocal microscopy revealed distinct changes in microglial morphology slices suggesting microglia activation. Our novel experimental platform produces extremely high dose rates and rapid normal/neoplastic tissue readouts for mechanistic research into the effects of FLASH radiation in the brain. HIGS-FLASH irradiation induces comparable cancer cell growth inhibition but differential effects on cytokines and microglial morphology, suggesting that acute innate immune responses may be involved in FLASH normal tissue effects in the brain.
Kay, Tyler V. [Duke University, Durham, NC (United↗
KamLAND’s search for correlated low-energy electron antineutrinos with astrophysical neutrinos from IceCube
In this work, we report the results of a search for MeV-scale astrophysical neutrinos in KamLAND presented as an excess in the number of coincident neutrino interactions associated with the publicly available high-energy neutrino datasets from the IceCube Neutrino Observatory. We find no statistically significant excess in the number of observed low-energy electron antineutrinos in KamLAND, given a coincidence time window of ±500 s, ±1,000 s, ±3,600 s, and ±10,000 s around each of the IceCube neutrinos. We use this observation to present limits from 1.8 MeV to 100 MeV on the electron antineutrino fluence, assuming a mono-energetic flux. We then compare the results to several astrophysical measurements performed by IceCube and place a limit at the 90% confidence level on the electron antineutrino isotropic thermal luminosity from the TXS 0506+056 blazar.
79 ASTRONOMY AND ASTROPHYSICS↗
Forecasting of in situ electron energy loss spectroscopy
Abstract Forecasting models are a central part of many control systems, where high-consequence decisions must be made on long latency control variables. These models are particularly relevant for emerging artificial intelligence (AI)-guided instrumentation, in which prescriptive knowledge is needed to guide autonomous decision-making. Here we describe the implementation of a long short-term memory model (LSTM) for forecasting in situ electron energy loss spectroscopy (EELS) data, one of the richest analytical probes of materials and chemical systems. We describe key considerations for data collection, preprocessing, training, validation, and benchmarking, showing how this approach can yield powerful predictive insight into order-disorder phase transitions. Finally, we comment on how such a model may integrate with emerging AI-guided instrumentation for powerful high-speed experimentation.
36 MATERIALS SCIENCE↗
Deep Learning with Reflection High-Energy Electron Diffraction Images to Predict Cation Ratio in Sr 2 x Ti 2(1– x ) O 3 Thin Films
Machine learning (ML) with in-situ diagnostics offers a transformative approach to accelerate, understand, and control thin film synthesis by uncovering relationships between synthesis conditions and material properties. In this study, we demonstrate the application of deep learning to predict the stoichiometry of Sr 2x Ti 2(1–x) O 3 thin films using reflection high-energy electron diffraction images acquired during pulsed laser deposition. A gated convolutional neural network trained for regression of the Sr atomic fraction achieved accurate predictions with a small dataset of 31 samples. Explainable AI techniques revealed a previously unknown correlation between diffraction streak features and cation stoichiometry in Sr 2x Ti 2(1–x) O 3 thin films. Here, our results demonstrate how ML can be used to transform a ubiquitous in-situ diagnostic tool, that is usually limited to qualitative assessments, into a quantitative surrogate measurement of continuously valued thin film properties. Such methods are critically needed to enable real-time control, autonomous workflows, and accelerate traditional synthesis approaches.
77 NANOSCIENCE AND NANOTECHNOLOGY↗
Collisionless ion-electron energy exchange in magnetized shocks
Energy partition between ions and electrons in collisionless shocks has been a long-standing unsolved fundamental physical question. Here, we show that kinetic simulations of moderate Alfv´enic Mach number, magnetized, collisionless shocks reveal rapid, faster-than-Coulomb, energy exchange between ions and electrons when the plasma is sufficiently magnetized. Using kinetic and multi-fluid models with counter-streaming ions, we identify resonances between electron whistler and ion magnetohydrodynamic waves that account for this rapid energy exchange.
High-energy-density plasmas↗
Combining molecular beam epitaxy and low-energy electron microscopy with in situ magnetic susceptibility measurements within an integrated ultrahigh vacuum system
Quantum two-dimensional materials, including ultrathin superconducting films, are of great current research interest. These films are typically fabricated under ultra-high vacuum (UHV) conditions and are sensitive to the environment—prone to oxidation and contamination when exposed to the atmosphere. This hampers the study of their intrinsic properties by standard ex situ techniques. Here, we present a variable-temperature mutual inductance probe system integrated under UHV with molecular beam epitaxy (MBE) synthesis and low-energy electron microscopy, enabling nondestructive in situ characterization of superconducting thin films. The system employs a reflection-type configuration and reaches a low temperature (∼4 K) using a high-cooling-power, vibration-isolated cryocooler. In conclusion, we demonstrate the system performance by measuring the superconducting critical temperature in a copper-oxide thin film.
2D materials↗
Modeling the energetic tail of a dusty plasma's electron energy distribution and its effect on dust grain charge and behavior
A model for a weakly ionized dusty plasma is proposed in which UV or x-ray radiation continuously creates free electrons at high energy, which then cool through collisions with a cold neutral gas before recombining. The transition of a free electron from high energy at birth to low energy at demise implies that the electron energy distribution is not the simple Maxwellian of an isolated system in thermal equilibrium, but instead has a high-energy tail that depends on the recombination time. This tail can have a major effect on dust grain charging because the flux of tail electrons can be substantial even if the density of tail electrons is small. Detailed analytic and numerical calculations of dust grain charging show that situations exist in which a small high-energy tail dominates charge behavior. This implies that dust grain charge in terrestrial and space dusty plasmas may be significantly underestimated if a Maxwellian distribution is assumed and the non-thermal dynamics are neglected.
Physics↗
Revealing Phase Heterogeneity in Vertically Aligned Nanocomposites via Plan-View Electron Energy Loss Spectroscopy
Hydrogen utilization in clean energy technologies is challenged by limited storage and transport within materials, owing to the complex hydrogen kinetics at interfaces [1]. Understanding these interfacial mechanisms at the nanoscale is crucial for developing improved materials for hydrogen applications, particularly proton-conducting fuel cells (PCFCs). Vertically aligned nanocomposites (VANs) grown by pulsed laser deposition (PLD) offer a unique platform for investigating the interfacial effects on hydrogen transport due to their well-defined interfaces parallel to the direction of charge transport [2-4]. To investigate hydrogen transport, the two phases within the VANs were chosen as BaZr 0.9 Y 0.1 O 3-x (BZY), a known proton conductor, and Pr 0.1 Ce 0.9 O 2-x (PCO), a mixed ionic-electronic conductor [5]. This PCO-BZY VANs architecture allows the investigation of how the interface between a proton conductor and a mixed conductor influences hydrogen transport. However, because of the small size of hydrogen, it is difficult to discern the nature of its interactions with interfaces from bulk measurements at the macroscale, thus necessitating nanoscale measurements [6]. Electron energy loss spectroscopy (EELS) allows for nanometer-resolution probing of the local atomic structure and chemistry at the BZY/PCO interface. In this study, plan-view analysis of PCO-BZY VANs films was employed to characterize the structure and phase distribution of the VANs and investigate the interface between the nanostructures. The films were imaged using scanning electron microscopy (SEM) in the Hitachi S-4800 SEM, collecting secondary electron images using mixed upper and lower detectors. Then, plan-view transmission electron microscopy (TEM) and scanning transmission electron microscopy (STEM) EELS were employed using a JEOL ARM300 microscope operated at 300kV with a Gatan K3 GIF Continuum detector to study the distribution of the BZY and PCO phases through the film. As a result, spectrum images were acquired at a dispersion of 0.18eV per channel and denoised afterward by principal component analysis (PCA) method.
Griffin, Elizabeth [Northwestern University, Evans↗
Identifying Spectral Descriptors for Protonation in BaZr 0.8 Y 0.2 O 3-x with Electron Energy Loss Spectroscopy
Hydrogen economy is of paramount importance in the global transition to a sustainable, clean energy source that contributes to decarbonization efforts. In particular, the proton conducting proton ceramic fuel cells (PCFCs) play a crucial role in promoting hydrogen energy technology [1-5]. In a PCFC, the electrolyte is typically a solid oxide material that enables proton transport and can operate at temperatures lower than those of traditional oxygen ion conducting fuel cells [6]. The reduced operating temperature of PCFCs contributes to their durability, scalability, and efficiency [7,8]. BaZr 0.8 Y 0.2 O 3-x (BZY) is a promising proton conducting solid oxide electrolyte [9,10]. The emphasis on proton conductivity entails the importance of understanding proton content in the system. However, previous studies have largely relied on bulk techniques such as electrochemical impedance spectroscopy [7,11], Karl-Fischer titration [12,13], and thermogravimetric analysis [14] to obtain proton concentration. This is due to the small atomic size and light mass of hydrogen species making direct detection challenging. Bulk methods may be useful in estimating the proton content; however, it overlooks possible proton concentration gradient or segregation that may occur across or within a nanoparticle, especially when proton incorporation occurs nonuniformly through steam exposure on powder samples. In this paper, BZY is protonated at an estimated 0.15 mol of protons via steam exposure. Electron energy loss spectroscopy (EELS) with nanoscale spatial resolution is explored to identify proxy signals for proton detection using a JEOL ARM300 microscope operated at 300 kV with a Gatan GIF Continuum detector.
08 HYDROGEN↗
Basic factors for acquiring, correcting, and interpreting probe current-voltage characteristic in moderate-collisional plasma for determining electron energy distribution
Methods for inferring the electron distribution function (EDF) from a probe current–voltage trace are reviewed for moderate-collisional plasma. The explicit accounting of particle collisions, modeling sheath depletion, and electron refilling processes are rarely performed when analyzing probe measurements, yet they are critical for regime validity, EDF-profile accuracy, and space potential quantification precision. Furthermore, the advantages, limitations, and utilization of large-area wall probes in moderate-collisional plasma, capable of highly resolved indications of energetic electrons in plasma, are outlined.
70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗