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At least 451 records · Page 25
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Deterministic Fast Scrambling with Neutral Atom Arrays

Fast scramblers are dynamical quantum systems that produce many-body entanglement on a timescale that grows logarithmically with the system size N. Here, we propose and investigate a family of deterministic, fast scrambling quantum circuits realizable in near-term experiments with arrays of neutral atoms. We show that three experimental tools—nearest-neighbor Rydberg interactions, global single-qubit rotations, and shuffling operations facilitated by an auxiliary tweezer array—are sufficient to generate nonlocal interaction graphs capable of scrambling quantum information using only O(logN) parallel applications of nearest-neighbor gates. These tools enable direct experimental access to fast scrambling dynamics in a highly controlled and programmable way and can be harnessed to produce highly entangled states with varied applications.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2021

Defect-driven selective metal oxidation at atomic scale

Nanoscale materials modified by crystal defects exhibit significantly different behaviours upon chemical reactions such as oxidation, catalysis, lithiation and epitaxial growth. However, unveiling the exact defect-controlled reaction dynamics (e.g. oxidation) at atomic scale remains a challenge for applications. Here, using in situ high-resolution transmission electron microscopy and first-principles calculations, we reveal the dynamics of a general site-selective oxidation behaviour in nanotwinned silver and palladium driven by individual stacking-faults and twin boundaries. The coherent planar defects crossing the surface exhibit the highest oxygen binding energies, leading to preferential nucleation of oxides at these intersections. Planar-fault mediated diffusion of oxygen atoms is shown to catalyse subsequent layer-by-layer inward oxide growth via atomic steps migrating on the oxide-metal interface. These findings provide an atomistic visualization of the complex reaction dynamics controlled by planar defects in metallic nanostructures, which could enable the modification of physiochemical performances in nanomaterials through defect engineering.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Redox Mediated Control of Electrochemical Potential in Liquid Cell Electron Microscopy

Liquid cell electron microscopy enables the study of nanoscale transformations in solvents with high spatial and temporal resolution, but for the technique to achieve its potential requires a new level of control over the reactivity caused by radical generation under electron beam irradiation. An understanding of how to control electron-solvent interactions is needed to further advance the study of structural dynamics for complex materials at the nanoscale. Additionally, we developed an approach that scavenges radicals with redox species that form well-defined redox couples and control the electrochemical potential in situ . This approach enables the observation of electrochemical structural dynamics at near-atomic resolution with precise control of the liquid environment. Analysis of nanocrystal etching trajectories indicates that this approach can be generalized to several chemical systems. The ability to simultaneously observe heterogeneous reactions at near-atomic resolution and precisely control the electrochemical potential enables the fundamental study of complex nanoscale dynamics with unprecedented detail.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Ab initio and force field molecular dynamics study of bulk organophosphorus and organochlorine liquid structures

Here, we performed ab initio molecular dynamics (AIMD) simulations to benchmark bulk liquid structures and to evaluate results from all-atom force field molecular dynamics (FFMD) simulations with the generalized Amber force field (GAFF) for organophosphorus (OP) and organochlorine (OC) compounds. Our work also addresses the current and important topic of force field validation, applied here to a set of nonaqueous organic liquids. Our approach differs from standard treatments, which validate force fields based on thermodynamic data. Utilizing radial distribution functions (RDFs), our results show that GAFF reproduces the AIMD-predicted asymmetric liquid structures moderately well for OP compounds that contain bulky alkyl groups. Among the OCs, RDFs obtained from FFMD overlap well with AIMD results, with some offsets in position and peak structuring. However, re-parameterization of GAFF for some OCs is needed to reproduce fully the liquid structures predicted by AIMD. The offsets between AIMD and FFMD peak positions suggest inconsistencies in the developed force fields, but, in general, GAFF is able to capture short-ranged and long-ranged interactions of OPs and OCs observed in AIMD. Along with the local coordination structure, we also compared enthalpies of vaporization. Overall, calculated bulk properties from FFMD compared reasonably well with experimental values, suggesting that small improvements within the FF should focus on parameters that adjust the bulk liquid structures of these compounds.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Molecular Simulation of Covalent Bond Dynamics in Liquid Silicon

Many atomic liquids can form transient covalent bonds reminiscent of those in the corresponding solid states. These directional interactions dictate many important properties of the liquid state, necessitating a quantitative, atomic-scale understanding of bonding in these complex systems. A prototypical example is liquid silicon, wherein transient covalent bonds give rise to local tetrahedral order and consequent nontrivial effects on liquid-state thermodynamics and dynamics. To further understand covalent bonding in liquid silicon, and similar liquids, we present an ab initio-simulation-based approach for quantifying the structure and dynamics of covalent bonds in condensed phases. Through the examination of structural correlations among silicon nuclei and maximally localized Wannier function centers, we develop a geometric criterion for covalent bonds in liquid Si. We use this to monitor the dynamics of transient covalent bonding in the liquid state and estimate a covalent bond lifetime. We compare covalent bond dynamics to other processes in liquid Si and similar liquids and suggest experiments to measure the covalent bond lifetime.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

The symmetric quasi-classical model using on-the-fly time-dependent density functional theory within the Tamm–Dancoff approximation

The primary computational challenge when simulating nonadiabatic ab initio molecular dynamics is the unfavourable compute costs of electronic structure calculations with molecular size. Simple electronic structure theories, like time-dependent density functional theory within the Tamm–Dancoff approximation (TDDFT/TDA), alleviate this cost for moderately sized molecular systems simulated on realistic time scales. Although TDDFT/TDA does have some limitations in accuracy, an appealing feature is that, in addition to including electron correlation through the use of a density functional, the cost of calculating analytic nuclear gradients and nonadiabatic coupling vectors is often computationally feasible even for moderately sized basis sets. Here in this work, some of the benefits and limitations of TDDFT/TDA are discussed and analysed with regard to its applicability as a ‘back-end’ electronic structure method for the symmetric quasi-classical Meyer–Miller model (SQC/MM). In order to investigate the benefits and limitations of TDDFT/TDA, SQC/MM is employed to predict and analyse a prototypical example of excited-state hydrogen transfer in gas-phase malonaldehyde. Then, the ring-opening dynamics of selenophene are simulated, which highlight some of the deficiencies of TDDFT/TDA. Additionally, some new algorithms are proposed that speed up the calculation of analytic nuclear gradients and nonadiabatic coupling vectors for a set of excited electronic states.

molecular dynamics↗
NASA NTRSDate not supplied

Building and Breaking Carbon Composites with REACTER

Carbon composites have become indispensable for aerospace and other high-performance applications, and a detailed picture of their morphology and failure mechanisms remains difficult to obtain through experiment. REACTER is a versatile computational modeling tool for atomistic molecular dynamics designed to model chemical reactions at the speed and length scales of classical force fields.1 In this work, several recent features of REACTER were applied to the creation and subsequent mechanical testing of two classes of carbon composites, carbon-fiber reinforced polymers (CFRP) and carbon nanotube (CNT) composites. Carbon fiber core morphologies were created by the method of Desai et al.,2 but using the advanced reaction constraints framework of REACTER, their proposed multistep procedure was reduced to a single uninterrupted molecular dynamics simulation. The carbon fiber filler was embedded into a polymer matrix by simulated in situ polymerization of several thermosetting resins, including bismaleimide and polyarylacetylene, to obtain the final CFRP model. To generate the second class of carbon composite, CNT networks were grown dynamically using the new ‘create atoms’ feature of REACTER, and similarly infiltrated with resin to obtain CNT composites. The resulting models were compared directly to experiment using simulated high resolution transmission electron microscopy and x-ray diffraction. Failure mechanisms were elucidated by simulating mechanically induced bond breaking, as characterized by third-order DFT-based tight-binding (DFTB3) simulations, via a reaction constraint on the total potential energy of the involved atoms.

Molecular Dynamics↗
DOE OSTI2024

HydraGNN_Predictive_GFM_2024 - Ensemble of predictive graph foundation models for ground state atomistic materials modeling

We provide the ensemble of fifteen pre-trained graph foundation models (GFMs) for atomistic materials modeling applications. Each one of the fifteen GFMs has been trained on five open-source datasets that (once aggregated) amount to over 154 million atomistic structures, which cover over two-thirds of the natural elements of the periodic table and that comprises a broad set of organic and inorganic compounds. This vast set of atomistic structures comprises ground state configurations that are dynamically stable (i.e., equilibrated structures with atomic forces approximately close to zero values) as well as dynamically unstable structures (i.e., non-equilibrium structures with non-negligible non-zero values of atomic forces). The ensemble of datasets aggregated does NOT include excited states. The datasets have been curated to remove atomistic structures with spectral norm of the force tensor above 100 eV/angstrom. Moreover, a linear term of the energy was computed for each dataset using a linear regression model that uses the chemical concentration of each natural element as regressor. The linear term predicted by the linear regression model has been subtracted from each original energy value to perform a re-alignment of the energy values across different electronic structures approximation theories performed to generate the diverse multi-source, multi-fidelity datasets. The folder "ADIOS_files" contains the set of pre-processed datasets in Adaptable I/O System (ADIOS) format (https://www.exascaleproject.org/research-project/adios/) that have been used for the development and training of GFMs in this work. The "ADIOS_files" directory contains 6 sub-directories named as follows: - ANI1x-v3.bp - MPTrj-v3.bp - OC2020-20M-v3.bp - OC2020-v3.bp - OC2022-v3.bp - qm7x-v3.bp Each sub-directory contains the pre-processed datasets converted in Adaptable I/O System (ADIOS) format (https://www.exascaleproject.org/research-project/adios/) that have been used to the development, training, and performance testing of the ensemble go predictive graph foundation models. Each GFM was developed using HydraGNN (https://github.com/ORNL/HydraGNN) as underlying graph neural network (GNN) architecture. The multi-task learning (MTL) capability of HydraGNN was used to simultaneously train the GFMs on labeled values for direct predictions of energy (a total system property of an atomistic structure that measures the chemical stability) and atomic forces (an atomic level property of an atomistic structure that measures the dynamical stability). The hyper parameters of the GFM have been tuned using scalable hyperparameter optimization (HPO) algorithms implemented in the software DeepHyper (https://github.com/deephyper/deephyper). The pre-training of each HPO trial was performed using distributed data parallelism (DDP) to scale the training across 128 compute nodes of the exascale OLCF supercomputer Frontier. Each HPO trial was trained only for 10 epochs and an early stopping was performed to avoid wasting significant computational resources on GNN architectures that were clearly underperforming. For each HPO trial, the 'omnistat' tool developed by (AMD Research - Advanced Micro Device) was used to measure the total energy consumption in kWh. The ensemble of GFMs was obtained by selecting the fifteen best performing HPO trials. Four models have been selected for their clear advantage in accuracy, and these are the GFMs with IDs 229, 156, 147, 260. Additional eleven models have been selected based on judicious balance between accuracy and energy consumption needed for training, and these are the GFMs with IDs 165, 78, 137, 1, 175, 171, 181, 67, 179, 167, 351. Each selected GFM of the ensemble was continued to cumulate a total of at most 30 epochs. In some cases, the total number of epochs actually performed was les than 30 due to two combined factors: (1) the size of the GFM (i.e., the number of model parameters to train) and (2) the total wall-clock time for which the computational resources could be allocated on OLCF-Frontier. The "Ensemble_of_models" directory contains 15 sub-directories named as follows: - gfm_0.229 - gfm_0.156 - gfm_0.147 - gfm_0.260 - gfm_0.165 - gfm_0.78 - gfm_0.137 - gfm_0.1 - gfm_0.175 - gfm_0.171 - gfm_0.181 - gfm_0.67 - gfm_0.179 - gfm_0.167 - gfm_0.351 Each one of these sub-directories refers to one of the fifteen HPO trials that have been selected to continue the pre-training with at most 30 epochs. With each sub-directory associated with a specific HPO trial, the following files can be found: - config.json: file for argument parsing to develop and train an HydraGNN architecture - gfm_0.ID_epoch_N.pk: file with model parameters for HPO ID trial after N epochs of training The ensemble of fifteen GFM architectures was used for (1) ensemble averaging to stabilize the predictions of energy and atomic forces after pre-training for post-processing analysis and (2) ensemble uncertainty quantification (UQ). The code used to develop, pre-train, and load the pre-trained models for post-processing analysis is available on the ORNL-GitHub at the following link: https://github.com/ORNL/HydraGNN/tree/Predictive_GFM_2024

36 MATERIALS SCIENCE↗
NASA NTRS1994

General properties of quantum optical systems in a strong field limit

We investigate the dynamics of an arbitrary atomic system (n-level atoms or many n-level atoms) interacting with a resonant quantized mode of an em field. If the initial field state is a coherent state with a large photon number then the system dynamics possesses some general features, independently of the particular structure of the atomic system. Namely, trapping states, factorization of the wave function, collapses and revivals of the atomic energy oscillations are discussed.

Chumakov, S. M.↗
DOE OSTI2020

Displacement of carbon atoms in few-layer graphene

Molecular dynamics simulations were performed to study the susceptibility of carbon atom displacement under electron irradiation. The mapping of threshold displacement energies at different recoiling directions showed that the energies are very sensitive to the layer configurations and positions of neighboring atoms. Carbon atoms on the top and the bottom layers of few-layer graphene are most vulnerable to irradiation damage due to lack of constraints from the neighboring graphene layers. As indirect experiment evidence, transmission electron microscopy was performed on the edge of folded few-layer graphene, which made it possible to reveal “the inside” and compare irradiation tolerance of atoms at different layers, by using an electron analysis beam for both displacement creation and in situ characterization.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2024

Oxidation of Silicon Carbide with Atomic Oxygen through the Passive-to-Active Transition

The inelastic and reactive scattering dynamics of O( 3 P) atoms on a 6H-silicon carbide (SiC) surface were investigated as a function of temperature with a molecular beam-surface scattering technique that employed a rotatable mass spectrometer detector. One set of experiments used a pulsed hyperthermal beam that produced ~8 km s –1 O atoms, and another set of experiments used a continuous beam that contained O atoms with a nominal velocity of ~2 km s –1 . When exposed to the relatively low-flux, pulsed hyperthermal O-atom beam, a passive oxide layer on the SiC that formed at lower temperatures decomposed as the temperature increased above 1673 K. Instead of entering an active oxidation regime, a graphitic layer formed on the surface and largely protected the underlying SiC from incoming O atoms. Investigation of the oxide decomposition without O-atom bombardment revealed volatile Si and SiO products at the moment that the oxide decomposed, implying that Si sublimation occurs concurrently with oxide decomposition. In the experiment with the continuous (higher flux) O-atom beam, volatile SiO and CO products were observed after the passive oxide decomposed, indicating that active oxidation was reached. Finally, the results of this study provide evidence for the importance of Si sublimation within the active oxidation regime. Above the passive-to-active transition temperature, Si sublimation is an ongoing process, and continuous active oxidation will only occur if sufficient oxygen reacts with the surface to produce SiO more quickly than a graphitic layer can form. Thus, accurate models of SiC ablation by atomic oxygen must account for multiple competing mechanisms that depend on the surface temperature and incident O-atom flux.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

A crossed molecular beams and computational study on the unusual reactivity of banana bonds of cyclopropane (c-C 3 H 6 ; X 1 A$^{'}_{1}$ ) through insertion by ground state carbon atoms (C( 3 P j ))

The mechanism and chemical dynamics of the reaction of ground electronic state atomic carbon C( 3 P j ) with cyclopropane c-C 3 H 6 (X 1 A$^{'}_{1}$) have been explored by combining crossed molecular beams experiments with electronic structure calculations of the pertinent triplet C 4 H 6 potential energy surface and statistical computations of product branching ratios under single-collision conditions. The experimental findings suggest that the reaction proceeds via indirect scattering dynamics through triplet C 4 H 6 reaction intermediate(s) leading to C 4 H 5 product(s) plus atomic hydrogen via a tight exit transition state, with the overall reaction exoergicity evaluated as 231 ± 52 kJ mol –1 . The calculations indicate that C( 3 P j ) can easily insert into one of the three equivalent C–C ‘banana’ bonds of cyclopropane overcoming a low barrier of only 2 kJ mol –1 following the formation of a van der Waals reactant complex stabilized by 15 kJ mol –1 . The carbon atom insertion into one of the six C–H bonds is also feasible via a slightly higher barrier of 5 kJ mol –1 . Here, these results highlight an unusual reactivity of cyclopropane's banana C–C bonds, which behave more like unsaturated C–C bonds with a π-character than saturated σ C–C bonds, which are known to be generally unreactive toward the ground electronic state atomic carbon such as in ethane (C 2 H 6 ). The statistical theory predicts the overall product branching ratios at the experimental collision energy as 50% for 1-butyn-4-yl, 33% for 1,3-butadien-2-yl, i-C 4 H 5 , and 11% for 1,3-butadien-1-yl, n-C 4 H 5 , with i-C 4 H 5 (230 kJ mol –1 below the reactants) favored by the C–C insertion providing the best match with the experimentally observed reaction exoergicity. The C( 3 P j ) + c-C 3 H 6 reaction is predicted to be a source of C 4 H 5 radicals under the conditions where its low entrance barriers can be overcome, such as in planetary atmospheres or in circumstellar envelopes but not in cold molecular clouds. Both i- and n-C 4 H 5 can further react with acetylene eventually producing the first aromatic ring and hence, the reaction of the atomic carbon with c-C 3 H 6 can be considered as an initial step toward the formation of benzene.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Machine learning molecular dynamics simulations toward exploration of high-temperature properties of nuclear fuel materials: case study of thorium dioxide

Predicting materials properties of nuclear fuel compounds is a challenging task in materials science. Their thermodynamical behaviors around and above the operational temperature are essential for the design of nuclear reactors. However, they are not easy to measure, because the target temperature range is too high to perform various standard experiments safely and accurately. Moreover, theoretical methods such as first-principles calculations also suffer from the computational limitations in calculating thermodynamical properties due to their high calculation-costs and complicated electronic structures stemming from f-orbital occupations of valence electrons in actinide elements. Here, we demonstrate, for the first time, machine-learning molecular-dynamics to theoretically explore high-temperature thermodynamical properties of a nuclear fuel material, thorium dioxide. The target compound satisfies first-principles calculation accuracy because f-electron occupation coincidentally diminishes and the scheme meets sampling sufficiency because it works at the computational cost of classical molecular-dynamics levels. We prepare a set of training data using first-principles molecular dynamics with small number of atoms, which cannot directly evaluate thermodynamical properties but captures essential atomistic dynamics at the high temperature range. Then, we construct a machine-learning molecular-dynamics potential and carry out large-scale molecular-dynamics calculations. Consequently, we successfully access two kinds of thermodynamic phase transitions, namely the melting and the anomalous λ transition induced by large diffusions of oxygen atoms. Furthermore, we quantitatively reproduce various experimental data in the best agreement manner by selecting a density functional scheme known as SCAN. Our results suggest that the present scale-up simulation-scheme using machine-learning techniques opens up a new pathway on theoretical studies of not only nuclear fuel compounds, but also a variety of similar materials that contain both heavy and light elements, like thorium dioxide.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2024

Probing Basal and Prismatic Planes of Graphitic Materials for Metal Single Atom and Subnanometer Cluster Stabilization

Abstract Supported metal single atom catalysis is a dynamic research area in catalysis science combining the advantages of homogeneous and heterogeneous catalysis. Understanding the interactions between metal single atoms and the support constitutes a challenge facing the development of such catalysts, since these interactions are essential in optimizing the catalytic performance. For conventional carbon supports, two types of surfaces can contribute to single atom stabilization: the basal planes and the prismatic surface; both of which can be decorated by defects and surface oxygen groups. To date, most studies on carbon‐supported single atom catalysts focused on nitrogen‐doped carbons, which, unlike classic carbon materials, have a fairly well‐defined chemical environment. Herein we report the synthesis, characterization and modeling of rhodium single atom catalysts supported on carbon materials presenting distinct concentrations of surface oxygen groups and basal/prismatic surface area. The influence of these parameters on the speciation of the Rh species, their coordination and ultimately on their catalytic performance in hydrogenation and hydroformylation reactions is analyzed. The results obtained show that catalysis itself is an interesting tool for the fine characterization of these materials, for which the detection of small quantities of metal clusters remains a challenge, even when combining several cutting‐edge analytical methods.

Vidal, Mathieu↗
DOE OSTI2020

Dimer rattling mode induced low thermal conductivity in an excellent acoustic conductor

A solid with larger sound speeds usually exhibits higher lattice thermal conductivity. Here, we report an exception that CuP2 has a quite large mean sound speed of 4155 m s –1 , comparable to GaAs, but single crystals show very low lattice thermal conductivity of about 4 W m –1 K –1 at room temperature, one order of magnitude smaller than GaAs. To understand such a puzzling thermal transport behavior, we have thoroughly investigated the atomic structures and lattice dynamics by combining neutron scattering techniques with first-principles simulations. This compound crystallizes in a layered structure where Cu atoms forming dimers are sandwiched in between P atomic networks. In this work, we reveal that Cu atomic dimers vibrate as a rattling mode with frequency around 11 meV, which is manifested to be remarkably anharmonic and strongly scatters acoustic phonons to achieve the low lattice thermal conductivity.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Spinon mediation of witness spin dynamics in herbertsmithite

The kagome lattice of spin-1/2 copper atoms in herbertsmithite is conjectured to sustain a quantum spin liquid state with spinon quasiparticles. Ideally, the kagome crystal planes are each separated by a plane of spinless zinc atoms. However, in real crystals, some spin-1/2 copper atoms substitute randomly onto these inter-kagome zinc sites. Here we reconceptualize such ‘impurity’ atoms as quantum witness spins whose dynamics is designed to probe the spin liquid state. We then introduce spin noise spectroscopy to measure the frequency and temperature dependence of witness spin dynamics, demonstrating that their phenomenology is consistent with extensive interactions between witness spins mediated by propagation of spinons through a quantum spin liquid. Ultimately, a sharp transition occurs at around 260 mK, below which the properties of both spin noise and magnetic susceptibility suggest that the witness spins form a spin glass phase. Among the theoretical models considered, we demonstrate that our observations are only consistent with spinon-mediated interactions between witness spins by either a Z 2 or U(1) quantum spin liquid, with the former model more closely matching the data. Our work demonstrates that quantum mechanical witness spins may now conceivably be used as a widely applicable probe of quantum spin liquid physics.

Takahashi, Hiroto [University of Oxford (United Ki↗
DOE OSTI2024

Effects of Nonequilibrium Atomic Structure on Ionic Diffusivity in LLZO: A Classical and Machine Learning Molecular Dynamics Study

To improve the performance of electrochemical devices, it is essential to understand the effects of nonequilibrium motifs in solids, such as grain boundaries, amorphous phases, and highly strained regions, on atomic-scale transport and stability. Molecular dynamics simulations are used to explore the combined effect of far-from-equilibrium atomic structures and the choice of interatomic potential on ionic diffusivity predictions for Li 7 La 3 Zr 2 O 12 (LLZO), a promising solid electrolyte for all-solid-state batteries. Amorphization and high strain are considered using both classical Buckingham interatomic potentials and machine learning force fields. Here we find that both crystalline expansion and amorphization tend to slow diffusion, although the different physical encodings in the two potentials impact the properties in different ways. We trace these variations to a combination of structural and transport factors, the contributions of which are deconvoluted computationally. Graph-based analysis reveals that the variations for amorphous LLZO arise from the connectivity of diffusion pathways within the predicted structures, which generally correlates with diffusivity and is notably higher for structures generated by the machine learning force fields. Our study provides additional insight into the relationship between atomic structure and diffusivity in LLZO, while also highlighting the need for care in choosing and validating potentials to simulate far from equilibrium structures.

25 ENERGY STORAGE↗
DOE OSTI2020

Atomic Resolution Imaging of Light Elements in a Crystalline Environment using Dynamic Hollow-Cone Illumination Transmission Electron Microscopy

Multiple electron scattering and the nonintuitive nature of image formation with coherent radiation complicate the interpretation of conventional transmission electron microscopy images. Precession of the illuminating beam in transmission electron microscopy (TEM) can lead to more robust and interpretable images with some penalty to image contrast, a technique known as dynamic hollow-cone illumination TEM. Here, we demonstrate direct and robust imaging of light and heavy atoms in a crystalline environment with this technique. This method is similar to the annular bright-field technique in scanning transmission electron microscopy, via the principle of reciprocity. Dynamic hollow-cone illumination TEM is challenging in practice due to sensitivity to the misalignment of the precession axis, microscope objective aperture, and crystal zone axis.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗