Subnanometer Scale Mapping of Hydrogen Doping in Vanadium Dioxide

Hydrogen donor doping of correlated electron systems such as vanadium dioxide (VO2) profoundly modifies the ground state properties. The electrical behavior of HxVO2 is strongly dependent on the hydrogen concentration; hence, atomic scale control of the doping process is necessary. It is however a nontrivial problem to quantitatively probe the hydrogen distribution in a solid matrix. As hydrogen transfers its sole electron to the material, the ionization mechanism is suppressed. In this study, a methodology mapping the doping distribution at subnanometer length scale is demonstrated across a HxVO2 thin film focusing on the oxygen-hydrogen bonds using electron energy loss spectroscopy (EELS) coupled with first-principles EELS calculations. The hydrogen distribution was revealed to be nonuniform along the growth direction and between different VO2 grains, calling for intricate hydrogenation mechanisms. Our study points to a powerful approach to quantitatively map dopant distribution in quantum materials relevant to energy and information sciences.

Relation between sampling, sensitivity and precision in strain mapping using the Geometric Phase Analysis method in Scanning Transmission Electron Microscopy

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). The counterintuitive concept of increasing the field of view to improve the GPA precision results is an extension of the application of strain characterization methods in STEM towards low deformation levels.

Characterization of transverse electron pulse trains using RF powered traveling wave metallic comb striplines

Advancements in ultrafast electron microscopy have allowed elucidation of spatially selective structural dynamics. However, as the spatial resolution and imaging capabilities have made progress, quantitative characterization of the electron pulse trains has not been reported at the same rate. In fact, inexperienced users have difficulty replicating the technique because only a few dedicated microscopes have been characterized thoroughly. Systems replacing laser driven photoexcitation with electrically driven deflectors especially suffer from a lack of quantified characterization because of the limited quantity. The primary advantages to electrically driven systems are broader frequency ranges, ease of use and simple synchronization to electrical pumping. Here, we characterize the technical parameters for electrically driven UEM including the shape, size and duration of the electron pulses using low and high frequency chopping methods. At high frequencies, pulses are generated by sweeping the electron beam across a chopping aperture. For low frequencies, the beam is continuously forced off the optic axis by a DC potential, then momentarily aligned by a countering pulse. Using both methods, we present examples that measure probe durations of 2 ns and 10 ps for the low and high frequency techniques, respectively. We also discuss how the implementation of a pulsed probe affects STEM imaging conditions by adjusting the first condenser lens.

Selective area doping for Mott neuromorphic electronics

The cointegration of artificial neuronal and synaptic devices with homotypic materials and structures can greatly simplify the fabrication of neuromorphic hardware. We demonstrate experimental realization of vanadium dioxide (VO₂) artificial neurons and synapses on the same substrate through selective area carrier doping. By locally configuring pairs of catalytic and inert electrodes that enable nanoscale control over carrier density, volatility or nonvolatility can be appropriately assigned to each two-terminal Mott memory device per lithographic design, and both neuron- and synapse-like devices are successfully integrated on a single chip. Feedforward excitation and inhibition neural motifs are demonstrated at hardware level, followed by simulation of network-level handwritten digit and fashion product recognition tasks with experimental characteristics. Spatially selective electron doping opens up previously unidentified avenues for integration of emerging correlated semiconductors in electronic device technologies.

Defect free strain relaxation of microcrystals on mesoporous patterned silicon

A perfectly compliant substrate would allow the monolithic integration of high-quality semiconductor materials such as Ge and III-V on Silicon (Si) substrate, enabling novel functionalities on the well-established low-cost Si technology platform. Here, we demonstrate a compliant Si substrate allowing defect-free epitaxial growth of lattice mismatched materials. The method is based on the deep patterning of the Si substrate to form micrometer-scale pillars and subsequent electrochemical porosification. The investigation of the epitaxial Ge crystalline quality by X-ray diffraction, transmission electron microscopy and etch-pits counting demonstrates the full elastic relaxation of defect-free microcrystals. The achievement of dislocation free heteroepitaxy relies on the interplay between elastic deformation of the porous micropillars, set under stress by the lattice mismatch between Ge and Si, and on the diffusion of Ge into the mesoporous patterned substrate attenuating the mismatch strain at the Ge/Si interface.

Many complex devices rely on epitaxial growth with high crystallinity and accurate composition. Here authors report epitaxial growth of Ge on deep etched porous Si pillars to provide a fully compliant substrate enabling elastic relaxation of defect free Ge microcrystals.

Alignment-invariant signal reality reconstruction in hyperspectral imaging using a deep convolutional neural network architecture

The energy resolution in hyperspectral imaging techniques has always been an important matter in data interpretation. In many cases, spectral information is distorted by elements such as instruments' broad optical transfer function, and electronic high frequency noises. In the past decades, advances in artificial intelligence methods have provided robust tools to better study sophisticated system artifacts in spectral data and take steps towards removing these artifacts from the experimentally obtained data. This study evaluates the capability of a recently developed deep convolutional neural network script, EELSpecNet, in restoring the reality of a spectral data. The particular strength of the deep neural networks is to remove multiple instrumental artifacts such as random energy jitters of the source, signal convolution by the optical transfer function and high frequency noise at once using a single training data set. Here, EELSpecNet performance in reducing noise, and restoring the original reality of the spectra is evaluated for near zero-loss electron energy loss spectroscopy signals in Scanning Transmission Electron Microscopy. EELSpecNet demonstrates to be more efficient and more robust than the currently widely used Bayesian statistical method, even in harsh conditions (e.g. high signal broadening, intense high frequency noise).

Crystal lattice image reconstruction from Moiré sampling scanning transmission electron microscopy

A wide range of reconstruction methods exist nowadays to retrieve data from their undersampled acquisition schemes. In the context of Scanning Transmission Electron Microscopy (STEM), compressed sensing methods successfully demonstrated the ability to retrieve crystalline lattice images from undersampled electron micrographs. In this manuscript, an alternative method is proposed based on the principles of Moiré sampling by intentionally generating aliasing artifacts and correcting them afterwards. The interference between the scanning grid of the electron beam raster and the crystalline lattice results in the formation of predictable sets of Moiré fringes (STEM Moiré hologram). Since the aliasing artifacts are simple spatial frequency shifts applied on each crystalline reflection, the crystal lattices can be recovered from the STEM Moiré hologram by reverting the aliasing frequency shifts from the Moiré reflections. Two methods are presented to determine the aliasing shifts for all the resolved crystalline reflections. The first approach is a prior knowledge-based method using information on the spatial frequency distribution of the crystal lattices (a common case in practice). The other option is a multiple sampling approach using different sampling parameters and does not require any prior knowledge. As an example, the Moiré sampling recovery method detailed in this manuscript is applied to retrieve the crystalline lattices from a STEM Moiré hologram recorded on a silicon sample. The great interest of STEM Moiré interferometry is to increase the field of view (FOV) of the electron micrograph (up to several microns). The Moiré sampling recovery method extends the application of the STEM imaging of crystalline materials towards low magnifications.

Assessment of the strain depth sensitivity of Moiré sampling Scanning Transmission Electron Microscopy Geometrical Phase Analysis through a comparison with Dark-Field Electron Holography

In this study, the Moiré sampling Scanning Transmission Electron Microscopy Geometrical Phase Analysis (or STEM Moiré GPA) strain characterization method is compared to the well-established Dark-Field Electron Holography technique on a thin film stack grown by Molecular Beam Epitaxy. While experimental data obtained with the two techniques are, overall, in good qualitative agreement, small statistically relevant differences are locally observed between the two methods. The results obtained from both techniques are further confronted with Finite Element Method (FEM) mechanical simulations modeling the strain relaxation phenomena from a thin lamella. The FEM simulation highlights a non-uniform deformation field along the beam propagation direction with a higher deformation level near the surface of the lamella compared to the center of the same lamella. The center-surface strain differences obtained from modeling are consistent with the experimentally derived differences accounting for the fact that the SMG method is sensitive to the strain state of the surface of the lamella with a very narrow depth-of-field, and the DFEH technique is measuring the strain state of the center of the same lamella averaging over a large section of the thickness. The depth-of-field difference between both methods can be reasonably related to their respective contrast mechanisms (STEM vs Conventional Transmission Electron Microscopy). As the SMG method is using a convergent probe, the narrow depth-of-field might be used to sense the deformation field over different sections of the lamella using the defocus and potentially retrieve the three-dimensional strain field.

Selective area epitaxy of AlGaN nanowire arrays across nearly the entire compositional range for deep ultraviolet photonics

Semiconductor light sources operating in the ultraviolet (UV)-C band (100-280 nm) are in demand for a broad range of applications but suffer from extremely low efficiency. AlGaN nanowire photonic crystals promise to break the efficiency bottleneck of deep UV photonics. We report, for the first time, site-controlled epitaxy of AlGaN nanowire arrays with Al incorporation controllably varied across nearly the entire compositional range. It is also observed that an Al-rich AlGaN shell structure is spontaneously formed, significantly suppressing nonradiative surface recombination. An internal quantum efficiency up to 45% was measured at room-temperature. We have further demonstrated large area AlGaN nanowire LEDs operating in the UV-C band on sapphire substrate, which exhibit excellent optical and electrical performance, including a small turn-on voltage of ~4.4 V and an output power of ~0.93 W/cm² at a current density of 252 A/cm². The controlled synthesis of AlGaN subwavelength nanostructures with well-defined size, spacing, and spatial arrangement and tunable emission opens up new opportunities for developing high efficiency LEDs and lasers and promises to break the efficiency bottleneck of deep UV photonics.