Bayesian inference of atomic column positions in scanning transmission electron microscopy images.

Atomic-resolution scanning transmission electron microscopy combined with 2D Gaussian fitting enables the accurate and precise identification of atomic column positions within a few picometers. The measurement performance significantly depends on the signal-to-noise ratio of the atomic columns. In areas with low signal-to-noise ratios, such as near surfaces, the measurement performance was lower than that of the bulk. However, previous studies evaluated the accuracy and precision only in bulk areas, underscoring the need for a method that quantitatively evaluates the accuracy and precision of each atomic column position with various signal-to-noise ratios. This study introduced Bayesian inference to assess the accuracy and precision of determining individual atomic column positions under various signals. We applied this method to simulated and experimental images and demonstrated its effectiveness in identifying statistically significant displacements, particularly near surfaces with signal degradation. The use of vector maps and kernel density estimate plots obtained from Bayesian inference provided a probabilistic understanding of the atom displacement. Therefore, this study highlighted the potential benefits of Bayesian inference in high-resolution imaging to reveal material properties.

Nonmagnetic framboid and associated iron nanoparticles with a space-weathered feature from asteroid Ryugu.

Extraterrestrial minerals on the surface of airless Solar System bodies undergo gradual alteration processes known as space weathering over long periods of time. The signatures of space weathering help us understand the phenomena occurring in the Solar System. However, meteorites rarely retain the signatures, making it impossible to study the space weathering processes precisely. Here, we examine samples retrieved from the asteroid Ryugu by the Hayabusa2 spacecraft and discover the presence of nonmagnetic framboids through electron holography measurements that can visualize magnetic flux. Magnetite particles, which normally provide a record of the nebular magnetic field, have lost their magnetic properties by reduction via a high-velocity (>5 km s-1) impact of a micrometeoroid with a diameter ranging from 2 to 20 µm after destruction of the parent body of Ryugu. Around these particles, thousands of metallic-iron nanoparticles with a vortex magnetic domain structure, which could have recorded a magnetic field in the impact event, are found. Through measuring the remanent magnetization of the iron nanoparticles, future studies are expected to elucidate the nature of the nebular/interplanetary magnetic fields after the termination of aqueous alteration in an asteroid.

Facilely Fabricated Zero-Bias Silicon-Based Plasmonic Photodetector in the Near-Infrared Region with a Schottky Barrier Properly Controlled by Nanoalloys.

Plasmonic Schottky devices have attracted considerable attention for use in practical applications based on photoelectric conversion, because they enable light to be harvested below the bandgap of semiconductors. In particular, silicon-based (Si) plasmonic Schottky devices have great potential for useful photodetection in the near-infrared region. However, the internal quantum efficiency (IQE) values of previously reported devices are low because the Schottky barrier is excessively high. Here, we are the first to develop AuAg nanoalloy-n-type Si plasmonic Schottky devices by cathodic arc plasma deposition. Interestingly, it is found that a novel nanostructure, which leads to the improvement of responsivities, is formed. Moreover, these plasmonic nanostructures can be fabricated in only ∼1 min. The fabricated AuAg nanoparticle-film structure enables proper control of the Schottky barrier height and increases the area of the Schottky interface for electron transfer. As a result, the considerably enhanced IQE of our device at a telecommunication wavelength of 1310 nm (1550 nm) without external bias is 4.6 (6.5) times higher than those in previous reports, and these responsivities are a record high. This approach can be applied to realize efficient photodetection in the NIR region and extend the use of light below the bandgap of semiconductors. This paves the way for future application advancements in a variety of fields, including photodetection, imaging, photovoltaics, and photochemistry.

Visualization of nanoscale magnetic domain states in the asteroid Ryugu.

In the samples collected from the asteroid Ryugu, magnetite displays natural remanent magnetization due to nebular magnetic field, whereas contemporaneously grown iron sulfide does not display stable remanent magnetization. To clarify this counterintuitive feature, we observed their nanoscale magnetic domain structures using electron holography and found that framboidal magnetites have an external magnetic field of 300 A m-1, similar to the bulk value, and its magnetic stability was enhanced by interactions with neighboring magnetites, permitting a disk magnetic field to be recorded. Micrometer-sized pyrrhotite showed a multidomain magnetic structure that was unable to retain natural remanent magnetization over a long time due to short relaxation time of magnetic-domain-wall movement, whereas submicron-sized sulfides formed a nonmagnetic phase. These results show that both magnetite and sulfide could have formed simultaneously during the aqueous alteration in the parent body of the asteroid Ryugu.

Enhancing performance of electron holography with mathematical and machine learning-based denoising techniques.

Electron holography is a useful tool for analyzing functional properties, such as electromagnetic fields and strains of materials and devices. The performance of electron holography is limited by the 'shot noise' inherent in electron micrographs (holograms), which are composed of a finite number of electrons. A promising approach for addressing this issue is to use mathematical and machine learning-based image-processing techniques for hologram denoising. With the advancement of information science, denoising methods have become capable of extracting signals that are completely buried in noise, and they are being applied to electron microscopy, including electron holography. However, these advanced denoising methods are complex and have many parameters to be tuned; therefore, it is necessary to understand their principles in depth and use them carefully. Herein, we present an overview of the principles and usage of sparse coding, the wavelet hidden Markov model and tensor decomposition, which have been applied to electron holography. We also present evaluation results for the denoising performance of these methods obtained through their application to simulated and experimentally recorded holograms. Our analysis, review and comparison of the methods clarify the impact of denoising on electron holography research.

Low-dose measurement of electric potential distribution in organic light-emitting diode by phase-shifting electron holography with 3D tensor decomposition.

To improve the performance of organic light-emitting diodes (OLEDs), it is essential to understand and control the electric potential in the organic semiconductor layers. Electron holography (EH) is a powerful technique for visualizing the potential distribution with a transmission electron microscope. However, it has a serious issue that high-energy electrons may damage the organic layers, meaning that a low-dose EH is required. Here, we used a machine learning technique, three-dimensional (3D) tensor decomposition, to denoise electron interference patterns (holograms) of bilayer OLEDs composed of N,N'-di-[(1-naphthyl)-N,N'-diphenyl]-(1,1'-biphenyl)-4,4'-diamine (α-NPD) and tris-(8-hydroxyquinoline)aluminum (Alq3), acquired under a low-dose rate of 130 e- nm-2 s-1. The effect of denoising on the phase images reconstructed from the holograms was evaluated in terms of both the phase measurement error and the peak signal-to-noise ratio. We achieved a precision equivalent to that of a conventional measurement that had an exposure time 60 times longer. The electric field within the Alq3 layer decreased as the cumulative dose increased, which indicates that the Alq3 layer was degraded by the electron irradiation. On the basis of the degradation of the electric field, we concluded that the tolerance dose without damaging the OLED sample is about 1.7 × 105 e- nm-2, which is about 0.6 times that of the conventional EH. The combination of EH and 3D tensor decomposition denoising is capable of making a time series measurement of an OLED sample without any effect from the electron irradiation.

Impact of early mobilization on the duration of delirium in elderly hospitalized patients: A retrospective cohort pilot study.

Development of delirium during hospitalization impairs the activities of daily living in elderly hospitalized patients. In clinical practice, early mobilization from bed is recommended to reduce delirium incidence and hospitalization stay. However, the effects of early mobilization on elderly inpatients with delirium have not been established yet. The aim of this study was to investigate the association between early mobilization and the duration of delirium in elderly inpatients with delirium. This retrospective cohort pilot study examined 45 participants (23 males, 22 females; mean age: 84.5 ±â€…6.6 years), who developed delirium during hospitalization. Of the participants, 28 were surgically treated and 17 were non-surgically treated. We classified early or delayed mobilization based on the median number of days until the start of mobilization and compared after propensity score matching to adjust for baseline characteristics. Additionally, we examined the correlation between the number of days until the start of mobilization and the duration of delirium. The duration of delirium was significantly shorter in the early mobilization group, particularly in terms of sitting on the bed and wheelchair use than that in the delayed mobilization group {median: 4.0 [interquartile range (IQR): 2.0-6.0] vs 8.0 [IQR: 7.0-14.5] days, P = .013; median: 3.0 [IQR: 2.0-5.5] vs 11.0 [IQR: 7.5-14.5] days, P = .004, respectively}. Moreover, the duration of delirium significantly positively moderate correlated with the time until the start of sitting on the bed and wheelchair use (Spearman r = 0.527; P = .012, Spearman r = 0.630; P = .002, respectively). The results of this study suggest that early mobilization from sitting on the bed or wheelchair use after hospitalization or surgery may shorten the duration of delirium. Because the sample size of this pilot study is small, careful interpretation is needed, and further research is warranted.

Computational evaluation of sparse coding on off-axis electron holograms: comparison between charge-coupled device and direct-detection device cameras.

The effectiveness of sparse coding for image inpainting and denoising of off-axis electron holograms was examined computationally based on hologram simulations according to considerations of two types of electron detectors, namely charge-coupled device (CCD) and direct-detection device (DDD) cameras. In this simulation, we used a simple-phase object with a phase step such as a semiconductor p-n junction and assumed that the holograms recorded by the CCD camera include shot noise, dark-current noise and read-out noise, while those recorded by the DDD camera include only shot noise. Simulated holograms with various electron doses were sparsely coded. Even though interference fringes cannot be recognized in the simulated CCD and DDD holograms when subjected to electron doses (per pixel) equal to 1 and 0.01, respectively, both the corresponding sparse-coded holograms exhibit meaningful interference fringes. We demonstrate that a combination of the DDD camera and sparse coding reduces the requisite dose used to obtain holograms to values less than one-thousandth compared with the CCD camera without image postprocessing. This combination is expected to generate lower-dose and/or higher-speed electron holography.

Denoising of series electron holograms using tensor decomposition.

In this study, a noise-reduction technique for series low-dose electron holograms using tensor decomposition is demonstrated through simulation. We treated an entire dataset of the series holograms with Poisson noise as a third-order tensor, which is a stack of 2D holograms. The third-order tensor, which is decomposed into a core tensor and three factor matrices, is approximated as a lower-rank tensor using only noise-free principal components. This technique is applied to simulated holograms by assuming a p-n junction in a semiconductor sample. The peak signal-to-noise ratios of the holograms and the reconstructed phase maps have been improved significantly using tensor decomposition. Moreover, the proposed method was applied to a more practical situation of time-resolved in situ electron holography by considering a nonuniform fringe contrast and fringe drift relative to the sample. The accuracy and precision of the reconstructed phase maps were quantitatively evaluated to demonstrate its effectiveness for in situ experiments and low-dose experiments on beam-sensitive materials.

Phase-shifting electron holography for accurate measurement of potential distributions in organic and inorganic semiconductors.

Phase-shifting electron holography (PS-EH) is an interference transmission electron microscopy technique that accurately visualizes potential distributions in functional materials, such as semiconductors. In this paper, we briefly introduce the features of the PS-EH that overcome some of the issues facing the conventional EH based on Fourier transformation. Then, we present a high-precision PS-EH technique with multiple electron biprisms and a sample preparation technique using a cryo-focused-ion-beam, which are important techniques for the accurate phase measurement of semiconductors. We present several applications of PS-EH to demonstrate the potential in organic and inorganic semiconductors and then discuss the differences by comparing them with previous reports on the conventional EH. We show that in situ biasing PS-EH was able to observe not only electric potential distribution but also electric field and charge density at a GaAs p-n junction and clarify how local band structures, depletion layer widths and space charges changed depending on the biasing conditions. Moreover, the PS-EH clearly visualized the local potential distributions of two-dimensional electron gas layers formed at AlGaN/GaN interfaces with different Al compositions. We also report the results of our PS-EH application for organic electroluminescence multilayers and point out the significant potential changes in the layers. The proposed PS-EH enables more precise phase measurement compared to the conventional EH, and our findings introduced in this paper will contribute to the future research and development of high-performance semiconductor materials and devices.

Simulation-Trained Sparse Coding for High-Precision Phase Imaging in Low-Dose Electron Holography.

We broaden the applicability of sparse coding, a machine learning method, to low-dose electron holography by using simulated holograms for learning and validation processes. The holograms, with shot noise, are prepared to generate a model, or a dictionary, that includes basic features representing interference fringes. The dictionary is applied to sparse representations of other simulated holograms with various signal-to-noise ratios (SNRs). Results demonstrate that this approach successfully removes noise for holograms with an extremely small SNR of 0.10, and that the denoised holograms provide the accurate phase distribution. Furthermore, this study demonstrates that the dictionary learned from the simulated holograms can be applied to denoising of experimental holograms of a p-n junction specimen recorded with different exposure times. The results indicate that the simulation-trained sparse coding is suitable for use over a wide range of imaging conditions, in particular for observing electron beam-sensitive materials.

Quantitative electric field mapping of a p-n junction by DPC STEM.

Local electromagnetic fields in a specimen is measured at high spatial resolutions using differential phase contrast (DPC) imaging in scanning transmission electron microscopy (STEM). According to previous studies, DPC signals can be quantified by measuring the center of mass of the diffraction pattern intensity and/or performing a deconvolution method based on a phase contrast transfer function (PCTF). However, when using a segmented detector, the field strength has been considerably underestimated for a very thick specimen. The main cause of the underestimation is assumed to be inelastic scattering, mainly bulk plasmon scattering. In this study, we develop a method to remove this inelastic scattering effect from segmented detector DPC signals by modifying the PCTF deconvolution method. Field quantification results using this new technique are compared with those using pixelated detector DPC and electron holography, and all results indicated good agreement within an error margin.

Visualization of different carrier concentrations in n-type-GaN semiconductors by phase-shifting electron holography with multiple electron biprisms.

Phase-shifting electron holography (PS-EH) using a transmission electron microscope (TEM) was applied to visualize layers with different concentrations of carriers activated by Si (at dopant levels of 1019, 1018, 1017 and 1016 atoms cm-3) in n-type GaN semiconductors. To precisely measure the reconstructed phase profiles in the GaN sample, three electron biprisms were used to obtain a series of high-contrast holograms without Fresnel fringes generated by a biprism filament, and a cryo-focused-ion-beam (cryo-FIB) was used to prepare a uniform TEM sample with less distortion in the wide field of view. All layers in a 350-nm-thick TEM sample were distinguished with 1.8-nm spatial resolution and 0.02-rad phase-resolution, and variations of step width in the phase profile (corresponding to depletion width) at the interfaces between the layers were also measured. Thicknesses of the active and inactive layers at each dopant level were estimated from the observed phase profile and the simulation of theoretical band structure. Ratio of active-layer thickness to total thickness of the TEM sample significantly decreased as dopant concentration decreased; thus, a thicker TEM sample is necessary to visualize lower carrier concentrations; for example, to distinguish layers with dopant concentrations of 1016 and 1015 atoms cm-3. It was estimated that sample thickness must be more than 700 nm to make it be possible to detect sub-layers by the combination of PS-EH and cryo-FIB.

Sparse coding and dictionary learning for electron hologram denoising.

We demonstrate the effect of image denoising with sparse coding and dictionary learning algorithms for low-dose electron holography. Electron interference patterns (holograms) of a GaAs semiconductor specimen having a p-n junction were recorded with different exposure times (1, 4 and 40 s) and computer algorithms were applied to the holograms. The algorithms reduced the noise in the low-dose holograms successfully, with high data fidelity. In addition, the denoised holograms resulted in the phase images of a higher signal-to-noise ratio, fitting well to those obtained from original holograms recorded with sufficiently-long exposure times. The standard deviation in the reconstructed phase images was reduced by one digit using the denoising process. These results indicate that the sparse coding with dictionary learning algorithms are effective for electron holography and can potentially improve the temporal resolution by a factor of 40 or more without deterioration in the spatial resolution, thus enabling the observation of materials sensitive to electron beam irradiation and high-speed dynamical in situ electron holography.

Factors related to home discharge in malnourished community-dwelling older adults: A retrospective longitudinal cohort study.

Patients who become malnourished during hospitalization because of illness or treatment often receive intervention from a nutrition support team (NST). The NST intervention not only enhances the nutritional status but also decreases medical expenses and catheter-related complications. However, the impact of the NST intervention on the home discharge of hospitalized community-dwelling older adults remains unclear. Hence, this study aims to investigate factors related to home discharge in malnourished community-dwelling older adults.In this retrospective longitudinal cohort study, examined 191 community-dwelling older adults aged ≥65 years (108 males; mean age: 80.9 ±â€Š7.8 years) who received the NST intervention. All participants were categorized into two groups based on whether they were home discharged or not (home discharge group and non-home discharge group). We performed intergroup comparisons using serum albumin (Alb) as an index of the nutritional status and functional independence measure (FIM: motor and cognitive items) as an index of activities of daily living (ADL). Furthermore, we constructed a prognostic model of home discharge using the logistic regression analysis.The home discharge group had 94 participants, with a home discharge rate of 50.8%. Baseline body mass index (BMI), motor-FIM score, and cognitive-FIM score were significantly higher in the home discharge group compared with the non-home discharge group (P = .002, P < .001, P < .001, respectively). In the home discharge group, BMI declined significantly, Alb elevated significantly, and both motor-FIM and cognitive-FIM score enhanced significantly by the completion of the NST intervention (P < .001, P < .001, P < .001, P = .005, respectively). The adjusted logistic regression analysis extracted the baseline BMI (odds ratio [OR], 1.146; 95% confidence interval [CI]: 1.034-1.270), baseline motor-FIM score (OR, 1.070; 95% CI: 1.036-1.105), and extent of change in the motor-FIM score (OR, 1.061; 95% CI: 1.026-1.098) as independent factors that predict home discharge.This study highlights the significance of higher baseline BMI, higher baseline ADL level, ADL enhancements, and improvements in the nutritional status by the NST intervention in malnourished community-dwelling older adults considering home discharge.

Accurate measurement of electric potentials in biased GaAs compound semiconductors by phase-shifting electron holography.

The innate electric potentials in biased p- and n-type GaAs compound semiconductors and the built-in potential were successfully measured with high accuracy and precision by applying in situ phase-shifting electron holography to a wedge-shaped GaAs specimen. A cryo-focused-ion-beam system was used to prepare the 35°-wedge-shaped specimen with smooth surfaces for a precise measurement. The specimen was biased in a transmission electron microscope, and holograms with high-contrast interference fringes were recorded for the phase-shifting method. A clear phase image around the p-n junction was reconstructed even in a thick region (thickness of ~700 nm) at a spatial resolution of 1 nm and precision of 0.01 rad. The innate electric potentials of the unbiased p- and n-type layers were measured to be 12.96 ± 0.17 V and 14.43 ± 0.19 V, respectively. The built-in potential was determined to be 1.48 ± 0.02 V. In addition, the in situ biasing measurement revealed that the measured electric-potential difference between the p and n regions changed by an amount equal to the voltage applied to the specimen, which indicates that all of the external voltage was applied to the p-n junction and that no voltage loss occurred at the other regions.