49 research outputs found
Defect Detection in Atomic Resolution Transmission Electron Microscopy Images Using Machine Learning
Point defects play a fundamental role in the discovery of new materials due to their strong influence on material properties and behavior. At present, imaging techniques based on transmission electron microscopy (TEM) are widely employed for characterizing point defects in materials. However, current methods for defect detection predominantly involve visual inspection of TEM images, which is laborious and poses difficulties in materials where defect related contrast is weak or ambiguous. Recent efforts to develop machine learning methods for the detection of point defects in TEM images have focused on supervised methods that require labeled training data that is generated via simulation. Motivated by a desire for machine learning methods that can be trained on experimental data, we propose two self-supervised machine learning algorithms that are trained solely on images that are defect-free. Our proposed methods use principal components analysis (PCA) and convolutional neural networks (CNN) to analyze a TEM image and predict the location of a defect. Using simulated TEM images, we show that PCA can be used to accurately locate point defects in the case where there is no imaging noise. In the case where there is imaging noise, we show that incorporating a CNN dramatically improves model performance. Our models rely on a novel approach that uses the residual between a TEM image and its PCA reconstruction
Optimum growth window for InAs/GaInSb superlattice materials tailored for very long wavelength infrared detection
The authors report growth studies to develop an InAs/GaInSb superlattice (SL) material for very long wavelength infrared detection. They select a SL structure of 47.0 Å InAs/21.5 Å Ga0.75In0.25Sb that is designed for the greatest possible detectivity, and tune growth conditions to achieve the best quality ternary material. Since the material quality of grown layers is particularly sensitive to extrinsic defects such as nonradiative recombination centers generated during the growth process, the authors investigate the effect of the growth temperature (Tg) on the spectral photoresponse (PR) and carrier recombination lifetime using photoconductivity and time-resolved differential reflectivity measurements. Results indicate that a molecular beam epitaxy growth process the authors developed produces a consistent energy gap around 50 meV, determined from the PR spectra, but the intensity of the spectra is sensitive to Tg. For SLs grown at Tg between 390 and 470 °C, the PR signal intensity gradually increases as Tg increases from 400 to 440 °C, reaching a maximum at 440 °C. Outside this growth window, the SL quality deteriorates very rapidly. However, the carrier recombination lifetime measured at 300 K was not sensitive to Tg. Although the SL sample grown at 430 °C produced the longest lifetime of 84 ns, the average 300 K lifetime value remained around 74 ns
Analytical High-Resolution Electron Microscopy Reveals Organ-Specific Nanoceria Bioprocessing
This is the first utilization of advanced analytical electron microscopy methods, including high-resolution transmission electron microscopy, high-angle annular dark field scanning transmission electron microscopy, electron energy loss spectroscopy, and energy-dispersive X-ray spectroscopy mapping to characterize the organ-specific bioprocessing of a relatively inert nanomaterial (nanoceria). Liver and spleen samples from rats given a single intravenous infusion of nanoceria were obtained after prolonged (90 days) in vivo exposure. These advanced analytical electron microscopy methods were applied to elucidate the organ-specific cellular and subcellular fate of nanoceria after its uptake. Nanoceria is bioprocessed differently in the spleen than in the liver
Effects of Crystalline Disorder on Interfacial and Magnetic Properties of Sputtered Topological Insulator/Ferromagnet Heterostructures
Thin films of Topological insulators (TIs) coupled with ferromagnets (FMs)
are excellent candidates for energy-efficient spintronics devices. Here, the
effect of crystalline structural disorder of TI on interfacial and magnetic
properties of sputter-deposited TI/FM, Bi2Te3/Ni80Fe20, heterostructures is
reported. Ni and a smaller amount of Fe from Py was found to diffuse across the
interface and react with Bi2Te3. For highly crystalline c-axis oriented Bi2Te3
films, a giant enhancement in Gilbert damping is observed, accompanied by an
effective out-of-plane magnetic anisotropy and enhanced damping-like spin-orbit
torque (DL-SOT), possibly due to the topological surface states (TSS) of
Bi2Te3. Furthermore, a spontaneous exchange bias is observed in hysteresis loop
measurements at low temperatures. This is because of an antiferromagnetic
topological interfacial layer formed by reaction of the diffused Ni with Bi2Te3
which couples with the FM, Ni80Fe20. For increasing disorder of Bi2Te3, a
significant weakening of exchange interaction in the AFM interfacial layer is
found. These experimental results Abstract length is one paragraph
High frequency atomic tunneling yields ultralow and glass-like thermal conductivity in chalcogenide single crystals
Crystalline solids exhibiting glass-like thermal conductivity have attracted substantial attention both for fundamental interest and applications such as thermoelectrics. In most crystals, the competition of phonon scattering by anharmonic interactions and crystalline imperfections leads to a non-monotonic trend of thermal conductivity with temperature. Defect-free crystals that exhibit the glassy trend of low thermal conductivity with a monotonic increase with temperature are desirable because they are intrinsically thermally insulating while retaining useful properties of perfect crystals. However, this behavior is rare, and its microscopic origin remains unclear. Here, we report the observation of ultralow and glass-like thermal conductivity in a hexagonal perovskite chalcogenide single crystal, BaTiS₃, despite its highly symmetric and simple primitive cell. Elastic and inelastic scattering measurements reveal the quantum mechanical origin of this unusual trend. A two-level atomic tunneling system exists in a shallow double-well potential of the Ti atom and is of sufficiently high frequency to scatter heat-carrying phonons up to room temperature. While atomic tunneling has been invoked to explain the low-temperature thermal conductivity of solids for decades, our study establishes the presence of sub-THz frequency tunneling systems even in high-quality, electrically insulating single crystals, leading to anomalous transport properties well above cryogenic temperatures
Effects of fluoxetine on functional outcomes after acute stroke (FOCUS): a pragmatic, double-blind, randomised, controlled trial
Background
Results of small trials indicate that fluoxetine might improve functional outcomes after stroke. The FOCUS trial aimed to provide a precise estimate of these effects.
Methods
FOCUS was a pragmatic, multicentre, parallel group, double-blind, randomised, placebo-controlled trial done at 103 hospitals in the UK. Patients were eligible if they were aged 18 years or older, had a clinical stroke diagnosis, were enrolled and randomly assigned between 2 days and 15 days after onset, and had focal neurological deficits. Patients were randomly allocated fluoxetine 20 mg or matching placebo orally once daily for 6 months via a web-based system by use of a minimisation algorithm. The primary outcome was functional status, measured with the modified Rankin Scale (mRS), at 6 months. Patients, carers, health-care staff, and the trial team were masked to treatment allocation. Functional status was assessed at 6 months and 12 months after randomisation. Patients were analysed according to their treatment allocation. This trial is registered with the ISRCTN registry, number ISRCTN83290762.
Findings
Between Sept 10, 2012, and March 31, 2017, 3127 patients were recruited. 1564 patients were allocated fluoxetine and 1563 allocated placebo. mRS data at 6 months were available for 1553 (99·3%) patients in each treatment group. The distribution across mRS categories at 6 months was similar in the fluoxetine and placebo groups (common odds ratio adjusted for minimisation variables 0·951 [95% CI 0·839–1·079]; p=0·439). Patients allocated fluoxetine were less likely than those allocated placebo to develop new depression by 6 months (210 [13·43%] patients vs 269 [17·21%]; difference 3·78% [95% CI 1·26–6·30]; p=0·0033), but they had more bone fractures (45 [2·88%] vs 23 [1·47%]; difference 1·41% [95% CI 0·38–2·43]; p=0·0070). There were no significant differences in any other event at 6 or 12 months.
Interpretation
Fluoxetine 20 mg given daily for 6 months after acute stroke does not seem to improve functional outcomes. Although the treatment reduced the occurrence of depression, it increased the frequency of bone fractures. These results do not support the routine use of fluoxetine either for the prevention of post-stroke depression or to promote recovery of function.
Funding
UK Stroke Association and NIHR Health Technology Assessment Programme
Redesign of the memory in digital data acquisition system of the NAL 4-Ft. trisonic wind tunnel
This note describes the redesign of the memory portion13; of the Digital Data Acquisition System (DD.,\S) of the NAL 4-ft.Trisonic Wind Tunnel, carried out by the 4-ft. Tunnel Electronics Group in association with the Electronics Division of the Laboratory.13; The DDAS performs basically the following functions (a)Acquisition of data, (b) Storing of the acquired data and (c) Read out cycle.13; The existing system was designed by Sarco Canada Ltd.,13; Toronto, Ontario. The system developed fault in the ferrite13; core memory module. The memory module was redesigned for reliable operation of the system by using solid state memory. The system with the solid state memory has been in successful operation since December 1974
Defect Detection in Atomic Resolution Transmission Electron Microscopy Images Using Machine Learning
Point defects play a fundamental role in the discovery of new materials due to their strong influence on material properties and behavior. At present, imaging techniques based on transmission electron microscopy (TEM) are widely employed for characterizing point defects in materials. However, current methods for defect detection predominantly involve visual inspection of TEM images, which is laborious and poses difficulties in materials where defect related contrast is weak or ambiguous. Recent efforts to develop machine learning methods for the detection of point defects in TEM images have focused on supervised methods that require labeled training data that is generated via simulation. Motivated by a desire for machine learning methods that can be trained on experimental data, we propose two self-supervised machine learning algorithms that are trained solely on images that are defect-free. Our proposed methods use principal components analysis (PCA) and convolutional neural networks (CNN) to analyze a TEM image and predict the location of a defect. Using simulated TEM images, we show that PCA can be used to accurately locate point defects in the case where there is no imaging noise. In the case where there is imaging noise, we show that incorporating a CNN dramatically improves model performance. Our models rely on a novel approach that uses the residual between a TEM image and its PCA reconstruction
Making sense of ‘new age data sets’: researching from afar
This chapter considers the central role of uncertainty for cognition and action in construction project organising with a focus on how project practitioners think about the future. It takes a cognitive approach to uncertainty in the context of a broader information processing approach to decision-making in organisations. The chapter’s main concern is the failure of this approach to connect cognition through to action. The chapter presents the UnCoCoH (Un-Certain Complex Complicated Hidden) model as a tool to assist in recognising the transition from individual cognition to collective action. It also highlights the role of narratives for stabilising uncertainty through this transition. This provides a foundation for working towards the development of a projectivity perspective in construction project organising and advancing a research agenda for this program of research.Green Open Access added to TU Delft Institutional Repository ‘You share, we take care!’ – Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.Integral Design & Managemen