Quantifying short-range order using atom probe tomography.

Medium- and high-entropy alloys are an emerging class of materials that can exhibit outstanding combinations of strength and ductility for engineering applications. Computational simulations have suggested the presence of short-range order (SRO) in these alloys, and recent experimental evidence is also beginning to emerge. Unfortunately, the difficulty in quantifying the SRO under different heat treatment conditions has generated much debate on the atomic preferencing and implications of SRO on mechanical properties. Here we develop an approach to measure SRO using atom probe tomography. This method balances the limitations of atom probe tomography with the threshold values of SRO to map the regimes where the required atomistic neighbourhood information is preserved and where it is not. We demonstrate the method with a case study of the CoCrNi alloy and use this to monitor SRO changes induced by heat treatments. These species-specific SRO measurements enable the generation of computational simulations of atomic neighbourhood models that are equivalent to the experiment and can contribute to the further understanding and design of medium- and high-entropy alloys and other materials systems where SRO may occur.

Effects of thermal annealing on the distribution of boron and phosphorus in p-i-n structured silicon nanocrystals embedded in silicon dioxide.

Thermal annealing temperature and time dictate the microstructure of semiconductor materials such as silicon nanocrystals (Si NCs). Herein, atom probe tomography (APT) and density functional theory (DFT) calculations are used to understand the thermal annealing temperature effects on Si NCs grown in a SiO2matrix and the distribution behaviour of boron (B) and phosphorus (P) dopant atoms. The APT results demonstrate that raising the annealing temperature promotes growth and increased P concentration of the Si NCs. The data also shows that the thermal annealing does not promote the incorporation of B atoms into Si NCs. Instead, B atoms tend to locate at the interface between the Si NCs and SiO2matrix. The DFT calculations support the APT data and reveal that oxygen vacancies regulate Si NC growth and dopant distribution. This study provides the detailed microstructure of p-type, intrinsic, and n-type Si NCs with changing annealing temperature and highlights how B and P dopants preferentially locate with respect to the Si NCs embedded in the SiO2matrix with the aid of oxygen vacancies. These findings will be useful towards future optoelectronic applications.

Integrative Atom Probe Tomography Using Scanning Transmission Electron Microscopy-Centric Atom Placement as a Step Toward Atomic-Scale Tomography.

Current reconstruction methodologies for atom probe tomography (APT) contain serious geometric artifacts that are difficult to address due to their reliance on empirical factors to generate a reconstructed volume. To overcome this limitation, a reconstruction technique is demonstrated where the analyzed volume is instead defined by the specimen geometry and crystal structure as determined by transmission electron microscopy (TEM) and diffraction acquired before and after APT analysis. APT data are reconstructed using a bottom-up approach, where the post-APT TEM image is used to define the substrate upon which APT detection events are placed. Transmission electron diffraction enables the quantification of the relationship between atomic positions and the evaporated specimen volume. Using an example dataset of ZnMgO:Ga grown epitaxially on c-plane sapphire, a volume is reconstructed that has the correct geometry and atomic spacings in 3D. APT data are thus reconstructed in 3D without using empirical parameters for the reverse projection reconstruction algorithm.

Levosimendan for the Prevention of Acute Organ Dysfunction in Sepsis.

BACKGROUND: Levosimendan is a calcium-sensitizing drug with inotropic and other properties that may improve outcomes in patients with sepsis. METHODS: We conducted a double-blind, randomized clinical trial to investigate whether levosimendan reduces the severity of organ dysfunction in adults with sepsis. Patients were randomly assigned to receive a blinded infusion of levosimendan (at a dose of 0.05 to 0.2 µg per kilogram of body weight per minute) for 24 hours or placebo in addition to standard care. The primary outcome was the mean daily Sequential Organ Failure Assessment (SOFA) score in the intensive care unit up to day 28 (scores for each of five systems range from 0 to 4, with higher scores indicating more severe dysfunction; maximum score, 20). Secondary outcomes included 28-day mortality, time to weaning from mechanical ventilation, and adverse events. RESULTS: The trial recruited 516 patients; 259 were assigned to receive levosimendan and 257 to receive placebo. There was no significant difference in the mean (±SD) SOFA score between the levosimendan group and the placebo group (6.68±3.96 vs. 6.06±3.89; mean difference, 0.61; 95% confidence interval [CI], -0.07 to 1.29; P=0.053). Mortality at 28 days was 34.5% in the levosimendan group and 30.9% in the placebo group (absolute difference, 3.6 percentage points; 95% CI, -4.5 to 11.7; P=0.43). Among patients requiring ventilation at baseline, those in the levosimendan group were less likely than those in the placebo group to be successfully weaned from mechanical ventilation over the period of 28 days (hazard ratio, 0.77; 95% CI, 0.60 to 0.97; P=0.03). More patients in the levosimendan group than in the placebo group had supraventricular tachyarrhythmia (3.1% vs. 0.4%; absolute difference, 2.7 percentage points; 95% CI, 0.1 to 5.3; P=0.04). CONCLUSIONS: The addition of levosimendan to standard treatment in adults with sepsis was not associated with less severe organ dysfunction or lower mortality. Levosimendan was associated with a lower likelihood of successful weaning from mechanical ventilation and a higher risk of supraventricular tachyarrhythmia. (Funded by the NIHR Efficacy and Mechanism Evaluation Programme and others; LeoPARDS Current Controlled Trials number, ISRCTN12776039 .).

Breaking the icosahedra in boron carbide.

Findings of laser-assisted atom probe tomography experiments on boron carbide elucidate an approach for characterizing the atomic structure and interatomic bonding of molecules associated with extraordinary structural stability. The discovery of crystallographic planes in these boron carbide datasets substantiates that crystallinity is maintained to the point of field evaporation, and characterization of individual ionization events gives unexpected evidence of the destruction of individual icosahedra. Statistical analyses of the ions created during the field evaporation process have been used to deduce relative atomic bond strengths and show that the icosahedra in boron carbide are not as stable as anticipated. Combined with quantum mechanics simulations, this result provides insight into the structural instability and amorphization of boron carbide. The temporal, spatial, and compositional information provided by atom probe tomography makes it a unique platform for elucidating the relative stability and interactions of primary building blocks in hierarchically crystalline materials.

Building a Library of Simulated Atom Probe Data for Different Crystal Structures and Tip Orientations Using TAPSim.

The process of building an open source library of simulated field desorption maps for differently oriented synthetic tips of the face-centered cubic, body-centered cubic, and hexagonal-close-packed crystal structures using the open source software TAPSim is reported. Specifically, the field evaporation of a total set of 4 × 101 single-crystalline tips was simulated. Their lattices were oriented randomly to sample economically the fundamental zone of crystal orientations. Such data are intended to facilitate the interpretation of low-density zone lines and poles that are observed on detector hit maps during Atom Probe Tomography (APT) experiments. The datasets and corresponding tools have been made publicly available to the APT community in an effort to provide better access to simulated atom probe datasets. In addition, a computational performance analysis was conducted, from which recommendations are made as to which key tasks should be optimized in the future to improve the parallel efficiency of TAPSim.

Quantification Challenges for Atom Probe Tomography of Hydrogen and Deuterium in Zircaloy-4.

Analysis and understanding of the role of hydrogen in metals is a significant challenge for the future of materials science, and this is a clear objective of recent work in the atom probe tomography (APT) community. Isotopic marking by deuteration has often been proposed as the preferred route to enable quantification of hydrogen by APT. Zircaloy-4 was charged electrochemically with hydrogen and deuterium under the same conditions to form large hydrides and deuterides. Our results from a Zr hydride and a Zr deuteride highlight the challenges associated with accurate quantification of hydrogen and deuterium, in particular associated with the overlap of peaks at a low mass-to-charge ratio and of hydrogen/deuterium containing molecular ions. We discuss possible ways to ensure that appropriate information is extracted from APT analysis of hydrogen in zirconium alloy systems that are important for nuclear power applications.

Correlating Atom Probe Crystallographic Measurements with Transmission Kikuchi Diffraction Data.

Correlative microscopy approaches offer synergistic solutions to many research problems. One such combination, that has been studied in limited detail, is the use of atom probe tomography (APT) and transmission Kikuchi diffraction (TKD) on the same tip specimen. By combining these two powerful microscopy techniques, the microstructure of important engineering alloys can be studied in greater detail. For the first time, the accuracy of crystallographic measurements made using APT will be independently verified using TKD. Experimental data from two atom probe tips, one a nanocrystalline Al-0.5Ag alloy specimen collected on a straight flight-path atom probe and the other a high purity Mo specimen collected on a reflectron-fitted instrument, will be compared. We find that the average minimum misorientation angle, calculated from calibrated atom probe reconstructions with two different pole combinations, deviate 0.7° and 1.4°, respectively, from the TKD results. The type of atom probe and experimental conditions appear to have some impact on this accuracy and the reconstruction and measurement procedures are likely to contribute further to degradation in angular resolution. The challenges and implications of this correlative approach will also be discussed.

Resolving the morphology of niobium carbonitride nano-precipitates in steel using atom probe tomography.

Atom probe is a powerful technique for studying the composition of nano-precipitates, but their morphology within the reconstructed data is distorted due to the so-called local magnification effect. A new technique has been developed to mitigate this limitation by characterizing the distribution of the surrounding matrix atoms, rather than those contained within the nano-precipitates themselves. A comprehensive chemical analysis enables further information on size and chemistry to be obtained. The method enables new insight into the morphology and chemistry of niobium carbonitride nano-precipitates within ferrite for a series of Nb-microalloyed ultra-thin cast strip steels. The results are supported by complementary high-resolution transmission electron microscopy.

Characterising the performance of an ultrawide field-of-view 3D atom probe.

The CAMECA Invizo 6000 atom probe microscope uses ion optics that differ significantly from the local electrode atom probe (LEAP). It uses dual antiparallel deep ultraviolet lasers, a flat counter electrode, and a series of accelerating and decelerating lenses to increase the field-of-view of the specimen without reducing the mass resolving power. In this work we characterise the performance of the Invizo 6000 using three material case studies: a model Al-Mg-Si alloy, a commercially-available Ni-based superalloy, and a Zr alloy, using a combination of air and vacuum-transfer between instruments. The ion optics of the Invizo 6000 significantly increase the field-of-view compared to the same specimen on a LEAP 4000 X Si. We also observe a significant increase in specimen yield, especially for the Zr alloy. These results combine to make the Invizo 6000 well-suited to research projects requiring large analysis volumes, particularly so for traditionally difficult samples such as oxides.

Exploration of atom probe tomography at sub-10K.

The operating temperature is a critical parameter in atom probe tomography experiments. It affects the spatial precision, mass resolving power and other key aspects of the field-evaporation process. Current commercially available atom probes operate at a minimum temperature of ∼25 K when measured at the specimen. In this paper, we explore and implement changes to the mechanical design of both the LEAPⓇ and EIKOS™ atom probe microscope systems manufactured by CAMECAⓇ to enable a specimen temperature in the sub-10 K regime. We use these modified instruments to analyze four materials systems: pure Al (in both pulsed-voltage and pulsed-laser mode), pure W (pulsed-voltage mode only), doped Si, and GaN (pulsed-laser mode only). The effects of conducting atom probe experiments in the sub-10 K regime were assessed with reference to a range of quantitative analysis metrics related to spatial precision, mass resolving power, stoichiometry and charge-state ratio. We demonstrate that the spatial precision is significantly improved with decreasing temperature, whilst the effect on mass resolving power is relatively minor. The enhanced spatial precision is significant insofar as it enables lattice planes from the doped Si samples to be resolved. Furthermore, mass spectral analysis, lower noise floors and changes in the field evaporation process enabled more accurate GaN compositional measurements. We discuss the significance of these findings for the semiconductor and metallurgical industries and the potential opportunities for further investigations of this parameter space.

FUSIC HD. Comprehensive haemodynamic assessment with ultrasound.

FUSIC haemodynamics (HD) - the latest Focused Ultrasound in Intensive Care (FUSIC) module created by the Intensive Care Society (ICS) - describes a complete haemodynamic assessment with ultrasound based on ten key clinical questions: 1. Is stroke volume abnormal? 2. Is stroke volume responsive to fluid, vasopressors or inotropes? 3. Is the aorta abnormal? 4. Is the aortic valve, mitral valve or tricuspid valve severely abnormal? 5. Is there systolic anterior motion of the mitral valve? 6. Is there a regional wall motion abnormality? 7. Are there features of raised left atrial pressure? 8. Are there features of right ventricular impairment or raised pulmonary artery pressure? 9. Are there features of tamponade? 10. Is there venous congestion? FUSIC HD is the first system of its kind to interrogate major cardiac, arterial and venous structures to direct time-critical interventions in acutely unwell patients. This article explains the rationale for this accreditation, outlines the training pathway and summarises the ten clinical questions. Further details are included in an online supplementary appendix.

Lattice rectification in atom probe tomography: toward true three-dimensional atomic microscopy.

Atom probe tomography (APT) represents a significant step toward atomic resolution microscopy, analytically imaging individual atoms with highly accurate, though imperfect, chemical identity and three-dimensional (3D) positional information. Here, a technique to retrieve crystallographic information from raw APT data and restore the lattice-specific atomic configuration of the original specimen is presented. This lattice rectification technique has been applied to a pure metal, W, and then to the analysis of a multicomponent Al alloy. Significantly, the atoms are located to their true lattice sites not by an averaging, but by triangulation of each particular atom detected in the 3D atom-by-atom reconstruction. Lattice rectification of raw APT reconstruction provides unprecedented detail as to the fundamental solute hierarchy of the solid solution. Atomic clustering has been recognized as important in affecting alloy behavior, such as for the Al-1.1 Cu-1.7 Mg (at. %) investigated here, which exhibits a remarkable rapid hardening reaction during the early stages of aging, linked to clustering of solutes. The technique has enabled lattice-site and species-specific radial distribution functions, nearest-neighbor analyses, and short-range order parameters, and we demonstrate a characterization of solute-clustering with unmatched sensitivity and precision.

An evaluation of advance care planning during the COVID-19 pandemic: a retrospective review of patient involvement in decision making using routinely collected data from digital ReSPECT records.

OBJECTIVE: To review advance care planning (ACP) practice during the COVID-19 pandemic, evaluating the number of plans created, patient participation, cardiopulmonary resuscitation recommendations and variation between different population groups. DESIGN: A retrospective analysis and comparison of routinely collected data from electronic recommended summary plan for emergency care and treatment (ReSPECT) records documented in April 2020 and January to December 2019. SETTING/PARTICIPANTS: Electronic ReSPECT documents completed for adult patients at a large, acute hospital trust in the UK. RESULTS: The number of plans created per 1,000 admissions in April 2020 was 333.0% higher than in 2019. A greater proportion of plans created during April 2020 were discussed with the patient and the proportion containing a 'for cardiopulmonary resuscitation' recommendation was higher across all population groups. A greater proportion of plans were created for younger adults and Black and minority ethnic groups during the pandemic. CONCLUSION: Increased ACP during a crisis can be achieved alongside increased patient participation in decision making. A tool such as ReSPECT that supports recommendations for, as well as limitations on, treatment may have enabled the expansion of ACP observed.

Open and strong-scaling tools for atom-probe crystallography: high-throughput methods for indexing crystal structure and orientation.

Volumetric crystal structure indexing and orientation mapping are key data processing steps for virtually any quantitative study of spatial correlations between the local chemical composition features and the microstructure of a material. For electron and X-ray diffraction methods it is possible to develop indexing tools which compare measured and analytically computed patterns to decode the structure and relative orientation within local regions of interest. Consequently, a number of numerically efficient and automated software tools exist to solve the above characterization tasks. For atom-probe tomography (APT) experiments, however, the strategy of making comparisons between measured and analytically computed patterns is less robust because many APT data sets contain substantial noise. Given that sufficiently general predictive models for such noise remain elusive, crystallography tools for APT face several limitations: their robustness to noise is limited, and therefore so too is their capability to identify and distinguish different crystal structures and orientations. In addition, the tools are sequential and demand substantial manual interaction. In combination, this makes robust uncertainty quantification with automated high-throughput studies of the latent crystallographic information a difficult task with APT data. To improve the situation, the existing methods are reviewed and how they link to the methods currently used by the electron and X-ray diffraction communities is discussed. As a result of this, some of the APT methods are modified to yield more robust descriptors of the atomic arrangement. Also reported is how this enables the development of an open-source software tool for strong scaling and automated identification of a crystal structure, and the mapping of crystal orientation in nanocrystalline APT data sets with multiple phases.

A Crystallography-Mediated Reconstruction (CMR) Approach for Atom Probe Tomography: Solution for a Singleton Pole.

Spatially accurate atom probe tomography reconstructions are vitally important when quantitative spatial measurements such as distances, volumes and morphologies etc. of nanostructural features are required information for the researcher. It is well known that the crystallographic information contained within the atom probe data of crystalline materials can be used to calibrate the tomographic reconstruction. Specifically, the crystallographic information projected into the field evaporation images is used. This offers a powerful and accurate enhancement of the atom probe technique. However, this is often difficult to do in practice. In previously reported approaches, it was necessary to index at least two poles to compute the image compression factor 'ξ' and observe crystallographic planes in at least one of the pole regions to obtain a measure of the field factor 'kf' while also manually accounting for a change in reconstruction parameters throughout the dataset. Not only is this error-prone and time consuming, it does not work for materials that exhibit limited crystallographic information in their field evaporation image. Here, we extend the applicability of the crystallographic calibration of atom probe data by proposing a reconstruction methodology where only one pole with observable lattice planes is required in the projected detector image. Our proposal also accounts for dynamic variations in the reconstruction parameters throughout the 3D dataset. The method is simpler and significantly faster to implement and is applicable to more atom probe situations than previously approaches. Our single-pole crystallography mediated reconstruction (SP-CMR) utilizes the Hawkes-Kasper projection model (equivalent to the equidistant-azimuthal projection model) and the direct fourier (DF) fit algorithm to determine the precise reconstruction parameters required to produce flat atomic planes. It is applied to experimental Al and highly Sb-doped Si data. The discrepancies between the spatial dimensions of the SP-CMR reconstructions compared to uncalibrated reconstructions are visually apparent. Consistent plane spacings and angles between crystallographic directions matching the theoretically known values for each crystal structure are demonstrated.

Long-term clinical outcomes in survivors of severe acute respiratory syndrome and Middle East respiratory syndrome coronavirus outbreaks after hospitalisation or ICU admission: A systematic review and meta-analysis.

OBJECTIVE: To determine long-term clinical outcomes in survivors of severe acute respiratory syndrome (SARS) and Middle East respiratory syndrome (MERS) coronavirus infections after hospitalization or intensive care unit admission. DATA SOURCES: Ovid MEDLINE, EMBASE, CINAHL Plus, and PsycINFO were searched. STUDY SELECTION: Original studies reporting clinical outcomes of adult SARS and MERS survivors 3 months after admission or 2 months after discharge were included. DATA EXTRACTION: Studies were graded using the Oxford Centre for Evidence-Based Medicine 2009 Level of Evidence Tool. Meta-analysis was used to derive pooled estimates for prevalence/severity of outcomes up to 6 months after hospital discharge, and beyond 6 months after discharge. DATA SYNTHESIS: Of 1,169 identified studies, 28 were included in the analysis. Pooled analysis revealed that common complications up to 6 months after discharge were: impaired diffusing capacity for carbon monoxide (prevalence 27%, 95% confidence interval (CI) 15­45%); and reduced exercise capacity (mean 6-min walking distance 461 m, CI 450­473 m). The prevalences of post-traumatic stress disorder (39%, 95% CI 31­47%), depression (33%, 95% CI 20­50%) and anxiety (30%, 95% CI 10­61) beyond 6 months after discharge were considerable. Low scores on Short-Form 36 were identified beyond 6 months after discharge. CONCLUSION: Lung function abnormalities, psychological impairment and reduced exercise capacity were common in SARS and MERS survivors. Clinicians should anticipate and investigate similar long-term outcomes in COVID-19 survivors.

3D nanostructural characterisation of grain boundaries in atom probe data utilising machine learning methods.

Boosting is a family of supervised learning algorithm that convert a set of weak learners into a single strong one. It is popular in the field of object tracking, where its main purpose is to extract the position, motion, and trajectory from various features of interest within a sequence of video frames. A scientific application explored in this study is to combine the boosting tracker and the Hough transformation, followed by principal component analysis, to extract the location and trace of grain boundaries within atom probe data. Before the implementation of this method, these information could only be extracted manually, which is time-consuming and error-prone. The effectiveness of this method is demonstrated on an experimental dataset obtained from a pure aluminum bi-crystal and validated on simulated data. The information gained from this method can be combined with crystallographic information directly contained within the data, to fully define the grain boundary character to its 5 degrees of freedom at near-atomic resolution in three dimensions. It also enables local atomic compositional and geometric information, i.e. curvature, to be extracted directly at the interface.

On the retrieval of crystallographic information from atom probe microscopy data via signal mapping from the detector coordinate space.

Atom probe tomography is a powerful microscopy technique capable of reconstructing the 3D position and chemical identity of millions of atoms within engineering materials, at the atomic level. Crystallographic information contained within the data is particularly valuable for the purposes of reconstruction calibration and grain boundary analysis. Typically, analysing this data is a manual, time-consuming and error prone process. In many cases, the crystallographic signal is so weak that it is difficult to detect at all. In this study, a new automated signal processing methodology is demonstrated. We use the affine properties of the detector coordinate space, or the 'detector stack', as the basis for our calculations. The methodological framework and the visualisation tools are shown to be superior to the standard method of crystallographic pole visualisation directly from field evaporation images and there is no requirement for iterations between a full real-space initial tomographic reconstruction and the detector stack. The mapping approaches are demonstrated for aluminium, tungsten, magnesium and molybdenum. Implications for reconstruction calibration, accuracy of crystallographic measurements, reliability and repeatability are discussed.

Machine-learning-based atom probe crystallographic analysis.

Atom probe tomography is known for its accurate compositional analysis at the nanoscale. However, the patterns created by successive hits on the single particle detector during experiments often contain complementary information about the specimen's crystallography, including structure and orientation. This information remains in most cases unexploited because it is, up to now, retrieved predominantly manually. Here, we propose an approach combining image analysis techniques for feature selection and deep-learning to automatically interpret the patterns. Application of unsupervised machine learning techniques allows to build and train a deep neural network, based on a library generated from theoretically known crystallographic angular relationships. This approach enables direct interpretation of the detector hit maps, as shown here on the example of numerous pure-Al, and is robust enough to function under various conditions of base temperature, pulsing mode and pulse fraction. We benchmark our approach against recent attempts to automate the pattern identification via Hough-transform and discuss the current limitations of our approach. This new automated approach renders crystallographic atom probe tomography analysis more efficient, feature-sensitive, robust, user-independent and reliable. With that, deep-learning algorithms show a great potential to give access to combined atom probe crystallographic and compositional analysis to a large community of users.