Maturation Pathway from Germline to Broad HIV-1 Neutralizer of a CD4-Mimic Antibody.

Antibodies with ontogenies from VH1-2 or VH1-46-germline genes dominate the broadly neutralizing response against the CD4-binding site (CD4bs) on HIV-1. Here, we define with longitudinal sampling from time-of-infection the development of a VH1-46-derived antibody lineage that matured to neutralize 90% of HIV-1 isolates. Structures of lineage antibodies CH235 (week 41 from time-of-infection, 18% breadth), CH235.9 (week 152, 77%), and CH235.12 (week 323, 90%) demonstrated the maturing epitope to focus on the conformationally invariant portion of the CD4bs. Similarities between CH235 lineage and five unrelated CD4bs lineages in epitope focusing, length-of-time to develop breadth, and extraordinary level of somatic hypermutation suggested commonalities in maturation among all CD4bs antibodies. Fortunately, the required CH235-lineage hypermutation appeared substantially guided by the intrinsic mutability of the VH1-46 gene, which closely resembled VH1-2. We integrated our CH235-lineage findings with a second broadly neutralizing lineage and HIV-1 co-evolution to suggest a vaccination strategy for inducing both lineages.

Atom Probe Tomography Investigation of Clustering in Model P2O5-Doped Borosilicate Glasses for Nuclear Waste Vitrification.

Atom probe tomography (APT) has been utilized to investigate the microstructure of two model borosilicate glasses designed to understand the solubility limits of phosphorous pentoxide (P2O5). This component is found in certain high-level radioactive defence wastes destined for vitrification, where phase separation can potentially lead to a number of issues relating to the processing of the glass and its long-term chemical and structural stability. The development of suitable focused ion beam (FIB)-preparation routes and APT analysis conditions were initially determined for the model glasses, before examining their detailed microstructures. In a 3.0 mol% P2O5-doped glass, both visual inspection and sensitive statistical analysis of the APT data show homogeneous microstructures, while raising the content to 4.0 mol% initiates the formation of phosphorus-enriched nanoscale precipitates. This study confirms the expected inhomogeneities and phase separation of these glasses and offers routes to characterizing these at near-atomic scale resolution using APT.

Phylogenomic Analyses of Alismatales Shed Light into Adaptations to Aquatic Environments.

Land plants first evolved from freshwater algae, and flowering plants returned to water as early as the Cretaceous and multiple times subsequently. Alismatales is the largest clade of aquatic angiosperms including all marine angiosperms, as well as terrestrial plants. We used Alismatales to explore plant adaptations to aquatic environments by analyzing a data set that included 95 samples (89 Alismatales species) covering four genomes and 91 transcriptomes (59 generated in this study). To provide a basis for investigating adaptations, we assessed phylogenetic conflict and whole-genome duplication (WGD) events in Alismatales. We recovered a relationship for the three main clades in Alismatales as (Tofieldiaceae, Araceae) + core Alismatids. We also found phylogenetic conflict among the three main clades that was best explained by incomplete lineage sorting and introgression. Overall, we identified 18 putative WGD events across Alismatales. One of them occurred at the most recent common ancestor of core Alismatids, and three occurred at seagrass lineages. We also found that lineage and life-form were both important for different evolutionary patterns for the genes related to freshwater and marine adaptation. For example, several light- or ethylene-related genes were lost in the seagrass Zosteraceae, but are present in other seagrasses and freshwater species. Stomata-related genes were lost in both submersed freshwater species and seagrasses. Nicotianamine synthase genes, which are important in iron intake, expanded in both submersed freshwater species and seagrasses. Our results advance the understanding of the adaptation to aquatic environments and WGDs using phylogenomics.

Understanding photochemical pathways of laser-induced metal ion reduction through byproduct analysis.

Laser-induced reduction of metal ions is attracting increasing attention as a sustainable route to ligand-free metal nanoparticles. In this work, we investigate the photochemical reactions involved in reduction of Ag+ and [AuCl4]- upon interaction with lasers with nanosecond and femtosecond pulse duration, using strong-field ionization mass spectrometry and spectroscopic assays to identify stable molecular byproducts. Whereas Ag+ in aqueous isopropyl alcohol (IPA) is reduced through plasma-mediated mechanisms upon femtosecond laser excitation, low-fluence nanosecond laser excitation induces electron transfer from IPA to Ag+. Both nanosecond and femtosecond laser excitation of aqueous [AuCl4]- produce reactive chlorine species by Au-Cl bond homolysis. Formation of numerous volatile products by IPA decomposition during both femtosecond and nanosecond laser excitation of [AuCl4]- is attributed to enhanced optical breakdown by the Au nanoparticle products of [AuCl4]- reduction. These mechanistic insights can inform the design of laser synthesis procedures to improve control over metal nanoparticle properties and enhance byproduct yields.

Large-Scale Atom Probe Tomography Data Mining: Methods and Application to Inform Hydrogen Behavior.

A large number of atom probe tomography (APT) datasets from past experiments were collected into a database to conduct statistical analyses. An effective way of handling the data is shown, and a study on hydrogen is conducted to illustrate the usefulness of this approach. We propose to handle a large collection of APT spectra as a point cloud and use a city block distance-based metric to measure dissimilarity between spectra. This enables quick and automated searching for spectra by similarity. Since spectra from APT experiments on similar materials are similar, the point cloud of spectra contains clusters. Analysis of these clusters of spectra in this point cloud allows us to infer the sample materials. The behavior of contaminant hydrogen is analyzed and correlated with voltage, electric field, and sample base material. Across several materials, the H2+ /H+ ratio is found to decrease with increasing field, likely an indication of postionization of H2+ ions. The absolute amounts of H2+ and H+ are found to frequently increase throughout APT experiments.

Nothing in Evolution Makes Sense Except in the Light of Biology.

A key question in biology is the predictability of the evolutionary process. If we can correctly predict the outcome of evolution, we may be better equipped to anticipate and manage species' adaptation to climate change, habitat loss, invasive species, or emerging infectious diseases, as well as improve our basic understanding of the history of life on Earth. In the present article, we ask the questions when, why, and if the outcome of future evolution is predictable. We first define predictable and then discuss two conflicting views: that evolution is inherently unpredictable and that evolution is predictable given the ability to collect the right data. We identify factors that generate unpredictability, the data that might be required to make predictions at some level of precision or at a specific timescale, and the intellectual and translational value of understanding when prediction is or is not possible.

Ligand-Protected Ultrasmall Pd Nanoclusters Supported on Metal Oxide Surfaces for CO Oxidation: Does the Ligand Activate or Passivate the Pd Nanocatalyst?

Herein, we report on the synthesis of ultrasmall Pd nanoclusters (∼2 nm) protected by L-cysteine [HOCOCH(NH2 )CH2 SH] ligands (Pdn (L-Cys)m ) and supported on the surfaces of CeO2 , TiO2 , Fe3 O4 , and ZnO nanoparticles for CO catalytic oxidation. The Pdn (L-Cys)m nanoclusters supported on the reducible metal oxides CeO2 , TiO2 and Fe3 O4 exhibit a remarkable catalytic activity towards CO oxidation, significantly higher than the reported Pd nanoparticle catalysts. The high catalytic activity of the ligand-protected clusters Pdn (L-Cys)m is observed on the three reducible oxides where 100 % CO conversion occurs at 93-110 °C. The high activity is attributed to the ligand-protected Pd nanoclusters where the L-cysteine ligands aid in achieving monodispersity of the Pd clusters by limiting the cluster size to the active sub-2-nm region and decreasing the tendency of the clusters for agglomeration. In the case of the ceria support, a complete removal of the L-cysteine ligands results in connected agglomerated Pd clusters which are less reactive than the ligand-protected clusters. However, for the TiO2 and Fe3 O4 supports, complete removal of the ligands from the Pdn (L-Cys)m clusters leads to a slight decrease in activity where the T100% CO conversion occurs at 99 °C and 107 °C, respectively. The high porosity of the TiO2 and Fe3 O4 supports appears to aid in efficient encapsulation of the bare Pdn nanoclusters within the mesoporous pores of the support.

Atom Probe Tomography of a Cu-Doped TiNiSn Thermoelectric Material: Nanoscale Structure and Optimization of Analysis Conditions.

Cu-doping and crystallographic site occupations within the half-Heusler (HH) TiNiSn, a promising thermoelectric material, have been examined by atom probe tomography. In particular, this investigation aims to better understand the influence of atom probe analysis conditions on the measured chemical composition. Under a voltage-pulsing mode, atomic planes are clearly resolved and suggest an arrangement of elements in-line with the expected HH (F-43m space group) crystal structure. The Cu dopant is also distributed uniformly throughout the bulk material. For operation under laser-pulsed modes, the returned composition is highly dependent on the selected laser energy, with high energies resulting in the measurement of excessively high absolute Ti counts at the expense of Sn and in particular Ni. High laser energies also appear to be correlated with the detection of a high fraction of partial hits, indicating nonideal evaporation behavior. The possible mechanisms for these trends are discussed, along with suggestions for optimal analysis conditions for these and similar thermoelectric materials.

Processing APT Spectral Backgrounds for Improved Quantification.

We describe a method to estimate background noise in atom probe tomography (APT) mass spectra and to use this information to enhance both background correction and quantification. Our approach is mathematically general in form for any detector exhibiting Poisson noise with a fixed data acquisition time window, at voltages varying through the experiment. We show that this accurately estimates the background observed in real experiments. The method requires, as a minimum, the z-coordinate and mass-to-charge-state data as input and can be applied retrospectively. Further improvements are obtained with additional information such as acquisition voltage. Using this method allows for improved estimation of variance in the background, and more robust quantification, with quantified count limits at parts-per-million concentrations. To demonstrate applications, we show a simple peak detection implementation, which quantitatively suppresses false positives arising from random noise sources. We additionally quantify the detectability of 121-Sb in a standardized-doped Si microtip as (1.5 × 10−5, 3.8 × 10−5) atomic fraction, α = 0.95. This technique is applicable to all modes of APT data acquisition and is highly general in nature, ultimately allowing for improvements in analyzing low ionic count species in datasets.

Reflections on the Analysis of Interfaces and Grain Boundaries by Atom Probe Tomography.

Interfaces play critical roles in materials and are usually both structurally and compositionally complex microstructural features. The precise characterization of their nature in three-dimensions at the atomic scale is one of the grand challenges for microscopy and microanalysis, as this information is crucial to establish structure-property relationships. Atom probe tomography is well suited to analyzing the chemistry of interfaces at the nanoscale. However, optimizing such microanalysis of interfaces requires great care in the implementation across all aspects of the technique from specimen preparation to data analysis and ultimately the interpretation of this information. This article provides critical perspectives on key aspects pertaining to spatial resolution limits and the issues with the compositional analysis that can limit the quantification of interface measurements. Here, we use the example of grain boundaries in steels; however, the results are applicable for the characterization of grain boundaries and transformation interfaces in a very wide range of industrially relevant engineering materials.

Differential responses of ecotypes to climate in a ubiquitous Arctic sedge: implications for future ecosystem C cycling.

The response of vegetation to climate change has implications for the carbon cycle and global climate. It is frequently assumed that a species responds uniformly across its range to climate change. However, ecotypes - locally adapted populations within a species - display differences in traits that may affect their gross primary productivity (GPP) and response to climate change. To determine if ecotypes are important for understanding the response of ecosystem productivity to climate we measured and modeled growing season GPP in reciprocally transplanted and experimentally warmed ecotypes of the abundant Arctic sedge Eriophorum vaginatum. Transplanted northern ecotypes displayed home-site advantage in GPP that was associated with differences in leaf area index. Southern ecotypes exhibited a greater response in GPP when transplanted. The results demonstrate that ecotypic differentiation can impact the morphology and function of vegetation with implications for carbon cycling. Moreover they suggest that ecotypic control of GPP may limit the response of ecosystem productivity to climate change. This investigation shows that ecotypes play a substantial role in determining GPP and its response to climate. These results have implications for understanding annual to decadal carbon cycling where ecotypes could influence ecosystem function and vegetation feedbacks to climate change.

DF-Fit: A Robust Algorithm for Detection of Crystallographic Information in Atom Probe Tomography Data.

We report on a new algorithm for the detection of crystallographic information in three-dimensional, as retained in atom probe tomography (APT), with improved robustness and signal detection performance. The algorithm is underpinned by one-dimensional distribution functions (DFs), as per existing algorithms, but eliminates an unnecessary parameter as compared to current methods.By examining traditional DFs in an automated fashion in real space, rather than using Fourier transform approaches, we utilize an error metric based upon the expected value for a spatially random distribution for detecting crystallography. We show cases where the metric is able to successfully obtain orientation information, and show that it can function with high levels of additive and displacive background noise. We additionally compare this metric to Fourier transform methods, showing fewer artifacts when examining simulated datasets. An extension of the approach is used to aid the automatic detection of high-quality data regions within an entire dataset, albeit with a large increase in computational cost.This extension is demonstrated on acquired aluminum and tungsten APT datasets, and shown to be able to discern regions of the data which have relatively improved spatial data quality. Finally, this program has been made available for use in other laboratories undertaking their own analyses.

A Gas-Phase Reaction Cell for Modern Atom Probe Systems.

In this work, we demonstrate a new system for the examination of gas interactions with surfaces via atom probe tomography. This system provides capability of examining the surface and subsurface interactions of gases with a wide range of specimens, as well as a selection of input gas types. This system has been primarily developed to aid the investigation of hydrogen interactions with metallurgical samples, to better understand the phenomenon of hydrogen embrittlement. In its current form, it is able to operate at pressures from 10-6 to 1000 mbar (abs), can use a variety of gasses, and is equipped with heating and cryogenic quenching capabilities. We use this system to examine the interaction of hydrogen with Pd, as well as the interaction of water vapor and oxygen in Mg samples.

Interpreting Atom Probe Data from Oxide-Metal Interfaces.

Understanding oxide-metal interfaces is crucial to the advancement of materials and components for many industries, most notably for semiconductor devices and power generation. Atom probe tomography provides three-dimensional, atomic scale information about chemical composition, making it an excellent technique for interface analysis. However, difficulties arise when analyzing interfacial regions due to trajectory aberrations, such as local magnification, and reconstruction artifacts. Correlative microscopy and field simulation techniques have revealed that nonuniform evolution of the tip geometry, caused by heterogeneous field evaporation, is partly responsible for these artifacts. Here we attempt to understand these trajectory artifacts through a study of the local evaporation field conditions. With a better understanding of the local evaporation field, it may be possible to account for some of the local magnification effects during the reconstruction process, eliminating these artifacts before data analysis.

Atom Probe Analysis of Ex Situ Gas-Charged Stable Hydrides.

In this work, we report on the atom probe tomography analysis of two metallic hydrides formed by pressurized charging using an ex situ hydrogen charging cell, in the pressure range of 200-500 kPa (2-5 bar). Specifically we report on the deuterium charging of Pd/Rh and V systems. Using this ex situ system, we demonstrate the successful loading and subsequent atom probe analysis of deuterium within a Pd/Rh alloy, and demonstrate that deuterium is likely present within the oxide-metal interface of a native oxide formed on vanadium. Through these experiments, we demonstrate the feasibility of ex situ hydrogen analysis for hydrides via atom probe tomography, and thus a practical route to three-dimensional imaging of hydrogen in hydrides at the atomic scale.

Single-Ion Deconvolution of Mass Peak Overlaps for Atom Probe Microscopy.

Due to the intrinsic evaporation properties of the material studied, insufficient mass-resolving power and lack of knowledge of the kinetic energy of incident ions, peaks in the atom probe mass-to-charge spectrum can overlap and result in incorrect composition measurements. Contributions to these peak overlaps can be deconvoluted globally, by simply examining adjacent peaks combined with knowledge of natural isotopic abundances. However, this strategy does not account for the fact that the relative contributions to this convoluted signal can often vary significantly in different regions of the analysis volume; e.g., across interfaces and within clusters. Some progress has been made with spatially localized deconvolution in cases where the discrete microstructural regions can be easily identified within the reconstruction, but this means no further point cloud analyses are possible. Hence, we present an ion-by-ion methodology where the identity of each ion, normally obscured by peak overlap, is resolved by examining the isotopic abundance of their immediate surroundings. The resulting peak-deconvoluted data are a point cloud and can be analyzed with any existing tools. We present two detailed case studies and discussion of the limitations of this new technique.

Detecting Clusters in Atom Probe Data with Gaussian Mixture Models.

Accurately identifying and extracting clusters from atom probe tomography (APT) reconstructions is extremely challenging, yet critical to many applications. Currently, the most prevalent approach to detect clusters is the maximum separation method, a heuristic that relies heavily upon parameters manually chosen by the user. In this work, a new clustering algorithm, Gaussian mixture model Expectation Maximization Algorithm (GEMA), was developed. GEMA utilizes a Gaussian mixture model to probabilistically distinguish clusters from random fluctuations in the matrix. This machine learning approach maximizes the data likelihood via expectation maximization: given atomic positions, the algorithm learns the position, size, and width of each cluster. A key advantage of GEMA is that atoms are probabilistically assigned to clusters, thus reflecting scientifically meaningful uncertainty regarding atoms located near precipitate/matrix interfaces. GEMA outperforms the maximum separation method in cluster detection accuracy when applied to several realistically simulated data sets. Lastly, GEMA was successfully applied to real APT data.

Automated Atom-By-Atom Three-Dimensional (3D) Reconstruction of Field Ion Microscopy Data.

An automated procedure has been developed for the reconstruction of field ion microscopy (FIM) data that maintains its atomistic nature. FIM characterizes individual atoms on the specimen's surface, evolving subject to field evaporation, in a series of two-dimensional (2D) images. Its unique spatial resolution enables direct imaging of crystal defects as small as single vacancies. To fully exploit FIM's potential, automated analysis tools are required. The reconstruction algorithm developed here relies on minimal assumptions and is sensitive to atomic coordinates of all imaged atoms. It tracks the atoms across a sequence of images, allocating each to its respective crystallographic plane. The result is a highly accurate 3D lattice-resolved reconstruction. The procedure is applied to over 2000 tungsten atoms, including ion-implanted planes. The approach is further adapted to analyze carbides in a steel matrix, demonstrating its applicability to a range of materials. A vast amount of information is collected during the experiment that can underpin advanced analyses such as automated detection of "out of sequence" events, subangstrom surface displacements and defects effects on neighboring atoms. These analyses have the potential to reveal new insights into the field evaporation process and contribute to improving accuracy and scope of 3D FIM and atom probe characterization.

Comparing the Consistency of Atom Probe Tomography Measurements of Small-Scale Segregation and Clustering Between the LEAP 3000 and LEAP 5000 Instruments.

The local electrode atom probe (LEAP) has become the primary instrument used for atom probe tomography measurements. Recent advances in detector and laser design, together with updated hit detection algorithms, have been incorporated into the latest LEAP 5000 instrument, but the implications of these changes on measurements, particularly the size and chemistry of small clusters and elemental segregations, have not been explored. In this study, we compare data sets from a variety of materials with small-scale chemical heterogeneity using both a LEAP 3000 instrument with 37% detector efficiency and a 532-nm green laser and a new LEAP 5000 instrument with a manufacturer estimated increase to 52% detector efficiency, and a 355-nm ultraviolet laser. In general, it was found that the number of atoms within small clusters or surface segregation increased in the LEAP 5000, as would be expected by the reported increase in detector efficiency from the LEAP 3000 architecture, but subtle differences in chemistry were observed which are attributed to changes in the way multiple hit detection is calculated using the LEAP 5000.

Nanoscale Stoichiometric Analysis of a High-Temperature Superconductor by Atom Probe Tomography.

The functional properties of the high-temperature superconductor Y1Ba2Cu3O7-δ (Y-123) are closely correlated to the exact stoichiometry and oxygen content. Exceeding the critical value of 1 oxygen vacancy for every five unit cells (δ>0.2, which translates to a 1.5 at% deviation from the nominal oxygen stoichiometry of Y7.7Ba15.3Cu23O54-δ ) is sufficient to alter the superconducting properties. Stoichiometry at the nanometer scale, particularly of oxygen and other lighter elements, is extremely difficult to quantify in complex functional ceramics by most currently available analytical techniques. The present study is an analysis and optimization of the experimental conditions required to quantify the local nanoscale stoichiometry of single crystal yttrium barium copper oxide (YBCO) samples in three dimensions by atom probe tomography (APT). APT analysis required systematic exploration of a wide range of data acquisition and processing conditions to calibrate the measurements. Laser pulse energy, ion identification, and the choice of range widths were all found to influence composition measurements. The final composition obtained from melt-grown crystals with optimized superconducting properties was Y7.9Ba10.4Cu24.4O57.2.