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Abstract Grain boundaries in noble metal catalysts have been identified as critical sites for enhancing catalytic activity in electrochemical reactions such as the oxygen reduction reaction. However, conventional methods to modify grain boundary density often alter particle size, shape, and morphology, obscuring the specific role of grain boundaries in catalytic performance. This study addresses these challenges by employing gold nanoparticle assemblies to control grain boundary density through the manipulation of nanoparticle collision frequency during synthesis. We demonstrate a direct correlation between increased grain boundary density and enhanced two-electron oxygen reduction reaction activity, achieving a significant improvement in both specific and mass activity. Additionally, the gold nanoparticle assemblies with high grain boundary density exhibit remarkable electrochemical stability, attributed to boron segregation at the grain boundaries, which prevents structural degradation. This work provides a promising strategy for optimizing the activity, selectivity, and stability of noble metal catalysts through precise grain boundary engineering.

Abstract Aluminum alloys play an important role in circular metallurgy due to their good recyclability and 95% energy gain when made from scrap. Their low density and high strength translate linearly to lower greenhouse gas emissions in transportation, and their excellent corrosion resistance enhances product longevity. The durability of Al alloys stems from the dense barrier oxide film strongly bonded to the surface, preventing further degradation. However, despite decades of research, the individual elemental reactions and their influence on the nanoscale characteristics of the oxide film during corrosion in multicomponent Al alloys remain unresolved questions. Here, we build up a direct correlation between the near-atomistic picture of the corrosion oxide film and the solute reactivity in the aqueous corrosion of a high-strength Al-Zn-Mg-Cu alloy. We reveal the formation of nanocrystalline Al oxide and highlight the solute partitioning between the oxide and the matrix and segregation to the internal interface. The sharp decrease in partitioning content of Mg in the peak-aged alloy emphasizes the impact of heat treatment on the oxide stability and corrosion kinetics. Through H isotopic labelling with deuterium, we provide direct evidence that the oxide acts as a trap for this element, pointing at the essential role of the Al oxide might act as a kinetic barrier in preventing H embrittlement. Our findings advance the mechanistic understanding of further improving the stability of Al oxide, guiding the design of corrosion-resistant alloys for potential applications.

Abstract Chemical short-range order (CSRO) refers to atoms of specific elements self-organising within a disordered crystalline matrix to form particular atomic neighbourhoods. CSRO is typically characterized indirectly, using volume-averaged or through projection microscopy techniques that fail to capture the three-dimensional atomistic architectures. Here, we present a machine-learning enhanced approach to break the inherent resolution limits of atom probe tomography enabling three-dimensional imaging of multiple CSROs. We showcase our approach by addressing a long-standing question encountered in body-centred-cubic Fe-Al alloys that see anomalous property changes upon heat treatment. We use it to evidence non-statistical B2-CSRO instead of the generally-expected D03-CSRO. We introduce quantitative correlations among annealing temperature, CSRO, and nano-hardness and electrical resistivity. Our approach is further validated on modified D03-CSRO detected in Fe-Ga. The proposed strategy can be generally employed to investigate short/medium/long-range ordering phenomena in different materials and help design future high-performance materials.

Abstract Grain boundaries, the two-dimensional defects between differently oriented crystals, tend to preferentially attract solutes for segregation. Solute segregation has a significant effect on the mechanical and transport properties of materials. At the atomic level, however, the interplay of structure and composition of grain boundaries remains elusive, especially with respect to light interstitial solutes like B and C. Here, we use Fe alloyed with B and C to exploit the strong interdependence of interface structure and chemistry via charge-density imaging and atom probe tomography methods. Direct imaging and quantifying of light interstitial solutes at grain boundaries provide insight into decoration tendencies governed by atomic motifs. We find that even a change in the inclination of the grain boundary plane with identical misorientation impacts grain boundary composition and atomic arrangement. Thus, it is the smallest structural hierarchical level, the atomic motifs, that controls the most important chemical properties of the grain boundaries. This insight not only closes a missing link between the structure and chemical composition of such defects but also enables the targeted design and passivation of the chemical state of grain boundaries to free them from their role as entry gates for corrosion, hydrogen embrittlement, or mechanical failure.

[This corrects the article DOI: 10.1371/journal.pone.0281703.].

Abstract Retrieving information on the chemical and bonding states of atoms in a material in three-dimensions is challenging even for the most advanced imaging techniques. Here, we demonstrate that this information is accessible via straight-flight-path atom probe tomography experimental data, however it requires additional processing. Using an activation energy model that involves linear field dependance, and complementing it with DFT simulations, we extract the ion energy loss related to the kinetics of the field evaporation process from the mass peak shape. In turn, we reconstruct how evaporated atoms were originally bound to the surface. We name our data processing approach evaporation energy loss spectroscopy (FEELS), and showcase its application by analyzing microstructural features and defects in an array of metallic materials. Finally, we discuss the general applicability of FEELS to any atom probe data set.

Abstract Gas–solid reactions are important for many redox processes that underpin the energy and sustainability transition. The specific case of hydrogen‐based iron oxide reduction is the foundation to render the global steel industry fossil‐free, an essential target as iron production is the largest single industrial emitter of carbon dioxide. This perception of gas–solid reactions has not only been limited by the availability of state‐of‐the‐art techniques which can delve into the structure and chemistry of reacted solids, but one continues to miss an important reaction partner that defines the thermodynamics and kinetics of gas phase reactions: the gas molecules. In this investigation, cryogenic‐atom probe tomography is used to study the quasi in situ evolution of iron oxide in the solid and gas phases of the direct reduction of iron oxide by deuterium gas at 700°C. So far several unknown atomic‐scale characteristics are observed, including, D2 accumulation at the reaction interface; formation of a core (wüstite)‐shell (iron) structure; inbound diffusion of D through the iron layer and partitioning of D among phases and defects; outbound diffusion of oxygen through the wüstite and/or through the iron to the next free available inner/outer surface; and the internal formation of heavy nano‐water droplets at nano‐pores.

Abstract Iron making is the biggest single cause of global warming. The reduction of iron ores with carbon generates about 7% of the global carbon dioxide emissions to produce ≈1.85 billion tons of steel per year. This dramatic scenario fuels efforts to re‐invent this sector by using renewable and carbon‐free reductants and electricity. Here, the authors show how to make sustainable steel by reducing solid iron oxides with hydrogen released from ammonia. Ammonia is an annually 180 million ton traded chemical energy carrier, with established transcontinental logistics and low liquefaction costs. It can be synthesized with green hydrogen and release hydrogen again through the reduction reaction. This advantage connects it with green iron making, for replacing fossil reductants. the authors show that ammonia‐based reduction of iron oxide proceeds through an autocatalytic reaction, is kinetically as effective as hydrogen‐based direct reduction, yields the same metallization, and can be industrially realized with existing technologies. The produced iron/iron nitride mixture can be subsequently melted in an electric arc furnace (or co‐charged into a converter) to adjust the chemical composition to the target steel grades. A novel approach is thus presented to deploying intermittent renewable energy, mediated by green ammonia, for a disruptive technology transition toward sustainable iron making.

Field evaporation from ionic or covalently bonded materials often leads to the emission of molecular ions. The metastability of these molecular ions, particularly under the influence of the intense electrostatic field (10 ^10 Vm ^−1 ), makes them prone to dissociation with or without an exchange of energy amongst them. These processes can affect the analytical performance of atom probe tomography (APT). For instance, neutral molecules formed through dissociation may not be detected at all or with a time of flight no longer related to their mass, causing their loss from the analysis. Here, we evaluated the changes in the measured composition of FeO, Fe _2 O _3 and Fe _3 O _4 across a wide range of analysis conditions. Possible dissociation reactions are predicted by density-functional theory calculations considering the spin states of the molecules. The energetically favoured reactions are traced on to the multi-hit ion correlation histograms, to confirm their existence within experiments, using an automated Python-based routine. The detected reactions are carefully analyzed to reflect upon the influence of these neutrals from dissociation reactions on the performance of APT for analysing iron oxides.

High-strength Al alloys are sensitive to stress corrosion cracking and hydrogen embrittlement that limit their applications. Here the authors examine them at near-atomic scale using advanced microscopy and reveal hydrogen at dislocations and grain boundaries, and subsequent microstructural changes.

Production defects prevent many industrially important materials from being adopted by metal additive manufacturing. Here, the authors propose a universal thermodynamics-guided alloy design approach to assist the discovery of crack-free materials.

Interstitials can substantially strengthen metals. Here the authors show a massive interstitial solid solution (MISS) approach enabling a model multicomponent alloy to achieve near-theoretical strength together with large deformability.

Interest in the technique of low temperature environmental nanoindentation has gained momentum in recent years. Low temperature indentation apparatuses can, for instance, be used for systematic measurements of the mechanical properties of ice in the laboratory, in order to accurately determine the inputs for the constitutive equations describing the rheologic behaviour of natural ice (i.e., the Glen flow law). These properties are essential to predict the movement of glaciers and ice sheets over time as a response to a changing climate. Herein, we introduce a new experimental setup and protocol for electron microscope loading and in situ nanoindentation of water ice. Preliminary testing on pure water ice yield elastic modulus and hardness measurements of 4.1 GPa and 176 MPa, respectively, which fall within the range of previously published values. Our approach demonstrates the potential of low temperature, in situ, instrumented nanoindentation of ice under controlled conditions in the SEM, opening the possibility for investigating individual structural elements and systematic studies across species and concentration of impurities to refine to constitutive equations for natural ice.

Layered LiMO2 (M = Ni, Co, Mn, and Al mixture) cathode materials used for Li‐ion batteries are reputed to be highly reactive through their surface, where the chemistry changes rapidly when exposed to ambient air. However, conventional electron/spectroscopy‐based techniques or thermogravimetric analysis fails to capture the underlying atom‐scale chemistry of vulnerable Li species. To study the evolution of the surface composition at the atomic scale, cryogenic atom probe tomography is used herein and the surface species formed during exposure of a LiNi0.8Mn0.1Co0.1O2 (NMC811) cathode material to air are probed. The compositional analysis evidences the formation of Li2CO3. Site‐specific examination from a cracked region of an NMC811 particle also reveals the predominant presence of Li2CO3. These insights will help to design improved protocols for cathode synthesis and cell assembly, as well as critical knowledge for cathode degradation.

Common wisdom to improve ductility of bulk metallic glasses (BMGs) is to introduce local loose packing regions at the expense of strength. Here the authors enhance structural fluctuations of BMGs by introducing dense local packing regions, resulting in simultaneous increase of ductility and strength.

Wear-resistant metals have long been a pursuit of reducing wear-related energy and material loss. Here the authors present the ‘reactive wear protection’ strategy via friction-induced in situ formation of strong and deformable oxide nanocomposites on a surface.

Abstract The development of strong-scaling computational tools for high-throughput methods with an open-source code and transparent metadata standards has successfully transformed many computational materials science communities. While such tools are mature already in the condensed-matter physics community, the situation is still very different for many experimentalists. Atom probe tomography (APT) is one example. This microscopy and microanalysis technique has matured into a versatile nano-analytical characterization tool with applications that range from materials science to geology and possibly beyond. Here, data science tools are required for extracting chemo-structural spatial correlations from the reconstructed point cloud. For APT and other high-end analysis techniques, post-processing is mostly executed with proprietary software tools, which are opaque in their execution and have often limited performance. Software development by members of the scientific community has improved the situation but compared to the sophistication in the field of computational materials science several gaps remain. This is particularly the case for open-source tools that support scientific computing hardware, tools which enable high-throughput workflows, and open well-documented metadata standards to align experimental research better with the fair data stewardship principles. To this end, we introduce paraprobe, an open-source tool for scientific computing and high-throughput studying of point cloud data, here exemplified with APT. We show how to quantify uncertainties while applying several computational geometry, spatial statistics, and clustering tasks for post-processing APT datasets as large as two billion ions. These tools work well in concert with Python and HDF5 to enable several orders of magnitude performance gain, automation, and reproducibility.

Abstract Segregation to grain boundaries affects their cohesion, corrosion, and embrittlement and plays a critical role in heterogeneous nucleation. In order to quantitatively study segregation and low-dimensional phase separation at grain boundaries, here, we apply a density-based phase-field model. The current model describes the grain-boundary thermodynamic properties based on available bulk thermodynamic data, while the grain-boundary-density profile is obtained using atomistic simulations. To benchmark the performance of the model, Mn grain-boundary segregation in the Fe–Mn system is studied. 3D simulation results are compared against atom probe tomography measurements conducted for three alloy compositions. We show that a continuous increase in the alloy composition results in a discontinuous jump in the segregation isotherm. The jump corresponds to a spinodal phase separation at grain boundary. For alloy compositions above the jump, we reveal an interfacial transient spinodal phase separation. The transient spinodal phenomenon opens opportunities for knowledge-based microstructure design through the chemical manipulation of grain boundaries. The proposed density-based model provides a powerful tool to study thermodynamics and kinetics of segregation and phase changes at grain boundaries.

The longevity of a lithium-ion battery is limited by cathode degradation. Combining atom probe tomography and scanning transmission electron microscopy reveals that the degradation results from atomic-scale irreversible structural changes once lithium leaves the cathode during charging, thereby inhibiting lithium intercalation back into the cathode as the battery discharges. This information unveils possible routes for improving the lifetime of lithium-ion batteries.

Atom probe tomography can image chemical composition at the nanoscale, but our understanding of how it images voids, or empty spaces, is still lacking. Here, the authors combine atom probe tomography, scanning transmission electron microscopy, and field-evaporation theory to show how voids are imaged and subsequently measured.

Adding minute amounts of rhenium to Ni-based single crystal superalloys extends their high temperature performance in engines, but the reasons behind that are still unclear. Here, the authors combine high resolution imaging and modelling to show that rhenium enriches and slows down partial dislocations to improve creep performance.

Hydrogen embrittlement can cause a dramatic deterioration of the mechanical properties of high-strength metallic materials. Despite decades of experimental and modelling studies, the exact underlying mechanisms behind hydrogen embrittlement remain elusive. To unlock understanding of the mechanism and thereby help mitigate the influence of hydrogen and the associated embrittlement, it is essential to examine the interactions of hydrogen with structural defects such as grain boundaries, dislocations and stacking faults. Atom probe tomography (APT) can, in principle, analyse hydrogen located specifically at such microstructural features but faces strong challenges when it comes to charging specimens with hydrogen or deuterium. Here, we describe three different workflows enabling hydrogen/deuterium charging of site-specific APT specimens: namely cathodic, plasma and gas charging. All the experiments in the current study have been performed on a model twinning induced plasticity steel alloy. We discuss in detail the caveats of the different approaches in order to help future research efforts and facilitate further studies of hydrogen in metals. Our study demonstrates successful cathodic and gas charging, with the latter being more promising for the analysis of the high-strength steels at the core of our work.

Numerous metallurgical and materials science applications depend on quantitative atomic-scale characterizations of environmentally-sensitive materials and their transient states. Studying the effect upon materials subjected to thermochemical treatments in specific gaseous atmospheres is of central importance for specifically studying a material’s resistance to certain oxidative or hydrogen environments. It is also important for investigating catalytic materials, direct reduction of an oxide, particular surface science reactions or nanoparticle fabrication routes. This manuscript realizes such experimental protocols upon a thermochemical reaction chamber called the "Reacthub" and allows for transferring treated materials under cryogenic & ultrahigh vacuum (UHV) workflow conditions for characterisation by either atom probe or scanning Xe+/electron microscopies. Two examples are discussed in the present study. One protocol was in the deuterium gas charging (25 kPa D2 at 200°C) of a high-manganese twinning-induced-plasticity (TWIP) steel and characterization of the ingress and trapping of hydrogen at various features (grain boundaries in particular) in efforts to relate this to the steel’s hydrogen embrittlement susceptibility. Deuterium was successfully detected after gas charging but most contrast originated from the complex ion FeOD+ signal and the feature may be an artefact. The second example considered the direct deuterium reduction (5 kPa D2 at 700°C) of a single crystal wüstite (FeO) sample, demonstrating that under a standard thermochemical treatment causes rapid reduction upon the nanoscale. In each case, further studies are required for complete confidence about these phenomena, but these experiments successfully demonstrate that how an ex-situ thermochemical treatment can be realised that captures environmentally-sensitive transient states that can be analysed by atomic-scale by atom probe microscope.

Quantitative imaging on the doping in phase-change materials for data storage remains scarce. Here, the authors combine electron microscopy, atom probe tomography, and simulations to determine the role of indium and silver dopants during recrystallization.

Hydrogen contamination in metals during sample preparation for high-resolution microscopy remains a challenge, especially when hydrogen itself is being investigated. Here, the authors show that using cryogenic milling significantly reduces hydrogen pick-up during sample preparation of titanium and titanium alloys.

Summary: Mass spectrometry is a widespread approach used to work out what the constituents of a material are. Atoms and molecules are removed from the material and collected, and subsequently, a critical step is to infer their correct identities based on patterns formed in their mass-to-charge ratios and relative isotopic abundances. However, this identification step still mainly relies on individual users' expertise, making its standardization challenging, and hindering efficient data processing. Here, we introduce an approach that leverages modern machine learning technique to identify peak patterns in time-of-flight mass spectra within microseconds, outperforming human users without loss of accuracy. Our approach is cross-validated on mass spectra generated from different time-of-flight mass spectrometry (ToF-MS) techniques, offering the ToF-MS community an open-source, intelligent mass spectra analysis. The bigger picture: Time-of-flight mass spectrometry (ToF-MS) is a mainstream analytical technique widely used in biology, chemistry, and materials science. ToF-MS provides quantitative compositional analysis with high sensitivity across a wide dynamic range of mass-to-charge ratios. A critical step in ToF-MS is to infer the identity of the detected ions. Here, we introduce a machine-learning-enhanced algorithm to provide a user-independent approach to performing this identification using patterns from the natural isotopic abundances of individual atomic and molecular ions, without human labeling or prior knowledge of composition. Results from several materials and techniques are compared with those obtained by field experts. Our open-source, easy-to-implement, reliable analytic method accelerates this identification process. A wide range of ToF-MS-based applications can benefit from our approach, e.g., hunting for patterns of biomarkers or for contamination on solid surfaces in high-throughput data.

Quantum mechanically guided materials design has been used to predict the mechanical property trends in crystalline materials. Thereby, the identification of composition-structure-property relationships is enabled. However, quantum mechanics based design guidelines and material selection criteria for ultra-strong metallic glasses have been lacking. Hence, based on an ab initio model for metallic glasses in conjunction with an experimental high-throughput methodology geared toward revealing the relationship between chemistry, topology and mechanical properties, we propose principles for the design of tough as well as stiff metallic glasses. The main design notion is that a low fraction of hybridized bonds compared to the overall bonding in a metallic glass can be used as a criterion for the identification of damage-tolerant metallic glass systems. To enhance the stiffness of metallic glasses, the bond energy density must be increased as the bond energy density is the origin of stiffness in metallic glasses. The thermal expansion, which is an important glass-forming identifier, can be predicted based on the Debye-Grüneisen model.

Focused-ion beam lift-out and annular milling is the most common method used for obtaining site specific specimens for atom probe tomography (APT) experiments and transmission electron microscopy. However, one of the main limitations of this technique comes from the structural damage as well as chemical degradation caused by the beam of high-energy ions. These aspects are especially critical in highly-sensitive specimens. In this regard, ion beam milling under cryogenic conditions has been an established technique for damage mitigation. Here, we implement a cryo-focused ion beam approach to prepare specimens for APT measurements from a quadruple cation perovskite-based solar cell device with 19.7% efficiency. As opposed to room temperature FIB milling we found that cryo-milling considerably improved APT results in terms of yield and composition measurement, i.e. halide loss, both related to less defects within the APT specimen. Based on our approach we discuss the prospects of reliable atom probe measurements of perovskite based solar cell materials. An insight into the field evaporation behavior of the organic-inorganic molecules that compose the perovskite material is also given with the aim of expanding the applicability of APT experiments towards nano-characterization of complex organo-metal materials.

High fracture toughness is crucial for the application of metallic glasses as structural materials to avoid catastrophic failure of the material in a brittle manner. One fingerprint for fracture toughness in metallic glasses is the fraction of hybridized bonds, which is affected by alloying Pd57.4Al23.5Y7.8M11.3 with M = Fe, Ni, Co, Cu, Os, Ir, Pt, and Au. It is shown that experimental fracture toughness data is correlated to the fraction of hybridized bonds which scale with the localized bonds at the Fermi level. Thus, the localized bonds at the Fermi level are utilized quantitatively as a measure for fracture toughness. Based on ab initio calculations, the minimum fraction of hybridized bonds was identified for Pd57.4Al23.5Y7.8Ni11.3. According to the ansatz that the crystal orbital overlap population at the Fermi level scales with fracture toughness, for Pd57.4Al23.5Y7.8Ni11.3 a value of around 95 ± 20 MPa·m0.5 is predicted quantitatively for the first time. Consistent with this prediction, in micro-mechanical beam bending experiments Pd57.4Al23.5Y7.8Ni11.3 thin films show pronounced plasticity and absence of crack growth. Keywords: Metallic glass, Ab initio, Fracture toughness, Chemical bonding

Atom probe tomography (APT) analysis is being actively used to provide near-atomic-scale information on the composition of complex materials in three-dimensions. In recent years, there has been a surge of interest in the technique to investigate the distribution of hydrogen in metals. However, the presence of hydrogen in the analysis of almost all specimens from nearly all material systems has caused numerous debates as to its origins and impact on the quantitativeness of the measurement. It is often perceived that most H arises from residual gas ionization, therefore affecting primarily materials with a relatively low evaporation field. In this work, we perform systematic investigations to identify the origin of H residuals in APT experiments by combining density-functional theory (DFT) calculations and APT measurements on an alkali and a noble metal, namely Na and Pt, respectively. We report that no H residual is found in Na metal samples, but in Pt, which has a higher evaporation field, a relatively high signal of H is detected. These results contradict the hypothesis of the H signal being due to direct ionization of residual H _2 without much interaction with the specimen’s surface. Based on DFT, we demonstrate that alkali metals are thermodynamically less likely to be subject to H contamination under APT-operating conditions compared to transition or noble metals. These insights indicate that the detected H-signal is not only from ionization of residual gaseous H _2 alone, but is strongly influenced by material-specific physical properties. The origin of H residuals is elucidated by considering different conditions encountered during APT experiments, specifically, specimen-preparation, transportation, and APT-operating conditions by taking thermodynamic and kinetic aspects into account.

Sodium doping is necessary to achieve high performance in polycrystalline chalcopyrite solar cells, but retards gallium interdiffusion, and thus efficiency optimisation. Here, Colombara et al. show that in contrast to the polycrystalline case, sodium accelerates atomic interdiffusion in monocrystalline samples.

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.

This study focuses on the synthesis of FeRh nanoparticles via pulsed laser ablation in liquid and on controlling the oxidation of the synthesized nanoparticles. Formation of monomodal γ-FeRh nanoparticles was confirmed by transmission electron microscopy (TEM) and their composition confirmed by atom probe tomography (APT). For these particles, three major contributors to oxidation were analysed: (1) dissolved oxygen in the organic solvents, (2) the bound oxygen in the solvent and (3) oxygen in the atmosphere above the solvent. The decrease of oxidation for optimized ablation conditions was confirmed through energy-dispersive X-ray (EDX) and Mössbauer spectroscopy. Furthermore, the time dependence of oxidation was monitored for dried FeRh nanoparticles powders using ferromagnetic resonance spectroscopy (FMR). By magnetophoretic separation, B2-FeRh nanoparticles could be extracted from the solution and characteristic differences of nanostrand formation between γ-FeRh and B2-FeRh nanoparticles were observed.

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

We present sample transfer instrumentation and integrated protocols for the preparation and atom probe characterization of environmentally-sensitive materials. Ultra-high vacuum cryogenic suitcases allow specimen transfer between preparation, processing and several imaging platforms without exposure to atmospheric contamination. For expedient transfers, we installed a fast-docking station equipped with a cryogenic pump upon three systems; two atom probes, a scanning electron microscope / Xe-plasma focused ion beam and a N2-atmosphere glovebox. We also installed a plasma FIB with a solid-state cooling stage to reduce beam damage and contamination, through reducing chemical activity and with the cryogenic components as passive cryogenic traps. We demonstrate the efficacy of the new laboratory protocols by the successful preparation and transfer of two highly contamination- and temperature-sensitive samples-water and ice. Analysing pure magnesium atom probe data, we show that surface oxidation can be effectively suppressed using an entirely cryogenic protocol (during specimen preparation and during transfer). Starting with the cryogenically-cooled plasma FIB, we also prepared and transferred frozen ice samples while avoiding significant melting or sublimation, suggesting that we may be able to measure the nanostructure of other normally-liquid or soft materials. Isolated cryogenic protocols within the N2 glove box demonstrate the absence of ice condensation suggesting that environmental control can commence from fabrication until atom probe analysis.

Directly imaging all atoms constituting a material and, maybe more importantly, crystalline defects that dictate materials’ properties, remains a formidable challenge. Here, we propose a new approach to chemistry-sensitive field-ion microscopy (FIM) combining FIM with time-of-flight mass-spectrometry ( tof-ms ). Elemental identification and correlation to FIM images enabled by data mining of combined tof-ms delivers a truly analytical-FIM (A-FIM). Contrast variations due to different chemistries is also interpreted from density-functional theory (DFT). A-FIM has true atomic resolution and we demonstrate how the technique can reveal the presence of individual solute atoms at specific positions in the microstructure. The performance of this new technique is showcased in revealing individual Re atoms at crystalline defects formed in Ni–Re binary alloy during creep deformation. The atomistic details offered by A-FIM allowed us to directly compare our results with simulations, and to tackle a long-standing question of how Re extends lifetime of Ni-based superalloys in service at high-temperature.

The cold emission of particles from surfaces under intense electric fields is a process which underpins a variety of applications including atom probe tomography (APT), an analytical microscopy technique with near-atomic spatial resolution. Increasingly relying on fast laser pulsing to trigger the emission, APT experiments often incorporate the detection of molecular ions emitted from the specimen, in particular from covalently or ionically bonded materials. Notably, it has been proposed that neutral molecules can also be emitted during this process. However, this remains a contentious issue. To investigate the validity of this hypothesis, a careful review of the literature is combined with the development of new methods to treat experimental APT data, the modeling of ion trajectories, and the application of density-functional theory simulations to derive molecular ion energetics. It is shown that the direct thermal emission of neutral molecules is extremely unlikely. However, neutrals can still be formed in the course of an APT experiment by dissociation of metastable molecular ions.