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Pair distribution function (PDF) analysis is a powerful technique to understand atomic scale structure in materials science. Unlike X-ray diffraction (XRD)-based PDF analysis, the PDF calculated from electron diffraction patterns (EDPs) using transmission electron microscopy can provide structural information from specific locations with high spatial resolution. The present work describes a new software tool for both periodic and amorphous structures that addresses several practical challenges in calculating the PDF from EDPs. The key features of this program include accurate background subtraction using a nonlinear iterative peak-clipping algorithm and automatic conversion of various types of diffraction intensity profiles into a PDF without requiring external software. The present study also evaluates the effect of background subtraction and the elliptical distortion of EDPs on PDF profiles. The EDP2PDF software is offered as a reliable tool to analyse the atomic structure of crystalline and non-crystalline materials.

Zr-based bulk metallic glasses (BMGs) are amorphous alloys that can exhibit excellent mechanical properties, including high yield strength and fracture toughness. These properties are linked to local microstructural heterogeneities. Whether via microscopy-based techniques, synchrotron techniques, or calorimetric approaches, the amorphous structure of BMGs makes the characterisation of the details of these local structural and chemical heterogeneities extremely challenging. Our focus here is on atom probe tomography (APT), where considerable uncertainty remains in terms of how and when to apply this otherwise powerful technique to amorphous materials. This work reports a systematic evaluation of the experimental parameter space. We report results of BMG composition acquired against various APT operating parameters for Zr63.96Cu13.36Ni10.29Al11.04Nb1.25 (at. %). We demonstrate that a customised peak-based ranging approach yields satisfactory compositional accuracy with absolute errors of

Bulk metallic glasses (BMGs) are materials with outstanding strength and elastic properties that make them tantalizing for engineering applications, yet our poor understanding of how their amorphous atomic arrangements control their broader mechanical properties (hardness, wear, fracture, etc.) impedes our ability to apply materials science principles in their design. In this work, we uncover the hierarchical structure that exists in BMGs across the nano- to microscale by using nanobeam electron diffraction experiments. Our findings reveal that local hardness of microscale domains decreases with increasing size and volume fraction of atomic clusters with higher local medium range order (MRO). Furthermore, we propose a model of ductile phase softening that will enable the future design of BMGs by tuning the MRO size and distribution in the nanostructure.

Atom probe tomography, and related methods, probe the composition and the three-dimensional architecture of materials. The software tools which microscopists use, and how these tools are connected into workflows, make a substantial contribution to the accuracy and precision of such material characterization experiments. Typically, we adapt methods from other communities like mathematics, data science, computational geometry, artificial intelligence, or scientific computing. We also realize that improving on research data management is a challenge when it comes to align with the FAIR data stewardship principles. Faced with this global challenge, we are convinced it is useful to join forces. Here, we report the results and challenges with an inter-laboratory call for developing test cases for several types of atom probe microscopy software tools. The results support why defining detailed recipes of software workflows and sharing these recipes is necessary and rewarding: Open source tools and (meta)data exchange can help to make our day-to-day data processing tasks become more efficient, the training of new users and knowledge transfer become easier, and assist us with automated quantification of uncertainties to gain access to substantiated results.

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.

The present work studies the strengthening mechanisms of a creep-resistant Mg-0.5Gd-1.2Ca (at.%) alloy at both room and elevated temperatures. Although peak-ageing (T6) at 180 °C for 32 h led to a significant increase in room temperature strength due to the precipitation strengthening by three types of precipitates (Mg2Ca, Mg5Gd on prismatic planes and a new type of Mg–Gd–Ca intermetallic compound on the basal plane), the as-solid solution treated (T4) alloy exhibited better resistance to temperature softening during compression and to stress relaxation at 180 °C and better creep resistance at 210 °C/100 MPa. The Gd–Ca co-clusters with short-range order in the Mg solid solution, which was verified, at the first time, by atom probe tomography (APT) analysis and atomic-resolution high angle annular dark field-scanning transmission electron microscopy (HAADF-STEM), were responsible for the solid solution hardening, offering a more effective strengthening effect through local order-strengthening. Such solid solution strengthening increased the thermal stability of the alloy structure at elevated temperatures, at least at early stage of the creep. Subsequently, dynamic precipitation started contributing to the creep resistance due to the formation of higher density of precipitates. However, in the T6 alloy, creep testing at elevated temperatures, particularly at 210 °C that was higher than the ageing temperature, led to coarsening of the precipitates, which acted as over ageing. As a result of such over ageing, the resistance of the T6 alloy to heat-induced softening was weakened, leading to lower creep resistance than the T4 alloy.

Boron (B) and phosphorous (P) co-doped colloidal silicon nanocrystals (Si NCs) have unique size-dependent optical properties, which lead to potential applications in optoelectronic and biomedical applications. However, the microstructure of the B and P co-doped colloidal Si NCs – in particular, the exact location of the dopant atoms in real space, has not been studied. A lack of understanding of this underlying question limits our ability to better control sample fabrication, as well as our ability to further develop the optical properties. To study the microstructure, a process enabling atom probe tomography (APT) of colloidal Si NCs was developed. A dispersion of colloidal Si NCs in a SiO2 sol-gel solution and a low temperature curing are demonstrated as the key sample preparation steps. Our APT results demonstrate that a B-rich region exists at the surface of the Si NCs, while P atoms are distributed within the Si NCs. First principles density functional theory calculations of a Si NC embedded in SiO2 matrix reveal that P atoms, which always prefer to reside inside a Si NC, significantly influence the distribution of B atoms. Specifically, P atoms lower the B diffusion barrier at Si/SiO2 interface and stabilize B atoms to reside within individual Si NCs. We propose that the B-modified surface changes the chemical properties of the Si NCs by (i) offering chemical resistance to attack by HF and (ii) enabling dispersibility in solution without aggregation.

In this study, the microstructure and mechanical properties, especially the impacts of low-temperature tempering, of the medium-Mn martensitic steel were examined. The low-temperature tempering simulated paint baking in car manufacturing. Significant improvement of tensile ductility was achieved by baking, associating with a change from brittle to ductile fracture behavior. The ductilization was attributed to the carbon re-distribution during baking, as allowed by the high volume fraction of retained austenite (15 pct). The carbon distribution was characterized by Atom Probe Tomography. The baked medium-Mn martensitic steel presents an excellent strength–ductility combination, which is a promising candidate as next-generation high-performance steels for vehicle lightweighting.

We define a measure for the accuracy of tomographic reconstruction in atom probe tomography, named here the spatial error index. We demonstrate that this index can be used to compare rigorously the spatial accuracy of various different approaches to the calculation of tomographic reconstruction. This is useful, for example, to evaluate the performance of alternate tomographic reconstruction approaches, and ensures that the comparisons are independent of individual data quality or other instrumental parameters. We then introduce a new “adaptive reconstruction” formalism that uses a progression of reconstruction parameters based on a per-atom correction from the cube root of the inverse of the voltage, along with linear correction factors linked to the evaporation sequence. We apply the measure for spatial accuracy to this new reconstruction protocol.

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 SiO2 matrix 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 SiO2 matrix. 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 SiO2 matrix with the aid of oxygen vacancies. These findings will be useful towards future optoelectronic applications.

Grain size stabilization is crucial for the production and application of nanocrystalline (NC) materials. The mechanically alloyed (MA) NC Fe-Zr system is known as a very successful NC system as it exhibits excellent thermal stability at elevated temperatures. The grain size stabilization of this system has been previously ascribed to its reduced grain boundary (GB) energy by Zr segregation and Zener pinning of Zr-rich intermetallic precipitates. In this work, we report a different mechanism that significantly contributes to grain size stabilization of this NC alloy system using two MA-produced NC Fe-Zr alloys (Fe-1 at.% Zr and Fe-5 at.% Zr) as examples. We show by using atom probe tomography and Cs-corrected transmission electron microscopy that highly dispersed coherent Fe-Zr-O nanoclusters, with a number density up to 1024 m−3, form in ferrite matrix after annealing at certain temperatures. Our first-principles calculations indicate that the formation of these nanoclusters is caused by the ordering of Zr and O-impurity in ferrite matrix. We analyzed the underlying mechanism of grain size stabilization in terms of the experimental results and the Zener pinning theory, and suggest that the pinning effect exerted by these nanoclusters significantly contributes to grain size stabilization of the NC Fe-Zr alloys.

The structural and chemical changes at omega/beta interfaces and the evolution of the morphology of omega in a near-beta alloy during isothermal ageing at 573 K were investigated by atom probe tomography and aberration-corrected high-resolution transmission electron microscopy. Ledges and local O enrichment at semi-coherent isothermal omega interfaces are proposed to provide the key driving force for nucleation of omega-assisted alpha. Following nucleation of alpha, the morphology of omega evolves from ellipsoidal to rod-like, induced by rapid consumption of omega by alpha.

The split quenching and partitioning (S-QP) process allows researchers to investigate microstructure and properties separately, i.e., before and after partitioning. After the partitioning process, the yield strength increases by approximately 300 MPa in the ferrite-bearing δ-quenching and partitioning (δ-QP) steel. We propose that carbon trapping in dislocations at the ferrite grain boundaries during partitioning process is responsible for the yield strength enhancement of ferrite. Combined transmission electron microscopy and 3D atom probe tomography observations demonstrate carbon atoms segregating in dislocations. The mechanisms for the high yield strength of ferrite presented QP steels are clarified for the first time in this research.

Atom probe tomography was used to analyze self-assembled monolayers of thiophene on different surfaces, including tungsten, platinum, and aluminum, where the tungsten was examined in both pristine and oxidized forms. A glovebag with controlled atmospheres was used to alter the level of oxidation for tungsten. It was shown that different substrates lead to substantial changes in the way thiophene adsorbs on the surface. Furthermore, the oxidation of the surface strongly influenced the adsorption behavior of the thiophene molecules, leading to clear differences in the amounts and compositions of field evaporated ions and molecular ions.

The microstructure of boron (B) and phosphorus (P) codoped silicon (Si) nanocrystals (NCs), cubic boron phosphide (BP) NCs and their mixed NCs (BxSiyPz NCs) has been studied using atom probe tomography (APT), transmission electron microscopy (TEM), and Raman scattering spectroscopy. The BxSiyPz NCs inherit superior properties of B and P codoped Si NCs such as high dispersibility in aqueous media and near infrared (NIR) luminescence and those of cubic BP NCs such as high chemical stability. The microanalyses revealed that BxSiyPz NCs are composed of a crystalline core and an amorphous shell. The core possesses a lattice constant between that of Si (diamond-cubic) and BP (cubic). The amorphous shell is comprised of B, Si and P, though the composition is not uniform and there are local B-rich, Si-rich and P-rich domains connected contiguously. The amorphous shell is proposed to be responsible for their superior chemical properties such as high dispersibility in polar solvents and high resistance to acids, and the crystalline core is responsible for the stable NIR luminescence.

A lightweight (5.06 g cm −3 ) AlTiVCr compositionally complex alloy consisting of four elements is presented. Interest in the system is due to its microstructural uniformity and the use of commodity elements. The focus of the present work was to highlight the systematic microstructural and chemical characterization – and the information gained by application of various physical and modeling techniques in concert – in the context of complete characterization of compositionally complex alloys. Herein, analysis of as-cast AlTiVCr was investigated via conventional and scanning transmission electron microscopy, revealing a simple, single-phase microstructure. Characterization was supported by atom probe tomography and X-ray diffraction, whilst first-principles calculations based on density functional theory (DFT) were employed to calculate the thermodynamic and structural properties of the AlTiVCr alloy. The study was able to reveal the unique atomic locations in the alloy, whilst revealing that the B2 phase has a lower formation enthalpy (−9.30 kJ/mol atom) and is more stable than the disordered BCC phase (−1.25 kJ/mol atom) at low temperatures. The study herein provides insight into the combined analysis methods as relevant to the study of compositionally complex and high entropy alloys, indicating means of unambiguous characterization employing generalized multicomponent short range order analysis.

We analyze phosphorus (P)- and boron (B)-doped silicon nanocrystals (Si NCs) with various compositions of silicon-rich oxide using atom probe tomography. By creating Si iso-concentration surfaces, it is confirmed that there are two types of Si NC networks depending on the amount of excess Si. A proximity histogram shows that P prefers to locate inside the Si NCs, whereas B is more likely to reside outside the Si NCs. We discuss the difference in a preferential location between P and B by a segregation coefficient.

Silicon nanocrystals (Si NCs) are intensively studied for optoelectronic and biological applications due to having highly attractive features such as band engineering. Although doping is often used to control the optical and electrical properties, the related structural properties of solely doped and codoped Si NCs are not well-understood. In this study, we report the boron (B) and/or phosphorus (P) distribution in Si NCs embedded in borosilicate glass (BSG), phosphosilicate glass (PSG), and borophosphosilicate glass (BPSG) using atom probe tomography (APT). We compared solely and codoped Si NCs grown at different temperatures so that we may compare the effects of codoping and temperature on the B and/or P distribution. Proximity histograms and cluster analyses reveal that there exist boron-rich layers surrounding Si NCs and also B–P clusters within the Si NCs. Raman spectra also show a structural change between codoped Si NCs in solids and free-standing codoped Si NCs. These results lead us to understand...

Materials that undergo a reversible change of crystal structure through martensitic transformation (MT) possess unusual functionalities including shape memory, superelasticity, and low/negative thermal expansion. These properties have many advanced applications, such as actuators, sensors, and energy conversion, but are limited typically in a narrow temperature range of tens of Kelvin. Here we report that, by creating a nano-scale concentration modulation via phase separation, the MT can be rendered continuous by an in-situ elastic confinement mechanism. Through a model titanium alloy, we demonstrate that the elastically confined continuous MT has unprecedented properties, such as superelasticity from below 4.2 K to 500 K, fully tunable and stable thermal expansion, from positive, through zero, to negative, from below 4.2 K to 573 K, and high strength-to-modulus ratio across a wide temperature range. The elastic tuning on the MT, together with a significant extension of the crystal stability limit, provides new opportunities to explore advanced materials.

The precipitation behaviors of Zr–rich phase in binary Al–0.5Zr and ternary Al–3Si–0.5Zr alloys were investigated by high resolution transmission electron microscopy and atom probe. After the alloys were aged at 525 °C for 24 h, the precipitates in Al–0.5Zr alloy are identified as L12–ZrAl3, performing a coherent relationship with the Al matrix. While in Al–3Si–0.5Zr alloy, the precipitates are Si–containing D023–Zr(Al,Si)3, which has an approximate 90° reversed cube–on–cube orientation relationship with Al. It is regarded that Si accelerates the precipitation of D023–Zr(Al,Si)3.

Current approaches to reconstruction in atom probe tomography produce results that exhibit substantial distortions throughout the analysis depth. This is largely because of the need to apply a multitude of assumptions when estimating the evolution of the tip shape, and other pseudo-empirical reconstruction factors, which vary both across the face of the tip and throughout the analysis depth. We introduce a new crystallography-mediated reconstruction to improve the spatial accuracy and dramatically reduce these in-depth variations. To achieve this, we developed a barycentric transform to directly relate atomic positions in detector space to real space. This is mediated by novel crystallographic analysis techniques, including: (1) calculating the orientation of a crystal directly from the field evaporation map, (2) tracking pole locations throughout the evaporation sequence, and (3) accounting for the evolving tip radius in a manner that removes the dependence on the geometric field factor. By improving the in-depth spatial accuracy of the atom probe reconstruction, a greater accuracy of the atomic neighborhood relationships is available. This is critical in modern materials science and engineering, where an understanding of the solid solution architecture, precipitate dispersions, and descriptions of the interfaces between phases or grains are key inputs to microstructure–property relationships.

For multicomponent near-β alloys, we have investigated the mechanisms responsible for the β-to-ω and ω-to-α phase transformations upon isothermal ageing at 573 K. Experimental evidence from atom probe tomography and aberration-corrected high-resolution transmission electron microscopy indicates that the formation of isothermal ω involves a structural reconstruction assisted by nanoscale spinodal decomposition of the β matrix, prior to the specific chemistry change required to form ω, rather than a mixed-mode process with structure and chemistry changes occurring simultaneously as has been previously suggested. First, incommensurate embryonic ω evolve via a displacive mechanism within Mo-lean regions created by second-order coherent spinodal decomposition of the β matrix. The subtle spinodal decomposition in β and chemistry of embryonic ω are carefully analysed by an advanced atom probe data analysis algorithm. When the size of embryonic ɷ exceeds a critical value, commensurate isothermal ɷ forms through the exit of the other alloying solutes. O-rich regions present at the isothermal ω/β interface provide potent sites for the formation of α. The concurrent compositional partitioning of solutes in ɷ and α indicates the transformation from ω to α involves both a rapid lattice reconstruction at the ω/α interface and a slow Al diffusion at the α/β, therefore a mixed-mode displacive-diffusive process. This study provides novel experimental evidence to understand the much-disputed transformation processes and elucidate the mechanisms responsible for these important phase transformations.

We study an Fe–18Al (at.%) alloy after various thermal treatments at different times (24–336 h) and temperatures (250–1100 °C) to determine the nature of the so-called ‘komplex’ phase state (or “K-state”), which is common to other alloy systems having compositions at the boundaries of known order-disorder transitions and is characterised by heterogeneous short-range-ordering (SRO). This has been done by direct observation using atom probe tomography (APT), which reveals that nano-sized, ordered regions/particles do not exist. Also, by employing shell-based analysis of the three-dimensional atomic positions, we have determined chemically sensitive, generalised multicomponent short-range order (GM-SRO) parameters, which are compared with published pairwise SRO parameters derived from bulk, volume-averaged measurement techniques (e.g. X-ray and neutron scattering, Mossbauer spectroscopy) and combined ab-initio and Monte Carlo simulations. This analysis procedure has general relevance for other alloy systems where quantitative chemical-structure evaluation of local atomic environments is required to understand ordering and partial ordering phenomena that affect physical and mechanical properties.

In this article, after a brief introduction to the principles behind atom probe crystallography, we introduce methods for unambiguously determining the presence of crystal planes within atom probe datasets, as well as their characteristics: location; orientation and interplanar spacing. These methods, which we refer to as plane orientation extraction (POE) and local crystallography mapping (LCM) make use of real-space data and allow for systematic analyses. We present here application of POE and LCM to datasets of pure Al, industrial aluminium alloys and doped-silicon. Data was collected both in DC voltage mode and laser-assisted mode (in the latter of which extracting crystallographic information is known to be more difficult due to distortions). The nature of the atomic planes in both datasets was extracted and analysed.

String-shaped morphologies consisting of preferentially aligned lath-shaped α precipitates were observed in the metastable β Ti-6Cr-5Mo-5V-4Al alloy after deformations at high strain rates and elevated temperatures. The morphology and 3-dimentional arrangement of this feature have been elaborated based on the characterizations via a combination of transmission electron microscopy, transmission kikuchi diffraction and atom probe tomography. The 2D projected morphology of the coalescent α laths observed in the etched samples by SEM depends on the metallographic section. All the microstructural observations indicate that dislocation structures are most likely the nucleation sites for the aligned α laths. In addition, an appropriate testing temperature, which can ensure a relatively high diffusion rate of solutes without inducing strong recovery of dislocation structures, is necessary for the occurrence of the string-shaped morphologies.

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.

Modification of the recently developed creep-resistant Mg-3Gd-2Ca (wt.%) magnesium alloy using Nd and Mn remarkably improved the creep resistance at both 180 °C and 210 °C . The modified Mg-2Gd-1Nd-2Ca-0.5Mn alloy after solid solution treatment exhibited outstanding creep resistance that is superior to the commercial creep-resistant Mg alloy, EV31, but contained less RE addition. The microstructural observations revealed that partial replacement of Gd with 1 wt% Nd did not enhance the effect of dynamic precipitates significantly. But further analysis by atom probe tomography verified the stronger co-segregation between Nd solute atoms and other solute atoms than that of Gd and Ca in the Mg solid solutions, leading to a higher solid solution strengthening effect on the creep resistance. The addition of 0.5 wt% Mn led to the formation of polygonal-shape α-Mn precipitates, which served as heterogeneous nucleants for dynamic precipitates, refining their size and increasing the number densities. As a result, the creep properties of newly developed Mg alloys were strengthened by a combination of improved solid solution strengthening by Nd and increased precipitation hardening by Mn addition.

Much effort has been devoted to the development of computational techniques in atom probe microscopy over the past decade. There have been several drivers for this effort. Firstly, there has been effort devoted to addressing the challenges of discerning information from the increasingly large size of the data, and capturing the opportunities that this large data presents. Secondly, there has been significant new effort devoted to the simulation of atom probe data so that pristine datasets that contain microstructural features of increasing complexity can be generated in-silico , and subjected to complex data-mining algorithms. This has enabled the benchmarking of various algorithms, guided the setting of parameters for particular analyses, and exposed the effects of instrumentation parameters such as detector efficiency and aberrations in ionic flight path. The authors are especially interested in the prospects of converging atomic-scale microscopy with atomic-scale materials modelling via first principles approaches. This involves excising parts of the APM data and using these as super-cell inputs to calculations of materials properties via density functional theory. It is our opinion that this represents a major advance for materials science because it enables microscopy to advance microstructure–property relationships to the direct mapping of such relationships based on many-body interactions. As such, this approach has great potential for materials design and development. The final part of this paper focuses on how cloud-based computing represents an exciting frontier of the computational aspects of atom probe microscopy. We discuss the opportunities and the barriers for conducting new materials science through the analysis and visualisation of atom probe data via new generation tools that are cloud-based, and which are managed, curated and governed with significant user-community input and integrated with contemporary electronic laboratory notebook technology.

In this paper we present new methods for feature analysis in atom probe tomography data that have useful applications in materials characterisation. The analysis works on the principle of Voronoi subvolumes and piecewise linear approximations, and feature delineation based on the distance to the centre of mass of a subvolume (DCOM). Based on the coordinate systems defined by these approximations, two examples are shown of the new types of analyses that can be performed. The first is the analysis of line-like-objects (i.e. dislocations) using both proxigrams and line-excess plots. The second is interfacial excess mapping of an InGaAs quantum dot.

Controllable doping of semiconductor nanowires is critical to realize their proposed applications, however precise and reliable characterization of dopant distributions remains challenging. In this article, we demonstrate an atomic-resolution three-dimensional elemental mapping of pristine semiconductor nanowires on growth substrates by using atom probe tomography to tackle this major challenge. This highly transferrable method is able to analyze the full diameter of a nanowire, with a depth resolution better than 0.17 nm thanks to an advanced reconstruction method exploiting the specimen's crystallography, and an enhanced chemical sensitivity of better than 8-fold increase in the signal-to-noise ratio.

Solute clustering is increasingly recognised as a significant characteristic within certain material systems that can be tailored to the optimization of bulk properties and performance. Atom probe tomography (APT) is emerging as a powerful tool for the detection of these nanoscale features; however, complementary to experiment, precise and efficient characterization algorithms are required to identify and characterise these nanoclusters within the potentially massive three-dimensional atomistic APT datasets. In this study, a new three-dimensional Markov field (3DMF) cluster identification algorithm is proposed. The algorithm is based upon an analysis of the direct atomic neighbourhood surrounding each atom, and the only input parameter required utilises known crystallographic properties of the system. Further, an array of statistical approaches has been developed and applied with respect to the results generated by the 3DMF algorithm including: an SN statistic, a two-tailed z-test, a difference measure, the ξ2 test, and a direct evaluation of the Warren-Cowley parameter for short-range ordering. Finally, the methodologies have been applied to the characterization of the nanostructural evolution of an Al-1.1Cu-0.5Mg (at.%) alloy subjected to a variety of heat treatments.

The generalized multicomponent short-range order (GM-SRO) parameter has been adapted for the characterization of short-range order within the highly chemically and spatially resolved three-dimensional atomistic images provided by the microscopy technique of atom-probe tomography (APT). It is demonstrated that, despite the experimental limitations of APT, in many cases the GM-SRO results derived from APT data can provide a highly representative description of the atomic scale chemical arrangement in the original specimen. Further, based upon a target set of the GM-SRO parameters, measured from APT experiments, a Monte Carlo algorithm was utilized to simulate statistically equivalent atomistic systems which, unlike APT data, are complete and lattice based. The simulations replicate solute structures that are statistically consistent with other correlation measures such as solute cluster distributions, enable more quantitative characterization of nanostructural phenomena in the original specimen and, significantly, can be incorporated directly into other models and simulations.

The following manuscript presents a novel approach for creating lattice based models of Sb-doped Si directly from atom probe reconstructions for the purposes of improving information on dopant positioning and directly informing quantum mechanics based materials modeling approaches. Sophisticated crystallographic analysis techniques are used to detect latent crystal structure within the atom probe reconstructions with unprecedented accuracy. A distortion correction algorithm is then developed to precisely calibrate the detected crystal structure to the theoretically known diamond cubic lattice. The reconstructed atoms are then positioned on their most likely lattice positions. Simulations are then used to determine the accuracy of such an approach and show that improvements to short-range order measurements are possible for noise levels and detector efficiencies comparable with experimentally collected atom probe data.

Thin films consisting of silicon nanocrystals fabricated by high silicon content in silicon rich oxide show unique properties of decreasing resistivity and increasing light absorption while maintaining quantum confinement effects. With that said, the effect of the annealing temperature and doping element on the microscopic structure of silicon nanocrystals (Si NCs) and the film are still under research. In this study, individual intrinsic, boron-, and phosphorus-doped films are annealed at various temperatures, and their structural properties are analyzed via atom probe tomography together with glancing incidence x-ray diffraction, Raman spectroscopy (Raman), transmission electron microscopy (TEM), and energy filtered TEM. In addition, photoluminescence (PL) is performed and linked with their microstructural properties. The Si NC growth is confirmed at annealing temperatures of 1000 °C and 1100 °C. The microstructure of the Si NCs in the whole film is dramatically changed by increasing the annealing tempe...

Picosecond-pulsed ultraviolet-laser (UV-355 nm) assisted atom probe tomography (APT) was used to analyze protective, thermally grown chromium oxides formed on stainless steel. The influence of analysis parameters on the thermal tail observed in the mass spectra and the chemical composition is investigated. A new parameter termed "laser sensitivity factor" is introduced in order to quantify the effect of laser energy on the extent of the thermal tail. This parameter is used to compare the effect of increasing laser energy on thermal tails in chromia and chromite samples. Also explored is the effect of increasing laser energy on the measured oxygen content and the effect of specimen base temperature and laser pulse frequency on the mass spectrum. Finally, we report a preliminary analysis of molecular ion dissociations in chromia.

Microscopy encompasses a wide variety of forms and scales. So too does the array of simulation techniques developed that correlate to and build upon microstructural information. Nevertheless, a true nexus between microscopy and atomistic simulations is lacking. Atom probe has emerged as a potential means of achieving this goal. Atom probe generates three-dimensional atomistic images in a format almost identical to many atomistic simulations. However, this data is imperfect, preventing input into computational algorithms to predict material properties. Here we describe a methodology to overcome these limitations, based on a hybrid data format, blending atom probe and predictive Monte Carlo simulations. We create atomically complete and lattice-bound models of material specimens. This hybrid data can then be used as direct input into density functional theory simulations to calculate local energetics and elastic properties. This research demonstrates the role that atom probe combined with theoretical approaches can play in modern materials engineering.

The analysis of the formation of clusters in solid solutions is one of the most common uses of atom probe tomography. Here, we present a method where we use the Voronoi tessellation of the solute atoms and its geometric dual, the Delaunay triangulation to test for spatial/chemical randomness of the solid solution as well as extracting the clusters themselves. We show how the parameters necessary for cluster extraction can be determined automatically, i.e. without user interaction, making it an ideal tool for the screening of datasets and the pre-filtering of structures for other spatial analysis techniques. Since the Voronoi volumes are closely related to atomic concentrations, the parameters resulting from this analysis can also be used for other concentration based methods such as iso-surfaces.

For a scientist in the modern era, reliability of results is no longer the key to a successful career in research. Increasingly, scientists must demonstrate the applicability (e.g. usefulness) of their work, as well as ensure the research is accessible (e.g. easy to find and easy to interpret). It is these three traits that define how others perceive a body of scientific work. Analyzing citations, such as h-index, is a mature measure of applicability of publications, but measuring the applicability of software is lagging behind. In this paper, we discuss a potential tool for data and software provenance that can be used to measure data and software applicability through usage reporting and citations.

Doping of silicon nanocrystals is essential to control their electronic and optical properties. The incorporation of an impurity into a silicon nanovolume is a nontrivial task due to the self-purification effect. Here, a systematic atom probe tomography study of the phosphorus distribution and incorporation in size-controlled silicon nanocrystals embedded in silicon dioxide is presented. Qualitatively, it turns out that the phosphorus distribution in the system follows a universal, nanocrystal-size independent trend: phosphorus-enrichment at the interface with a substantial phosphorus-incorporation in the silicon nanocrystal as small as 2 nm in diameter. This clearly contradicts strict self-purification. These observations are explained by the bulk-solubility and -segregation behaviour, kinetic effects related to the diffusion lengths, and nanoscale interface strain. The quantitative determination of the amount of phosphorus atoms per quantum dot enables a systematic understanding of phosphorus-induced effects on optical and electronic properties of silicon nanovolumes.

Intrinsic, boron (B)-doped, and phosphorus (P)-doped silicon nanocrystals (Si NCs) formed from an excess Si concentration of 40 at. % were investigated to study their structural, optical, and electrical properties. Atom probe tomography (APT) revealed that the size and arrangement of Si NCs were different in each sample. A strong blue shift in photoluminescence spectra for the intrinsic and B-doped Si NCs was correlated with the volume fraction of small Si NCs. The lower resistivity of the B-doped sample than the P-doped one was explained by the percolation of Si NCs through the film.

In order to unravel the magnetism of Co-doped ZnO films, we have performed rigorous experiments on Co-doped ZnO grown on O-polar ZnO (0001̄) substrates by molecular beam epitaxy. We find that the ZnO:Co with Co composition less than 20% is paramagnetic even at low temperatures, whereas that with Co composition of 20% shows ferromagnetism at room temperature. Although an additional n-type doping with Ga increases the magnitude of magnetization, the origin of the observed ferromagnetism is not carrier induced, as confirmed by electric-field effect measurements. Three-dimensional atom probe tomography shows that Co ions are randomly distributed, indicating that Co clustering or spinodal decomposition is not the origin of the ferromagnetism either. One possible mechanism for the ferromagnetism is hydrogen-facilitated interaction, which is supported experimentally by magnetic measurements on hydrogen-treated ZnO:Co as well as theoretically by first-principles calculation. © 2012 American Physical Society.

Two methods for separating the constituent atoms of molecular ions within atom probe tomography reconstructions are presented. The Gaussian Separation Method efficiently deconvolutes molecular ions containing two constituent atoms and is tested on simulated data before being applied to an experimental HSLA steel dataset containing NbN. The Delaunay Separation Method extends separation to larger complex ions and is also tested on simulated data before being applied to an experimental GaAs dataset containing many large (>3 atoms) complex ions. First nearest neighbour (1NN) distributions and images of the reconstruction before and after the separations are used to show the effect of the algorithms and their validity and practicality are also discussed.