Precession Electron Diffraction Data Research Articles

High precision orientation mapping from 4D-STEM precession electron diffraction data through quantitative analysis of diffracted intensities

The association of scanning transmission electron microscopy (STEM) and detection of a diffraction pattern at each probe position (so-called 4D-STEM) represents one of the most promising approaches to analyze structural properties of materials with nanometric resolution and low irradiation levels. This is widely used for texture analysis of materials using automated crystal orientation mapping (ACOM). Herein, we perform orientation mapping in InP nanowires exploiting precession electron diffraction (PED) patterns acquired by an axial CMOS camera. Crystal orientation is determined at each probe position by the quantitative analysis of diffracted intensities minimizing a residue comparing experiments and simulations in analogy to x-ray structural refinement. Our simulations are based on the two-beam dynamical diffraction approximation and yield a high angular precision (∼0.03°), much lower than the traditional ACOM based on pattern matching algorithms (∼1°). We anticipate that simultaneous exploration of both spot positions and high precision crystal misorientation will allow the exploration of the whole potentiality provided by PED-based 4D-STEM for the characterization of deformation fields in nanomaterials.

Scanning precession electron diffraction data analysis approaches for phase mapping of precipitates in aluminium alloys

Mapping the spatial distribution of crystal phases with nm-scale spatial resolution is an important characterisation task in studies of multi-phase materials. One popular approach is to use scanning precession electron diffraction which enables semi-automatic phase mapping at the nanoscale by collecting a single precession electron diffraction pattern at every probe position over regions spanning up to a few micrometers. For a successful phase mapping each diffraction pattern must be correctly identified. In this work four different approaches for phase mapping of embedded precipitates in an Al-Cu-Li alloy are compared on a sample containing three distinct crystal phases. These approaches are based on: non-negative matrix factorisation, vector matching, template matching and artificial neural networks. To evaluate the success of each approach a ground truth phase map was manually created from virtual images based on characteristic phase morphologies and compared with the deduced phase maps. The percentage accuracy of all methods when compared to the ground truth was satisfactory, with all approaches obtaining scores above 98%. The optimal method depends on the specific task at hand. Non-negative matrix factorisation is suitable with limited prior data knowledge but performs best with few unique diffraction patterns and requires substantial post-processing. It has the advantage of reducing the dimensionality of the dataset and handles weak diffracted intensities well given that they occur repeatedly. The current vector matching implementation is fast, simple, based only on the Bragg spot geometry and requires few parameters. It does however demand that each Bragg spot is accurately detected in each pattern and the current implementation is limited to zone axis patterns. Template matching handles a large range of orientations, including off-axis patterns. However, achieving successful and reliable results often require thorough data pre-processing and do require adequate diffraction simulations. For artificial neural networks a substantial setup effort is demanded but once trained it excels for routine tasks, offering fast predictions. The implemented codes and the data used are available open-source. These resources and the detailed assessment of the methods will allow others to make informed decisions when selecting a data analysis approach for 4D-STEM phase mapping tasks on other material systems.

Improving orientation mapping by enhancing the diffraction signal using Auto-CLAHE in precession electron diffraction data

Precession electron diffraction (PED) is a powerful technique for revealing the crystallographic orientation of samples at the nanoscale. However, the quality of orientation indexing is strongly influenced by the quality of diffraction patterns. In this study, we have developed a novel algorithm called Auto-CLAHE (automatic contrast-limited adaptive histogram equalization), which automatically enhances low-intensity diffraction pattern signals using contrast-limited adaptive histogram equalization (CLAHE). The degree of enhancement is dynamically adjusted based on the overall intensity of the diffraction pattern, with greater enhancement applied to patterns with fewer spots (i.e., away from zone axes) and little or no enhancement applied to patterns with many spots (i.e., at a zone axis). By improving the visibility of low-intensity diffraction spots, Auto-CLAHE significantly improves the template matching between experimentally acquired and simulated diffraction patterns, leading to orientation maps with dramatically higher quality and lower noise. We anticipate that Auto-CLAHE provides an efficient and practical solution for preprocessing PED data, enabling higher-quality crystal orientation mapping to be routinely obtained.

Low Energy Twist Defects in Pentatwinned Silver Nanowires

Transmission electron microscopy investigation of networks of pentatwinned silver nanowires has identified the presence of nanoscale defects within individual wires, showing narrow regions of banded contrast normal to the nanowire axis (bamboo faults). Structural analysis using machine learning decomposition of scanning precession electron diffraction data identifies these bamboo faults as a pair of twist boundaries normal to the wire axis creating low energy coincident site lattices between the faulted region and the parent nanowire. This leads to a conservation of the relative misorientation of the twinned structure within the faulted region, leading to an apparent local rotation of the nanowire. Their presence after spraying and nonthermal processing suggests that they may form during nanowire synthesis. However, examination of the networks before and after cyclic straining finds an increase in the density of the defects, indicating that they may also form as a result of mechanical deformation.

Correcting for probe wandering by precession path segmentation.

Precession electron diffraction has in the past few decades become a powerful technique for structure solving, strain analysis, and orientation mapping, to name a few. One of the benefits of precessing the electron beam, is increased reciprocal space resolution, albeit at a loss of spatial resolution due to an effect referred to as 'probe wandering'. Here, a new methodology of precession path segmentation is presented to counteract this effect and increase the resolution in reconstructed virtual images from scanning precession electron diffraction data. By utilizing fast pixelated electron detector technology, multiple frames are recorded for each azimuthal rotation of the beam, allowing for the probe wandering to be corrected in post-acquisition processing. Not only is there an apparent increase in the resolution of the reconstructed images, but probe wandering due to instrument misalignment is reduced, potentially easing an already difficult alignment procedure.

A reference-area-free strain mapping method using precession electron diffraction data

In this work, we developed a method using precession electron diffraction data to map the residual elastic strain at the nano-scale. The diffraction pattern of each pixel was first collected and denoised. Template matching was then applied using the center spot as the mask to identify the positions of the diffraction disks. Statistics of distances between the selected diffracted disks enable the user to make an informed decision on the reference and to generate strain maps. Strain mapping on an unstrained single crystal sapphire shows the standard deviation of strain measurement is 0.5%. With this method, we were able to successfully measure and map the residual elastic strain in VO2 on sapphire and martensite in a Ni50.3Ti29.7Hf20 shape memory alloy. This approach does not require the user to select a “strain-free area” as a reference and can work on datasets even with the crystals oriented away from zone axes. This method is expected to provide a robust and more accessible alternative means of studying the residual strain of various material systems that complements the existing algorithms for strain mapping.

Crystallographic variant mapping using precession electron diffraction data

In this work, we developed three methods to map crystallographic variants of samples at the nanoscale by analyzing precession electron diffraction data using a high-temperature shape memory alloy and a VO2 thin film on sapphire as the model systems. The three methods are (I) a user-selecting-reference pattern approach, (II) an algorithm-selecting-reference-pattern approach, and (III) a k-means approach. In the first two approaches, Euclidean distance, Cosine, and Structural Similarity (SSIM) algorithms were assessed for the diffraction pattern similarity quantification. We demonstrated that the Euclidean distance and SSIM methods outperform the Cosine algorithm. We further revealed that the random noise in the diffraction data can dramatically affect similarity quantification. Denoising processes could improve the crystallographic mapping quality. With the three methods mentioned above, we were able to map the crystallographic variants in different materials systems, thus enabling fast variant number quantification and clear variant distribution visualization. The advantages and disadvantages of each approach are also discussed. We expect these methods to benefit researchers who work on martensitic materials, in which the variant information is critical to understand their properties and functionalities.

Structural Evolution in an Annealed (Eu, Tb)-Doped ZnO/Si Nanoscale Junction: Implication for Red LED Development

Codoped (Tb,Eu) ZnO films grown by magnetron sputtering on a silicon substrate and annealed up to 1200 °C showed intense photoluminescence (PL) emission from Eu3+ ions. The high-temperature annealing led to diffusion and segregation of rare earth (RE) elements toward the bottom of the film, which induced the formation of nanometric Zn-free inclusions responsible for remarkable PL emission intensity. Combined electron diffraction, chemical contrast imaging, and optical studies of these nanometric phases have been carried out. Large inclusions of zinc silicates and RE silicates a few hundreds of nanometers in size were observed, embedded in a silica phase. The structural determination of these RE-rich inclusions was carried out by combining atomic Z contrast imaging (high-angle annular dark-field imaging) and precession electron diffraction data. Upon annealing at 1200 °C, it appeared that the structure was related to an F-type disilicate structure. Energy-dispersive X-ray spectroscopy and electron energy loss spectroscopy experiments were carried out to determine the ratios between elements and the oxidation states of the RE elements in the abovementioned inclusions. A (Tb,Eu)2Si2O7 formulation is proposed from dynamical precession electron diffraction tomography refinements, leading to a +III valence state for the RE species in agreement with spectroscopic results. PL modeling is also in good agreement with the experimental data. These results complete those obtained at 1100 °C for which the inclusions were identified as some RE10–x(SiO4)6O2–x oxyapatite structures and pointed out a combined structural and PL properties’ evolution between 1100 and 1200 °C annealing temperatures.

Accurate lattice parameters from 3D electron diffraction data. I. Optical distortions.

Determination of lattice parameters from 3D electron diffraction (3D ED) data measured in a transmission electron microscope is hampered by a number of effects that seriously limit the achievable accuracy. The distortion of the diffraction patterns by the optical elements of the microscope is often the most severe problem. A thorough analysis of a number of experimental datasets shows that, in addition to the well known distortions, namely barrel-pincushion, spiral and elliptical, an additional distortion, dubbed parabolic, may be observed in the data. In precession electron diffraction data, the parabolic distortion leads to excitation-error-dependent shift and splitting of reflections. All distortions except for the elliptical distortion can be determined together with lattice parameters from a single 3D ED data set. However, the parameters of the elliptical distortion cannot be determined uniquely due to correlations with the lattice parameters. They can be determined and corrected either by making use of the known Laue class of the crystal or by combining data from two or more crystals. The 3D ED data can yield lattice parameter ratios with an accuracy of about 0.1% and angles with an accuracy better than 0.03°.

Determination of Spinel Content in Cycled Li1.2Ni0.13Mn0.54Co0.13O2 Using Three-Dimensional Electron Diffraction and Precession Electron Diffraction

Among lithium battery cathode materials, Li1.2Ni0.13Mn0.54Co0.13O2 (LR-NMC) has a high theoretical capacity, but suffers from voltage and capacity fade during cycling. This is partially ascribed to transition metal cation migration, which involves the local transformation of the honeycomb layered structure to spinel-like nano-domains. Determination of the honeycomb layered/spinel phase ratio from powder X-ray diffraction data is hindered by the nanoscale of the functional material and the domains, diverse types of twinning, stacking faults, and the possible presence of the rock salt phase. Determining the phase ratio from transmission electron microscopy imaging can only be done for thin regions near the surfaces of the crystals, and the intense beam that is needed for imaging induces the same transformation to spinel as cycling does. In this article, it is demonstrated that the low electron dose sufficient for electron diffraction allows the collection of data without inducing a phase transformation. Using calculated electron diffraction patterns, we demonstrate that it is possible to determine the volume ratio of the different phases in the particles using a pair-wise comparison of the intensities of the reflections. Using this method, the volume ratio of spinel structure to honeycomb layered structure is determined for a submicron sized crystal from experimental three-dimensional electron diffraction (3D ED) and precession electron diffraction (PED) data. Both twinning and the possible presence of the rock salt phase are taken into account. After 150 charge–discharge cycles, 4% of the volume in LR-NMC particles was transformed irreversibly from the honeycomb layered structure to the spinel structure. The proposed method would be applicable to other multi-phase materials as well.

Nanocrystal segmentation in scanning precession electron diffraction data.

Scanning precession electron diffraction (SPED) enables the local crystallography of materials to be probed on the nanoscale by recording a two-dimensional precession electron diffraction (PED) pattern at every probe position as a dynamically rocking electron beam is scanned across the specimen. SPED data from nanocrystalline materials commonly contain some PED patterns in which diffraction is measured from multiple crystals. To analyse such data, it is important to perform nanocrystal segmentation to isolate both the location of each crystal and a corresponding representative diffraction signal. This also reduces data dimensionality significantly. Here, two approaches to nanocrystal segmentation are presented, the first based on virtual dark-field imaging and the second on non-negative matrix factorization. Relative merits and limitations are compared in application to SPED data obtained from partly overlapping nanoparticles, and particular challenges are highlighted associated with crystals exciting the same diffraction conditions. It is demonstrated that both strategies can be used for nanocrystal segmentation without prior knowledge of the crystal structures present, but also that segmentation artefacts can arise and must be considered carefully. The analysis workflows associated with this work are provided open-source. LAY DESCRIPTION: Scanning precession electron diffraction is an electron microscopy technique that enables studies of the local crystallography of a broad selection of materials on the nanoscale. The technique involves the acquisition of a two-dimensional diffraction pattern for every probe position in an area of the sample. The four-dimensional dataset collected by this technique can typically comprise up to 500 000 diffraction patterns. For nanocrystalline materials, it is common that single diffraction patterns contain signals from overlapping crystals. To process such data, we use nanocrystal segmentation, where a representative diffraction pattern is constructed for each individual crystal, together with a real space image showing its morphology and location in the data. This reduces the dimensionality of the data and allows unmixing of signals from overlapping crystals. In this work, we demonstrate two methods for nanocrystal segmentation, one based on creating virtual dark-field images, and one based on unsupervised machine learning. A model system of partly overlapping nanoparticles is used to demonstrate the segmentation, and a demanding case for segmentation is highlighted, where some crystals are not discernible based on their diffraction patterns. To obtain a more complete nanocrystal segmentation, we add an image segmentation routine to both methods, and we discuss benefits and limitations of the two methods. The demonstration data and the used code are provided open-source, so that it can be used by everyone for analysis of nanocrystalline materials or as a starting point for further development of nanocrystal segmentation in scanning precession electron diffractiondata.

Methods for orientation and phase identification of nano-sized embedded secondary phase particles by 4D scanning precession electron diffraction.

The diffraction patterns acquired with transmission electron microscopes gather reflections from all crystallites that overlap in the foil thickness. The superimposition renders automated orientation or phase mapping difficult, in particular when secondary phase particles are embedded in a dominant diffracting matrix. Several numerical approaches specifically developed to overcome this issue for 4D scanning precession electron diffraction data sets are described. They consist either in emphasizing the signature of the particles or in subtracting the matrix information out of the collected set of patterns. The different strategies are applied successively to a steel sample containing precipitates that are in Burgers orientation relationship with the matrix and to an aluminium alloy with randomly oriented Mn-rich particles.

Lasnierite, (Ca,Sr)(Mg,Fe)2Al(PO4)3, a new phosphate accompanying lazulite from Mt. Ibity, Madagascar: an example of structural characterization from dynamical refinement of precession electron diffraction data on submicrometre sample

Lasnierite, (Ca,Sr)(Mg,Fe)2Al(PO4)3, is a new phosphate mineral from Mt. Ibity, close to Itremo, central Madagascar. The mineral was found as inclusions accompanying blue lazulite and many other minerals in blue metaquartzite occasionally used as a gemstone or ornamental stone. The crystals were very small and embedded in quartz so that they could not be extracted mechanically, precluding any “classical” X-ray diffraction on either single-crystal or powder sample. Hence, Focused Ion Beam (FIB) lamellae were extracted and the structure was successfully solved and refined using the recently proposed method of precession electron diffraction tomography (PEDT) associated to dynamical refinement. This underlines the efficiency of this new method for defining mineral species on volumes too small to be manipulated by classical means of X-ray diffraction. Accompanying minerals include various phosphates, sulfates, oxides and silicates. Lasnierite occurs as transparent, near-colourless bladed crystals up to 120 × 60 μm in section. Only five crystals have been identified yet in our samples. The empirical formula, based on wavelength dispersive spectrometry (WDS) electron microprobe analyses and calculated on 12 (O+F) atoms per formula unit, is (Ca0.59Sr0.37)∑0.96(Mg1.42Fe0.54)∑1.96Al0.87(P2.99Si0.01)∑3.00(O11.41F0.59)∑12. LA-ICPMS shows that concentrations of Li, Be and B are below the detection limit. The calculated density based on the empirical formula is 3.162 g cm−3. Lasnierite is orthorhombic, space group Pbcn, with unit-cell parameters: a = 6.2771(3) A, b = 17.684(3) A, c = 8.1631(4) A, Z = 4 and V = 906.1(2) A3. The structure is new. The Raman spectra show characteristic peaks at 99, 122, 278, 418, 510, 569, 590, 621, 661, 985, 1028, 1040, 1063, 1100, 1126 and 1148 cm−1 (most intense bands are italicised). Raman spectra also show the absence of H2O and CO2.

Nanoscale Structure of Zoned Laurites from the Ojén Ultramafic Massif, Southern Spain

We report the first results of a combined focused ion beam and high-resolution transmission electron microscopy (FIB/HRTEM) investigation of zoned laurite (RuS2)-erlichmanite (OS2) in mantle-hosted chromitites. These platinum-group minerals form isolated inclusions (<50 µm across) within larger crystals of unaltered chromite form the Ojén ultramafic massif (southern Spain). High-magnification electron microscopy (HMEM), high angle-annular dark field (HAADF) and precession electron diffraction (PED) data revealed that microscale normal zoning in laurite consisting of Os-poor core and Os-rich rims observed by conventional micro-analytical techniques like field emission scanning electron microscope and electron microprobe analysis (FE-SEM and EPMA) exist at the nanoscale approach in single laurite crystals. At the nanoscale, Os poor cores consist of relatively homogenous pure laurite (RuS2) lacking defects in the crystal lattice, whereas the Os-richer rim consists of homogenous laurite matrix hosting fringes (10–20 nm thickness) of almost pure erlichmanite (OsS2). Core-to-rim microscale zoning in laurite reflects a nonequilibrium during laurite crystal growth, which hampered the intra-crystalline diffusion of Os. The origin of zoning in laurite is related to the formation of the chromitites in the Earth’s upper mantle but fast cooling of the chromite-laurite magmatic system associated to fast exhumation of the rocks would prevent the effective dissolution of Os in the laurite even at high temperatures (~1200 °C), allowing the formation/preservation of nanoscale domains of erlichmanite in laurite. Our observation highlights for the first time the importance of nanoscale studies for a better understanding of the genesis of platinum-group minerals in magmatic ore-forming systems.

Unsupervised machine learning applied to scanning precession electron diffraction data

Scanning precession electron diffraction involves the acquisition of a two-dimensional precession electron diffraction pattern at every probe position in a two-dimensional scan. The data typically comprise many more diffraction patterns than the number of distinct microstructural volume elements (e.g. crystals) in the region sampled. A dimensionality reduction, ideally to one representative diffraction pattern per distinct element, may then be sought. Further, some diffraction patterns will contain contributions from multiple crystals sampled along the beam path, which may be unmixed by harnessing this oversampling. Here, we report on the application of unsupervised machine learning methods to achieve both dimensionality reduction and signal unmixing. Potential artefacts are discussed and precession electron diffraction is demonstrated to improve results by reducing the impact of bending and dynamical diffraction so that the data better approximate the case in which each crystal yields a given diffraction pattern.

The structure of nano-twinned rhombohedral YCuO2.66 solved by electron crystallography

In the search for frustrated spin interactions, a YCuO2.66 phase has been synthesized by a treatment under oxygen pressure of YCuO2.5. X-ray powder diffraction and electron diffraction studies have been conducted. Electron diffraction shows that the sample is twinned on a 10 nm scale. Precession electron diffraction data obtained from a twinned crystal was treated in order to obtain intensities corresponding to only one of the orientations of the twins. From this data a structure solution was obtained where, as in YCuO2.5, the Cu atoms form triangular planes. The Cu atoms are linked in two dimensions by oxygen atoms in the present structure whereas in YCuO2.5 they are only linked in one-dimensional chains.

Riding the camel: the double-peaked rocking curve and its use in the processing of precession electron diffraction data

Riding the camel: the double-peaked rocking curve and its use in the processing of precession electron diffraction data

Silicon carbide grain boundary distributions, irradiation conditions, and silver retention in irradiated AGR-1 TRISO fuel particles

Distributions of silicon carbide grain boundary types (random high angle, low angle, and coincident site lattice-related boundaries), were compared in irradiated tristructural isotropic-coated fuel particles from the Advanced Gas Reactor-1 experiment exhibiting high (>80%) and low (<19%) Ag-110m retention. Grain orientation from transmission electron microscope-based precession electron diffraction data, and, ultimately, grain boundary distributions, indicate irradiated particles with high Ag-110m retention correlate with lower relative fractions of random, high-angle grain boundaries. An inverse relationship between the random, high-angle grain boundary fraction and Ag-110m retention was found and is consistent with grain boundary percolation theory. Also, the SiC grain boundary distribution in an irradiated, low Ag-110m retention, Variant 1 particle was virtually identical to that of a previously reported as-fabricated (unirradiated) Variant 1 TRISO particle. Thus, SiC layers with grain boundary distributions associated with low Ag-110m retention may have developed during fabrication and were present prior to irradiation, assuming significant microstructural evolution did not occur during irradiation. Finally, irradiation levels up to 3.6 × 1025 n/m2 and 16.7% fissions per initial metal atom were found to have little effect on association of fission product precipitates with specific grain boundary types in particles exhibiting between 19% and 80% Ag-110m retention.

Precipitate statistics in an Al-Mg-Si-Cu alloy from scanning precession electron diffraction data

The key microstructural feature providing strength to age-hardenable Al alloys is nanoscale precipitates. Alloy development requires a reliable statistical assessment of these precipitates, in order to link the microstructure with material properties. Here, it is demonstrated that scanning precession electron diffraction combined with computational analysis enable the semi-automated extraction of precipitate statistics in an Al-Mg-Si-Cu alloy. Among the main findings is the precipitate number density, which agrees well with a conventional method based on manual counting and measurements. By virtue of its data analysis objectivity, our methodology is therefore seen as an advantageous alternative to existing routines, offering reproducibility and efficiency in alloy statistics. Additional results include improved qualitative information on phase distributions. The developed procedure is generic and applicable to any material containing nanoscale precipitates.

Hakite from Příbram, Czech Republic: compositional variability, crystal structure and the role in Se mineralization

AbstractHakite, ideally Cu10Hg2Sb4Se13, is a Se-dominant member of the tetrahedrite group occurring at only a few localities in the World. A new occurrence of this mineral in the Příbram uranium and base-metal ore district, Central Bohemia, Czech Republic, is reported in this paper. Hakite was found to be locally abundant and was identified in several samples with Se mineralization. Three chemically distinct types of hakite were distinguished based on electron microprobe study, Hg-rich hakite (hakitesensu stricto), Zn-rich hakite and Cd-rich hakite. Hg-hakite dominates among the samples studied. Its average empirical formula based on 29 apfu (n= 54) is (Cu5.61Ag0.39)∑6.00Cu4.00(Hg1.61Zn0.20Cu0.19Cd0.15Fe0.04)∑2.19(Sb3.85As0.28)∑4.13(Se11.55S1.14)∑12.69. Less common is the Zn-hakite, (Cu5.80Ag0.20)∑6.00Cu4.00(Zn1.33Hg0.42Cd0.22Cu0.18Fe0.01)∑2.16(Sb3.85As0.26)∑4.11(Se10.92S1.81)∑12.73(n= 22), and rare Cd-hakite has an empirical formula (n= 7) of (Cu5.84Ag0.16)∑6.00Cu4.00(Cd1.27Zn0.60Cu0.10Hg0.07Fe0.02)∑2.06(Sb4.00As0.19)∑4.19(Se12.14S0.61)∑12.75. The refined unit cell of Hg-hakite from Příbram, obtained from powder X-ray diffraction data, isa= 10.8783(3) Å withV= 1287.3(1) Å3(Z= 4, for the cubic space groupI4̄3m). Structure refinement from the precession electron diffraction data collected on the transmission electron microscope (R= 24.4% for 424 observed reflections), confirmed that hakite is isostructural with tetrahedrite. The evolution of hydrothermal fluids, from which Se mineralization formed, suggests a distinct enrichment in sulfur and depletion in selenium over the time span of crystallization.