scholarly journals 3D Microstructure Simulation of Reactive Aggregate in Concrete from 2D Images as the Basis for ASR Simulation

Materials ◽  
2021 ◽  
Vol 14 (11) ◽  
pp. 2908
Author(s):  
Xiujiao Qiu ◽  
Jiayi Chen ◽  
Maxim Deprez ◽  
Veerle Cnudde ◽  
Guang Ye ◽  
...  
Keyword(s):  
Focused Ion Beam ◽  
Ion Beam ◽  
Simulation Models ◽  
Sem Images ◽  
Average Pore ◽  
Heterogeneous Distribution ◽  
Reactive Aggregate ◽  
Coarse Aggregates ◽  
Reactive Silica ◽  
2D Images

The microstructure of alkali-reactive aggregates, especially the spatial distribution of the pore and reactive silica phase, plays a significant role in the process of the alkali silica reaction (ASR) in concrete, as it determines not only the reaction front of ASR but also the localization of the produced expansive product from where the cracking begins. However, the microstructure of the aggregate was either simplified or neglected in the current ASR simulation models. Due to the various particle sizes and heterogeneous distribution of the reactive silica in the aggregate, it is difficult to obtain a representative microstructure at a desired voxel size by using non-destructive computed tomography (CT) or focused ion beam milling combined with scanning electron microscopy (FIB-SEM). In order to fill this gap, this paper proposed a model that simulates the microstructures of the alkali-reactive aggregate based on 2D images. Five representative 3D microstructures with different pore and quartz fractions were simulated from SEM images. The simulated fraction, scattering density, as well as the autocorrelation function (ACF) of pore and quartz agreed well with the original ones. A 40×40×40 mm3 concrete cube with irregular coarse aggregates was then simulated with the aggregate assembled by the five representative microstructures. The average pore (at microscale μm) and quartz fractions of the cube matched well with the X-ray diffraction (XRD) and Mercury intrusion porosimetry (MIP) results. The simulated microstructures can be used as a basis for simulation of the chemical reaction of ASR at a microscale.

scholarly journals In Situ Delineation Etch Reveals Subtle Detail in SEM Images of Ion Milled Cross Sections Enabling In-Fab 3-D Metrology and Characterization

2000 ◽  
Vol 8 (2) ◽  
pp. 36-39
Author(s):  
Clive Chandler
Keyword(s):  
Sample Preparation ◽  
Cross Sections ◽  
Focused Ion Beam ◽  
Ion Beam ◽  
Automated System ◽  
Sem Images ◽  
Difficult Time ◽  
Device Structures ◽  
Wet Etch ◽  
Conventional Sample

Control of layer thickness is critically important in the manufacture of semiconductor devices. Cross-sectioning exposes device structures for direct examination but conventional sample preparation procedures are difficult, time consuming, and grossly destructive. Cross sections created by focused ion beam (FIB) milling are easier, faster, and less destructive but have not offered the clear layer delineation provided by etching in the conventional sample preparation process. A new gas etch capability (Delineation Etch™ from FEI Company) offers results that are equivalent to conventional wet-etch preparations in a fraction of the time from a single, automated system in the fab without destroying the wafer. The new etch process also has application in milling high-aspect-ratio holes to create contacts to buried metal layers, and in deprocessing devices to reveal silicon and polysilicon structures.

scholarly journals Two-Stage Alignment of FIB-SEM Images of Rock Samples

2020 ◽  
Vol 6 (10) ◽  
pp. 107
Author(s):  
Iryna Reimers ◽  
Ilia Safonov ◽  
Anton Kornilov ◽  
Ivan Yakimchuk
Keyword(s):  
High Frequency ◽  
Focused Ion Beam ◽  
Pore Space ◽  
Ion Beam ◽  
Affine Transformations ◽  
Sem Images ◽  
Alignment Procedure ◽  
Natural Rock ◽  
Alignment Algorithms ◽  
Frequency Components

Focused Ion Beam Scanning Electron Microscopy (FIB-SEM) tomography provides a stack of images that represent serial slices of the sample. These images are displaced relatively to each other, and an alignment procedure is required. Traditional methods for alignment of a 3D image are based on a comparison of two adjacent slices. However, such algorithms are easily confused by anisotropy in the sample structure or even experiment geometry in the case of porous media. This may lead to significant distortions in the pore space geometry, if there are no stable fiducial marks in the frame. In this paper, we propose a new method, which meaningfully extends existing alignment procedures. Our technique allows the correction of random misalignments between slices and, at the same time, preserves the overall geometrical structure of the specimen. We consider displacements produced by existing alignment algorithms as a signal and decompose it into low and high-frequency components. Final transformations exclude slow variations and contain only high frequency variations that represent random shifts that need to be corrected. The proposed algorithm can operate with not only translations but also with arbitrary affine transformations. We demonstrate the performance of our approach on a synthetic dataset and two real FIB-SEM images of natural rock.

FIB Micro-Pillar Sampling of Si Devices and its 3D Observation

2003 ◽  
Author(s):  
T. Yaguchi ◽  
T. Kamino ◽  
T. Ohnishi ◽  
T. Hashimoto ◽  
K. Umemura ◽  
...  
Keyword(s):  
Focused Ion Beam ◽  
Ion Beam ◽  
Three Dimensional ◽  
Sampling Technique ◽  
Scanning Transmission Electron Microscope ◽  
Dark Field ◽  
Limiting Factor ◽  
Sem Images ◽  
Cross Sectional ◽  
Scanning Transmission

Abstract A novel technique for three-dimensional structural and elemental analyses using a dedicated focused ion beam (FIB) and scanning transmission electron microscope (STEM) has been developed. The system employs an FIB-STEM compatible sample holder with sample stage rotation mechanism. A piece of sample (micro sample) is extracted from the area to be characterized by the micro-sampling technique [1-3]. The micro sample is then transferred onto the tip of the stage (needle stage) and bonded by FIB assisted metal deposition. STEM observation of the micro sample is carried out after trimming the sample into a micro-pillar 2-5 micron squared in cross-section and 10 -15 micron in length (micro-pillar sample). High angle annular dark field (HAADF) STEM, bright field STEM and secondary electron microscopy (SEM) images are obtained at 200kV resulting in threedimensional and cross sectional representations of the microsample. The geometry of the sample and the needle stage allows observation of the sample from all directions. The specific site can be located for further FIB milling whenever it is required. Since the operator can choose materials for the needle stage, the geometry of the original specimen is not a limiting factor for quantitative energy dispersive X-ray (EDX) analysis.

Scanning Electron Microscopy Observation of Interface Between Single Neurons and Conductive Surfaces

2016 ◽  
Vol 16 (4) ◽  
pp. 3383-3387 ◽  
Author(s):  
Toichiro Goto ◽  
Nahoko Kasai ◽  
Rick Lu ◽  
Roxana Filip ◽  
Koji Sumitomo
Keyword(s):  
Electron Microscopy ◽  
Scanning Electron Microscopy ◽  
Indium Tin Oxide ◽  
Focused Ion Beam ◽  
Ion Beam ◽  
Single Neurons ◽  
Sem Images ◽  
Cross Sectional ◽  
Integrated Devices ◽  
Scanning Electron

Interfaces between single neurons and conductive substrates were investigated using focused ion beam (FIB) milling and subsequent scanning electron microscopy (SEM) observation. The interfaces play an important role in controlling neuronal growth when we fabricate neuron-nanostructure integrated devices. Cross sectional images of cultivated neurons obtained with an FIB/SEM dual system show the clear affinity of the neurons for the substrates. Very few neurons attached themselves to indium tin oxide (ITO) and this repulsion yielded a wide interspace at the neuron-ITO interface. A neuron-gold interface exhibited partial adhesion. On the other hand, a neuron-titanium interface showed good adhesion and small interspaces were observed. These results are consistent with an assessment made using fluorescence microscopy. We expect the much higher spatial resolution of SEM images to provide us with more detailed information. Our study shows that the interface between a single neuron and a substrate offers useful information as regards improving surface properties and establishing neuron-nanostructure integrated devices.

scholarly journals Morphological Processes of Foot Process Effacement in Puromycin Aminonucleoside Nephrosis Revealed by FIB/SEM Tomography

2018 ◽  
Vol 30 (1) ◽  
pp. 96-108 ◽  
Author(s):  
Koichiro Ichimura ◽  
Takayuki Miyaki ◽  
Yuto Kawasaki ◽  
Mui Kinoshita ◽  
Soichiro Kakuta ◽  
...  
Keyword(s):  
Cell Body ◽  
Focused Ion Beam ◽  
Developmental Process ◽  
Ion Beam ◽  
Primary Process ◽  
Puromycin Aminonucleoside ◽  
Sem Images ◽  
Foot Process Effacement ◽  
Foot Process ◽  
Morphologic Changes

BackgroundFoot process effacement is one of the pathologic indicators of podocyte injury. However, the morphologic changes associated with it remain unclear.MethodsTo clarify the developmental process, we analyzed puromycin nephrotic podocytes reconstructed from serial focused-ion beam/scanning electron microscopy (FIB/SEM) images.ResultsIntact podocytes consisted of four subcellular compartments: cell body, primary process, ridge-like prominence (RLP), and foot process. The RLP, a longitudinal protrusion from the basal surface of the cell body and primary process, served as an adhesive apparatus for the cell body and primary process to attach to the glomerular basement membrane. Foot processes protruded from both sides of the RLP. In puromycin nephrotic podocytes, foot process effacement occurred in two ways: by type-1 retraction, where the foot processes retracted while maintaining their rounded tips; or type-2 retraction, where they narrowed across their entire lengths, tapering toward the tips. Puromycin nephrotic podocytes also exhibited several alterations associated with foot process effacement, such as deformation of the cell body, retraction of RLPs, and cytoplasmic fragmentation. Finally, podocytes were reorganized into a broad, flattened shape.ConclusionsThe three-dimensional reconstruction of podocytes by serial FIB/SEM images revealed the morphologic changes involved in foot process effacement in greater detail than previously described.

scholarly journals Super High-Quality SEM/FIB Imaging of Dentine Structures Without Collagen Fiber Loss Through a Metal Staining Process

2021 ◽  
Author(s):  
Shiyou Xu ◽  
Michael Stranick ◽  
Deon Hines ◽  
Ke Du ◽  
Long Pan
Keyword(s):  
Collagen Fiber ◽  
Focused Ion Beam ◽  
Ion Beam ◽  
Milling Process ◽  
Collagen Fibers ◽  
Real Sample ◽  
Acquisition Time ◽  
High Quality ◽  
Sem Images ◽  
The Real

Abstract Scanning Electron Microscope/Focused Ion Beam (SEM/FIB) system has become a valuable and popular tool for the analysis of biological materials such as dentine structures. According to physiological and anatomical studies, dentine structures are a complicated system containing collagen fibers, nanocrystalline hydroxyapatite, and numerous networks of tubular pores. During a routine FIB milling process, collagen fibers and other organic structures are vaporized, while the number of tubular pores remaining is increased. This causes the final cross-section to be more porous than the real sample. Unfortunately, little attention has been paid to the collagen fiber loss and how to preserve them during a FIB milling process. In this work, we present a novel and simple approach to preserve the organic portions of the dentine structure through metal staining. By using this method, the porosity of the dentine structure after the FIB milling process is significantly reduced similar to the real sample. This indicates that the organic portion of the dentine structure is well protected by the metal staining. This approach enables the SEM/FIB system to generate super-high quality SEM images with less ion beam damage; and the SEM images can better reflect the original condition of the dentine structure. Further, serial energy-dispersive X-ray spectroscopy (EDS) mapping of the stained dentine structure is achieved without an additional metal coating; and three-dimensional (3-D) elemental mapping of an occluded dentine is achieved with a significantly reduced data acquisition time.

scholarly journals Rendering Semisynthetic FIB-SEM Images of Rock Samples

2021 ◽  
Author(s):  
Ilia Safonov ◽  
Anton Kornilov ◽  
Iryna Reimers
Keyword(s):  
Focused Ion Beam ◽  
Oil And Gas ◽  
Rock Sample ◽  
Pore Space ◽  
Ion Beam ◽  
Ground Truth ◽  
Fine Tuning ◽  
Back Side ◽  
Sem Images ◽  
Rock Samples

Digital rock analysis is a prospective approach to estimate properties of oil and gas reservoirs. This concept implies constructing a 3D digital twin of a rock sample. Focused Ion Beam - Scanning Electron Microscope (FIB-SEM) allows to obtain a 3D image of a sample at nanoscale. One of the main specific features of FIB-SEM images in case of porous media is pore-back (or shine-through) effect. Since pores are transparent, their back side is visible in the current slice, whereas, in fact, it locates in the following ones. A precise segmentation of pores is a challenging problem. Absence of annotated ground truth complicates fine-tuning the algorithms for processing of FIB-SEM data and prevents successful application of machine- learning-based methods, which require a huge training set. Recently, several synthetic FIB- SEM images based on stochastic structures were created. However, those images strongly differ from images of real samples. We propose fast approaches to render semisynthetic FIB- SEM images, which imply that intensities of voxels of mineral matrix in a milling plane, as well as geometry of pore space, are borrowed from an image of rock sample saturated by epoxy. Intensities of voxels in pores depend on the distance from milling plane to the given voxel along a ray directed at an angle equal to the angle between FIB and SEM columns. The proposed method allows to create very realistic FIB-SEM images of rock samples with precise ground truth. Also, it opens the door for numerical estimation of plenty of algorithms for processing FIB-SEM data.

Machine-Learning-Assisted Segmentation of Focused Ion Beam-Scanning Electron Microscopy Images with Artifacts for Improved Void-Space Characterization of Tight Reservoir Rocks

SPE Journal ◽  
2021 ◽  
pp. 1-20
Author(s):  
Andrey Kazak ◽  
Kirill Simonov ◽  
Victor Kulikov
Keyword(s):  
Image Segmentation ◽  
Focused Ion Beam ◽  
Pore Space ◽  
Ion Beam ◽  
Reservoir Rock ◽  
Data Sets ◽  
Sem Images ◽  
Reservoir Rocks ◽  
Tight Reservoir

Summary The modern focused ion beam-scanning electron microscopy (FIB-SEM) allows imaging of nanoporous tight reservoir-rock samples in 3D at a resolution up to 3 nm/voxel. Correct porosity determination from FIB-SEM images requires fast and robust segmentation. However, the quality and efficient segmentation of FIB-SEM images is still a complicated and challenging task. Typically, a trained operator spends days or weeks in subjective and semimanual labeling of a single FIB-SEM data set. The presence of FIB-SEM artifacts, such as porebacks, requires developing a new methodology for efficient image segmentation. We have developed a method for simplification of multimodal segmentation of FIB-SEM data sets using machine-learning (ML)-based techniques. We study a collection of rock samples formed according to the petrophysical interpretation of well logs from a complex tight gas reservoir rock of the Berezov Formation (West Siberia, Russia). The core samples were passed through a multiscale imaging workflow for pore-space-structure upscaling from nanometer to log scale. FIB-SEM imaging resolved the finest scale using a dual-beam analytical system. Image segmentation used an architecture derived from a convolutional neural network (CNN) in the DeepUNet (Ronneberger et al. 2015) configuration. We implemented the solution in the Pytorch® (Facebook, Inc., Menlo Park, California, USA) framework in a Linux environment. Computation exploited a high-performance computing system. The acquired data included three 3D FIB-SEM data sets with a physical size of approximately 20 × 15 × 25 µm with a voxel size of 5 nm. A professional geologist manually segmented (labeled) a fraction of slices. We split the labeled slices into training, validation, and test data. We then augmented the training data to increase its size. The developed CNN delivered promising results. The model performed automatic segmentation with the following average quality indicators according to test data: accuracy of 86.66%, precision of 54.93%, recall of 83.76%, and F1 score of 55.10%. We achieved a significant boost in segmentation speed of 14.5 megapixel (MP)/min. Compared with 0.18 to 1.45 MP/min for manual labeling, this yielded an efficiency increase of at least 10 times. The presented research work improves the quality of quantitative petrophysical characterization of complex reservoir rocks using digital rock imaging. The development allows the multiphase segmentation of 3D FIB-SEM data complicated with artifacts. It delivers correct and precise pore-space segmentation, resulting in little turn-around-time saving and increased porosity-data quality. Although image segmentation using CNNs is mainstream in the modern ML world, it is an emerging novel approach for reservoir-characterizationtasks.

scholarly journals Shale fabric and organic nanoporosity in lower Palaeozoic shales, Bornholm, Denmark

2018 ◽  
pp. 17-20 ◽  
Author(s):  
Lucy Malou Henningsen ◽  
Christian Høimann Jensen ◽  
Niels Hemmingsen Schovsbo ◽  
Arne Thorshøj Nielsen ◽  
Gunver Krarup Pedersen
Keyword(s):  
Focused Ion Beam ◽  
Oil And Gas ◽  
Ion Beam ◽  
Mineralogical Composition ◽  
Gas Content ◽  
High Porosity ◽  
Gas Generation ◽  
Sem Images ◽  
Lower Palaeozoic ◽  
Pore Types

In organic-rich shales, pores form during oil and gas genesis within organic matter (OM) domains. The porosity thus differs markedly from that of conventional reservoir lithologies. Here we present the first description of shale fabric and pore types in the lower Palaeozoic shales on Bornholm, Denmark. The pores have been studied using the focused ion beam scanning electron microscope (FIB-SEM) technique, which allows for high resolution SEM images of ion polished surfaces. Shale porosity is influenced by many factors including depositional fabric, mineralogical composition, diagenesis and oil and gas generation (Schieber 2013). Here we discuss some of these factors based on a study of lower Palaeozoic shale samples from the Billegrav-2 borehole on Bornholm (Fig. 1) undertaken by Henningsen & Jensen (2017). The shales are dry gas-mature (2.3% graptolite reflectance; Petersen et al. 2013) and have been extensively used as analogies for the deeply buried Palaeozoic shales elsewhere in Denmark (Schovsbo et al. 2011; Gautier et al. 2014). The Danish lower Palaeozoic shale gas play was tested by the Vendsyssel-1 well drilled in northern Jylland in 2015. Gas was discovered within a c. 70 m thick gas-mature, organicrich succession (Ferrand et al. 2016). However, the licence was subsequently relinquished, due to a too low gas content. The present study confirms a close similarity of pore development between the shales on Bornholm and in the Vendsys sel-1 indicating a high porosity within this stratigraphic level throughout the subsurface of Denmark. However, the rather different development of porosity in the different shale units presents a hitherto neglected aspect of the Palaeozoic gas play in Denmark.

Multi-Angle Plasma Focused Ion Beam (FIB) Curtaining Artifact Correction Using a Fourier-Based Linear Optimization Model

2018 ◽  
Vol 24 (6) ◽  
pp. 657-666 ◽  
Author(s):  
Christopher W. Schankula ◽  
Christopher K. Anand ◽  
Nabil D. Bassim
Keyword(s):  
Optimization Model ◽  
Focused Ion Beam ◽  
Ion Beam ◽  
Linear Optimization ◽  
Three Dimensional ◽  
Sample Surface ◽  
Sem Images ◽  
Linear Optimization Model ◽  
Straight Line ◽  
Automated Processing

AbstractWe present a flexible linear optimization model for correcting multi-angle curtaining effects in plasma focused ion beam scanning electron microscopy (PFIB-SEM) images produced by rocking-polishing schemes. When PFIB-SEM is employed in a serial sectioning tomography workow, it is capable of imaging large three-dimensional volumes quickly, providing rich information in the critical 10–100 nm feature length scale. During tomogram acquisition, a “rocking polish” is often used to reduce straight-line “curtaining” gradations in the milled sample surface. While this mitigation scheme is effective for deep curtains, it leaves shallower line artifacts at two discretized angles. Segmentation and other automated processing of the image set requires that these artifacts be corrected for accurate microstructural quantification. Our work details a new Fourier-based linear optimization model for correcting curtaining artifacts by targeting curtains at two discrete angles. We demonstrate its capabilities by processing images from a tomogram from a multiphase, heterogeneous concrete sample. We present methods for selecting the parameters which meet the user’s goals most appropriately. Compared to previous works, we show that our model provides effective multi-angle curtain correction without introducing artifacts into the image, modifying non-curtain structures or causing changes to the contrast of voids. Our algorithm can be easily parallelized to take advantage of multi-core hardware.

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