Thin-Film Microtensile-Test Structures for High-Throughput Characterization of Mechanical Properties

Oellers, Tobias; Arigela, Viswanadh Gowtham; Kirchlechner, Christoph; Dehm, Gerhard; Ludwig, Alfred

doi:10.1021/acscombsci.9b00182

Cited by 17 publications

(21 citation statements)

References 39 publications

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“…For orientation mapping, a thin foil of nanocrystalline Cu–Ag alloy with a thickness of 5 μ m was used (Oellers et al, 2020). A disc with a diameter of 3 mm was cut out from the foil using a disc puncher and glued to a Cu single hole grid.…”

Section: Methodsmentioning

confidence: 99%

Automated Crystal Orientation Mapping by Precession Electron Diffraction-Assisted Four-Dimensional Scanning Transmission Electron Microscopy Using a Scintillator-Based CMOS Detector

et al. 2021

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Section: Methodsmentioning

confidence: 99%

Automated Crystal Orientation Mapping by Precession Electron Diffraction-Assisted Four-Dimensional Scanning Transmission Electron Microscopy Using a Scintillator-Based CMOS Detector

et al. 2021

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“…The first dataset was collected on a sample of Cu-Ag alloy described in ref. [26]. The dataset was thoroughly analyzed in ref.…”

Section: Materials Methods and Datasetsmentioning

confidence: 99%

Free, flexible and fast: orientation mapping using the multi-core and GPU-accelerated template matching capabilities in the python-based open source 4D-STEM analysis toolbox Pyxem

Cautaerts¹,

Crout²,

Ånes³

et al. 2021

Preprint

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This work presents the new template matching capabilities implemented inPyxem, an open source Python library for analyzing four-dimensional scanning transmission electron microscopy (4D-STEM) data. Template matching is a brute force approach for deriving local crystal orientations. It works by comparing a library of simulated diffraction patterns to experimental patterns collected with nano-beam and precession electron diffraction (NBED and PED). This is a computationally demanding task, therefore the implementation combines efficiency and scalability by utilizing multiple CPU cores or a graphical processing unit (GPU). The code is built on top of the scientific python ecosystem, and is designed to support custom and reproducible workflows that combine the image processing, template library generation, indexation and visualisation all in one environment. The tools are agnostic to file size and format, which is significant in light of the increased adoption of pixelated detectors from different manufacturers. This paper details the implementation, validation, and benchmarking results of the method. The method is illustrated by calculating orientation maps of nanocrystalline materials and precipitates embedded in a crystalline matrix. The combination

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“… 9 − 11 However, these tests require custom instrumentation or fabrication of samples into a specific form. 12 , 13 As a result, the low throughput of the specific fabrication or instrumentation requirements significantly hinder the accessibility and the overall throughput of these techniques. Therefore, a high-throughput mechanical testing pipeline that combines simple sample fabrication/preparation steps with easy characterization techniques would provide the materials science community broad access to large mechanical property data sets that would enable transformative advances.…”

Section: Introductionmentioning

confidence: 99%

“…Existing methods can measure properties such as elastic modulus, hardness, and residual stress at throughputs of hundreds or thousands of formulations per run. These methods use techniques such as scanning nanoindentation, micromachined cantilever beams, and micro-electro-mechanical systems. − However, these tests require custom instrumentation or fabrication of samples into a specific form. , As a result, the low throughput of the specific fabrication or instrumentation requirements significantly hinder the accessibility and the overall throughput of these techniques. Therefore, a high-throughput mechanical testing pipeline that combines simple sample fabrication/preparation steps with easy characterization techniques would provide the materials science community broad access to large mechanical property data sets that would enable transformative advances.…”

Section: Introductionmentioning

confidence: 99%

High-Throughput Screening Test for Adhesion in Soft Materials Using Centrifugation

et al. 2021

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High-throughput screening of mechanical properties can transform materials science research by both aiding in materials discovery and developing predictive models. However, only a few such assays have been reported, requiring custom or expensive equipment, while the mounting demand for enormous data sets of materials properties for predictive models is unfulfilled by the current characterization throughput. We address this problem by developing a high-throughput colorimetric adhesion screening method using a common laboratory centrifuge, multiwell plates, and microparticles. The technique uses centrifugation to apply a homogeneous mechanical detachment force across individual formulations in a multiwell plate. We also develop a high-throughput sample deposition method to prepare films with uniform thickness in each well, minimizing well-to-well variability. After establishing excellent agreement with the well-known probe tack adhesion test, we demonstrate the consistency of our method by performing the test on a multiwell plate with two different formulations in an easily discernible pattern. The throughput is limited only by the number of wells in the plates, easily reaching 10 3 samples/run. With its simplicity, low cost, and large dynamic range, this high-throughput method has the potential to change the landscape of adhesive material characterization.

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Thin-Film Microtensile-Test Structures for High-Throughput Characterization of Mechanical Properties

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Cited by 17 publications

References 39 publications

Automated Crystal Orientation Mapping by Precession Electron Diffraction-Assisted Four-Dimensional Scanning Transmission Electron Microscopy Using a Scintillator-Based CMOS Detector

Automated Crystal Orientation Mapping by Precession Electron Diffraction-Assisted Four-Dimensional Scanning Transmission Electron Microscopy Using a Scintillator-Based CMOS Detector

Free, flexible and fast: orientation mapping using the multi-core and GPU-accelerated template matching capabilities in the python-based open source 4D-STEM analysis toolbox Pyxem

High-Throughput Screening Test for Adhesion in Soft Materials Using Centrifugation

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