AQUAMI: An open source Python package and GUI for the automatic quantitative analysis of morphologically complex multiphase materials

Stuckner, Joshua; Frei, Katherine; McCue, Ian; Demkowicz, Michael J.; Murayama, Mitsuhiro

doi:10.1016/j.commatsci.2017.08.012

Cited by 59 publications

(47 citation statements)

References 28 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The automated image analysis software used in this study, AQUAMI 9 , applies advanced algorithms to extract accurate microstructural information even with significant additions of noise, blurring, and magnification errors (see Methods and Supplementary Fig. 1 for a schematic of the image analysis process).…”

Section: Resultsmentioning

confidence: 99%

“…The NPG images used in this study were exported in TIFF format from manuscripts using Adobe Illustrator without any reduction in image resolution. The images were analyzed using a custom segmentation and measurement procedure implemented in the AQUAMI software 9 . The segmentation procedure consists of two steps: first, bilateral filtering to remove noise from the micrographs while preserving edges; second, Local Otsu’s Method to assign pixels to the solid or void phase, generating a binary image.…”

Section: Methodsmentioning

confidence: 99%

“…Our method relies on novel image-analysis software, developed and discussed in a previous publication 9 , to extract microstructure characteristics – such as NPG ligament and pore dimensions – in a consistent and reproducible manner. Combining this information with reported processing histories, we obtain a quantitative numerical description of NPG coarsening as a function of time and temperature.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Gaining new insights into nanoporous gold by mining and analysis of published images

McCue

Stuckner

Murayama

et al. 2018

Sci Rep

Self Cite

View full text Add to dashboard Cite

One way of expediting materials development is to decrease the need for new experiments by making greater use of published literature. Here, we use data mining and automated image analysis to gather new insights on nanoporous gold (NPG) without conducting additional experiments or simulations. NPG is a three-dimensional porous network that has found applications in catalysis, sensing, and actuation. We assemble and analyze published images from among thousands of publications on NPG. These images allow us to infer a quantitative description of NPG coarsening as a function of time and temperature, including the coarsening exponent and activation energy. They also demonstrate that relative density and ligament size in NPG are not correlated, indicating that these microstructure features are independently tunable. Our investigation leads us to propose improved reporting guidelines that will enhance the utility of future publications in the field of dealloyed materials.

show abstract

Section: Resultsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Gaining new insights into nanoporous gold by mining and analysis of published images

McCue

Stuckner

Murayama

et al. 2018

Sci Rep

Self Cite

View full text Add to dashboard Cite

show abstract

“…Consistent with the results of Rösner et al (2007) and Hu et al (2016), the mean ligament distributions were reported to be nearly self-similar for the examined ligament sizes. Stuckner et al (2017) present a Python package AQUAMI, which automatically analyzes microstructural features from micrographs. The approach is similar to the approach by Badwe et al (2017), which was independently published, but has no need for manual calculation in ImageJ.…”

Section: Introductionmentioning

confidence: 99%

“…In summary, two algorithms are found to be dominantly used in literature to estimate the ligament size distribution: The Thickness algorithm, which is able to analyze 3D volumes and the Euclidean distance transformation (EDT), which is applied for analyzing 2D SEM images by Badwe et al (2017), Stuckner et al (2017), andMcCue et al (2018). It calculates at each point of the structure the distance to the nearest background point.…”

Section: Introductionmentioning

confidence: 99%

Computation of Thickness and Mechanical Properties of Interconnected Structures: Accuracy, Deviations, and Approaches for Correction

2019

View full text Add to dashboard Cite

Roughness Suppression in Electrochemical Nanoimprinting of Si for Applications in Silicon Photonics

et al. 2022

View full text Add to dashboard Cite

Metal‐assisted electrochemical nanoimprinting (Mac‐Imprint) scales the fabrication of micro‐ and nanoscale 3D freeform geometries in silicon and holds the promise to enable novel chip‐scale optics operating at the near‐infrared spectrum. However, Mac‐Imprint of silicon concomitantly generates mesoscale roughness (e.g., protrusion size ≈45 nm) creating prohibitive levels of light scattering. This arises from the requirement to coat stamps with nanoporous gold catalyst that, while sustaining etchant diffusion, imprints its pores (e.g., average diameter ≈42 nm) onto silicon. In this work, roughness is reduced to sub‐10 nm levels, which is in par with plasma etching, by decreasing pore size of the catalyst via dealloying in far‐from equilibrium conditions. At this level, single‐digit nanometric details such as grain‐boundary grooves of the catalyst are imprinted and attributed to the resolution limit of Mac‐Imprint, which is argued to be twice the Debye length (i.e., 1.7 nm)—a finding that broadly applies to metal‐assisted chemical etching. Last, Mac‐Imprint is employed to produce single‐mode rib‐waveguides on pre‐patterned silicon‐on‐insulator wafers with root‐mean‐square line‐edge roughness less than 10 nm while providing depth uniformity (i.e., 42.9 ± 5.5 nm), and limited levels of silicon defect formation (e.g., Raman peak shift < 0.1 cm−1) and sidewall scattering.

show abstract

AQUAMI: An open source Python package and GUI for the automatic quantitative analysis of morphologically complex multiphase materials

Cited by 59 publications

References 28 publications

Gaining new insights into nanoporous gold by mining and analysis of published images

Gaining new insights into nanoporous gold by mining and analysis of published images

Computation of Thickness and Mechanical Properties of Interconnected Structures: Accuracy, Deviations, and Approaches for Correction

Roughness Suppression in Electrochemical Nanoimprinting of Si for Applications in Silicon Photonics

Contact Info

Product

Resources

About