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Most of the time, the deep analysis of a biological sample requires the acquisition of images at different time points, using different modalities and/or different stainings. This information gives morphological, functional, and physiological insights, but the acquired images must be aligned to be able to proceed with the co-localisation analysis. Practically speaking, according to Aristotle’s principle, “The whole is greater than the sum of its parts”, multi-modal image registration is a challenging task that involves fusing complementary signals. In the past few years, several methods for image registration have been described in the literature, but unfortunately, there is not one method that works for all applications. In addition, there is currently no user-friendly solution for aligning images that does not require any computer skills. In this work, DS4H Image Alignment (DS4H-IA), an open-source ImageJ/Fiji plugin for aligning multimodality, immunohistochemistry (IHC), and/or immunofluorescence (IF) 2D microscopy images, designed with the goal of being extremely easy to use, is described. All of the available solutions for aligning 2D microscopy images have also been revised. The DS4H-IA source code; standalone applications for MAC, Linux, and Windows; video tutorials; manual documentation; and sample datasets are publicly available.

Multimodal datasets for materials provide the large amount of information needed for expediting the discovery of process–structure–property relationships important to materials performance. In this Data Descriptor article, we describe a dataset for magnetron-sputtered molybdenum thin films. The dataset is taken from 27 unique depositions that vary sputter power and argon sputter pressure. High-angle annular dark field and bright-field cross-section transmission electron micrographs were obtained from films produced in each of the depositions. Automated crystal orientation mapping was used to derive inverse pole figures from the imaged areas covering hundreds of grains, and MTEX, a MATLAB toolbox for analyzing crystallographic textures, extracted statistics of the grain sizes and tilt . Additionally, the binary-collision Monte Carlo computer program SIMTRA was used to simulate aspects of film deposition. SIMTRA monitors the gas-phase transport effects on the energy and angular distributions of the arriving metal species as a function of the process parameters. The SIMTRA simulations accounted for sample rotation in a true planetary configuration wherein substrates passed repeatedly under a 200-mm-diameter cathode in a sputter-down, co-planar geometry. For the predicted angle of incidence and energy, probability density functions, uniformity maps, and average quantities are reported for different sputter powers, Ar pressures, and working distances. Overall, the described dataset provides opportunities for examining process–structure relationships. The entirety of this data is committed to a public repository in the materials data facility.