RAITH Group’s Post

We’ve created a Tofu microscope! Well, it is not really a microscope made from tofu…But, it does capture high-resolution 3D phase-sensitive polarimetric images - so still pretty good! Please check out Shiqi’s recent paper about this new 3D microscope to learn more - https://lnkd.in/euRGdV4J

🟠 Embrace the Future of Design with nanoCAD Raster Modules! 🚀 Unlock the power to effortlessly transform raster images into editable vector files with our latest updates. Experience enhanced performance and a sleeker interface for seamless design workflows. Stay tuned for more exciting details! Exciting functionalities await: ☑ Automatic vectorization ☑ Monochrome filtering ☑ Image geometry correction ☑ Color reduction and separation ☑ Color correction ☑ Color filtering ☑ Semi-automatic tracing ☑ Rasterization ☑ Raster image selections 🔶 Visit to know more www.nanocad.com.bd Discover the future of design with nanoCAD Raster Modules! #DesignEvolution #RasterToVector #nanoCAD 🎨🔍

Geometry checks can reveal a lot about your structure — from element assignments, to stability, or a better understanding of ligand binding. Learn how to perform a geometry check in this free online course. You'll use Mogul to compare geometry to the over 1.25M published structures in the Cambridge Structural Database, to get a real data-driven picture of your structure. Find the course here: https://lnkd.in/gYDu29D2 #crystallography #structuralscience #drughunter #drugdesign

🔎Are you looking for the best way to show features of your crystal structure in an upcoming paper, or in your thesis? In this blog you'll learn more about the selection of tools available in Mercury that can help you prepare compelling graphics of crystal structures and visualize complex concepts of crystallography. 🔗https://lnkd.in/eXJBqma3 #Crystallography

Hi3D: Pursuing High-Resolution Image-to-3D Generation with Video Diffusion Models 🤘 The Hi3D model presents a breakthrough in creating high-resolution, multi-view consistent 3D images from a SINGLE image. By incorporating a 3D-aware sequential image generation process, Hi3D addresses challenges in texture detail and view consistency that traditional 2D diffusion methods face. A key component? 3D Gaussian Splatting 🤘 All information: https://lnkd.in/eXkCQZ6M #gaussiansplatting #3DGS Gaussian Splatting

NumGrad-Pull transforms surface reconstruction by using tri-plane structures and numerical gradients for 3D point clouds! 🚀🔍 Enhancing detail fidelity and training stability in computer vision. #SurfaceReconstruction #ComputerVision #AIResearch

We’ve been obsessing about pushing the limits of vision with an ordinary camera: Fadlullah Adeola Raji’s recent work at ECCV 2024 demonstrates 3D imaging of hidden environments from a photograph of their soft shadows. Ordinary soft shadow photographs encode 3D information; however, reliably extracting that information is challenging. (Hint: The choice of representation is crucial, and this is consistent with Robinson Czajkowski's recent related work [https://lnkd.in/eRRnJdWT].) If you’re at #ECCV2024 and want to learn more, stop by tomorrow at Poster 232 on Soft Shadow Diffusion: Physics-inspired Learning for 3D Computational Periscopy. Congrats, Raji. Manuscript: https://lnkd.in/exRQej7Y Project page: https://lnkd.in/eXdGEYZK #ECCV2024 #ComputerVision #Imaging #NLOS

Free 2-hour online course to explore structure searching. Learning outcomes include performing advanced 3D structure searches to explore the values of distances, angles, rings, vectors, and planes in structures of interest. 🔗https://lnkd.in/e8_yg9C8 #STEM #Crystallography

How do you demonstrate the power of X-ray CT? What would you scan to showcase its abilities? This case study is one of my favorites for its creativity and its practical insights: "Christmas tree case study: computed tomography as a tool for mastering complex real world objects with applications in computer graphics" by Kanitsar et al. See the original paper here: https://lnkd.in/gCRMpM_Z The authors chose a 🎄 Christmas tree 🎄 as an example of a complex object that can be easily modeled using CT. CT effortlessly captured the intricate details of the tree's surfaces and interiors, proving the method's ability to handle real-world objects regardless of their complexity. The only catch was the metal artifacts. They removed all the metal parts, including the ornaments' hooks and candy wrappings, which left the study subject looking a little sad, but the CT scan turned out great. They concluded the case study by stating, "The data acquisition is independent from the object complexity, and both surfaces and object interiors are represented." It's such a brilliant and festive example of what X-ray CT can do. What's the most creative or surprising use of CT you've come across? Share your favorite case studies below! #computedtomography #christmastree

Proud to announce our recently published paper "Influence of Au alloying on solid state dewetting kinetics and texture evolution of Ag and Ni thin films" , which is also my first paper as a first-author. Many thanks to all contributors! https://lnkd.in/ezn2jjjc In the present work, we aim at a fundamental understanding of the role of alloying on the Solid-state Dewetting (SSD) kinetics and texture evolution of binary metallic alloy films by correlating X-ray diffraction and electron microscopy techniques. For that bilayers of a high (AuNi) and low (AuAg) atomic mismatch system are fabricated on different substrates and annealed utilizing a rapid thermal annealing furnace. Via quantitative texture analysis, we were able to show, that alloying reduces the degree of <111> texturing in the thin films deposited on amorphous substrates, whereas the AuNi films on Sapphire remain their <111> texture which is likely due to in-plane texturing along densely packed directions stabilizing the <111> out-of-plane texture. Regarding the thermal stability of alloy films, we found, that the SSD kinetics of the low-misfit AuAg system continuously changes with the Au concentration and can be perfectly described by composition dependent hole growth as reflected by the Mullins’ coefficient, while the high-misfit AuNi system resembles this behaviour only during early stages of SSD and shows a strong deviation of this behavior is found. The deviation from the Mullins coefficient indicates a shift in the prevailing mechanism, suggesting that this accelerated SSD occurs at compositions where the annealing temperature (T) approaches the melting temperature (Tm), i.e. liquidus line. Indeed, the reduced temperature (T/ Tm) exhibits its maximum within the compositional range where accelerated SSD is prominent.