Nanoscale Insights

Driven by AI

Raynetics is accelerating materials discovery and characterization through next-gen 3D imaging and AI-driven analysis

Deeper
insights into
nanostructures

Raynetics transforms raw S/TEM microscopic images into precise 3D models up using AI.
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Partners & Supporters
Platform
3D-Imaging of Nanostructures
Raynetics helps companies and research institutions transform their raw electron microscopic images into precise 3D models using AI.
Unmatched Precision
Fast Turnaround:
Scalable Access
Applications
3D imaging is critical for defect detection, design optimization, and functional analysis
Challenge
Detecting sub-microscopic defects e.g. in advanced semiconductor components often leads to production delays or compromised quality. Traditional methods struggle with identifying these defects efficiently.
Solution
Raynetics’ AI-powered 3D imaging provides precise visualizations of nanostructures, enabling early detection of surface and subsurface defects. This accelerates quality control processes and reduces costly production downtime.
Early defect detection
Minimized production delays
Improved product reliability
Challenge
Ensuring that nanostructures meet design specifications is critical for product performance. However, conventional imaging techniques often fail to accurately compare complex designs to production outputs
Solution
Raynetics creates highly detailed 3D models that allow side-by-side comparisons of designs and final structures. This ensures compliance with specifications and speeds up iterations for R&D teams
Precise design validation
Faster R&D cycles
Reduced risk of performance issues
Challenge
Understanding how nanostructures behave under operational conditions is essential for predicting performance. Traditional imaging techniques do not offer the level of detail needed to assess functionality at the nanoscale
Solution
Raynetics’ 3D imaging enables researchers to analyze the structural integrity and functional properties of nanostructures under simulated operational environments. This supports better predictions of real-world performance.
In-depth functional insights
Enhanced reliability predictions
Optimized performance designs

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