Tungsten’s exceptional density, strength, and thermal properties make it one of the most important materials in metal additive manufacturing (AM). But when it comes to successful printing, particle size alone isn’t enough - manufacturers have to dig deeper.
Vision Analytical’s Raptor Dynamic Image Analyzer provides users with in-depth insight into tungsten powder morphology, looking beyond particle size to highlight their behavior and variety in both wet and dry suspensions.
The Limits of Conventional Particle Size Analysis
Traditional techniques such as laser diffraction or sieve analysis only provide information on particle size distributions.
These methods are unable to reveal particles’ true shape, surface texture, or dispersion behavior; particle characteristics that are essential for predicting flowability, sintering performance, packing density, and powder spreadability in AM processes.
Dynamic Image Analysis (DIA) can be used to fill this analytical gap.
Wet Versus Dry Dispersion Analysis
Vision Analytical tested tungsten metal powders on its Raptor Dynamic Image Analyzer under different conditions:
- Dry dispersion, using the instrument’s integrated dry powder feeder
- Wet suspension, using the instrument’s liquid flow cell
Key Observations
Wet dispersion revealed primary particles by breaking up agglomerates, while dry dispersion was found to maintain more of the bulk morphology. The capacity to compare both modes facilitated improved understanding of the powder’s true characteristics.
It was also noted that the Raptor’s image-based classification engine offered both visual validation and vital quantitative data on particle shape and size. This combination of visual and quantitative data is unachievable via traditional methods.
Switching Between Wet and Dry Modes
The Raptor’s seamless transition between dry and wet analysis is one of its most versatile features. Users can switch between these modes in less than 5 minutes, with no need for recalibration or complex setup.
This flexibility offers production teams and materials scientists several advantages, including:
- The ability to validate results across dispersion conditions
- The capacity to troubleshoot processing issues
- The potential to optimize formulation or blending techniques
- Real-time maintenance of consistent powder quality control
True Particle Classification
The Raptor’s automated classification and data filtering tools are another key benefit, in addition to its high-resolution imaging. During the tungsten powder analysis, the Raptor’s software enabled:
- Filtering by aspect ratio, circularity, and elongation
- Detection of outliers, including oversized contaminants or fines
- Segmentation of particle population into shape-defined classes
These capabilities are essential in meeting the strict tolerances necessary in metal AM, powder metallurgy, and thermal spraying.
Applications in Metal Additive Manufacturing
Understanding the behavior of tungsten powders in both wet and dry forms has direct implications for applications such as powder bed fusion (PBF), binder jetting, refractory part manufacturing, and hot isostatic pressing (HIP).
Manufacturers looking to maintain tight control over material performance and print quality can gain significant benefits from shape-based particle classification.
Additive manufacturing metal powders. Particle size & shape, wet & dry suspension. Shape matters!
Video Credit: Vision Analytical Inc.
Conclusion
Using both wet and dry suspension analysis with the Raptor DIA provides a clearer, more comprehensive picture of tungsten powder properties, whether used in additive manufacturing, materials research and development, or quality control.
The Raptor sets a new standard for advanced particle analysis with its capacity for shape-based classification and a rapid, user-friendly interface.
Acknowledgments
Produced from materials originally authored by Vision Analytical Incorporated.
This information has been sourced, reviewed, and adapted from materials provided by Vision Analytical Inc.
For more information on this source, please visit Vision Analytical Inc.