Segment Anything Model for Grain Characterization in Hard Drive Design
This work addresses nanoscale material analysis for hard drive design, but it is incremental as it adapts an existing model to a new domain.
The paper tackles grain segmentation in hard drive material characterization by applying the Segment Anything Model (SAM) out-of-the-box, showing promising accuracy for property distribution extraction, and identifies four improvement areas with preliminary gains in two.
Development of new materials in hard drive designs requires characterization of nanoscale materials through grain segmentation. The high-throughput quickly changing research environment makes zero-shot generalization an incredibly desirable feature. For this reason, we explore the application of Meta's Segment Anything Model (SAM) to this problem. We first analyze the out-of-the-box use of SAM. Then we discuss opportunities and strategies for improvement under the assumption of minimal labeled data availability. Out-of-the-box SAM shows promising accuracy at property distribution extraction. We are able to identify four potential areas for improvement and show preliminary gains in two of the four areas.