Authors: Ceren Cengiz, Shima Shahab

Published on: February 05, 2024

Impact Score: 8.15

Arxiv code: Arxiv:2402.02682

Summary

• What is new: Development of Acoustic Holographic Lenses (AHLs) that can generate programmable heat patterns from ultrasound, facilitated by machine learning.
• Why this is important: Limited understanding of acousto-thermal dynamics in AHLs for precise temperature control in materials.
• What the research proposes: A machine learning-assisted approach for efficient AHL design, translating thermal information into a holographic representation.
• Results: Successful experimental verification of pressure and thermal measurements, proving the capability of AHLs in precise temperature control within complex mediums.

Technical Details

Technological frameworks used: Machine learning-assisted single inverse problem approach

Models used: Latent functions for pressure phase and amplitude conversion

Data used: Experimental pressure and thermal measurements

Potential Impact

Medical imaging and therapy, materials processing, consumer electronics

Want to implement this idea in a business?

We have generated a startup concept here: HoloTherm.