According to a recent LinkedIn post from Rad AI, the company is emphasizing simulation work comparing THM-grown and Bridgman-grown CZT crystals for photon-counting CT detectors. The post suggests that higher hole lifetimes in THM-grown CZT materially improve charge collection efficiency, especially under clinical CT photon flux conditions.
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The post highlights Monte Carlo simulations showing that charge collection efficiency can rise from 78% at 10 ns hole lifetime to 99.8% at 2000 ns, with Bridgman material typically in the 50–200 ns range and THM achieving over 1000 ns. According to the analysis, even a few percentage points of efficiency difference may translate into measurable gains in spectral resolution, material decomposition accuracy, and reduced dose requirements.
The content also notes that higher bias voltages can partially offset limitations in Bridgman-grown CZT, but that THM-grown material retains an advantage across voltages. While THM crystals are described as more costly, the post frames them as potentially delivering superior performance where photon-counting CT image quality is critical.
For investors, the post implies that Rad AI is focusing on detailed detector-physics simulations to guide spectral CT detector optimization before fabrication. This simulation-driven approach could support differentiated product performance in photon-counting CT, potentially improving the company’s competitive positioning in advanced medical imaging and justifying premium pricing for higher-end detector solutions.