Theoretical modeling demonstrates a terahertz biosensor's ability to detect leukemia via resonance shifts, suggesting practical implications for noninvasive diagnostics.
Bone marrow biopsy remains the standard for leukemia diagnosis because no noninvasive test can yet resolve the slight refractive index difference between healthy and cancerous lymphocytes. Terahertz metamaterial absorbers promise label-free dielectric sensing, yet existing designs mostly operate below 5 THz with sensitivities under 1300 GHz/RIU. To address this gap, this work proposes a highly sensitive terahertz metamaterial absorber, utilizing an Al-PTFE-Al configuration with an octagonal complementary resonator. The design partitions electromagnetic fields through strategically placed capacitive gaps that decouple radiative and absorptive loss channels, yielding ultra-narrow absorption peaks. At the third resonance peak, the maximum quality factor reaches 468.16 for the healthy condition and 409.92 for the cancerous condition. Simulations demonstrate a maximum absorption of 99.99%, a sensitivity of 3926 GHz/RIU, and a figure of merit reaching 141.8 ⁻ ¹ RIU ⁻ ¹ . When numerically tested with the dielectric signature of Jurkat cells, an established model of acute T-cell leukemia, the sensor exhibits distinct resonance frequency shifts that differentiate malignant from healthy lymphocytes. The third absorption band exhibits particularly stable and high performance, suggesting its suitability for consistent biosensing operation. Since this work is purely computational and does not involve building a physical prototype at the present stage, it remains theoretical in nature. Nevertheless, a detailed fabrication pathway compatible with standard microfabrication techniques is outlined to guide future experimental validation. The findings indicate that the proposed Al–PTFE–Al metamaterial absorber is a promising candidate for further development toward terahertz biosensing platforms, with potential relevance to leukemia detection and other hematologic malignancy diagnostics.
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Chy et al. (2026) studied this question.
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