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Optimizing strong magnetic fields to scale up semiconductor manufacturing

JUN 14, 2024
Magnetic fields can be optimized to enhance the yield of extreme ultraviolet radiation from laser-driven plasmas.

Optimizing strong magnetic fields to scale up semiconductor manufacturing lead image

Created using laser-driven plasmas, Extreme Ultraviolet (EUV) lithography is essential to our ability to scale semiconductor manufacturing. EUV is typically generated from laser-produced plasmas (LPPs), but researchers have not fully investigated the effects of one key method used to generate those plasmas: strong magnetic fields. Kim et al. simulated the behavior of LPPs in the presence of strong magnetic fields, showing that magnetic fields can significantly alter plasma behavior and consequently affect EUV generation.

The team found that LPPs are highly dependent on the strength and direction of the magnetic field applied to the plasma, resulting in an anisotropic plasma confinement that can be tuned to reduce the amount of radiation that escapes. These results can be applied to optimize magnetic fields and maximize EUV generation.

“The transport of charged particles within this magnetically confined plasma favors effective plasma heating,” author Joohwan Kim said. “The magnetic confinement and enhanced heating facilitate easier radiation escape with reduced loss, leading to a higher EUV yield compared to the non-magnetized plasma case.”

In the study, the team used the simulation tools FLASH (for radiation hydrodynamics) and SPECT3D (for atomic dynamics) to model LPPs, EUV generation, and radiation transport for laser intensities below 1011 W cm−2. These techniques allowed the team to model EUV flux at different angles for a given strength of magnetic field.

Kim says future work could investigate parameters beyond those in the study, such as varying laser intensity within the magnetic field and incorporating a pre-pulse process.

Source: “Computational study of laser-produced plasma, EUV generation, and the impact of magnetic fields,” by J. Kim, M. Bailly-Grandvaux, and F. N. Beg, AIP Advances (2024). The article can be accessed at https://doi.org/10.1063/5.0207401 .

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