A hollow capillary array is examined as a coupling window between an electron cyclotron resonance plasma vacuum ultraviolet ͑vuv͒ source and a separate processing chamber. The transmission of vuv through the capillary array as a function of wavelength is measured and shown to agree with theoretical calculations. A silicon wafer with a dielectric surface is then placed in the processing chamber and exposed to vuv, both with and without the capillary array. A Kelvin probe is used to measure the surface charge induced on the wafer by photoemission in both cases, which confirms the previously measured transmission values. The results show that a capillary array can efficiently couple vuv radiation from a source to a processing chamber without significant modification in the spectrum and its resulting effects on a material.
The dispersion and radiation loss of propagating modes in a plasma-filled Bragg waveguide are investigated. The Bragg waveguide at a center frequency of 10 GHz is modeled with the transfer-matrix method, which has been used to analyze optical Bragg fibers. We calculate the dispersion and radiation loss of the TE 01 , TM 01 , and HE 11 modes and show how they vary as a function of plasma density. As the plasma density inside the waveguide increases, the cutoff frequency of each mode increases. An increase in plasma density increases the radiation loss in the TE 01 mode while it decreases the radiation loss in the TM 01 mode; the effect on the HE 11 mode is to increase the radiation loss for frequencies above 10.2 GHz and decrease the radiation loss for frequencies below 10.2 GHz.
The resonant frequencies of a single cavity embedded in the three-dimensional layer-by-layer photonic crystal are studied with microwave experiments and transfer-scattering matrix method simulations. The effects of the number of cladding layers and the size of the embedded cavity on resonant frequencies and Q values are carefully examined. The fine increments of cavity size indicate a new pattern of relation between resonant frequencies and cavity sizes.
Introduction: MRI gradient-fields may induce extrinsic voltage between electrodes and conductive neurostimulator enclosure of implanted deep brain stimulation (DBS) systems, and may cause unintended stimulation and/or malfunction. Electromagnetic (EM) simulations using detailed anatomical human models, therapy implant trajectories, and gradient coil models can be used to calculate clinically relevant induced voltage levels. Incorporating additional anatomical human models into the EM simulation library can help to achieve more clinically relevant and accurate induced voltage levels, however, adding new anatomical human models and developing implant trajectories is time-consuming, expensive and not always feasible.Methods: MRI gradient-field induced voltage levels are simulated in six adult human anatomical models, along clinically relevant DBS implant trajectories to generate the dataset. Predictive artificial neural network (ANN) regression models are trained on the simulated dataset. Leave-one-out cross validation is performed to assess the performance of ANN regressors and quantify model prediction errors.Results: More than 180,000 unique gradient-induced voltage levels are simulated. ANN algorithm with two fully connected layers is selected due to its superior generalizability compared to support vector machine and tree-based algorithms in this particular application. The ANN regression model is capable of producing thousands of gradient-induced voltage predictions in less than a second with mean-squared-error less than 200 mV. Conclusion:We have integrated machine learning (ML) with computational modeling and simulations and developed an accurate predictive model to determine MRI gradientfield induced voltage levels on implanted DBS systems.
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