Mr. Christian Tolfa Profile

Christian Tolfa

at Lawrence Livermore National Lab

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Publications (2)

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Proceedings Article | 4 March 2022 Presentation + Paper

Bio-organism detection using microsphere resonators in fluidics

B. Demory, L. Echeveria, S. Gilmore, C. Tolfa, S. Harrison, G. Chavez, P. Singh, A. S. Chang, T. Bond

Proceedings Volume 11987, 1198708 (2022) https://doi.org/10.1117/12.2610234

KEYWORDS: Sensors, Microfluidics, Particles, Resonators, Optical spheres, Pathogens, Bacteria, Water, Refraction

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The evolution of pathogens has increased the demand for a sensing and detection platform, capable of qualifying constituents in real time. Whispering Gallery Mode Resonators provide an ideal biochemical sensing platform due to their low cost, high sensitivity, and low impact on the analyte. These resonators have high quality factors and possess the ability to detect minute changes in the local environment, as the light traveling on the surface of the resonator, when at resonance interacts with the surrounding medium for interaction lengths on the order of ~10-100cm’s . These changes in physical properties are captured through shifts of the resonance wavelength, resonance dip intensity, and/or quality factor. In this work, we provide our design of a 3-D printed microfluidic cell that is compatible with our taper and sphere coupling scheme developed from our previous work. Initially, the baseline performance of the resonator fluidic system was established by measuring the resonance wavelength shift due to refractive index change from water to phosphate buffered saline (PBS). Next, we showcase our biofunctionalization procedure and measure the accumulation of pathogens, such as E. Coli and Influenza A, on the resonator’s surface. The presence of these biological analytes results in small changes in the resonator’s diameter and refractive index, which manifests in real time as a red shift of the resonance wavelength on the picometer scale. Finally, we develop the foundation for a silicon integrated circuit chip resonator system, resulting in a further reduction of our system’s footprint.

Proceedings Article | 5 March 2021 Presentation + Paper

Progress on optical microspheres for CO2 sensors

B. Demory, S. Harrison, C. Tolfa, L. Echeveria, P. Singh, V. Khitrov, K. Heinz, A. S.-P. Chang, T. Bond

Proceedings Volume 11672, 116720R (2021) https://doi.org/10.1117/12.2583278

KEYWORDS: Sensors, Carbon dioxide, Optical fabrication, Microresonators, Gas sensors, Environmental sensing, Thermal optics, Tapered optical fibers, Spherical lenses, Resonators

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Shrinking the volumetric footprint of gas sensors is desirable as it allows for nonintrusive, nonperturbing gas mixture analysis and access to tight enclosures. Micro-resonators are a perfect candidate for these sensors as their size parameter (~micron) is minimal, and the typical surface propagating whispering gallery modes can interact with an analyte without disrupting the environment. The large, quality factor (Q) of these resonant cavity modes enables long interaction lengths on the order of 100s of centimeters between the optical field and analyte. Thus, the presence of a gas different than the nominal environment will result in a shift of the resonant properties, including the resonant wavelength, amplitude, and quality factor, that can be detected in real-time. To illustrate this effect, we utilized a spherical micro resonator on the end of a piece of optical fiber, formed using standard ball lens fabrication, and excited the resonant modes using a tapered optical fiber connected to tunable Infrared laser. The resonator was fixed in contact with the tapered region of fiber, and the assembly was placed inside an in-house, optically coupled, vacuum-tight vessel for gas testing. We compared the spectral response of air, pure CO2, and pure N2 gas, observing spectral shifting and broadening of the cavity resonances. In addition, the effect of vessel temperature on resonance peak position due to the thermo-optic effect was investigated and quantified. Lastly, a feedback arm was added to the setup to reduce signal noise and automated data analysis was implemented to improve data clarity.

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