Ciencias Exactas y Ciencias de la Salud

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Multiplexed biossensors based ok multimode nanoslits
(Instituto Tecnológico y de Estudios Superiores de Monterrey, 2025-06) Valero Recio Ramirez, Marcos Enrique; Mallar, Ray; emimmayorquin; De León Arizpe, Israe; Coello Cárdenas, Víctor Manuel; Pérez González, Víctor Hugo; Hernández Arana, Raúl Ignacio; Anis, Hanan; Prakash, Ravi; Campus Monterrey; Berini, Pierre
Surface plasmon-based biosensors are widely recognized for their exceptional sensitivity, ease of integration, and versatility across various fields, including biomedical diagnostics, environmental monitoring, and chemical analysis. While these sensors have demonstrated significant potential for real-time, label-free detection, they still face key challenges—one of the most critical being multiplexing. The ability to simultaneously detect multiple biomarkers is particularly important in medical diagnostics, where comprehensive assessments can lead to earlier and more precise disease detection. However, current surface plasmon technologies face limitations in achieving effective multiplexing, underscoring the need for innovative configurations. This thesis presents the design, modeling, fabrication, and experimental validation of a novel surface plasmon resonance (SPR) interferometric biosensor capable of supporting multiplexed detection. The proposed device operates by exciting and interfering counter-propagating surface plasmon waves in a nanoslit structure using optimized grating couplers, achieving high-visibility interference patterns. Full-wave electromagnetic simulations demonstrate a maximum bulk sensitivity of Sb = −3.87W/(m·RIU), a surface sensitivity of Ss = 0.002W/(m·nm), and a resolution down to Rb = 6.3 × 10−6 RIU and Rs = 10 pm, depending on the nanoslit geometry. The optimal grating coupler design reached a total coupling efficiency of 54.7%, ensuring effective SPR excitation with Gaussian beam illumination. To enable multiplexing, a shadowing structure was developed and integrated to allow simultaneous excitation of multiple sensing units with a single expanded Gaussian beam. Simulations confirmed that the device maintains independent sensing responses in each channel with minimal crosstalk. A complete fabrication process, including gold deposition, electron beam lithography, focused ion beam milling, and CYTOP-based microfluidic integration, was implemented. The final device successfully detected refractive index changes in water-glycerol mixtures, experimentally validating the interferometric sensing principle and confirming agreement with theoreticalpredictions. These findings demonstrate that the interferometric SPR platform not only functions as a highly sensitive refractive index sensor, but also offers scalable multiplexing capabilities. This work lays the groundwork for future advancements in three key directions: miniaturizing the optical system for portable diagnostics, functionalizing the sensor for selective biomarker detection, and integrating spatial light modulators for real-time, multi-channel interrogation. Together, these developments promise to enhance the applicability of SPR biosensing in real-world biomedical and clinical diagnostics.
Design and Development of Conducting Polymer and Carbon Nanostructure based Efficient Thermoelectric Materials
(Instituto Tecnológico y de Estudios Superiores de Monterrey, 2024-12-02) Ebrahimibagha, Dariush; Mallar, Ray; emimmayorquin; Aguirre Soto, Héctor Alán; Niladri, Banerjee; Gallo Villanueva, Roberto Carlos; School of Engineering and Sciences; Campus Monterrey; Datta, Shubhabrata
Thermoelectric materials present a promising renewable energy technology for directly converting thermal energy into electricity and vice versa. However, their practical application is hindered by low conversion efficiencies, quantified by the dimensionless figure of merit, 𝑍𝑇 = 𝑆 2 𝜎 𝑘 𝑇 , where 𝑆,𝜎, and 𝑘 are the Seebeck coefficient, electrical onductivity, and thermal conductivity, respectively. Achieving a high 𝑍𝑇 is challenging because enhancing one parameter often degrades the others. Various nanoscale strategies have been explored, yet a comprehensive framework for improving 𝑍𝑇 remains elusive. Recently, polymer-based nanocomposites, particularly carbon nanotubes (CNTs) dispersed in polyaniline (PANI), have gained attention due to their flexibility, non-toxicity, and processability, key traits for next-generation flexible electronic devices. Despite this potential, optimizing thermoelectric performance in PANI-CNT systems is complex, as it depends on numerous factors, including CNT dimensions, functionality, and PANI's doping and morphology. This research employs machine learning (ML) and genetic algorithms (GA) to model and optimize the thermoelectric properties of PANI-CNT nanocomposites. By analyzing structural and compositional variables—such as CNT length, diameter, type, and PANI morphology—we identified strategies that enhance electrical conductivity and the Seebeck coefficient while minimizing thermal conductivity. Our ML models revealed that selecting appropriate dopants for PANI and using single-walled CNT (SWCNT) improves overall thermoelectric performance. Multi-objective GA optimization further refined these findings, demonstrating that SWCNTs help reduce thermal conductivity and that CNT length plays a dual role: shorter CNTs decrease 𝑘, while longer ones enhance both 𝑆 and 𝜎. Experimental validation was performed by fabricating PANI-CNT nanocomposite pellets, but achieving high 𝑍𝑇 remained elusive due to limitations in dataset quality and the variability introduced by diverse synthesis techniques. The synthesis method influences PANI dimensionality (e.g., 0D, 1D, 2D) and the morphology of PANI-CNT composites (core-shell vs. dispersed), complicating performance consistency. While the experiments confirmed the general trend of model predictions, they highlighted the necessity of cleaner, more comprehensive datasets for future research. Ultimately, this study lays the groundwork for designing high-efficiency thermoelectric nanocomposites and outlines the next steps in developing more accurate predictive models and synthesis methods for improved thermoelectric performance.

Ciencias Exactas y Ciencias de la Salud

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