About Me

Hi, Iam a senior at The University of Texas at El Paso, pursuing a Bachelor of Science in Mechanical Engineering with a Minor in Mathematics and Computer Science. My passion lies in addressing engineering challenges at the intersection of additive manufacturing, machine learning, and advanced modeling, particularly for microelectronics and energy storage applications. With research experience at The University of Texas at El Paso, including contributions to the Energy Storage and Electronics 3D Printing Laboratory and the Advanced Modeling and Simulation Laboratory, as well as internships at Lawrence Berkeley National Laboratory, I aim to contribute to innovative solutions through interdisciplinary research.

  • Ferroelectric Devices
    Muñoz, J. A., Fernández, C. A., Kumar, P., Zeng, Y., Broad, J., Tritt, A., Nonaka, A., Griffin, S., Ramakrishnan, L., & Yao, Z. (Under Submission). Negative capacitance of ferroelectric field-effect transistor gate stacks in design parameter space.
  • Neural Operator Generalization
    Soroco, M., Tang, Y., Fernández, C. A., Totounferoush, A., Ren, P., Yao, J., Nonaka, A., Chen, W., & Mahoney, M. (Under Submission). Super-OOD-Bench: Evaluating, understanding, and improving out-of-distribution generalization of neural operators.
  • 3D Printed Solid Polymer Electrolytes
    Maurel, A., Fernández, C. A., Schiaffino, E. M., Mahmud, M. S., Delgado Ramos, K. L., Lin, Y., MacDonald, E., Merrill, L. C., Cardenas, J. A., & Martinez, A. C. (Under Submission). The effect of polymer molecular weight on the electrochemical and mechanical performance of 3D printed solid polymer electrolytes.
  • Advanced Additive Manufacturing
    Martínez, A. C., Schiaffino, E. M., Aranzola, A. P., Fernández, C. A., Seol, M.-L., Sherrard, C. G., Jones, J., Huddleston, W. H., Dornbusch, D. A., Sreenivasan, S. T., Cortes, P., MacDonald, E., & Maurel, A. (2023). Multiprocess 3D printing of sodium-ion batteries via VAT photopolymerization and direct ink writing. *Journal of Physics: Energy, 5(4), 045010.* https://doi.org/10.1088/2515-7655/acf958
  • Conference Presentations
    - Fernández, C. A., Muñoz, J., Zeng, Y., Kumar, P., Nonaka, A., & Yao, Z. (2024). Ferroelectricity-induced negative capacitance in microelectronic devices via phase-field simulations and machine learning. *APS March Meeting 2024.* (Oral presentation).
    - Fernández, C. A., Schiaffino, E., MacDonald, E., Merrill, L., Cardenas, J., Martínez, A., & Maurel, A. (2024). Digital light processing of solid polymer electrolytes for lithium-ion batteries. *Solid Freeform Fabrication Symposium 2024.*
    - Fernández, C. A., Schiaffino, E., Aranzola, A., Martínez, A., Maurel, A., & MacDonald, E. (2023). Electrochemical stability of 3D printed separators and gaskets for shape-conformable lithium-ion batteries. *Solid Freeform Fabrication Symposium 2023.*
  • Lawrence Berkeley National Laboratory
    Developed and tested machine learning models to optimize microelectronic devices and contributed to high-performance computing frameworks.
  • UTEP Energy Storage and Electronics 3D Printing Lab
    Contributed to advanced material development for sodium-ion and lithium-ion batteries, optimizing electrochemical and mechanical performance.
  • UTEP Advanced Modeling and Simulation Lab
    Utilized stochastic modeling and molecular dynamics to analyze thermal diffusion and fluid dynamics in complex systems.
  • Mechanical Engineering
    Designed and optimized systems using Autodesk Fusion 360 and nTopology for 3D printing and energy storage applications.
  • Molecular Simulations
    Developed Python-based simulations for temperature-dependent diffusion and fluid mechanics challenges under Dr. Muñoz’s mentorship.
  • 3D Printing & Design
    Formulated polymer electrolytes and conducted mechanical characterization tests to enhance battery performance.
  • Data Analysis & Machine Learning
    Post-processed large datasets, developed CNNs and FNO models, and automated workflows for high-performance computing projects using libraries such as Python, NumPy, Pandas, Matplotlib, Scikit-learn, and PyTorch.
  • The University of Texas at El Paso
    Bachelor of Science in Mechanical Engineering with a Minor in Mathematics and Computer Science (Expected: May 2025).
  • NASA L'SPACE Academy
    Collaborated on mission concepts and preliminary design reviews, focusing on system requirements and risk management.

Research Interests

Additive Manufacturing for Energy Storage

My research focuses on advancing additive manufacturing techniques, such as digital light processing (DLP) and stereolithography, to create high-performance materials for energy storage systems. I have worked on optimizing gel polymer and solid polymer electrolytes for sodium-ion and lithium-ion batteries, balancing printability and electrochemical performance.

Modeling of Advanced Materials

I am dedicated to computational modeling of advanced materials, particularly ferroelectric and dielectric compounds. Using phase-field simulations and partial differential equation solvers, I aim to optimize material properties and device performance, contributing to advancements in microelectronics.

Machine Learning in Engineering

My research integrates machine learning techniques, such as Convolutional Neural Networks (CNNs) and Fourier Neural Operators (FNOs), into engineering workflows. I am particularly interested in using these methods to improve simulation efficiency and scalability in materials science and microelectronics applications.

Highlights

Simulations

Simulations provide a controlled environment to model, analyze, and predict complex systems, offering insights that guide real-world decisions

Design

Simulations provide a controlled environment to model, analyze, and predict complex systems, offering insights that guide real-world decisions

data analisis

Simulations provide a controlled environment to model, analyze, and predict complex systems, offering insights that guide real-world decisions

See more

Contact Me

[email protected]

(915)-478-95-83

Download CV