Opportunity: Next-Generation Microelectronics: Characterization, Modeling, and Analysis of Emerging Ferroelectric Devices

Opportunity Number:

ARL-SRP-00060

Opportunity Location:

Adelphi, MD

Opportunity Description:

Are you interested in exploring the physical hardware technologies that will power the future of microelectronics?

Next-generation ferroelectric devices, including Ferroelectric Field-Effect Transistors (FeFETs) and Ferroelectric Capacitors (FeCAPs), are at the forefront of solid-state research, offering transformative potential for low-power non-volatile memory and neuromorphic hardware.

Because characterizing these emerging technologies is a multifaceted challenge, this research opportunity is designed to be flexible. Depending on your academic background, technical strengths, and interests, your project will focus primarily on one or more of the following core areas:

1) Experimental Testing & Hardware Setup: Collaborating with research staff to develop, configure, and execute custom electrical test protocols across various wafer probe stations.

2) Data Analysis & Visualization: Designing and implementing automated Python or MATLAB pipelines to process, analyze, and visualize large, high-throughput experimental datasets.

3) Device Physics & Modeling: Fitting experimental laboratory data to physical models using numerical tools to assist with parameter extraction and help explain underlying device behavior.

The Universal Expectation: Regardless of which technical track your project focuses on, reproducibility and clear communication are key. You will be expected to author comprehensive technical documentation, detailed code comments, or standard operating procedures for the specific workflows, scripts, or test setups you develop during the summer.

This approach ensures a tailored, high-impact summer experience that aligns with your career goals, whether you are leaning toward experimental laboratory engineering, scientific computing, or device physics.

Opportunity Skill Set:

Computer Science, Computer Modeling/Simulation, Data Science, Electrical Engineering, Electronics, Materials Engineering, Physics