Tag: Physics and Engineering

Low Cost Design Techniques to Convert Radio Frequency (RF) Signals into usable DC power sources (Paul Aiken)

On campus: this project is scheduled to begin on 6/30/2025 and run for 6 weeks, finishing on 8/8/2025.

Project Description

Extracting usable power from RF signals involves converting electromagnetic energy into a usable DC form. The following techniques will be explored using components employed in RF energy harvesting systems: 1. Tuned and matched antenna Design to capture RF signals from the environment and converts them into AC voltage. 2. Impedance matching techniques to maximize the power transfer from the antenna to the the rectifier circuit. 3. Rectification of AC signals to convert the captured AC signal into DC power for storage. 4. Voltage multipliers to get usable magnitude for DC voltages.

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Prerequisites

Students should have taken ENGN 295D-01 Analog Circuits and Applications and/or ENGN/PHYS 207 Electrical Circuits.

Special Comments

Project Information (subject to change)

Estimated Start Date: 6/30/2025

Estimated End Date: 8/8/2025

Estimated Project Duration: 6 weeks

Maximum Number of Students Sought: 3

Research Location: On campus

Contact Information: Paul Aiken (email: paiken@wlu.edu)

Lattice regularization of one-dimensional field theory (Son Nguyen)

Remote: this project is scheduled to begin on 6/2/2025 and run for 10 weeks, finishing on 8/8/2025.

Project Description

Lattice regularization is a technique for studying quantum field theories (QFTs). It involves breaking continuous space into discrete points, forming a “lattice.” In continuous QFT, the mathematics often leads to infinities that are ambiguous and difficult to handle. Discretizing space is an efficient method to remove these infinities and allow calculations to be performed numerically. This makes the theory more straightforward to study on a computer. In the limit where the lattice spacing approaches zero, one crucial question is whether we can get back the physics of the continuum theory. This approach provides the foundation for simulating particle interactions on quantum computers.

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Prerequisites

PHYS 111, PHYS 112, Modern Physics, Quantum mechanics and some experience with SciPy or NumPy.

Special Comments

N/A

Project Information (subject to change)

Estimated Start Date: 6/2/2025

Estimated End Date: 8/8/2025

Estimated Project Duration: 10 weeks

Maximum Number of Students Sought: 1

Research Location: Remote

Contact Information: Son Nguyen (email: snguyen@wlu.edu)

CLOSED: Toward a hyper-empirical gravitational wave source localization routine based on the Northstar algorithm (Tom McClain)

On campus: this project is scheduled to begin on 6/23/2025 and run for 8 weeks, finishing on 8/15/2025.

Project Description

The primary purpose of this research project is to determine if it is possible to build a hyper-empirical gravitational wave source localization routine around the Northstar algorithm I developed some years ago. This routine would use empirical signal modeling techniques similar to those (presumably) used by neural networks to perform source localization very quickly (i.e., on the same time scales as a neural network) while maintaining full control over parameter choices and failure modes (like the traditional approach using numerical templates from general relativity). Depending upon the success or failure of the initial builds, the project may also include testing or refinement of the routine, from small tweaks in program parameters up full runs on realistic data sets using cutting-edge GPUs on Amazon Web Services.

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Prerequisites

The ideal candidate would have completed PHYS 111, PHYS 112, and CS 111, and would have at least a small amount of experience with SciPy or NumPy. But the most important criteria is engagement; interested students should apply regardless of previous experience.

Special Comments

Project Information (subject to change)

Estimated Start Date: 6/23/2025

Estimated End Date: 8/15/2025

Estimated Project Duration: 8 weeks

Maximum Number of Students Sought: 3

Research Location: On campus

Contact Information: Tom McClain (email: mcclaint@wlu.edu)

CLOSED: Machine learning based method for rock texture analysis (Mengying Liu)

Hybrid: this project is scheduled to begin on 6/2/2025 and run for 10 weeks, finishing on 8/8/2025.

Project Description

The typical methods used to assess crystallographic texture of rocks are classical U-stage microscopy (which is based on light microscopy) or electron backscatter diffraction (EBSD, which is based on scanning electron microscopy). The first is an inherently laborious technique with low resolution, while the second is very time-consuming and could only take a limited number of grains per measurement. The idea of this project is to leverage both techniques’ strengths and develop an automated system capable of accurate crystallographic texture analysis using polarized light microscopy. Using machine learning, we can now analyze the polarization-dependent reflectance signals of crystalline surfaces from a stack of micrographs and register them with their crystal orientations. The success of the proposed research can revolutionize the texture analysis of rocks by reducing the time from days to minutes.

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Prerequisites

One student has taken Materials Engineering or Earth Materials or plans to take in Winter 2025; The other one student must have coding experience with MATLAB or Python

Special Comments

Students are expected to take one credit research during Winter or Spring 2025; One student might need to travel to the University of Cambridge for data collection.

Project Information (subject to change)

Estimated Start Date: 6/2/2025

Estimated End Date: 8/8/2025

Estimated Project Duration: 10 weeks

Maximum Number of Students Sought: 2

Research Location: Hybrid

Contact Information: Mengying Liu (email: mliu@wlu.edu)