Neurotronics: Designing Materials for Bioelectronics
Explore cutting-edge projects in computational materials design, machine learning, and emerging applications in neuromorphic computing, bioelectronics, and light-harvesting.
Project description
You’ll tackle projects in computational materials design (from high-throughput modeling and phase-diagram simulations to training machine-learning models on experimental signals such as UV–Vis/IR) that predict synthesis routes for new materials. You’ll also collaborate closely with partners leading synthesis and characterization.
We study a broad range of conjugated polymers, solvents, and small-molecule systems for applications in neuromorphic computing, bioelectronics, and light-harvesting. Prior experience in computational modeling, ML, or materials informatics is a plus, but curiosity, rigor, and willingness to learn matter most.
Project outcome
Perform high throughput analysis of phase diagrams for the design of co-solvents and understanding of phase behavior in organic thin films
Develop technical expertise in computational materials modeling, machine learning, and simulation methods.
Gain interdisciplinary research experience by connecting computational predictions with experimental signals (UV-Vis/IR) and collaborating with synthesis/characterization teams.
Strengthen scientific communication through presenting results, writing reports, and engaging with a diverse research team.
Project details
| Length of commitment | Year-long (10-12 months) |
| Start time | Anytime |
| In-person, remote, or hybrid? | Hybrid Project (can be remote and/or in-person; to be determined by mentor and student) |
| Level of collaboration | Small group project (2-3 students) |
| Benefits | Research experience Stipend |
| Who is eligible | All undergraduate students with programming and analytical thinking skills |
Project mentor
Olga Wodo
Associate Professor
Materials Design and Innovation
Phone: (716) 645-1377
Email: olgawodo@buffalo.edu
Start the project
- Email the project mentor using the contact information above to express your interest and get approval to work on the project. (Here are helpful tips on how to contact a project mentor.)
- After you receive approval from the mentor to start this project, click the button to start the digital badge. (Learn more about ELN's digital badge options.)
Preparation activities
Once you begin the digital badge series, you will have access to all the necessary activities and instructions. Your mentor has indicated they would like you to also complete the specific preparation activities below. Please reference this when you get to Step 2 of the Preparation Phase.
- Familiarize yourself with the principles and application of bioelectronics (mixed transport).
- Read this article.
Keywords
machine learning, AI, materials science, engineering, physics, mathematics, materials design and innovation