Building Chemistry and Professional Skills in a Solid-State Research Laboratory through Automated Materials Discovery
Let's build an automated lab together!
Project description
The De Jesús Báez lab seeks to understand how structural distortions can be engineered by tuning metamorphology, composition, and nucleation/growth pathways and how these alter oxidation states in solids. These distortions act as an additional knob to design materials with improved catalytic function and electrochemical energy storage. Because the combinatorial space of chemistries and synthesis conditions is enormous, exhaustive exploration by manual student-led synthesis is unfeasible. To overcome this limit, the lab seeks to integrate artificial intelligence-driven materials discovery with automated synthesis to accelerate exploration of vast synthetic space. In this project, students will prototype an AI-directed automated experimental platform to traverse large synthetic design spaces and to determine links between synthesis conditions and the extent of stabilization of defects/distortions.
Project outcome
Students will learn how to develop scientific questions that focus on fundamental chemistry and the development of a hypothesis-driven experiments that can help answer the questions. Students will also gain proficiency in essential computational and experimental techniques, such as AI for scientific discovery, X-ray diffraction, Raman spectroscopy, X-ray absorption and emission spectroscopy, electrochemistry, heterogeneous catalysis, and electron microscopy. These are techniques that are usually associated with graduate level studies and thus they will provide students with a different perspective in the sciences from lecture classes and help expand on their understanding of chemistry.
Project details
| Length of commitment | Year-long |
| Start time | Spring |
| In-person, remote, or hybrid? | In-person |
| Level of collaboration | Large group collaboration (4+ students) |
| Benefits | Stipend |
| Who is eligible | Sophomores, juniors, and seniors with an interest in chemical/materials sciences and basic knowledge of coding in Python. Must have passed CHE 101/102 and at are at least currently taking CHE 201/202. |
Project mentor
Luis De Jesús Báez
Assistant Professor
Chemistry
Phone: (716) 645-4310
Email: ldjesus@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.
Read about automated lab in the article titled Self-Driving Laboratories for Chemistry and Materials Science (https://pubs.acs.org/doi/10.1021/acs.chemrev.4c00055). This will provide perspective in what the current challenges are and think about how to address it.
Keywords
automated labs, chemistry, computer science, AI, engineering