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Bringing Chemistry, AI, and Design Together: Molecular Maker Lab Institute’s Escape Room

CBriddell
Contributor III
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By Christiana Briddell, ACS Green Chemistry Institute

The year is 2323, and you have been tasked with breaking into Lab 217 to restore it to a functional space after a previous team’s disagreements lead to disaster...

The year is 2323, and you have been tasked with breaking into Lab 217 to restore it to a functional space after a previous team’s disagreements lead to disaster…

Escape Room at the GC&E ConferenceEscape Room at the GC&E ConferenceThe Molecular Maker Lab Institute’s Escape Room: Lab 217 took its maiden voyage off the University of Illinois campus to the Green Chemistry & Engineering (GC&E) Conference in Atlanta, Georgia this past June, where it was a major success with the attendees. The Escape Room was nestled in the GC&E’s Innovation Hub, where shouts of triumph and delight could be heard as groups took on the Escape Room challenge.

Created through a collaboration between University of Illinois Urbana-Champaign students in the theater department and the School of Information Sciences, and the Molecular Maker Lab Institute researchers, Lab 217 was designed to emphasize teamwork and problem-solving as groups solved problems using AI and block-based chemistry to complete the mission.

The Molecular Maker Lab Institute (MMLI) is an NSF-funded AI Institute for Molecular Discovery, Synthesis Strategy, and Manufacturing. Not only is it a first-of-its-kind research institute within the U.S., but MMLI has a strong educational component to make AI and chemistry more accessible to students, educators and researchers from other disciplines. The Escape Room was only one one of many educational components of the Institute.

Rachel Switzky, the Director of the Siebel Center for Design leads the Education and Outreach team for MMLI. I caught up with her after the event to learn more about the project.

Q: Collaboration was a key concept both in the design of the Escape Room experience and of its creation between students with different backgrounds and researchers. What did you learn from this experience?

A: The escape room design project was a great example of successful collaboration. On the MMLI side, we created documents to provide sufficient context information to the escape room design students while ultimately leaving it open-ended to give them creative freedom. This approach allowed them to design something that could excite even those without a science background. MMLI graduate students supplemented the context with lab tours for the design students and assisted with the first rounds of puzzle pilot testing to ensure the puzzles were both interesting and true to their research. The ongoing communication between both sides resulted in this fantastic outcome!

Q:  Bringing the Escape Room to GC&E was a first for your team. How was the experience and how do you plan to use the Escape Room moving forward?

A: It was fantastic to see people outside of Illinois experience the escape room and to watch this less traditional approach take off at an ACS conference! Moving forward, we are partnering with the Siebel Center for Computer Science at UIUC to build a permanent installation of the escape room in their building. This will free up the mobile escape room for future conference deployments. In the near future, we will be at the ACS Conference in Denver this August and hope to take on more engagements beyond that.

Group at the GC&E Conference who did the Escape Room.Group at the GC&E Conference who did the Escape Room.

 

Q: The MMLI has many other educational and outreach initiatives. How were these designed? How are they being shared and what resources can the wider community access?

A: Beyond the escape room, we engage with K-12 students through informal STEM outreach via after-school programs, summer camps, and field trips. This past year, we piloted our curriculum in 10th grade chemistry classrooms and have begun making draft versions of these lesson plans available online in our resources section. All of our online education resources are available here and will continue to be updated.

We have also developed a digital tool called the “Digital Molecule Maker,” which allows users to create molecules based on specific functions without needing to understand chemical structures.

At the higher education level, we are creating content to introduce machine learning and automated synthesis into general chemistry classrooms. Through a collaboration with UIUC’s general chemistry department, we have piloted our function-first and HCD-informed curriculum. With new advances to our DMM platform, we hope to further integrate this into general chemistry labs. We will present our work at the Biennial Conference for Chemical Education at the end of July, and we aim to formalize our findings and curriculum for public access and future expansion.

Q: What is human-centered design and how does it relate to chemistry and AI?

A: Human-centered design (HCD) is an approach that prioritizes the end-user's experience throughout the design process. MMLI’s mission emphasizes “democratizing the fields of chemistry and AI through accessibility and approachability,” making HCD a natural fit and a key advantage of MMLI’s partnership with the Siebel Center for Design. Traditional chemistry education often relies heavily on memorization, which does not accurately reflect the true nature of being a scientist and can unnecessarily filter out talented students. HCD ensures that students interact with MMLI content in a way that empowers them and helps them develop critical thinking skills to explore scientific questions independently.

In bridging AI and chemistry, we face the unique challenge of designing not only for the end user but also for the AI or ML algorithms to understand the data and produce better predictions. The creativity required for designing AI systems also yields excellent results in education. The concept of “block-based chemistry,” featured in the Lab217 escape room and our Digital Molecule Maker, emerged from designing a “closed-loop exploration” of different molecule blocks. These blocks can be assembled via Suzuki coupling, produced and synthesized through automated synthesis, and the resulting data fed back into the algorithm to generate new predictions. This approach is well-suited for education because, much like AI, our target audience is not familiar with chemical structures, and thanks to block-based chemistry, they don’t need to be. It's exciting to see how HCD practices drive innovation in both research and education.

Interior of the Escape Room.Interior of the Escape Room.