ILM Funding Will Help Advance Undergraduate Exposure to Computational Chemistry, Update Lab Equipment

In 1965, Intel CEO Gordon Moore theorized that the number of transistors on silicon computer chips would exponentially increase every 10 years, making increasingly powerful computing components less expensive over time. In the nearly 50 years since his idea was dubbed “Moore’s Law” in 1970, his hunch has proven true. Today, smartphones contain more computing power than the 1970s supercomputers that occupied entire rooms.

As computing equipment continues to improve at a rapid pace, maintaining a modern computing infrastructure becomes an ongoing priority. For the Department of Chemistry at UW-Madison, modern computing facilities and equipment help support a robust research enterprise and provide computational chemistry experiences for some of the nearly 12,000 students who take chemistry classes each year.

Two efforts to update the department’s computational facilities and lab equipment recently received funding from UW-Madison’s Instructional Laboratory Modernization (ILM) program. ILM supports updates to existing learning environments by funding new equipment and supplies, as well as improvements to physical spaces. Undergraduates who take chemistry classes benefit greatly from departmental lab directors’ success in obtaining ILM awards that help the department maintain state-of-the-art lab instrumentation and facilities.

An award of $40,000 will expand the capacity of the department’s Phoenix Research Computing Cluster. In recent semesters, the 100 undergraduates per semester who enroll in Advanced General Chemistry (109H) have used the computing cluster to begin learning computational approaches to chemistry. This push to incorporate computational chemistry into a general chemistry course was modeled after a similar computational initiative developed by Dr. Nicholas Hill, organic lab director, and Dr. Brian Esselman, assistant organic lab director. Funding from the Madison Initiative for Undergraduates supported their efforts to develop lectures, practice exercises, and other training resources in order to fully incorporate computational chemistry into the undergraduate organic curriculum.

However, the primary purpose of the cluster, which was funded in part by a grant from the National Science Foundation, is to support research computations. Although the shared computing approach worked well as a test case for the general chemistry course, the existing cluster cannot support additional students while maintaining the desired level of support for research computing. ILM funding will grow the cluster’s capacity so that it can support additional general chemistry sections as new computational modules are incorporated into the classes.

“Computational chemistry is a powerful tool for modern research,” says Dr. Desiree Bates, computational chemistry leader. “A substantial number of new chemistry publications now include a computational component. That’s why training undergraduates in computational methods is vital to their success in any STEM discipline.”

LabQuest 2 data acquisition unitAn additional $50,000 award will provide replacements for existing Vernier Technology LabQuest data acquisition units. Undergraduates use the units to collect, analyze, and share data from their general chemistry lab experiments. The existing units were purchased about 5 years ago with support from a previous ILM award. Vernier Technology has since released a new LabQuest 2 model and has discontinued the original model, which means that repairing the older units would have become increasingly difficult.

“The LabQuest units can be used with a wide variety of sensors, such as spectrometers, pH probes, and temperature probes,” says Dr. Chad Wilkinson, general chemistry lab director. “Students and TAs benefit from repeated use of the LabQuest, as it reduces the need for training across multiple interfaces and allowing them to focus on data collection and processing.”

LabQuest 2 photo courtesy of Vernier Technologies

Story by Libby Dowdall