Puzzle pieces with graphics of research topics

Leonard Lab Research Topics

Research projects in the Leonard Lab seek to find sustainable solutions to our world's most challenging problems through the use of electrochemistry.

Goals

The long-term goal of the Leonard Lab is to reduce the impacts on the environment through the development of new catalysts to improve the efficiency of and reduce emissions associated with the production of fuels and chemicals. To accomplish this goal, we develop tools to gain fundamental understandings of electrocatalysts and electrocatalytic media, and use that understanding to design enhanced electrocatalytic systems to facilitate renewable chemistry for the benefit of society.

The projects of the Leonard Lab focus on creating solutions at every step of the process, cradle to grave. When designing improvements for existing processes, we seek lasting viable changes through utilizing abundant metals for catalysts or by-product waste for our feedstocks. To better understand and further advance catalyst performance, we are helping to evolve characterization techniques to expand fundamental insights into key characteristics of active catalysts. In order to accelerate catalyst discovery we have invested in the field of data harnessing and machine learning through which a novel catalyst could create a breakthrough for green electrochemistry. In all areas we aspire to learn, cultivate, and promote sustainable practices to achieve our overarching goal in producing fuels and chemicals for the future.

Current Projects

Electrocatalysis

Discovering new materials and reaction media to catalyze electrochemical reactions for the creation of renewable fuels and chemicals in an environmentally-beneficial manner.
Catalyst improvements through renewable energy schematic

Scanning Electrochemical Microscopy

Advancing characterization techniques for catalytic and electrocatalytic materials to increase fundamental understanding of reaction mechanisms.
Depiction of two tip electrodes in SECM with intermediates on one electrode surface.

Machine Learning for Data Mining

Developing novel data mining and extraction methodologies to accelerate catalytic insights and innovations.
Artificial intelligence and the six subsets shown in a mind map graphic

CO₂ Expanded Electrolytes

Utilizing CO₂, otherwise released as waste product, as a feedstock to produce value-added products.
An increase of volume with CXE and positive effects like higher mass transfer, gas concentrations, and a tunable pressure

Inside the Leonard Lab

Flask on stir plate with student recording data

Jane observing a chemical synthesis.

Student loading SECM sample

Dinu setting up an experiment on our custom built SECM.

Student putting together a reactor

Bree checking the reactor used for CXE experiments.