Research

Our Research Philosophy 

LOGICS = Linearly Optimized, Geometrically Interfaced Chemical Systems

• Linearly Optimized — Streamlining experimental workflows through automation, high-throughput methods, and data-driven optimization.

• Geometrically Interfaced — Understanding and controlling interfaces across molecular, nanoscale, porous, and device-level architectures.

• Chemical Systems — Connecting fundamental molecular interactions with the performance of functional energy and chemical technologies.

Molecular and Interfacial Design for Energy and Chemical Systems 

The LOGICS Lab integrates electrochemistry, surface and interfacial science, advanced characterization, functional materials design, automation, and data-driven experimentation. We seek to uncover how molecular interactions and spatial organization at reactive interfaces govern system-level performance and to translate these insights into sustainable energy-storage and chemical-conversion technologies.

Researchers in the LOGICS Lab will work across the following interconnected areas:

1. Reactive Interphases in Batteries

We investigate how electrolyte decomposition, molecular transport, electric fields, and electrode morphology govern the formation and evolution of solid-electrolyte and cathode-electrolyte interphases. Our goal is to establish predictive design principles for safer, longer-lasting, and more reversible battery chemistries.

2. Electrocatalytic Molecular Manufacturing

We develop selective electrochemical pathways that transform abundant, renewable, or waste-derived feedstocks into fuels and value-added chemicals. This work connects molecular electrocatalysis with sustainable manufacturing and circular resource use.

3. Solar-Driven Chemical Conversion

We design photoelectrochemical and photocatalytic interfaces that use sunlight to drive fuel production, environmental remediation, resource recovery, and other beneficial chemical transformations.

4. Autonomous and Data-Driven Experimentation

We combine laboratory automation, high-throughput experimentation, robotics, machine learning, and physically informed data analysis to accelerate the discovery of materials, electrolytes, interfaces, and operating conditions.

Across these areas, the group combines mechanistic investigation with materials innovation to connect molecular-scale interfacial phenomena with device-level performance.