(565d) The importance of model systems in biology and materials science: A measurement perspective

Models provide an experimentally tractable means of studying complex systems whose interconnected components can result in non-additive and non-obvious responses. Guided by measurements—some new, some established, and others reimagined forms of the tried-and[1]true—we develop models to systematically dissect aspects of complex phenomena that impact our everyday lives in the areas of solar fuels and drug discovery. In the area of solar fuels, we quantify the effect of surface chemistry on the performance of silicon- and carbon-based photoelectrodes. The electronic properties of (bulk) silicon, diamond, and graphite are well characterized. The surface of these materials has proven challenging to study due to the low concentration of surface states and chemically appended molecules (a limit of detection problem) and their reactivity in operando and under ambient conditions (a stability problem). Using silicon as a model semiconductor surface, we evaluate: 1) how introducing dipoles on the surface alters the favorability and kinetics of electron transfer from the surface to appended catalysts. 2) The effect of lateral interactions on the electrochemical reversibility of surface-appended catalysts. 3) The effect of electric fields on the ordering and activity of surface-appended catalysts. We apply these findings to amorphous carbon films, representing a disordered (and more challenging to characterize) chemical environment. In the area of drug discovery, we focus on developing physiologically relevant tissues for in vitro screening applications. Our laboratory develops devices and methods to evaluate the role of oxygen on cellular behavior in tissue-like environments. By treating oxygen as a reagent, we specifically focus on how traditionally relied-upon culture methods (e.g., atmospheric or 20% O2 levels) overlook important cellular responses occurring at physiologically relevant oxygen tensions. Some of our recent findings show oxygen should be accounted for when predicting (1) drug sensitivity and resistance in tumor models, (2) the potential toxicity of environmental contaminants, and (3) the metabolic activity and competency of healthy hepatocytes in liver models