Principal Investigator Srinivas Devadas
In an increasingly carbon-constrained world, lignocellulosic biomass, natural gas, and carbon dioxide have emerged as attractive options to supply energy, fuels, and chemicals at scale in a cleaner and more sustainable manner. However, the unique chemical makeup of these alternative carbon sources has created daunting conversion challenges, requiring the development a new generation of robust, active, and selective catalysts. In this lecture, I will show how advanced synthesis techniques can be coupled with rigorous reactivity and characterization studies to uncover unique synergies in nanostructured catalysts.
First, the cooperativity between catalytic pairs in metalloenzyme-like microporous materials will be demonstrated. Specific examples will include the synthesis of diacids from coupling bio-derived keto acids, and the conversion of methane into acetic acid via tandem oxidation and carbonylation reactions.
Second, new developments in the use of heterometallic early transition metal carbide (TMC) nanoparticles will be described as a novel platform to replace (or drastically reduce) noble metal utilization in electro- and thermo-catalytic applications. A new method to synthesize TMCs and core-shell TMC-noble metal structures with exquisite control over composition, size, crystal phase, and purity will be demonstrated. Structure-activity descriptors can then be elucidated and used to guide the design of new catalytic materials.
Marzyeh Ghassemi Associate Professor, MIT Department of Electrical Engineering and Computer Science (EECS) and Institute for Medical Engineering & Science (IMES)
Machine learning in health has made impressive progress in recent years, powered by an increasing availability of health-related data and high-capacity models. While many models in health now perform at, or above, humans in a range of tasks across the human lifespan, models also learn societal biases and may replicate or expand them. In this talk, Dr. Marzyeh Ghassemi will focus on the need for machine learning researchers and model developers to create robust models that can be ethically deployed in health settings, and beyond. Dr. Ghassemi's talk will span issues in data collection, outcome definition, algorithm development, and deployment considerations.
Principal Investigator Linda Griffith
Sara Beery
Assistant Professor of AI and Decision-Making, MIT Department of Electrical Engineering and Computer Science
Brian Anthony | Associate Director, MIT.nano Moungi Bawendi Lester Wolfe Professor of Chemistry MIT Department of Chemistry Juejun (JJ) Hu Associate Professor, Department of Materials Science & Engineering Daniel Moyer Postdoctoral Associate, MIT Computer Science & Artificial Intelligence Lab
Day 2 Welcomes & Opening Remarks
Will Roper Distinguished Professor, Sam Nunn School of International Affairs