Depending on when trainees start in their graduate programs, they would take some or all of the five Soft AE courses. Unless noted, courses run every year and will be offered for the same semester as listed (Spring or Fall) each year.
Spring
CBE 5700 Experimental Methods and Autonomous Experimentation in Soft Materials Research -Theory and Practice
This course covers the relevant theory and practical application of experimental methods used to study the structure, dynamics and physico-chemical properties of soft matter and macromolecular materials. Systems of interest include self-assembled polymers and (macro)molecular materials, liquid crystals, colloidal suspensions, biological materials, gels, and other complex fluids. Particular emphasis is placed on the development of kinematic theory for X-ray scattering, methods of structure determination by (x-ray/electron) diffraction, microscopy (optical; atomic force; electron), dynamic scattering (light/optical; x-ray; neutron) and rheology (bulk and microrheology). Machine learning and autonomous experimentation in soft materials will be covered as emerging areas of interest. Thermo-mechanical, electronic and optical property characterization are also addressed. Lectures are complemented by lab exercises and projects. The subject matter is particularly relevant for students conducting experimental research on macromolecular materials, soft matter and complex fluids.
EAS 5110/ENMG 5100 Societal Grand Challenges at the Interface of Technology and Policy
This new collaborative course — co-taught by faculty from the Kleinman Center for Energy Policy, Weitzman School of Design and School of Engineering and Applied Science — uses societal grand challenges as scenarios for identifying repeatable, process-oriented best practices for solving complex, systemic problems in the energy transition. This course is intended for graduate students with a background in either the social sciences (economics, political science, law, or policy) or who are in STEM programs (science and engineering). This course will complement the material covered in the Kleinman Center Introduction to Energy Policy course (ENMG 5020) taught in the fall. It will be an opportunity to learn from one another and build a holistic understanding of the technical and policy dimensions of the energy transition and the global response to climate change and environmental degradation.
Fall
ENM 5310 Data-driven Modeling and Probabilistic Scientific Computing
We will revisit classical scientific computing from a statistical learning viewpoint. In this new computing paradigm, differential equations, conservation laws, and data act as complementary agents in a predictive modeling pipeline. This course aims explore the potential of modern machine learning as a unifying computational tool that enables learning models from experimental data, inferring solutions to differential equations, blending information from a hierarchy of models, quantifying uncertainty in computations, and efficiently optimizing complex engineering systems.
ENMG 5020 Introduction to Energy Policy
This course provides an advanced introduction to the design and delivery of energy policy at various levels of government in the U.S. and beyond. Energy presents theoretical and practical challenges across many disciplines and professions, especially in the context of economic development and environmental sustainability at scales ranging from local to global. This course is intended to provide a broad overview of the institutions, legal frameworks, technologies, and markets involved in energy policy by exploring theories and case studies across these topics, with an emphasis on the energy transition necessitated by climate change. That said, a full introduction to energy policy requires multiple courses and Penn offers many salient ones across several schools including Law, Wharton, Weitzman, SAS, and SEAS. The primary goal of this course is to teach students how to think—rather than what to know—about energy policy. As such, this course provides both (a) a foundation for students who want to take additional courses on energy law, markets, technology, or policy and (b) a synthesis for students who have taken such courses and want to connect ideas and issues across disciplines and professions. Our seminar sessions will be largely discussion and exercise based to allow students to develop skills as energy policy analysts and to collectively theorize connections between laws, institutions, policy design, and outcomes.
Thermodynamics – multiple departments offer courses that would be appropriate, including the below courses.
BE 6620 / CBE 6180 / MEAM 6620 Advanced Molecular Thermodynamics
MSE 5300 Thermodynamics and Phase Equilibria
PHYS 5581 Thermodynamics