Hendrik Clausdeinken

Hendrik Clausdeinken was a visiting graduate researcher at the Institute for Data, Systems and Society (IDSS) at MIT. He is pursuing his M.S. in Energy Science and Technology at ETH Zurich, Switzerland, and holds a B.S. in Mechanical Engineering and Business Administration from RWTH Aachen University, Germany. Before starting his M.S., Hendrik worked for BASF’s business development in Hongkong and with The Boston Consulting Group on a change project at a big German utility. His research focuses techno-economic modeling of energy storage technologies to define cost performance targets for their future deployment in European markets. He is a recipient of scholarships by the German Academic Foundation and the Dr. Peter Schaefer Sustainability Program.

Contact: hclausd at mit dot edu

MRS abstract

Goksin Kavlak presents at the 2014 Materials Research Society Fall Meeting on December 3rd, 2014, at Symposium FF: Materials as Tools for Sustainability http://www.mrs.org/fall-2014-program-ff/


Metals Production Requirements for Large-Scale Photovoltaics Deployment

Goksin Kavlak1, James McNerney1, Robert L. Jaffe2,3, Jessika E. Trancik1,4

  1. Engineering Systems Division, MIT, Cambridge, Massachusetts, USA;
  2. Center for Theoretical Physics, MIT, Cambridge, Massachusetts, USA;
  3. Department of Physics, MIT, Cambridge, Massachusetts, USA;
  4. Santa Fe Institute, Santa Fe, New Mexico, USA.

Energy scenarios with aggressive carbon reduction goals have projected the increasing adoption of photovoltaics (PV) in future years. This rapid deployment of PV would require growth in the supply of materials that are used to manufacture these technologies. In this work, we estimate the growth rates of global metals production that would be needed to meet PV deployment targets put forward in aggressive low-carbon energy scenarios. We then compare the required growth rates to historical production trends for a large set of metals. We find that if crystalline silicon PV provides 25% of the electricity generation in 2030, the required growth in silicon production does not exceed 5% per year even at current material intensities. This growth rate is within the range of historical rates for metals production. In contrast, if cadmium telluride PV provides more than 1% of the projected electricity generation in 2030, tellurium production would need to grow at unprecedented rates unless there are dramatic decreases in material intensity.

Fabian Riether

Fabian Riether completed his master’s degree in Mechanical Engineering at MIT in 2016. His thesis demonstrated the potential of novel optimization algorithms for controlling high-dimensional stochastic systems such as  quadrotors. In 2014-2015, he worked with the Trancik Lab to investigate energy storage and consumption patterns in transportation and energy infrastructure to derive design rules and optimal policies. He received his B.Sc. in Engineering Cybernetics from the University of Stuttgart. Research projects in Stuttgart and Abu Dhabi focused on modeling and analyzing single-device man-machine systems. Before coming to MIT, Fabian worked on increasing the scalability of autonomous driving solutions in Silicon Valley. Currently, Fabian is pursuing a co-op MBA program at the Collège des Ingénieurs where he works as a Junior Consultant for Infineon Technologies.

Contact: friether at alum dot mit dot edu

Linda Jing

Linda Jing was an undergraduate in Materials Science and Engineering and minoring in Energy Studies with a concentration in Economics at MIT. Her research is focused on evaluating the materials constraints for energy storage.

Contact: weijing at mit dot edu

research overview

The goal of our work is to accelerate the
discovery and scaling of new energy technologies.

Our research focuses on discovering frameworks and quantitative methods to compare and optimize energy technologies by integrating technological details and climate change mitigation targets. We take a data-driven, quantitative approach to studying the dynamics of change and performance limits of various energy systems. We are also developing models to guide materials optimization in nanostructured energy conversion devices.