Bio

Dr. Karan Bhuwalka leads the materials supply chain modeling at STEER, a research group that conducts rigorous techno-economic analysis to guide investment, innovation, and policy for the energy transition. Karan's research integrates economics, statistics, manufacturing and materials science to identify pathways to sustainably scale-up critical minerals production. Scaling-up energy supply chains rapidly while minimising life-cycle impacts requires aligning technology, markets and policies. STEER takes a systems approach that links engineering process models with supply and demand considerations to inform decision-making under uncertainty. Karan's current work is focused on modeling graphite production. Previous work spans lithium, nickel, recycled plastics systems and Bayesian modeling to reduce uncertainity in material demand.

Academic Appointments

  • Research Engineer, Energy Science & Engineering

Professional Education

  • PhD, Massachusetts Institute of Technology, Mechanical Engineering (2024)
  • MS, Massachusetts Institute of Technology, Technology & Policy (2021)
  • MS, Massachusetts Institute of Technology, Computer Science (2021)
  • BTech, Indian Institute of Technology, Metallurgical Engineering and Materials Science (2018)

Contact

  • Academic
    bhuwalka@stanford.edu
    University - Academic staff Department: Precourt Institute for Energy Position: Research Engineer

Additional Info

Links

All Publications

  • Understanding key mineral supply chain dynamics using economics-informed material flow analysis and Bayesian optimization JOURNAL OF INDUSTRIAL ECOLOGY Ryter, J., Bhuwalka, K., O'Rourke, M., Montanelli, L., Cohen-Tanugi, D., Roth, R., Olivetti, E. 2024

    View details for DOI 10.1111/jiec.13517

    View details for Web of Science ID 001263838100001

  • Characterizing the Changes in Material Use due to Vehicle Electrification. Environmental science & technology Bhuwalka, K., Field, F. R., De Kleine, R. D., Kim, H. C., Wallington, T. J., Kirchain, R. E. 2021; 55 (14): 10097-10107

    Abstract

    Modern automobiles are composed of more than 2000 different compounds comprising 76 different elements. Identifying supply risks across this palette of materials is important to ensure a smooth transition to more sustainable transportation technologies. This paper provides insight into how electrification is changing vehicle composition and how that change drives supply risk vulnerability by providing the first comprehensive, high-resolution (elemental and compound level) snapshot of material use in both conventional and hybrid electric vehicles (HEVs) using a consistent methodology. To make these contributions, we analyze part-level data of material use for seven current year models, ranging from internal combustion engine vehicles (ICEV) to plug-in hybrid vehicles (PHEVs). With this data set, we apply a novel machine learning algorithm to estimate missing or unreported composition data. We propose and apply a metric of vulnerability, referred to as exposure, which captures economic importance and susceptibility to price changes. We find that exposure increases from $874 per vehicle for ICEV passenger vehicles to $2344 per vehicle for SUV PHEVs. The shift to a PHEV fleet would double automaker exposure adding approximately $1 billion per year of supply risk to a hypothetical fleet of a million vehicles. The increase in exposure is largely not only due to the increased use of battery elements like cobalt, graphite, and nickel but also some more commonly used materials, most notably copper.

    View details for DOI 10.1021/acs.est.1c00970

    View details for PubMedID 34213890

  • Emission impacts of China's solid waste import ban and COVID-19 in the copper supply chain. Nature communications Ryter, J., Fu, X., Bhuwalka, K., Roth, R., Olivetti, E. A. 2021; 12 (1): 3753

    Abstract

    Climate change will increase the frequency and severity of supply chain disruptions and large-scale economic crises, also prompting environmentally protective local policies. Here we use econometric time series analysis, inventory-driven price formation, dynamic material flow analysis, and life cycle assessment to model each copper supply chain actor's response to China's solid waste import ban and the COVID-19 pandemic. We demonstrate that the economic changes associated with China's solid waste import ban increase primary refining within China, offsetting the environmental benefits of decreased copper scrap refining and generating a cumulative increase in CO2-equivalent emissions of up to 13 Mt by 2040. Increasing China's refined copper imports reverses this trend, decreasing CO2e emissions in China (up to 180 Mt by 2040) and globally (up to 20 Mt). We test sensitivity to supply chain disruptions using GDP, mining, and refining shocks associated with the COVID-19 pandemic, showing the results translate onto disruption effects.

    View details for DOI 10.1038/s41467-021-23874-7

    View details for PubMedID 34145227

    View details for PubMedCentralID PMC8213787

https://orcid.org/0000-0002-1963-6717