Scientific Events

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In order to address climate change, we must transition to a low-carbon economy. Many clean primary energy sources, such as solar panels and wind turbines, are being deployed and promise an abundant supply of clean electricity in the near future. The key question becomes how to store, transport and trade this clean energy in a manner that is as convenient as fossil fuels. The Alternative Fuels Laboratory (AFL) at McGill University is actively researching the use of recyclable metal fuels as a key enabling technology for a low-carbon society. Metal fuels, reduced using clean primary energy, have the highest energy density of any chemical fuel and are stable solids, simplifying trade and transport. The chemical energy stored in the metal fuels can be converted to useful thermal or motive power through two main routes: the Dry Cycle, where metal powders/sprays are burned with air, or the Wet Cycle, where metal powders are reacted with water to produce hydrogen and heat as an intermediate step before using the hydrogen as a fuel for various power systems. This talk will overview the concept of metal fuels and the various power system options. It will also touch on the combustion and reaction physics of metal fuels and the propagation of metal flames. Bio: Jeffrey Bergthorson is the Panda Faculty Scholar in Sustainable Engineering and Design, and a Professor in the Department of Mechanical Engineering, at McGill University where he leads the Alternative Fuels Laboratory. He received his B.Sc. in Mechanical Engineering from the University of Manitoba (1999), and his M.Sc. (2000) and Ph.D. (2005) in Aeronautics from the Graduate Aeronautical Laboratories of the California Institute of Technology. Prof. Bergthorson is a Fellow of the Combustion Institute and a Fellow of the American Society of Mechanical Engineers. Prof. Bergthorson’s research interests are in the broad area of the combustion and emissions properties of alternative and sustainable fuels, including biofuels, hydrogen, and the use of metals as recyclable fuels. [more]

Where: virtual on Zoom (link follows) [more]

The photovoltaic (PV) industry is in rapid growth and a large supply of PV feedstock materials must be provided to maintain this growth. Since silicon is the dominant material for the fabrication of solar cells, low-cost solar-grade silicon (SoG-Si) feedstock is demanded. The most cost-effective and direct approach for producing SoG-Si is to purify and upgrade metallurgical-grade silicon (MG-Si). Many impurities in MG-Si can be effectively removed through directional solidification of molten silicon. However, the removal of boron (B) and phosphorus (P) by this method is difficult and expensive due to the relatively large distribution coefficients of these elements. Therefore, the elimination of B and P to the levels required for SoG-Si feedstock requires the development of new processes. In the present study, the effect of impurities on the solar cell efficiencies and the impurity contents in silicon materials are studied. The metallurgical processes that can be applied to purify metallurgical silicon to solar grade silicon are reviewed and evaluated. It is shown that under development metallurgical refining processes are applicable to produce solar grade silicon. [more]

Where: virtual on Zoom (link follows) [more]

Electrochemical Energy Storage, in particular Li-Ion Batteries, have become one of the most important technological cornerstones for the current energy transition. The further development and progress in existing technology will depend on both, the introduction of new active electrode materials and the better understanding and mitigation of existing materials challenges. After an introduction in battery technology and the used materials, I will focus on a few examples where advanced characterization is able to bring new insights and better understanding of performance and degradation mechanisms. [more]

In 2020, every major company’s annual report contained the word digitalization, A.I. or industry 4.0. It is easy to perceive these as buzzwords, aimed at investors, but the reality is more complex: companies are expected to transform now, driven by the fear of becoming obsolete. As researchers, this exciting transition creates significant opportunities: huge amounts of data are becoming readily available, while computing power and machine learning (ML) algorithms are more accessible than ever. However, this is also leading to disproportionate hopes and expectations regarding the actual capabilities of such methods, that only a working knowledge of ML combined with technical expertise in your field can rationalize. As R&D engineers, this critical view will be expected from you. Since technical expertise has already been the focus of your professional career, the effort should therefore be put on acquiring a practical knowledge of ML, that is, what problems can be solved and how to solve them? In this talk, some applications of ML to solve industrial issues (predictive modeling, visualization, combination with physical models...) will be discussed. Furthermore, practical aspects, such as data preparation, models implementation and maintenance will be reviewed, with the aim of providing actual insights on the root causes of successes and failures of ML applied to the steelmaking process. [more]