Nakamura-Kanayama Lab

AboutAbout the lab

Toward zero greenhouse gas emissions and zero fires in energy systems.

Nakamura-Kanayama Lab studies reactive flow fields related to propulsion systems such as aerospace vehicles and to energy conversion equipment, working to uncover and model their chemical reactions.
The lab uncovers and models the chemical reactions of decarbonized and low-carbon fuels such as ammonia, hydrogen, and biofuels.
It also works on advancing the methods of fundamental experiments that use micro flow reactors and counterflow flames.
Based on an understanding of the chemical reactions of battery electrolytes, refrigerants, and the flame retardants added to them, the lab aims to reduce fires.

ResearchResearch themes

Energy conversion by combustion has the characteristics of following load fluctuations easily and delivering high output for its size and weight. Through experiments using micro flow reactors and burners together with numerical simulation of elementary reactions, the lab understands and models the chemical reactions and flame characteristics of new fuels, and builds the foundation of combustion numerical simulation needed for designing and developing zero-emission combustors.

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Reaction models for ammonia combustion↗

Ammonia can be produced from renewable energy and emits no CO2 when used. On the other hand, it burns less readily than hydrocarbons and also produces NOx from its nitrogen atoms, so the lab investigates flame characteristics and elementary reactions, and builds and validates models.

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Combustion of battery electrolytes and flame retardants↗

To suppress fires in lithium-ion batteries, the lab evaluates the reactivity of carbonate esters, the main components of electrolytes, and builds combustion reaction models. Fluorine- and phosphorus-containing compounds considered as flame retardants that dissolve in electrolytes are also targets of study.

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Reduced reaction models built with machine learning↗

Detailed combustion reaction models include many chemical species, which places an enormous computational load on numerical simulation. The lab studies methods of building reduced reaction models that have fewer chemical species while maintaining predictive performance, incorporating the support of machine learning.

VoicesStudent voices

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