Thermal Runaway and Fire Suppression Applications for Different Types of Lithium Ion Batteries

With the improvement of lithium-ion battery (LIB) technology, safety is becoming increasingly urgent topic for battery electric vehicles (BEVs). Short circuits, overcharging, high temperatures and overheating can cause thermal runaway reactions and the release of the flammable electrolyte which makes fire suppression very difficult. This study focuses on the mechanism of thermal runaway and fire suppression applications of LIBs. In order to understand this, 10 experiments were carried out. The experiments were divided into as Exp. A and Exp. B. A manual water suppression system was used in Exp. A and an automatic boron-based suppression system (AUT-BOR) was used in Exp. B. LIBs were heated in a controlled manner with a heat source and the effects of thermal runaway and fire suppression were observed. In Exp. A, a large amount of water was required to extinguish the LIB fires. The holes and slits which formed in the LIB after a fire were useful for injecting water. A projectile effect of cylindrical cells was observed in Exp. A. The Exp. B results showed that AUT-BOR mitigates risks effectively and safely. Also, AUT-BOR provides an early fire warning system and spot cooling to prevent thermal runaway reactions while localizing and suppressing the fire. In Exp. B, fire detection and suppression occurred without any explosion.

Algorithmic biosynthesis of eukaryotic glycans

An algorithm converts inputs to corresponding unique outputs through a sequence of actions. Algorithms are used as metaphors for complex biological processes such as organismal development. Here we make this metaphor rigorous for glycan biosynthesis. Glycans are branched sugar oligomers that are attached to cell-surface proteins and convey cellular identity. Eukaryotic O-glycans are synthesized by collections of enzymes in Golgi compartments. A compartment can stochastically convert a single input oligomer to a heterogeneous set of possible output oligomers; yet a given type of protein is invariably associated with a narrow and reproducible glycan oligomer profile. Here we resolve this paradox by borrowing from the theory of algorithmic self-assembly. We rigorously enumerate the sources of glycan microheterogeneity: incomplete oligomers via early exit from the reaction compartment; tandem repeat oligomers via runaway reactions; and competing oligomer fates via divergent reactions. We demonstrate how to diagnose and eliminate each of these, thereby obtaining “algorithmic compartments” that convert inputs to corresponding unique outputs. Given an input and a target output we either prove that the output cannot be algorithmically synthesized from the input, or explicitly construct an ordered series of algorithmic compartments that achieves this synthesis. Our theoretical analysis allows us to infer the causes of non-algorithmic microheterogeneity and species-specific diversity in real glycan datasets.