ABSTRACT
Lithium-ion battery electrodes are typically manufactured via slurry casting, which involves mixing active material particles, conductive carbon, and a polymeric binder in a solvent, followed by casting and drying the coating on current collectors (Al or Cu). These electrodes are functional but still limited in terms of pore network percolation, electronic connectivity, and mechanical stability, leading to poor electron/ion conductivities and mechanical integrity upon cycling, which result in battery degradation. To address this, we fabricate trichome-like carbon-iron fabrics via a combination of electrospinning and pyrolysis. Compared with slurry cast Fe2O3 and graphite-based electrodes, the carbon-iron fabric (CMF) electrode provides enhanced high-rate capacity (10C and above) and stability, for both half cell and full cell testing (the latter with a standard lithium nickel manganese oxide (LNMO) cathode). Further, the CMFs are free-standing and lightweight; therefore, future investigation may include scaling this as an anode material for pouch cells and 18,650 cylindrical batteries.
ABSTRACT
The controlling factors that underlie the growth of tumors have often been hard to identify because of the presence in this system of a large number of intracellular biochemical parameters. Here, we propose a simplifying framework to identify the key physical parameters that govern the early growth of tumors. We model growth by means of branching processes where cells of different types can divide and differentiate. First, using this process that has only one controlling parameter, we study a one cell type model and compute the probability for tumor survival and the time of tumor extinction. Second, we show that when cell death and cell division are perfectly balanced, stochastic effects dominate the growth dynamics and the system exhibits a near-critical behavior that resembles a second-order phase transition. We show, in this near-critical regime, that the time interval before tumor extinction is power-law distributed. Finally, we apply this branching formalism to infer, from experimental growth data, the number of different cell types present in the observed tumor.
