Paper-based microfluidic fuel cells (MFCs) are a potential replacement for traditional FCs and batteries due to their low cost, portability, and simplicity to operate. In MFCs, separate solutions of fuel and oxidant migrate through paper due to capillary action and laminar flow and, upon contact with each other and catalyst, produce electricity. In the present work, we describe an improved microfluidic paper-based direct formate FC (DFFC) employing formate and hydrogen peroxide as the anode fuel and cathode oxidant, respectively. The dimensions of the lateral column, current collectors, and cathode were optimized. A maximum power density of 2.53 mW/cm(2) was achieved with a DFFC of surface area 3.0 cm(2) , steel mesh as current collector, 5% carbon to paint mass ratio for cathode electrode and, 30% hydrogen peroxide. The longevity of the MFC's detailed herein is greater than eight hours with continuous flow of streams. In a series configuration, the MFCs generate sufficient energy to power light-emitting diodes and a handheld calculator.

Fabric-based microfluidic fuel cells (MFCs) serve as a novel, cost-efficient alternative to traditional FCs and batteries, since fluids naturally travel across fabric via capillary action, eliminating the need for an external pump and lowering production and operation costs. Building on previous research with Y-shaped paper-based MFCs, fabric-based MFCs mitigate fragility and durability issues caused by long periods of fuel immersion. In this study, we describe a microfluidic fabric-based direct formate fuel cell, with 5 M potassium formate and 30% hydrogen peroxide as the anode fuel and cathode oxidant, respectively. Using a two-strip, stacked design, the optimized parameters include the type of encasement, the barrier, and the fabric type. Surface contact of the fabric and laminate sheet expedited flow and respective chemical reactions. The maximum current (22.83 mA/cm ) and power (4.40 mW/cm ) densities achieved with a 65% cotton/35% polyester blend material are a respective 8.7% and 32% higher than previous studies with Y-shaped paper-based MFCs. In series configuration, the MFCs generate sufficient energy to power a handheld calculator, a thermometer, and a spectrum of light-emitting diodes.

Spotting refers to the transport of burning pieces of firebrand by wind which, at the time of landing, may ignite new fires beyond the direct ignition zone of the main fire. Spot fires that occur far from the original burn unit are rare but have consequential ramifications since their prediction and control remains challenging. To facilitate their prediction, we examine three methods for quantifying the landing distribution of firebrands: crude Monte Carlo simulations, importance sampling, and large deviation theory (LDT). In particular, we propose an LDT method that accurately and parsimoniously quantifies the low probability events at the tail of the landing distribution. In contrast, Monte Carlo and importance sampling methods are most efficient in quantifying the high probability landing distances near the mode of the distribution. However, they become computationally intractable for quantifying the tail of the distribution due to the large sample size required. We also show that the most probable landing distance grows linearly with the mean characteristic velocity of the wind field. Furthermore, defining the relative landed mass as the proportion of mass landed at a given distance from the main fire, we derive an explicit formula which allows computing this quantity as a function of the landing distribution at a negligible computational cost. We numerically demonstrate our findings on two prescribed wind fields.