• Canada
• 02 engineering and technology close
• Natural Sciences and Engineering Research Council of Canada close

Magnetic actuation is a droplet manipulation mechanism in digital microfluidics (DMF), where droplets can be actuated over a (super)hydrophobic surface with a magnetic force. Superparamagnetic particles or ferromagnetic liquids are added to the droplets to provide a “handle” by which the magnet can exert a force on the droplet. In this study, we present a novel method of magnetic manipulation, where droplets instead contain paramagnetic salts with molar magnetic susceptibilities (χm) approximately ≈10 000× < that for superparamagnetic particles. Droplet actuation is facilitated by low surface friction on fluorous silica nanoparticle-based superhydrophobic coatings, where <2 μN is required for reproducible droplet actuation. Different paramagnetic salts with χm from ≈4500 to 72 000 (× 10–6 cm3 mol–1) were used to make aqueous solutions of different concentration and tested for droplet actuation and sliding angle using permanent magnets (1.8–2.1 kG). Paramagnetic salts are compared in terms of solubility, m...

AbstractIn this study, the 3D printability of a series of poly(3-hydroxybutyrate-co-3-hydroxyvalerate) (PHBV)/poly(lactic acid) (PLA) blends were investigated using fused filament fabrication (FFF). The studied blends suffered from poor 3D printability due to differences in compatibility and low thermal resistance. These shortcomings were addressed by incorporating a functionalized styrene-acrylate copolymer with oxirane moieties as a chain extender (CE). To enhance mechanical properties, the synergistic effect of 3D printing parameters such as printing temperature and speed, layer thickness and bed temperature were explored. Rheological analysis showed improvement in the 3D printability of PHBV:PLA:CE blend by allowing a higher printing temperature (220 °C) and sufficient printing speed (45 mm s−1). The surface morphology of fractured tensile specimens showed good bonding between layers when a bed temperature of 60 °C was used and a layer thickness of 0.25 mm was designed. The optimized printing samples shown higher storage modulus and strength, resulting in stiffer and stronger parts. The crystallinity, morphology and performance of the 3D printed products were correlated to share key methods to improve the 3D printability of PHBV:PLA based blends which may be implemented in other biopolymer blends, and further highlight how process parameters enhance the mechanical performance of 3D printed products.

Lithium-ion (Li-ion) batteries are an important component of energy storage systems used in various applications such as electric vehicles and portable electronics. There are many chemistries of Li-ion battery, but LFP, NMC, LMO, and NCA are four commonly used types. In order for the battery applications to operate safely and effectively, battery modeling is very important. The equivalent circuit model (ECM) is a battery model often used in the battery management system (BMS) to monitor and control Li-ion batteries. In this study, experiments were performed to investigate the performance of three different ECMs (1RC, 2RC, and 1RC with hysteresis) on four Li-ion battery chemistries (LFP, NMC, LMO, and NCA). The results indicated that all three models are usable for the four types of Li-ion chemistries, with low errors. It was also found that the ECMs tend to perform better in dynamic current profiles compared to non-dynamic ones. Overall, the best-performed model for LFP and NCA was the 1RC with hysteresis ECM, while the most suited model for NMC and LMO was the 1RC ECM. The results from this study showed that different ECMs would be suited for different Li-ion battery chemistries, which should be an important factor to be considered in real-world battery and BMS applications.

Elemental copper and potassium are immiscible under ambient conditions. It is known that pressure is a useful tool to promote the reaction between two different elements by modifying their electronic structure significantly. Here, we predict the formation of four K–Cu compounds (K3Cu2, K2Cu, K5Cu2, and K3Cu) under moderate pressure through unbiased structure search and first-principles calculations. Among all predicted structures, the simulated x-ray diffraction pattern of K3Cu2 perfectly matches a K–Cu compound synthesized in 2004. Further simulations indicate that the K–Cu compounds exhibit diverse structural features with novel forms of Cu aggregations, including Cu dimers, linear and zigzag Cu chains, and Cu-centered polyhedrons. Analysis of the electronic structure reveals that Cu atoms behave as anions to accept electrons from K atoms through fully filling 4s orbitals and partially extending 4p orbitals. Covalent Cu–Cu interaction is found in these compounds, which is associated with the sp hybridizations. These results provide insights into the understanding of the phase diversity of alkali/alkaline earth and metal systems.

Abstract This paper presents a method for quantifying drivers’ driving skills using closed-loop dynamic simulations of articulated heavy vehicles (AHVs). Due to AHVs’ multi-unit configurations, large sizes, and high centers of gravity (CGs), these large vehicles exhibit poor directional performance. AHVs require wide roads and large radii of path curvature for evasive maneuvers; these large vehicles frequently display unstable motion modes, including trailer sway, jackknifing, and rollover. The directional performance of AHVs is frequently evaluated in terms of maneuverability and lateral stability. There exists a trade-off between the performance measures of maneuverability and lateral stability. An AHV, its driver and the road constitute a unique closed-loop dynamic system. The unique dynamic characteristics of AHVs impose significant challenges for safe operations of these vehicles. However, little attention has been paid to the interactions of driver-AHV. This paper tackles the problem of quantifying drivers’ driving skills considering the interactions of driver-AHV under simulated single lane-change (SLC) maneuvers. Based on two driver characteristic parameters, namely preview time (PT) and transport delay (TD), we propose two performance measures, i.e., path-following score (PFS) and combined stability score (CSS), as the indicators for assessing the driving skills of AHV drivers under the simulated maneuvers. The driver-AHV closed-loop dynamic simulation is implemented using the built-in driver model and virtual vehicles developed in TruckSim. The numerical simulation results for rearward amplification (RA) measures are validated using driver-in-the-loop (DIL) real-time simulation. The simulation identifies AHV drivers’ driving skills in terms of lateral stability, path-following, as well as balanced path-following and stability regions considering PT and TD properties.

Here we present Fydlyty, a web-based, low-fidelity serious game to educate, and inform medical practitioners and trainees about cultural competence. Fydlyty includes a dialogue editor which has the ability to build a conversation, interpret responses, and respond to questions/answers from the game player. These responses are based on predefined cultural characteristics of the virtual character (avatar), and on different moods that the avatar may express depending on the situation (i.e., normal, upset, or angry). In addition to its educational purposes, Fydlyty has been developed as a research tool to examine the role of graphical-based fidelity in the learning process.

In this work, significant enhancement in absorption, especially in the near infra-red region, is achieved for ultra-thin crystalline silicon of various thicknesses using a photonic crystal structure. This is realized by patterning the silicon with close-packed inverted pyramid structuring, wherein the lattice spacing is comparable to the wavelength of the near infra-red light, which results in strong wave-interference-based light trapping. Absorption enhancement of more than a factor of two in the spectral range of 1000–1100 nm is achieved without any other optical enhancments. Details on the techniques used to realize the ultra-thin silicon, the fabrication of the inverted pyramids using standard photolithography and a complete optical analysis are reported in this work.

Abstract Fuzzy arithmetic operations are applied to mathematical equations that include fuzzy numbers, which are commonly used to represent non-probabilistic uncertainty in different applications. Although there are two mathematical approaches available in the literature for implementing fuzzy arithmetic (i.e., the α-cut approach, and the extension principle approach), the existing computational methods are mainly focused on implementing the α-cut approach due to its simplicity. However, this approach causes overestimation of uncertainty in the resulting fuzzy numbers, a phenomenon that reduces the interpretability of the results. This overestimation can be reduced by implementing fuzzy arithmetic using the extension principle; however, existing computational methods for implementing the extension principle approach are limited to the use of min and drastic product t-norms. Using the min t-norm produces the same result as the α-cuts and interval calculations approach, and the drastic product t-norm is criticized for producing resulting fuzzy numbers that are highly sensitive to the changes in the input fuzzy numbers. This paper presents original computational methods for implementing fuzzy arithmetic operations on triangular fuzzy numbers using the extension principle approach with product and Lukasiewicz t-norms. These computational methods contribute to the different applications of fuzzy arithmetic; they reduce the overestimation of uncertainty, as compared to the α-cut approach, and they reduce the sensitivity of the resulting fuzzy numbers to changes in the input fuzzy numbers, as compared to the extension principle approach using drastic product t-norm.

Abstract Minimum fluidization velocity of binary mixtures is one of the most important parameters when applying an Air Dense Medium Fluidized Bed for dry coal beneficiation. Measurements of minimum fluidization velocities were carried out for binary mixtures of magnetite and sand/gangue/coal particles. The experimental results showed that the minimum fluidization velocity of binary mixtures remained almost unchanged when the volume fraction of magnetite particles was above 50%, whereas it varied significantly when the volume fraction of magnetite particles was below 50%. A general correlation based on the Cheung equation has been developed for predicting the minimum fluidization velocity of binary mixtures in terms of particle size ratio, volumetric composition and incipient fluidization velocity of each component. The extended Cheung equation is in reasonable agreement with almost all the available experimental data in the present work and the literature, and it can be used to estimate accurately the minimum fluidization velocity of binary mixtures of medium particles for the ADMFB and other similar fluidized bed operations.