Comparative study of conventional and unconventional designs of cathode flow fields in PEM fuel cell

The choice of an appropriate flow field distributor is crucial to circumvent mass and charge transfer resistance-related issues in proton exchange membrane fuel cells (PEMFCs). In this work, incorporating all the anisotropic nature of the gas diffusion layers (GDLs), a three-dimensional, multiphase CFD model is built to perform a comparative study of several types of cathode flow field designs. Three conventional (i.e. parallel, serpentine and interdigitated) and two recently-introduced (i.e. parallel with blocks and the metal foam) flow field designs were considered for the cathode side. The results showed that the best fuel cell performance is obtained with the metal foam flow field as it induces the lowest water saturation, the lowest values and more uniform distribution of current density and temperature as well as relatively medium pressure drop. Compared with the parallel flow field case, the peak power density increases by about 50% when using the metal foam flow field and by about 10% when using the other three investigated flow fields (i.e. serpentine, interdigitated and parallel with blocks). The parametric analysis reveals that the metal foam outperforms other designs at intermediate and high humidity conditions whereas the interdigitated flow field design outperforms other designs at low humidity conditions

Sweat permeable and ultrahigh strength 3D PVDF piezoelectric nanoyarn fabric strain sensor

Commercial wearable piezoelectric sensors possess excellent anti-interference stability due to their electronic packaging. However, this packaging renders them barely breathable and compromises human comfort. To address this issue, we develop a PVDF piezoelectric nanoyarns with an ultrahigh strength of 313.3 MPa, weaving them with different yarns to form three-dimensional piezoelectric fabric (3DPF) sensor using the advanced 3D textile technology. The tensile strength (46.0 MPa) of 3DPF exhibits the highest among the reported flexible piezoelectric sensors. The 3DPF features anti-gravity unidirectional liquid transport that allows sweat to move from the inner layer near to the skin to the outer layer in 4 s, resulting in a comfortable and dry environment for the user. It should be noted that sweating does not weaken the piezoelectric properties of 3DPF, but rather enhances. Additionally, the durability and comfortability of 3DPF are similar to those of the commercial cotton T-shirts. This work provides a strategy for developing comfortable flexible wearable electronic devices

Modelling Temperature Variation of Mushroom Growing Hall Using Artificial Neural Networks

The recent developments of computer and electronic systems have made the use of intelligent systems for the automation of agricultural industries. In this study, the temperature variation of the mushroom growing room was modeled by multi-layered perceptron and radial basis function networks based on independent parameters including ambient temperature, water temperature, fresh air and circulation air dampers, and water tap. According to the obtained results from the networks, the best network for MLP was in the second repetition with 12 neurons in the hidden layer and in 20 neurons in the hidden layer for radial basis function network. The obtained results from comparative parameters for two networks showed the highest correlation coefficient (0.966), the lowest root mean square error (RMSE) (0.787) and the lowest mean absolute error (MAE) (0.02746) for radial basis function. Therefore, the neural network with radial basis function was selected as a predictor of the behavior of the system for the temperature of mushroom growing halls controlling system