Technical and economic analysis of solvent-based lithium-ion electrode drying with water and NMP

Processing lithium-ion battery (LIB) electrode dispersions with water as the solvent during primary drying offers many advantages over N-methylpyrrolidone (NMP). An in-depth analysis of the comparative drying costs of LIB electrodes is discussed for both NMP- and water-based dispersion processing in terms of battery pack $/kWh. Electrode coating manufacturing and capital equipment cost savings are compared for water vs. conventional NMP organic solvent processing. A major finding of this work is that the total electrode manufacturing costs, whether water- or NMP-based, contribute about 8–9% of the total pack cost. However, it was found that up to a 2?×?reduction in electrode processing (drying and solvent recovery) cost can be expected along with a $3–6?M savings in associated plant capital equipment (for a plant producing 100,000 10-kWh Plug-in Hybrid Electric Vehicle (PHEV) batteries) using water as the electrode solvent. This paper shows a different perspective in that the most important benefits of aqueous electrode processing actually revolve around capital equipment savings and environmental stewardship and not processing cost savings.     

Evaluation of antioxidant level and protein oxidation of rainbow trout (Oncorhynchus mykiss) fillets during rigor and post-rigor

In this study, the relationship between stunning techniques and protein oxidation which are accepted as the main cause of food spoilage was investigated. For this purpose, the antioxidant status, in vivo myofibrillary protein (MP) oxidation and sensitivity, and postmortem oxidation (inducted with hydroxyl radical system) of rainbow trout (Oncorhynchus mykiss) fillets killed by hitting to head (T1), neck crushing (T2), and convulsion (T3) methods, were investigated. Statistically significant differences (p < .05) were found among all parameters examined and it was observed that the most stressing technique was the convulsion method. It was determined that in protein profiles myosin were influenced too much from stunning technique and in actin observed oxidation-induced reductions. Reductions in S-S and S-H were also found to be increased in carbonyl concentrations, but the most effective values in both processes were determined by the convulsive technique. Our results show that short-term stunning techniques (hitting to head, neck crushing) give better meat quality results in terms of O. mykiss welfare and low MP oxidation rates. In general, we can say that T3 group fillets are more sensitive to oxidative damage, while T1 and T2 groups give better results in maintaining meat quality with low MP oxidation rates.     

Life cycle cost analysis of alternative vehicles and fuels in Thailand

High crude oil prices and pollution problems have drawn attention to alternative vehicle technologies and fuels for the transportation sector. The question is: What are the benefits/costs of these technologies for society? To answer this question in a quantitative way, a web-based model (http://vehiclesandfuels.memebot.com) has been developed to calculate the societal life cycle costs, the consumer life cycle costs and the tax for different vehicle technologies. By comparing these costs it is possible to draw conclusions about the social benefit and the related tax structure. The model should help to guide decisions toward optimality, which refers to maximum social benefit. The model was applied to the case of Thailand. The life cycle cost of 13 different alternative vehicle technologies in Thailand have been calculated and the tax structure analyzed.     

Detection of COVID-19 and its pulmonary stage using Bayesian hyperparameter optimization and deep feature selection methods

Since the first case of COVID-19 was reported in December 2019, many studies have been carried out on artificial intelligence for the rapid diagnosis of the disease to support health services. Therefore, in this study, we present a powerful approach to detect COVID-19 and COVID-19 findings from computed tomography images using pre-trained models using two different datasets. COVID-19, influenza A (H1N1) pneumonia, bacterial pneumonia and healthy lung image classes were used in the first dataset. Consolidation, crazy-paving pattern, ground-glass opacity, ground-glass opacity and consolidation, ground-glass opacity and nodule classes were used in the second dataset. The study consists of four steps. In the first two steps, distinctive features were extracted from the final layers of the pre-trained ShuffleNet, GoogLeNet and MobileNetV2 models trained with the datasets. In the next steps, the most relevant features were selected from the models using the Sine–Cosine optimization algorithm. Then, the hyperparameters of the Support Vector Machines were optimized with the Bayesian optimization algorithm and used to reclassify the feature subset that achieved the highest accuracy in the third step. The overall accuracy obtained for the first and second datasets is 99.46% and 99.82%, respectively. Finally, the performance of the results visualized with Occlusion Sensitivity Maps was compared with Gradient-weighted class activation mapping. The approach proposed in this paper outperformed other methods in detecting COVID-19 from multiclass viral pneumonia. Moreover, detecting the stages of COVID-19 in the lungs was an innovative and successful approach.     

Silver Nanoflower Decorated Graphene Oxide Sponges for Highly Sensitive Variable Stiffness Stress Sensors

Soft conductive materials should enable large deformation while keeping high electrical conductivity and elasticity. The graphene oxide (GO)‐based sponge is a potential candidate to endow large deformation. However, it typically exhibits low conductivity and elasticity. Here, the highly conductive and elastic sponge composed of GO, flower‐shaped silver nanoparticles (AgNFs), and polyimide (GO‐AgNF‐PI sponge) are demonstrated. The average pore size and porosity are 114 µm and 94.7%, respectively. Ag NFs have thin petals (8–20 nm) protruding out of the surface of a spherical bud (300–350 nm) significantly enhancing the specific surface area (2.83 m² g^?1). The electrical conductivity (0.306 S m^?1 at 0% strain) of the GO‐AgNF‐PI sponge is increased by more than an order of magnitude with the addition of Ag NFs. A nearly perfect elasticity is obtained over a wide compressive strain range (0–90%). The strain‐dependent, nonlinear variation of Young's modulus of the sponge provides a unique opportunity as a variable stiffness stress sensor that operates over a wide stress range (0–10 kPa) with a high maximum sensitivity (0.572 kPa^?1). It allows grasping of a soft rose and a hard bottle, with the minimal object deformation, when attached on the finger of a robot gripper.