Simulation of microwave thin layer drying process by a new theoretical model

Loss factor and moisture diffusivity property estimation of lentil crop during microwave processing

Characterization of loss factor and moisture diffusivity are required to understand materials' precise behavior during microwave processing. However, providing the processing facilities to measure these properties in a real or simulated situation directly can be complicated or unachievable. Hence, this study proposes an alternative procedure for modeling these properties according to their affecting factors including temperature, and moisture content. The basis of this method is to use an algorithm that combines the optimization approach and the numerical solution of the heat and mass transfer governing equations, including boundary conditions. For this aim, the coefficients of estimated models for loss factor and moisture diffusivity were obtained by minimizing the sum square error of the experimentally measured mean surface temperature and moisture content and the predicted values by solving the system of partial differential equations. The suggested models illustrated that during the microwave process, the moisture diffusivity grows arithmetically, and the loss factor generally raises, but transition points were observed in the trend for the samples tempered up to the 50% moisture content. These points have been attributed to the starch gelatinization and confirm how the bio-chemical reaction would have a noticeable effect on this property, determining the microwave energy absorbance. The results of differential scanning calorimetry thermograms and the Fourier transform mid-infrared spectra of flours obtained from microwave processed lentil seeds also confirmed the greatest intensity of starch structure alteration happened for the samples tempered to 50% moisture content by showing the highest shifts in the endothermic peak and lowest degree of order.

From Materials to Cell: State-of-the-Art and Prospective Technologies for Lithium-Ion Battery Electrode Processing

Electrode processing plays an important role in advancing lithium-ion battery technologies and has a significant impact on cell energy density, manufacturing cost, and throughput. Compared to the extensive research on materials development, however, there has been much less effort in this area. In this Review, we outline each step in the electrode processing of lithium-ion batteries from materials to cell assembly, summarize the recent progress in individual steps, deconvolute the interplays between those steps, discuss the underlying constraints, and share some prospective technologies. This Review aims to provide an overview of the whole process in lithium-ion battery fabrication from powder to cell formation and bridge the gap between academic development and industrial manufacturing.

Opportunities for the State-of-the-Art Production of LIB Electrodes—A Review

A sustainable shift from internal combustion engine (ICE) vehicles to electric vehicles (EVs) is essential to achieve a considerable reduction in emissions. The production of Li-ion batteries (LIBs) used in EVs is an energy-intensive and costly process. It can also lead to significant embedded emissions depending on the source of energy used. In fact, about 39% of the energy consumption in LIB production is associated with drying processes, where the electrode drying step accounts for about a half. Despite the enormous energy consumption and costs originating from drying processes, they are seldomly researched in the battery industry. Establishing knowledge within the LIB industry regarding state-of-the-art drying techniques and solvent evaporation mechanisms is vital for optimising process conditions, detecting alternative solvent systems, and discovering novel techniques. This review aims to give a summary of the state-of-the-art LIB processing techniques. An in-depth understanding of the influential factors for each manufacturing step of LIBs is then established, emphasising the electrode structure and electrochemical performance. Special attention is dedicated to the convection drying step in conventional water and N-Methyl-2-pyrrolidone (NMP)-based electrode manufacturing. Solvent omission in dry electrode processing substantially lowers the energy demand and allows for a thick, mechanically stable electrode coating. Small changes in the electrode manufacturing route may have an immense impact on the final battery performance. Electrodes used for research and development often have a different production route and techniques compared to those processed in industry. The scalability issues related to the comparison across scales are discussed and further emphasised when the industry moves towards the next-generation techniques. Finally, the critical aspects of the innovations and industrial modifications that aim to overcome the main challenges are presented.

Study of color kinetics of banana (Musa cavendish) under microwave drying by application of image analysis

Microwave drying works on the volumetric heating concept promoted by electromagnetic radiation at 0.915 or 2.450 GHz. In this study, banana (Musa Cavendish) was taken as the sample and treated under microwave drying. The effect of two process variables, namely slice thickness (2, 3.5, and 5 mm) and microwave power (180 W, 360 W, and 540 W), were studied on drying kinetics and color kinetics. It was observed that the inverse variation relationship exists between drying time and microwave power level while drying time and slice thickness exhibited a direct variation relationship. A Computer Vision System (CVS) was developed to measure the color values of banana in CIELab space using an algorithm written in MATLAB software. Once the color parameters were obtained, they were fitted in First and Zero-order kinetic models. Both models were found to describe the color values adequately. This study concludes that microwave drying is a promising dehydration technique for banana drying that reduces the significant time of drying. Application of CVS is an excellent approach to measure the surface color of banana.

Computational analysis of temperature distribution in microwave-heated potatoes

This research article reports the computational analysis of temperature distribution in microwave-heated convenience food such as potato. The detailed study of temperature (because temperature is a function of bacterial inactivation) and microwave powers along with drying time for the preservation of food material has been presented. Therefore, a mathematical model for potato sample is developed to predict the behavior of temperature distribution at each possible point and different shapes (slab, cylindrical, and spherical) of food material. The developed mathematical model is programmed by MATLAB software. Another parameter, microwave power is also a function of temperature. The ranging values of various microwave powers (125 W, 375 W, 625 W, 875 W, and 1250 W) along with different values of drying time (0 to 10 minutes) have been used for computation. The obtained results show the uniformity of temperature distribution throughout the whole product in the form of a three-dimensional structure. The model provides the minimum and maximum temperature ranges in specimens without performing an experiment which depicts the condition of bacterial inactivation.

Thin-layer drying of parchment Arabica coffee by controlling temperature and relative humidity

This paper presents thin-layer drying of parchment coffee (Coffea arabica). Thin-layer drying of parchment coffee was conducted under controlled temperatures (50°C, 60°C, and 70°C) and relative humidities (10%-30%). The temperature of the drying air was important for drying at a high temperature, which results in the rapid removal of moisture and reduced time for drying. Nine thin-layer drying models (Newton, Page, Henderson and Pabis, logarithmic, two-term, modified Henderson and Pabis, two-term exponential, approximation diffusion, and modified-Midilli) were fitted to the experimental data for parchment coffee. The drying parameters of parchment coffee were related to temperature and relative humidity. The best model was the modified-Midilli model, which can be used to design the optimal dryer. The effective moisture diffusivity of parchment coffee drying was determined by minimizing the sum of squares of the deviations between the experimental data for the moisture content and the predicted values of thin-layer drying. The effective moisture diffusivity as a function of the temperature at each relative humidity was expressed by the Arrhenius-type equation.