The iron and steelmaking industry faces the dilemma of the need to decrease their greenhouse gas emissions to align with decarbonization goals, while at the same time fulfill the increasing steel demand from the growing population. Replacing fossil coal and coke with biomass-based carbon materials reduces the net carbon dioxide emissions. However, there is currently a shortage of charcoal to fully cover the demand from the iron and steelmaking industry to achieve the emission-reduction goals. Moreover, the transportation and energy sectors can compete for biofuel usage in the next few decades. Simultaneously, our society faces challenges of accumulation of wastes, especially wet organic wastes that are currently not reused and recycled to their full potentials. Here, hydrothermal carbonization is a technology which can convert organic feedstocks with high moisture contents to solid fuels (hydrochar, one type of biochar) as an alternative renewable carbon material. This work studied the differences between a hydrochar, produced from lemon peels (Lemon Hydrochar), and two types of charcoals (with and without densification) and an Anthracite coal. Characterizations such as chemical and ash compositions, thermogravimetric analyses in nitrogen and carbon dioxide atmospheres, scanning electron microscope analyses of carbon surface morphologies, and pyrolysis up to 1200 °C were performed. The main conclusions from this study are the following: (1) hydrochar has a lower thermal stability and a higher reactivity compared to charcoal and Anthracite; (2) densification resulted in a reduction of the moisture pickup and CO2 reactivity of charcoal; (3) pyrolysis of Lemon Hydrochar resulted in the formation of a large amount of tar (17 wt%) and gas (39 wt%), leading to its low fixed carbon content (27 wt%); (4) a pyrolyzed hydrochar (up to 1200 °C) has a comparable higher heating value to those of charcoal and Anthracite, but its phosphorous, ash, and alkalis contents increased significantly; (5) based on the preliminary assessment, hydrochar should be blended with charcoal or Anthracite, or be upgraded through slow pyrolysis to fulfill the basic functions of carbon in the high-temperature metallurgical processes.

Hydrochar (a solid product from hydrothermal carbonization of organic feedstock) and charcoal have the potential to substitute coke and coal consumption in the iron and steelmaking processes for reduction of greenhouse gas (GHG) emissions. Among steelmaking processes, melt carburization is an important but less-studied application. In this study, briquettes produced with mixture a of iron powder, hydrochar or charcoal powder, and binder were tested as iron melt recarburizers. It was found that the hydrochar briquettes have good mechanical properties, whereas those of charcoal briquettes were poor. Melt carburization with briquettes was performed in a lab induction furnace (10 kg) in two steps: firstly, by heating up some briquettes with charged electrolytic iron from room temperature up to 1600 °C, followed by the addition of some briquettes into the melt. Recarburization efficiency (RE) during the first step of carburization was found to be controlled by the amount of carbon content bound in the solid phase (fixed carbon) determined at 1200 °C. Thus, the REs of charcoal briquettes (70–72%) were higher than those of hydrochar (43–58%) due to the higher fixed carbon contents in charcoal. REs obtained from the second step were strongly affected by the amount of briquette losses during their addition into the iron melt, which correlate with the mechanical strengths of the briquettes. Thus, the REs for hydrochar briquettes (48–54%) were higher than those of charcoal (26–39%). This study proves the feasibility of using hydrochar and charcoal as liquid steel recarburizers.

Fingerprint orientation field (OF) estimation is important for basic fingerprint image processing and impacts the accuracy of fingerprint image enhancements, such as Gabor filters. In this article, we introduce an OF estimation algorithm based on differential values of grayscale intensity and examine the accuracy and reliability of the proposed algorithm by applying it to fingerprint images processed using Gaussian blurring and the Gaussian white noise process. The experimental results indicate that the OF estimation reliability of the proposed algorithm is higher than the gradient-based method and the power spectral density (PSD) based method in low quality fingerprints. The proposed algorithm is especially useful in noisy fingerprint images, where the OF estimation reliability of the algorithm is 6.46% and 32.93% higher than the gradient-based method and the PSD-based method, respectively.