Devolatilization Kinetics of Different Types of Bio-Coals Using Thermogravimetric Analysis

Abstract

The interest of the steel industry in utilizing bio-coal (pre-treated biomass) as CO2-neutral carbon in iron-making is increasing due to the need to reduce fossil CO2 emission. In order to select a suitable bio-coal to be contained in agglomerates with iron oxide, the current study aims at investigating the thermal devolatilization of different bio-coals. A thermogravimetric analyzer (TGA) equipped with a quadrupole mass spectrometer (QMS) was used to monitor the weight loss and off-gases during non-isothermal tests with bio-coals having different contents of volatile matter. The samples were heated in an inert atmosphere to 1200 °C at three different heating rates: 5, 10, and 15 °C/min. H2, CO, and hydrocarbons that may contribute to the reduction of iron oxide if contained in the self-reducing composite were detected by QMS. To explore the devolatilization behavior for different materials, the thermogravimetric data were evaluated by using the Kissinger– Akahira–Sonuse (KAS) iso-conversional model. The activation energy was determined as a function of the conversion degree. Bio-coals with both low and high volatile content could produce reducing gases that can contribute to the reduction of iron oxide in bio-agglomerates and hot metal quality in the sustained blast furnace process. However, bio-coals containing significant amounts of CaO and K2O enhanced the devolatilization and released the volatiles at lower temperature.

Self-Reduction Behavior of Bio-Coal Containing Iron Ore Composites

“…This may affect the release of H 2 O during reaction as the ion current for H 2 O is highest for FRC although that the H-content is similar as for SDC. The impact of ash composition on the devolatilization behavior of bio-coals was indicated in a previous study [28] where bio-coal with a higher content of catalyzing components released the VM at lower temperature, and this may restrict its contribution to the reduction. High intensity of H 2 O followed by CO 2 and H 2 detected in QMS analyses for FRC indicates that some of the CO is consumed in the reaction.…”

“…Carbonaceous materials used are stated in Table 1, their proximate and ultimate analysis as analyzed by ALS Scandinavia AB using standard methods are presented in Table 2 and the composition of other raw materials can be seen in Table 3. The ash composition in bio-coal materials was reported in detail in a previous study [28], c.f. Table 4.…”

Ironmaking and Steelmaking

“…This Special Issue published 33 high quality articles from 10 countries (according to the country of the corresponding author) with the number of contributions in brackets: China (22) , Japan (1) [23], Korea (1) [24], Canada (1) [25], Sweden (2) [26,27], Italy (1) [28], UK (1) [29], France (1) [30], Austria (1) [31], and Slovakia (2) [32,33]. This clearly reflects the enormous investment in R&D in China and the resultant outstanding outcomes to support its steel industry with~50% of global steel production.…”

“…A UK-Netherland-USA contribution (Slater et al [29]) studied the solidification phenomena of a molten steel surface by using infrared thermography and a Sweden-Russia contribution (Sidorova et al [27]) reported the modification of non-metallic inclusions in oil-pipeline steels by Ca-treatment. A paper co-authored by scientists from Sweden and Egypt (El-Tawil et al [26]) investigated the thermal devolatilisation of different bio-coals for the purpose of reducing fossil CO 2 emission in the steel industry. Other international collaborations include France-Canada-Albania (Kanari et al [30]), Slovakia-Czech Republic (Neslušan et al [33]), China-Ukraine (Cao et al [1]), and China-UK (Ge et al [2]).…”

“…Naseri Seftejani and Schenk [31] analysed the thermodynamics of the hydrogen plasma smelting reduction of iron ore in the process of using hydrogen in a plasma state to reduce iron oxides. The other nine papers covered experimental studies (El-Tawil et al [26], Fukushima, and Takizawa [23], Wu et al [5], Zhou et al [6], Zhang et al [7]), modelling predictions (Gao et al [8], Tang et al [9]), and kinetic analysis (Wang et al [10], Chen et al [11]).…”