Biomass is a key renewable feedstock for producing green fuels; however, renewable feedstock presents a high risk for catalyst deactivation and poor stability. In addition, the heat source of industrial reforming processes comes from fuel combustion and most heat is lost in the flue gas. In this study, a Ni/Al2O3/FeCrAl-based monolithic catalyst with a periodic open cellular structure (POCS) was designed and 3D-printed. A reforming process was then conducted by directly heating the catalyst using electricity instead of fuel combustion. This e-reformer technology was demonstrated in continuous catalytic steam reforming of biomass pyrolysis volatiles. A high H2 yield of ≈7.1 wt % of biomass has been obtained at a steam-to-biomass (S/B) ratio of 4.5, reforming temperature of 800 °C and weight hourly space velocity (WHSV) of 310 h−1, resulting in an energy consumption of 8 kWhel kg−1 biomass (66% energy efficiency). The results show a successful demonstration of the electrified technology with improvement potential; in addition, a process was designed and assessed economically for synthetic natural gas (SNG) production of 80 MWHHV, comparing electrification and partial oxidation in different scenarios.

This study aims to improve the quality and yield of bio-oil produced from ex-situ catalytic pyrolysis of lignocellulosic biomass (sawdust) using a combination of stage catalysts with Al-MCM-41, HZSM-5, and ZrO2. The research employed various methods, including thermogravimetric analysis (TGA), differential scanning calorimetry, bench-scale experiments, and process simulations to analyze the kinetics, thermodynamics, products, and energy flows of the catalytic upgrading process. The introduction of ZrO2 enhances the yield of monoaromatic hydrocarbons (MAHs) in heavy organics. Compared with the dual-catalyst case, the MAHs yield escalates by approximately 344% at a catalyst ratio of 1:3:0.25. Additionally, GC-MS data indicate that the incorporation of ZrO2 promotes the deoxygenation reaction of the guaiacol compound and the oligomerization reactions of PAHs. The integration of ZrO2 as the third catalyst enhances the yield of heavy organics significantly, achieving 16.85% at a catalyst ratio of 1:3:1, which increases by nearly 35.6% compared to the dual-catalyst case. Also, the addition of ZrO2 as the third catalyst enhanced the energy distribution in heavy organics. These findings suggest that the combination of these catalysts improves the fuel properties and yields of the bio-oil.

The global Sustainable Development Goals highlight the necessity for affordable and clean energy, designated as SDG7. A sustainable and feasible biorefinery concept is proposed for the carbon-negative utilization of biomass waste for affordable H2 and battery anode material production. Specifically, an innovative tandem biocarbon + NiAlO + biocarbon catalyst strategy is constructed to realize a complete reforming of biomass pyro-vapors into H2+CO (as a mixture). The solid residues from pyrolysis are upgraded into high-quality hard carbon (HCs), demonstrating potential as sodium ion battery (SIBs) anodes. The product, HC-1600-6h, exhibited great electrochemical performance when employed as (SIBs) anodes (full cell: 263 Wh/kg with ICE of 89%). Ultimately, a comprehensive process is designed, simulated, and evaluated. The process yields 75 kg H2, 169 kg HCs, and 891 kg captured CO2 per ton of biomass achieving approx. 100% carbon and hydrogen utilization efficiencies. A life cycle assessment estimates a biomass valorization process with negative-emissions (−0.81 kg CO2/kg-biomass, reliant on Sweden wind electricity). A techno-economic assessment forecasts a notably profitable process capable of co-producing affordable H2 and hard carbon battery anodes. The payback period of the process is projected to fall within two years, assuming reference prices of 13.7 €/kg for HCs and 5 €/kg for H2. The process contributes to a novel business paradigm for sustainable and commercially viable biorefinery process, achieving carbon-negative valorization of biomass waste into affordable energy and materials.

This study introduces a distributed electrified heating approach that is able to innovate chemical engineering involving endothermic reactions. It enables rapid and uniform heating of gaseous reactants, facilitating efficient conversion and high product selectivity at specific equilibrium. Demonstrated in catalyst-free CH4 pyrolysis, this approach achieves stable production of H2 (530 g h−1 L reactor−1) and carbon nanotube/fibers through 100% conversion of high-throughput CH4 at 1150 °C, surpassing the results obtained from many complex metal catalysts and high-temperature technologies. Additionally, in catalytic CH4 dry reforming, the distributed electrified heating using metallic monolith with unmodified Ni/MgO catalyst washcoat showcased excellent CH4 and CO2 conversion rates, and syngas production capacity. This innovative heating approach eliminates the need for elongated reactor tubes and external furnaces, promising an energy-concentrated and ultra-compact reactor design significantly smaller than traditional industrial systems, marking a significant advance towards more sustainable and efficient chemical engineering society.

The decarbonisation of the Swedish iron and steel industry is crucial in achieving Sweden's target to achieve zero net emissions of greenhouse gases (GHG) by 2045. Direct electrification of industrial furnaces could be an important milestone in decarbonising the iron and steel plants. In this study, pilot-scale trials were performed to investigate the possibility of plasma torch application for steel reheating furnaces. A 250 kW DC plasma torch was used to heat the furnace from room to the operating temperature of 1200 degrees C. Different plasma carrier gases were then used to study their impact on the plasma torch efficiency, furnace temperature profile, NOX emission, and steel oxidation. The results show that the furnace could be heated at a relatively uniform temperature and reasonable time. The combination of air and LPG in the plasma generator provides the most uniform temperature distribution and highest plasma torch efficiency, but it generates the highest NOX emission. N2 as plasma gas resulted in notably poorer temperature distribution and lower plasma torch efficiency; however, it can suppress the oxide formations. Meanwhile, CO2 as plasma gas could be a promising option among the studied gas mixtures as it can provide a good heating performance with a low NOX formation. In summary, the current study has proved that it is practical and functionally possible to heat steel using plasma technology.

Catalyst research on reforming processes for syngas production has mainly focused on the active metals and support materials, while the effect of the catalyst's geometry on the reforming reactions has been poorly studied. The application of 3D-printed materials with enhanced geometries has recently started to be studied in heterogeneous catalysis and is of interest to be implemented for reforming biomass and plastic waste to produce H2-rich syngas. In this study, a geometry-enhanced 3D-printed Ni/Al2O3/FeCrAl-based monolithic catalyst with a periodic open cellular structure (POCS) was designed and fabricated. The catalyst was used for batch steam reforming biomass pyrolysis volatiles for syngas production at different parameters (temperature and steam-to-carbon ratio). The results showed complete reforming of pyrolysis volatiles in all experimental cases, a high H2 yield of ≈ 7.6 wt% of biomass was obtained at the optimized steam-to-carbon ratio of 8 and a reforming temperature of 800 °C, which is a higher yield compared to other batch reforming tests reported in the literature. Moreover, CFD simulation results in COMSOL Multiphysics demonstrated that the POCS configuration improves the reforming of pyrolysis volatiles for tar/bio-oil reforming and H2 production thanks to enhanced mass and heat transfer properties compared to the regular monolithic single-channel configuration.

Bioenergy with carbon capture and storage (CCS) in iron and steel production offers significant potential for CO2 emission reduction and may even result in carbon-negative steel. With a strong ambition to reach net-zero emissions, some countries, such as Sweden, have recently proposed measures to incentivise bioenergy with CCS (BECCS), which opens a window of opportunities to enable the production of carbon-negative steel. One of the main potential applications of this route is to decarbonise the iron reduction processes that account for 85 % of the total CO2 emission in the iron and steel plants. In this study, gasification is proposed to convert biomass into biosyngas to reduce iron ore directly. Different cases of integrating the biomass gasifier, Direct Reduced Iron (DRI) shaft furnace, and CCS are evaluated through process simulation work. Based on the result of the work, the proposed biosyngas DRI route has comparable energy demand compared to other DRI routes, such as the well-established coal gasification and natural gas DRI route. The proposed process can also capture 0.65-1.13 t of CO2 per t DRI depending on the integration scenarios, which indicates a promising route to achieving carbon-negative steel production.

Given the urgent need for transitions towards global net zero emissions, decarbonisation of the iron and steel industry is critical. Deep decarbonising this sector requires a breakaway from current blast furnace-basic oxygen furnace (BF-BOF) technologies that largely depend on fossil resources. Biosyngas is considered to be a promising alternative to fossil energy and reductants used in existing ironmaking due to its renewability, technological maturity and compatibility for use in existing furnaces. The present work assesses the environmental impacts of biosyngas-based direct reduced iron production followed by electric arc furnace (DRI-EAF) routes for crude steel production. Further, the proposed routes are compared with the other steelmaking routes, including BF-BOF, natural gas (NG)-based and hydrogen-based direct reduction routes by performing life cycle assessment (LCA). The results indicate that the global warming potential (GWP) value for the biosyngas-based DRI-EAF system is 75% lower than the existing NG-based DRI-EAF route and 85% lower than the BF-BOF route. Moreover, the proposed system possibly has lower GWP values than the renewable hydrogen-based DRI-EAF route. The pro-posed system has an estimated cradle-to-gate GWP of 251 kg CO2 eq./t crude steel, of which 80% is from up-stream emissions. Combined with CO2 storage, the GWP of the proposed system is a net negative, estimated at-845 kg CO2 eq./t crude steel for the selected system boundary. In addition to GWP, other non-climate impact indicators are also evaluated to identify potential burden shifting. The results highlight the emissions reduction potential of the novel biosyngas DRI production route. Large-scale deployment, however, requires sustainable forest management and adequate CCS infrastructure, along with a strong, long-term policy framework to incentivise the transitions.

Feedstock properties play a crucial role in thermal conversion processes, where understanding the influence of these properties on treatment performance is essential for optimizing both feedstock selection and the overall process. In this study, a series of van Krevelen diagrams were generated to illustrate the impact of H/C and O/C ratios of feedstock on the products obtained from six commonly used thermal conversion techniques: torrefaction, hydrothermal carbonization, hydrothermal liquefaction, hydrothermal gasification, pyrolysis, and gasification. Machine learning methods were employed, utilizing data, methods, and results from corresponding studies in this field. Furthermore, the reliability of the constructed van Krevelen diagrams was analyzed to assess their dependability. The van Krevelen diagrams developed in this work systematically provide visual representations of the relationships between feedstock and products in thermal conversion processes, thereby aiding in optimizing the selection of feedstock and the choice of thermal conversion technique.

An in-depth knowledge of pyrolytic kinetics is vital for understanding the thermal decomposition process. Numerous experimental studies have investigated the kinetic performance of the pyrolysis of different raw materials. An accurate prediction of pyrolysis kinetics could substantially reduce the efforts of researchers and decrease the cost of experiments. In this work, a model to predict the mean values of model-free activation energies of pyrolysis for five types of feedstocks was successfully constructed using the random forest machine learning method. The coefficient of determination of the fitting result reached a value as high as 0.9964, which indicates significant potential for making a quick initial pyrolytic kinetic estimation using machine learning methods. Specifically, from the results of a partial dependence analysis of the lignocellulose-type feedstock, the atomic ratios of H/C and O/C were found to have negative correlations with the pyrolytic activation energies. However, the effect of the ash content on the activation energy strongly depended on the organic component species present in the lignocellulose feedstocks. This work confirms the possibility of predicting model-free pyrolytic activation energies by utilizing machine learning methods, which can improve the efficiency and understanding of the kinetic analysis of pyrolysis for biomass and fossil investigations.