Search Results (86)

Chemical recycling via catalytic pyrolysis is constrained by coke deposition and costly catalyst make-up. We investigate polypropylene (PP) and low-density polyethylene (LDPE) conversion over a spent FCC equilibrium catalyst (AXL) and, critically, quantify the re-activation energy landscape of the resulting coke. Using a semi-batch reactor (350 °C) and thermogravimetric analysis to 1100 °C combined with the Ozawa–Flynn–Wall method, we distinguish soft and hard coke under inert, oxidative, and sequential N₂ to air regimes. LDPE yields mainly gas (70.7 wt%) with 5.5 wt% coke, whereas PP favors liquids (47.1 wt%) with 3.4 wt% coke. LDPE-derived coke is softer (71% of total; E_A = 170 kJ mol⁻¹ soft) than PP coke (60% soft; E_A = 166 kJ mol⁻¹), evidencing a more refractory PP residue. Oxygen lowers E_A to ~155 kJ mol⁻¹ for both polymers. We introduce a simple TGA-based “softness ratio” to guide regeneration severity and show that a refinery-waste FCC catalyst delivers selective plastic-to-fuel conversion while enabling energy-aware regeneration protocols. The framework directly supports scale-up by linking polymer structure, coke quality, and atmosphere-dependent re-activation energetics. Full article

Using a relatively inexpensive method, phenol–cresol–formaldehyde resin (PhCR-F) was produced utilizing the byproducts of coal coking. It is shown that petroleum road bitumens, to which 1.0 wt.% PhCR-F is added, in terms of basic physical and mechanical parameters, comply with the requirements of the regulatory document for bitumens modified with adhesive additives. Research on the operational properties of these modified bitumens as a binding material for asphalt concrete is described. It has been proven that modified bitumen can store stable properties during its application (resistance to aging). The interaction of bitumens modified by PhCR-F with the surfaces of mineral materials, which occurs during the creation of asphalt concrete coatings, was studied. It was shown that adding 1.0 wt.% PhCR-F to road bitumen significantly improves the adhesion of the binder to the mineral material and increases the hydrophobicity of such a coating. The production of effective bitumen modifiers from non-target coking products of coal will not only make it possible to use new resources in road construction but will also increase the depth of decarbonization of the coking industry. Full article

The conceptual design and techno-economic assessment of Pressure Swing Adsorption (PSA) for the recovery of H₂, CO₂, and CO from steel making Blast Furnace-Basic Oxygen Furnace and Coke Oven off-gases, major contributors to anthropogenic carbon emissions, are presented. Three PSA units are modeled on Aspen Adsorption V14, each utilising dedicated adsorbents and configurations tailored for the target gas. Model validation is successfully conducted by comparing breakthrough simulation results with experimental data. The simulation results demonstrate that the PSA systems effectively separate H₂ (99.3% purity, 80% recovery), CO (98% purity, 87% recovery), and CO₂ (96.9% purity, 75% recovery) from steelmaking off-gases. Meanwhile, the techno-economic assessment indicates that the PSA systems are economically viable, with competitive costs of £2768/tH₂, £52.78/tCO, and £16.89/tCO₂ captured, making them an effective solution for gas separation in the steel industry. Full article

When applying advanced technologies and technological methods for the preparation of coal raw materials (technology for coking stamped batch, technology for coking dry or thermally prepared batch), the problem of developing high bursting pressure arises. The aim of this research is to assess the possibility of predicting the bursting pressure of coal blends taking into account their technological properties and petrographic characteristics, as well as to study the effect of bursting pressure on the metallurgical properties of coke. Standardized methods were used to study the technological properties of coal and coal blends (determination of technical and petrographic analyses). The qualitative characteristics of coke were studied using physical, mechanical, and thermochemical methods for the study of standardized indicators: crushability (M₂₅), abrasion (M₁₀), reactivity (CRI), and post-reaction strength (CSR). The regression equations for predicting the bursting pressure of coal blends, taking into account the volatile matter in the blend, vitrinite content, and grinding, which are characterized by high correlation coefficients (0.89 and 0.9), were proposed. Their use will make it possible to optimize the composition of coal batches, control the bursting pressure during regrinding, and reduce the number of experimental measurements in a particular coke production. It was also found that an increase in the bursting pressure by 1 kPa can be expected to increase the mechanical strength of coke in terms of crushability M₂₅ by about 2.6% and reduce the abrasion of coke M₁₀ by 1%. Full article

The efficient utilization of heavy oil is of great significance to alleviating the global energy crisis. How to efficiently convert heavy oil into high-value-added light fuel oil has become a hot issue in the field of petrochemicals. As the residual part of crude oil processing, heavy oil has a complex composition and contains polycyclic aromatic hydrocarbons, long-chain alkanes, and heteroatom compounds, which makes it difficult to process directly. Zeolite, as an important type of solid acid catalyst, has a unique pore structure, adjustable acidity, and good thermal stability. It can promote the efficient cracking and conversion of heavy oil molecules, reduce coke formation, and improve the yield and quality of light oil products. This paper systematically reviews the development status of heavy oil cracking technology, focusing on the structural characteristics, acidity regulation of zeolite catalysts, and their applications in heavy oil cracking and hydrocracking. The mechanism of the cracking reaction of polycyclic aromatic hydrocarbons and long-chain alkanes is analyzed in detail, and the catalytic characteristics and modification methods of zeolite in the reaction process are explained. In addition, this paper summarizes the main challenges faced by zeolite catalysts in practical applications, including uneven acidity distribution, limited pore diffusion, and easy catalyst deactivation, and proposes targeted development strategies. Finally, this paper looks forward to the future development direction of zeolite catalysts in the field of heavy oil cracking and upgrading reactions, emphasizes the importance of structural optimization and multi-scale characterization, and provides theoretical support and practical reference for the design and industrial application of efficient zeolite catalysts. Full article

The conventional diagnostic techniques for ethylene cracker furnace tube coking rely on manual expertise, offline analysis and on-site inspection. However, these methods have inherent limitations, including prolonged inspection times, low accuracy and poor real-time performance. This makes it challenging to meet the requirements of chemical production. The necessity for high efficiency, high reliability and high safety, coupled with the inherent complexity of the production process, results in data that is characterized by multimodal, nonlinear, non-Gaussian and strong noise. This renders the traditional data processing and analysis methods ineffective. In order to address these issues, this paper puts forth a novel soft measurement approach, namely the ‘Mixed Student’s t-distribution regression soft measurement model based on Variational Inference (VI) and Markov Chain Monte Carlo (MCMC)’. The initial variational distribution is selected during the initialization step of VI. Subsequently, VI is employed to iteratively refine the distribution in order to more closely approximate the true posterior distribution. Subsequently, the outcomes of VI are employed to initiate the MCMC, which facilitates the placement of the iterative starting point of the MCMC in a region that more closely approximates the true posterior distribution. This approach allows the convergence process of MCMC to be accelerated, thereby enabling a more rapid approach to the true posterior distribution. The model integrates the efficiency of VI with the accuracy of the MCMC, thereby enhancing the precision of the posterior distribution approximation while preserving computational efficiency. The experimental results demonstrate that the model exhibits enhanced accuracy and robustness in the diagnosis of ethylene cracker tube coking compared to the conventional Partial Least Squares Regression (PLSR), Gaussian Process Regression (GPR), Gaussian Mixture Regression (GMR), Bayesian Student’s T-Distribution Mixture Regression (STMR) and Semi-supervised Bayesian T-Distribution Mixture Regression (SsSMM). This method provides a scientific basis for optimizing and maintaining the ethylene cracker, enhancing its production efficiency and reliability, and effectively addressing the multimodal, non-Gaussian distribution and uncertainty of the coking data of the ethylene cracker furnace tube. Full article

In modern nickel mineral processing operations, the aim is to separate pentlandite from gangue minerals. One of these gangue minerals, pyrrhotite, contains up to 1 wt% Ni but is disposed of as waste, i.e., as tailings. Declining sulfide ore grades and increasing nickel demand have led to renewed interest in extracting nickel from pyrrhotite tails. One proposed process is thermal concentration, which aims to recover the nickel as a ferronickel alloy via thermal treatment at temperatures greater than 900 °C. Achieving these temperatures requires substantial energy input as the reactions involved are highly endothermic. In the present research, microwave radiation was used to process a reaction mixture consisting of a concentrate of pyrrhotite tails, iron ore, and metallurgical coke. The fundamental property that determines the interaction of microwaves with a material is complex permittivity. It was found that the reaction mixture had very high real and imaginary permittivities, making it a good candidate for microwave treatment. An input power of 800 W of microwave radiation (2450 MHz) was then employed to heat various reaction mixtures for thermal treatment times of 120, 300, and 600 s. The ferroalloy grades (6–7.5 wt% Ni) were comparable to those produced by conventional heating and to those obtained by other authors using conventional heating techniques. The microwaved samples had increased metallization of nickel, which was attributed to increased melting due to the higher internal temperatures. Full article

Industrial heat sources (IHSs) are major contributors to energy consumption and environmental pollution, making their accurate detection crucial for supporting industrial restructuring and emission reduction strategies. However, existing models either focus on single-class detection under complex backgrounds or handle multiclass tasks for simple targets, leaving a gap in effective multiclass detection for complex scenarios. To address this, we propose a novel multiclass IHS detection model based on the YOLOv8-FC framework, underpinned by the multiclass IHS training dataset constructed from optical remote sensing images and point-of-interest (POI) data firstly. This dataset incorporates five categories: cement plants, coke plants, coal mining areas, oil and gas refineries, and steel plants. The proposed YOLOv8-FC model integrates the FasterNet backbone and a Coordinate Attention (CA) module, significantly enhancing feature extraction, detection precision, and operational speed. Experimental results demonstrate the model’s robust performance, achieving a precision rate of 92.3% and a recall rate of 95.6% in detecting IHS objects across diverse backgrounds. When applied in the Beijing–Tianjin–Hebei (BTH) region, YOLOv8-FC successfully identified 429 IHS objects, with detailed category-specific results providing valuable insights into industrial distribution. It shows that our proposed multiclass IHS detection model with the novel YOLOv8-FC approach could effectively and simultaneously detect IHS categories under complex backgrounds. The IHS datasets derived from the BTH region can support regional industrial restructuring and optimization schemes. Full article

Carbon dioxide is emitted in several industrial processes and contributes to global warming. One of the industries that is considered a significant emitter is metallurgy. Therefore, it is necessary to search for and implement methods to reduce its emissions from metallurgical processes. An alternative option to the use of conventional coke, which is produced solely from fossil coal, is the utilization of bio-coke. The production of bio-coke involves the use of coking coal and the incorporation of biomass-derived substances such as biochar (charcoal). The article presents the results of the research on the influence of the biochar addition on the structural, textural, and technological properties of produced bio-coke. Research on the production and analysis of the properties of the obtained bio-coke aimed at assessing the potential possibilities of applying it in the process of a carbothermal reduction of manganese ore in order to smelt ferroalloys. Studies have shown that biochar addition to the coking blend in an amount of up to 20% allows a bio-coke characterized by properties enabling the mentioned use to be obtained. Bio-coke was characterized by higher CO₂ reactivity index (CRI), lower post-reaction strength (CSR), and higher reactivity to synthetic manganese ore than regular metallurgical coke. In the context of industrial applications of bio-coke, it is necessary to verify its production and use on a pilot and industrial scale. Full article

This paper investigates the potential use of coked sands, a byproduct of the thermal processing (pyrolysis) of oil sands, in asphalt concrete mixtures. After pyrolysis extracts the oil from the oil sand, the remaining mineral part becomes coked and changes color to black as solid waste, resulting in a coating of biochar. The coked sand’s X-ray phase analysis (XRD) shows peaks at 4.2564, 3.6749, 3.3768, 3.2380, 3.1903, 2.4581, 2.2800, and 2.2365. Quartz, aluminosilicates, metal oxides, and possibly even carbonates make up the sand’s mineral makeup, as indicated by these peaks. One way to use them is in road construction. In this study, we substituted sand screenings with coked sand in amounts of 5%, 7%, and 10% to examine its impact on the composition of asphalt concrete. This study used 5% paving bitumen (BND 70/100) as a binder for asphalt mineral materials of varying sizes. It concludes that using coked sand to produce asphalt concrete can save 5–10% of sand screenings. The test results showed that adding 5% and 7% of coked sand increases the compressive strength at 50 °C by 8% and 31%, respectively. Adding 10% of coked sand does not increase the strength and actually makes it weaker. The results of the asphalt concrete samples meet type B grade 1 standards of ST RK 1225-2019. Full article

The exhaustion of conventional light oils necessitates the shift towards unconventional sources such as biomass, heavy oil, oil shale, and coal. Non-catalytic thermal cracking by a free radical mechanism is at the heart of the upgrading, prior to refining into valuable products. However, thermal pyrolysis is hindered by the formation of asphaltenes, precursors to coke, limiting cracking, causing equipment fouling, and reducing product stability. Free radicals are inherently present in heavy fractions and are generated during thermal processes. This makes these reactive intermediates central to understanding these mechanisms and limiting coking. Electron spin resonance (ESR) spectroscopy facilitates such mechanistic studies. Over the past decade, there has been no review of using in-situ ESR for studying thermal processes. This work begins with a brief description of free radicals’ chain reactions during thermal reactions and the wealth of information ESR provides. We then critically review the literature that uses ESR for mechanistic studies in thermal pyrolysis of biomass, heavy oil, shales, and coal. We conclude that limited literature exist, and more investigations are necessary. The key findings from existing literature are summarized to know the current state of knowledge. We also explicitly highlight the research gaps. Full article

High-pressure air injection (HPAI) is an enhanced oil recovery process in which compressed air is injected into deep, light oil reservoirs, with the expectation that the oxygen in the injected air will react with a fraction of the reservoir oil at an elevated temperature to produce carbon dioxide. The different chemical reactions taking place can be grouped into oxygen addition, thermal cracking, oxygen-induced cracking, and bond scission reactions. The latter reactions involve the combustion of a flammable vapor as well as the combustion of solid fuel, commonly known as “coke”. Since stable peak temperatures observed during HPAI experiments are typically below 300 °C, it has been suggested that thermal cracking and combustion of solid fuel may not be important reaction mechanisms for the process. The objective of this work is to assess the validity of that hypothesis. Therefore, this study makes use of different oxidation and combustion HPAI experiments, which were performed on two different light oil reservoir samples. Modeling of those tests indicate that thermal cracking is not an important reaction mechanism during HPAI and can potentially be ignored. The work also suggests that the main fuel consumed by the process is a flammable vapor generated by the chemical reactions. This represents a shift from the original in situ combustion paradigm, which is based on the combustion of coke. Full article

This paper presents the results of analytical studies of the combustion process of semi-coke, cedar sawdust, and their mixtures using the TGA method at three different heating rates with the determination of the main characteristics of heating: the presence of synergetic interaction between the components of the mixture affecting the maximum rate of combustion and kinetic parameters. Calculations of activation energy and pre-exponential multiplier of the Arrhenius equation by the Friedman and Ozawa–Flynn–Wall priori methods for initial combustibles and their mixtures have been carried out. Semi-coke was obtained by thermal treatment of brown coal at 700–900 °C to remove volatile substances, which makes it more environmentally friendly than the original coal. Semi-coke has a higher heat of combustion than biomass, and biomass has a higher reactivity than semi-coke. The combustion process of biomass occurs in a lower temperature range, and adding biomass to semi-coke shifts the combustion process to a lower temperature range than such for biomass. Adding at least 50% of biomass to semi-coke increases the combustion index by at least 1.1 times. Regardless of the heating rate of mixtures, synergetic interaction between the mixture’s components increases the maximum combustion rate of coke residue by 20%. Full article

The quality of coking coal is vital in steelmaking, impacting final product quality and process efficiency. Conventional forecasting methods often rely on empirical models and expert judgment, which may lack accuracy and scalability. Previous research has explored various methods for forecasting coking coal quality parameters, yet these conventional methods frequently fall short in terms of accuracy and adaptability to different mining conditions. Existing forecasting techniques for coking coal quality are limited in their precision and scalability, necessitating the development of more accurate and efficient methods. This study aims to enhance the accuracy and efficiency of forecasting coking coal quality parameters by employing neural networks and artificial intelligence algorithms, specifically in the context of Knurow and Szczyglowice mines. The research involves gathering historical data on various coking coal quality parameters, including a proximate and ultimate analysis, to train and test neural network models using the Group Method of Data Handling (GMDH). Real-world data from Knurow and Szczyglowice mines’ coal production facilities form the basis of this case study. The integration of neural networks and artificial intelligence techniques significantly improves the accuracy of predicting key quality parameters such as ash content, sulfur content, volatile matter, and calorific value. This study also examines the impact of these quality indicators on operational costs and highlights the importance of final indicators like the Coke Reactivity Index (CRI) and Coke Strength after Reaction (CSR) in expanding industrial reserve concepts. Model performance is evaluated using metrics such as mean absolute error (MAE), root mean square error (RMSE), and coefficient of determination (R²). The findings demonstrate the effectiveness of these advanced techniques in enhancing predictive modeling in the mining industry, optimizing production processes, and improving overall operational efficiency. Additionally, this research offers insights into the practical implementation of advanced analytics tools for predictive maintenance and decision-making support within the mining sector. Full article

The metallurgical sector is one of the most emission- and energy-intensive industries. The possibility of using fossil carbon substitutes has been investigated to reduce the environmental impact of the steelmaking sector. Among others, biochar emerged as a promising fossil coal/coke substitute. We conducted a literature review on biochar use in the metallurgical sector and its potential environmental benefits. The possibility for biochar as a coal/coke substitute is influenced by the source of biochar production and the process within which it can be used. In general, it has been observed that substitution of biochar ranging from a minimum of 5% to a maximum of 50% (mostly around 20–25%) is possible without affecting, or in some cases improving, the process, in coke making, iron sintering, blast furnaces and electric furnaces application. In some studies, the potential CO₂ reduction due to biochar use was estimated, ranging from 5% to about 50%. Despite there still being an area of further investigation, biochar appeared as a promising resource with a variety of uses in the metallurgical sector, contributing to the lowering of the environmental impact of the sector. Full article