Flowsheet Model and Simulation of Produced Slag in Electric Steelmaking to Improve Resource Management and Circular Production

The steel industry is one of the most energy-intensive sectors, as it requires a great amount of resources and produces a considerable quantity of by-products, with not negligible environmental impact. Therefore, the main challenge of steelworks consists in improving sustainability and reducing carbon footprint of the production process, by ensuring the required quality of final products. In this context, the reuse and recycling of by-products can play a key role in preventing their landfilling and waste of valuable products, reducing the exploitation of primary raw materials, decreasing CO2 emissions, and supporting the implementation of the Circular Economy concept. In particular, one of the main by-products is slag, which can be used as a potentially valuable source of secondary raw materials, leading to a substantial reduction of natural resources usage and related costs. This paper concerns part of the work developed inside the EU-funded project entitled “Optimising slag reuse and recycling in electric steelmaking at optimum metallurgical performance through on-line characterization devices and intelligent decision support system – iSlag”. The main focus of this project is the valorisation of slags produced in the electric steelmaking route, by defining good practices, investigating new recycling paths, and promoting industrial symbiosis solutions. In this paper, the adaptation and the improvement of a previously developed Aspen Plus® simulation model are presented to obtain an accurate prediction of slag features. In particular, the model estimates amount and composition of slags produced in the primary and the secondary steelmaking processes, and it allows simulating different case scenarios including usual and unusual conditions, for instance, process operating conditions, raw materials compositions, steel families to be produced. In addition to slag features, product compositions and environmental and energy impacts can be monitored with the model

Optimizing integrated steelworks process off-gas distribution through Economic Hybrid Model Predictive Control and Echo State Networks

Steel production in integrated steelworks involves the simultaneous production of various byproducts, including process off-gases that are usually exploited for generating electricity in the internal power plant, heat and steam. Their discontinuous production is managed through complex network, gasholders and torches, which must be managed with stringent operational constraints. In this paper we present a supervision and control system designed to optimize the economic management of the distribution of process off-gases that also allows minimizing the environmental impact. The system implements a digital twin based mainly on machine learning techniques, including Echo State Networks, and a hierarchical optimization system, which first level is based on an economic model predictive approach and the second level is based on the economic hybrid model predictive control. This system allows to effectively maximize the use of off-gases while minimizing the environmental impact of their use up to 97%

Self-assembled monolayers of cobalt(II)- (4-tert-butylphenyl)-porphyrins: the influence of the electronic dipole on scanning tunneling microscopy images.

Self-assembled monolayers (SAMs) of cobalt(II) 5,10,15,20-tetrakis(4-teit-butylphenyl)-porphyrin, a promising material for optical, photoelectrochemical, and chemical sensor applications, were prepared on Au(111) via axial ligation to 4-aminothiophenol, and studied by several surface science techniques. Scanning tunneling microscopy (STM) and spectroscopy (STS) measurements showed the apparent topology of the Au(111) herringbone structure reconstruction. but with bias-dependent contrast images and asymmetric W characteristics. Photoelectron spectroscopy confirmed the presence of metalloporphyrins on the surface, whereas near-edge X-ray absorption (NEXAFS) measurements revealed that the porphyrin ring was tilted by about 70degrees with respect to the surface plane. The above effects are ascribed to the presence of oriented molecular dipole layers between the metal and the organic material as confirmed by a comparison with first-principles density-functional theory calculations. The measured bias-dependent STM profiles have been reproduced by a simple monodimensional tunneling model

A flowsheet-based model approach to reduce water consumption and improve water networks management in the steel sector

Resource consumption is an important topic for steelmaking industry, which is spending significant efforts to reduce its environmental impact and improve its competitiveness. Water is largely exploited in steelworks for indirect and direct cooling, specific surface treatment, and fumes washing and cooling. It is already reused and recycled after restoring its quality through treatments for temperature and/or pollutant reduction. However, sometimes water networks are not optimized due to outdated water treatments, lack of continuous monitoring, and water network management strategies often based on experience without automation. In recent years, new water treatments, simulation, and optimization tools are becoming available, together with a stronger awareness of the importance of online parameters monitoring. Therefore, improvement of water cleaning, reuse, recycling, and consequent reduction of impact related to water exploitation are potentially achievable. The introduction of innovative treatments must be tested before their implementation in steel plants and the exploration of their behavior in different operating conditions is fundamental. The presented work addresses this topic through the application of several models of operational units, developed in OpenModelica environment and aggregated into a plant simulator. The simulator was used in different case studies related to an Italian plant to assess the impact of new filtering technology for reducing suspended solids on the analyzed water networks and test the effects of different operating configurations on the treatment efficiency. The introduction of new filtration technology leads to environmental and economic advantages due to freshwater intake reduction and water management improvemen

X-ray excited visible luminescence spectroscopy of organic materials using a portable optical spectrometer

The use of a portable video telescope, mounted externally to a beamline endstation, to obtain synchrotron-radiation-excited visible luminescence, is described. Real-time video monitoring permits simple and quick alignment, and allows a visual record of the luminescence experiment. The telescope is fibre-optic-coupled to an optical spectrometer. Examples are given of X-ray excited optical spectroscopy from organic materials for light-emitting-diode applications

Zinc Porphyrin‐Driven Assembly of Gold Nanofingers

Nanofingers of gold covered by porphyrins are prepared by a combination of atomic manipulation and surface self-organization. A submonolayer of zinc(II) 5,10,15,20-tetrakis(4-tert-butylphenyl)-porphyrin (ZnTBPP) axially ligated to a self-assembled monolayer of 4-aminothiophenol (4-ATP) on Au(111) is prepared and studied using a combination of ultrahigh vacuum techniques. Under the electric field produced by the STM tip, the relatively weakly bound Au surface atoms along the discommensuration lines become mobile due to the strong bond to 4-ATP, while the tendency of the porphyrins towards self-assembly result in a collective motion of gold clusters. The clusters diffuse onto the surface following well-defined pathways along the [112] direction and then reach the step edges where they assembled, thus forming nanofingers. First-principles density functional theory calculations demonstrate the reduction of the binding energies between the surface gold clusters and the substrate induced by adsorption of thiols. Scanning tunneling microscopy images show assemblies across three adjacent discommensuration lines of the Au(111)-(22 x square root 3) reconstruction, which collectively diffuse along these lines to form islands nucleated at step edges

Engagement of nuclear coactivator 7 by 3-hydroxyanthranilic acid enhances activation of aryl hydrocarbon receptor in immunoregulatory dendritic cells

Indoleamine 2,3-dioxygenase 1 (IDO1) catalyzes the first step in the kynurenine pathway of tryptophan (Trp) degradation that produces several biologically active Trp metabolites. L-kynurenine (Kyn), the first byproduct by IDO1, promotes immunoregulatory effects via activation of the Aryl hydrocarbon Receptor (AhR) in dendritic cells (DCs) and T lymphocytes. We here identified the nuclear coactivator 7 (NCOA7) as a molecular target of 3-hydroxyanthranilic acid (3-HAA), a Trp metabolite produced downstream of Kyn along the kynurenine pathway. In cells overexpressing NCOA7 and AhR, the presence of 3-HAA increased the association of the two molecules and enhanced Kyn-driven, AhR-dependent gene transcription. Physiologically, conventional (cDCs) but not plasmacytoid DCs or other immune cells expressed high levels of NCOA7. In cocultures of CD4+ T cells with cDCs, the co-addition of Kyn and 3-HAA significantly increased the induction of Foxp3+ regulatory T cells and the production of immunosuppressive transforming growth factor β in an NCOA7-dependent fashion. Thus, the co-presence of NCOA7 and the Trp metabolite 3-HAA can selectively enhance the activation of ubiquitary AhR in cDCs and consequent immunoregulatory effects. Because NCOA7 is often overexpressed and/or mutated in tumor microenvironments, our current data may provide evidence for a new immune check-point mechanism based on Trp metabolism and AhR