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By D Brown, Z Tabor

Projects must be flexible to account for the rapid development of new technologies and changing stakeholder expectations. Coupled with calls for bleeding-edge solutions, customers, shareholders, and regulators demand robust, safe products and systems-of-systems. Developing and integrating these solutions is becoming increasingly complex and maintaining the flexibility required to ‘pivot’ to effective solutions can be a serious challenge. The necessary flexibility is fundamental to the Agile ethos, and this family of methodologies therefore offers a potential solution to this challenge (Beedle et al, 2001). These have traditionally been delivered with systems engineering applied through a Waterfall methodology. Agile Systems Engineering combines both approaches and presents a means to achieve these goals without compromising flexibility, quality or safety. A robust methodology for the application of Agile Systems Engineering is required to enhance practical outcomes and reduce risk for real-world mining projects.

Sep 1, 2024

By B Taylor, S Evans

Bulk explosive technology for underground mining has not seen any significant technological advances since the widespread transition from ammonium nitrate fuel oil (ANFO) to ammonium nitrate emulsions (ANE) commencing in the 1980s. The in-hole energy profile that conventional ANE systems deliver is limited by the physics of chemical gassing and simple control systems. This compromises the range, precision, and accuracy of energy delivery into the blasthole, and in some cases limits the length of charge that can be delivered. Orica’s 4D™ bulk system removes many of these constraints, enabling better blasting performance across all underground mining methods. This paper reviews work completed at three mining operations across Australia, the United States, and Chile with a focus on how this system can improve mining operations and deliver sustained commercial and productivity benefits into the future. These benefits include improved ore recovery, reduced dilution from waste rock, and reduced overall explosives consumption. This paper also reviews how this new technology can be applied for planning future mining operations.

Sep 1, 2024

By B Gyngell, P Culvenor

Large language models (LLMs) have generated a lot of hype since ChatGPT was released in early 2023. In essence, they allow people to interact with computer systems through natural language and have the ability to generate highly complex text, images and videos (Patil and Gudivada, 2024). It is clear that this technology has significant potential, however most mining companies have not yet found practical applications for it within their operations. In this paper, we present a range of such applications along with the tactical considerations associated with developing and implementing them. We have identified use cases across a variety of operational and functional areas within the mining industry and evaluated them based on their potential business value and ease of implementation. Firstly, we provide an overview of how LLMs work and a review of how LLMs are being applied in other industries to provide best practice inspiration for mining. Next, we present a list of possible applications in mining and a critical assessment of each use case. This section also includes a technical deep dive into the different methodologies for developing the technologies as well as an analysis of barriers to adoption within mining organisations. Finally, we share a discussion of the potential path forward for LLMs in mining and the impact they could have on the industry. We analyse the potential differences between early adopters and laggards in the artificial intelligence (AI) space. This research draws on interviews and surveys with artificial intelligence experts as well as mining subject matter experts to connect cutting edge thought leadership with the specific problems faced by our industry.

Sep 1, 2024

By M Rea, E O’Connell

Decarbonising explosives manufacturing and catalysing low-carbon mining supply is a significant global challenge. Low-carbon manufacturing precincts – clusters of geographically close businesses across multiple industries that share a goal of adopting firmed renewable energy and decarbonising process emissions – offer one potential solution. In an Australian first, Orica commissioned tertiary catalyst abatement technology in 2023 to mitigate greenhouse gas (GHG) emissions at its Kooragang Island (KI) facility in New South Wales (NSW), Australia. The EnviNOx® technology (ThyssenKrupp Industrial Solutions AG, Dortmund, Germany) used reduces nitrous oxide (N2O), a potent greenhouse gas arising as a by-product of nitric acid manufacture. As a result, mining customers in NSW are now benefitting from ammonium nitrate (AN) products that are almost 50 per cent less emissions-intensive than those Orica previously offered. The $37 million project is a private-public partnership that has involved partners across Federal and State government, global engineering and technology vendors, local community groups and local carbon advisors to overcome financial barriers.

Sep 1, 2024

By J Herd, J Rowe, M Cutbush, d F. Aziz

WearApp provides expertise for assessing the degradation of removable screening media panels on vibrating screens right in a user’s pocket. Through the WearApp application, users can simply take a picture of a panel using their mobile, enter some basic information and have the application assess the wear to provide a recommendation for whether the panel needs to be replaced. Where traditional mechanisms for assessing panel wear only measure a few points across the panel face and rely on having personnel with specialised knowledge available to perform the assessment, WearApp uses deep learning models to analyse the entire panel face and support the user to make an informed decision. The application works through analysing a panel image and using a model to automatically detect the corners of the panel. Given the known dimensions of the panel, this enables the application to calibrate the pixel size against a known reference. A second set of models then detect the apertures and measure their dimensions. With the aperture dimensions defined the application assesses the wear of the panel through referencing a stored 3D model of the aperture. Finally, the data from each aperture is collated and the wear of the entire panel face defined. Since WearApp performs measurement of the entire panel face, it also allows the user to perform a more detailed analysis of the panel’s wear profile. Where typically, the panel wear is only measured in a few locations, WearApp’s analysis enables users to visualise the panel wear across the entire panel face, identifying areas of high wear that could be leading to premature panel replacement. Additionally, because the entire panel face is measured the change in screening efficiency can be calculated accurately for the worn panel, even taking into account the impact of aperture pegging by small rocks.

Sep 1, 2024

By M Jones

Legacy tailings storage facilities exist within operating mine sites across Australia. These tailings storage facilities are often viewed as rehabilitation liabilities but with considered assessment may prove to be a resource. Extraction of such a resource might add value to operations by providing cash flow during the development of new mines; providing supplementary mill feed for existing mines undergoing step changes in operations; and supporting mine closure activities. Hellyer Gold Mines is successfully extracting and reprocessing sub-aqueous material from legacy tailings storage facilities at their Hellyer operation in north-west Tasmania. The Hellyer tailings storage facilities contain poly-metallic material from the Hellyer and Fossey underground deposits dating back to the 1980s as well as material from tailings reprocessing activities by other operators of the Hellyer site. Hellyer Gold Mines is reclaiming sub-aqueous material using cutter-suction dredgers and reprocessing on-site. Hellyer is the only operation of its type in Australia and few such operations exist worldwide. Key learnings around the estimation of a resource for legacy tailings storage facilities have been acquired at Hellyer that can be applied to the assessment of other tailings storage facilities. The application of dredging as a mining method at Hellyer is delivered through collaboration with experts from outside the mining industry under the direction of a mining engineer. Key elements required for the planning and delivery of safe and efficient dredging inside tailings storage facilities have been identified at Hellyer and are presented to provide a road map to the development of other dredging operations.

Sep 1, 2024

By M Barkh, F X. Spachtholz

The mining industry faces significant environmental challenges in managing tailing ponds and wastewater treatment, including the risk of contaminated water, breaches of tailing dams, and energy-intensive treatment processes. Traditional methods involve pumping water to secondary treatment facilities for neutralisation, which is costly and poses operational and environmental risks. In response to these challenges, the Professional Mine Water Action Plan (PMAP) introduces a revolutionary approach that combines cutting-edge AI technology and environmentally friendly reagents for in situ neutralisation of acidic wastewater. PMAP leverages magnesium-based slowrelease reagents and AI-driven intelligent dispensing systems to optimise treatment processes within the tailing pond itself. The unmanned smart dispensing vessel (USDV) conducts bathymetry to gather data on water quality and hydrography, allowing the system to determine the appropriate reagent quantity and injection strategy. This approach transforms the tailing pond into virtual reaction columns, enabling individual and simultaneous water treatment while optimising efficiency. PMAP’s novel reagent demonstrates exceptional efficacy in removing critical metals like cobalt, nickel, and copper, as well as reducing harmful metals such as mercury and manganese to undetectable concentrations. Unlike traditional lime-based treatments, PMAP’s reagent prevents gypsum formation and reduces waste volume significantly, improving reagent utilisation and solid waste handling. Furthermore, PMAP technology offers benefits beyond environmental stewardship. By reducing water treatment costs and improving resource management, it enhances operational efficiency and aligns with broader corporate sustainability goals. Additionally, PMAP expedites permitting processes by eliminating the need for traditional water treatment infrastructure and mitigating risks associated with hazardous reagent transportation. Integrating PMAP as a pre-treatment for existing lime facilities provides further benefits, including optimisation of treatment operations, reduced reagent consumption, and the recovery of valuable metals from generated sludges. Overall, PMAP represents a groundbreaking advancement in mining wastewater management, showcasing the transformative potential of AI and environmentally friendly solutions to foster sustainable and responsible mining practices globally. Its inaugural project in the Yukon Territory aims to demonstrate its capability to remove contaminants from mine water, paving the way for widespread adoption in the industry.

Sep 1, 2024

By A Tsang, D La Rosa, L Julian, W Hunt, R Pratama

Mineral extraction is facing the twin challenges of finite resources and increasing environmental and economic costs. Society’s growth is matched by an increase in demand for the earth’s resources. It is incumbent on us as contemporary mining professionals to promote and facilitate ethical and efficient practices. Technological developments have and will continue to allow a decrease in viable cut-off grades, creating new economic opportunities from deposits that were previously uneconomic. Mining low-grade deposits however, even with perfect recoveries, will have a significant environmental cost for the metal won. The greatest opportunity to increase metal with the least environmental cost is to increase the metal yield from existing mines. The determination of mining polygons is a critical juncture where rock is typically subjected to the binary grading of either ore or waste. This is undertaken using a number of factors, such as the mining equipment being used and the recovery in the processing plant. Traditionally, mining polygons were generated on the in situ grade control model. This ignores the complex differential blast dynamics that occur during blasting. Two opportunities exist to improve metal yields: optimise the blast design to achieve the post-blast muck pile that will support the greatest outcome; and generate optimised polygons on the post-blast muck pile. A data set from a Canadian Gold deposit is used to demonstrate the potential benefit of iterative blast movement modelling and grade control polygon optimisation on metal yield. The impact of blasting on the total recoverable metal is presented, highlighting blast design as a critical process in the mining value chain.

Sep 1, 2024

By B P. Voutharoj, R A. Dutch, M Paknezhad, T Ostersen

With the proliferation of new sensor technologies, acquiring multiple data sets over the same ground is becoming cheaper and easier than ever. This new, higher resolution multivariate data provides a significant resource for exploration and resource geologists but comes with the added complexity of effectively integrating the various data sets in useful and meaningful ways to elucidate new geological understanding. Both geophysical data sets and hyperspectral data are extensively used for exploration targeting, providing different information at different resolutions and crustal scales. One of the biggest challenges comes from trying to effectively integrate data sets that record very different physical properties, across the different scales these data are captured at, in a way which can allow for a data-driven analysis of these combined data sets.

Sep 1, 2024

By S Gulati, N Sarkar, T Vink, S Battersby, L Okada

This paper examines a successful project implemented by BHP Mitsubishi Alliance (BMA) and the Polymathian team at Deswik, aimed at enhancing short-term scheduling processes to reduce vessel turn times in the BMA Central Queensland coal value chain. The project’s objective was to digitalise the planning process to enable planners to make data-driven insights to improve the profitability of the value chain. The strategy involved developing a digital mining system that incorporates data storage, cloud computing, and the ability to meet the integration needs of both internal and external business systems. This was complemented by a sophisticated, optimisation-based, decision-support tool to enhance the planning teams’ ability to make timely and effective decisions.

Sep 1, 2024

By K Sherry, N Shahbazi

Scope 3 emissions are a set of often overlooked indirect greenhouse gas emissions within a company’s value chain and represent the majority of emissions for many sectors. These emissions arise from activities conducted by entities beyond the reporting organisation’s ownership or direct control and are often challenging to calculate. Scope 3 emissions typically encompass purchasing goods and services, transportation and distribution, managing operational waste, downstream processing and utilising sold products. Within the mining sector, scope 3 emissions often constitute a significant portion of the overall carbon footprint. Therefore, these emissions are a significant aspect of the future of sustainable mining. As the journey towards a world committed to achieving Net Zero Emissions has started, the time to spark a transformative conversation in the mining industry has arrived. Consequently, a better knowledge of scope 3 footprints allows organisations to assess their emission mitigation projects against the total carbon impact of their operations and products.

Sep 1, 2024

By J Coveney, A Rich, D Grimsey, J Wood, S Creedy

In 2021, BHP and Metso examined processing of high-MgO nickel sulfide concentrates using Metso’s Ausmelt Top-Submerged-Lance (TSL) technology. Test work was conducted in Metso’s pilot test work facility in Dandenong, Australia to explore operability of the SiO2-FeO-MgO-CaO-NiO slag system across a wide range of compositions, temperatures and bath oxygen potentials. Pilot-scale testing aimed to define slag ‘operability limits’, representing the lowest bath temperature at which stable process and equipment operation could be maintained. This work was supported by FactSage™, version 8.2 (by Thermfact/CRCT and GTT-Technologies) thermodynamic modelling, slag viscosity measurements, physical characterisation of quenched slag samples performed by the University of Queensland and benchmarking of commercial-scale TSL nickel smelting operations. A wide range of slag compositions were examined, with Fe/SiO2 ratios varying from 0.4–1.1, CaO content from 0.8–7.0 wt per cent and MgO content from 6–19 wt per cent. Slag SiO2/MgO ratio, wt per cent CaO and matte grade were found to have the greatest impacts on identified operability limits. Operability limits were found to be influenced by both the solids content in slag and viscosity of the remaining liquid slag phase, with the relative contribution of these parameters heavily influenced by the slag composition. In the majority of trials, limits were defined by a theoretical solids content of 40–50 per cent, however in trials with a low Fe/SiO2 ratio and/or low wt per cent CaO, limits were characterised by a much lower solids content due to the increased effect of the liquid slag viscosity in determining the behaviour of these slags. The test work highlighted inherent flexibility of the Ausmelt TSL process to operate across a wide slag range of slag compositions and recover from process disturbances without an interruption to feeding. The trials also demonstrated the possibility for Ausmelt TSL technology to process concentrates with an Fe/MgO ratio as low as 1.4, which has important implications to the commercial-scale processing of high MgO feeds. Arsenic rejection across the trials was very good, with only 30 per cent of arsenic in the feed inputs reporting to the matte phase. Such high levels of arsenic removal provide the Ausmelt TSL process with a notable advantage over alternative smelting technologies.

Aug 21, 2024

By A Van den Bulck, K Verbeken, O Vergote, I Bellemans

Viscosity is one of the most important physicochemical properties during pyrometallurgical operations. In the sub-liquidus regime, an important factor is the presence of suspended solid particles, yet its influence is not well-described in earlier literature, despite the significance of this factor. This project aims to determine the influence of spinel particles (Zn(Al,Fe)2O4) on the rheology of a multiphase synthetic PbO-SiO2-ZnO-Fe2O3-CaO-Al2O3 slag system. Three data sets with a wellcontrolled methodology and three different spinel sizes (small (13 μm), medium (34 μm) and large particles (76 μm)) were published previously, using a custom-built high-temperature rheometer. This study presents an additional data set of slag viscosity measurements, performed using a different apparatus, the Anton Paar FRS 1800, to verify the consistency of the earlier determined viscosity behaviour. Within this data set, no consistent trend could be found between the predicted wt per cent spinel and the relative viscosity. Therefore, additional quenching experiments were conducted to identify the morphology and experimentally determined volume fraction of the spinel particles in the slag. These measurements revealed a difference in spinel size across the samples and corresponding viscosity behaviour, emphasizing the importance of spinel particle size on slag viscosity. Once the spinel size was taken into account, consistent viscosity results (relative apparent viscosity and flow index) were observed across the two devices. This study confirms that, once all parameters affecting slag viscosity are considered, the viscosity behaviour of a heterogeneous slag can be uniquely determined. The resulting optimised slag viscosity models can be used to predict viscosity before processing, addressing relevant phenomena such as slag tapping, slag foaming and copper droplet settlement.

Aug 21, 2024

By R E. Gerald II, B Zhang, T Sander, J D. Smith, J Huang, R J. O’Malley, H Tekle

In the steelmaking process, mold fluxes are essential for ensuring thermal insulation, refining, and the efficiency of continuous casting. Real-time understanding of the in-service composition of slags and fluxes are crucial for optimising the steel production process and improving the quality of the final product. An in situ fibre-optic Raman probe that enables the study of the structure, composition, and viscosity of molten slags and fluxes at steelmaking temperatures has been developed and demonstrated both in the lab and in foundry scale experiments. The focus of this study is on the structural, compositional, and property analysis of molten fluxes in a laboratory setting, with the aim of applying this technology for in situ monitoring during industrial production. Raman spectra were successfully collected at various temperatures from 1000°C to 1400°C in real-time and analysed using a deconvolution algorithm to isolate and quantify peaks in the spectra associated with the specific structures of molecular components in molten and solidifying flux. The research successfully combines in situ Raman spectroscopy with high-temperature viscosity data, specifically targeting CaO-CaF-SiO2-Al2O3 based mould flux systems. Specified ratios of the deconvoluted Raman peaks, such as Al-O-Al/Si-O-Si ratio, shows good correlation with the flux chemistry, while the Q3/Q0 peak ratio shows good correlation with viscosity. A ruggedised Raman probe system was also developed and demonstrated in an 80 kg induction furnace. Ultimately, the goal of this work is to demonstrate in situ slag and mould flux analysis in industrial processes, such as in the continuous caster or electric arc furnace (EAF).

Aug 21, 2024

By G M. Tranell, M Tangstad

The CO2 footprints in the production of Mn-ferroalloys and silicon/ferrosilicon are correlated with the fossil carbon consumption. The CO2 emissions may be reduced in the Mn-ferroalloy process by increasing the degree of prereduction and reduction of carbonate materials, while the silicon/ferrosilicon process is optimised based on silicon yield. By changing the fossil reductant into biogenic reductants, the global warming potential will be decreased even more. Even if the reductants are biogenic reductants, there will still be a global warming potential (GWP) in eg the electrode consumption and the CH4 emissions in the charcoal production. To reduce the use of fossil reductants there are also more disruptive technologies like the use of H2 that at least for the silicon production is on a very low technology readiness level (TRL). Using metallothermic processes will reduce the use of carbon but requires carbon neutral metal reductants. Electrowinning can have low CO2 emissions, and the electrowinning of pure Mn is a technology of high TRL. Salt and oxide electrolysis is under investigation for both Mn and Si production however the research is still on a low TRL. The use of CCS/CCU (carbon capture storage/utilisation) is a part of obtaining carbon neutral processes. Last, the energy mix used for these energy demanding processes is discussed.

Aug 21, 2024

By E Jak, M Shevchenko, E Nekhoroshev, D Shishin

In the field of pyrometallurgy, the presence of multiple molten phases with distinct chemical compositions, such as slags, mattes, speiss liquids, metals and molten salts, is a well-known phenomenon. These phases exhibit strongly non-ideal solution behaviour and are mutually miscible to varying degrees. To describe these complex molten liquids, the Modified Quasichemical Model (MQM) has proven effective and has been applied to numerous binary, ternary and several higher-order multicomponent systems related to pyrometallurgy. In recent decades, the complexity of high-temperature processes has escalated due to increased impurity concentrations in primary ores, the incorporation of recycled consumer products and the integration of metallurgical plants through by-product and waste exchanges. To address these issues, PYROSEARCH laboratory has been developing large 20-component thermodynamic database using a generalised CALPHAD (CALculation of PHAse Diagrams) methodology integrated with experimental investigations. Over the past decade, strategic decisions were made balancing the ability to generate experimental data, prediction power, accuracy, stability of calculations, as well as computational time, which are discussed in the paper. Examples provided for issues of >3 liquid immiscibility, non-ionic behaviour and exaggerated ‘sharp’ enthalpies of mixing in silicate slags, dealing with multiple oxidation states, as well as comparative analysis of pair and quadruplet approximation in MQM.

Aug 21, 2024

By P Taskinen, D Lindberg

The increase in metals demand in the electrifying globe means significant growth in the smelting of copper, nickel, zinc, and lead, produced from primary sulfide sources or using sulfide mattes as the intermediates of the process chains. This means that leaner and complex mineral deposits will be evaluated as ores and are in the future traded in the commodity market for smelting and refining to pure metals. An important issue in the trend is the technology metals, like antimony, tellurium, and gallium, which exist as trace elements in sulfide ores and form no ores of their own. Their recovery becomes important in the coming decades as will be the case with growing slag amounts without use in other industries. The key is to produce environmentally acceptable slags in the smelting operations. It sets new boundary conditions to the treatment of flue dusts. This means that all material streams of smelting and refining must be re-evaluated for the deportments of the main and minority metals. In copper smelting, the recoveries of precious metals are today important for the feasibility of the custom smelters but due to low prices of many minority metals they are discarded in slag landfills. It is one of the emerging issues also in the secondary copper smelting today and once the demand grows, the same question will be faced also in the mining-beneficiation-smelting-refining chain of the primary production of nickel, zinc, and lead. The distributions of many technology metals in the copper and nickel smelting have been recently studied using methods where the chemically bound trace elements in the slag and its phases at the smelting conditions have been studied. Thus, the key data about options for process modifications and additional processing steps are piling up. Short processing routes in the metals smelting and refining are attractive due to their simplicity. At the same time, complexity of many raw materials challenges the fluxing at high oxygen partial pressures in low silica slags with high metal concentrations. The compromise between high primary recovery and safe operation is a demanding task in conditions where slag foaming outside the processing window is evident. The increase in the demand of pure nickel is challenging the raw material basis where low-grade sulfide ores are soon smelted along with nickel laterites to matte. It is a demanding task at high MgO concentrations. The low solubility of MgO in iron silicate slags requires new fluxing strategies and new smelting end points for the operation at reasonable temperatures; the direct nickel matte smelting in one-matte mode may be an option.

Aug 21, 2024

By M K. Nahian, R G. Reddy

The thermodynamic model for species distribution in aluminium chloride (AlCl3) and 1-butyl-3- methylimidazolium chloride (BMIC) system was developed. The experimental thermodynamic data, considering a range of aluminium chloride species, such as AlCl4-, Al2Cl7-, Al3Cl10-, Al4Cl13-, and Al2Cl6 were used in developing the model. When the XAlCl3 was in the range of 0 to 0.50, only anion species Cl- and AlCl4- were existing in the solution. As the XAlCl3 value increased more than 0.50, the available anions were Al2Cl7-, Al3Cl10-, Al4Cl13-, and Al2Cl6. Specifically, the concentration of Al2Cl7- increased in the composition range from 0.50 to 0.67 XAlCl3, after which it decreased. This change in the concentration of Al2Cl7- was due to its reaction with excess AlCl3, leading to the formation of Al3Cl10-. The average cathode current density was determined by the electrochemical experiments varying XAlCl3 from 0.50 to 0.71 in the AlCl3:BMIC solutions. The average cathode current density increased as the XAlCl3 increased from 0.50 to 0.67. However, it decreased when the XAlCl3 > 0.67. This trend can be attributed to the electroactive species Al2Cl7-. The Al2Cl7- promotes the reduction rate at the cathode, resulting in an increase in the average cathode current density.

Aug 21, 2024

By B Laidens, D Souza, W Bielefeldt

The CaO-MgO-SiO2-Al2O3 system, characterised by its intricate phases and thermodynamic properties, plays a pivotal role in steel secondary refining processes, encompassing desulfurisation, non-metallic inclusion capture, and refractory protection. Accurate predictions for diverse industrial applications, including metallurgy, ceramics, and materials science, are imperative. To address this challenge, a combination of machine learning techniques will be specifically applied to model the liquid fraction of the slag and the solid fraction of MgO. The development of an artificial intelligence (AI) system, leveraging various machine learning techniques, has gained momentum in this project. The focus of this work is on constructing an AI model, based on machine learning techniques, within the CaO-MgO-SiO2-Al2O3 system, utilising simulation results from FactSage™, version 8.1 (by GTT Technologies). The primary objective is to train the AI model using these simulation outputs to predict the percentage of liquid fraction and MgO saturation based on chemical composition parameters. The AI model will undergo training with a comprehensive data set of simulations within the CaOMgO- SiO2-Al2O3 system, covering a diverse range of compositional at 1873 K. These simulations, conducted through FactSage™ 8.1 software, provide a robust foundation for AI model training, ensuring generalisability and precise predictions for the liquid fraction of the slag and the solid fraction of MgO, the solid fraction of MgO in this case is determined by the difference between the total MgO and the MgO in the liquid fraction, so it is not the objective of this study to determine which phase of MgO is in the solid state.. The predictive capabilities of this AI model hold significant implications for process optimisation, quality control, and decision-making in CaO-MgO-SiO2-Al2O3- dependent industries. Precise estimations of the liquid fraction and MgO saturation empower researchers and engineers to enhance operational efficiency and quality. This paper explores the methodologies employed for AI model creation and training, achieved results in terms of prediction accuracy, and potential applications in the field. The development of this AI system signifies a notable advancement in utilising machine learning for better comprehension and control of complex chemical systems. Furthermore, to align the study with real-world steel production, we introduce FeO and MnO at concentrations of 2 per cent and 1 per cent at 1873 K, respectively, following the validation of model results using the CaO-MgO-SiO2-Al2O3 system. This adjustment aims to bring the study closer to the observed reality in steel mills globally.

Jun 19, 2024

By F Tang, Ö K. Büyükuslu, M Baben, S Petersen

GTT-Technologies’ ChemApp for Python was developed to provide a powerful, easy to use interface to ChemApp for a programming language highly popular with scientists and engineers. It is used, for instance, by GTT to develop program modules such as the CALPHAD Optimiser for the FactSage™ software, by customers to move from interactive FactSage calculations to perform versatile scripting with Python, and by GTT and its partners in research projects in the area of materials informatics. Computational thermochemistry is fundamental for advancing sustainable metallurgy and creating new alloy compositions for engineering applications. Materials informatics involves handling vast amounts of data and complex workflows. GTT’s approach uses ChemApp for Python and the FactSage thermodynamic databases to design recyclable alloys from the start, incorporating a higher percentage of scraps while aiming to simplify the workflows to simulate material design steps. Challenges arise due to recycling scraps, introducing more elements for consideration. CALPHAD-based databases accurately cover materials from primary metallurgy, but additional data for minority and critical elements is crucial for precise computational modelling. GTT combines machine learning-based ab-initio databases with traditional CALPHAD databases to cover the complete chemical space with appropriate accuracy. The design of a hardfacing alloy through a high-throughput materials informatics approach is used as a demonstrator of the current possibilities.

Jun 19, 2024