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All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Computationally Guided and Experimentally Validated Design of Custom Chelators for Critical Mineral Recovery

Selective, high throughput separation of target critical metals from complex environments such as fly ash leachates and mining process streams presents a significant challenge for economical production. Custom chelators and sorbents are an attractive technology for selective metal extraction, however it can be difficult to predict their performance, and significant experimental efforts are often required to develop chelating technologies. Here, we present a computational strategy focused on modelling chelator-metal binding interactions and benchmark these results versus experimental data. A computational pipeline combining forcefield, semiempirical, and meta-GGA methods with a thermodynamic framework optimized for error cancellation has been developed to predict binding energies of chelator complexes towards critical mineral recovery applications. This approach, originally validated on [2.2.2] cryptates binding mono- and divalent cations, demonstrated robust predictive capabilities with an R2 of 0.850 against experimental aqueous binding energies. The workflow includes metadynamics for exploring high-dimensional potential energy surfaces and a cluster-continuum model for accurate yet computationally efficient solvation modeling. Error cancellation between solvation energies of free and chelator-coordinated ions enables faster convergence, even with finite cluster sizes. Initial studies on the cryptates revealed consistent metal-ligand coordination patterns, with systematic variations influenced by ion size and charge, highlighting key structural features linked to binding selectivity. Further studies of a proprietary chelator have resulted in identification of previously unreported selectivity towards economically significant metals, which in-house experiments have confirmed, demonstrating the feasibility of this approach. By applying this methodology to new chelators targeting critical minerals such as lithium, cobalt, nickel and other strategic metals, we aim to accelerate the discovery of next-generation chelators for efficient recovery, recycling, and separation processes. This computational framework serves as the backbone of a high-throughput design pipeline tailored for sustainable resource utilization and may be applied to a wide range of systems to meet experimental needs.

computational materials↗
DOE OSTI2025

Heterostructured nano-catalysts with efficient metal-oxide interfaces unlock high-performance direct methanol protonic ceramic fuel cells

Direct methanol protonic ceramic fuel cells (PCFCs) are attractive due to their low cost, convenient storage, and high volumetric energy density, as well as their suitability for transportation. However, the poor coking tolerance of conventional nickel-based anodes leads to their susceptibility to severe carbon deposition and significant deactivation after long-term exposure to hydrocarbons. Herein, we report a nano-catalyst of Ce 0.6 Ni 0.2 Cu 0.2 O 2 with a heterogeneous structure that is spontaneously reduced into a Ce 0.6 Ni 0.2-x Cu 0.2-x O 2-δ (CeNCO) oxide framework interfaced with a nano NiCu alloy (denoted as NC/CeNCO) under operating conditions, as confirmed by analyses of X-ray diffraction, X-ray photoelectron spectroscopy, scanning electron microscopy, and transmission electron microscopy. A Ni-BaCe 0.7 Y 0.06 Yb 0.06 Zr 0.06 Hf 0.06 Gd 0.06 O 3-δ anode-supported PCFC employing the NC/CeNCO metal-oxide catalyst achieved a peak power density of 1.11 W cm −2 and operational stability of about 100 h at 700 °C when fueled by 35 % CH 3 OH-15 % H 2 O-50 % N 2 . In conclusion, the enhanced performance and coking resistance are attributed to the efficient interfaces of Ni, Cu, and ceria-based oxide in NC/CeNCO for CH 3 OH reforming, as confirmed by analyses of electrochemical performance and Raman spectroscopy with density functional theory calculations, revealing that these interfaces can enhance CH 3 OH activation and promote efficient OH-mediated carbon removal via COH intermediates.

30 DIRECT ENERGY CONVERSION↗
DOE OSTI2026

Colorado Technology Primer for Economists and Social Scientists: Cooperative Research and Development Final Report, CRADA Number CRD-19-00790

NLR will assist the Colorado School of Mines (Mines) in supporting a series of one-week training workshops. This proposed training program will be two, week-long summer school sessions in each of the next two years to help give early career economists and social scientists a solid introduction and grounding on the technical components of the electrical distribution, transmission, and generation systems as well as basic to advanced overview of clean energy and traditional generation systems.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2020

Integrating Clean Energy in Mining Operations: Opportunities, Challenges, and Enabling Approaches

The mining industry is a major source of raw materials for several industries such as manufacturing, transportation, construction, energy, and mining industry itself. It is anticipated that demand for raw materials is going to increase as the population growth and many low-income economies shift to middle-income countries. The increase in mineral demand accompanies by falling mineral ore grade is expected to increase energy demand raising concern of greenhouse gas emission (GHG). Renewable energy can provide mine operators with solutions to several of the challenges they face today, including energy costs, fossil fuel volatility, social license to operate, and meeting environmental, societal, and governance goals. However, the integration of wind, solar, storage, and other renewable technologies face several barriers that are generally not well understood. Many of these barriers will require further research, development, demonstration, and deployment before we see higher levels of renewables adoption in the mining industry. Thus, this report highlights renewable opportunities, barriers, and enabling approaches.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2020

Integrating Renewable Energy into Mining Operations

The mining industry is a major source of raw materials for several industries such as manufacturing, transportation, construction, energy, and mining industry itself. It is anticipated that demand for raw materials is going to increase as the population growth and many low-income economies shift to middle-income countries. The increase in mineral demand accompanies by falling mineral ore grade is expected to increase energy demand raising concern of greenhouse gas emission (GHG). Renewable energy can provide mine operators with solutions to several of the challenges they face today, including energy costs, fossil fuel volatility, social license to operate, and meeting environmental, societal, and governance goals. However, the integration of wind, solar, storage, and other renewable technologies face several barriers that are generally not well understood. Many of these barriers will require further research, development, demonstration, and deployment before we see higher levels of renewables adoption in the mining industry. Thus, this report highlights renewable opportunities, barriers, and enabling approaches.

clean energy↗
DOE OSTI2024

Rare Earth Elements (REE) and Critical Minerals (CM) in Middle Pennsylvanian-Age Coals and Associated Sediments in the Central Appalachian Basin, Eastern U.S.A.

The Central Appalachian Basin (CAB) of Kentucky, Tennessee, West Virginia and Virginia has a long history of coal mining and oil and gas extraction that has empowered the regional and national economies, the development of infrastructure, and a highly trained energy resources work force. As our societal demands for advanced technologies have rapidly increased in recent years, coal-related materials are viewed as an important new unconventional domestic source of critical minerals (CM) that are required for telecommunications, aerospace and transportation industries, electronics, the transition to low-carbon emissions energy production, and many consumer products. Coal-related materials encompass coal, associated sediments, coal mining waste materials, produced waters, and ash residues from coal-fired power plants. An important objective of the Evolve Central Appalachia Project (Evolve CAPP), sponsored by the U.S. Department of Energy (DOE) National Energy Technology Laboratory (NETL) is to assess the quantity and distribution of CM resources in the CAB region. The rare earth elements (REE) are considered highest priority, although other important CM such as niobium, gallium, and zirconium are known to occur in the Middle Pennsylvanian-age coals and sediments. Working with coal industry partners who provided access to drill cores, coal-related sediments and waste materials, over 600 samples have been collected for laboratory analysis, and over 730 materials have been scanned using portable x-ray fluorescence (pXRF) equipment. The application of pXRF provides the means for real-time semiquantitative analysis of CM content at very close spacings (typically 2-3 inch intervals) along drill core and in-situ channel samples that span the roof, coal seam, and floor rock. The comparison of pXRF geochemical data with laboratory results, geologic data, and downhole spectral gamma logs can provide high resolution input to lithologic and depositional models for future CM resource evaluations. The preliminary findings show that pXRF is capable of accurately measuring low concentrations of many of the CM with a high level of confidence (Ba, Cr, Ga, K, Nb, Rb, Sr, Th, Y), whereas for others (La, Ce, Co, Mn, Nd, Ni, Sc, Ti, V) the detection limits are very high or spectral interferences increase the uncertainty. Notably, the mean abundances of Y (34 ppm), La (86 ppm), Ga (40 ppm), and V (146 ppm) in coal underclays in the CAB region are up to 7X enriched compared with the overlying coal. These values also exceed the reported concentrations in published reference materials for upper continental crustal rocks (Rudnick and Gao, 2003), North American Shale Composite (Gromet et al., 1984), and North American coal (Finkelman, 1993). The pXRF data are in part verified by laboratory results that indicate the mean Y abundance (36 ppm) is highly correlated (R2 = 0.807) with total REE (ΣREE). The correlation is even higher (R2 = 0.957) with heavy REE (ΣHREE). Applying these correlations to the pXRF data for the coal underclays, the mean estimated values for ΣREE+Y and ΣHREE+Y are 270 ppm and 58 ppm, respectively. Although these average values are not considered high, the range of Y measured by pXRF in the coal underclays extended as high as 114 ppm, which would suggest ΣREE+Y equal to 847 ppm. The mean abundances of Zr (192 ppm) and Th (21 ppm) in coal underclays are also enriched compared with the overlying coal and these results likely reflect the presence of resistant detrital heavy minerals such as monazite, xenotime, and zircon in the underclay matrix. Several of the profiled coal seams and associated wall rocks contained thin volcanic ash layers up to 4-5 inches in thickness. The extent to which these ash fall layers provided a source for CM under the paleoenvironmental conditions that resulted in coal deposits in the CAB remains to be fully studied. Continuing investigations in the Evolve CAPP study area will include laboratory determinations of mineralogic and clay compositions, and evaluations of CM geochemical mobility in the coal and coal underclays.

Lassetter, Billy↗
DOE OSTI2026

Computer vision-based rock bolt detection in orthomosaic imagery obtained in the Waste Isolation Pilot Plant underground facility

Assessing structural integrity of large underground tunnel facilities is often a time consuming and human-labor intensive task. Thus, research using various modes of sensing and automated detection of key structural components in mines is posed to aid in safety assessments and establishing overall structural health. We propose an approach utilizing off-the-shelf camera and lidar technology fixed to a custom sensing platform, image stitching techniques, fine-tuned object detection models, and specialized model-inference methods to automatically detect, count, and map roof bolts for assessment of structural safety in man-made underground tunnels. Results show a novel workflow for effective object counting in orthomosaic tunnel ceiling images generated from collections in GPS-denied mining environments. Additionally, we demonstrate effective fine-tuning of EfficientDet object detectors utilizing state-of-the-art image augmentation techniques known as the mosaic and mixup transformations. Our work is demonstrated on sensed data and imagery collected from the Department of Energy (DOE) Waste Isolation Pilot Plant (WIPP) where miles of tunnel ceiling must be assessed for structural integrity.

42 ENGINEERING↗
DOE OSTI2023

Addressing Data Center Cooling Needs through the Use of Subsurface Thermal Energy Storage Systems

This study aims to evaluate the feasibility of addressing the cooling needs for information technology (IT) equipment in data centers by using reservoir thermal energy storage (RTES) to provide reliable and sustainable low-temperature fluid. This project focuses on the technical viability of operating such a system in Houston, Texas, which is a representative location for crypto mining data centers. An analysis has been performed to investigate the technical feasibility with climate data for Houston. Results show that data centers on the scale of 30 MW, and operating at a temperature of 27 degrees C, can be reliably cooled by a combined RTES and dry coolers setup. A techno-economic analysis will be performed and energy/water saving benefits will be quantified in the future. In addition, the study will be extended to other representative data center locations with different climates and geographical locations.

cooling↗
DOE OSTI2025

Measurement of three-dimensional inclusive muon-neutrino charged-current cross sections on argon with the MicroBooNE detector

We report the measurement of the triple-differential cross section d 3 σ/dE vis d cos(θ μ )dP μ for inclusive muon-neutrino charged-current scattering on argon. This measurement utilizes data from 6.4 x 10 20 protons on target of exposure collected using the MicroBooNE liquid argon time projection chamber located along the Fermilab Booster Neutrino Beam with a mean neutrino energy of approximately 0.8 GeV. The mapping from reconstructed kinematics to truth quantities is validated within uncertainties by comparing the distribution of reconstructed hadronic energy in data to that of the model prediction in different muon scattering angle bins after applying a conditional constraint from the muon momentum distribution in data. The success of this validation provides confidence that the energy transfer in the MicroBooNE detector is well-modeled within simulation uncertainties, enabling a reliable unfolding to a triple-differential cross section defined at the nominal neutrino flux over muon momentum, muon scattering angle, and visible neutrino energy. This validation not only supports accurate cross-section extraction, but also establishes a critical foundation for tuning interaction models used in future neutrino oscillation measurements. The unfolded measurement covers an extensive phase space, providing a wealth of information useful for future liquid argon time projection chamber experiments measuring neutrino oscillations. Comparisons against a number of commonly used model predictions are included and their performance in different parts of the available phase-space is discussed.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2022

Disentangling error structures of precipitation datasets using decision trees

Characterizing error structures in precipitation products not only facilitates their proper applications for scientific and practical purposes but also helps improve their retrieval algorithms and processing methods. Despite the fact that multiple precipitation products have been assessed in the literature, factors that affect their error structures remain inadequately addressed. By interpreting 60 binary decision trees, this study disentangles the error characteristics of precipitation products in terms of their spatiotemporal patterns and geographical factors. Three independent precipitation products - two satellite-based and one reanalysis datasets: the Integrated Multi-satellitE Retrievals for GPM (Global Precipitation Measurement) late run (IMERG-L), Soil Moisture to Rain-Advanced SCATterometer (SM2RAIN-ASCAT), and the Modern-Era Retrospective analysis for Research and Applications, Version 2 uncorrected precipitation output (MERRA2-UC), are evaluated across the contiguous United States from 2010 to 2019. Here, the ground-based Stage IV precipitation dataset is used as the ground truth. Results indicate that the MERRA2-UC outperforms the IMERG-L and SM2RAIN-ASCAT with higher accuracy and more stable interannual patterns for the analysis period. Decision trees cross-assess three spatiotemporal factors and find that the underestimation of MERRA2-UC occurs in the east of the Rocky Mountains, and SM2RAIN-ASCAT underestimates precipitation over high latitudes, especially in winter. Additionally, the decision tree method ascribes system errors to nine different geographical characteristics, of which the distance to the coast, soil type, and DEM are the three dominant features. On the other hand, the land cover type, topography position index, and aspect are three relatively weak factors.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

An Overview of R and D on Retrievability and Retrieval Technology in Germany - 20462

Retrievability is a term that is included in most radioactive waste management programs around the world. Although national definitions vary, the overall understanding of retrievability concerns the ability to recover waste packages from the repository mine after their emplacement. Different countries may implement retrievability in very different ways, ranging from a built-in reversibility into the emplacement process to the stipulation that retrievability may in no way impede passive safety in the post-closure phase. Germany takes a middle course such that retrievability in a HLW repository (repository for high level radioactive waste) may have no significant detrimental effect on passive safety. In Germany, the current siting process considers rock salt, clay rock, and crystalline rock as potential host rocks. Therefore, Research and Development (R and D) has been investigating repository concepts and retrievability in all host rocks. After introduction of retrievability in 2010, existing repository concepts were modified to facilitate retrieval. The changes made comprised, for example, equipping boreholes with steel liners, developing new technologies, and modifying existing emplacement devices. Apart from retrieval of HLW, retrieval of other wastes from underground repositories that were designed and operated without retrievability in mind, poses major technical and scientific challenges. Currently, studies are under way to investigate the feasibility and costs of partial retrieval of waste from an underground repository for hazardous and highly toxic waste in France, Stocamine. With regard to retrieval, the rock-mechanical conditions are deteriorating rapidly, so time is of the essence. In the Asse II mine in Germany, about 126,500 waste casks with low and intermediate level waste await retrieval. The repository mine suffers from difficult rock-mechanical conditions and inflow of brine, locally into emplacement areas. The Federal Company for Radioactive Waste Disposal (BGE) is legally required to retrieve all wastes from the Asse. Due to the specific challenges, R and D is needed to develop technical solutions for the safe retrieval from each of the emplacement chambers. R and D on retrievability and retrieval technology does not only address challenges in radioactive or toxic waste retrieval but may also help to germinate innovation to better master complex underground situations in general, e.g. in deep mining, tunneling, or repository construction. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2024

Intensification and Integration of Hydrogen and Ammonia Production

In this project the Colorado School of Mines developed a more efficient method for on-site and on-demand generation of high purity hydrogen from ammonia for hydrogen fueling stations. Used primarily as a fertilizer, ammonia is the world’s highest volume commodity chemical. Having 17.6% hydrogen by mass, it also shows potential as a hydrogen carrier and carbon-free fuel. The team developed new technology to generate fuel cell quality hydrogen from ammonia using a catalytic membrane reactor (CMR). In addition, during the project we pivoted to use this CMR technology for the production of NH3/H2 mixtures for use in clean combustion applications. We demonstrated that these mixtures may serve as a drop-in replacement for conventional hydrocarbons such as natural gas. This project entails development of new catalysts, new membranes, and their innovative integration. This project helped generate >$4M in follow on funding at Mines, and resulted in the formation of a clean tech startup, Blaze Energy Technologies, which has licensed IP developed in this project and is working to commercialize this technology.

08 HYDROGEN↗
NASA NTRS1998

Sixth Goddard Conference on Mass Storage Systems and Technologies Held in Cooperation with the Fifteenth IEEE Symposium on Mass Storage Systems

This document contains copies of those technical papers received in time for publication prior to the Sixth Goddard Conference on Mass Storage Systems and Technologies which is being held in cooperation with the Fifteenth IEEE Symposium on Mass Storage Systems at the University of Maryland-University College Inn and Conference Center March 23-26, 1998. As one of an ongoing series, this Conference continues to provide a forum for discussion of issues relevant to the management of large volumes of data. The Conference encourages all interested organizations to discuss long term mass storage requirements and experiences in fielding solutions. Emphasis is on current and future practical solutions addressing issues in data management, storage systems and media, data acquisition, long term retention of data, and data distribution. This year's discussion topics include architecture, tape optimization, new technology, performance, standards, site reports, vendor solutions. Tutorials will be available on shared file systems, file system backups, data mining, and the dynamics of obsolescence.

Kobler, Benjamin↗
NASA NTRS2001

Performance of Li-Ion Cells Under Battery Voltage Charge Control

A study consisting of electrochemical characterization and Low-Earth-Orbit (LEO) cycling of Li-Ion cells from three vendors was initiated in 1999 to determine the cycling performance and to infuse the new technology in the future NASA missions. The 8-cell batteries included in this evaluation are prismatic cells manufactured by Mine Safety Appliances Company (MSA), cylindrical cells manufactured by SAFT and prismatic cells manufactured by Yardney Technical Products, Inc. (YTP). The three batteries were cycle tested in the LEO regime at 40% depth of discharge, and under a charge control technique that consists of battery voltage clamp with a current taper. The initial testing was conducted at 20 C; however, the batteries were cycled also intermittently at low temperatures. YTP 20 Ah cells consisted of mixed-oxide (Co and Ni) positive, graphitic carbon negative, LIPF6 salt mixed with organic carbonate solvents. The battery voltage clamp was 32 V. The low temperature cycling tests started after 4575 cycles at 20 C. The cells were not capable of cycling. at low temperature since the charge acceptance at battery level was poor. There was a cell in the battery that showed too high an end-of-charge (EOC) voltage thereby limiting the ability to charge the rest of the cells in the battery. The battery has completed 6714 cycles. SAFT 12 Ah cells consisted of mixed-oxide (Co and NO positive, graphitic carbon negative, LiPF6 salt mixed with organic carbonate solvents. The battery voltage clamp was for 30.8 V. The low temperature cycling tests started after 4594 cycles at 20 C. A cell that showed low end of discharge (EOD) and EOC voltages and three other cells that showed higher EOC voltages limited the charge acceptance at the selected voltage limit during charge. The cells were capable of cycling at 10 C and 0 C but the charge voltage limit had to be increased to 34.3 V (4.3 V per cell). The low temperature cycling may have induced poor chargeability since the voltage had to be increased to achieve the required charge input. The battery has completed 6226 cycles. MSA 10 Ah cells consisted of Co oxide positive, graphitic carbon negative, LiPF6 salt mixed with organic carbonate solvents. The battery voltage clamp was 30.8 V. The low temperature cycling tests were started after 2182 cycles at 20 C. The cells were capable of cycling at 10 C and 0 C. Like SAFT, the voltage limit on charge had to be increased to 36 V (4.5 V per cell). There was a cell (cell S/N 13) in the battery that showed poor performance features such as low EOD voltage and high EOC voltage. The battery has completed 3441 cycles. A reconditioning procedure that consisted of C15 charge to a taper current of C/100 and C/20 discharge improved the voltage behavior of SAFT and MSA cells with no significant effect on YTP cells. We have demonstrated that the charge operation with VT clamp at battery rather than at cell level is feasible for onboard Li-Ion battery operation.

Rao, Gopalakrishna M.↗
NASA NTRS2019

Lunar Development Lab (LDL) Concept Leading to the First Human Lunar Outpost

The Lunar Development Lab (LDL) is a new concept to bring together academia, industry, non-profit organizations and NASA in an accelerator environment to generate new design solutions, technologies and architectures that will lead to the first human lunar outpost. By leveraging key partnerships in lunar science, mining, construction, chemical engineering and other key fields as well as making available rapid design, economic analysis, artificial intelligence (AI) and machine learning (ML) tools, significant progress can be made in a short amount of time. Therefore, the goal of LDL is to accelerate development and focus on economic solutions that can lead to sustainable and economical human lunar outpost.

Zuniga, Allison↗
DOE OSTI2025

System Engineers and Decisions: It?s All about Knowledge

In order to guarantee that a system meets adequate levels of reliability and availability, system performances are continuously monitored and analyzed thanks to the technological advancements driving the Industry 4.0 revolution. An Industry 4.0 approach is typically based on advanced statistical, big data mining, machine learning, and internet-of-things methods designed to detect anomalies in the behavior of system, detect the most likely failure modes, and provide indications to system engineers on when maintenance activities should be performed before system performance are deemed unacceptable (which can be generated by diagnostic and prognostic methods). However, these analyses, which are designed to automatize and increase the efficacy of the system maintenance program, require large amount of data which can come in various forms: numeric, textual, images, sounds etc. Such data constitutes the historic knowledge benchmark to track system performances and support system engineer decisions. Here we claim that data is not sufficient to support this kind of analyses when applied to systems characterized by complex architectures and behaviors. Robust system engineer decisions require the ability to understand the system operational context that lies behind the observed data elements. In this respect, system models are in fact necessary to “put data in context” and capture relationships between data elements. Industry 4.0 methods require in fact contextual knowledge as a basis upon which hypotheses can be generated and assumptions tested. In our view, for complex systems, model-based system engineering (MBSE) models can afford this contextual knowledge, as they are typically used to describe systems architecture and dynamic behaviors. System knowledge is here intended as the blending of collected data and system architecture which takes the form of a “knowledge graph”. A knowledge graph is a database which consists of a large set of nodes (in our case an entity can be either a data or an MBSE element) which are linked to each other. The types of nodes and links follow a pre-defined topology, sometimes also refers as an ontology, that is designed to fit the actual decisions that needs to be performed. We show here how a knowledge graph can be defined to support system engineer maintenance decisions and how the same graph can be built based on system MBSE models and pre-processed data from numeric (through anomaly detections and diagnostic methods) and textual elements (through technical language processing TLP).

97 - MATHEMATICS AND COMPUTING↗
DOE OSTI2026

Characterization and effects of impurities on carbonate quantification in heterogenous matrices

Mineral carbonation simulates a natural weathering phenomena by breaking down silicates and oxides to form Ca & Mg carbonates. Various mineralization methods have been demonstrated as a potential technique to improve the quality of slags and tailings through neutralization and stabilization of problematic species to yield a product better suited for use in concrete. This study aims to characterize, quantify and analyze carbonates in various carbonated products such as mineralized CaCO 3 , CO 2 mineralized Steel Slags and Mine Tailings. More than 10 samples were analyzed for carbonate measurement and verification from industrial and academic partners that pioneer commercial CO 2 mineralization technologies. The samples were characterized primarily by using X-ray diffraction (XRD), Thermogravimetric Analyses (TGA), and Scanning Electron Microscopy (SEM) to gain insights into CaCO 3 content. A baseline characterization of lab-grade CaCO 3 and MgCO 3 also revealed important considerations for CaCO 3 measurement using TGA alone. The experiments using synthetic lab-grade samples also revealed that the presence of MgCO 3 /MgO can accelerate the decomposition of CaCO 3 and thus can affect measurement parameters. Lab-grade CaCO 3 samples dosed into steel slag and mine tailing also showed significant deviation in their decomposition behavior. These insights are used to inform the development of a standardized protocol for the measurement and verification of carbonate-bearing products.

97 MATHEMATICS AND COMPUTING↗