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arxiv: 2606.05798 · v1 · pith:2LG65ZEPnew · submitted 2026-06-04 · ❄️ cond-mat.other

Beyond Critical Minerals Targets: Digital Rock Physics as Infrastructure for Secure and Circular Supply Chains

Hannah P. Menke , Alessio Scanziani , Maja R\"ucker This is my paper

Pith reviewed 2026-06-27 22:52 UTC · model grok-4.3

classification ❄️ cond-mat.other
keywords digital rock physicscritical mineralssupply chain resiliencecircular economymineral processingpore-scale modellingresource efficiencypolicy infrastructure
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The pith

Digital Rock Physics should be treated as shared policy infrastructure that links mineral textures to viable processing decisions for critical minerals.

A machine-rendered reading of the paper's core claim, the machinery that carries it, and where it could break.

The paper contends that ambitious UK and European targets for critical minerals extraction, processing, recycling, and supply resilience will remain unfulfilled without pre-competitive measurement and modelling tools that can assess which complex or marginal resources are actually workable. It positions Digital Rock Physics as the mechanism that integrates 3D imaging, correlative chemistry, AI image analysis, and pore-scale modelling to connect rock properties directly to practical choices about ore liberation, leaching, direct lithium extraction, waste valorisation, and battery recycling. If adopted as common infrastructure rather than specialist lab work, this approach would enable better characterisation of ores, brines, mine waste, and recycling feedstocks, supporting more secure, efficient, and lower-impact supply chains. The paper outlines concrete steps including translational demonstrators, training programmes, a Digital Ore Passport standard, a federated database, and integrated geo-reactive facilities to make this operational.

Core claim

Treated as shared implementation infrastructure, Digital Rock Physics can turn critical minerals strategies into practical routes for supply security, resource efficiency, circularity, and more environmentally responsible development by connecting mineral texture and reactive pathways to decisions on ore characterisation, liberation prediction, leaching, Direct Lithium Extraction, mine-waste valorisation, and battery recycling.

What carries the argument

Digital Rock Physics (DRP), the combination of three-dimensional imaging, correlative chemistry, AI-enabled image analysis, and pore-scale modelling that connects mineral texture and reactive pathways to processing viability.

If this is right

  • DRP enables determination of which prospective regional resources can be processed viably and with lower environmental impact.
  • Implementation of the EU Critical Raw Materials Act and UK Vision 2035 depends on this kind of pre-competitive data infrastructure in addition to permitting reforms.
  • A UK-European policy agenda built on translational demonstrators, cross-disciplinary training, a Digital Ore Passport standard, a federated Digital Ore Database, and integrated geo-reactive end stations follows directly.
  • Adoption supports supply security, resource efficiency, circularity, and environmentally responsible development for complex or historically worked resources.

Where Pith is reading between the lines

These are editorial extensions of the paper, not claims the author makes directly.

  • Standardising DRP outputs across borders could reduce duplication in national resource assessments.
  • The same infrastructure might later extend to predictive screening of emerging recycling chemistries before pilot investment.
  • Policy prioritisation of DRP end stations could shift research funding toward integrated imaging-modelling workflows rather than isolated techniques.

Load-bearing premise

Combining three-dimensional imaging, correlative chemistry, AI image analysis, and pore-scale modelling can reliably connect mineral textures and reactive pathways to viable processing decisions for ores, brines, waste streams, and recycling feedstocks.

What would settle it

A set of blind tests on real ore and waste samples where DRP-derived predictions of processing outcomes diverge substantially from measured laboratory or pilot-scale results.

Figures

Figures reproduced from arXiv: 2606.05798 by Alessio Scanziani, Hannah P. Menke, Maja R\"ucker.

Figure 1
Figure 1. Figure 1: Integrated Digital Rock Physics workflow for critical-mineral systems. Static [PITH_FULL_IMAGE:figures/full_fig_p005_1.png] view at source ↗
Figure 2
Figure 2. Figure 2: Digital Rock Physics contributions across the critical-minerals value chain. Top [PITH_FULL_IMAGE:figures/full_fig_p006_2.png] view at source ↗
Figure 3
Figure 3. Figure 3: Proposed implementation roadmap for a UK-European critical-minerals DRP [PITH_FULL_IMAGE:figures/full_fig_p015_3.png] view at source ↗
read the original abstract

The United Kingdom and Europe are moving rapidly from critical minerals target-setting to implementation. The EU Critical Raw Materials Act and the UK's Vision 2035 create ambitious benchmarks for domestic extraction, processing, recycling, circularity, and supply-chain resilience, but many prospective regional resources remain complex, under-explored, historically worked, or economically marginal. This paper argues that implementation will depend not only on permitting reform and project designation, but also on pre-competitive measurement, modelling, and data infrastructure capable of determining which ores, brines, waste streams, and recycling feedstocks can be processed viably and with lower environmental impact. Digital Rock Physics (DRP) should therefore be understood as enabling infrastructure for resource policy rather than as a specialist laboratory method alone. By combining three-dimensional imaging, correlative chemistry, AI-enabled image analysis, and pore-scale modelling, DRP can connect mineral texture and reactive pathways to decisions about ore characterisation, liberation prediction, leaching, Direct Lithium Extraction, mine-waste valorisation, and battery recycling. The paper sets out a UK-European policy agenda built around translational demonstrators, cross-disciplinary training, a Digital Ore Passport standard, a federated Digital Ore Database, and integrated geo-reactive end stations. Treated as shared implementation infrastructure, DRP could help turn critical minerals strategies into practical routes for supply security, resource efficiency, circularity, and more environmentally responsible development.

Editorial analysis

A structured set of objections, weighed in public.

Desk editor's note, referee report, simulated authors' rebuttal, and a circularity audit. Tearing a paper down is the easy half of reading it; the pith above is the substance, this is the friction.

Referee Report

2 major / 1 minor

Summary. The manuscript argues that Digital Rock Physics (DRP) should be treated as shared pre-competitive infrastructure for implementing UK and EU critical minerals policies. By combining three-dimensional imaging, correlative chemistry, AI-enabled image analysis, and pore-scale modelling, DRP can link mineral textures and reactive pathways to viable processing decisions for ores, brines, waste streams, and recycling feedstocks. It outlines a policy agenda of translational demonstrators, cross-disciplinary training, a Digital Ore Passport standard, a federated Digital Ore Database, and integrated geo-reactive end stations to advance supply security, resource efficiency, circularity, and lower environmental impact.

Significance. If the claimed connectivity between DRP techniques and processing decisions can be established, the work could help reframe DRP as policy-relevant infrastructure rather than a specialist method, potentially guiding public investment in data standards and facilities for critical minerals implementation.

major comments (2)
  1. [Abstract] Abstract: The central assertion that DRP 'can connect mineral texture and reactive pathways to decisions about ore characterisation, liberation prediction, leaching, Direct Lithium Extraction, mine-waste valorisation, and battery recycling' is advanced without any cited studies, datasets, or methodological examples demonstrating such connections; this connectivity is load-bearing for the claim that DRP constitutes enabling infrastructure.
  2. [Abstract] Abstract (policy agenda paragraph): The proposals for a 'Digital Ore Passport standard' and 'federated Digital Ore Database' are presented without discussion of technical requirements, interoperability challenges, or validation approaches, leaving the implementation pathway unspecified despite its role in the overall argument.
minor comments (1)
  1. The manuscript introduces several new terms (e.g., 'Digital Ore Passport', 'geo-reactive end stations') without providing concise definitions or references to analogous existing standards.

Simulated Author's Rebuttal

2 responses · 0 unresolved

We thank the referee for the constructive feedback, which highlights opportunities to strengthen the evidentiary grounding and implementation clarity of the manuscript. We address each major comment below.

read point-by-point responses

  1. Referee: [Abstract] Abstract: The central assertion that DRP 'can connect mineral texture and reactive pathways to decisions about ore characterisation, liberation prediction, leaching, Direct Lithium Extraction, mine-waste valorisation, and battery recycling' is advanced without any cited studies, datasets, or methodological examples demonstrating such connections; this connectivity is load-bearing for the claim that DRP constitutes enabling infrastructure.

    Authors: The referee is correct that the abstract advances this connectivity without inline citations. The full manuscript develops the argument by reference to established DRP literature on texture-reactivity linkages, but the abstract itself does not. We will revise the abstract to incorporate 1-2 representative citations (e.g., studies on AI-enabled liberation prediction and pore-scale reactive transport) so that the load-bearing claim is explicitly supported. revision: yes

  2. Referee: [Abstract] Abstract (policy agenda paragraph): The proposals for a 'Digital Ore Passport standard' and 'federated Digital Ore Database' are presented without discussion of technical requirements, interoperability challenges, or validation approaches, leaving the implementation pathway unspecified despite its role in the overall argument.

    Authors: We agree that the policy proposals are presented at a strategic level without technical detail on requirements or challenges. This is consistent with the manuscript's scope as a policy-position paper rather than a standards-development document. To respond to the comment, we will add a short paragraph in the policy-agenda section that flags key issues (data interoperability, validation via demonstrators, and governance) while noting that detailed technical specifications lie outside the present work. revision: partial

Circularity Check

0 steps flagged

No significant circularity

full rationale

The manuscript is a qualitative policy position paper with no equations, derivations, fitted parameters, predictions, or technical modeling steps. Its claims are forward-looking recommendations about DRP as infrastructure; none reduce by construction to inputs, self-citations, or ansatzes. The argument is self-contained as advocacy and does not invoke load-bearing uniqueness theorems or renamed empirical patterns.

Axiom & Free-Parameter Ledger

0 free parameters · 0 axioms · 0 invented entities

The paper is a policy perspective with no mathematical content. Its claims rest on unstated domain assumptions about DRP effectiveness rather than explicit axioms or parameters.

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Reference graph

Works this paper leans on

76 extracted references · 37 canonical work pages

  1. [1]

    A Benchmark Dataset for Machine Learning Surrogates of Pore-Scale CO 2-Water Interaction,

    Abdellatif, A., Menke, H.P., Maes, J., Elsheikh, A.H., & Doster, F., “A Benchmark Dataset for Machine Learning Surrogates of Pore-Scale CO 2-Water Interaction,” Scientific Data, 2026. DOI:https://doi.org/10.1038/s41597-025-05794-z

    work page doi:10.1038/s41597-025-05794-z 2026

  2. [2]

    Department of Energy, August 2025.https://arpa-e.e nergy.gov/sites/default/files/2025-09/ARPA-E%20FY%202023%20Annual%20 Report.pdf

    Advanced Research Projects Agency-Energy (ARPA-E),ARPA-E FY 2023 Annual Report to Congress, U.S. Department of Energy, August 2025.https://arpa-e.e nergy.gov/sites/default/files/2025-09/ARPA-E%20FY%202023%20Annual%20 Report.pdf

    2023

  3. [3]

    Mapping Critical Raw Materials (CRM) hard rock deposits in Europe,

    Albert, C., Bertrand, G., Berthier, H., de Oliveira, D.P.S., & Tulstrup, J., “Mapping Critical Raw Materials (CRM) hard rock deposits in Europe,”Advances in Geo- sciences, 67, 45–55, 2025. DOI:https://doi.org/10.5194/adgeo-67-45-2025. 17

    work page doi:10.5194/adgeo-67-45-2025 2025

  4. [4]

    Towards mine tailings valorization: Recovery of critical materials from Chilean mine tailings,

    Araya, N., Kraslawski, A., & Cisternas, L.A., “Towards mine tailings valorization: Recovery of critical materials from Chilean mine tailings,”Journal of Cleaner Pro- duction, 263, 121555, 2020. DOI:https://doi.org/10.1016/j.jclepro.2020.1 21555

    work page doi:10.1016/j.jclepro.2020.1 2020

  5. [5]

    Mi- croporous Polymer Sorbents for Direct Lithium Extraction,

    Baird, E.J., Kingsbury, R.S., Wang, X., Gang, O., Zhu, Y., & Whittaker, M.L., “Mi- croporous Polymer Sorbents for Direct Lithium Extraction,”ACS Energy Letters, 9(9), 4229–4237, 2024. DOI:https://doi.org/10.1021/acsenergylett.4c01590

    work page doi:10.1021/acsenergylett.4c01590 2024

  6. [6]

    Fast X-Ray Micro-CT Study of the Impact of Brine Salinity on the Pore-Scale Fluid Distribution During Waterflooding,

    Bartels, W.-B., Lin, Q., de Winter, D.A.M., Mahani, H., Berg, S., Cnudde, V., & Ajo-Franklin, J.B., “Fast X-Ray Micro-CT Study of the Impact of Brine Salinity on the Pore-Scale Fluid Distribution During Waterflooding,”Petrophysics, 58(1), 36–47, 2017

    2017

  7. [7]

    The contribution of applied mineralogy to sustainability in the mine life cycle,

    Becker, M., “The contribution of applied mineralogy to sustainability in the mine life cycle,”Minerals Engineering, 202, 108121, 2023. DOI:https://doi.org/10.1 016/j.mineng.2023.108121

    arXiv 2023

  8. [8]

    From interface dynamics to Darcy scale description of multiphase flow in porous media,

    Berg, S., Armstrong, R.T., R¨ ucker, M., Hansen, A., Kjelstrup, S., & Bedeaux, D., “From interface dynamics to Darcy scale description of multiphase flow in porous media,”Advances in Colloid and Interface Science, 351, 103791, 2026. DOI:https: //doi.org/10.1016/j.cis.2026.103791

    work page doi:10.1016/j.cis.2026.103791 2026

  9. [9]

    Pore-scale imaging and modelling,

    Blunt, M.J., Bijeljic, B., Dong, H., Gharbi, O., Iglauer, S., Mostaghimi, P., Paluszny, A., & Pentland, C., “Pore-scale imaging and modelling,”Advances in Water Re- sources, 51, 197–216, 2013. DOI:https://doi.org/10.1016/j.advwatres.2012.0 3.003

    work page doi:10.1016/j.advwatres.2012.0 2013

  10. [10]

    Applied Machine Learning for Geometallurgical Throughput Prediction: A Case Study Using Production Data at the Tropicana Gold Mining Complex,

    Both, C., & Dimitrakopoulos, R., “Applied Machine Learning for Geometallurgical Throughput Prediction: A Case Study Using Production Data at the Tropicana Gold Mining Complex,”Minerals, 11(11), 1257, 2021. DOI:https://doi.org/10 .3390/min11111257

    2021

  11. [11]

    Report identifies areas of the UK prospective for critical raw materials,

    British Geological Survey, “Report identifies areas of the UK prospective for critical raw materials,” 2022.https://www.bgs.ac.uk/news/report-identifies-areas -of-the-uk-prospective-for-critical-raw-materials/. Accessed March 24, 2026

    2022

  12. [12]

    Combining Automated Miner- alogy with X-ray Computed Tomography for Internal Characterization of Ore Sam- ples at the Microscopic Scale,

    Buyse, F., Dewaele, S., Boone, M.N., & Cnudde, V., “Combining Automated Miner- alogy with X-ray Computed Tomography for Internal Characterization of Ore Sam- ples at the Microscopic Scale,”Natural Resources Research, 32(2), 461–478, 2023. DOI:https://doi.org/10.1007/s11053-023-10161-z

    work page doi:10.1007/s11053-023-10161-z 2023

  13. [13]

    Decreasing Ore Grades in Global Metallic Mining: A Theoretical Issue or a Global Reality?,

    Calvo, G., Mudd, G., Valero, A., & Valero, A., “Decreasing Ore Grades in Global Metallic Mining: A Theoretical Issue or a Global Reality?,”Resources, 5(4), 36,

  14. [14]

    DOI:https://doi.org/10.3390/resources5040036

    work page doi:10.3390/resources5040036

  15. [15]

    X-ray micro CT and nano CT research LAB,

    CEITEC, “X-ray micro CT and nano CT research LAB,”https://www.ceitec .eu/x-ray-micro-ct-and-nano-ct-research-lab/t9853. Accessed March 27, 2026. 18

    2026

  16. [16]

    Metal-organic frameworks for extraction of radionu- clide/noble metals/lithium,

    Cao, X., Gao, H., & Zeng, Y., “Metal-organic frameworks for extraction of radionu- clide/noble metals/lithium,” inMetal Organic Frameworks for Energy and Environ- mental Applications, 13–33, 2026. DOI:https://doi.org/10.1016/B978-0-443-4 0377-4.00002-1

    work page doi:10.1016/b978-0-443-4 2026

  17. [17]

    Critical Materials Innovation Hub (CMI),

    Department of Energy, “Critical Materials Innovation Hub (CMI),”https://www. energy.gov/eere/ammto/critical-materials-institute-energy-innovatio n-hub. Accessed March 26, 2026

    2026

  18. [18]

    Project Selection for Critical Materials Supply Chain Re- search Facility,

    Department of Energy, “Project Selection for Critical Materials Supply Chain Re- search Facility,”https://www.energy.gov/fecm/project-selection-critica l-materials-supply-chain-research-facility. Accessed March 26, 2026

    2026

  19. [19]

    U.S. Department of Energy Launches Mine of the Future Initiatives to Bolster the U.S. Mining Industry,

    Department of Energy, “U.S. Department of Energy Launches Mine of the Future Initiatives to Bolster the U.S. Mining Industry,” September 26, 2025.https://ww w.energy.gov/fecm/articles/us-department-energy-launches-mine-futur e-initiatives-bolster-us-mining-industry. Accessed March 26, 2026

    2025

  20. [20]

    U.S. Department of Energy Invests$45 Million to Support Regional Consortia Focused on Securing Domestic Critical Minerals and Materials,

    Department of Energy, “U.S. Department of Energy Invests$45 Million to Support Regional Consortia Focused on Securing Domestic Critical Minerals and Materials,” January 6, 2025.https://www.energy.gov/hgeo/articles/us-department-ene rgy-invests-45-million-support-regional-consortia-focused-securing. Accessed March 26, 2026

    2025

  21. [21]

    Welcome to DIAD,

    Diamond Light Source, “Welcome to DIAD,”https://www.diamond.ac.uk/Inst ruments/Imaging-and-Microscopy/DIAD.html. Accessed March 25, 2026

    2026

  22. [22]

    XRF Beamlines for Industry,

    Diamond Light Source, “XRF Beamlines for Industry,”https://www.diamond.ac .uk/industry/Techniques-Available/Spectroscopy/X-ray-Fluorescence-XRF /XRF-beamlines.html. Accessed March 25, 2026

    2026

  23. [23]

    NIKON XT H 225/320 LC Computer Tomography, University of Strathclyde,

    ECCSEL ERIC, “NIKON XT H 225/320 LC Computer Tomography, University of Strathclyde,” Facility catalogue,https://eccsel.eu/catalogue/facility/?id=1

  24. [24]

    Accessed March 27, 2026

    2026

  25. [25]

    EGDI – European Geological Data Infrastructure,

    EuroGeoSurveys, “EGDI – European Geological Data Infrastructure,”https://eu rogeosurveys.org/projects/egdi/. Accessed March 24, 2026

    2026

  26. [26]

    Map of Critical Raw Material Deposits in Europe,

    EuroGeoSurveys, “Map of Critical Raw Material Deposits in Europe,” 2016, updated online.https://eurogeosurveys.org/egs-publications/map-of-critical-raw -material-deposits-in-europe/. Accessed March 24, 2026

    2016

  27. [27]

    The two wide maps data sets of EuroGeoSurveys,

    EuroGeoSurveys, “The two wide maps data sets of EuroGeoSurveys,” including the lithium mineralization map of Europe, 2020.https://eurogeosurveys.org/the-t wo-wide-maps-data-sets-of-eurogeosurveys/. Accessed March 24, 2026

    2020

  28. [28]

    The European Critical Raw Materials Board,

    European Commission, “The European Critical Raw Materials Board,”https:// single-market-economy.ec.europa.eu/sectors/raw-materials/areas-speci fic-interest/critical-raw-materials/critical-raw-materials-act/board _en. Accessed March 24, 2026. 19

    2026

  29. [29]

    Selected strategic projects under CRMA,

    European Commission, “Selected strategic projects under CRMA,”https://sing le-market-economy.ec.europa.eu/sectors/raw-materials/areas-specific-i nterest/critical-raw-materials/strategic-projects-under-crma/selected -projects_en. Accessed March 26, 2026

    2026

  30. [30]

    Recycling of end of life battery packs for domestic raw material supply chains and enhanced circular economy (BATRAW),

    European Commission CORDIS, “Recycling of end of life battery packs for domestic raw material supply chains and enhanced circular economy (BATRAW),” Project ID 101058359.https://cordis.europa.eu/project/id/101058359. Accessed March 24, 2026

    arXiv 2026

  31. [31]

    RMIS – Raw Materials Information System,

    European Commission Joint Research Centre, “RMIS – Raw Materials Information System,”https://rmis.jrc.ec.europa.eu/. Accessed March 24, 2026

    2026

  32. [32]

    European Battery HUB (Eu- Bat),

    European Synchrotron Radiation Facility (ESRF), “European Battery HUB (Eu- Bat),”https://www.esrf.fr/HUB/EuBattery. Accessed March 25, 2026

    2026

  33. [33]

    ID16B - Nano-analysis Beam- line,

    European Synchrotron Radiation Facility (ESRF), “ID16B - Nano-analysis Beam- line,”https://www.esrf.fr/UsersAndScience/Experiments/ID16B. Accessed March 25, 2026

    2026

  34. [34]

    ID26 - X-ray absorption and emission spectroscopy,

    European Synchrotron Radiation Facility (ESRF), “ID26 - X-ray absorption and emission spectroscopy,”https://www.esrf.fr/UsersAndScience/Experiments/ ID26. Accessed March 25, 2026

    2026

  35. [35]

    Materials Chemistry - EH3,

    European Synchrotron Radiation Facility (ESRF), “Materials Chemistry - EH3,” https://www.esrf.fr/home/UsersAndScience/Experiments/ID15A/materials -chemistry--eh3.html. Accessed March 25, 2026

    2026

  36. [36]

    European Union, “Regulation (EU) 2024/1252 of the European Parliament and of the Council of 11 April 2024 establishing a framework for ensuring a secure and sustainable supply of critical raw materials,”Official Journal of the European Union, 2024.https://eur-lex.europa.eu/eli/reg/2024/1252/oj/eng

    2024

  37. [37]

    Facility access,

    EXCITE Network, “Facility access,”https://excite-network.eu/access/tna-p ortal/. Accessed March 27, 2026

    2026

  38. [38]

    Magnetic resonance imaging characterisation of the influence of flowrate on liquid distribution in drip irrigated heap leaching,

    Fagan-Endres, M.A., Harrison, S.T.L., Johns, M.L., & Sederman, A.J., “Magnetic resonance imaging characterisation of the influence of flowrate on liquid distribution in drip irrigated heap leaching,”Hydrometallurgy, 157, 116–124, 2015. DOI:https: //doi.org/10.1016/j.hydromet.2015.10.003

    work page doi:10.1016/j.hydromet.2015.10.003 2015

  39. [39]

    Porous materials: The next frontier in energy technologies,

    Farber, E.M., Seraphim, N.M., Tamakuwala, K., Stein, A., R¨ ucker, M., & Eisenberg, D., “Porous materials: The next frontier in energy technologies,”Science, 387(6730), eadn9391, 2025. DOI:https://doi.org/10.1126/science.adn9391

    work page doi:10.1126/science.adn9391 2025

  40. [40]

    Experimental Study on the Effect of Pretreatment with High-Voltage Electrical Pulses on Mineral Libera- tion and Separation of Magnetite Ore,

    Gao, P., Yuan, S., Han, Y., Li, Y., & Chen, H., “Experimental Study on the Effect of Pretreatment with High-Voltage Electrical Pulses on Mineral Libera- tion and Separation of Magnetite Ore,”Minerals, 7(9), 153, 2017. DOI:https: //doi.org/10.3390/min7090153. 20

    work page doi:10.3390/min7090153 2017

  41. [41]

    Determination of the spatial distribution of wetting in the pore networks of rocks,

    Garfi, G., John, C.M., R¨ ucker, M., Lin, Q., Spurin, C., Berg, S., & Krevor, S., “Determination of the spatial distribution of wetting in the pore networks of rocks,” Journal of Colloid and Interface Science, 613, 786–795, 2022. DOI:https://doi. org/10.1016/j.jcis.2021.12.183

    work page doi:10.1016/j.jcis.2021.12.183 2022

  42. [42]

    Predicting porosity, permeability, and tortuosity of porous media from images by deep learning,

    Graczyk, K.M., & Matyka, M., “Predicting porosity, permeability, and tortuosity of porous media from images by deep learning,”Scientific Reports, 10, 21459, 2020. DOI:https://doi.org/10.1038/s41598-020-78415-x

    work page doi:10.1038/s41598-020-78415-x 2020

  43. [43]

    The value of automated mineralogy,

    Gu, Y., Schouwstra, R.P., & Rule, C., “The value of automated mineralogy,”Min- erals Engineering, 58, 100–103, 2014. DOI:https://doi.org/10.1016/j.mineng .2014.01.020

    work page doi:10.1016/j.mineng 2014

  44. [45]

    HM Government,Resilience for the Future: The UK’s Critical Minerals Strategy, London, 2022.https://www.gov.uk/government/publications/uk-critical-m ineral-strategy

    2022

  45. [46]

    Accessed March 26, 2026

    HM Government,Vision 2035: Critical Minerals Strategy, London, updated 23 Jan- uary 2026.https://www.gov.uk/government/publications/uk-critical-miner als-strategy/vision-2035-critical-minerals-strategy. Accessed March 26, 2026

    2035

  46. [47]

    International Energy Agency (IEA),Global Critical Minerals Outlook 2025, IEA, Paris, 2025.https://www.iea.org/reports/global-critical-minerals-outlo ok-2025

    2025

  47. [48]

    Critical Minerals and Materials Recovery Tech- nology Collaboration Programme (CMMR TCP),

    International Energy Agency (IEA), “Critical Minerals and Materials Recovery Tech- nology Collaboration Programme (CMMR TCP),”Technology Collaboration Pro- gramme: Cross-cutting, 2026.https://www.iea.org/programmes/technology-c ollaboration-programme/cross-cutting. Accessed May 24, 2026

    2026

  48. [49]

    Subsur- face hydrogen storage controlled by small-scale rock heterogeneities,

    Jangda, Z., Menke, H., Busch, A., Geiger, S., Bultreys, T., & Singh, K., “Subsur- face hydrogen storage controlled by small-scale rock heterogeneities,”International Journal of Hydrogen Energy, 72, 467–482, 2024. DOI:https://doi.org/10.1016/ j.ijhydene.2024.02.233

    2024

  49. [50]

    2021 Physics-informed machine learning.Nature Reviews Physics3, 422–440

    Karniadakis, G.E., Kevrekidis, I.G., Lu, L., Perdikaris, P., Wang, S., & Yang, L., “Physics-informed machine learning,”Nature Reviews Physics, 3, 422–440, 2021. DOI:https://doi.org/10.1038/s42254-021-00314-5

    work page doi:10.1038/s42254-021-00314-5 2021

  50. [51]

    Automated drill core mineralogical characterization method for texture classification and modal mineralogy estima- tion for geometallurgy,

    Koch, P.H., Lund, C., & Rosenkranz, J., “Automated drill core mineralogical characterization method for texture classification and modal mineralogy estima- tion for geometallurgy,”Minerals Engineering, 136, 99–110, 2019. DOI:https: //doi.org/10.1016/j.mineng.2019.03.008. 21

    work page doi:10.1016/j.mineng.2019.03.008 2019

  51. [52]

    Application of high resolution X-ray computed to- mography to mineral deposit origin, evaluation, and processing,

    Kyle, J.R., & Ketcham, R.A., “Application of high resolution X-ray computed to- mography to mineral deposit origin, evaluation, and processing,”Ore Geology Re- views, 65, 821–839, 2015. DOI:https://doi.org/10.1016/j.oregeorev.2014.0 9.034

    work page doi:10.1016/j.oregeorev.2014.0 2015

  52. [53]

    Towards integrated geometallurgical approach: Critical review of current practices and future trends,

    Lishchuk, V., Koch, P.H., Ghorbani, Y., & Butcher, A.R., “Towards integrated geometallurgical approach: Critical review of current practices and future trends,” Minerals Engineering, 145, 106072, 2020. DOI:https://doi.org/10.1016/j.mine ng.2019.106072

    work page doi:10.1016/j.mine 2020

  53. [54]

    Evaluation and comparison of different machine-learning methods to integrate sparse process data into a spatial model in geometallurgy,

    Lishchuk, V., Lund, C., & Ghorbani, Y., “Evaluation and comparison of different machine-learning methods to integrate sparse process data into a spatial model in geometallurgy,”Minerals Engineering, 138, 144–153, 2019. DOI:https://doi.or g/10.1016/j.mineng.2019.01.032

    work page doi:10.1016/j.mineng.2019.01.032 2019

  54. [55]

    GeoChemFoam: Direct Modelling of Multiphase Reac- tive Transport in Real Pore Geometries with Equilibrium Reactions,

    Maes, J., & Menke, H.P., “GeoChemFoam: Direct Modelling of Multiphase Reac- tive Transport in Real Pore Geometries with Equilibrium Reactions,”Transport in Porous Media, 139, 271–299, 2021. DOI:https://doi.org/10.1007/s11242-021 -01661-8

    work page doi:10.1007/s11242-021 2021

  55. [56]

    Permanent Carbon Dioxide Storage into Basalt: The CarbFix Pilot Project, Iceland,

    Matter, J.M., Broecker, W.S., Stute, M., Gislason, S.R., Oelkers, E.H., Stefansson, A.,et al., “Permanent Carbon Dioxide Storage into Basalt: The CarbFix Pilot Project, Iceland,”Energy Procedia, 1(1), 3641–3646, 2009. DOI:https://doi.org/ 10.1016/j.egypro.2009.02.160

    work page doi:10.1016/j.egypro.2009.02.160 2009

  56. [57]

    Beamlines,

    MAX IV Laboratory, “Beamlines,” including proposed SpectroWISE and Tomo- WISE beamlines,https://www.maxiv.lu.se/beamlines-accelerators/beamli nes/. Accessed March 25, 2026

    2026

  57. [58]

    Multimodal in-situ XAS-XRD,

    MAX IV Laboratory, “Multimodal in-situ XAS-XRD,”https://www.maxiv.lu.s e/beamlines-accelerators/beamlines/balder/experimental-station/multi modal-in-situ-xas-xrd/. Accessed March 25, 2026

    2026

  58. [59]

    Dynamic Three- Dimensional Pore-Scale Imaging of Reaction in a Carbonate at Reservoir Condi- tions,

    Menke, H.P., Bijeljic, B., Andrew, M.G., & Blunt, M.J., “Dynamic Three- Dimensional Pore-Scale Imaging of Reaction in a Carbonate at Reservoir Condi- tions,”Environmental Science & Technology, 49(7), 4407–4414, 2015. DOI:https: //doi.org/10.1021/es505789f

    work page doi:10.1021/es505789f 2015

  59. [60]

    Machine learn- ing for sustainable geoenergy: uncertainty, physics and decision-ready inference,

    Menke, H.P., Elsheikh, A.H., Wei, L., Wang, N., & Busch, A., “Machine learn- ing for sustainable geoenergy: uncertainty, physics and decision-ready inference,” arXiv:2603.14907, 2026. DOI:https://doi.org/10.48550/arXiv.2603.14907

    work page doi:10.48550/arxiv.2603.14907 2026

  60. [61]

    Upscaling the porosity-permeability rela- tionship of a microporous carbonate for Darcy-scale flow with machine learning,

    Menke, H.P., Maes, J., & Geiger, S., “Upscaling the porosity-permeability rela- tionship of a microporous carbonate for Darcy-scale flow with machine learning,” Scientific Reports, 11(1), 2625, 2021. DOI:https://doi.org/10.1038/s41598-0 21-82029-2

    work page doi:10.1038/s41598-0 2021

  61. [62]

    A review on advances in direct lithium ex- traction from continental brines: Ion-sieve adsorption and electrochemical methods for varied Mg/Li ratios,

    Mojid, R.A., Lee, M.-G., & You, J.-K., “A review on advances in direct lithium ex- traction from continental brines: Ion-sieve adsorption and electrochemical methods for varied Mg/Li ratios,”Sustainable Materials and Technologies, 41, e00923, 2024. DOI:https://doi.org/10.1016/j.susmat.2024.e00923. 22

    work page doi:10.1016/j.susmat.2024.e00923 2024

  62. [63]

    Digital Porous Media Portal (DPMP) for Publication, Analysis, and Simulation of Porous Media Images,

    Prodanovic, M., Esteva, M., Ketcham, R., Chang, B., Turhan, C., Gentle, J., Khan, S., & Belcher, V., “Digital Porous Media Portal (DPMP) for Publication, Analysis, and Simulation of Porous Media Images,”Digital Porous Media Portal, 2025. DOI: https://doi.org/10.17612/FGMN-D889. Repository note: the Digital Rocks Portal has been re-branded as the Digital P...

    work page doi:10.17612/fgmn-d889 2025

  63. [64]

    Energy and greenhouse gas impacts of mining and mineral processing operations,

    Norgate, T., & Haque, N., “Energy and greenhouse gas impacts of mining and mineral processing operations,”Journal of Cleaner Production, 18(3), 266–274, 2010. DOI:https://doi.org/10.1016/j.jclepro.2009.09.020

    work page doi:10.1016/j.jclepro.2009.09.020 2010

  64. [65]

    Valorisation of mine waste - Part II: Resource evaluation for consolidated and mineralised mine waste using the Central African Copperbelt as an exam- ple,

    Nwaila, G.T., Ghorbani, Y., Zhang, S.-E., Tolmay, V., Rose, D.H., & Nwaila, N.G., “Valorisation of mine waste - Part II: Resource evaluation for consolidated and mineralised mine waste using the Central African Copperbelt as an exam- ple,”Journal of Environmental Management, 288, 113553, 2021. DOI:https: //doi.org/10.1016/j.jenvman.2021.113553

    work page doi:10.1016/j.jenvman.2021.113553 2021

  65. [66]

    Beamline Information — BL: SLS/TOMCAT,

    Paul Scherrer Institute (PSI), “Beamline Information — BL: SLS/TOMCAT,”ht tps://www.psi.ch/de/sls/tomcat/beamlines. Accessed March 24, 2026

    2026

  66. [67]

    A Review of Sensor-Based Sorting in Mineral Processing: The Potential Benefits of Sensor Fusion,

    Peukert, W., Xu, Z., & Dowd, P.A., “A Review of Sensor-Based Sorting in Mineral Processing: The Potential Benefits of Sensor Fusion,”Minerals, 12(11), 1364, 2022. DOI:https://doi.org/10.3390/min12111364

    work page doi:10.3390/min12111364 2022

  67. [68]

    Digital Rocks Portal (Digital Porous Media): Connecting data, simulation and community,

    Prodanovi´ c, M., Esteva, M., McClure, J., Chang, B.C., Santos, M., Radhakrishnan, S.,et al., “Digital Rocks Portal (Digital Porous Media): Connecting data, simulation and community,”E3S Web of Conferences, 367, 01010, 2023. DOI:https://doi. org/10.1051/e3sconf/202336701010

    work page doi:10.1051/e3sconf/202336701010 2023

  68. [69]

    Critical Minerals,

    Reich, M., & Simon, A.C., “Critical Minerals,”Annual Review of Earth and Plan- etary Sciences, 53, 149–177, 2025. DOI:https://doi.org/10.1146/annurev-ear th-040523-023316

    work page doi:10.1146/annurev-ear 2025

  69. [70]

    Recovery of strategically important critical minerals from mine tailings,

    Sarker, P.K., Haque, N., Bhuiyan, M.A.H., Bruckard, W., & Pramanik, B.K., “Recovery of strategically important critical minerals from mine tailings,”Jour- nal of Environmental Chemical Engineering, 10(3), 107622, 2022. DOI:https: //doi.org/10.1016/j.jece.2022.107622

    work page doi:10.1016/j.jece.2022.107622 2022

  70. [71]

    NXCT at the Henry Moseley X-ray Imaging Facility,

    University of Manchester, “NXCT at the Henry Moseley X-ray Imaging Facility,” Research Explorer,https://research.manchester.ac.uk/en/equipments/nxct -at-the-henry-moseley-x-ray-imaging-facility/. Accessed March 27, 2026

    2026

  71. [72]

    The UCL Centre for Correlative X-ray Microscopy,

    University College London, “The UCL Centre for Correlative X-ray Microscopy,” https://www.ucl.ac.uk/engineering/chemical-engineering/research/cros s-disciplinary-centres/ucl-electrochemical-innovation-lab/ucl-centr e-correlative-x-ray-microscopy. Accessed March 27, 2026

    2026

  72. [73]

    Mineral liberation by 3D X-ray microtomography and SEM-based image analysis in low-grade iron ores with different mineralogy and tex- ture,

    Uliana, D., & Ulsen, C., “Mineral liberation by 3D X-ray microtomography and SEM-based image analysis in low-grade iron ores with different mineralogy and tex- ture,”Minerals Engineering, 222, 109150, 2025. DOI:https://doi.org/10.1016/ j.mineng.2024.109150. 23

    arXiv 2025

  73. [74]

    Automated mineralogy as a novel approach for the compositional and textural characterization of spent lithium-ion batteries,

    Vanderbruggen, A., Gugala, E., Blannin, R., Bachmann, K., Serna-Guerrero, R., & Rudolph, M., “Automated mineralogy as a novel approach for the compositional and textural characterization of spent lithium-ion batteries,”Minerals Engineering, 169, 106924, 2021. DOI:https://doi.org/10.1016/j.mineng.2021.106924

    work page doi:10.1016/j.mineng.2021.106924 2021

  74. [75]

    Artificial intelligence for mineral exploration: A review and perspectives on future directions from data science,

    Yang, L., Zuo, R., & Kreuzer, O.P., “Artificial intelligence for mineral exploration: A review and perspectives on future directions from data science,”Earth-Science Reviews, 255, 104941, 2024. DOI:https://doi.org/10.1016/j.earscirev.2024 .104941

    work page doi:10.1016/j.earscirev.2024 2024

  75. [76]

    Upscaling reactive transport models from pore-scale to continuum-scale using deep learning method,

    You, J., & Lee, K.J., “Upscaling reactive transport models from pore-scale to continuum-scale using deep learning method,”Geoenergy Science and Engineering, 242, 212850, 2024. DOI:https://doi.org/10.1016/j.geoen.2024.212850

    work page doi:10.1016/j.geoen.2024.212850 2024

  76. [77]

    Support vector machine: A tool for mapping mineral prospectivity,

    Zuo, R., & Carranza, E.J.M., “Support vector machine: A tool for mapping mineral prospectivity,”Computers & Geosciences, 37(12), 1967–1975, 2011. DOI:https: //doi.org/10.1016/j.cageo.2010.09.014. 24

    work page doi:10.1016/j.cageo.2010.09.014 1967