The CRM-geothermal database was created within the Horizon Europe CRM-geothermal project (Grant Agreement No. 101058163) to support the assessment of geothermal systems as sources of both renewable energy and critical raw materials (CRMs). The primary purpose of data collection was to compile, harmonise, and make openly available geoscientific and geochemical data relevant to the occurrence, enrichment, and potential co-production of CRMs from geothermal environments in Europe and East Africa.
The database integrates legacy data compiled from peer-reviewed literature, national geological and geothermal databases, and previous European research projects (notably REFLECT), together with new data generated by project partners through field sampling and laboratory analyses. Sampling campaigns targeted geothermal wells and surface manifestations in selected regions, including Türkiye, the East African Rift (Kenya, Tanzania, Malawi), Cornwall (UK), and Iceland. Laboratory analyses include major ion chemistry, trace and critical element concentrations, mineralogical composition, and gas data, determined using methods such as ICP-MS, XRF, and XRD.
All records were harmonised using a unified metadata schema, standardised units, and consistent reporting formats. Quality control involved automated validation routines and manual expert review. Each record includes spatial coordinates, sampling context, analytical method, references, and a quality flag indicating data origin and traceability.
The database is provided as a structured Excel file and contains interconnected datasets on geothermal wells, fluids, rocks, gases, and mineral precipitates. In total, the dataset comprises 9,773 records covering a wide range of geological settings, from volcanic and metamorphic systems to sedimentary basins. The CRM-geothermal database is FAIR-aligned, openly available, and intended for reuse in geothermal research, resource assessment, and studies on the sustainable co-production of geothermal energy and critical raw materials.
Method:
The CRM-geothermal database was compiled using a combined approach integrating literature-based data collection, database harmonisation, and new data generation through field sampling and laboratory analysis.
Legacy data were collected from peer-reviewed scientific publications, national geological and geothermal databases, technical reports, and previous European research projects, with a particular emphasis on the REFLECT project. Relevant parameters were manually extracted, digitised where necessary, and cross-checked against original sources to ensure consistency and traceability.
New data were generated within the CRM-geothermal project through targeted sampling campaigns at selected geothermal sites in Europe and Eastern Africa. Samples of geothermal fluids, rocks, gases, and mineral precipitates were collected from wells and surface manifestations following standard geochemical sampling protocols.
Laboratory analyses were performed by project partner institutions using established analytical techniques, including inductively coupled plasma mass spectrometry (ICP-MS) for trace and critical elements, X-ray fluorescence (XRF) for bulk chemical composition, and X-ray diffraction (XRD) for mineralogical characterisation. Gas compositions were determined using gas chromatography and noble gas mass spectrometry where applicable. Detection limits and analytical uncertainties follow laboratory-specific standards and are documented where available.
All data were harmonised using a unified metadata schema. Units, parameter names, and reporting formats were standardised, and spatial information was converted to WGS 84 decimal degrees. Quality control was applied through automated validation scripts checking metadata completeness, coordinate validity, and numerical plausibility, followed by manual expert review to ensure scientific coherence and correct sample attribution.
The final dataset was organised into interconnected thematic tables (wells, fluids, rocks, gases, and scales) and exported as a structured Excel file for dissemination. Each record includes references, analytical method information, and a quality flag indicating data origin and traceability.
Technical Info:
The CRM-geothermal data publication is provided as a structured multi-sheet Excel (XLSX) file representing a curated snapshot of the CRM-geothermal database at the time of publication. The dataset was generated through controlled export workflows following data validation and harmonisation.
The Excel file contains separate worksheets for thematic data tables (wells, fluids, rocks, gases, and mineral precipitates). Each worksheet preserves unique identifiers, standardised metadata fields, and cross-references between related records, allowing the dataset to be used independently of any external system or software platform.
Cutting samples of 23 geological formations from different depths (measured depth, MD) between 1.4 and 4.4 km of the geothermal research well Groß Schönebeck site were analyzed with focus on lithium (Li), copper (Cu), and strontium (Sr).
To determine how strong and to which components these critical raw materials (CRM) are bound within the rocks, leaching and sequential extraction experiments were performed on five selected formation rock samples that are considered either for geothermal exploitation (Muschelkalk, Buntsandstein, Rotliegend sandstone) and/or as potential source for the CRM Li, Cu, Sr from the Permo-Carboniferous volcanic rocks and/or the Ohre anhydrite. In addition, electron probe micro analyses (EPMA) and laser ablation ICP-OES was performed on thin sections of the Rotliegend formation.
Die Energiewende ist rohstoffintensiv. Unser Hauptziel ist zu untersuchen wie sich die Verfügbarkeit kritischer Rohstoffe - und deren Versorgungsrisiko und Recycling-Potenzial - auf mögliche Umsetzungspfade für die deutsche Energiewende auswirkt. Zu diesem Zweck werden die Rohstoffverfügbarkeiten sowie die Rohstoffanforderungen von Energietechnologien in ein Energiesystemmodell integriert, um aus Rohstoffbedarfssicht nicht realisierbare Pfade verwerfen und robuste Pfade identifizieren zu können. Genauer gesagt, wird der prospektive Rohstoffbedarf in einem Modell für die Ausbauplanung explizit modelliert (endogenisiert). Es kann erwartet werden, dass die sich aus der Modellierung ergebenden Energiesysteme resilienter beispielsweise gegenüber gestörten Lieferketten sind, wenn die Verfügbarkeit kritischer Rohstoffe Modellentscheidungen beeinflusst. Dabei wird das Design des Energiesystems nicht nur auf die zu erwartenden Versorgungskosten, sondern im Zuge einer Mehrzieloptimierung auch bezüglich Versorgungsrisiko und die Rohstoffkritikalität ausgelegt. Dieser Aspekt ist von besonderer Relevanz, da Optimierungsmodelle demzufolge so weiterentwickelt werden, dass deren Zielfunktion erstmals das Zieldreieck der Energieversorgung aus Kosteneffizienz, Versorgungssicherheit und Nachhaltigkeit widerspiegelt. Um die Rechenlast einer solch komplexen Planungsaufgabe in einem angemessenen Rahmen zu halten, ist die Entwicklung einer intelligenten Methode zur Erforschung von Kompromisslösungen (Pareto-Fronten) zentraler Teil des Vorhabens. Weiterhin wird ein visuelles Analysewerkzeug entwickelt und angewendet, um Entscheidungsprozesse von Stake-holdern bei solch hochdimensionalen Problemen zu verbessern.