TIMA

TIMA
Uses
  • Automated mineral identification
  • Quantification and textural analysis
ManufacturerTescan
Components

TIMA (Tescan Integrated Mineral Analyzer) is an automated mineral analysis system manufactured by the Czech company Tescan. It combines scanning electron microscopy, backscattered-electron imaging and energy-dispersive X-ray spectroscopy with software to identify and quantify minerals in solid samples. The system produces mineral maps and data on mineral abundance, grain size, mineral associations (contacts between neighboring minerals) and liberation (the extent to which a mineral occurs separately from other minerals within particles).

TIMA was introduced in 2011. It is used in mineral processing and geological research, including the characterization of ores and petroleum reservoir rocks. The system has also been applied to extraterrestrial materials such as lunar soil returned by the Chang'e-5 mission.

History

TIMA's mineral analysis software was introduced in 2011. The TIMA system used Tescan's MIRA and VEGA scanning electron microscope platforms. In 2021, Tescan released a new generation of TIMA, which shared its hardware platform with the MIRA G4 field-emission scanning electron microscope.

Design and operation

Instrumentation

TIMA combines a scanning electron microscope with backscattered-electron (BSE) and secondary-electron detectors, energy-dispersive X-ray (EDS) silicon drift detectors and software for automated data acquisition. TIMA instruments have used either field-emission or tungsten-filament electron sources, with one to four EDS detectors. Multiple EDS detectors increase the rate of X-ray collection and reduce shadowing from uneven sample surfaces. TIMA sample holders accommodate batches of thin sections or polished blocks.

Rock sections and grain mounts are typically polished to expose a flat surface and given a conductive coating to reduce charging. Surface preparation affects focusing and the quality of BSE and EDS data.

Mineral identification and quantification

TIMA identifies mineral phases using BSE image contrast and EDS spectra. BSE contrast reflects differences in average atomic number, while EDS spectra provide information on elemental composition. The software uses these measurements and a mineral classification scheme to assign phase identities and generate a two-dimensional mineral map. Stored measurements can be reprocessed after the classification scheme is revised.

The software reports mineral abundances as volume percentages and converts them to mass percentages using assigned phase densities. These abundances and assigned phase compositions are used to calculate bulk chemical composition and elemental deportment, or the distribution of individual elements among mineral phases. Spatial data provide grain and particle size distributions, mineral associations and liberation. The software can export grain coordinates for subsequent electron probe microanalysis or laser ablation inductively coupled plasma mass spectrometry (LA-ICP-MS).

These surface measurements do not directly describe the complete three-dimensional structure of the sample; two-dimensional sections can lead to errors in estimates of mineral size and spatial relationships. Quantification also depends on whether the analyzed surface represents the sample.

Identification accuracy depends on how well the classification library represents the minerals and compositional variations present in the sample. Generic libraries can leave phases unclassified or misidentify them; refinement can also be checked using complementary techniques such as electron probe microanalysis. Phases with similar chemical compositions can be difficult to distinguish. Small intergrown mineral grains and mineral boundaries can produce mixed EDS signals, which the software attempts to classify by matching the resulting spectra against adjacent phases. Although EDS cannot directly detect elements such as hydrogen and lithium, phases containing these elements can still be identified based on the proportions of other detectable elements. Low elemental concentrations and overlapping X-ray peaks can also limit chemical quantification.

Measurement modes

TIMA uses four acquisition modes:

  1. High-resolution mapping collects BSE signals and EDS spectra at each point on a regular grid over the selected material.
  2. Point spectrometry uses BSE contrast to identify regions and collects one EDS spectrum per region. This reduces acquisition time but can misclassify adjacent phases with similar BSE brightness and different chemical compositions.
  3. Line mapping collects BSE and EDS data along regularly spaced lines. It reduces acquisition time and retains some textural information, but does not produce complete two-dimensional mineral maps.
  4. Dot mapping collects BSE data on a finer grid and EDS spectra on a coarser grid. Each detected region receives at least one EDS measurement, including regions smaller than the EDS grid spacing.

These acquisition modes are used within separate analysis types. Modal analysis measures mineral abundances, while liberation analysis collects mineralogical and textural information. Bright phase search targets phases selected by BSE intensity, chemical composition or both, with an option to analyze surrounding material. Section analysis maps phases in thin sections or polished rock surfaces without detecting individual particles.

Applications

TIMA has been used in:

References

  1. 1 2 3 4 5 Changqing Fu; Yi Du; Wenlei Song; Shuxun Sang; Zhejun Pan; Ning Wang (2023). "Application of automated mineralogy in petroleum geology and development and CO2 sequestration: A review". Marine and Petroleum Geology. 151 106206. doi:10.1016/j.marpetgeo.2023.106206.
  2. 1 2 3 4 5 6 7 8 9 Tomáš Hrstka; Paul Gottlieb; Roman Skála; Karel Breiter; David Motl (2018). "Automated mineralogy and petrology – applications of TESCAN Integrated Mineral Analyzer (TIMA)". Journal of Geosciences. 63 (1): 47–63. doi:10.3190/jgeosci.250.
  3. 1 2 L. Santoro; F. Putzolu; N. Mondillo; R. Herrington; J. Najorka; M. Boni; M. Dosbaba; M. Maczurad; G. Balassone (2021). "Quantitative mineralogical evaluation of Ni-Co laterite ores through XRPD-QPA- and automated SEM-based approaches: The Wingellina (Western Australia) case study". Journal of Geochemical Exploration. 223 106695. Bibcode:2021JCExp.22306695S. doi:10.1016/j.gexplo.2020.106695. hdl:2318/1769740.
  4. 1 2 3 4 5 6 Qian Chen; Wenlei Song; Zaicong Wang; Hongyi Chen; Zhuang Guo; Yiheng Li; Danni Xu; Xing Wang; Kangjun Huang (2024). "Automated Fast and Quantitative Mineralogical Characterization of Chang'e-5 Lunar Soils". Atomic Spectroscopy. 45 (5): 381–390. doi:10.46770/AS.2024.202.
  5. ↑ Bernhard Schulz; Dirk Sandmann; Sabine Gilbricht (2020). "SEM-Based Automated Mineralogy and Its Application in Geo- and Material Sciences". Minerals. 10 (11): 1004. Bibcode:2020Mine...10.1004S. doi:10.3390/min10111004.
  6. ↑ "TESCAN speeds up and automates mineralogical analysis with TESCAN TIMA". International Mining. March 3, 2021. Retrieved October 6, 2026.
  7. 1 2 Florian Buyse; Stijn Dewaele; Matthieu N. Boone; Veerle Cnudde (2023). "Combining Automated Mineralogy with X-ray Computed Tomography for Internal Characterization of Ore Samples at the Microscopic Scale". Natural Resources Research. 32 (2): 461–478. Bibcode:2023NRR....32..461B. doi:10.1007/s11053-023-10161-z.
  8. ↑ Z. Li; B. I. A. McInnes; L. S. Normore (2024). Mineralogy and petrology atlas of sedimentary rocks from stratigraphic well Barnicarndy 1 using the TESCAN Integrated Mineral Analyzer (TIMA) (PDF) (Record 2024/6). Geological Survey of Western Australia. Retrieved October 6, 2026.
  9. ↑ Lisa I. Kearney; Andrew G. Christy; Elena A. Belousova; Benjamin R. Hines; Alkis Kontonikas-Charos; Mitchell de Bruyn; Henrietta E. Cathey; Vladimir Lisitsin (2025). "Automated, Not Autonomous: Integrating Automated Mineralogy with Complementary Techniques to Refine and Validate Phase Libraries in Complex Mineral Systems". Minerals. 15 (11): 1118. Bibcode:2025Mine...15.1118K. doi:10.3390/min15111118.
  10. 1 2 Marek Tuhý; Tomáš Hrstka; Vojtěch Ettler (2020). "Automated mineralogy for quantification and partitioning of metal(loid)s in particulates from mining/smelting-polluted soils". Environmental Pollution. 266 (Pt 1) 115118. Bibcode:2020EPoll.26615118T. doi:10.1016/j.envpol.2020.115118. PMID 32623271.
  11. ↑ "Exploration breakthroughs". CSIRO. July 31, 2017. Retrieved October 6, 2026.
  12. ↑ "The Analytical Fingerprint Laboratory". African Minerals and Geosciences Centre. Retrieved October 6, 2026.
  13. ↑ Mahmud Esad Uluer; Lizeth Jaramillo Taborda; Emily Sarver (2026). "Evaluating particle complexity in respirable coal mine dust using automated SEM-EDX with an integrated mineral analyzer". Journal of Hazardous Materials. 509 142068. Bibcode:2026JHzM..50942068U. doi:10.1016/j.jhazmat.2026.142068. PMID 41990659.
  14. ↑ Anna Vanderbruggen; Eligiusz Gugala; Rosie Blannin; Kai Bachmann; Rodrigo Serna-Guerrero; Martin Rudolph (2021). "Automated mineralogy as a novel approach for the compositional and textural characterization of spent lithium-ion batteries". Minerals Engineering. 169 106924. Bibcode:2021MiEng.16906924V. doi:10.1016/j.mineng.2021.106924.
  15. ↑ Zhengxiang Liu; Yanxiu Wang; Yi Tian; Qiang Yuan; Wei Sun; Xuekun Tang; Anqi Yang (2026). "Evaluation of porphyry copper mine waste rock using TIMA analysis and its manufactured sand properties". Minerals Engineering. 235 109861. Bibcode:2026MiEng.23509861L. doi:10.1016/j.mineng.2025.109861.
  16. ↑ Ingrid Ward; Kelly Merigot; Brent I. A. McInnes (2018). "Application of Quantitative Mineralogical Analysis in Archaeological Micromorphology: a Case Study from Barrow Is., Western Australia". Journal of Archaeological Method and Theory. 25: 45–68. doi:10.1007/s10816-017-9330-6.