Below you will find a collection of publications that highlight how Dragonfly contributed to the success of diverse scientific investigations.

Contact Us if you would like your research to be featured in our spotlight series.

Light and electron microscopy continuum-resolution imaging of 3D cell cultures and image analysis using Dragonfly.

In this study, researchers used Dragonfly to understand the complex cellular sociology in 3D cancer organoids by analysing multimodal and multi-scale imaging.

  • 3D cell culture was performed in a single carrier amenable to multi-scale imaging that traverses millimeter scale live-cell light microscopy to nanometer-scale volume electron microscopy.
  • Dragonfly was used to train deep-learning automatic image segmentation to infer quantitative information that allowed analysis of subcellular structures in colorectal cancer organoids.
  • Dragonfly was used for 3D rendering of segmented subcellular structures helping to identify local organization of diffraction-limited cell junctions in compact and polarized epithelia.


Non-destructive multi-scale imaging of batteries

In this study, researchers from Research Center on Nanotechnologies Applied to Engineering (CNIS) of Sapienza University of Rome and ENEA Casaccia Research Center used Dragonfly software to segment, characterize, and visualize single components of batteries from their assembled states. In summary:

  • Reaching a holistic understanding of the inner workings of a battery.
  • ZEISS Xradia Versa 610 microscope used for imaging.
  • Image processing and 3D modeling investigation performed in Dragonfly, which assisted non-invasive early diagnosis of battery degradation.
  • Na-ion coin cell, Li-ion pouch cell, and Commercial VARTA NiMH cylindrical cell were investigated.
  • Work selected as Cover Feature of the journal ChemElectroChem.


Early stages of bone mineralization studied at nanoscale

In this work from the Max Planck Institute of Colloids and Interfaces, researchers shed light on early stages of bone mineralization using a variety of nanoscale imaging techniques. Performed at unprecedented resolution, the study provides insights into how mineralization progresses through the extracellular matrix.

  • Mineral propagates forming spherulites (ellipsoidal structures).
  • The mineral accommodates both inside and outside the collagen fibrils.
  • Nanosized spaces remain unmineralized within the fibril, likely determined by the presence of macromolecular complexes.
  • Correlative nanoscale imaging used, including ESEM, FIB-SEM, S/TEM, and STEM-EDS.


3D deep learning mineralogy by data fusion of XRF and XCT

Deep learning was used to segment and classify a range of minerals in a magmatic rock core. Mineral classification was achieved by data fusion of microXRF and X-ray CT, with deep learning segmentation.

  • Automated mineralogy using deep learning and 2D/3D data fusion
  • Minimal sample preparation for efficient analysis.
  • XCT performed on custom system using a General Electric X-ray tube.
  • Helical scan trajectory used for scanning.
  • XRF performed on Bruker M4 Tornado instrument.
  • Mineralogy obtained from XRF K-means clustering.
  • Dragonfly used for data fusion and segmentation.


Dragonfly used to quantify porosity reduction in additive manufacturing using pulsed laser

This work involved the study of porosity in metal additive manufacturing and its potential reduction by adding an additional pulsed laser into the process. Porosity was quantified in high resolution X-ray microtomography images using Dragonfly and porosity reduction was investigated by changing the process parameters of the pulsed laser. In summary:

  • Pulsed laser addition to additive manufacturing process investigated.
  • MicroCT images acquired using a ZEISS Versa 520.
  • Dragonfly used for porosity quantification.
  • 90% porosity reduction achieved.


Lithium ion battery study using Dragonfly

Lithium ion batteries were studied non-destructively using X-ray microscopy of the same cells before and after a full discharge. Despite X-ray imaging challenges, the transport of lithium was mapped to provide evidence of current constriction, a key parameter in lithium ion battery quality and its effective lifetime. In summary:

  • X-ray microscopy used to image entire lithium ion cells (anode, cathode, electrolyte and lithium).
  • Visualization of lithium was achieved in CT by enclosing Li with Cu plates.
  • Tomography performed with ZEISS Xradia Versa 520.
  • Dragonfly used for image analysis including registration and comparison of virgin and discharged states.
  • Information about current constriction in lithium ion cells is described.
  • Work published in MRS Communications.



Diffraction contrast tomography for powder crystallographic characterization

In this work, the authors demonstrated the first diffraction contrast tomography of polycrystalline powders using a laboratory system. The method is useful for characterization of powders relevant to pharmaceutical production and fine chemicals industries and the work demonstrates the combined analysis of such powders using diffraction contrast and absorption contrast tomography. In summary:

  • X-ray microscopy combined with diffraction contrast tomography (DCT).
  • Tomography performed with ZEISS Xradia Versa 520 fitted with labDCT module.
  • Dragonfly used for image registration, segmentation, and visualization.
  • Work published in the Royal Society of Chemistry’s CrysEngComm.


Correlative analytical and microscopic study of Icelandic soils

In this work, researchers used the Dragonfly software platform to study Icelandic soils using images and data acquired using a variety of hardware tools across multiple length scales. In summary:

  • Soil structure and chemistry studied using multiple microscopy and analytical tools.
  • Microscopy hardware included ZEISS Versa 520 XRM, Crossbeam FIB-SEM and Observer Z1M.
  • Dragonfly used for image registration, segmentation and visualization of data from all modalities.
  • Work published in Nature’s Scientific Reports.
  • Multi-scale structure of soils reported including channel thickness.


Researchers investigate ancient shark egg cases

In this interesting study from the Swedish Museum of Natural History, ancient shark egg cases from the early Jurassic period were studied using X-ray microCT. The non-destructive imaging aspect was crucial to make this study possible as the fragile specimens were partially embedded in rock. Segmentation is usually quite challenging in this type of image data, but no problem for Dragonfly. In summary:

  • Ancient shark egg cases studied.
  • MicroCT images acquired using a ZEISS Versa 520 instrument.
  • Dragonfly used for segmentation and 3D visualization.


Sheffield tomography facility publishes first paper

The newly established Sheffield Tomography Centre (STC) at the University of Sheffield recently published their first paper from data generated at the facility. This paper involves an investigation of cutting damage in carbon fibre reinforced composites; Dragonfly was used for visualization and evaluation of this damage.

  • Research published in Elsevier’s Composites Part A.
  • Carbon fibre reinforced polymers (CFRPs) with the epoxy matrix modified by addition of particle reinforcements.
  • Damage induced when cutting investigated by microscopy and tomography.
  • ZEISS Versa 620 X-ray microscope used in the study.
  • Sheffield Tomography Centre’s first publication.


X-ray microscopy for plants across multiple resolution scales

The capabilities of X-ray microscopy for plant sciences are highlighted in the recent paper entitled “X-ray microscopy enables multiscale high-resolution 3D imaging of plant cells, tissues, and organs”.

Summary of this spotlight:
  • Overview for sample preparation and imaging workflows described for XRM in plant sciences.
  • Dragonfly used for image registration, segmentation, and visualization.
  • Work published in the journal Plant Physiology.


Additively manufactured lattice structure surface morphology evaluation

In this study, researchers used Dragonfly software to study the surface morphology of single lattice struts built by additive manufacturing in stainless steel (metal 3D printing). The summary of the work:

  • Single struts of 316L stainless steel evaluated.
  • ZEISS Versa 520 X-ray microscopy used to acquire images.
  • Image analysis and visualization performed in Dragonfly.
  • Simplified models reconstructed for simulation and correlation to mechanical properties.
  • Work published in Materials Science and Engineering: A.


Nature paper: Dragonfly used to unveil the earliest Bryozoa fossil

In this spotlight, researchers used Dragonfly in work reported in the journal Nature. In this noteworthy scientific discovery:

  • Byrozoa fossils were investigated.
  • Both scanning electron microscopy and microtomography used.
  • SEM using ZEISS Supra 35 VP field emission at Uppsala University, FEI Quanta 450-FEGSEM at Northwest University and JEOL JSM 7100F-FESEM at Macquarie University.
  • Microtomography using a ZEISS Xradia MicroXCT-400 system.
  • Dragonfly used for image processing, segmentation and visualization.


Two heads are not always better than one - two-faced and double-headed sea turtle morphology evaluation

Researchers from the Florida Atlantic University recently published an interesting study of the malformation of sea turtle embryos and hatchlings found on south Florida beaches. As described in the Journal of Anatomy publication…

  • Microtomography was performed on a series of two-headed turtles using a Bruker Skyscan 1173 X-ray microCT instrument.
  • Dimensional measurements and 3D visualizations were done with Dragonfly.
  • Carapace length and other morphological features were also measured.

Quantifying Fast Charge Degradation in 18650 Li-Ion Batteries with X-Ray Microtomography and Distance Mapping


Researchers collaborated to study battery degradation under fast charging using advanced imaging and deep learning techniques.

  • High resolution microCT imaging observed battery microstructure during fast charging and discharging.
  • Dragonfly deep learning models automatically segmented hundreds of electrode layers, revealing void formation and delamination risks.
  • Dragonfly distance mapping enabled direct characterization of electrode dilation.