Automated Etching Processes in Robo-Met.3D

April 05, 2021


Metallographic etching is a chemical technique used to create accelerated differential corrosion between different phases in a metallic sample. The morphological characteristics, quantities and distributions of these phases can help investigators better understand structure property relationships in metals.

Read also: Robo-Met Recognized for Providing Ground Truth Data in NASA SBIR Award

The Robo-Met.3D system can be relied on to repeatably create fine polished surfaces on metallic
samples, suitable for even SEM/EBSD investigations. However to an optical microscope, such surfaces show limited phase contrast (Fig. 1). Etching can create the requisite contrast to optically investigate sample surfaces (Fig. 2)3.

Figure 1: 2D Microstructure (unetched for Ti6242)

Figure 1: 2D Microstructure (unetched for Ti6242)

Figure 3: Alpha-Beta Microstructure (etched with Kroll’s Reagent) with Defect Distribution for Ti6242

Figure 3: Alpha-Beta Microstructure (etched with Kroll’s Reagent) with Defect Distribution for Ti6242

Etching Reagent Selection for the Robo-Met.3D

The dip wells in the Robo-Met.3D system are configured for immersion etching. Etching in the Robo-Met system must always be performed with the exhaust on, to ensure operator safety. The etching
mechanism used also provides some guidelines to select etchants for use in the Robo-Met.3D. In
addition to being metallographically appropriate to immersion etching the sample, the etchants need to:

  • Demonstrate a stable pH over the planned course of the investigation (hours, days..)
  • Be stable under storage without outgassing

Common etchants used in the Robo-Met system, along with the metal compositions they are used to
investigate, are listed in Table 1 as a guideline.

Table 1: Etchants Appropriate for Immersion Technique Usage in the Robo-Met.3D System


Reagent Name

Reagent Composition

Metal Families Studied

Nital (2-4%)

Ethanol 100ml

Nitric acid 1-10 ml

Common etchant for Fe, carbon and alloys steels and cast iron

Waterless Kalling’s Reagent

CuCl 2 5 grams

Hydrochloric acid -100 ml

Ethanol 100 ml

Ni-Cu, nickel-based superalloys, ferritic and martensitic 400 series stainless steels. This etchant will darken martensite, attack ferrite readily and etch austenite slightly. It will not attack carbides.

Kroll’s Reagent

Distilled water 92ml

Nitric acid 6 ml

Hydrofluoric acid 2 ml

The primary alpha structure of titanium will appear white after etching. Alpha prime and acicular alpha structures will be outlined. Intergranular beta structure and beta grains will be darkened.

Frye’s Reagent

40 ml HCl 

5 g CuCl2 

30 ml Water 

25 ml Ethanol

Fry's reagent for martensitic and precipitation hardenable grades of stainless steel.

Marble’s Reagent

CuSO4 10g

Hydrochloric acid 50ml

Water 50 ml

For etching Ni, Ni-Cu and Ni-Fe alloys and superalloys.

Handling Etching Effluents from the Robo-Met.3D

A large amount of water is used to flush and clean the metallographic samples and platens. We studied
etching during serial sectioning with Robo-Met.3D, with a tap established in the rear effluent port of the
system to monitor pH and estimate flows. We found that for the etchants studied (Marbles, Nital, Kroll’s
and Kalling’s reagents):

  • Over the collection period (1-2h), we generated ~ 0.8– 1.2 cu. ft ( ~23-34l) of water per section.
  • Effluent pH levels (~ 8.0) were well within safe and expected parameters (5.5-9.0) for all

This enabled us to conclude that subject to variations in applicable environmental safety regulations,
discharging the metallographic waste water directly into the lab waste stream should be safe.

Do not hesitate to contact us if you have questions about etching in the Robo-Met.3D system.

Read also: 2020 Research Using Robo-Met's Materials Analysis

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  1. Seifi, M., Ghamarian, I., Samimi, P., Ackelid, U., Collins, P., & Lewandowski, J. (2016,May). Microstructure and mechanical properties of Ti-48Al-2Cr-2Nb manufactured via electron beam melting. In Proceedings of world conference on titanium, 13th. TMS/Wiley, Warrendale, PA/Hoboken, NJ.
  2. Rowenhorst, D. J., Nguyen, L., Murphy-Leonard, A. D., & Fonda, R. W. (2020). Characterization of microstructure in additively manufactured 316L using automated serial sectioning. Current Opinion in Solid State and Materials Science, 24(3), 100819.
  3. Lu, Y., Wang, M., Wu, Z., Jones, I. P., Wickins, M., Green, N. R., & Basoalto, H. C. (2020). Three-dimensional analysis of dendrites via automated serial sectioning using a Robo-Met. 3D. MRS Communications, 10(3), 461-466.
  4. Ganti, S., Turner, B., Kirsch, M., Anthony, D., McCoy, B., Trivedi, H., & Sundar, V. (2018). Three-dimensional (3D) analysis of white etching bands (WEBs) in AISI M50 bearing steel using automated serial sectioning. Materials Characterization, 138, 11-18.
  5. Sundar, V., Turner, B., Ganti, S., & Davis, W. (2018). Light Optical Microscopy Based Automated 3D Serial Sectioning Enables Defect Analysis in Large Volumes of Additively Manufactured Alloy Samples. Microscopy and Microanalysis, 24(S1), 554-555.

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