the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Grain growth of ice doped with soluble impurities
Abstract. The grain size of polycrystalline ice affects key parameters related to the dynamics of ice masses, such as the rheological and dielectric properties of terrestrial ice flow as well as the ice shells of icy satellites. To investigate the effect of soluble impurities on the grain-growth kinetics of polycrystalline ice, we conducted annealing experiments on polycrystalline ice samples doped with different concentrations of KCl (10−2, 10−3, 10−4 and 10−5 mol/L) or MgSO4 (10−2 and 10−5 mol/L). Samples were annealed for a maximum of 100 h at a hydrostatic confining pressure of 20 MPa (corresponding to a depth of about 2 km ) and different constant temperatures of 268, 263, 258 and 253 K. After each experiment, images of a polished sample surface were obtained using an optical microscope equipped with a cold stage. With grain boundaries detected, grains were reconstructed from the images and an average grain size was determined for each sample. Normal grain growth occurred in all samples. Grain-size data are interpreted using the grain-growth model, dn − d0n kt (d: grain size; d0: starting grain size; n: grain-growth exponent; k: growth constant; t: duration). Values of the best-fit grain growth exponent, n, for all samples range from 2.6 to 6.2, with an average value of 4.7. Pure ice exhibits 3.1 ≤ n ≤ 4.6, with an average value of 3.8. Above the eutectic point, soluble impurities enhance grain growth, as a melt phase is formed and it could provide a fast diffusion pathway. Below the eutectic point, soluble impurities impede grain growth probably via the formation of salt hydrates that could pin the grain boundaries. Close to the eutectic point, the grain growth of doped ice is similar to pure ice. The effect of soluble impurities on grain growth can be articulated as the application of a factor on the growth constant, k. We found this factor is a function of temperature and eutectic temperature. Natural ice is impure, often containing air bubbles and soluble impurities, and is usually subjected to a hydrostatic pressure. Our data set and the established impurity factor will provide new insights to the evolution of grain size within and the dynamics of natural ice masses.
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Notice on discussion status
The requested preprint has a corresponding peer-reviewed final revised paper. You are encouraged to refer to the final revised version.
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Preprint
(16635 KB)
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The requested preprint has a corresponding peer-reviewed final revised paper. You are encouraged to refer to the final revised version.
- Preprint
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- Final revised paper
Journal article(s) based on this preprint
Interactive discussion
Status: closed
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RC1: 'Comment on egusphere-2023-2344', Lisa Craw, 27 Nov 2023
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CC1: 'Reply on RC1', Qinyu Wang, 15 Dec 2023
Publisher’s note: this comment was edited on 15 December 2023. The following text is not identical to the original comment, but the adjustments were minor without effect on the scientific meaning.
We thank reviewer 1, Dr Lisa Craw for their thoughtful and helpful reviews of our paper. Please refer to the attached PDF for detailed replies.
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CC2: 'Reply on CC1', Qinyu Wang, 15 Dec 2023
Publisher’s note: the content of this comment was removed on 15 December 2023 since the comment was posted by mistake.
Citation: https://doi.org/10.5194/egusphere-2023-2344-CC2
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CC2: 'Reply on CC1', Qinyu Wang, 15 Dec 2023
- AC2: 'Reply on RC1', Chao Qi, 08 Jan 2024
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CC1: 'Reply on RC1', Qinyu Wang, 15 Dec 2023
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RC2: 'Comment on egusphere-2023-2344', Christopher Gerbi, 15 Dec 2023
This manuscript reports on a valuable topic in the glaciological community, and I appreciate the care taken with the experimental design and execution. These are clearly difficult experiments, as indicated by the challenges in achieving similar results as past work, so these additional test with different methodologies are important to help the community move towards a common solution for quantifying grain growth.
The conclusions seem to be mostly well supported by the data, so I suggest only minimal adjustment to them, as indicated below. More significant to me is the treatment of n within the manuscript, and the relationship between the conclusions and the manuscript body. My comments here are about providing the strongest statements the data can support.
1. Many places in the manuscript and in the conclusions (e.g., lines 198, 209, 230, 231, 286, 294, 472, 473) n is described as varying. Yet Line 232 (similar to line 364) claims that "n can be regarded as relatively independent of both temperature and concentration". I find those statements incompatible, but perhaps I am missing something. In my limited time spent with these data, I do not see a systematic relationship, but I have difficulty seeing n as independent, particularly given how far outside of uncertainty the values lie according to Table 1. Possible resolutions are that the uncertainties are higher than reported or that the data aren't able to capture some additional complexity.
2. Throughout the manuscript, including in the conclusions, n is characterized as having an average value. I do not have a sense of how that average is calculated, and how much the experimental condition choices affect the determination of that average. Meaning, if 5 experiments had been run above the eutectic but still in the same temperature range, I expect the average n would be different. So it is hard for me to see how reliable the average is.
3. The manuscript spends significant time discussing the grain growth constant, k, yet no conclusion point relates to this value.
4. In conclusion point #4, I suggest separating the observations from the inferred cause (i.e., that soluble impurities enhance grain growth above the eutectic and the presence of a melt phase; similar comment for below the eutectic).
5. In Figures 6, 7, and 9, please describe how the best fits are calculated.
Citation: https://doi.org/10.5194/egusphere-2023-2344-RC2 - AC1: 'Reply on RC2', Chao Qi, 08 Jan 2024
Interactive discussion
Status: closed
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RC1: 'Comment on egusphere-2023-2344', Lisa Craw, 27 Nov 2023
-
CC1: 'Reply on RC1', Qinyu Wang, 15 Dec 2023
Publisher’s note: this comment was edited on 15 December 2023. The following text is not identical to the original comment, but the adjustments were minor without effect on the scientific meaning.
We thank reviewer 1, Dr Lisa Craw for their thoughtful and helpful reviews of our paper. Please refer to the attached PDF for detailed replies.
-
CC2: 'Reply on CC1', Qinyu Wang, 15 Dec 2023
Publisher’s note: the content of this comment was removed on 15 December 2023 since the comment was posted by mistake.
Citation: https://doi.org/10.5194/egusphere-2023-2344-CC2
-
CC2: 'Reply on CC1', Qinyu Wang, 15 Dec 2023
- AC2: 'Reply on RC1', Chao Qi, 08 Jan 2024
-
CC1: 'Reply on RC1', Qinyu Wang, 15 Dec 2023
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RC2: 'Comment on egusphere-2023-2344', Christopher Gerbi, 15 Dec 2023
This manuscript reports on a valuable topic in the glaciological community, and I appreciate the care taken with the experimental design and execution. These are clearly difficult experiments, as indicated by the challenges in achieving similar results as past work, so these additional test with different methodologies are important to help the community move towards a common solution for quantifying grain growth.
The conclusions seem to be mostly well supported by the data, so I suggest only minimal adjustment to them, as indicated below. More significant to me is the treatment of n within the manuscript, and the relationship between the conclusions and the manuscript body. My comments here are about providing the strongest statements the data can support.
1. Many places in the manuscript and in the conclusions (e.g., lines 198, 209, 230, 231, 286, 294, 472, 473) n is described as varying. Yet Line 232 (similar to line 364) claims that "n can be regarded as relatively independent of both temperature and concentration". I find those statements incompatible, but perhaps I am missing something. In my limited time spent with these data, I do not see a systematic relationship, but I have difficulty seeing n as independent, particularly given how far outside of uncertainty the values lie according to Table 1. Possible resolutions are that the uncertainties are higher than reported or that the data aren't able to capture some additional complexity.
2. Throughout the manuscript, including in the conclusions, n is characterized as having an average value. I do not have a sense of how that average is calculated, and how much the experimental condition choices affect the determination of that average. Meaning, if 5 experiments had been run above the eutectic but still in the same temperature range, I expect the average n would be different. So it is hard for me to see how reliable the average is.
3. The manuscript spends significant time discussing the grain growth constant, k, yet no conclusion point relates to this value.
4. In conclusion point #4, I suggest separating the observations from the inferred cause (i.e., that soluble impurities enhance grain growth above the eutectic and the presence of a melt phase; similar comment for below the eutectic).
5. In Figures 6, 7, and 9, please describe how the best fits are calculated.
Citation: https://doi.org/10.5194/egusphere-2023-2344-RC2 - AC1: 'Reply on RC2', Chao Qi, 08 Jan 2024
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Qinyu Wang
Sheng Fan
The requested preprint has a corresponding peer-reviewed final revised paper. You are encouraged to refer to the final revised version.
- Preprint
(16635 KB) - Metadata XML