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Continuous rapid cooling of polarized electrons initiates Mpemba superfreezing

  • Andrew Das Arulsamy EMAIL logo
Published/Copyright: July 28, 2025

Abstract

Hot water freezing faster than cold water is simply startling, and this observation is known as the Mpemba effect since its rediscovery in 1969. But we are still confused and grappling in search of the underlying experimental conditions and the microscopic physics that can confirm, experimentally and theoretically whether this effect is real or misunderstood. Here, we derive the macroscopic physics of water freezing based on Newtonian cooling. Subsequently, we invoke the effect of covalent-bonded hydrogen and oxygen atoms with polarized electrons to evaluate the temperature (T)-dependent interaction strength between water molecules that determines the length of dynamical hydrogen bonds. After doing so, we expose the hidden Mpemba physics of superfreezing – low-density hot water (due to repulsion caused by highly polarized electrons) induce faster complete freezing compared to high-density cold water if and only if the cooling rate is sufficiently and continuously rapid. However, the question as to which water starts to freeze first (and/or reaches 0 °C first), is conditional. Along the way, we also derive the microscopic interaction potential inequality responsible for supercooling that delays freezing of cold water.


Corresponding author: Andrew Das Arulsamy, Condensed Matter Group, Thiruvalluvar Institute of Interdisciplinary Science, No. 24, Level-4, Block C, Lorong Bahagia, Pandamaran, 42000 Port Klang, Selangor DE, Malaysia, E-mail:

Acknowledgments

ADA is grateful to Sebastiammal Savarimuthu for her continuous support for the advancement of science and humanity. I would like to thank Proceedings A board member for insisting that I should comment on Ref. 26] and references therein.

  1. Research ethics: Not applicable.

  2. Informed consent: Not applicable.

  3. Author contributions: The author has accepted responsibility for the entire content of this manuscript and approved its submission.

  4. Use of Large Language Models, AI and Machine Learning Tools: None declared.

  5. Conflict of interest: The author states no conflict of interest.

  6. Research funding: No funding received.

  7. Data availability: Used experimental data have been cited, while all calculated data can be reproduced from the listed equations.

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Received: 2025-03-11
Accepted: 2025-04-07
Published Online: 2025-07-28
Published in Print: 2025-10-27

© 2025 Walter de Gruyter GmbH, Berlin/Boston

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