Molecular control via dynamic bonding enables material responsiveness in additively manufactured metallo-polyelectrolytes
Abstract
Metallo-polyelectrolytes are versatile materials for applications like filtration, biomedical devices, and sensors, due to their metal-organic synergy. Their dynamic and reversible electrostatic interactions offer high ionic conductivity, self-healing, and tunable mechanical properties. However, the knowledge gap between molecular-level dynamic bonds and continuum-level material properties persists, largely due to limited fabrication methods and a lack of theoretical design frameworks. To address this critical gap, we present a framework, combining theoretical and experimental insights, highlighting the interplay of molecular parameters in governing material properties. Using stereolithography-based additive manufacturing, we produce durable metallo-polyelectrolytes gels with tunable mechanical properties based on metal ion valency and polymer charge sparsity. Our approach unveils mechanistic insights into how these interactions propagate to macroscale properties, where higher valency ions yield stiffer, tougher materials, and lower charge sparsity alters material phase behavior. This work enhances understanding of metallo-polyelectrolytes behavior, providing a foundation for designing advanced functional materials.
Copyright and License
Open Access. This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.
Acknowledgement
The authors gratefully acknowledge the financial support from the Center for Autonomous Systems and Technologies (CAST) at Caltech and the Schwartz/Reisman Collaborative Science Program from the Schwartz/Reisman Foundation. Research was also sponsored, in part, by the U.S. Army Research Office and accomplished under contract W911NF-19-D-0001 for the Institute for Collaborative Biotechnologies. We thank Beckman Institute as well as the critical support of Molecular Materials Research Center (MMRC), Beckman Bioimaging Facility (BIF), Beckman X-Ray Crystallography Facility (XRCF), and Geological and Planetary Sciences Division Analytical Facility at Caltech. Z-G.W. acknowledges funding from Hong Kong Quantum AI Lab, AIRInnoHK of the Hong Kong Government. We also acknowledge Dr. Daryl Yee and Dr. Widianto Moestopo for their contribution to project ideation and Sophie Howell for supporting preliminary feasibility studies. We thank Dr. Chi Ma, Dr. Giada Spigolon, Dr. Kathy Faber and Dr. Guruswami Ravichandran at Caltech for equipment support and technical assistance in this research. Useful discussions with Sammy Shaker, Alec Glisman, Alexandros Tsamopoulos, Dr. Alejandro Gallegos, Dr. George Rossman, and Dr. Igor Lubomirsky are also gratefully acknowledged.
Errata
Author Correction: Molecular control via dynamic bonding enables material responsiveness in additively manufactured metallo-polyelectrolytes - https://doi.org/10.1038/s41467-024-52457-5
In the Acknowledgements section, the following sentence, ‘The authors gratefully acknowledge the financial support from the Center for Autonomous Systems and Technologies (CAST) at Caltech, the Institute for Collaborative Biotechnologies from the Army Research Office (ARO), and the Schwartz/Reisman Collaborative Science Program from the Schwartz/Reisman Foundation’ should have read, ‘The authors gratefully acknowledge the financial support from the Center for Autonomous Systems and Technologies (CAST) at Caltech and the Schwartz/Reisman Collaborative Science Program from the Schwartz/Reisman Foundation. Research was also sponsored, in part, by the U.S. Army Research Office and accomplished under contract W911NF-19-D-0001 for the Institute for Collaborative Biotechnologies’. The original article has been corrected.
Data Availability
Data generated and/or analysed during this study are included in the Supplementary Information. Further data are available from the corresponding authors on request.
Code Availability
Example codes used to perform DFT, MD and mean-field theory calculations are provided on GitHub: https://github.com/zgw-group/Metallo-Polyelectrolyte-Gels
Files
Name | Size | Download all |
---|---|---|
md5:eda2857d742ec76b9903b3953a73e084
|
3.6 MB | Preview Download |
md5:3dc29e1a635eff0afc1c2fbe688d4327
|
42.9 MB | Preview Download |
Additional details
- PMCID
- PMC11316739
- California Institute of Technology
- Center for Autonomous Systems and Technologies (CAST) -
- United States Army Research Office
- W911NF-19-D-0001
- Publication Status
- Published, Erratum