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Synthesis of Information-bearing Peptoids and their Sequence-directed Dynamic Covalent Self-assembly
Published on: February 6, 2020
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Building blocks for autonomous computing materials: Dimers, trimers, and tetramers
Xingfei Wei1, Yinong Zhao2, Yi Zhuang1
1Department of Chemistry, Johns Hopkins University, Baltimore, Maryland 21218, USA.
The Journal of Chemical Physics
|October 23, 2021
Summary
Stable nanoparticle networks mimicking neuronal connections were created using gold nanoparticles and polymer linkers. These assemblies show promise for brain-like computing, with potential for advanced data storage and processing applications.
Area of Science:
- Materials Science
- Nanotechnology
- Computational Chemistry
Background:
- Autonomous computing materials are key for next-generation devices.
- Nanoparticle networks show potential for brain-like computing.
Purpose of the Study:
- To investigate the stability of polymer-networked gold nanoparticle assemblies.
- To explore their potential for emulating neuronal networks.
Main Methods:
- Molecular dynamics (MD) simulations were employed.
- Citrate-capped gold nanoparticles (cit-AuNPs) were linked by poly(allylamine hydrochloride) (PAH) chains of varying lengths.
- Dimer, trimer, and tetramer structures were simulated.
Main Results:
- Stable dimer, trimer, and tetramer structures were successfully built.
- The tetramer structure demonstrated up to 11 distinct states with specific PAH linkers.
- AuNP-AuNP distances were reduced, maintaining local stability over 10 ns MD simulations.
- Global potential energy minimum observed at short distances due to electrostatic attraction.
Conclusions:
- Polymer-networked gold nanoparticle assemblies exhibit structural stability.
- These structures show potential for emulating neuronal networks and advancing computing.
- Further improvements in stability and applications can be achieved with alternative materials.
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