Block Copolymer Aided Controllable Design of Colloidal Molecules by DNA-programmable Assembly

Xian-Deng Qiu; Hao Tang; Rong Wang

doi:10.1007/s10118-025-3424-5

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Block Copolymer Aided Controllable Design of Colloidal Molecules by DNA-programmable Assembly

RESEARCH ARTICLE | Updated：2025-12-03

- Block Copolymer Aided Controllable Design of Colloidal Molecules by DNA-programmable Assembly
- Chinese Journal of Polymer Science Vol. 43, Issue 12, Pages: 2213-2221(2025)
- Affiliations：
  
  Department of Polymer Science and Engineering, State Key Laboratory of Coordination Chemistry, Key Laboratory of High Performance Polymer Materials and Technology of Ministry of Education, School of Chemistry and Chemical Engineering, Nanjing University, Nanjing 210023, China
- Author bio：
  
  wangrong@nju.edu.cn
- Funds：
- DOI：10.1007/s10118-025-3424-5
  CLC：
- Received：25 June 2025，
  
  Accepted：02 August 2025，
  
  Published Online：03 November 2025，
  
  Published：15 December 2025
- Accepted：
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Qiu, X. D.; Tang, H.; Wang, R. Block copolymer aided controllable design of colloidal molecules by DNA-programmable assembly. Chinese J. Polym. Sci. 2025, 43, 2213–2221

Xian-Deng Qiu, Hao Tang, Rong Wang. Block Copolymer Aided Controllable Design of Colloidal Molecules by DNA-programmable Assembly[J]. Chinese Journal of Polymer Science, 2025, 43(12): 2213-2221.
Qiu, X. D.; Tang, H.; Wang, R. Block copolymer aided controllable design of colloidal molecules by DNA-programmable assembly. Chinese J. Polym. Sci. 2025, 43, 2213–2221 DOI： 10.1007/s10118-025-3424-5.

Xian-Deng Qiu, Hao Tang, Rong Wang. Block Copolymer Aided Controllable Design of Colloidal Molecules by DNA-programmable Assembly[J]. Chinese Journal of Polymer Science, 2025, 43(12): 2213-2221. DOI： 10.1007/s10118-025-3424-5.

摘要

The synergistic strategy that integrates molecular dynamics simulations and interpretable machine learning was used to program the assembly of block-copolymer and DNA-functionalized nanoparticles into stable colloidal molecules

achieving precise

high-yield assembly. SHAP analysis was used to identify key structural descriptors and clarifies mechanisms governing ordered coassembly.

Abstract

Colloidal molecules exhibit unique electronic

optical

and magnetic properties owing to their molecular-like configurations and coupling effects

making them promising building blocks for multifunctional materials. However

achieving precise and controllable assembly of isotropic nanoparticles with high yields remains a great challenge. In this study

we present a synergistic strategy that integrates molecular dynamics simulations with interpretable machine learning to develop a programmable assembly system based on block copolymers and DNA-functionalized nanoparticles. Our simulation results reveal that block copolymer modification facilitates stepwise control over surface phase separation and nanoparticle coassembly

thereby enhancing structural stability and efficiently suppressing disordered aggregation of atom-like nanoparticles. Furthermore

we demonstrated that precise

controllable

and programmable assembly of colloidal molecules can be achieved through rational DNA sequence design. SHapley Additive exPlanations (SHAP) analysis identified key structural descriptors that govern assembly outcomes and elucidated their underlying mechanistic roles. This work not only deepens the understanding of colloidal molecule assembly mechanisms but also lays a theoretical foundation for the rational design of functional colloidal architectures in nanomaterial science.

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references

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