Optimization of Linear Sequence-controlled Copolymers for Maximizing Adsorption Capacity

Sheng-Da Zhao; Qiu-Ju Chen; Zhi-Xin Liu; Quan-Xiao Dong; Xing-Hua Zhang

doi:10.1007/s10118-025-3380-0

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Optimization of Linear Sequence-controlled Copolymers for Maximizing Adsorption Capacity

RESEARCH ARTICLE | Updated：2025-09-26

- Optimization of Linear Sequence-controlled Copolymers for Maximizing Adsorption Capacity
- Chinese Journal of Polymer Science Vol. 43, Issue 10, Pages: 1739-1748(2025)
- Affiliations：
  
  a.School of Physical Sciences and Engineering, Beijing Jiaotong University, Beijing 100044, China
  b.Beijing Key Laboratory of Novel Materials Genetic Engineering and Application for Rail Transit, Beijing Jiaotong University, Beijing 100044, China
  c.School of Physics and Astronomy, Beijing Normal University, Beijing 100875, China
  d.Hebei Tieke Yichen New Materials Technology Co., Ltd., Shijiazhuang 052160, China
- Author bio：
  
  dongquanxiaotjs@163.com (Q.X.D.)
  zhangxh@bjtu.edu.cn (X.H.Z.)
- Funds：
- DOI：10.1007/s10118-025-3380-0
  CLC：
- Received：18 April 2025，
  
  Revised：2025-05-06，
  
  Accepted：12 May 2025，
  
  Online First：11 July 2025，
  
  Published：05 October 2025
- Accepted：
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Zhao, S. D.; Chen, Q. J.; Liu, Z. X.; Dong, Q. X.; Zhang, X. H. Optimization of linear sequence-controlled copolymers for maximizing adsorption capacity. Chinese J. Polym. Sci. 2025, 43, 1739–1748

Sheng-Da Zhao, Qiu-Ju Chen, Zhi-Xin Liu, et al. Optimization of Linear Sequence-controlled Copolymers for Maximizing Adsorption Capacity[J]. Chinese Journal of Polymer Science, 2025, 43(10): 1739-1748.
Zhao, S. D.; Chen, Q. J.; Liu, Z. X.; Dong, Q. X.; Zhang, X. H. Optimization of linear sequence-controlled copolymers for maximizing adsorption capacity. Chinese J. Polym. Sci. 2025, 43, 1739–1748 DOI： 10.1007/s10118-025-3380-0.

Sheng-Da Zhao, Qiu-Ju Chen, Zhi-Xin Liu, et al. Optimization of Linear Sequence-controlled Copolymers for Maximizing Adsorption Capacity[J]. Chinese Journal of Polymer Science, 2025, 43(10): 1739-1748. DOI： 10.1007/s10118-025-3380-0.

摘要

We demonstrate the effectiveness of the Simulated Bifurcation (SB) algorithm

based on the concept of conjugate fields

in polymer sequence optimization. Despite requiring numerical gradients

SB outperforms stochastic methods like simulated annealing and exhibits excellent scalability in high-dimensional design spaces.

Abstract

The optimization of polymer structures aims to determine an optimal sequence or topology that achieves a given target property or structural performance. This inverse design problem involves searching within a vast combinatorial phase space defined by components

sequences

and topologies

and is often computationally intractable due to its NP-hard nature. At the core of this challenge lies the need to evaluate complex correlations among structural variables

a classical problem in both statistical physics and combinatorial optimization. To address this

we adopt a mean-field approach that decouples direct variable-variable interactions into effective interactions between each variable and an auxiliary field. The simulated bifurcation (SB) algorithm is employed as a mean-field-based optimization framework. It constructs a Hamiltonian dynamical system by introducing generalized momentum fields

enabling efficient decoupling and dynamic evolution of strongly coupled structural variables. Using the sequence optimization of a linear copolymer adsorbing on a solid surface as a case study

we demonstrate the applicability of the SB algorithm to high-dimensional

non-differentiable combinatorial optimization problems. Our results show that SB can efficiently discover polymer sequences with excellent adsorption performance within a reasonable computational time. Furthermore

it exhibits robust convergence and high parallel scalability across large design spaces. The approach developed in this work offers a new computational pathway for polymer structure optimization. It also lays a theoretical foundation for future extensions to topological design problems

such as optimizing the number and placement of side chains

as well as the co-optimization of sequence and topology.

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Keywords

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