Li Hongfei, Chen Yazhou, Zhou Linsen, Xie Zun, Cao Wei, Qu Zhaoming
National Key Laboratory on Electromagnetic Environment Effects, Army Engineering University of PLA Shijiazhuang 050003 China
Institute of Materials, China Academy of Engineering Physics Mianyang 621907 China.
RSC Adv. 2025 May 28;15(22):17711-17719. doi: 10.1039/d5ra00705d. eCollection 2025 May 21.
Polymer/graphene (Py/GN) composites under the influence of external electric fields often exhibit unique nonlinear conducting behaviors. However, the underlying mechanism of this field effect at the molecular level is still obscure until now. Herein, the evolution of electrical properties of Py/GN composites induced by electric fields has been explored by combining high-throughput first-principles calculations with machine learning models. The results show that the polymer valence band maximum (PVBM) and polymer conduction band minimum (PCBM) of Py/GN composites under different electric fields can be accurately predicted by the XGBoost regression algorithm. The band arrangement of polymers in Py/GN composites can be easily altered with applied electric fields, where charges accumulate around the graphene layer and depleted around the polymer layer. Moreover, the electrons at the pyrrole/GN interface may overcome the Schottky barrier height, leading to a transition from a Schottky contact to an ohmic contact under a critical field ( ), which can be effectively predicted with an value of 0.854. Then, two types of novel Py/GN composites with lower or higher values were screened by reverse engineering the ML model, offering valuable guidance for the application of Py/GN composites in different electric field conditions. This work can provide new insights into the nonlinear electrical response of Py/GN composites under electric fields, which has significant implications for practical applications.
聚合物/石墨烯（Py/GN）复合材料在外部电场作用下通常表现出独特的非线性导电行为。然而，迄今为止，这种场效应在分子水平上的潜在机制仍不清楚。在此，通过将高通量第一性原理计算与机器学习模型相结合，探索了电场诱导的Py/GN复合材料电学性质的演变。结果表明，利用XGBoost回归算法可以准确预测不同电场下Py/GN复合材料的聚合物价带最大值（PVBM）和聚合物导带最小值（PCBM）。施加电场时，Py/GN复合材料中聚合物的能带排列很容易改变，电荷在石墨烯层周围积累，在聚合物层周围耗尽。此外，吡咯/GN界面处的电子可能会克服肖特基势垒高度，导致在临界场（ ）下从肖特基接触转变为欧姆接触，其 值为0.854时可有效预测。然后，通过对机器学习模型进行逆向工程，筛选出了两种具有较低或较高 值的新型Py/GN复合材料，为Py/GN复合材料在不同电场条件下的应用提供了有价值的指导。这项工作可以为Py/GN复合材料在电场下的非线性电响应提供新的见解，对实际应用具有重要意义。
