Cellulose, a linear polymer of glucose residues, is the most abundant biopolymer on Earth. However, its inability to conduct electricity limits its applications in flexible electronics and energy storage devices. Here, we performed high-throughput first-principles computational screening to identify promising molecules for surface doping of cellulose nanocrystals (CNCs). We examined over 1600 molecules, including those from the TABS database, to find candidates for p-type and n-type doping. Our results identified several p-type dopants, such as hexacyano-trimethylene-cyclopropane (CN6-CP) and octacyanoquinodimethane (OCNQ). However, no suitable n-type dopants were found due to the low electron affinity of cellulose. We constructed atomic models of CNCs of cellulose Iα and Iβ crystals, showing how their electronic band structures depend on surface hydrogen bond reconstructions. We propose a novel mechanism for photocurrent generation in CNC Iα surfaces by manipulating the hydrogen bond network at the surfaces. The selection of potential p-type dopants was further refined through the first-principles calculations of the CNC models with molecular dopants adsorbed on the surface. Finally, we demonstrate that suitable surface functionalization can enhance the electron affinity of CNCs, partially overcoming the challenges of n-type doping.

中文翻译：

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纤维素纳米晶的分子表面掺杂：一项高通量计算研究


纤维素是一种葡萄糖残基的线性聚合物，是地球上含量最丰富的生物聚合物。然而，它的不导电能力限制了其在柔性电子和储能设备中的应用。在这里，我们进行了高通量第一性原理计算筛选，以确定用于纤维素纳米晶体 （CNC） 表面掺杂的有前途的分子。我们检查了 1600 多个分子，包括来自 TABS 数据库的分子，以寻找 p 型和 n 型掺杂的候选分子。我们的结果鉴定了几种 p 型掺杂剂，例如六氰基-三亚甲基-环丙烷 （CN6-CP） 和八氰基喹代二甲烷 （OCNQ）。然而，由于纤维素的电子亲和力低，没有找到合适的 n 型掺杂剂。我们构建了纤维素 Iα 和 Iβ 晶体的 CNC 原子模型，展示了它们的电子能带结构如何依赖于表面氢键重建。我们提出了一种通过操纵表面氢键网络在 CNC Iα 表面产生光电流的新机制。通过分子掺杂剂吸附在表面的 CNC 模型的第一性原理计算，进一步细化了潜在 p 型掺杂剂的选择。最后，我们证明合适的表面功能化可以增强 CNC 的电子亲和力，部分克服了 n 型掺杂的挑战。