Density functional theory study of silicon nanowires functionalized by grafting organic molecules

Functionalizing Silicon Nanowires (SiNWs) through covalent attachment of organic molecules offers diverse advantages, including surface passivation, introduction of new functionalities, and enhanced material performance in applications like electronic devices and biosensors. Given the wide range of available functional molecules, systematic large-scale screening is crucial. Therefore, we developed an automated computational workflow using Python scripts in conjunction with the AiiDa framework to explore structural configurations of functional molecules adsorbed onto silicon surfaces. This workflow generates multiple adhesion configurations corresponding to different binding orientations using surface and functional molecule structures as inputs. This dataset contains data related to the structural optimization of molecules with single, double, and triple carbon-carbon bonds attached to the nanowire surface in various adhesion configurations. We describe the chemisorption on SiNWs using the slab models for the Si facets since our reference are samples with diameters of SiNWs around 50 nm, while the quantum confinement effects are important for diameters below 10 nm. For each configuration, structural characterization was conducted by calculating quantities including the bond distance between the two carbons closest to the surface and their respective bond angle relative to the z-axis, the carbon-silicon bond distance and its respective bond angle relative to the z-axis, along with the molecule's rotation angle in the xy plane. The values obtained are summarized in the main folder. The version v1 of dataset contains data related to the Si(111) surface and alkanes, alkenes, and alkynes with lengths from C2 to C10. The version v2 and v3 include also the moieties from C12 to C18. This version (v4) extends the dataset with the data related to the Si(110) surface and alkanes, alkenes, and alkynes with lengths from C2 to C18. For each system the most stable configuration will be identified, and the analysis of the electronic properties will be conducted.

通过有机分子共价接枝功能化硅纳米线（Silicon Nanowires, SiNWs）具有多重显著优势，包括表面钝化、引入全新功能属性，以及在电子器件、生物传感器等应用场景中提升材料综合性能。鉴于可选用的功能分子品类丰富，系统性大规模筛选工作至关重要。为此，我们开发了一套自动化计算流程，依托Python脚本结合AiiDa框架，探究吸附于硅表面的功能分子的结构构型。该流程以表面与功能分子的结构作为输入，可生成对应不同结合取向的多种吸附构型。本数据集涵盖了以单、双、三碳-碳键连接的分子，以多种吸附构型接枝于纳米线表面的结构优化相关数据。由于我们的参考样品硅纳米线直径约为50 nm，且量子限域效应仅在直径小于10 nm时才具备显著影响，因此我们采用硅晶面的平板模型来描述硅纳米线表面的化学吸附过程。针对每种构型，我们通过计算多项参数完成结构表征：包括最接近表面的两个碳原子间的键长及其相对于z轴的键角、碳-硅键长及其相对于z轴的键角，以及分子在xy平面内的旋转角。所得计算结果已汇总至主文件夹中。数据集v1版本包含Si(111)晶面以及碳链长度为C2至C10的烷烃、烯烃和炔烃相关数据。v2与v3版本额外补充了C12至C18的官能团相关数据。本版本（v4）进一步扩展了数据集，新增了Si(110)晶面以及碳链长度为C2至C18的烷烃、烯烃和炔烃相关数据。后续将针对每个体系确定最稳定构型，并开展电子性质分析。