Suppr超能文献

铱(Ir)和锇(Os)修饰的BP/BSe异质结构作为用于检测HS、SOF和SOF气体的有前景的纳米级分子传感器:密度泛函理论展望。

Iridium (Ir) and osmium (Os) modified BP/BSe heterostructures as promising nanoscale molecule sensors for detection of HS, SOF and SOF gases: a DFT outlook.

作者信息

Abbasi Amirali

机构信息

Department of Chemistry Education, Farhangian University P.O. Box 14665-889 Tehran Iran

出版信息

Nanoscale Adv. 2025 Jun 24;7(16):5019-5030. doi: 10.1039/d5na00266d. eCollection 2025 Aug 5.

Abstract

A density functional theory approach was utilized to gain insights into the electronic properties and optimized structures of the novel Ir and Os modified BP/BSe heterostructures as gas sensing substrates for the detection of HS, SOF and SOF molecules. The band gap of 1.20 eV represents the excellent semiconducting properties of the BP/BSe heterostructure. The formation energies for the most stable structures of Ir and Os modified BP/BSe systems were calculated to be -3.17 eV and -1.92 eV, respectively, indicating the significant geometric stability of the studied heterostructures. The optimized Ir-Se and Os-Se bond lengths were measured to be 2.51 Å and 2.46 Å, respectively. The considered HS, SOF and SOF molecules were strongly chemisorbed on the Ir modified BP/BSe heterostructures. The highest adsorption energy of -2.97 eV was observed for SOF molecules, which show dissociative adsorption with S-F bond cleavage. The newly formed Ir-F bond lengths were calculated to be 1.98 Å. The important objective of this research is to design an innovative BP/BSe heterostructure based sensor device for the detection of HS, SOF and SOF molecules.

摘要

采用密度泛函理论方法,以深入了解新型铱(Ir)和锇(Os)修饰的BP/BSe异质结构作为用于检测HS、SOF和SOF分子的气敏底物的电子性质和优化结构。1.20 eV的带隙代表了BP/BSe异质结构优异的半导体性质。计算得出Ir和Os修饰的BP/BSe体系最稳定结构的形成能分别为-3.17 eV和-1.92 eV,表明所研究的异质结构具有显著的几何稳定性。测得优化后的Ir-Se和Os-Se键长分别为2.51 Å和2.46 Å。所考虑的HS、SOF和SOF分子强烈化学吸附在Ir修饰的BP/BSe异质结构上。SOF分子的最高吸附能为-2.97 eV,表现出S-F键断裂的解离吸附。计算得出新形成的Ir-F键长为1.98 Å。本研究的重要目标是设计一种用于检测HS、SOF和SOF分子的创新型基于BP/BSe异质结构的传感器装置。

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验