A Comparative Study of the Electronic Transport and Gas-Sensitive Properties of Graphene+, T-graphene, Net-graphene, and Biphenylene-Based Two-Dimensional Devices

石墨烯 联苯 材料科学 石墨烯纳米带 分子 密度泛函理论 费米能级 费米能量 化学物理 碳纤维 纳米技术 计算化学 化学 亚苯基 电子 有机化学 物理 复合材料 量子力学 复合数 聚合物
作者
Luzhen Xie,Tong Chen,Xiansheng Dong,Guogang Liu,Hui Li,Ning Yang,Desheng Liu,Xianbo Xiao
出处
期刊:ACS Sensors [American Chemical Society]
卷期号:8 (9): 3510-3519 被引量:29
标识
DOI:10.1021/acssensors.3c01087
摘要

The electronic transport properties of the four carbon isomers: graphene+, T-graphene, net-graphene, and biphenylene, as well as the gas-sensing properties to the nitrogen-based gas molecules including NO2, NO, and NH3 molecules, are systematically studied and comparatively analyzed by combining the density functional theory with the nonequilibrium Green's function. The four carbon isomers are metallic, especially with graphene+ being a Dirac metal due to the two Dirac cones present at the Fermi energy level. The two-dimensional devices based on these four carbon isomers exhibit good conduction properties in the order of biphenylene > T-graphene > graphene+ > net-graphene. More interestingly, net-graphene-based and biphenylene-based devices demonstrate significant anisotropic transport properties. The gas sensors based on the above four structures all have good selectivity and sensitivity to the NO2 molecule, among which T-graphene-based gas sensors are the most prominent with a maximum ΔI value of 39.98 μA, being only three-fifths of the original. In addition, graphene+-based and biphenylene-based gas sensors are also sensitive to the NO molecule with maximum ΔI values of 29.42 and 25.63 μA, respectively. However, the four gas sensors are all physically adsorbed for the NH3 molecule. By the adsorption energy, charge transfer, electron localization functions, and molecular projection of self-consistent Hamiltonian states, the mechanisms behind all properties can be clearly explained. This work shows the potential of graphene+, T-graphene, net-graphene, and biphenylene for the detection of toxic molecules of NO and NO2.
最长约 10秒,即可获得该文献文件

科研通智能强力驱动
Strongly Powered by AbleSci AI
科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
刚刚
刚刚
李健的小迷弟应助lllll采纳,获得10
2秒前
空空发布了新的文献求助10
2秒前
2秒前
3秒前
羊1234发布了新的文献求助30
4秒前
4秒前
欢呼的井发布了新的文献求助10
4秒前
拂袖发布了新的文献求助10
4秒前
余国辉发布了新的文献求助10
5秒前
大个应助kiki采纳,获得10
6秒前
平淡的天宇完成签到,获得积分10
6秒前
京畿府尹完成签到,获得积分10
6秒前
天天快乐应助小帅采纳,获得10
6秒前
TTT发布了新的文献求助10
7秒前
7秒前
8秒前
9秒前
10秒前
科研通AI5应助羊1234采纳,获得30
10秒前
10秒前
空空完成签到,获得积分10
11秒前
小二郎应助chen采纳,获得30
11秒前
乐观黎云完成签到,获得积分10
11秒前
12秒前
认真一斩发布了新的文献求助10
12秒前
笨蛋琪露诺完成签到,获得积分10
13秒前
勤劳涵山发布了新的文献求助10
14秒前
Zhang发布了新的文献求助10
14秒前
HH发布了新的文献求助20
15秒前
无花果应助111采纳,获得10
15秒前
科研通AI2S应助明明采纳,获得10
15秒前
15秒前
bkagyin应助TTT采纳,获得10
16秒前
17秒前
喜悦彩虹发布了新的文献求助10
17秒前
科研通AI5应助叶青文采纳,获得10
17秒前
SciGPT应助一杯百事采纳,获得10
17秒前
小苏完成签到,获得积分10
18秒前
高分求助中
【此为提示信息,请勿应助】请按要求发布求助,避免被关 20000
Production Logging: Theoretical and Interpretive Elements 3000
J'AI COMBATTU POUR MAO // ANNA WANG 660
Izeltabart tapatansine - AdisInsight 600
Introduction to Comparative Public Administration Administrative Systems and Reforms in Europe, Third Edition 3rd edition 500
Geotechnical characterization of slope movements 500
Individualized positive end-expiratory pressure in laparoscopic surgery: a randomized controlled trial 400
热门求助领域 (近24小时)
化学 材料科学 医学 生物 工程类 有机化学 物理 生物化学 纳米技术 计算机科学 化学工程 内科学 复合材料 物理化学 电极 遗传学 量子力学 基因 冶金 催化作用
热门帖子
关注 科研通微信公众号,转发送积分 3753120
求助须知:如何正确求助?哪些是违规求助? 3296709
关于积分的说明 10095413
捐赠科研通 3011483
什么是DOI,文献DOI怎么找? 1653825
邀请新用户注册赠送积分活动 788485
科研通“疑难数据库(出版商)”最低求助积分说明 752854