RESUMO
The ability to precisely regulate the size of a nanogap is essential for establishing high-yield molecular junctions, and it is crucial for the control of optical signals in extreme optics. Although remarkable strategies for the fabrication of nanogaps are proposed, wafer-compatible nanogaps with freely adjustable gap sizes are not yet available. Herein, two approaches for constructing in situ adjustable metal gaps are proposed which allow Ångstrom modulation resolution by employing either a lateral expandable piezoelectric sheet or a stretchable membrane. These in situ adjustable nanogaps are further developed into in-plane molecular break junctions, in which the gaps can be repeatedly closed and opened thousands of times with self-assembled molecules. The conductance of the single 1,4-benzenediamine (BDA) and the BDA molecular dimer is successfully determined using the proposed strategy. The measured conductance agreeing well with the data by employing another well-established scanning tunneling microscopy break junction technique provides insight into the formation of molecule dimer via hydrogen bond at single molecule level. The wafer-compatible nanogaps and in-plane dynamical break-junctions provide a potential approach to fabricate highly compacted devices using a single molecule as a building block and supply a promising in-plane technique to address the dynamical properties of single molecules.
RESUMO
BACKGROUND: Haemorrhagic stroke accounts for approximately 31.52% of all stroke cases, and the most common origin is hypertension. However, little is known about the method to identify high-risk populations of hypertensive intracerebral haemorrhage. RESULTS: The results showed that the angle between the middle cerebral artery and the internal carotid artery (AMIC), the distance between the beginning of the median artery and superior trunk (DMS), and the density (CT value) of the lenticulostriate artery (CTL) were statistically significant enough to cause intracerebral haemorrhage. In addition, we chose these three potential features for the ensemble learning classification model. Our developed ensemble-learning method outperforms not only previous work but also three other classic classification methods based on accuracy measurements. CONCLUSIONS: The developed mathematical model in the present study is efficient in predicting the probability of intracerebral haemorrhage.
