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1.
Nanotechnology ; 35(33)2024 May 31.
Article in English | MEDLINE | ID: mdl-38772350

ABSTRACT

Single-molecule detection technology is a technique capable of detecting molecules at the single-molecule level, characterized by high sensitivity, high resolution, and high specificity. Nanopore technology, as one of the single-molecule detection tools, is widely used to study the structure and function of biomolecules. In this study, we constructed a small-sized nanopore with a pore-cavity-pore structure, which can achieve a higher reverse capture rate. Through simulation, we investigated the electrical potential distribution of the nanopore with a pore-cavity-pore structure and analyzed the influence of pore size on the potential distribution. Accordingly, different pore sizes can be designed based on the radius of gyration of the target biomolecules, restricting their escape paths inside the chamber. In the future, nanopores with a pore-cavity-pore structure based on two-dimensional thin film materials are expected to be applied in single-molecule detection research, which provides new insights for various detection needs.


Subject(s)
DNA , Nanopores , DNA/chemistry , Nanotechnology/methods , Single Molecule Imaging/methods
2.
IEEE Trans Cybern ; 52(6): 5113-5123, 2022 Jun.
Article in English | MEDLINE | ID: mdl-33112756

ABSTRACT

This article addresses the quantitative fault diagnosability evaluation for dynamic systems without distribution knowledge. The system dynamics in different cases are first characterized by mean vectors and covariance matrices. Then, fault detectability and isolability are defined based on the constructed characteristics. On this basis, the Mahalanobis distance (MD) is employed to propose a fault diagnosability analysis measure. Furthermore, model-based and data-driven algorithms for fault diagnosability evaluation are given according to the MD-based measure. In addition, the reliabilities of the evaluation results are considered by taking advantage of ambiguity sets of mean vectors and covariance matrices of the system dynamics. Finally, two examples are employed to verify the effectiveness of the proposed algorithms.

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