| 1. |
|
|
| 2. |
- He, Yuhui, et al.
(författare)
-
Salt-Gradient Approach for Regulating Capture-to-Translocation Dynamics of DNA with Nanochannel Sensors
- 2016
-
Ingår i: ACS Sensors. - : American Chemical Society (ACS). - 2379-3694. ; 1:6, s. 807-816
-
Tidskriftsartikel (refereegranskat)abstract
- Understanding the physical mechanisms that govern the ion and fluidic transport in salt-concentration-based nanochannel/nanopore systems is essential for the potential applications in bioanalysis. One central challenge is to interpret the observed four-stage change from osmosis to the reverse one with increasing salt gradient. Here we provide a unified model that outlines the intriguing role of two competing factors, the exclusion- and diffusion-induced electrical potentials. We demonstrate theoretically a direction control of a hydrodynamic flow via the salt gradient. Based on this, we also propose a salt-gradient approach for regulating DNA motion in nanochannels that enables voltage-free single-molecule capture with a significantly low translocation speed. The present method would be used as a useful protocol to overcome the key hurdle of tailoring the capture-to-translocation dynamics of polynucleotides for nanopore sequencing.
|
|
| 3. |
- Wang, Kuan, et al.
(författare)
-
Threshold switching memristor-based stochastic neurons for probabilistic computing
- 2021
-
Ingår i: Materials Horizons. - : Royal Society of Chemistry. - 2051-6347 .- 2051-6355. ; 8:2, s. 619-629
-
Tidskriftsartikel (refereegranskat)abstract
- Biological neurons exhibit dynamic excitation behavior in the form of stochastic firing, rather than stiffly giving out spikes upon reaching a fixed threshold voltage, which empowers the brain to perform probabilistic inference in the face of uncertainty. However, owing to the complexity of the stochastic firing process in biological neurons, the challenge of fabricating and applying stochastic neurons with bio-realistic dynamics to probabilistic scenarios remains to be fully addressed. In this work, a novel CuS/GeSe conductive-bridge threshold switching memristor is fabricated and singled out to realize electronic stochastic neurons, which is ascribed to the similarity between the stochastic switching behavior observed in the device and that of biological ion channels. The corresponding electric circuit of a stochastic neuron is then constructed and the probabilistic firing capacity of the neuron is utilized to implement Bayesian inference in a spiking neural network (SNN). The application prospects are demonstrated on the example of a tumor diagnosis task, where common fatal diagnostic errors of a conventional artificial neural network are successfully circumvented. Moreover, in comparison to deterministic neuron-based SNNs, the stochastic neurons enable SNNs to deliver an estimate of the uncertainty in their predictions, and the fidelity of the judgement is drastically improved by 81.2%.
|
|
| 4. |
- Zhang, Pan, et al.
(författare)
-
Nanochannel-Based Transport in an Interfacial Memristor Can Emulate the Analog Weight Modulation of Synapses
- 2019
-
Ingår i: Nano letters (Print). - : AMER CHEMICAL SOC. - 1530-6984 .- 1530-6992. ; 19:7, s. 4279-4286
-
Tidskriftsartikel (refereegranskat)abstract
- By exploiting novel transport phenomena such as ion selectivity at the nanoscale, it has been shown that nanochannel systems can exhibit electrically controllable conductance, suggesting their potential use in neuromorphic devices. However, several critical features of biological synapses, particularly their conductance modulation, which is both memorable and gradual, have rarely been reported in these types of systems due to the fast flow property of typical inorganic electrolytes. In this work, we demonstrate that electrically manipulating the nanochannel conductance can result in nonvolatile conductance tuning capable of mimicking the analog behavior of synapses by introducing a room-temperature ionic liquid (IL) and a KCl solution into the two ends of a nanochannel system. The gradual conductance-tuning mechanism is identified through fluorescence measurements as the voltage-induced movement of the interface between the immiscible IL and KCl solution, while the successful memorization of the conductance tuning is ascribed to the large viscosity of the IL. We applied a nanochannel-based synapse to a handwritten digit-recognition task, reaching an accuracy of 94%. These promising results provide important guidance for the future design of nanochannel-based neuromorphic devices and the manipulation of nanochannel transport for computing.
|
|
