Magneto-Electroluminescence in ITO/MEH-PPV:PEO:LiCF3SO3/Al Polymer Light-Emitting Electrochemical Cells

Zhu, Ming; Yuan, X. Q.; Ni, Gang

doi:10.3390/mi10080546

Cited by 4 publications

(3 citation statements)

References 29 publications

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“…Interestingly, many conjugated light-emitting polymers are hole conductive and show low electron mobility, therefore having low efficiency . However, doping of an electron transport material can enhance the efficiency of these polymers. − Careful selection of these dopants and their concentration, in the blended polymer, improves both the carrier injection and transport properties of the semiconducting polymer. , …”

Section: Introductionmentioning

confidence: 99%

Excitation Energy Transfer/Migration between Tris(8-hydroxyquinoline) Aluminum and Poly[2-methoxy-5-(2-ethylhexyloxy)-1,4-phenylenevinylene] in Chloroform

et al. 2020

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Excitation energy transfer/migration between fluorescent electron transport molecule tris(8-hydroxyquinoline) aluminum (donor) and fluorescent hole transport polymer poly[2-methoxy-5-(2-ethylhexyloxy)-1,4-phenylenevinylene] (acceptor) were studied in chloroform solution at room temperature using steady-state and time-domain fluorescence measurements. The blend of this pair is widely used in the fabrication of organic light-emitting diode. The considerable overlap integral between the emission spectrum of donor and absorption spectrum of acceptor indicates high donor−acceptor interaction, and the effective enhancement of the acceptor fluorescence along with a decrease in fluorescence intensity of donor by exciting the donor states characterized the excitation energy transfer between them. Relatively faster decay of donor in the presence of a higher concentration of acceptor followed the Forster kind of long-range fluorescence resonance energy transfer, which is illustrated by the agreement in the values of the energy transfer parameters observed from the fluorescence decay analysis and the values calculated from the spectral overlap. However, at lower acceptor concentrations, the excitation energy migration and diffusion/intrachain interaction influence the kinetics, resulting in a significant difference in the observed and calculated value of the energy transfer parameters. The influence of intrachain and interchain interactions during nonradiative excitation energy transfer is confirmed by the donor and acceptor decay dynamics on increasing acceptor concentration in donor−acceptor solution. No evidence of excimer formation is noticed in the donor−acceptor solution.

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Section: Introductionmentioning

confidence: 99%

Excitation Energy Transfer/Migration between Tris(8-hydroxyquinoline) Aluminum and Poly[2-methoxy-5-(2-ethylhexyloxy)-1,4-phenylenevinylene] in Chloroform

et al. 2020

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“…When a voltage pulse (presynaptic spike) is applied at the electrode, the p−i−n junction is formed, resulting from the redox reaction, which promotes photons emission through the recombination of electron−hole pairs. 40 A typical EL spectrum of the synaptic device is shown in Figure 2g, which indicates that the EL peak is at the wavelength of ∼540 nm, which is the emission wavelength for MEH-PPV. The normalized EL spectrum under the applied voltage from 4 to 6 V is shown in Figure S3, in which the amplitude of the peak increases with the increase of applied voltage, while the peak positions are quite stable.…”

mentioning

confidence: 98%

“…The structure of MXene can be observed by SEM (Figure f). When a voltage pulse (presynaptic spike) is applied at the electrode, the p–i–n junction is formed, resulting from the redox reaction, which promotes photons emission through the recombination of electron–hole pairs . A typical EL spectrum of the synaptic device is shown in Figure g, which indicates that the EL peak is at the wavelength of ∼540 nm, which is the emission wavelength for MEH-PPV.…”

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confidence: 99%

Artificial Tactile Sensing System with Photoelectric Output for High Accuracy Haptic Texture Recognition and Parallel Information Processing

et al. 2022

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Developing multifunctional artificial sensory systems is an important task for constructing future artificial neural networks. A system with multisignal output capability is highly required by the rising demand for high-throughput data processing in the Internet of Things (IoT) society. Here, a novel dual-output artificial tactile sensing (DOATS) system with parallel output of photoelectric signals was proposed. Because of the ionic−electronic coupling mechanism in lightemitting synaptic (LES) devices in the DOATS system, modulating electric current and light emission can coexist through ion accumulation and electron−hole recombination. As a result, the DOATS system can realize the simulation of human tactile information, and the recognition of 16 kinds of fabrics was demonstrated with an accuracy rate of 94.1%. A photoelectric hybrid artificial neural network was proposed, which achieved efficient and accurate multitask operation. The DOATS system proposed in this work is promising for implementing photoelectric hybrid neural network and promoting the development of interactive artificial intelligence.

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Towards mixed physical node reservoir computing: light-emitting synaptic reservoir system with dual photoelectric output

Lian,

Gao,

Lin

et al. 2024

Light Sci Appl

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Memristor-based physical reservoir computing holds significant potential for efficiently processing complex spatiotemporal data, which is crucial for advancing artificial intelligence. However, owing to the single physical node mapping characteristic of traditional memristor reservoir computing, it inevitably induces high repeatability of eigenvalues to a certain extent and significantly limits the efficiency and performance of memristor-based reservoir computing for complex tasks. Hence, this work firstly reports an artificial light-emitting synaptic (LES) device with dual photoelectric output for reservoir computing, and a reservoir system with mixed physical nodes is proposed. The system effectively transforms the input signal into two eigenvalue outputs using a mixed physical node reservoir comprising distinct physical quantities, namely optical output with nonlinear optical effects and electrical output with memory characteristics. Unlike previously reported memristor-based reservoir systems, which pursue rich reservoir states in one physical dimension, our mixed physical node reservoir system can obtain reservoir states in two physical dimensions with one input without increasing the number and types of devices. The recognition rate of the artificial light-emitting synaptic reservoir system can achieve 97.22% in MNIST recognition. Furthermore, the recognition task of multichannel images can be realized through the nonlinear mapping of the photoelectric dual reservoir, resulting in a recognition accuracy of 99.25%. The mixed physical node reservoir computing proposed in this work is promising for implementing the development of photoelectric mixed neural networks and material-algorithm collaborative design.

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Magneto-Electroluminescence in ITO/MEH-PPV:PEO:LiCF3SO3/Al Polymer Light-Emitting Electrochemical Cells

Cited by 4 publications

References 29 publications

Excitation Energy Transfer/Migration between Tris(8-hydroxyquinoline) Aluminum and Poly[2-methoxy-5-(2-ethylhexyloxy)-1,4-phenylenevinylene] in Chloroform

Excitation Energy Transfer/Migration between Tris(8-hydroxyquinoline) Aluminum and Poly[2-methoxy-5-(2-ethylhexyloxy)-1,4-phenylenevinylene] in Chloroform

Artificial Tactile Sensing System with Photoelectric Output for High Accuracy Haptic Texture Recognition and Parallel Information Processing

Towards mixed physical node reservoir computing: light-emitting synaptic reservoir system with dual photoelectric output

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