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1.
Sci Rep ; 9(1): 11550, 2019 Aug 09.
Artigo em Inglês | MEDLINE | ID: mdl-31399603

RESUMO

Networks of metallic nanowires have the potential to meet the needs of next-generation device technologies that require flexible transparent conductors. At present, there does not exist a first principles model capable of predicting the electro-optical performance of a nanowire network. Here we combine an electrical model derived from fundamental material properties and electrical equations with an optical model based on Mie theory scattering of light by small particles. This approach enables the generation of analogues for any nanowire network and then accurately predicts, without the use of fitting factors, the optical transmittance and sheet resistance of the transparent electrode. Predictions are validated using experimental data from the literature of networks comprised of a wide range of aspect ratios (nanowire length/diameter). The separation of the contributions of the material resistance and the junction resistance allows the effectiveness of post-deposition processing methods to be evaluated and provides a benchmark for the minimum attainable sheet resistance. The predictive power of this model enables a material-by-design approach, whereby suitable systems can be prescribed for targeted technology applications.

2.
Sci Rep ; 9(1): 11738, 2019 Aug 13.
Artigo em Inglês | MEDLINE | ID: mdl-31409846

RESUMO

Considerable attention has been drawn to the lead halide perovskites (LHPs) because of their outstanding optoelectronic characteristics. LHP nanosheets (NSs) grown from single crystalline lead halide possess advantages in device applications as they provide the possibility for control over morphology, composition, and crystallinity. Here, free-standing lead bromide (PbBr2) single-crystalline NSs with sizes up to one centimeter are synthesized from solution. These NSs can be converted to LHP while maintaining the NS morphology. We demonstrate that these perovskite NSs can be processed directly for fabrication of photodetector and laser arrays on a large scale. This strategy will allow high-yield synthesis of large-size perovskite NSs for functional devices in an integrated photonics platform.

3.
Nat Commun ; 9(1): 3219, 2018 08 13.
Artigo em Inglês | MEDLINE | ID: mdl-30104665

RESUMO

Nanowire networks are promising memristive architectures for neuromorphic applications due to their connectivity and neurosynaptic-like behaviours. Here, we demonstrate a self-similar scaling of the conductance of networks and the junctions that comprise them. We show this behavior is an emergent property of any junction-dominated network. A particular class of junctions naturally leads to the emergence of conductance plateaus and a "winner-takes-all" conducting path that spans the entire network, and which we show corresponds to the lowest-energy connectivity path. The memory stored in the conductance state is distributed across the network but encoded in specific connectivity pathways, similar to that found in biological systems. These results are expected to have important implications for development of neuromorphic devices based on reservoir computing.

4.
ACS Appl Mater Interfaces ; 9(44): 38959-38966, 2017 Nov 08.
Artigo em Inglês | MEDLINE | ID: mdl-29027461

RESUMO

Nonpolar resistive switching (RS), a combination of bipolar and unipolar RS, is demonstrated for the first time in a single nanowire (NW) system. Exploiting Ag@TiO2 core-shell (CS) NWs synthesized by postgrowth shell formation, the switching mode is controlled by adjusting the current compliance effectively, tailoring the electrical polarity response. We demonstrate ON/OFF ratios of 105 and 107 for bipolar and unipolar modes, respectively. In the bipolar regime, retention times could be controlled up to 103 s, and in the unipolar mode, >106 s was recorded. We show how the unique dual-mode switching behavior is enabled by the defect-rich polycrystalline material structure of the TiO2 shell and the interaction between the Ag core and the Ag electrodes. These results provide a foundation for engineering nonpolar RS behaviors for memory storage and neuromorphic applications in CSNW structures.

5.
Phys Chem Chem Phys ; 18(39): 27564-27571, 2016 Oct 05.
Artigo em Inglês | MEDLINE | ID: mdl-27722404

RESUMO

Motivated by numerous technological applications, there is current interest in the study of the conductive properties of networks made of randomly dispersed nanowires. The sheet resistance of such networks is normally calculated by numerically evaluating the conductance of a system of resistors but due to disorder and with so many variables to account for, calculations of this type are computationally demanding and may lack mathematical transparency. Here we establish the equivalence between the sheet resistance of disordered networks and that of a regular ordered network. Rather than through a fitting scheme, we provide a recipe to find the effective medium network that captures how the resistance of a nanowire network depends on several different parameters such as wire density, electrode size and electrode separation. Furthermore, the effective medium approach provides a simple way to distinguish the sheet resistance contribution of the junctions from that of the nanowires themselves. The contrast between these two contributions determines the potential to optimize the network performance for a particular application.

6.
ACS Nano ; 9(11): 11422-9, 2015 Nov 24.
Artigo em Inglês | MEDLINE | ID: mdl-26448205

RESUMO

Networks of silver nanowires appear set to replace expensive indium tin oxide as the transparent conducting electrode material in next generation devices. The success of this approach depends on optimizing the material conductivity, which until now has largely focused on minimizing the junction resistance between wires. However, there have been no detailed reports on what the junction resistance is, nor is there a known benchmark for the minimum attainable sheet resistance of an optimized network. In this paper, we present junction resistance measurements of individual silver nanowire junctions, producing for the first time a distribution of junction resistance values and conclusively demonstrating that the junction contribution to the overall resistance can be reduced beyond that of the wires through standard processing techniques. We find that this distribution shows the presence of a small percentage (6%) of high-resistance junctions, and we show how these may impact the performance of network-based materials. Finally, through combining experiment with a rigorous model, we demonstrate the important role played by the network skeleton and the specific connectivity of the network in determining network performance.

7.
Nanoscale ; 7(30): 13011-6, 2015 Aug 14.
Artigo em Inglês | MEDLINE | ID: mdl-26169222

RESUMO

In this work, we introduce a combined experimental and computational approach to describe the conductivity of metallic nanowire networks. Due to their highly disordered nature, these materials are typically described by simplified models in which network junctions control the overall conductivity. Here, we introduce a combined experimental and simulation approach that involves a wire-by-wire junction-by-junction simulation of an actual network. Rather than dealing with computer-generated networks, we use a computational approach that captures the precise spatial distribution of wires from an SEM analysis of a real network. In this way, we fully account for all geometric aspects of the network, i.e. for the properties of the junctions and wire segments. Our model predicts characteristic junction resistances that are smaller than those found by earlier simplified models. The model outputs characteristic values that depend on the detailed connectivity of the network, which can be used to compare the performance of different networks and to predict the optimum performance of any network and its scope for improvement.

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