Evidence map›Paper›PMID 32313264›Full record

ArticleNature materials2020

Modelling electrical conduction in nanostructure assemblies through complex networks.

Heming Yao, Ya-Ping Hsieh, Jing Kong, Mario Hofmann

Abstract read
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In one paragraph

Article in Nature materials, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

5 citing papers in PubMed.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Heming YaoDepartment of Electrical and Electronic Engineering, The University of Hong Kong, Hong Kong, China.ORCID http://orcid.org/0000-0003-2814-9539
Ya-Ping HsiehInstitute for Atomic and Molecular Sciences, Academia Sinica, Taipei, Taiwan. yphsieh@gate.sinica.edu.tw.ORCID http://orcid.org/0000-0002-6065-751X
Jing KongDepartment of Electrical Engineering and Computer Science, Massachusetts Institute of Technology, Cambridge, MA, USA.
Mario HofmannDepartment of Physics, National Taiwan University, Taipei, Taiwan. mario@phys.ntu.edu.tw.ORCID http://orcid.org/0000-0003-1946-2478

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Carrier transport processes in assemblies of nanostructures rely on morphology-dependent and hierarchical conduction mechanisms, whose complexity cannot be captured by current modelling approaches. Here we apply the concept of complex networks to modelling carrier conduction in such systems. The approach permits assignment of arbitrary connectivity and connection strength between assembly constituents and is thus ideal for nanostructured films, composites and other geometries. Modelling of simplified rod-like nanostructures is consistent with analytical solutions, whereas results for more realistic nanostructure assemblies agree with experimental data and reveal conduction behaviour not captured by previous models. Fitting of ensemble measurements also allows the conduction properties of individual constituents to be extracted, which are subsequently used to guide the realization of transparent electrodes with improved performance. A global optimization process was employed to identify geometries and properties with high potential for transparent conductors. Our intuitive discretization approach, combined with a simple solver tool, allows researchers with little computational experience to carry out realistic simulations.

Indexed as

Electric ConductivityModels, ChemicalComputer SimulationModels, MolecularNanostructures

Identifiers

What OpenQuestion holds

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Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.