Visualizing and Analyzing 3D Metal Nanowire Networks for Stretchable Electronics. Issue 8 (7th July 2020)
- Record Type:
- Journal Article
- Title:
- Visualizing and Analyzing 3D Metal Nanowire Networks for Stretchable Electronics. Issue 8 (7th July 2020)
- Main Title:
- Visualizing and Analyzing 3D Metal Nanowire Networks for Stretchable Electronics
- Authors:
- Forró, Csaba
Ihle, Stephan J.
Reichmuth, Andreas M.
Han, Hana
Stauffer, Flurin
Weaver, Sean
Bonnin, Anne
Stampanoni, Marco
Tybrandt, Klas
Vörös, János - Abstract:
- Abstract: Composites based on conductive nanowires embedded in elastomers are popular in a wide range of stretchable electronics applications where the requirements are either a stable or a highly increasing electrical resistance upon strain. Despite the widespread use of such composites, their production is not based in solid theoretical grounds but rather in empirical observations. The lack of such a framework is due to limitations in the methods for studying nanowire meshes, in particular the lack of knowledge on the spatial distribution of the nanowires and the change of their position under strain. This hurdle is overcome by collecting 3D reconstructed X‐ray tomographies of silver nanowires embedded in polydimethylsiloxane (PDMS) under variable deformations and the missing structural information of the nanomaterial is obtained by unsupervised artificial intelligence image analysis. This allowed to reveal the precise assembly mechanisms of nanowire systems and derive a precise analytical formula for the piezoresistive response of the composite and finally to simulate the behavior of arbitrary samples in‐silico. Abstract : A predictive model of the piezoresistive response of conductive nanowire‐meshes in elastomers has to include knowledge of nanowire arrangement and reorganization upon strain. The presented model is supported by high‐resolution reconstructed X‐ray tomography of the nanowire mesh and reproduces experimental piezoresistivity measurements. Additionally, aAbstract: Composites based on conductive nanowires embedded in elastomers are popular in a wide range of stretchable electronics applications where the requirements are either a stable or a highly increasing electrical resistance upon strain. Despite the widespread use of such composites, their production is not based in solid theoretical grounds but rather in empirical observations. The lack of such a framework is due to limitations in the methods for studying nanowire meshes, in particular the lack of knowledge on the spatial distribution of the nanowires and the change of their position under strain. This hurdle is overcome by collecting 3D reconstructed X‐ray tomographies of silver nanowires embedded in polydimethylsiloxane (PDMS) under variable deformations and the missing structural information of the nanomaterial is obtained by unsupervised artificial intelligence image analysis. This allowed to reveal the precise assembly mechanisms of nanowire systems and derive a precise analytical formula for the piezoresistive response of the composite and finally to simulate the behavior of arbitrary samples in‐silico. Abstract : A predictive model of the piezoresistive response of conductive nanowire‐meshes in elastomers has to include knowledge of nanowire arrangement and reorganization upon strain. The presented model is supported by high‐resolution reconstructed X‐ray tomography of the nanowire mesh and reproduces experimental piezoresistivity measurements. Additionally, a simulation framework is validated and provides exploratory possibilities for nanowire mesh design. … (more)
- Is Part Of:
- Advanced theory and simulations. Volume 3:Issue 8(2020)
- Journal:
- Advanced theory and simulations
- Issue:
- Volume 3:Issue 8(2020)
- Issue Display:
- Volume 3, Issue 8 (2020)
- Year:
- 2020
- Volume:
- 3
- Issue:
- 8
- Issue Sort Value:
- 2020-0003-0008-0000
- Page Start:
- n/a
- Page End:
- n/a
- Publication Date:
- 2020-07-07
- Subjects:
- machine learning -- nanocomposites -- nanowire networks -- piezo resistance
Science -- Simulation methods -- Periodicals
Science -- Methodology -- Periodicals
Engineering -- Simulation methods -- Periodicals
Engineering -- Methodology -- Periodicals
507.21 - Journal URLs:
- http://onlinelibrary.wiley.com/ ↗
- DOI:
- 10.1002/adts.202000038 ↗
- Languages:
- English
- ISSNs:
- 2513-0390
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 0696.935575
British Library DSC - BLDSS-3PM
British Library HMNTS - ELD Digital store - Ingest File:
- 13781.xml