List of Journal Publications
2024
2.
Grazioli, D., Gangi, G., Nicola, L., Simone, A.
Predicting mechanical and electrical failure of nanowire networks in flexible transparent electrodes Journal Article
In: COMPOSITES SCIENCE AND TECHNOLOGY, vol. 245, no. 110304, 2024.
Abstract | BibTeX | Tags: electrodes, nanowires | Links:
@article{D.2024,
title = {Predicting mechanical and electrical failure of nanowire networks in flexible transparent electrodes},
author = {D. Grazioli and G. Gangi and L. Nicola and A. Simone},
doi = {https://doi.org/10.1016/j.compscitech.2023.110304},
year = {2024},
date = {2024-01-05},
urldate = {2024-01-05},
journal = {COMPOSITES SCIENCE AND TECHNOLOGY},
volume = {245},
number = {110304},
abstract = {Flexible transparent electrodes employing metal nanowires (NWs) find extensive use in various applications such as optoelectronic devices, solar cells, light-emitting diodes, and transparent heaters. NW networks in flexible transparent electrodes can withstand mechanical deformations and conduct electricity but are susceptible to localized damage caused by mechanical stress and current density concentration. This localized damage ultimately results in electrode failure. Our study aims to track locally induced damage from both mechanical and electrical sources and assess their collective influence on electrode performance until failure occurs. To this end, we create two-dimensional digital samples that represent the NW networks, transform them into beam networks and equivalent resistor networks, and perform finite element simulations of the mechanical and electrical network responses while varying the NW content.
Our simulations reveal crack-like patterns in the distribution of damaged elements at network failure that depend on the process inducing the damage. While our results suggest that the impact of electrically induced damage on overall network stability is more significant than that of mechanically induced damage, the latter must not be ignored.},
keywords = {electrodes, nanowires},
pubstate = {published},
tppubtype = {article}
}
Flexible transparent electrodes employing metal nanowires (NWs) find extensive use in various applications such as optoelectronic devices, solar cells, light-emitting diodes, and transparent heaters. NW networks in flexible transparent electrodes can withstand mechanical deformations and conduct electricity but are susceptible to localized damage caused by mechanical stress and current density concentration. This localized damage ultimately results in electrode failure. Our study aims to track locally induced damage from both mechanical and electrical sources and assess their collective influence on electrode performance until failure occurs. To this end, we create two-dimensional digital samples that represent the NW networks, transform them into beam networks and equivalent resistor networks, and perform finite element simulations of the mechanical and electrical network responses while varying the NW content.
Our simulations reveal crack-like patterns in the distribution of damaged elements at network failure that depend on the process inducing the damage. While our results suggest that the impact of electrically induced damage on overall network stability is more significant than that of mechanically induced damage, the latter must not be ignored.
Our simulations reveal crack-like patterns in the distribution of damaged elements at network failure that depend on the process inducing the damage. While our results suggest that the impact of electrically induced damage on overall network stability is more significant than that of mechanically induced damage, the latter must not be ignored.
2023
1.
Grazioli, D., Dadduzio, Alberto C, Roso, Martina, Simone, A.
Quantitative electrical homogeneity assessment of nanowire transparent electrodes Journal Article
In: NANOSCALE, vol. 15, no. 14, pp. 6770–6784, 2023.
Abstract | BibTeX | Tags: electrodes, nanowires | Links:
@article{Grazioli2023,
title = {Quantitative electrical homogeneity assessment of nanowire transparent electrodes},
author = {D. Grazioli and Alberto C Dadduzio and Martina Roso and A. Simone},
doi = {10.1039/d2nr06564a},
year = {2023},
date = {2023-01-01},
journal = {NANOSCALE},
volume = {15},
number = {14},
pages = {6770–6784},
publisher = {ROYAL SOC CHEMISTRY},
abstract = {The homogeneous distribution of electric current (electrical homogeneity) is not guaranteed in nanowire electrodes but is crucial for the stability of the electrode and actually desirable in most applications. Despite the relevance of this feature, it is common practice to perform qualitative assessments at the electrode scale, thus masking local effects. To address this issue, we have developed a computational strategy to aid in the design of nanowire electrodes with improved electrical homogeneity. Nanowire electrodes are modeled as two-dimensional networks of stick and junction resistors (with resistance R-w and R-j, respectively) to simulate the electric conduction process. Electrodes are discretized into regular grids of squares and the electrical power of the network contained in each square is computed. The mismatch between the areal power density of the entire electrode and that of the squares provides a quantitative electrical homogeneity evaluation. Repeating the analysis with squares of different size yields an evaluation that spans across length scales. A scalar indicator, coined the homogeneity index, summarizes the results of the multiscale evaluation. The proposed strategy is employed to assess the electrical homogeneity of silver nanowire electrodes through the analysis of scanning electron microscopy images. Our results agree with the outcomes of the experimental assessment performed on the same electrodes. Parametric studies are performed by varying nanowire content and nanowire-to-junction resistance ratio R-w/R-j. We observe that a significant reduction of contact resistance is not necessary to ensure a high degree of homogeneity. The ideal condition of negligible junction resistance (R-w >> R-j) leads to the best-case scenario, a situation which is closely approached if R-w approximate to R-j (15% difference at the most in terms of homogeneity index).},
keywords = {electrodes, nanowires},
pubstate = {published},
tppubtype = {article}
}
The homogeneous distribution of electric current (electrical homogeneity) is not guaranteed in nanowire electrodes but is crucial for the stability of the electrode and actually desirable in most applications. Despite the relevance of this feature, it is common practice to perform qualitative assessments at the electrode scale, thus masking local effects. To address this issue, we have developed a computational strategy to aid in the design of nanowire electrodes with improved electrical homogeneity. Nanowire electrodes are modeled as two-dimensional networks of stick and junction resistors (with resistance R-w and R-j, respectively) to simulate the electric conduction process. Electrodes are discretized into regular grids of squares and the electrical power of the network contained in each square is computed. The mismatch between the areal power density of the entire electrode and that of the squares provides a quantitative electrical homogeneity evaluation. Repeating the analysis with squares of different size yields an evaluation that spans across length scales. A scalar indicator, coined the homogeneity index, summarizes the results of the multiscale evaluation. The proposed strategy is employed to assess the electrical homogeneity of silver nanowire electrodes through the analysis of scanning electron microscopy images. Our results agree with the outcomes of the experimental assessment performed on the same electrodes. Parametric studies are performed by varying nanowire content and nanowire-to-junction resistance ratio R-w/R-j. We observe that a significant reduction of contact resistance is not necessary to ensure a high degree of homogeneity. The ideal condition of negligible junction resistance (R-w >> R-j) leads to the best-case scenario, a situation which is closely approached if R-w approximate to R-j (15% difference at the most in terms of homogeneity index).