Energy harvesting from ambient light using PVDF with highly conductive and transparent silver nanowire/PEDOT:PSS hybride electrodes

Bobinger, Marco; Hinterleuthner, Stefan; Becherer, Markus; Keddis, Sherif; Schwesinger, Norbert; Lugli, Paolo

doi:10.1109/nano.2017.8117272

Cited by 8 publications

(10 citation statements)

References 22 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…It is noteworthy to mention here that the obtained voltage and current outputs are much improved than our earlier reported work based on metal electrodes for δ-PVDF nanoparticles. This might be due to the proper synergistic effect of organic active materials with organic electrodes as well as the intrinsic piezoelectric contribution from the electrode . Furthermore, the voltage, current, and power density output of the device were also recorded with external load resisters of 50 kΩ–100 MΩ (Figure d).…”

Section: Resultsmentioning

confidence: 96%

“…This might be due to the proper synergistic effect of organic active materials with organic electrodes as well as the intrinsic piezoelectric contribution from the electrode. 18 Furthermore, the voltage, current, and power density output of the device were also recorded with external load resisters of 50 kΩ−100 MΩ (Figure 5d). A maximum voltage of ∼2 V was obtained at 100 MΩ.…”

Section: ■ Results and Discussionmentioning

confidence: 99%

“…In some of the earlier works, people have also tried to deposit the organic electrodes on PVDF by using ozone treatment/surface functionalization to overcome the hydrophobic incompatibility between the electrode material and PVDF. 18,19 However, such surface treatment functionalization causes defluorination of the active layer, affecting the surface roughness and physical and electrical properties between the active later and the electrode material. Therefore, such an approach needs a better alternative solution.…”

Section: ■ Introductionmentioning

confidence: 99%

“…Furthermore, the hydrophobic nature of PVDF nanoparticles and their incompatibility with metal electrodes along with the presence of air gaps between the active material and the electrode material enhance the major concern for device fabrication. In some of the earlier works, people have also tried to deposit the organic electrodes on PVDF by using ozone treatment/surface functionalization to overcome the hydrophobic incompatibility between the electrode material and PVDF. , However, such surface treatment functionalization causes defluorination of the active layer, affecting the surface roughness and physical and electrical properties between the active later and the electrode material. Therefore, such an approach needs a better alternative solution.…”

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Machine Learning-Aided All-Organic Air-Permeable Piezoelectric Nanogenerator

Gupta¹,

Kumar²,

Mondal³

et al. 2023

ACS Sustainable Chem. Eng.

View full text Add to dashboard Cite

All-organic piezoelectric mechanical energy harvesters display an excellent electrical output with higher sensitivity due to the superior electrode compatibility between active materials and organic electrodes in comparison to that of metal electrodes. Herein, a stretchable, breathable, and flexible all-organic piezoelectric nanogenerator, made up of PVDF nanofibers and δ-PVDF nanoparticles, fabricated through the electrospinning process in a single step, has been demonstrated for prospective machine learning applications. The δphase PVDF nanoparticles serve as efficient active piezoelectric and ferroelectric components with a piezoelectric coefficient of ∼13 pm/V. In terms of electrical response, a peak-to-peak ∼V OC of 4 V, I SC of 1.8 μA, and maximum power density of ∼1600 μW/m 2 were obtained. The fabricated device also exhibits excellent stretchability and air permeability, enabling the properties of robust wearable devices with a water vapor transmission rate of ∼250 g m −2 day −1 . Here, we have shown that a machine learning algorithm proposed for the different finger motion responses can predict with 94.6% accuracy. Thus, it could recognize different finger gestures efficiently with the highest possible accuracy and predict the possible source point. This feature could be advantageous for prospective health care and security purposes apart from the device and sensor applications.

show abstract

Section: Resultsmentioning

confidence: 96%

Section: ■ Results and Discussionmentioning

confidence: 99%

Section: ■ Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Machine Learning-Aided All-Organic Air-Permeable Piezoelectric Nanogenerator

Gupta¹,

Kumar²,

Mondal³

et al. 2023

ACS Sustainable Chem. Eng.

View full text Add to dashboard Cite

show abstract

“…Concerning light as a source of energy, research on traditional photovoltaics is mature and consolidated over time. Low-power distributed applications in the IoT scenario are recently stimulating the research community to investigate miniaturized and efficient EH solutions [61]. Research on EH devices that target RF radiation scattered in the surrounding environment is dense of significant contributions.…”

Section: ) Energy Harvesting: As Knownmentioning

confidence: 99%