Multi‐Objective Bayesian Optimization for Laminate‐Inspired Mechanically Reinforced Piezoelectric Self‐Powered Sensing Yarns DOI Creative Commons
Ziyue Yang,

Kundo Park,

Jisoo Nam

et al.

Advanced Science, Journal Year: 2024, Volume and Issue: 11(33)

Published: June 27, 2024

Piezoelectric fiber yarns produced by electrospinning offer a versatile platform for intelligent devices, demonstrating mechanical durability and the ability to convert strain into electric signals. While conventional methods involve twisting single poly(vinylidene fluoride-co-trifluoroethylene)(P(VDF-TrFE)) mat create yarns, limiting control over properties, an approach inspired composite laminate design principles is proposed strengthening. By stacking multiple electrospun mats in various sequences them properties of P(VDF-TrFE) yarn structures are efficiently optimized. leveraging multi-objective Bayesian optimization-based machine learning algorithm without imposing specific restrictions, optimal sequence determined that simultaneously enhances ultimate tensile strength (UTS) failure considering orientation angles each aligned as discrete variables. The conditions on Pareto front achieve balanced improvement both UTS identified. Additionally, applying corona poling induces extra dipole polarization state, successfully fabricating mechanically robust high-performance piezoelectric yarns. Ultimately, strengthened demonstrate superior capabilities self-powered sensing applications, particularly challenging environments sports scenarios, substantiating their potential real-time signal detection.

Language: Английский

Synergistic integration of energy harvesters and supercapacitors for enhanced performance DOI Creative Commons
Mariya Aleksandrova, И. М. Пандиев

Heliyon, Journal Year: 2025, Volume and Issue: 11(4), P. e42808 - e42808

Published: Feb. 1, 2025

In this paper, it is integrated a piezoelectric energy harvester and supercapacitor storage device on flexible substrate with connection through an innovative alternative current (AC) to direct (DC) boosting power management system for wearable biosensors' supply. Flexible substrates can conform irregular surfaces or shapes, enabling harvesting devices be into variety of form factors, including curved bendable surfaces. Having ensures reliable portable source, providing autonomy. The proposed element was layer-by-layer design silver electrode, polyvinylidene fluoride-trifluoroethylene/multiwall carbon nanotubes, poly(3,4-ethylenedioxythiophene) polystyrene sulfonate: aluminium oxide, graphene nanotubes (Ag/PVDF-TrFE:MWCNT/PEDOT:PSS:CNT/Al2O3/Gr/PEDOT:PSS:CNT), prepared by spray coating. A voltage rectifier low-pass filter (DC-DC) converter used as intermediate unit between the part element. type electronic circuit voltage-doubler rectifier. It found that generates magnitude 2V at loading 110 g/cm2@10 Hz determined workability created during repeated charging discharging, without introducing interfering changes in capacity. behaviour dependent thickness Al2O3 demonstrates more favourable characteristics thicker film 750 nm, where time short (6s), ripples are small (±0.50 mV), maximum output after almost reached input supply (∼1.94 V 2 voltage). addition, resists up 15500 cycles shows stable retention capacitance 1.63 mF. retain their capacity multiple bending (1000) 93 % 91 %, according oxide thickness, which suitable devices.

Language: Английский

Citations

2

Multi‐Objective Bayesian Optimization for Laminate‐Inspired Mechanically Reinforced Piezoelectric Self‐Powered Sensing Yarns DOI Creative Commons
Ziyue Yang,

Kundo Park,

Jisoo Nam

et al.

Advanced Science, Journal Year: 2024, Volume and Issue: 11(33)

Published: June 27, 2024

Piezoelectric fiber yarns produced by electrospinning offer a versatile platform for intelligent devices, demonstrating mechanical durability and the ability to convert strain into electric signals. While conventional methods involve twisting single poly(vinylidene fluoride-co-trifluoroethylene)(P(VDF-TrFE)) mat create yarns, limiting control over properties, an approach inspired composite laminate design principles is proposed strengthening. By stacking multiple electrospun mats in various sequences them properties of P(VDF-TrFE) yarn structures are efficiently optimized. leveraging multi-objective Bayesian optimization-based machine learning algorithm without imposing specific restrictions, optimal sequence determined that simultaneously enhances ultimate tensile strength (UTS) failure considering orientation angles each aligned as discrete variables. The conditions on Pareto front achieve balanced improvement both UTS identified. Additionally, applying corona poling induces extra dipole polarization state, successfully fabricating mechanically robust high-performance piezoelectric yarns. Ultimately, strengthened demonstrate superior capabilities self-powered sensing applications, particularly challenging environments sports scenarios, substantiating their potential real-time signal detection.

Language: Английский

Citations

7