Underwater Wireless: TENG Advances for Marine Communication

Wireless communication underwater has long been a challenge due to the high attenuation of electromagnetic waves in water. Traditional acoustic and optical methods have limitations, such as low bandwidth or signal distortion. As marine exploration, environmental monitoring, and underwater robotics advance, there is a growing need for more efficient wireless communication technologies.

A promising approach involves triboelectric nanogenerators (TENGs), which harness mechanical energy from water movement to generate electrical signals for wireless data transmission in aquatic environments.

Wave Propagation Basics

Underwater signal transmission is constrained by the aquatic medium’s unique properties. Unlike air, where electromagnetic waves travel with minimal resistance, water’s high permittivity and conductivity cause rapid attenuation of radio waves, limiting their effective range to a few meters. As a result, traditional wireless communication methods reliant on electromagnetic propagation, such as Wi-Fi or radio frequency (RF) signals, are largely ineffective for long-distance transmission.

Acoustic waves have been the primary means of underwater communication due to their ability to travel long distances with relatively low attenuation. Sound waves propagate efficiently in water because of its high density, enabling communication over several kilometers. However, acoustic methods suffer from low data transmission rates, multipath interference, and susceptibility to environmental noise from marine life, ship traffic, and natural oceanic processes. These drawbacks make them less suitable for high-speed data transfer applications like real-time video transmission or large-scale sensor networks.

Optical communication offers an alternative by using modulated light signals to transmit data. While it provides higher bandwidth than acoustic signals, it is highly sensitive to water turbidity, scattering, and absorption. Even in clear water, optical signals degrade significantly after tens of meters, making them impractical for deep-sea applications or environments with high particulate matter.

TENG Principles In Water

Triboelectric nanogenerators (TENGs) convert mechanical energy into electrical energy through contact electrification and electrostatic induction. In water, this process is influenced by the interaction between water flow and triboelectric materials. When water movement induces periodic contact and separation between materials with differing electron affinities, charge transfer occurs, generating an alternating electrical signal for underwater communication. The efficiency of this energy conversion depends on material properties, surface morphology, and water-induced mechanical motion frequency.

Submerged conditions introduce complexities affecting TENG performance. Water acts as both a medium for charge transfer and a variable dielectric layer, influencing charge generation. Hydrophobic surfaces retain more charge, while hydrophilic materials experience charge dissipation due to water adsorption. The ionic composition of the surrounding water further alters charge dynamics, particularly in saline environments where dissolved ions screen electrostatic interactions, reducing output efficiency.

Optimizing TENGs for underwater use requires careful structural design. Flexible and multilayered configurations enhance contact area and durability, allowing devices to withstand turbulent flow. Encapsulation techniques using water-resistant polymers mitigate charge loss while maintaining mechanical flexibility. Microstructured or nanostructured surface patterns amplify charge generation by increasing contact area and trapping air pockets that facilitate triboelectric interactions. These design considerations ensure stable signal generation in shifting aquatic environments.

Material Selection For TENG Devices

The effectiveness of TENGs in underwater applications depends on material choice, as triboelectric properties, durability, and water interaction dictate performance. Selecting materials with a high triboelectric charge affinity difference enhances charge transfer efficiency, a key requirement for generating strong electrical signals. Polytetrafluoroethylene (PTFE), fluorinated ethylene propylene (FEP), and polydimethylsiloxane (PDMS) exhibit strong electron affinity, making them ideal negative triboelectric materials. Nylon, aluminum, and polyaniline serve as effective positive counterparts due to their electron-donating tendencies.

Beyond triboelectric compatibility, materials must withstand prolonged water exposure without degradation. Hydrophobic polymers like PTFE and FEP resist water absorption, preserving charge retention and minimizing performance loss. Hydrophilic materials may suffer charge dissipation due to water infiltration, necessitating protective coatings. Encapsulation with waterproof layers such as parylene or silicone-based sealants maintains stability while preventing ionic interference in saline environments.

Mechanical resilience is also critical, as TENGs deployed in dynamic aquatic conditions must endure continuous fluid motion and mechanical stress. Flexible substrates such as polyurethane or elastomer-based composites improve durability, ensuring reliable operation under varying water flow conditions.

Surface modifications further enhance performance by increasing charge density and contact area. Micro-nanostructured surfaces, created through laser etching or electrospinning, form air pockets that facilitate charge separation even in submerged environments. This structural enhancement helps counteract water-induced charge screening, which can otherwise reduce efficiency. Integrating conductive nanomaterials such as silver nanowires or graphene into TENG layers improves charge transport, optimizing signal transmission for wireless communication.

Performance Variables In Saline Environments

TENG functionality in saline water is influenced by ionic concentration, with seawater’s average salinity of 35 parts per thousand (ppt) introducing significant charge transfer challenges. Dissolved ions create a conductive medium that facilitates charge dissipation, reducing triboelectric interactions. Electrical double layers form at material interfaces, enhancing or hindering charge retention depending on material dielectric properties. Hydrophobic surfaces mitigate ion penetration, while hydrophilic materials experience greater charge screening, leading to diminished output.

Beyond charge interference, saline environments introduce mechanical and electrochemical challenges. Varying water flow speeds affect triboelectric contact frequency and intensity, impacting signal stability. Coastal waters, where turbulence fluctuates unpredictably, require materials and structural designs that adapt to these conditions. Saltwater exposure accelerates material degradation, particularly in metal components prone to corrosion. Protective coatings such as fluoropolymer layers or graphene-based barriers help extend device longevity, ensuring sustained performance in long-term deployments.

TENG Based Signal Detection Techniques

Harnessing TENG-generated signals for underwater communication requires robust detection techniques capable of isolating weak electrical outputs from background noise. Unlike traditional methods that rely on strong, continuous signals, TENG outputs are often low in amplitude and intermittent, necessitating advanced signal processing. The irregular nature of water flow introduces variability in signal strength and frequency, making filtering and amplification essential for enhancing data clarity. Signal conditioning techniques such as low-noise amplification and adaptive thresholding refine raw electrical output into a more reliable data stream.

Frequency-domain analysis is an effective method for detecting and interpreting TENG signals. Since TENGs generate alternating currents in response to mechanical motion, analyzing spectral characteristics helps differentiate useful information from environmental noise. Fast Fourier Transform (FFT) algorithms decompose raw signals into distinct frequency components, identifying patterns associated with specific water movements. Machine learning techniques further improve detection accuracy by training models to recognize characteristic signal variations under different flow conditions, enhancing real-time underwater data transmission.

Integrating phase-sensitive detection methods can further boost signal clarity by synchronizing with known oscillatory patterns, reducing interference from external sources such as marine life or shifting currents.