Even if you haven’t heard of piezoelectric materials, you have probably used them to your advantage.
Solid materials like crystals, bones, and proteins are known as piezoelectric materials because, when subjected to mechanical stress, they generate an electric current.
Solar cells, wearable and implantable electronics, and even spacecraft are incorporating materials that use light, heat, and motion as sources of energy. They let us keep gadgets charged for longer, perhaps perpetually, without the need to connect them to a power source.
However, in order for these energy harvesters to function properly, we need to know precisely how much energy they can generate.
Our group has now demonstrated, for the first time, that electrostatic (or phantom) energy is included in electrical signals used to benchmark piezoelectric materials.
When we harvest energy from motion, our study, which was published in the journal Nano Energy, found that more electricity is produced than we anticipated.
When designing the next generation of advanced electronics, this extra energy, or “phantom” energy, needs to be taken into account. Until recently, motion-based energy harvesters didn’t have a way to tell how much phantom energy they had, if any at all.
By simply observing the electrical signal produced by a material exposed to motion, our research team has discovered a straightforward method for determining whether this phantom energy is present.
Estimating apparition energy
Piezoelectric materials have been utilized for energy gathering and detection for a considerable length of time.
From straightforward contact-based energy harvesters to intricate networks of industrial vibration sensors, pacemakers, structural health monitoring devices, and micro-thrusters in space satellites, their uses are diverse.
Traditional, movement-based energy gatherers use at least one energy change standard, such as electromagnetic acceptance (e.g., wind turbines), electrostatic enlistment (e.g., Van Der Graaff generators), and piezoelectricity.
The design and development of functional materials that rely on the phenomenon of piezoelectricity have been accelerated by recent advancements in materials science.
Through deformation, piezoelectricity transforms mechanical energy into electrical energy (voltage). Polymers that are quite flexible, for instance, have the ability to undergo brief physical changes like bending or twisting before resuming their original form.
In turn, this causes the internal polymer chains to move, resulting in the production of electricity in some polymers.
Researchers and manufacturers from a variety of fields have been intrigued by these materials’ capacity to continuously produce an electrical output with minimal effort.
Nowadays, piezoelectric materials, particularly polymers, are frequently utilized in wearable devices to convert motion into electrical energy that can be stored and utilized, such as smart shoes, watches, or gloves.
However, electrostatic charges can build up on the surface of the piezoelectric material as a result of the friction caused by the material’s electrical output.
Many of us have experienced static electricity, such as receiving electric shocks after walking on carpet in socks or watching lightning bolts during a thunderstorm.
The “triboelectric” effect, which can occur when two materials come into contact, is the name given to this phenomenon. Understanding these additional effects brought about by friction is essential for practical applications like harvesting energy from movement to avoid exposing intricate electronic devices to an unexpected increase in energy yields.
Sadly, distinguishing between triboelectricity-hindered signals and intrinsic piezoelectric signals is extremely difficult. This is basically because of the similarities between piezoelectricity and the puzzling triboelectric signals.
In order to determine whether the measurements from piezoelectric materials were accurate, we encased energy harvesters in conductive adhesive like carbon tape.
Finding phantom energy
We tracked down that signs from safeguarded energy collectors (with no triboelectric impedance) had an exceptional recurrence reaction, compared with the signs from unshielded energy reapers.
Using a common signal processing technique known as the fast Fourier transform, we were able to quickly determine that the measurements contained phantom energy by simply converting the electrical output from an energy harvester into the frequency domain.
Simple mathematical software like MATLAB can be used with this method.
The purpose of converting an analog signal, such as voltage over time, into the frequency domain using the fast Fourier transform is to determine how much and how frequently the same signal repeats itself.
As motion-based energy harvesting is a relatively straightforward process, a straightforward frequency spectrum is to be expected. This spectrum is like a single building. In any case, when the examination group purposefully added ghost energy, this recurrence range currently seemed to be a whole city horizon.
Phantom energy interferences, also known as harmonic-induced distortions, can be distinguished as those that typically amplify the source signal.
Engineers can be sure that any energy-harvesting materials, whether they are in space or implanted in the body, will produce the exact amount of energy they need by knowing how to look for phantom energy.
Getting rid of phantom energy
The Fourier transform is a tool we can use to find interferences in our piezoelectric measurements. It is commonly used in data analysis to find trends and anomalies in signals.
During testing, friction occurs in a lot of small places on energy harvesting devices, and these small places can make a big difference in output.
During benchmark testing, for instance, they could increase the expected output from 1 volt (V) to 10 V or even 50 V.
While this might appear as something to be thankful for, this additional energy won’t be gathered. The device would not be able to handle the additional energy, which would be like a fuse blowing during a lightning strike.
not something you want in your body or in space.
Using our straightforward and quick Fourier transform method, we demonstrated how phantom energy could be identified during benchmarking by testing piezoelectric samples in a variety of ways.
Researchers can use straightforward signal filters to isolate and eliminate any interference by identifying and measuring phantom energy.
Makers of piezoelectric energy gatherers can apply it during development — with certainty, making gadgets for bionics, rockets, or some other accuracy application — and produce the specific measure of energy they need to work on the lifetime of a gadget. Perhaps everlastingly piezo-lifetimes
More information: Ronald T. Leon et al, Decoupling piezoelectric and triboelectric signals from PENGs using the fast fourier transform, Nano Energy (2023). DOI: 10.1016/j.nanoen.2023.108445