An autonomous wearable biosensor powered by a perovskite solar cell

An autonomous wearable biosensor powered by a perovskite

solar cell

Jihong Min

1,6

Stepan Demchyshyn

2,3,6

Juliane R. Sempionatto

Yu Song

Bekele

Hailegnaw

2,3

Changhao Xu

Yiran Yang

Samuel Solomon

Christoph Putz

2,3

Lukas

Lehner

2,3

Julia Felicitas Schwarz

Clemens Schwarzinger

Markus Scharber

Ehsan

Shirzaei Sani

Martin Kaltenbrunner

2,3,*

Wei Gao

1,*

Andrew and Peggy Cherng Department of Medical Engineering, Division of Engineering and

Applied Science, California Institute of Technology, Pasadena, California, 91125, USA.

Division of Soft Matter Physics, Institute of Experimental Physics, Johannes Kepler University

Linz, Altenbergerstrasse 69, 4040 Linz, Austria.

Soft Materials Lab, Linz Institute of Technology, Johannes Kepler University Linz,

Altenbergerstrasse 69, 4040 Linz, Austria.

Institute for Chemical Technology of Organic Materials, Johannes Kepler University Linz,

Altenbergerstrasse 69, 4040 Linz, Austria.

Linz Institute for Organic Solar Cells, Johannes Kepler University Linz, Altenbergerstrasse 69,

4040 Linz, Austria.

These authors contributed equally to this work.

Abstract

Wearable sweat sensors can potentially be used to continuously and non-invasively monitor

physicochemical biomarkers that contain information related to disease diagnostics and fitness

tracking. However, the development of such autonomous sensors faces a number of challenges

including achieving steady sweat extraction for continuous and prolonged monitoring, and

addressing the high power demands of multifunctional and complex analysis. Here we

report an autonomous wearable biosensor that is powered by a perovskite solar cell and

can provide continuous and non-invasive metabolic monitoring. The device uses a flexible

quasi-two-dimensional perovskite solar cell module that provides ample power under outdoor

and indoor illumination conditions (power conversion efficiency exceeding 31% under indoor

light illumination). We show that the wearable device can continuously collect multimodal

weigao@caltech.edu; martin.kaltenbrunner@jku.at.

Author contributions

W.G., J.M., M.K., and S.D. initiated the concept and designed the studies; J.M. and S.D. led the experiments and collected the

overall data; J.R.S., Y.S., B.H., C.X., Y.Y., and S. S. contributed to wearable device characterization, validation, and sample analysis.

B.H., C.P., L.L., M.S., S.S. contributed to solar module development, fabrication, and characterization. S.D., B.H., J.F.S., and C. S.

contributed to experimental design and characterization of Pb leakage test for the solar cell module. E.S.S. contributed to cell viability

and metabolic activity characterization. J.M., S.D., W.G., and M.K. co-wrote the paper. All authors contributed to the data analysis and

provided the feedback on the manuscript.

Competing interests

The authors declare no competing interests.

HHS Public Access

Author manuscript

Nat Electron

. Author manuscript; available in PMC 2024 March 08.

Published in final edited form as:

Nat Electron

. 2023 August ; 6(8): 630–641. doi:10.1038/s41928-023-00996-y.

Author Manuscript

physicochemical data — glucose, pH, sodium ions, sweat rate, and skin temperature — across

indoor and outdoor physical activities for over 12 hours.

Introduction

The recent shift towards personalized and remote healthcare has accelerated the

development and adoption of wearable devices that can continuously monitor physical vital

signs as well as biochemical markers

–

. Wearable biosensors can potentially be used to

continuously and non-invasively analyze body fluids such as sweat, which contains a wealth

of information pertinent to disease diagnostics and fitness tracking

. A variety of

electrochemical sensing strategies, including amperometry, potentiometry, voltammetry, and

impedance spectroscopy, have been used to detect sweat biomarkers (such as electrolytes,

metabolites, nutrients, drugs, and hormones)

–

and sweat rate (which may have a

close link to secreted biomarker levels)

. For practical health monitoring beyond that

during vigorous exercise, wearable biosensors can also benefit from steady sweat extraction

via iontophoresis, a localized sedentary sweat stimulation technique

. However, due to

challenges related to multimodal system miniaturization and integration, the development of

a wearable system capable of autonomous sweat induction and sampling, real-time sweat

rate monitoring, and continuous multiplexed biomarker analysis remains limited.

High power demand also impedes the development of such multifunctional wearable sensing

systems. Wearable sensors typically rely on the use of batteries: a bulky and unsustainable

power source that requires an external source of electricity to recharge. Various energy

harvesting strategies — including biofuel cells and triboelectric nanogenerators — have

been explored for powering battery-free wearables

–

. However, biofuel cells typically

suffer from limited long-term stability due to biofouling in human sweat

, and triboelectric

nanogenerators require extensive physical activity to generate electricity

. Furthermore, the

power densities produced by biofuel cells and triboelectric nanogenerators from casual daily

activities are limited

Ambient light, including natural sunlight and artificial indoor light, is an abundant form

of energy that is readily available during daily activities. The commercially dominant

photovoltaics technologies, which are based on silicon, work well for large-scale solar

energy harvesting, but struggle to address the power needs of wearable devices. In particular,

silicon cells are often fragile, bulky and rigid. They also provide insufficient power

conversion efficiency (PCE) under low or indoor illumination, due to their narrow bandgap

and preferentially trap-assisted recombination, limiting their range of applications

. Light

harvesting technologies based on the III-V family of semiconductors can address some of

the limitations of silicon, but their fabrication often requires complex processing conditions,

which is reflected in their price/energy payback time and thus their potential areas of

application

Perovskite solar cells offer a number of favorable intrinsic properties including long

charge carrier diffusion lengths, high absorption coefficients, solution processability, small

exciton binding energies, high structural defect tolerance, tunable bandgap, and high

photoluminescence quantum yields

. Such solar cells have developed quickly in the

Min et al.

Page 2

Nat Electron

. Author manuscript; available in PMC 2024 March 08.

Author Manuscript

last decade due to their evolving fabrication protocols and the adaptability of the material

compositions

. Perovskites also offer strong defect tolerance that leads to high parallel

resistance (Rp), which is the key parameter of solar cell performance under low light

conditions. This results in increased fill factor (FF) and reduced open circuit voltage (Voc)

losses at low light conditions, which in combination with the matching of perovskite solar

cell spectral response to common indoor lighting emission spectrum, yields high PCE under

indoor illumination

In this Article, we report an autonomous wearable biosensor that is powered by a flexible

perovskite solar cell (FPSC) and can provide continuous and non-invasive metabolic

monitoring (Fig. 1a). Our multifunctional wearable device offers autonomous sweat

extraction via iontophoresis, dynamic microfluidic sweat sampling, multiplexed monitoring

of sweat biomarkers using different electrochemical detection techniques, impedance-based

sweat rate analysis, and Bluetooth-based wireless data transmission. The wearable device

operates under a wide range of illumination conditions ranging from full sunlight to indoor

lighting. It is powered by an efficient 2 cm

active area lightweight quasi-2D FPSC energy

harvesting module with a PCE of 14% under air mass global 1.5 (AM1.5) illumination, and

29.64% under 600 lx indoor illumination with a white light LED light bulb. The sensing

platform can be used to continuously collect multimodal physicochemical data (glucose, pH,

, sweat rate, and temperature) across indoor and outdoor physical activities for over 12

hours, and without the need for batteries or vigorous exercise.

Wearable device design for autonomous biomarker analysis

The wearable device consists of disposable and reusable modules assembled in an origami-

like fashion (Fig. 1b and Supplementary Figs. 1,2). Among the reusable parts is the highly

efficient quasi-2D FPSC module that converts ambient light into electrical power and the

energy-efficient flexible printed circuit board (FPCB) for electrochemical instrumentation,

signal processing, and Bluetooth wireless communication. A daily disposable flexible patch

contains a pair of carbachol hydrogel (carbagel) coated iontophoresis electrodes for sweat

stimulation, a laser-engraved microfluidic module integrated with interdigitated electrodes

for sweat sampling and sweat rate monitoring, and a multiplexed electrochemical sweat

biosensor array for molecular analysis (Fig. 1c). Compared to traditionally used pilocarpine

gels, carbachol gels were selected for iontophoresis as they allow for efficient and long-

lasting sudomotor axon reflex sweat secretion from the surrounding sweat glands, ideally

suitable for microfluidic sweat sampling

. Inkjet printing was used to fabricate all flexible

biosensing electrodes and interconnects at a large scale and low cost. Considering that

chemical sensors usually suffer from signal drift during long-term use, their capacity

for mass-production allows disposable use on a daily or multi-day basis for reliable

wearable health monitoring. Potentiometric, amperometric, voltammetric, and impedimetric

techniques can all be performed using the wearable device to analyze a broad spectrum

of sweat biomarkers ranging from metabolites, electrolytes, nutrients, to substances and

drugs. The fully assembled wearable device is 20 mm × 27 mm × 4 mm in size and can

comfortably adhere to the skin (Fig. 1d,e). The custom embedded algorithm and mobile

application enable an energy-saving adaptive power consumption scheme such that the

wearable device can extract and analyze sweat across various activities and illumination

Min et al.

Page 3

Nat Electron

. Author manuscript; available in PMC 2024 March 08.

Author Manuscript

conditions in a prolonged and efficient fashion. All calibrated biomarker information can be

wirelessly transmitted and displayed on a custom mobile app (Fig. 1e, Supplementary Fig. 3,

Supplementary Video 1).

FPSC design and characterization for wearable use

To effectively and sustainably power the wearable device, an FPSC module (Fig.

2a) is designed to have a high power density and PCE for energy harvesting under

diverse lighting conditions, flexibility to endure the mechanical stresses common for on-

body wear, and stable performance with reliable encapsulation against sweat exposure.

The FPSC device utilizes a p-i-n architecture and comprises of flexible polyethylene

terephthalate (PET) coated with indium tin oxide (ITO), Cr/Au busbars, a poly(3,4-

ethylenedioxythiophene)-poly(styrenesulfonate)(PEDOT:PSS) hole transport layer, quasi-2D

perovskite photoactive layer, [6,6]−phenyl-C61-butyric acid methyl-ester (PCBM) electron

transport layer, TiO

interlayer, Cr/Au contacts, and an epoxy/PVC/PCTFE encapsulation

(Fig. 2b). The perovskite absorber layer (ca. 450 nm thick) with an empirical formula of

(MBA)

(Cs

0.12

0.88

)

1-x

)

is at the heart of the device (Fig. 2c). A large organic

spacer,

-methylbenzylamine (MBA), facilitates the formation of a quasi-2D perovskite

structure with large grain size and improved defect passivation, resulting in an excellent

device performance (Supplementary Fig. 4). Under simulated solar illumination (AM1.5)

quasi-2D FPSC with a small active area (0.165 cm

) achieve PCE of up to 18.1 %,

which remains as high as 16.5 % for large area device (1 cm

), and 14.0% for modules

consisting of two large cells joined in series (total active area 2 cm

) (Supplementary Fig. 5,

Supplementary Table 1).

The main advantage of our quasi-2D FPSC energy harvesting module is its ability to operate

at high efficiency even under indoor and low light illumination conditions. Common indoor

lighting sources, like LEDs, have a narrower emission spectrum that closely matches the

external quantum efficiency (EQE) of our quasi-2D FPSC, and a lower photon flux density,

when compared to sunlight (Fig. 2d). This results in an increased PCE due to reduced

sub-bandgap relaxation and recombination losses, as well as passivation of trap states and

grain boundaries via MBA incorporation. Thus, quasi-2D FPSC practically double their

efficiency under 600 lx (215 μW cm

−2

) LED indoor illumination, achieving a PCE as high

as 31.2 % in small area devices, scaling up efficiently to large area with a PCE of up to

29.9 %, and reaching 29.6 % in module configuration (Fig. 2e, Supplementary Table 2).

These are the highest reported PCE values among indoor flexible solar cells, outperforming

not only perovskite but also other PV technologies in this field (Supplementary Table

3). Furthermore, the power output of the quasi-2D FPSC module reliably extends over

a broad range of indoor illuminance ranging from very bright (10k lx), common for

special environments like surgery rooms, down to dimly lit surroundings (20 lx) (Fig. 2f,

Supplementary Figs. 6 and 7).

In order to acquire light-source-independent performance values, we also measured PCE

using a monochromatic light source (continuous laser,

= 637 nm) over a range of indoor

and low light irradiances (0.07 < P

< 18 mW cm

−2

) (Supplementary Fig. 8). We achieved

a record breaking PCE of 41.4±0.1% measured at P

= 12.23 mW cm

−2

for the small

Min et al.

Page 4

Nat Electron

. Author manuscript; available in PMC 2024 March 08.

Author Manuscript

area devices, and a PCE of 30.4±0.2% at P

= 6.08 mW cm

−2

for large area devices

(Supplementary Table 4, Supplementary Note 1).

The quasi-2D FPSC modules show steady power output with no loss in performance after

continuous 24 hours operation under both AM1.5 and indoor illumination conditions (Fig.

2g, Supplementary Fig. 9). Additionally, the module mechanical stability was confirmed

to withstand 2000 bending cycles (bending radius 5 cm) with only negligible reduction

in performance that can be attributed to decrease in ITO electrode resistance (Fig. 2h,

Supplementary Figs. 10 and 11).

Considering the concern of possible Pb leakage while using perovskite solar cells, a set

of Pb-release tests were performed in deionized water (Supplementary Fig. 12), as well as

in a standard synthetic sweat solution

on a fully-encapsulated quasi-2D FPSC module

(Fig. 2i). Continuous operation of the FPSC module under AM1.5 for 24 hours while fully

immersed in simulated sweat solution resulted in a Pb concentration that remained more

than one order of magnitude below the maximum allowable level in drinking water as

per the Joint Food and Agriculture Organization/World Health Organization (FAO/WHO)

Expert Committee on Food Additives (JECFA)

(Fig. 2i), indicating the encapsulation

robustness and module safety even under conditions that far exceed the expected operational

conditions of the wearable device. Furthermore, the encapsulated FPSC maintained high

biocompatibility even after vigorous mechanical bending tests as evidenced by low Pb-

leakage as well as high cell viability and metabolic activity of the cells seeded on the FPSCs

(Supplementary Figs. 13 and 14).

System-level integration and operation of wearable device

Composed of off-the-shelf electronic components, the judiciously designed wearable

electrochemical instrumentation system of the wearable device is more powerful in

functionality and power-efficient than any other reported wearable sweat analyzer. The

battery-free electronic system interfaces with the skin via an inkjet-printed disposable sweat

patch that contains two gel-loaded iontophoretic electrodes, three electrochemical sweat

biosensors, and one sweat rate sensor embedded in the microfluidics (Fig. 3a). The system

performs constant-current iontophoresis for sweat induction; amperometry, potentiometry,

and voltammetry for continuous analysis of a variety of sweat biomolecular markers;

impedance measurements for sweat rate monitoring; and Bluetooth data communication

with the user interface (Fig. 3b,c, Supplementary Figs. 15 and 16).

More specifically, the wearable device’s electronic system consist of: 1) an energy

harvesting power management integrated circuit (PMIC) that efficiently boost converts and

manages the output from the quasi-2D FPSC, 2) a compact programmable system-on-chip

(PSoC) Bluetooth low energy (BLE) module that integrates a microcontroller (MCU)

and BLE radio, 3) an electrochemical analog front-end (AFE) that integrates various

configurable blocks necessary for electrochemical detection, and 4) a high compliance-

voltage current source with an overcurrent protection switch for iontophoresis (Fig. 3b

and Supplementary Fig. 17a,b). Under illumination, the PMIC charges the 5 mF solar

energy storage capacitor up to ~5 V to continuously power the wearable device. Our

Min et al.

Page 5

Nat Electron

. Author manuscript; available in PMC 2024 March 08.

Author Manuscript

custom-developed embedded algorithm ensures that each block of the system operates

at its lowest viable power mode, enabling ultra-low-power multiplexed electrochemical

measurements consuming below 60 μW (Supplementary Fig. 17c and Supplementary Fig.

17). During operation, the wearable device stays in deep-sleep (33 μW during standby)

or sleep (47 μW during potentiostat operations) modes and wakes up intermittently

to either wirelessly communicate with the host software, perform an electrochemical

measurement, or process measurement data (Supplementary Fig. 19). Depending on the

illumination conditions and the quasi-2D FPSC’s power output, the wearable device adapts

its operation mode (e.g., parameters such as BLE communication interval and sensor

data acquisition interval to mediate power consumption) (Supplementary Note 2). The

power consumption profiles for each electrochemical operation and the corresponding

capacitor charging/discharging curves of the solar energy storage capacitor when powered

by a quasi-2D FPSC module under various illumination conditions (2k–18k lx) are

highlighted in Fig. 3d as well as Supplementary Fig. 20 and Supplementary Table 5.

The electrochemical instrumentation performance of the wearable device was successfully

validated by comparing its potentiometric, amperometric, and voltammetric responses to

those of a commercial potentiostat (Supplementary Fig. 21).

Characterization of device for multimodal biosensing

An iontophoretic sweat induction microfluidic module was carefully designed and optimized

for minimal power consumption and prolonged use. Unlike standard pilocarpine gels that

can only stimulate local sweat glands directly beneath the agonist gel for a short duration

and lead to low sensing accuracy due to the mixing of sweat and gel fluid

, carbagels

stimulate local and neighboring sweat glands steadily for extended durations

. This

property enables the use of miniaturized carbagels for prolonged sweat induction and

microfluidic neighboring sweat collection on a single patch design. The dimensions and

layout of the carbagels with respect to the sweat accumulation reservoir were optimized for

minimal size, applied current, and maximal sweat extraction efficiency (Supplementary Note

3). The reusable carbagel, capable of stimulating sweat continuously throughout the day, is

a part of the mass-producible and disposable microfluidic sensor patch that can be replaced

for daily use. To demonstrate the device’s wearable use, the sweat processing system

was paired with a sensor array consisting of an amperometric enzymatic glucose sensor,

potentiometric ion-selective pH and Na

sensors, and an impedimetric sweat rate sensor.

The individual current, potential, and admittance responses of each sensor were recorded

by the wearable device under physiologically relevant target analyte concentrations and/or

sweat rates (Fig. 3e, Supplementary Fig. 22); linear responses were observed between the

measured electrochemical signals and target concentrations (for glucose sensor), logarithm

target concentrations (for pH and Na

sensors), and reciprocal flow rate (for sweat rate

sensor). While sweat Na

and pH levels can individually serve as a potent biomarker for

various health conditions, they could synergistically aid in calibrating the sweat rate and

glucose sensors, respectively (Supplementary Fig. 23). In addition, temperature information

recorded by the built-in temperature sensor in the AFE of the wearable device aids in

more accurate sensor calibrations during wearable use (Supplementary Fig. 24). Moreover,

Min et al.

Page 6

Nat Electron

. Author manuscript; available in PMC 2024 March 08.

Author Manuscript

the sweat rate sensor can be reconfigured with different volumetric capacities for desired

operation duration (Supplementary Fig. 25).

When powered by the quasi-2D FPSC module, the wearable device performs multiplexed

on-body measurement sequences under a wide range of indoor illumination conditions.

With indoor LED illumination with a brightness as low as 1k lx, the wearable device

simultaneously monitors glucose, pH, Na

, and temperature, along with the periodic

impedimetric measurement of sweat rate; when less light as low as 400 lx is available,

the wearable device’s custom algorithm adapts to decrease the multiplexed measurement

frequency and transmits data over BLE advertisements (Fig. 3f). With a larger area

wearable solar cell (8.9 cm x 7.4 cm), the wearable device performs the same multiplexed

on-body measurement sequences under even darker illumination conditions (100–300 lx)

(Supplementary Fig. 26).

In vitro

multimodal analysis of glucose, pH, Na

, temperature, and flow rate through the

assembled microfluidic sensor patch was performed in a phosphate-buffered saline (PBS)

solution containing 100 μM glucose under varying flow rates (0.12–3 μL min

−1

) and under

lab-light illumination (1200 lx) (Fig. 3g). The glucose, pH, and Na

biosensors maintained

stable and accurate responses even at a flow rate as low as 0.12 μL min

−1

, while the

sweat rate sensor responded accurately according to the increasing volume. This indicates

that while the integrated biosensors will respond to physiologically-induced analyte level

changes during the on-body tests, their performance will not be substantially affected by

changes in sweat rates. The long-term stability of the wearable device for continuous energy

harvesting and multiplexed biosensing was further validated in a long-term study with a

constant flow rate of 1 μL min

−1

for 100 min under varying indoor illumination conditions

(Supplementary Fig. 27).

On-body device evaluation for multimodal sweat monitoring

The compact design of the wearable device enables the comfortable and strong adhesion

of the device to different body parts with access to ambient light (Fig. 4a). When worn on

body under various outdoor and indoor illumination conditions, the wearable device harvests

energy sufficient to enable iontophoresis and multiplexed sweat biosensing sequences;

additionally, the light-powered iontophoresis results in efficient and prolonged sweat

extraction to allow dynamic sweat biomarker analysis (Fig. 4b, Supplementary Fig. 28, and

Supplementary Video 2). The accuracy of the device’s interdigitated electrode-enabled sweat

rate sensor during wearable use was successfully validated with image-based colorimetric

sweat rate analysis (enabled by filling a color dye in the microfluidic sweat inlet before

the on-body test) (Supplementary Fig. 29a). Autonomous periodical sweat induction allows

prolonged continuous sweat extraction: our pilot studies show that a single sweat induction

event was on average able to extract ~52 μL over a duration of 3 hours, while sustaining a

steady sweat rate over 0.1 μL min

−1

(Supplementary Fig. 29b,c).

The wearable device’s efficient light energy harvesting capability and powerful sweat

processing system enable continuous and non-invasive physiochemical monitoring

under laboratory illumination conditions. The evaluation of the wearable device for

Min et al.

Page 7

Nat Electron

. Author manuscript; available in PMC 2024 March 08.

Author Manuscript

cardiometabolic monitoring was performed by continuously monitoring sweat glucose,

pH, Na

, and sweat rate levels along with the skin temperature of human subjects in

both sedentary and exercise trials (Fig. 4c–f and Supplementary Figs. 30 and 31). In

the sedentary studies, light-powered iontophoretic sweat extraction was followed by the

continuous monitoring of key biomarkers. In the fasting studies, sweat glucose, pH, Na

and skin temperature remained stable while sweat rate rapidly increased in the first 30 min

and then gradually decreased (Fig. 4c). In the oral glucose intake studies, a substantial

increase in sweat glucose was observed through the first hour (Fig. 4d). Sedentary fasting

and glucose intake studies were repeated twice for two additional subjects (Supplementary

Figs. 30 and 31). From the sedentary oral glucose intake studies performed across 3

subjects, a high correlation was observed between blood glucose levels and sweat glucose

levels (Supplementary Fig. 32). Similarly, in the exercise studies, sweat glucose remained

relatively stable or slightly decreased during fasting, while clearly elevated glucose levels

were observed after oral glucose intake followed by a quick decrease after 30 min

(Fig. 4e,f). We also noticed a conspicuous discrepancy between pH levels of carbachol

iontophoresis-induced sweat (~pH 9) and exercise-induced sweat (~pH 5), indicating the

importance of sweat induction approaches and pH calibrations on personalized metabolic

monitoring (Supplementary Fig. 33). In all sedentary and exercise studies, positive

correlations between the real-time calibrated sweat glucose and blood glucose levels were

obtained, indicating the high potential of realizing non-invasive glucose monitoring using

the wearable device. Potential noise due to motion artifacts during on-body sensing was

mitigated by tightly packing and adhering the miniaturized wearable system onto the skin,

where electrochemical sensing was performed in a bound microfluidic reservoir to prevent

direct skin-sensor contact. Noise was further reduced by hardware filters integrated on-board

as well as smoothing algorithms implemented in the custom app.

Prolonged cross-activity multimodal monitoring of sweat biomarkers in real-life scenarios

was enabled by the wearable device as illustrated in Fig. 4g. Throughout the day, over

a 12-hour time span, the subject performed various physical activities under various

lighting environments. During this time, the wearable device performed iontophoresis

intermittently to ensure that a sufficient sweat rate could be maintained for sweat refreshing

and continuous sensor measurements throughout the day. Depending on the available

illumination, the wearable device switched its on-body measurement sequence to adjust

its power consumption while trading off for measurement intervals. While the multiplexed

data interval varied from 8 s to 60 s throughout the day, the wearable device was able to

collect, process, and calibrate sensor data continuously in all scenarios. The glucose trend

throughout the day shows that the larger meal during dinner results in a higher and longer

sweat glucose spike than the lighter lunch. In addition, the average sweat rate during outdoor

sedentary activities was higher than the average sweat rate during indoor sedentary activities

while vigorous exercise leads to a substantial increase in sweat rate. Considering that the

battery-free version of the wearable device requires access to light for long-term operation,

integrating a small battery into the wearable device could realize 24-hour operation (even

during sleep) (Supplementary Figs. 34 and 35).

Min et al.

Page 8

Nat Electron

. Author manuscript; available in PMC 2024 March 08.

Author Manuscript

Conclusion

We have reported a wearable biosensor platform that is powered by a quasi-2D FPSC. The

wearable device can persistently extract sweat and simultaneously monitor physicochemical

markers (glucose, pH, Na

, sweat rate, and skin temperature) via a spectrum of

electrochemical techniques (potentiometry, amperometry, voltammetry, and impedimetry).

It can achieve this under various illumination conditions (strong outdoor sunlight to dim

indoor LED light) and across various activities (sleep to vigorous exercise).

Our quasi-2D FPSC is uniquely suitable for powering wearable technologies. The solar

harvesting technology offers high efficiency under indoor and low light illumination

conditions, maintains high power conversion efficiency and power output across a wide

range of illumination conditions, withstands mechanical stress common for on-body wear

during vigorous exercise, and remains safe through proper encapsulation. The wearable

solar cell is paired with a compact, wireless, and low-power wearable multichannel

electrochemical workstation that dynamically adjusts its power consumption to continuously

operate without a battery under varying illumination conditions. The modular design of the

wearable device is readily scalable; if required, additional energy harvesting modules can be

incorporated.

The microfluidic iontophoretic sweat processing module enables prolonged flow rate-

monitored sweat extraction. This allows sweat biosensing to be applied beyond situations

where vigorous exercise is required — that is, normal everyday activity — as well as use for

patients with mobility impairments. The rate-monitored persistent sweat flow continuously

refreshes the sensor reservoir for accurate biomarker measurements; the sensor responses are

calibrated in real-time by personalized factors such as skin temperature, sweat pH, and sweat

to further improve measurement accuracy.

Future work for the technology will involve improving the long-term stability of the sensor

patch and investigating the correlation between sweat/blood biomarker levels in large-scale

human trials. The wearable device can also be paired with different biosensors based

on a wide array of electrochemical detection mechanisms (potentiometry, amperometry,

voltammetry, and impedimetry) for the identification of an endless number of target

biomarkers. Potential fields of application including sport science and daily tracking, as

well care for people with health conditions or impairments.

Methods

Materials and reagents

All chemicals and solvents were purchased from commercial suppliers and used as received,

if not stated otherwise.

Agarose, carbachol, potassium chloride (KCl), nickel chloride (NiCl

), potassium (III)

ferricyanide (K

Fe(Cn)

), potassium (IV) ferrocyanide (K

Fe(Cn)

), glucose oxidase (GOx),

glutaraldehyde, bovine serum albumin (BSA), 10X phosphate buffered saline (PBS), 3,4-

ethylenedioxythiophene (EDOT), poly(sodium 4-styrenesulfonate) (PSS), sodium ionophore

Min et al.

Page 9

Nat Electron

. Author manuscript; available in PMC 2024 March 08.

Author Manuscript

X, bis(2-ethylehexyl) sebacate (DOS), polyvinyl butyral resin BUTVAR B-98 (PVB),

polyvinyl chloride (PVC), sodium tetrakis[3,5-bis(trifluoromethyl)phenyl] borate (Na-

TFPB), aniline, iron (III) chloride (FeCl

), sodium hydroxide (NaOH), citric acid, ITO

covered 125 μm PET foil, lead iodide (PbI

), lead chloride (PbCl

), methylamine

(CH

), (R)-(+)-

-methylbenzylamine (C

), cesium iodide (CsI), hydroiodic

acid (HI), N,N-dimethylformamide (DMF), acetylacetone (CH

COCH

), titanium

(IV) isopropoxide (Ti[OCH(CH

)

]

), 2-methoxyethanol (CH

OCH

OH), sodium

chloride (NaCl), lactic acid (C

), urea (NH2CONH2), ammonia (NH

OH), and

ethanolamine (H

NCH

OH) were purchased from Sigma-Aldrich. Sodium chloride

(NaCl), methanol, ethanol, acetone, hydrogen peroxide (30% (w/v)), dextrose (D-glucose)

anhydrous, tetrahydrofuran (THF), hydrochloric acid (HCl), tetrachloroauric acid (HAuCl

and disodium phosphate (Na

HPO

) were purchased from Thermo Fisher Scientific. Diethyl

ether ((CH

)

O), chlorobenzene, hexane, dimethyl sulfoxide (DMSO), PEDOT:PSS

aqueous dispersion (Clevios PH1000), and chloroform (CHCl

) were purchased from

VWR. [6,6]−phenyl-C61-butyric acid methyl ester (PCBM) was purchased from Solenne

BV. Hellmanex III detergent was purchased from Hellma Analytics. Zonyl

FS-300

fluorosurfactant was purchased from Fluka. UV curable flexible epoxy (LP4115) was

purchased from DELO Photobond. Liveo Aclar DX 2000 encapsulating polymer (PVC/

PCTFE) was purchased from Liveo Research. PDMS (SYLGARD 184) was purchased from

Dow Corning. Medical adhesives were purchased from 3M. Polyimide films (12 ~ 75 μm

thick) were purchased from DuPont. PET films (12 ~ 250 μm thick) were purchased from

McMaster-Carr.

Solar cell fabrication and characterization

Glass substrates (1 × 1 inch, 1 mm thick) were cut and cleaned in an ultrasonic bath for 30

min each in 2 v/v% Hellmanex in DI water solution, 2 × DI water solution, acetone, and

isopropanol, and dried using N

stream. Flexible ITO-covered PET substrates were patterned

using insulating tape for masking and etched using concentrated HCl for 10 min. After that

they were also cut to 1 × 1 inch size and washed using the same procedure as for glass.

PDMS solution was spin-coated onto glass at 4000 rpm for 30 s and placed on a heat plate at

105 °C for 1 min. After that, flexible substrates were placed on to the PDMS-covered glass,

carefully avoiding any trapped air underneath. Finally, the whole substrate was annealed

for 15–20 min at 105 °C. Cr-Au bus bars were deposited via thermal evaporation using a

shadow mask (base pressure 3 × 10

−6

mbar).

The PEDOT:PSS solution was prepared by mixing Clevios PH1000 stock solution with

7 vol% DMSO and 0.7 vol% Zonyl FS-300. The PEDOT:PSS solution was stirred at

room temperature for an hour, then kept at 4 °C overnight. Right after filtering through

Minisart RC25 Syringe filter 0.45 μm regenerated cellulose, the PEDOT:PSS solution was

spin-coated on the substrates with busbars at 1500 rpm for 45 s (ramp 2 s) followed by 1000

rpm for 2 s (ramp 1 s) and annealed at 120 °C for 15 min. Then the film was washed by

spin-coating isopropanol at 1000 rpm for 4 s followed by 4000 rpm for 12 s and annealed

again at 120 °C for 15 min.

Min et al.

Page 10

Nat Electron

. Author manuscript; available in PMC 2024 March 08.

Author Manuscript

Perovskite solution ((MBA)

(Cs

0.12

0.88

)

1-x

)

) was prepared by mixing PbI

(322.4 mg,), PbCl

(83.5 mg,), (R)-(+)-

-methylbenzylamine iodide (MBAI) (74.7 mg,),

and Methylamonium iodide (MAI) (187.7 mg,) in DMF containing 10 vol% acetylacetone

and stirred for 1 h at 55 °C. MBAI was synthesized from (R)-(+)-

-methylbenzylamine

and hydroiodic acid and purified using diethylether (VWR) and absolute ethanol (Merck

Millipore) using a procedure previously described in the literature

. MAI was synthesized

using an analogous procedure. Afterwards, CsI (~0.12 mmol, from 1.5 M stock solution

in DMSO) was added to the mixture and stirred overnight. The solution was filtered using

polytetrafluoroethylene (PTFE) syringe filters (0.45 μm; Whatman) before spin-coating.

Perovskite solution was then deposited using an anti-solvent procedure inside of the nitrogen

) glovebox. The solution was spin-coated in two steps at 1000 rpm for 5 s with ramp 200

rpm s

−1

followed by 4000 rpm for 25 s with ramp 2000 rpm s

−1

. Approximately ~0.2 mL

of chlorobenzene (anti-solvent) was dropped at 15

second for about 3 s. Then the film was

annealed at 100 °C for 1 h.

After the film cooled down to room temperature PCBM solution was spin-coated onto the

sample at 1500 rpm for 16 s (ramp 2 s) followed by 2000 rpm for 15 s (ramp 2 s). PCBM

solution was prepared by dissolving 2 wt% PCBM in chlorobenzene and chloroform (1:1

volume ratio). TiOx solgel was prepared based on procedure reported by Heilgenaw et al

TiO

was spin-coated at 4000 rpm 30 s (ramp 2 s) and annealed at 110 °C for about 5

min in an ambient atmosphere. Cr/Au contacts were evaporated at rate of 0.01–0.5 nm

−1

and base pressure 3 × 10

−6

mbar. Finally, the devices were encapsulated using UV

curable flexible epoxy and PVC/PCTFE protective films. Absorbance spectra were recorded

using LAMBDA 1050 UV/Vis Spectrophotometer, Perkin Elmer, U.S.A. Photoluminescence

spectra were recorded on a photomultiplier tube–equipped double-grating input and output

fluorometer (Photon Technology International).

Current density-voltage (J-V) characteristics of solar cells under sunlight illumination were

recorded under simulated AM1.5 global spectrum irradiation from a 150 W xenon light

source using Keithley 2400 source meter and a custom Lab-View program. The intensity

of the solar simulator was adjusted using a commercial Si reference diode (Si-01TC,

Ingenieurburo Mencke & Tegtmeyer, Germany). The performance of the solar cells under

indoor lighting was tested using a set of commercial off-the-shelf warm light LED light

bulbs (Philips, 2700 K, 4.3 W, 470 lm; Philips, 2700 K, 7 W, 806 lm; Osram, 2700 K, 21

W, 2451 lm). The measurement was performed inside of a light-tight black cloth-covered

characterization chamber with the cell tightly wrapped with black tape, allowing only the

active area to be exposed to the light, thus reducing the influence of reflections or stray

light. A broad range of intermediate illuminance levels was achieved by utilizing a set of

neutral density filters placed directly on the device. The emission spectrum of the light bulbs

was measured using a fiber spectrometer (Avantes, AvaSpec-2048-USB2) (Supplementary

Fig. 6) Illuminance of the LED light sources was measured using ISO calibrated lux meter

(Voltcraft MS-1300). Spectral incident power intensity of the LED light bulbs was calculated

as reported in literature

. Additionally, reference PCE under low light conditions was

calculated from a JV curve measured under a monochromatic light source (637 nm laser,

Coherent OBIS 637 nm, 140 mW), with the incident power intensity calculated using a

calibrated Si diode (Hamamatsu S2281).

Min et al.

Page 11

Nat Electron

. Author manuscript; available in PMC 2024 March 08.

Author Manuscript

Surface SEM measurements were made using the Zeiss 1540 XB CrossBeam SEM

(acceleration voltage 5 keV). A cross-section image was prepared by prepared using a

standard focus ion beam cutting approach. Images of the cross-section were performed

under the same conditions as surface SEM measurements.

Maximum Power Point (MPP) tracking was performed using an in-house written

Python script utilizing a common Perturb-and-Observe algorithm. Starting voltage for the

measurements was V

· FF, with a step size of 50 mV and 15 s waiting time between

voltage perturbations.

Lead release test was performed using standard artificial sweat solution (containing sodium

chloride 0.5 % w/w, lactic acid 0.1 % w/w, and urea 0.1 % w/w in deionized water)

as described in European Standard EN 1811:1998. Encapsulated solar cell modules were

immersed into 100 mL freshly prepared synthetic sweat buffer and placed at about 20 cm

under a xenon lamp solar simulator with AM1.5G spectrum (distance adjusted so to achieve

approximately 1 Sun illumination). The buffer was continuously stirred with a magnetic

stirrer and 1 mL extract samples were collected periodically and stored in the fridge at

4 °C until the next day when they were analyzed using inductively coupled plasma mass

spectrometry (ICP-MS). Alternatively the lead tests were also performed with just deionized

water, following the same procedure described above.

Each ICP-MS sample was extracted with 18.2 MOhm water. The extracts were measured

without further dilution on an XSeries 2, Thermo Scientific ICP-MS instrument equipped

with a MiraMist nebulizer. Calibration was performed with a Certipur multielement standard

XXI.

In vitro cell studies

Normal Adult human dermal fibroblast cells (HDFs, Lonza) were cultured in manufacturer’s

recommended media (FGMTM-2 Growth Media) under 37 °C and 5% CO2. The cells

were then passaged at 80% confluency (passage number 5) and were used for all cell

studies. For in vitro cytocompatibility tests, two groups of FPSCs (before and after bending)

were placed in media during the course of study to release the possible undesired toxic

residuals. The HDF cells were seeded into 24 well plates (1 × 105 cells per well) and

were treated with appropriate media and incubated under 37 °C and 5% CO2 for up to 7

days. For the control, cells were treated with fresh media without contact with FPSCs. Cell

viability was evaluated by using a commercial calcein AM/ethidium homodimer-1 live/dead

kit (Invitrogen) on day 1 and 7 post culture. The samples were then visualized by using an

Axio Observer inverted microscope (ZEISS) and cell viability was calculated using ImageJ

software and reported as the ratio of live cells to total number of cells (live + dead). A

commercial PrestoBlue assay (Thermo Fisher) was also used to evaluate cell metabolic

activity according to manufacturer’s protocol.

Electronic system design and characterization

The electronic system consists of four main blocks for power management, data processing

and wireless communication, electrochemical instrumentation, and iontophoretic induction

(Supplementary Fig. 8). The power management block consists of an energy harvesting

Min et al.

Page 12

Nat Electron

. Author manuscript; available in PMC 2024 March 08.

Author Manuscript

PMIC (BQ25504, Texas Instruments) and a voltage regulator (ADP162, Analog Devices).

The PMIC utilizes maximum point power tracking (MPPT) to efficiently boost charge

the solar cell output of 5 V and charge the 5mF energy storage capacitor. The threshold

control unit of the PMIC enables the capacitor to power the rest of the system while the

capacitor voltage stays within a threshold voltage between 3~5 V. The voltage regulator then

regulates the capacitor voltage to a stable 2.8 V to supply the data processing and wireless

communication, and electrochemical instrumentation blocks.

Data processing and wireless communication are performed by a compact programmable

system-on-chip (PSoC) BLE module (Cyble-222014, Cypress Semiconductor) that

integrates a microcontroller (MCU) and BLE radio, and electrochemical instrumentation is

performed by an electrochemical front-end (AD5941, Analog Devices) and voltage buffers

(MAX40018, Analog Devices) that integrate various configurable blocks necessary for

electrochemical detection. The PSoC BLE module communicates with the host software

via BLE and controls the Electrochemical AFE via serial peripheral interface (SPI). The

electrochemical AFE is the core of the platform. The electrochemical AFE’s configurable

amplifiers can be configured for various electrochemical measurements at multiple modes

of measurement ranges and resolutions. For high bandwidth impedance measurements,

the high speed loop can be configured, and for lower bandwidth measurements such as

potentiometry, amperometry, and voltammetry, the low-power loop can be configured.

The AFE contains multiple elements such as a sequencer, a memory block, a waveform

generator, and a DFT hardware accelerator that enables independent operation of complex

electrochemical procedures, minimizing the workload of the microcontroller and the overall

power consumption. Furthermore, a switch matrix and multiplexer flexibly connect the

sensors and analog signals to the appropriate channels.

The iontophoresis induction block generates a high compliance-voltage constant current

with current monitoring to safely deliver current across the skin through a gel. A boost

converter (TPS61096, Texas Instruments) boosts the energy storage capacitor voltage

from the PMIC to a high compliance-voltage, and a BJT array (BCV62C, Nexperia)

is configured as a current mirror to supply a steady current through the analog switch

(DG468, Vishay Intertechnology) while the iontophoresis block is actuated. Furthermore,

the electrochemical AFE’s switch matrix enables the iontophoresis block to flexibly connect

to the electrochemical AFE’s low-power current measurement channel for iontophoresis

current monitoring overcurrent protection during iontophoresis.

The wearable device was powered by a custom developed quasi-2D FPSC in most

experiments, The power consumption of the system was characterized using a power profiler

(PPK2, Nordic Semiconductor), and the energy storage capacitor charging-discharging

curves were collected using an electrochemical workstation (CHI 660E). For experiments

under bright to room-light illumination conditions (>400 lx), a custom developed quasi-2D

FPSC was used to power the wearable device; for experiments under dim-light illumination

conditions (<300 lx), a commercial flexible solar cell was used (LL200-2.4-75, PowerFilm

Inc.). To validate the performance of the wearable device for electrochemical measurements,

we compared the potentiometric, amperometric, and voltammetric responses collected by

Min et al.

Page 13

Nat Electron

. Author manuscript; available in PMC 2024 March 08.

Author Manuscript

the wearable device under laboratory-light mode with those collected by an electrochemical

workstation (CHI 660E).

Microfluidic sensor patch fabrication and assembly

The PI substrates were cleaned prior to inkjet printing via O

plasma surface treatment

(Plasma Etch PE-25, 10–20 cm

min

−1

, 100 W, 150–200 mTorr) to remove debris

and improve surface hydrophilicity. Next, an inkjet printer (DMP-2850, Fujifilm) was

used for the sequential printing of silver (interconnects and connection pads, interdigitated

sweat rate sensor, and reference electrode), carbon (iontophoresis, counter, and working

electrodes), and PI (encapsulation). The reference and working electrodes were further

modified via electrochemical deposition (CHI 660E) and drop-casting methods for selective

electrochemical sensing. Meanwhile, a 50 W CO

laser cutter (Universal Laser System)

was used to pattern M-tape (3M 468MP) and PET layers to be further assembled onto the

sensor patch for microfluidic sweat processing. Z-axis conductive tape (3M 9703) was used

to electrically connect the encapsulated PCBs, solar cells, and microfluidic sensor patch

through the connection pads and interconnects printed on the PI substrate.

Both anode and cathode carbagels were prepared by heating DI water containing 3% w/w

agarose to 250 °C under constant stirring until the mixture became homogenous. After

cooling down the mixture to 165 °C, 1% w/w carbachol was added to the anode mixture,

and 1% w/w KCl was added to the cathode mixture. Then, the mixtures were poured into the

assembled microfluidic sensor patches’ carbagel cutouts, where the hydrogels solidified.

Biosensor preparation and characterization

An electrochemical workstation (CHI 660E) was used for electrochemical deposition,

and both the electrochemical workstation and the wearable device were used for sensor

characterization.

Reference electrode:

To form Ag/AgCl, 0.1 M FeCl

was drop-casted onto the inkjet-

printed Ag reference electrode for 30 s. A PVB reference cocktail was prepared by

dissolving 79.1 mg of PVB, 50 mg of NaCl, 1 mg of F127, and 0.2 mg of MWCNT into 1

ml of methanol. 1.66 μL of the PVB reference cocktail was drop-casted onto the Ag/AgCl

reference electrode and left to dry overnight such that the reference electrode can maintain a

steady potential regardless of the ionic strength of the solution.

Glucose sensor:

Au nano-dendrites were modified on a carbon working electrode by

applying a pulsed voltage from −0.9 V to 0.9 V at a frequency of 50 Hz in a solution

containing 50 mM HAuCl

and 50 mM HCl. A Prussian blue layer was electrochemically

deposited on the modified working electrode by performing cyclic voltammetry from −0.2

V to 0.6 V at a scan rate of 50 mV s

−1

for 20 cycles in a solution containing 2mM FeCl

2.5 mM K

[Fe(CN)

], 0.1 M KCl, and 0.1 M HCl. Then, the electrode was further modified

by performing cyclic voltammetry from 0 V to 0.8 V at a scan rate of 100 mV s

−1

for 8

cycles in a solution containing 5 mM NiCl

, 2.5 mM K

[Fe(CN)

], 0.1 M KCl, and 0.1

M HCl. A GOx enzyme cocktail was prepared by mixing 99 uL of 1% BSA, 1 uL of 2.5

Min et al.

Page 14

Nat Electron

. Author manuscript; available in PMC 2024 March 08.

Author Manuscript

% glutaraldehyde, and 0.25 uL of 10 mg/mL GOx. 1.66 μL of the enzyme cocktail was

drop-casted onto the modified working electrode and left overnight to dry.

Sodium sensor:

A carbon working electrode was modified in a solution containing 30

mg K

[Fe(CN)

]·3H

O, 206.1 mg NaPSS, 10.7 μL EDOT in 10 mL DI water by applying a

constant potential of 0.865 V for 10 min. A Na

selective membrane cocktail was prepared

by dissolving 1 mg of Na ionophore X, 0.55 mg Na-TFPB, 33 mg PVC, and 65.45 mg DOS

into 660 μL THF. 1.66 μL of the Na

selective membrane cocktail was drop-casted onto the

modified carbon working electrode and left to dry overnight.

pH sensor:

Au was deposited on a carbon working electrode by applying a constant

potential of 0 V for 30 s in a solution containing 50 mM HAuCl

and 50 mM HCl. A PANI

layer was electropolymerized on the Au modified working electrode by performing cyclic

voltammetry from −0.2 V to 1 V at a scan rate of 50 mV s

−1

for 50 cycles.

Biosensor characterization:

For in vitro characterizations for the Na

and sweat rate

sensors, NaCl solutions (12.5–200 mM) were prepared in DI water. For characterization of

the pH sensors, Mcllvaine’s buffers with pH values ranging from 4 to 8, and HCl-mediated

Mcllvaine’s buffer with a pH of 10 were used. For characterization of the glucose sensors,

glucose solutions (0–200 μM) were prepared in PBS buffers with pH ranging from 4 to 10.

For characterization of the sensors’ dependence on temperature, a ceramic hot plate (Thermo

Fisher Scientific) was used. For in vitro flow tests, a syringe pump (78-01001, Thermo

Fisher Scientific) was used to inject various fluids through the microfluidic sensor patch at

flow rates varying form (0.12–3 μL min

−1

On-body evaluation of the wearable device

The validation and evaluation of the wearable device were performed using human subjects

in compliance with the ethical regulations under protocols (ID 19-0892 and 21-1079)

that were approved by the Institutional Review Board (IRB) at the California Institute of

Technology (Caltech). Participating subjects between the ages of 18 and 65 were recruited

from the Caltech campus and neighboring communities through advertisement by posted

notices, word of mouth, and email distribution. All subjects gave written informed consent

before participation in the study. For all human studies, subjects cleaned their skin with

water and alcohol swabs before applying the wearable device on the skin.

System evaluation conditions:

For chemical sweat induction, the subjects were

illuminated under bright-light conditions for 10 min to enable light-powered iontophoresis

(55 μA, 10 min). Following iontophoretic stimulation, the subjects were illuminated under

either bright-light (14k lx), laboratory-light (1200 lx), or room-light (600 lx) illumination

conditions to enable continuous biomarker detection for the remainder of the study. Sweat

rate was measured periodically either with the impedimetric sweat rate sensor, visually, or

by both ways.

System evaluation with sugar intake:

For fasting and intake studies, subjects reported

to the laboratory after fasting overnight. For the iontophoresis-based studies, the wearable

Min et al.

Page 15

Nat Electron

. Author manuscript; available in PMC 2024 March 08.

Author Manuscript

device was applied to the ventral forearm region and the subject was illuminated under

bright-light (14k lx) conditions for the first 10 minutes to power iontophoresis. For the

remainder of the study, the subject was illuminated under lab-light (1200 lx) conditions

at rest, while the wearable device performed wireless multimodal monitoring of sweat

biomarkers with multiplexed glucose, pH, sodium, and temperature measurements occurring

at 8 s intervals, and sweat rate measurements occurring at 5 min intervals. The data

was wirelessly transmitted in real-time via BLE indications. For the iontophoresis intake

study, the subject was provided a soft drink containing 55 g of sugars. For the exercise-

based studies, the wearable device was applied to the forehead region, and the subject

was illuminated under lab-light (1200 lx) conditions throughout the entire study, wherein

subjects performed constant-load cycling (50 rpm) on a stationary exercise bike (Kettler

Axos Cycle M-LA) for 60 minutes. For the exercise intake study, the subject was provided a

soft drink containing 55 g of sugars.

System evaluation during daily activities:

For the full day study spanning from 9 AM

to 9 PM, the subject was iontophoretically stimulated

via

the wearable device for 10 min at 9

AM, 12 PM, 3 PM, and 6 PM. The microfluidics was reset before each iontophoresis section

to obtain continuous sweat rate reading. From 9 AM to 1 PM, the subject was outdoors

under the sun (100k lx); from 1 PM to 6 PM, the subject was under lab-light (1200 lx)

conditions; and from 6 PM to 9 PM, the subject was in room-light (600 lx) conditions.

From 9 AM to 6 PM, the wearable device performed multiplexed glucose, pH, Na

, and

temperature measurements occurring at 8 s intervals, and sweat rate measurements occurring

at 5 min intervals. The data was wirelessly transmitted

via

BLE indications. From 6 PM

to 9 PM, the wearable device performed multiplexed glucose, pH, sodium, and temperature

measurements occurring at 60 s intervals and transmitted the data wirelessly

via

BLE

advertisements, while sweat rate was evaluated optically every 10 min.

Supplementary Material

Refer to Web version on PubMed Central for supplementary material.

Acknowledgements

This project was supported by the National Institutes of Health grants R01HL155815 and R21DK13266, Office of

Naval Research grants N00014-21-1-2483 and N00014-21-1-2845, the Translational Research Institute for Space

Health through NASA NNX16AO69A, and National Science Foundation grant 2145802, (to W.G.) and by the

European Research Council Starting Grant ‘GEL-SYS’ under grant agreement no. 757931 (to M.K.). S.D. would

like to also acknowledge Marshall Plan Foundation that provided financial support for 3 months research visit to

California Institute of Technology that initiated this work.

Data availability

The main data supporting the results in this study are available within the paper and its

Supplementary Information. Source data for human studies in Figure 4 are provided with

this paper. All raw and analyzed datasets generated during the study are available from the

corresponding author on request.

Min et al.

Page 16

Nat Electron

. Author manuscript; available in PMC 2024 March 08.

Author Manuscript

References

1. Kim J, Campbell AS, de Ávila BE-F & Wang J Wearable biosensors for healthcare monitoring. Nat.

Biotechnol 37, 389–406 (2019). [PubMed: 30804534]

2. Ray TR et al. Bio-integrated wearable systems: A comprehensive review. Chem. Rev 119, 5461–

5533 (2019). [PubMed: 30689360]

3. Yang Y & Gao W Wearable and flexible electronics for continuous molecular monitoring. Chem.

Soc. Rev 48, 1465–1491 (2019). [PubMed: 29611861]

4. Heikenfeld J et al. Accessing analytes in biofluids for peripheral biochemical monitoring. Nat.

Biotechnol 37, 407–419 (2019). [PubMed: 30804536]

5. Libanori A, Chen G, Zhao X, Zhou Y & Chen J Smart textiles for personalized healthcare. Nat.

Electron 5, 142–156 (2022).

6. Someya T, Bao Z & Malliaras GG The rise of plastic bioelectronics. Nature 540, 379–385 (2016).

[PubMed: 27974769]

7. Bariya M, Nyein HYY & Javey A Wearable sweat sensors. Nat. Electron 1, 160–171 (2018).

8. Gao W et al. Fully integrated wearable sensor arrays for multiplexed in situ perspiration analysis.

Nature 529, 509–514 (2016). [PubMed: 26819044]

9. Choi J, Ghaffari R, Baker LB & Rogers JA Skin-interfaced systems for sweat collection and

analytics. Sci. Adv 4, eaar3921 (2018). [PubMed: 29487915]

10. Bandodkar AJ et al. Battery-free, skin-interfaced microfluidic/electronic systems for simultaneous

electrochemical, colorimetric, and volumetric analysis of sweat. Sci. Adv 5, eaav3294 (2019).

[PubMed: 30746477]

11. Nyein HYY et al. Regional and correlative sweat analysis using high-throughput microfluidic

sensing patches toward decoding sweat. Sci. Adv 5, eaaw9906 (2019). [PubMed: 31453333]

12. Kim S et al. Soft, skin-interfaced microfluidic systems with integrated immunoassays, fluorometric

sensors, and impedance measurement capabilities. Proc. Natl. Acad. Sci. U.S.A 117, 27906–27915

(2020). [PubMed: 33106394]

13. Son D et al. Multifunctional wearable devices for diagnosis and therapy of movement disorders.

Nat. Nanotech 9, 397–404 (2014).

14. Niu S et al. A wireless body area sensor network based on stretchable passive tags. Nat. Electron 2,

361–368 (2019).

15. Sempionatto JR et al. An epidermal patch for the simultaneous monitoring of haemodynamic and

metabolic biomarkers. Nat. Biomed. Eng 5, 737–748 (2021). [PubMed: 33589782]

16. Emaminejad S et al. Autonomous sweat extraction and analysis applied to cystic fibrosis and

glucose monitoring using a fully integrated wearable platform. Proc. Natl. Acad. Sci. U.S.A 114,

4625–4630 (2017). [PubMed: 28416667]

17. Lee H et al. Wearable/disposable sweat-based glucose monitoring device with multistage

transdermal drug delivery module. Sci. Adv 3, e1601314 (2017). [PubMed: 28345030]

18. Yang Y et al. A laser-engraved wearable sensor for sensitive detection of uric acid and tyrosine in

sweat. Nat. Biotechnol 38, 217–224 (2020). [PubMed: 31768044]

19. Torrente-Rodríguez RM et al. Investigation of cortisol dynamics in human sweat using a graphene-

based wireless mHealth system. Matter 2, 921–937 (2020). [PubMed: 32266329]

20. Kwon K et al. An on-skin platform for wireless monitoring of flow rate, cumulative loss and

temperature of sweat in real time. Nat. Electron 4, 302–312 (2021).

21. Sonner Z, Wilder E, Gaillard T, Kasting G & Heikenfeld J Integrated sudomotor axon reflex sweat

stimulation for continuous sweat analyte analysis with individuals at rest. Lab Chip 17, 2550–2560

(2017). [PubMed: 28675233]

22. Simmers P, Li SK, Kasting G & Heikenfeld J Prolonged and localized sweat stimulation by

iontophoretic delivery of the slowly-metabolized cholinergic agent carbachol. J. Dermatol. Sci 89,

40–51 (2018). [PubMed: 29128285]

23. Yu Y et al. Biofuel-powered soft electronic skin with multiplexed and wireless sensing for human-

machine interfaces. Sci. Robot 5, eaaz7946 (2020). [PubMed: 32607455]

Min et al.

Page 17

Nat Electron

. Author manuscript; available in PMC 2024 March 08.

Author Manuscript

24. Song Y et al. Wireless battery-free wearable sweat sensor powered by human motion. Sci. Adv 6,

eaay9842 (2020). [PubMed: 32998888]

25. Yin L et al. A passive perspiration biofuel cell: High energy return on investment. Joule 5, 1888–

1904 (2021).

26. Yin L et al. A self-sustainable wearable multi-modular E-textile bioenergy microgrid system. Nat.

Commun 12, 1542 (2021). [PubMed: 33750816]

27. Xu F et al. Scalable fabrication of stretchable and washable textile triboelectric nanogenerators as

constant power sources for wearable electronics. Nano Energy 88, 106247 (2021).

28. Park S et al. Self-powered ultra-flexible electronics via nano-grating-patterned organic

photovoltaics. Nature 561, 516–521 (2018). [PubMed: 30258137]

29. Meng K et al. A wireless textile-based sensor system for self-powered personalized health care.

Matter 2, 896–907 (2020).

30. Polyzoidis C, Rogdakis K & Kymakis E Indoor perovskite photovoltaics for the internet of things

—challenges and opportunities toward market uptake. Adv. Energy Mater 11, 2101854 (2021).

31. Mathews I, King PJ, Stafford F & Frizzell R Performance of III–V solar cells as indoor light

energy harvesters. IEEE J. Photovoltaics 6, 230–235 (2016).

32. Espinosa N, Hösel M, Angmo D & Krebs FC Solar cells with one-day energy payback for the

factories of the future. Energy Environ. Sci 5, 5117–5132 (2012).

33. Roy P, Kumar Sinha N, Tiwari S & Khare A A review on perovskite solar cells: Evolution of

architecture, fabrication techniques, commercialization issues and status. Sol. Energy 198, 665–

688 (2020).

34. Gao F, Zhao Y, Zhang X & You J Recent progresses on defect passivation toward efficient

perovskite solar cells. Adv. Energy Mater 10, 1902650 (2020).

35. Green MA et al. Solar cell efficiency tables (Version 58). Prog. Photovolt. Res. Appl 29, 657–667

(2021).

36. Zheng H et al. Emerging organic/hybrid photovoltaic cells for indoor applications: Recent

advances and perspectives. Sol. RRL 5, 2100042 (2021).

37. Hashemi SA, Ramakrishna S & Aberle AG Recent progress in flexible–wearable solar cells for

self-powered electronic devices. Energy Environ. Sci 13, 685–743 (2020).

38. Zhao J et al. A fully integrated and self-powered smartwatch for continuous sweat glucose

monitoring. ACS Sens 4, 1925–1933 (2019). [PubMed: 31271034]

39. Mallick A & Visoly-Fisher I Pb in halide perovskites for photovoltaics: reasons for optimism.

Mater. Adv 2, 6125–6135 (2021).

40. Hamann D et al. Jewellery: alloy composition and release of nickel, cobalt and lead assessed with

the EU synthetic sweat method. Contact Derm 73, 231–238 (2015).

41. World Health Organization. Regional Office for Europe. (2000). Air quality guidelines for Europe,

2nd ed. World Health Organization. Regional Office for Europe.

https://apps.who.int/iris/handle/

10665/107335

42. Hailegnaw B et al. Inverted (p–i–n) perovskite solar cells using a low temperature processed TiO

interlayer. RSC Adv 8, 24836–24846 (2018). [PubMed: 30713680]

43. Venkateswararao A, Ho JKW, So SK, Liu S-W & Wong K-T Device characteristics and material

developments of indoor photovoltaic devices. Mater. Sci. Eng. R Rep 139, 100517 (2020).

Min et al.

Page 18

Nat Electron

. Author manuscript; available in PMC 2024 March 08.

Author Manuscript

Figure 1 |. Schematics and images of the ambient light-powered battery-free lab on the skin.

, Illustration of the energy autonomous wearable device that is powered from both

outdoor and indoor illumination

via

a quasi-2D flexible perovskite solar cell (FPSC) and

perform multiplexed wireless biomolecular analysis across a wide range of activities.

Carbagel, carbachol hydrogel; M-tape, medical tape; PET, polyethylene terephthalate; PI,

polyimide.

, Exploded 3D model of the layer assembly of the wearable device.

, Photo

of an inkjet-printed disposable microfluidic sensor patch that contains an iontophoretic

module for autonomous sweat stimulation, microfluidics for sweat sampling, multiplexed

electrochemical biosensors for perspiration analysis, and an impedimetric sweat rate sensor.

Scale bar, 0.5 cm.

, Photo of the wearable device assembled in origami-style. Scale bar, 1

cm.

, Photo of the wearable device worn on the ventral forearm and wirelessly connected to

a custom developed mobile app over BLE. Scale bar, 2 cm.

Min et al.

Page 19

Nat Electron

. Author manuscript; available in PMC 2024 March 08.

Author Manuscript