Inkjet-Printed Carbon Nanotubes for Fabricating a Spoof Fingerprint on Paper

Soum, Veasna; Park, Soo‐Young; Brilian, Albertus Ivan; Kim, Yunpyo; Ryu, Madeline Y.; Brazell, Taler; Burpo, F. John; Parker, Kevin Kit; Kwon, Oh‐Sun; Shin, Kwanwoo

doi:10.1021/acsomega.9b00936

Cited by 23 publications

(26 citation statements)

References 42 publications

(79 reference statements)

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Carbon nanotubes are common materials used for printing on various substrates based to obtain accurate and controllable conductive circuits and sensors [18][19][20][21]. A counterfeit fingerprint with electrical and geometric patterns of exquisite ridges and furrows of one to five layers was printed on paper using an inkjet printer; the printed patterned CNT film electrode as the top plate of the capacitive sensor could unlock a smartphone [22]. Some researchers in a previous study fabricated an inkjet-printed 20-layer CNT-based strain sensor with a 4.7% standard deviation over 20 cycles for strains between 0 and 800 µε [23].…”

Section: Introductionmentioning

confidence: 99%

A Fully Inkjet-Printed Strain Sensor Based on Carbon Nanotubes

et al. 2020

View full text Add to dashboard Cite

A fully inkjet-printed strain sensor based on carbon nanotubes (CNTs) was fabricated in this study for microstrain and microcrack detection. Carbon nanotubes and silver films were used as the sensing layer and conductive layer, respectively. Inkjet-printed CNTs easily undergo agglomeration due to van der Waals forces between CNTs, resulting in uneven films. The uniformity of CNT film affects the electrical and mechanical properties. Multi-pass printing and pattern rotation provided precise quantities of sensing materials, enabling the realization of uniform CNT films and stable resistance. Three strain sensors printed eight-layer CNT film by unidirectional printing, rotated by 180° and 90° were compared. The low density on one side of eight-layer CNT film by unidirectional printing results in more disconnection and poor connectivity with the silver film, thereby, significantly increasing the resistance. For 180° rotation eight-layer strain sensors, lower sensitivity and smaller measured range were found because strain was applied to the uneven CNT film resulting in non-uniform strain distribution. Lower resistance and better strain sensitivity was obtained for eight-layer strain sensor with 90° rotation because of uniform film. Given the uniform surface morphology and saturated sheet resistance of the 20-layer CNT film, the strain performance of the 20-layer CNT strain sensor was also examined. Excluding the permanent destruction of the first strain, 0.76% and 1.05% responses were obtained for the 8- and 20-layer strain sensors under strain between 0% and 3128 µε, respectively, which demonstrates the high reproducibility and recoverability of the sensor. The gauge factor (GF) of 20-layer strain sensor was found to be 2.77 under strain from 71 to 3128 µε, which is higher than eight-layer strain sensor (GF = 1.93) due to the uniform surface morphology and stable resistance. The strain sensors exhibited a highly linear and reversible behavior under strain of 71 to 3128 µε, so that the microstrain level could be clearly distinguished. The technology of the fully inkjet-printed CNT-based microstrain sensor provides high reproducibility, stability, and rapid hardness detection.

show abstract

Section: Introductionmentioning

confidence: 99%

A Fully Inkjet-Printed Strain Sensor Based on Carbon Nanotubes

et al. 2020

View full text Add to dashboard Cite

show abstract

“…Conductive ink coating is the most simple technique for creation of a conductive layer on the thread [ 15 ] and carbon nanotube (CNT) is a promising additive for conductive ink due to its high conductivity and high surface area. [ 16 ] For enzyme‐based sensor, preservation of enzymatic activity is also critical; thus, chitosan is selected for enzyme preservation on the electrode using hydroxyl (OH) and amine (NH 2 ) groups for binding with enzymes via covalent bonding, electrostatic interaction, or physical entrapment. [ 14,17 ] Furthermore, the liquid absorption efficiency is also essential for sweat biomarker absorption, thus cellulose nanofibers (CNFs) was chosen for thread surface coating owing to its high water absorption property and high surface area.…”

Section: Introductionmentioning

confidence: 99%

Thread‐Based Wristwatch Sensing Device for Noninvasive and Simultaneous Detection of Glucose and Lactate

Promphet

Thanawattano

Buekban

et al. 2022

Adv Materials Technologies

View full text Add to dashboard Cite

Glucose is a key biomarker for both type 1 and type 2 diabetes [2] and an effective approach for glucose monitoring is essential for diabetes management. Commonly, glucose levels have been measured by blood drawing requiring a painful sample collection. Alternatively, glucose can be detected in other biofluids such as tears, saliva, and sweat. [3] To avoid pain and infection risk arising from traditional invasive diagnosis, noninvasive methods have been explored. Sweat can be collected continuously and may be less prone to contamination than other biofluids. [4] Glucose level in sweat has been reported to be in a range of 0.01-1.11 × 10 −3 m and it is correlated well with blood glucose levels. [5] Likewise, lactate is an important biomarker for pressure ischemia, and hypoxia. [6] It has been reported that the increase of lactate level is directly related with DKA which is a serious complication of diabetes. [7] Wearable sensors play an important role for self-health monitoring. [8] However, the commercial wearable sensors such as Fitbit, Garmin, and Apple watch provide only physical information, such as heart rate without chemical information of the wearer. Since the electrochemistry is a simple, rapid, and portable analytical technique, the researchers have attempted to develop noninvasive wearable chemical sensors based on electrochemical An electrochemical sensing device based on a cotton-thread electrode for real-time and simultaneous detection of sweat glucose and sweat lactate is reported. The cotton thread surfaces are simply modified by cellulose nanofibers/carbon nanotube ink-Prussian blue/chitosan to enhance liquid adsorption, bioreceptor immobilization, and sensor performance in addition to minimize potential irritation and allergies on the wearer's skin. The modified thread surfaces are characterized by laser scanning confocal microscopy, scanning electron microscopy, and Fourier transform Raman spectroscopy. Amperometry is carried out via hydrogen peroxide detection for electrochemical characterization of the modified thread electrodes. A circuit and digital readout of this wearable sensor are customized designed to be integrated with thread electrodes for real-time and simultaneous detection of sweat glucose and sweat lactate. The wristwatch sensing device provides a linear range of 0.025-3 × 10 −3 m with a detection limit of 0.025 × 10 −3 m for glucose and a linear range of 0.25-35 × 10 −3 m with a detection limit of 0.25 × 10 −3 m for lactate. This device can effectively determine the cut-off levels of both glucose and lactate, which can distinguish between a normal individual and one with a diabetic condition. This platform opens a new avenue for noninvasive and real-time detection of other sweat biomarkers.

show abstract

“…A recent study by Roy et al showed that the same simulated “MasterPrint” with common arrangements of minutiae can find a match to 10% of phone users . It is also becoming easier to make illicit forgeries of fingerprints from images in a database or latent fingerprints; as suchinkjet and 3D printing of spoofing fingerprints have been reported recently. , These issues highlight the urgent need for better fingerprint scanning resolution and matching algorithms.…”

Section: Introductionmentioning

confidence: 99%

Three-Dimensional Conductive Fingerprint Phantoms Made of Ethylene-Vinyl Acetate/Graphene Nanocomposite for Evaluating Smartphone Scanners

Schultz

Fawzy

Nasirpouri

et al. 2021

ACS Appl. Electron. Mater.

View full text Add to dashboard Cite

Fingerprints consist of unique patterns of skin ridges and valleys, and are commonly described by three levels of feature details. Most fingerprint identification systems rely on matching only first- and second-level details; their calibration using unrealistic targets combined with human sampling are cumbersome and time-consuming. We have developed a true-to-life fingerprint phantom with optimized conductive properties and third-level fingerprint details for developing more reliable matching algorithms for popular capacitive fingerprint scanners. An impression of a live finger is made into a solvent-softened polycarbonate template, which is subsequently adapted to thermally mold ethylene-vinyl acetategraphene (EVA-G) nanocomposite of satisfactory conductivity (1.2 ± 0.1 × 10–3 S/m) and mechanical flexibility. It was confirmed with SEM, optical, and profilometry imaging that the phantom made of EVA-G nanocomposite replicates the three-dimensional morphology of fingerprint with high fidelity, including well-defined third-level details. The EVA-G phantoms can operate capacitive scanners in popular brands of smartphones and tablets with either iOS or Android operating systems (>80% success rate). As these permanent phantoms include defined third-level details based on real fingerprints, their potential application as calibration standards for developing the next generation of scanners with improved security is warranted.

show abstract

Inkjet-Printed Carbon Nanotubes for Fabricating a Spoof Fingerprint on Paper

Cited by 23 publications

References 42 publications

A Fully Inkjet-Printed Strain Sensor Based on Carbon Nanotubes

A Fully Inkjet-Printed Strain Sensor Based on Carbon Nanotubes

Thread‐Based Wristwatch Sensing Device for Noninvasive and Simultaneous Detection of Glucose and Lactate

Three-Dimensional Conductive Fingerprint Phantoms Made of Ethylene-Vinyl Acetate/Graphene Nanocomposite for Evaluating Smartphone Scanners

Contact Info

Product

Resources

About