Integrated Nanosensors for Health and Environmental Monitoring

Integrated Nanosensors for Health and Environmental Monitoring Hubert Brückl

Miniaturization roadmap in medical devices Heterogeneous Integration

Yole Developpment

Sensors and Sensorsystems for applications in Health & Environment

Complexity

Micro-/Nano-Sensor-Systems

• magnetic Lab-on-a-Chip / Bead • 3D-SiP integrated gas sensor • µ-fluidic integrated biosensor system

NanoSensors

• magnetoresistive sensor • gas sensor • photonic biosensor

Level of Integration

Outline • transducers for magnetic biosignals • in-line in-vitro monitoring of mammalian cell cultures • CMOS integrated gas sensors • IR camera detector with tunable wavelength • Integrated Photonic Wavguides

B-field Ranges & Frequencies

B-field Magnetic field Range

1 mT (10-3) 1 T (10-6) 1 nT

1 nT

1 gauss  10-4 T ~ earth’s B-field Industrial 1A@1m

(10-9)

1 pT 1 pT (10-12)

Industrial

Geophysical Geophysical Magnetic Anomaly Magnetic

Magnetocardiography Magneto-cardiography MagnetoMagnetoencephalography encephalography

Anomaly

1 fT (101-15fT)

1 aT (10-18) 0.0001 0.0001

0.01 0.01

11

Frequency (Hz)

100 100

Non-destructive evaluation & hdd’s

10,000 10,000

Adapted from “Magnetic Sensors and Magnetometers”, P. Ripka, Artech, (2001)

Recording of small magnetic fields

3D Fluxgate, Bartington, UK

SQUID: Maternal-Fetal Recording noise power spectral density

4 k BT  S  02 M  Micro‐fluxgate sensor with 2 cores and 2 interlaced coils, on a  1x1 mm2 silicon chip at MEMS facility of CEA‐LETI (right: Cross  section of copper coil)

Combination of TMR and fluxgate principle current line MTJ switches periodically between two resistance states

DC field Hx

magnetic tunnel junction (MTJ)

alternating magnetic field H(t) = H0sin(2ft) 10 m

MTJ layer stack

300 m

2.5 nm MgO

Image of the sensor bonded to a PCB

Targeted breakthrough

Noise (pT/rtHz)

1.0E+04 1.0E+02 1.0E+00

Hall

GMI ME AMR, GMR, TMR combi TMR/fluxgate

MCG Fluxgate SQUID, 77K

1.0E-02 1.0E-04 1.0E-07

SQUID, 4K 1.0E-05

1.0E-03

1.0E-01

1.0E+01

Volume (cm^3) Aim: online monitoring of magnetic biosignals • electrode-less (e.g. fetal heart, toco control) • low-power • light weight • wearable, combination with data transfer system

Online in-vitro monitoring of stem cells • human mesenchymal stem cells derived from bone marrow • useful for therapy after primary cell isolation and culture-expansion • requirement: high quality cells / problem: quality diminishes during cultivation • standard quality check: end-point detection • demand to sensor technology: reliable, label-free, continuous, online in incubator

http://www.news.wisc.edu/packages/stemcells/illustration.html

Online in-vitro monitoring of stem cells

 37 °C temperature for optimized cell growth  5 % CO2-concentration to stabilize the pHvalue of the culture medium

 >95% rel. humidity to minimize culture medium loss due to evaporation

Measurement principle Capacitance change in an interdigital electrode sensor (IDES) ac voltage with impedance change

 Glass substrate AF45  Ti/Au metallization  50um gap / 50um finger width

 1.8 x 2 mm² per field

System Design  battery-free sensor tags in standard 6-well titer plate

 reader connected to data acquisition unit (e.g. PC)

 wireless energy and data transfer based on RFID Antenna coil

 13.56 MHz with 250 kHz subcarrier

 advantages: to PC

 ease of handling and µC

manipulation

 encapsulated, humidityproven

 sterilisation  re-usable

Prototype: measurement technique

µC

Frequency Generator

Sensor or Reference resistor

I/VConverter

ADC

 Wireless battery-less sensor system  Tolerance < 2%  assembly of single components  < 25mW power consumption

Phase trigger Bypass

Peak detector

RFID: interrupted antenna signal

 

RF disturbs sensor signal RF interrupted during sensor measurement

Measurements of cell cultures  On sensor osteogenic and adipogenic differentiation

 A) MSC undergoing osteoblastogenesis  B) Adipogenic differentiation  Compiled impedance signals from 9 parallel measurements of differentiating (difference signal to untreated controls)

S. Reitinger, J. Wissenwasser, W. Kapferer, R. Heer, G. Lepperdinger, “Electric impedance sensing in cell-substrates for rapid and selective multipotential differentiation capacity monitoring of human mesenchymal stem cells” Biosensors and Bioelectronics 34 (2012) 63– 69

NFC Applications for HealthCare Contact: Manfred Bammer, BU Biomedical Systems [email protected]

 Detection of filling level in syringes, etc.  Capactitve measurement  NFC data transfer

 Indication of Symbols  Inductive positioning measurement  NFC data transfer

© Images: AIT & Seibersdorf Laboratories

Conclusion Sensor integration opens new market possibilities:  Sensor miniaturization  Technology fusion (sensor, actuator, software, RFID, ..)  Smart sensors (readout, signal conversion / evaluation, transfer)

Smart systems:

Sensors

Transfer Central Processing Unit / Memory Energy

Actuators

Team Magnetic biosignal sensors: Theo Dimopoulos Jörg Schotter Astrit Shoshi Moritz Eggeling Leoni Breth Hubert Brückl PD Dr. D. Suess, TU Wien Prof. J. Kosel, KAUST

Cell monitoring: Rudolf Heer Jürgen Wissenwasser Markus Milnera Prof. G. Lepperdinger, Institute for biomedical Ageing Research Prof. M. Vellekop, TU Wien

Gas Sensors IR camera detector with tunable wavelength Integrated Photonic Waveguides

D.-H. Kim, N. Lu, R. Ghaffari, J.A. Rogers, “Inorganic semiconductor nanomaterials for flexible and stretchable bio-integrated electronics”, Science 333, 838 (2011)