Integrated Nanosensors for Health and Environmental Monitoring

Transcription

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
manfred.bammer@ait.ac.at
 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)