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(2ft) 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)
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