Sensor Research in NASA, Director Meyya Meyyappan, NASA Ames Research Center
M. Meyyappan NASA Ames Research Center Moffett Field, CA 94035 email: firstname.lastname@example.orgAcknowledgements: Jing Li, Y. Lu, Jessica Koehne, Cattien Nguyen, Jeong-Soo Lee
Innovation: Breaking StereotypeSince 1960 ~ SiO2(solid) Gate high-k(solid) Fluid S D Gate Gas/liquid S D • Solid-state Gate Dielectric • Insolating gate to drain“The guys like us who work with the <Fluid Gate Dielectric>stuff every day consider silicon • Stimuli responsive fluiddioxide the greatest gift from • ExchangeableGod ”, John S. Suehle, NIST • Drop-on-demand
Structure:Nanogap Gate Dielectric FET Gate oxide D Removal D S SIndependent Double-Gate FinFET Nanogap Double-Gate FinFET• Flexible threshold voltage • Radioresponsive liquid - radiation sensor• Low-power application • Chemical responsive liquid - gas sensor • Bio responsive treatment - bio sensor
Prototype of Nanogap FET Liquid Sol-Gel DNA Protein 4
Bacteria DNA Protein Insulating Dielectrics (optional) e- e- e- Electrical contact Si waferDirectly interface solid-state electronics with DNAs, RNAs, proteins, and microbesin a miniaturized multiplex chip for quick detection(Lock and Key approach)
Nanoscale electrodes create a dramatic improvement in signal detection over traditional electrodes Traditional Macro- or NanoelectrodeElectrode Micro- Electrode Array Insulator Nano- • Scale difference between macro- • CNT tips are at the scale close Electrode /micro- electrodes and molecules is to biomolecules tremendous • Dramatically reduced • Background noise on electrode background noise surface is therefore significant • Multiple electrodes result in • Significant amount of target magnified signal and desired molecules required redundance for statistical reliability. X X Candidates: SWNTs, MWNTs, Vertical CNFs or Vertical SiNWs Source: Jun Li
Embedded CNT Arrays after r. e. Metal Film c. e. planarization Deposition w. e. Catalyst EC Deposition Plasma CMP CVD TEOS CVD 300 mm30 dies on a 4” Si wafer 200 mm
Troponin Detection for Heart Disease i 0.20 0.15 (a) bare electrodeCurrent/10 -6 A 0.10 5.00 g 0.00 -5.00 f e (b) bare / anti–cTnI electrode d -0.10 c b -0.15 a 0.8 0.6 0.4 0.2 0.0 -0.2 -0.4 Potential (V vs. SCE) curve c–g represent 0.25, 0.5, -120 ii 1.0, 5.0, and 10.0 ng ml-1 -100 human cTnI antigen binding -80 to the bare electrode afterZim (kΩ) -60 g f immobilization with anti–cTnI -40 e d c antibody respectively. -20 b a 0 0 15 30 45 60 75 90 Zre (kΩ)
WHY: Effective Clinical Technique • DBS has been clinically effective in the treatment of movement disorder HOW: Four Interrelated Hypothesis • Paradox of similar effects to lesioning of target structure is explained by the following: -Depolarization Blockage -Synaptic Inhibition -Synaptic Depression -Stimulation Induced Modulation of Pathways PROBLEMS: Indiscriminate Activation • Stimulation indiscriminately affects all tissue around the electrode (size: 1.27mm diameter with four 1.5mm contacts) • Crude method without feedback IMPROVEMENTS: Targeted Activation to specific location down to sub mm scale Obtain feedback information – such as neurotransmitter levelsMedtronic
Discrimination of Dopamine, Serotonin and Ascorbic Acid a) Baseline-corrected DPV plots of individual detection of 10 µM DA, 1 mM AA, and 10 µM 5-HT with a glassy carbon electrode b) Background subtracted DPV plots of individual detection of 10 µM DA, 1 mM AA, and 10 µM 5-HT with a carbon nanofiber electrode c) Baseline-corrected DPV plots of a ternary mixture of 10 uµM DA, 1 mM AA, and 10 µM 5-HT with a glassy carbon electrode d) Baseline-corrected DPV plots of a ternary mixture of 10 uµM DA, 1 mM AA, and 10 µM 5-HT with a carbon nanofiber electrode e) Baseline-corrected DPV plots of a ternary mixture of 1 mM AA, 10 µM DA, and 5-HT (10 µM, 5 µM, 2.5 µM, 1 µM, 0.5 µM, 0.25 µM) with a carbon nanofiber electrode f) Baseline-corrected DPV plots of a ternary mixture of 1 mM AA, 10 µM 5-HT, and DA (10 µM, 5 µM, 2.5 µM, 1 µM, 0.5 µM, 0.25 µM, 0.1 µM) with a carbon nanofiber electrode
(a) and (b) : EIS spectra with an antibody probe(c) and (d) : with an aptamer probe (b) and (d) use control targets
Rct decreases after washing with elution buffer and returns to a similar value to theaptamer functionalized chip, i.e. the ricin protein is washed away but the aptamer proberemains bound to the VACNFs. Upon reintroduction to ricin, Rct increases to a valuesimilar to the original ricin-bound EIS curve. Thus, the aptamer retains its bioactivity andis able to be regenerated, thus indicating the reusability of the aptamer based biosensor.
300 mm 200 mm Potential applications: 30 dies on a 4” Si wafer (1) Lab-on-a-chip applications (2) Early cancer detectionThe electronic chip needs to (3) Infectious disease detectionbe integrated with (4) Environmental monitoringmicrofluidics for sample (5) Pathogen detection
• First, a single device has no value. We need a system consisting of: - Sensor array (Electronic Nose, Pattern recognition…) - Pre-concentrator ? - Sample delivery, Microfan? Jet? - Signal processing chip - Readout unit (data acquisition, storage) - Interface control I/O - Integration of the above (Nano-Micro-Macro)• Criteria for Selection/Performance - Sensitivity (ppm to ppb as needed) - Absolute discrimination - Small package (size, mass) - Low power consumption - Rugged, reliable - Preferably, a technology that is adaptable to different platforms - Amenable for sensor network or sensor web when needed
• Compared to existing systems, potential exists to improve sensitivitylimits, and certainly size and power needs• Why? Nanomaterials have a large surface area. Example: SWCNTshave a surface area ~1600 m2/gm which translates to the size of afootball field for only 4 gm.• Large surface area large adsorption rates for gases and vapors changes some measurable properties of the nanomaterial basis for sensing - Dielectric constant - Capacitance - Conductance - - 4 grams
• Easy production using simple microfabrication • 2 Terminal current-voltage measurement • Low energy barrier - Room temperature sensing • Low power consumption: 50-100 µW/sensor Processing Steps 1. Interdigited microscale electrode device fabrication 2. Disperse purified nanotubes in DMF (dimethyl formamide) 3. Solution casting of CNTs across the electrodesJing Li et al., Nano Lett., 3, 929 (2003)
• Test conditions: Flow rate: 400 ml/min Temperature: 23 oC Purge & carrier gas: N2 , Air • Measure response to various concentrations, plot conductance change vs. concentration • Sensor recovery can be speeded up by exposing to UV light, heatingDetection limit for NO2 is 4 ppb. or
• Use of a sensor array (32-256sensors)• Variations among sensors - physical differences - coating - doping - nanowires Operation: 1. The relative change of current or resistance is correlated to the concentration of analyte. 2. Array device “learns” the response pattern in the training mode. 3. Unknowns are then classified in the identification mode. 4. Sensor can be “refreshed” using UV LED, heating or purging
Analyte Sensitivity/Detection LimitCH4 1 ppm in airHydrazine 10 ppb tested by KSCNO2 4.6 ppb in airNH3 0.5 ppm in airSO2 25 ppm in airHCl 5 ppm in airFormaldehyde 10 ppb in air tested by JPLAcetone 10 ppm in airBenzene 20 ppm in airCl2 0.5 ppm in airHCN 10 ppm in N2Malathion Open bottle in airDiazinon Open bottle in airToluene 1 ppm in airNitrotoluene 256 ppb in N2H2O2 3.7 ppm in airDMMP 100 ppb in air
2nd 1st expos expos ure ure 3rd 4th exposure exposure• Pristine, Rh-loaded and PEI- Gaps functionalized SWCNT: all give fast Fingers response ~18 seconds• Recovery time ~1 min• Detection limit: 10-20 ppb
H2O2 • Fast sensor response: 6 seconds • Detection limit: 25 ppm Mechanisms? polyethyleneimine (PEI)-functionalized •Electron donation from an SWCNTs oxidizer like H2O2 decreases the• Headspace test: sensor exposed to conductivity of the inherently p- open bottles of H2O2, water, and type SWCNTs in air methanol •PEI-functionalized SWCNTs have• Substantial difference in responses been shown to be n-type. Their conductivity increases after• Adequate to construct e-nose with exposure to H2O2 32-sensor elements
A 32-channel sensor chip (1cm x 1cm) with different nanostructured materials for chemical sensing 5”NASA Ames chemical sensor module wason a secondary payload of a Navysatellite (Midstar-1) that was launchedvia Atlas V on March 9, 2007. The nanosensor module (5”x 5”x 1.5”) contains a chip of 32 sensors, a data acquisition board, sampling system, and a tank with 20ppm NO2 in N2.
1. Temperature data 2. Humidity data 3. Pressure data 4. Altitude data 9. Chemical IDSensor state and concentration 5. Sensor state Pump condition 8. Pump state Pump location 7. Sensor settings 6. App information
• Some diseases have specific markers which show up in excess concentration in the breath of sick people relative to normal population. Examples: Acetone in diabetes patients NO in asthma patients•In these cases, simple chemical sensors (gas/vapor sensing) withpattern recognition can be valuable.
Room Temperature Sensing of Acetone• ZnO nanoparticles show a good response to 1-50 ppm at room temperature• Humidity effects are important and have been investigated• ZnO NP is a useful candidate to include in the sensor array for providing reliable patterns
• Emerging of nano will NOT eclipse micro or MEMS• Indeed, in many cases (but not all), nano-based products would needMEMS to achieve desirable performance goals. This means,hierarchical Nano - Micro - Macro Integration• Nanotechnology, if it succeeds in the market place, will breathe new lifeand renewed vigor into the MEMS (research, applications,infrastructure, fabs, products, market, companies, profit…..)• We have discussed some examples, in terms of chemicaland bio sensors , where the “heart and soul” of the systemis a nanomaterial, or some nano phenomena and the system itself needs a seamless integration to micro/macro for a technically feasible and commercially viable product.