Multidisciplinary Aspects of Developing Small Sensing Devices
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Multidisciplinary Aspects of Developing Small Sensing Devices for Monitoring Chemicals and Biochemicals Steve Semancik Biomolecular Measurement Division National Institute of Standards and Technology Gaithersburg, Maryland USA [email protected] 100 mm 300 µm 200 nm Chemiresistive Plasmonic Gas Electrochemical Gas Sensing & Solution Sensing DNA-Based Monitoring small device platforms, nanomaterials, temperature variation National Institute of Standards and Technology (NIST) Gaithersburg, Maryland Contributors to efforts at NIST: Materials Platforms Gas Sensing Biosensing Kurt Benkstein John Suehle Doug Meier* Charles Choi* Carlos Martinez* Mike Gaitan Phil Rogers* Herman Sintim Josh Hertz* Richard Cavicchi Barani Raman Zuliang Shen Tekin Kunt Sarah Robinson Yangyang Zhao Acknowledgments: Technical Support - Mike Carrier, Chip Montgomery Funding - *NRC Postdoctoral Associateship Program Growing Demand for Sensors: Examples iPhone and • tablet apps, • wearables • • • • Fitbit • Electronics/interfacing/communication components are much more mature (low $$) • Physical sensing is more prominent in commercial devices – easier (fewer degrees of freedom) • Need good sensor devices for chemicals/biochemicals - reliable “chemical signals” chemical/biochemical interactions produce a richness that is much more challenging (sensitivity, interferences) Microdevice Sensing Technology device-based electronic sensing can add convenience at low cost Acoustic Calorimetric Electrochemical Optical Magnetic Resistive Data Data CollectionData Processing (Bio)Chemical Input Signal Output learned responses are stored Themes • Functional microplatforms • Integrated nanomaterials for transduction • Signal processing of data streams • Operational concepts and enabling technology Bio-Inspiration for Chemical Detection Trained Dogs Insects tracking low molecular conc’s.of target reliable detection of drugs, explosives molecules to locate and disease [not overly food or a mate convenient or network friendly] evolutionary success (biological olfaction) challenges “electronic noses” (artificial olfaction) “system” is sensitive and fast Measurement Choices: Sensors vs Instruments Instruments larger, more expensive, “gold standard” intrinsic molecular properties Direct measurement of chemical target Mass spectrometry IR-vis-UV/fluorescence spectroscopy photo-electron spectroscopy NMR spectroscopy Orbitrap LC/MS 1 meter ~ $1M Sensors smaller, cheaper, less precise, screening/networks Indirect detection of chemical target < 1 cm, $10s to $100s Electrochemical effects from interactions Colorimetric/Opto-chemical Bio-molecular (assays) Solid State Multidisciplinary Research Device Fabrication Materials and Materials Mechanistic Research Processing Chemistry GChemAS M/BioICR OmSensorSENSOR • kinetics, thermodynamics Performance Signal Proc. and Testing Optimization • surface reactions • etching/micromachining reactions Physics Materials Science • semiconductor/insulator properties • thin films • electron transfer • nanomaterials Engineering Math • design and fabrication of • data collection microdevices • signal processing • testing equipment Biology • biomolecule binding • medical screening Outline • Chemiresistor Array 100 mm elements application-adaptable gas sensing • Plasmonic Optical Sensor Platform 380 nm features gas-phase and condensed-phase sensing • Microscale Electrochemical Device biochemical characterization DNA on 500 mm working electrode Chemical Sensor Array Concepts: Adaptable Platform Solid State Chemiresistor Devices Materials gas-induced changes in electrical conductance • semiconducting oxides • conducting polymers • chemical and electronic modifiers • nanotextured and nanostructured films Operating Temperature Tn(t) materials-dependent and temperature-dependent surface interactions • adsorption f1(T) • desorption f (T) 2 Sensing Film CVD – TiO2/SnO2 • coadsorbate reactions f3(T) T(t) programming controls these phenomena in time approach produces analytically rich datastreams and allows a tunable technology for varied applications Chemiresistive Sensing: Mechanistic Effects Variable electron Chemical depletion Input Interparticle percolation • Oxygen vacancy defects - set base conductance levels for oxide films • Surface charge transfer to bonded adsorbates • Adsorbates react to control adsorbed oxygen (air background) T and microstructure are critical to transduction/performance (chemical and electronic interfacial properties) sensitivity, selectivity, stability, speed Approach: Trace Detection in Varied Backgrounds tunable microsensor arrays - MEMS platforms - robust chemiresistive nanomaterials - surface and sensor science - advanced signal processing increased analytical content per unit time with Temperature Programmed Sensing (TPS) 50 mm large T(t) databases from “virtual sensors” Signal Processing independent chemiresistive target detection/recognition/monitoring MEMS microhotplate array elements Microhotplate Platforms for Chemiresistive Sensing SnO2 Oxide Film single microhotplate Suspended Film Contacts element Structure Insulating SiO (mass ~ 250 ng; (micromachining 2 heating/cooling tc < 5 ms) of Si) Doped Polysilicon Heater Insulating SiO2 50 mm layers Si wafer schematic Functionality Features - T measurement and control - 20 °C to 500 °C; (~ 20 °C per mW) - electrical characterization - capable of heating rates of 105 - 106 °C/s - CMOS design rules replication to packaged 16-element device array multi-channel electronics used for operation & data collection MEMS Platform Fabrication Processing Steps Top-Surface Si Micromachining • Design of multilevel mask set* • Fab run at Si foundry • Dicing of wafer and/or die • Si etch “micromachining” • Post-processing (e.g. - contacts) • Mounting/wirebonding * CMOS design rules 15 mm x 15 mm die with multiple micohotplate-related designs 75 die on 6” wafer (~ 1500 array devices) Film Deposition and Processing Methods Local Heating • Thermally-activated CVD • Sol-gel, suspensionSputter/Evaporation Mask drying for 48 Element Array 100 m 600 um Top• ViewAnnealing 500 um • Thermal lithography 600 um 25 um 48 array 3280 um • Thermallypartial- assistedcuts (2458 ximprinting 2080) Local Potential Control 9375 um 600 um 25 um partial cut 3658 um Micro-Dispensing • Addressable electrochemical23708 um Side View (pipetting) Side orView Alongelectrophoretic Length deposition 2458 um MaskingExpanded View of Openings 2080 um all processing done after etching and packaging (to avoid etchants litho-defined shadow mask and to use electrical contacts) S. Semancik and R. E. Cavicchi, Accounts of Chemical Research 31, 279-287 Examples: Integrated Nanostructured Materials High Area and Nanoparticle Materials Nanowires, Nanorods and Nanotubes SnO2 thin film WO3 wires ZnO rods CNTs 4 mm SnOx nanowires 600 nm Sb:SnO2 nanopaticle microshells “Fast” Nanostructured Polymers TiO nanotube spongy PANI/nafion 2 Journal of Nanoparticle Research 8, 809-822 Temperature in Gas-Phase Chemical Sensing desorption contact adsorption reaction sensing film embedded heater s = f (T, ) Sticking coefficient, adsorption and desorption rates - enable interesting operating modes when platforms have time constants in ms range R des (Chemiresistive Sensing) Klaus Christmann Higher Dimensionality: Temperature Programmed Sensing Phase2-Base, I (2 -Exponentialbase exponential) TPS Cycle TPS Phase4-Base, II (4 Quadratic-base quadratic) TPS Cycle TPS 500 500 ) ) C C o o ( ( 400 400 300 300 200 200 100 100 Sensor Temperature Temperature Sensor Sensor Temperature Temperature Sensor 0 0 0 1 2 3 4 5 6 0.0 3.5 7.0 10.5 14.0 17.5 21.0 24.5 Time (s) diffusion & charge Time (s) exchange also • gas-film interactions alter film’s electronic transport • purposeful temperature excursions as a function of time drive surface phenomena that produce an analytically-rich temporal signal • TPS cycles are run repeatedly to collect environmental information Single Microdevice Sensing With fast temperature modulation, what discrimination can be accomplished? TPS-based operation of a single sensor (SnO2 film + ~20A annealed Pd) Challenge – discriminating 2 similar chemicals 50 µm ethanol methanol alcohol vapors in air How should the temperature of the microsensor be varied to best discriminate between the two alcohols? Let the sensor LEARN the answer …… Learning about the Sensor’s Response vs T using semi-random response information to aid discrimination Measured response (for ethanol) Temperature can be flexibly programmed to vary between ~ 20 °C and 450 °C Random jumps were found to be too erratic - but 10 points along randomly generated T slopes worked well, with T reset period ~ 300 ms T. A. Kunt, T. J. McAvoy, R. E. Cavicchi and S. Semancik, Optimization of temperature programmed sensing for gas identification using micro-hotplate sensors, (Sensors and Actuators B 53, 24-43) Predicted Response/Measured Response Comparisons T. A. Kunt, T. J. McAvoy, R. E. Cavicchi and S. Semancik, Optimization of temperature programmed sensing for gas identification using micro-hotplate sensors, (Sensors and Actuators B 53, 24-43) Predicted optimal discrimination T program (by maximizing learned response separation) ethanol prediction ethanol data Optimized operation predicts “polarity reversals” (out-of-phase) responses for ethanol and methanol which greatly aids discrimination methanol prediction methanol data (Minimum discrimination time for these alcohols: ~ 2.2 sec) [with rich data and PCA/LDA can do mixtures] Systematic Data Acquisition for development of application-optimized