MASTERING VOC DETECTION FOR BETTER INDOOR AIR QUALITY

Transcription

1 European Network on New Sensing Technologies for Air Pollution Control and Environmental Sustainability - EuNetAir COST Action TD1105 WGs and MC Meeting at ISTANBUL, 3-5 December 2014 Action Start date: 01/07/ Action End date: 30/06/2016 Year 3: 1 July June 2015 (Ongoing Action) MASTERING VOC DETECTION FOR BETTER INDOOR AIR QUALITY Donatella Puglisi / donpu@ifm.liu.se Participant Linköping University / Sweden COST is supported by the EU Framework Programme ESF provides the COST Office through a European Commission contract

2 Scientific context and objectives in the Action Background / Problem statement: +85 % time spent indoor / costly HVAC systems M. Gemelli Bad air quality causes serious problems on environment, health, society Good air quality is a key-issue! Stringent legislation for NOx and VOCs Adequate control of emissions for more efficient reduction of hazardous air pollutants Brief reminder of MoU objectives: WG1: sensor materials and nanotechnology Research on gas-sensitive materials for detection of specific air pollutants Integration in gas sensor devices for indoor AQC Functionalization and surface modification to enhance gas adsorption and sensitivity; stability, reproducibility, and selectivity Material characterization (e.g. AFM, SEM) WG2: Sensors, devices and sensor systems for AQC Design, fabrication, testing, characterization of cost-effective high-performance gas sensors Innovative sensor technologies: SiC-FET and graphene-based sensors 2

3 Current research activities (SiC-FET) 330 C ppb 1 ppb 10 ppb 0.2 ppb Sensing mechanisms / device operation 100 ppb 10 % 0.90 Response time Recovery time 90 % Dry air 1 ppm pts smooth Time (h) Sensor Signal (mv) C ppb 0.5 ppb ppb 800 Naphthalene (C10H8) 20 % r.h. Selectivity 10 ppb Time (h) 1.5 Sensitivity ppb ppb (air) 5 ppb 10 ppb ppb 40 ppb Addressed challenges VGS = 2.8 V nd discriminant function (1.12 %) Formaldehyde (CH2O) 1.00 counts Sensor Signal (norm. values) Sensor processing / characterization naphthalene 20 % and 40 % r.h. Pt-gate st discriminant function (98.72 %) 3

4 Morphology Current research activities (Graphene) Normalized Resistance Sensor processing / characterization Sensing mechanisms / device operation Addressed challenges Resistance C 50 ppb CH 2 O Annealed at 250 C 20% r.h Time (min) 1,25 1,20 1,15 1,10 1,05 Air NO ppb 50 ppb sensor 1 sensor 3 sensor 2 1, Time (hours) Sensitivity Reproducibility Selectivity 4

5 Ongoing research topics +15 years experience on high-performance, low-cost FE gas sensors for room and high temperature applications, such as car/truck engines and power plants emission monitoring combustion control and exhaust systems indoor air quality applications Why SiC-FET sensors? V DS V GS D S n-type active layer p-type buffer layer n-type 4H-SiC substrate Chemical inertness Wide band gap (3.26 ev 4H-SiC) HARSH ENVIRONMENTS HIGH-TEMPERATURE OPERATION - High, stable, reproducible performance - Flexibility when using temperature cycling mode - Possibility to use high temperature for regeneration of the sensor surface 5

6 No! But SiC is so expensive Yole Développement: transition to 4-inch SiC wafers - a milestone towards reduced cost of SiC technology The ongoing transition to 6-inch wafers will usher in further cost reduction and SiC market growth 4-inch SiC wafer ~ 1800 chips (cost < 1 euro/each) The ongoing wafer cost reduction and market expansion in SiC will spill over also to EG/SiC Further steps towards cost-efficient preparation of EG/SiC through up-scaling of sample size in combination with a novel epitaxy technique allowing growth on inexpensive SiC substrates 6

7 FE sensor platform Absence of gas Presence of gas Cross section of a SiC-FET FET current controlled by V GS Gas molecules decompose and react on the catalytic metal Simple electronics Gate composed by a porous catalytic metal (Ir, Pt) as sensing layer Sensitivity by Number of three phase boundaries gas-metal-oxide Adsorption sites on the insulator Selectivity by Choice of temperature Different catalytic materials Structure of the metal M. Andersson, R. Pearce, A. Lloyd Spetz, Sens. & Act. B 179 (2013) Gas adsorption/reaction at the gate contact I-V shift 7

8 Detection Limit (ppb) 2nd discriminant function (15.77 %) Sensor operation High sensitivity: excellent detection limits High selectivity: discrimination of VOCs Ir-gate SiC-FET 330 C Formaldehyde Benzene Naphthalene % + 40 % r.h. benzene 2.5, 3.5, 4.5 ppb naphthalene 5, 10, 20 ppb < below threshold synth. air formaldehyde 50 ppb napthalene 2.5 ppb benzene 1.5 ppb formaldehyde 75, 100, 200 ppb cv-rate: 89.7 % st discriminant function (80.68 %) Relative Humidity (%) Multi-dimensional data evaluated by pattern recognition techniques Linear discriminant analysis (LDA) + cross-validation to avoid over-fitting data For on demand ventilation, «below threshold» means ventilation not needed Robust discrimination against changing humidity level and varying concentration of VOCs In cooperation with Saarland University 8

9 Suggested R&I Needs for future research Innovation SiC-FET Detection limits under threshold of legal requirements Discrimination and quantification of specific VOCs Stability during long-term operation Morphology Surface potential Gate Insulator Gate Insulator 10 µm Height (nm) 60 nm ΔV pot (mv) 200 mv 3 μm 3 µm Height (nm) 30 nm ΔV pot (mv) 30 mv Ir-gate before and after two weeks operation Iridium - Sensing layer not degraded is extremely important for our target application (indoor AQC) Research directions as R&I NEEDS: Development of new materials as sensing layers using PLD (work in progress in cooperation with Univ. Oulu) 9

10 Ongoing research topics Increased sensitivity and reproducibility Functionalization with metal and metal oxide nanostructures for selectivity tuning Controlling layer uniformity and doping Effect of surface restructuring during graphene growth on SiC Effect of humidity on sensor performance Why gas sensors in graphene? Unique band structure of graphene leads to a low density of states near the Dirac point (E D ) small changes in the number of charge carriers result in large changes in the electronic state Every atom at the surface ultimate surface to volume ratio Low noise, chemically stable (in non-oxidizing environment) enables very low detection limits p p* e <1eV Graphene is highly sensitive to chemical gating due to its linear energy dispersion and vanishing density of states near the Dirac point and therefore has potential as a low noise, ultra-sensitive transducer. 10

11 manufactures and supplies Very high quality, wafer scale, epitaxially grown Graphene on SiC Produced by sublimation of Si from SiC in Ar at 2000 ºC Scalable, wafer-size graphene films compatible with standard semiconductor processing High thickness uniformity (> 90 % 1LG, rest 2LG) Thickness controlled by temperature Spin off from Linköping University, Sweden

12 Graphene sensors issues: sensitivity, reproducibility Normalized Resistance ΔS depends on thickness due to differing band structures for 1LG, 2LG,... MLG Ambient 1 ppm NO 2 Uniform 1LG leads to very reproducible sensor characteristics 1,25 1,20 1,15 NO C sensor 1 sensor 3 sensor 2 1,10 1,05 Air 100 ppb 50 ppb NO 2 withdraws electrons Same change in charge carriers causes larger shift of the Fermi energy for 1LG R. Pearce, J. Eriksson, T. Iakimov, L. Hultman, A. Lloyd Spetz, and R. Yakimova, ACS Nano 7 (5), pp (2013) 1, Time (hours) NO 2 sensing interesting for: Emission control (few ppm) Air quality control (few ppb) Epitaxial graphene on SiC enables highly reproducible sensor fabrication Different sensors fabricated on 100 % 1LG show identical response 1LG is more sensitive to NOx than 2LG or MLG Uniform 1LG required for maximum sensitivity and reproducibility 12

13 Graphene sensors issues: selectivity, response/recovery time Functionalization with metal and metal oxides nanostructures for selectivity tuning Aim: To develop a reproducible method for functionalization with metal nano structures Thin layers of Au and Pt DC sputtered onto EG/SiC at elevated pressure Ideally we want islands or nanoparticles to maximize metal-graphene-gas boundaries Resistance change R/R 0 As grown graphene 1, ,6 100 C 120 1, ,4 80 1,3 60 1,2 40 1,1 20 1, Time (hours) Effect of Au decoration on sensor response NO 2 concentration (ppb) in N 2 Resistance change R/R 0 2,0 1,8 1,6 1,4 1,2 Au on graphene 100 C 1, Time (hours) RT Detection limit < 1 ppb NO NO 2 concentration (ppb) in N 2 Resistance change R/R 0 1,6 1,5 1,4 1,3 1,2 1,1 1,0 0,9 0,8 0,7 0,6 0,5 500 ppb NO 2 40 ppm NH ppb NO 2 50 ppm NH 3 Au, Pt Epitaxial graphene 100 ppb NO 2 SI 4H-SiC on-axis 250 ppm H 2 50 ppb NO Time (hours) 13 RT 100 C 500 ppm CO 30 ppb NO 2 Selectivity: blind to H 2 and CO J. Eriksson, D. Puglisi, Y. H. Kang, R. Yakimova, A. Lloyd Spetz, Physica B 439 (2014)

14 Suggested R&I Needs for future research Innovation - Graphene Reproducible growth Wafer-scale films compatible with standard semiconductor processing High thickness uniformity (> 90 % 1LG, rest 2LG) Decoration changes the surface chemistry but does not alter the graphene band structure Research directions as R&I NEEDS: Designed nanoparticles by pulsed plasma: it is expected that decoration with different metals or metal-oxide nanostructures will allow careful targeting of selectivity to specific molecules 14

15 Designed Nanoparticles by Pulsed Plasma Plasma-based nanoparticle (NP) synthesis process Highly versatile (metals, metal-oxides, core-shells) and reproducible thin film deposition technique Preliminary results show that TiO 2 NPs allow enhanced sensitivity towards formaldehyde and benzene The effect depends on the size of the deposited NPs (< 5 nm, sensitive to benzene; > 50 nm, sensitive to formaldehyde) TiO 2 NPs (Ø < 5 nm and Ø 50 nm) Resistance C 50 ppb CH 2 O Ø < 5 nm 20 nm 100 nm Annealed at 250 C 20% r.h Time (min) 15

16 Research Facilities available for current research Clean room, ISO 6 (magnetron sputtering, lithography, CVD, etc.) Sensor processing and characterization (gas mixing systems, readout electronics, bonding machine, spot welding, scribers, thermal evaporation, shadow masks, optical microscopes, AFM, SEM, etc.) Hardware and software for data acquisition and data analysis Gas bottles: CH 2 O, C 6 H 6, CO, NO, NO 2, NH 3, N 2, O 2, synthetic air Other facilities available at: Saarland University, SenSiC, GraphenSiC 16

17 Acknowledgements Special thanks to (in alphabetic order): Dr. Mike Andersson, associate professor Linköping University and SenSiC Manuel Bastuck, PhD student Saarland University Dr. Robert Bjorklund, senior researcher Linköping University Christian Bur, joint PhD student Saarland University and Linköping University Dr. Jens Eriksson, assistant professor Linköping University Joni Huotari, PhD student University Oulu Prof. Jyrki Lappalainen, University Oulu Prof. Anita Lloyd Spetz, Action Vice-Chair, Director of FunMat, Linköping University Peter Möller, tech. engineer and PhD student Linköping University Dr. Michele Penza, Action Chair, ENEA Prof. Andreas Schuetze, SENSIndoor coordinator, Saarland University Prof. Rositsa Yakimova, Linköping University and GraphenSiC 17

18 Thank you for your attention! (Looking forward to see you in Linköping!) 18