Supporting Information Artificial Sensing Intelligence with Silicon Nanowires for Ultra-Selective Detection in the Gas Phase
Bin Wang,† John C. Cancilla,‡ Jose S. Torrecilla,‡ Hossam Haick†,* †
Department of Chemical Engineering and Russell Berrie Nanotechnology Institute, Technion–Israel Institute of Technology, Haifa 3200003, Israel
‡ *
Department of Chemical Engineering, Complutense University of Madrid, Madrid 28040, Spain Corresponding authors (H.H.):
[email protected]
SiNW FET preparation: The applied p-type SiNWs are synthesized on Si wafer substrate by chemical vapor deposition method. The average diameter of as-grown SiNWs is 40±8 nm and average length is 8.5±1.5 µm. The as-grown SiNWs are first treated in buffered hydrofluoric acid for 15 sec and in KI/I2/H2O (mass ratio 4:1:40) solution for 2 min. Then the SiNWs are dispersed in ethanol by ultra-sonation. The SiNWs suspensions are spray coated on a Si wafer with 300 nm SiO2. The source/drain (Ti/Au, 30/110 nm) electrodes with channel width of 2 µm are prepared by photolithograph and lift-off. A detailed description of the fabrication procedure is found elsewhere.1
Molecular modification of SiNW FETs: The surface of SiNW FET devices are activated using a 60 sec oxygen plasma treatment. Then surface activated SiNW FETs are immersed in a solution of 3-aminopropyl-triethoxylsilane (APTES) in dehydrated ethanol (10 mM, 20 ml) at room temperature for 60 min. Following rinsed with acetone, ethanol and isopropanol and dried by N2 flow. Not clear --- ... at room temperature for 60 min. after rinsing with acetone, ethanol and isopropanol and ... OR at room temperature for 60 min. Following this, the SiNW FETs are rinsed with acetone, ethanol and isopropanol and ...
APTES modified SiNW FETs are immersed in a solution
of acyl chloride (10 mM) in chloroform with 10 µL of triethylamine for 17 hrs. 7 kinds of acyl chloride, including 5-phenylvaleric chloride (C11H13ClO), 1,4-butanedicarbonyl chloride (C6H8Cl2O2), methyl adipoly chloride (C7H11ClO3), hexanoyl chloride (C6H11ClO), heptanoyl 1S
chloride (C7H13ClO), decanoyl chloride (C10H19ClO), and dodecanoyl chloride (C12H23ClO) are used in this study. SiNW FETs treated with 1,4-butanedicarbonyl chloride are put into 90 °C hot water for 2 hrs to hydrolyze the end acyl chloride groups. These molecularly modified SiNW FETs are then rinsed with acetone, ethanol and isopropanol and dried by N2 flow. Finally, molecularly modified SiNW FETs are integrated into TO5 holders by wire binding.
Scheme S1. Schematics of molecular modification on SiNW surface
Characterization of molecular layers: X-ray photoelectron spectroscopy (XPS; Thermo VG Scientific, Sigma Probe, England; monochromatized X-ray Al Kα 1486.6 eV source) was used for surface characterization, as described in Refs. 2, 3. Briefly, dense SiNW layers were spraycoated onto 200nm Al/Si(100) substrates and molecularly functionalized as described in the text. Peak fitting software (XPSPEAK version 4.1) was used to analyze the XPS spectra after subtraction of a Shirley background; here we focused on N 1s spectra (Figure S1). The N 1s of APTES can be fitted into two peaks: (I) neutral nitrogen (399.6 eV, 46.0% peak area ratio), and (II) positively charged nitrogen (-NH3+, 401.8 eV, 54.0% peak area ratio). After reaction with acyl chloride (molecular layer S1-S7), the area percentage of peak II decreases and the peak I shifts ~0.4 eV to higher binding energy, implying the formation of amide bonds. Additionally, peak II can be used to monitor second acyl chloride layer coverage. The disappearing of peak II in S3-S5 indicates that near all of the amine groups of APTES transformed to amide groups. On the other hand, the relative large area ratio of peak II in S1, S2, S6 and S7 implies relatively low second acyl chloride layer coverage. 2S
Figure S1. XPS N 1s spectra of APTES layer and molecular layers that used for SiNW sensors. 3S
Since direct detection of the molecular layer’s thickness on SiNW is still challenging, the thickness of molecular layer is measured on 2D silicon wafer surface. Planer Si(111) wafers with 1.7 ± 0.3 nm native oxide are modified with various molecular layers using the same process as for the SiNWs. The thicknesses of applied molecular layers, as well as APTES layer, are measured by spectroscopic ellipsometer (SE, M-2000 V, J. A. Woollam Co., Inc.). As shown in Figure S2, the measured thicknesses are similar to the theoretically calculated values (based on Chem 3D Software), suggesting that all the modified molecular layers are in monolayer form.
Figure S2.Measured and calculated thickness of applied molecular layers and APTES layer. Chem 3D software was used to calculate the theoretical molecular layer thickness.
Extraction of the sensing parameters: Voltage threshold (Vth) is calculated by extrapolating the linear fit of Ids vs.Vg plot to Ids = 0. Subthreshold swing (SS) is defined as the liner fitting slope of linear regime of log(Ids) vs. Vg curve. Hole mobility (µh) is calculated using the following equation:4
µh =
ln[(2tox + RNW ) / RNW ] LNW ∂I ds (1) 2πε ox n Vds ∂Vg
where tox is the thickness of the gate oxide, εoxis the dielectric permittivity of the oxide, n is the bridged SiNW number, RNW is the radius of the SiNW, LNW is the length of the FET channel, and
∂I ds is the the liner fitting slope of linear regime of Ids vs. Vg curve. ∂Vg 4S
Table S1. Target ANN output vectors of applied VOCs. Decane
Hexane
Mesitylene
Octane
Dibutylether Chlorobenzene Cyclohexanone Decanol
Ethanol
Hexanol
Octanol
1,00E+00 0,00E+00
0,00E+00
0,00E+00
0,00E+00
0,00E+00
0,00E+00
0,00E+00 0,00E+00 0,00E+00 0,00E+00
0,00E+00 1,00E+00
0,00E+00
0,00E+00
0,00E+00
0,00E+00
0,00E+00
0,00E+00 0,00E+00 0,00E+00 0,00E+00
0,00E+00 0,00E+00
1,00E+00
0,00E+00
0,00E+00
0,00E+00
0,00E+00
0,00E+00 0,00E+00 0,00E+00 0,00E+00
0,00E+00 0,00E+00
0,00E+00
1,00E+00
0,00E+00
0,00E+00
0,00E+00
0,00E+00 0,00E+00 0,00E+00 0,00E+00
0,00E+00 0,00E+00
0,00E+00
0,00E+00
1,00E+00
0,00E+00
0,00E+00
0,00E+00 0,00E+00 0,00E+00 0,00E+00
0,00E+00 0,00E+00
0,00E+00
0,00E+00
0,00E+00
1,00E+00
0,00E+00
0,00E+00 0,00E+00 0,00E+00 0,00E+00
0,00E+00 0,00E+00
0,00E+00
0,00E+00
0,00E+00
0,00E+00
1,00E+00
0,00E+00 0,00E+00 0,00E+00 0,00E+00
0,00E+00 0,00E+00
0,00E+00
0,00E+00
0,00E+00
0,00E+00
0,00E+00
1,00E+00 0,00E+00 0,00E+00 0,00E+00
0,00E+00 0,00E+00
0,00E+00
0,00E+00
0,00E+00
0,00E+00
0,00E+00
0,00E+00 1,00E+00 0,00E+00 0,00E+00
0,00E+00 0,00E+00
0,00E+00
0,00E+00
0,00E+00
0,00E+00
0,00E+00
0,00E+00 0,00E+00 1,00E+00 0,00E+00
Table S2.Main parameters of ANN models for VOC classification (Classifier) and concentration estimation (Estimator). ANN Parameters
Optimized values Classifier
Estimator
Transfer function
Sigmoid
Training function
TrainBR
Hidden neuron number
3
3
Lc
0.01
0.001
Lcd
0.1
0.3
Lci
10
5
5S
Table S3. Output vectors of trained ANN based on sensing datasets obtained by sensor S1. Decane
Hexane
Mesitylene
Octane
Dibutylether Chlorobenzene Cyclohexanone Decanol Ethanol Hexanol Octanol
8,41E-01 2,02E-31
6,70E-28
7,30E-26
3,68E-38
1,20E-36
8,56E-32
1,01E-39 3,30E-33 1,44E-34 3,12E-34
1,96E-26 1,00E+00
2,29E-04
8,68E-03
1,15E-33
3,80E-29
4,70E-44
8,17E-48 4,08E-53 2,84E-52 2,39E-52
4,03E-02 1,83E-15
9,93E-01
3,07E-05
7,66E-04
8,48E-03
2,76E-15
8,37E-22 5,67E-31 2,80E-27 2,08E-27
2,88E-15 1,62E-14
4,62E-14
8,91E-13
1,45E-15
2,26E-15
1,57E-14
1,25E-13 8,86E-11 5,31E-13 5,94E-13
3,97E-05 4,33E-03
1,38E-22
1,22E-32
7,98E-01
2,66E-03
4,43E-03
8,43E-09 4,14E-10 3,53E-10 3,95E-10
9,44E-36 1,64E-18
8,56E-03
9,15E-17
7,58E-01
7,84E-01
3,13E-18
1,46E-29 6,90E-40 4,80E-38 3,77E-38
3,78E-05 3,28E-44
3,39E-14
3,50E-23
8,28E-03
2,56E-04
1,00E+00
1,35E-15 2,14E-04 2,67E-09 1,12E-08
2,99E-04 2,10E-11
2,73E-05
1,77E-03
8,30E-04
4,52E-04
6,06E-11
9,79E-01 8,89E-09 3,65E-05 1,22E-05
6,73E-30 1,78E-05
2,18E-29
2,08E-24
1,43E-29
9,43E-30
2,14E-06
1,93E-18 9,97E-01 2,66E-03 1,63E-02
7,55E-15 1,06E-07
1,39E-13
8,34E-08
8,56E-15
8,51E-15
8,52E-08
9,11E-03 2,85E-02 9,00E-01 1,09E-01
6S
Table S4. Output vectors of trained ANN based on sensing datasets obtained by sensor S2. Decane
Hexane
Mesitylene
Octane
Dibutylether Chlorobenzene Cyclohexanone
Decanol
Ethanol
Hexanol
Octanol
1.00E+00
5.24E-14
2.11E-142
2.81E-04
3.65E-126
2.50E-130
3.75E-06
2.96E-33
6.51E-07
2.54E-36
3.13E-32
2.38E-08
1.00E+00
4.05E-28
1.21E-10
1.10E-12
1.39E-06
2.28E-71
1.10E-05
4.78E-21
4.64E-07
5.17E-09
6.64E-07
5.23E-16
1.00E+00
1.24E-44
1.08E-06
2.78E-08
2.02E-15
3.87E-44
3.28E-32
2.88E-41
5.38E-40
1.72E-149 1.34E-114 6.07E-202 1.00E+00
5.73E-150
1.25E-143
1.54E-108
6.76E-32
1.23E-07
2.73E-37
3.59E-33
1.51E-06
9.95E-38
4.81E-16
1.33E-26
9.95E-01
1.58E-06
2.04E-19
3.06E-112 2.20E-62 1.33E-120 1.63E-112
3.06E-132 1.33E-87
1.68E-05
1.89E-57
6.87E-07
1.00E+00
7.16E-80
4.82E-102 1.24E-94 4.73E-109 4.60E-107
3.69E-19
8.94E-68
6.02E-07
3.53E-20
4.45E-17
3.63E-20
1.00E+00
8.24E-09
2.88E-06
4.25E-06
4.10E-06
3.12E-10
4.60E-22
1.01E-06
8.55E-25
3.24E-11
1.76E-10
2.84E-28
1.00E+00 1.62E-87
1.36E-09
1.70E-20
5.82E-19
2.24E-13
8.57E-19
9.45E-14
9.93E-19
6.65E-19
5.78E-14
1.09E-10 1.00E+00 9.67E-07
5.29E-05
3.60E-149 4.09E-108 1.98E-148
2.95E-98
8.82E-149
3.85E-148
3.20E-126
1.41E-15
2.70E-04
7S
1.23E-05 1.00E+00
Table S5. Output vectors of trained ANN based on sensing datasets obtained by sensor S3. Decane
Hexane
Mesitylene
Octane
Decanol
Ethanol
Hexanol
Octanol
9.99E-01
9.79E-21
2.98E-50
1.62E-25
1.58E-37
1.45E-42
5.91E-08
2.03E-03
4.17E-53
5.91E-52
1.39E-52
3.41E-17
9.99E-01
7.78E-09
4.72E-05
1.40E-24
2.46E-25
1.59E-160
1.17E-100 6.20E-125 4.08E-117 1.08E-118
2.12E-01
4.74E-93
1.00E+00
2.59E-57
6.85E-23
4.15E-11
1.68E-105
2.20E-113 9.64E-62
2.47E-63
1.30E-62
4.77E-44 2.65E-108
1.30E-36
1.00E+00
1.45E-41
1.27E-48
2.19E-111
2.17E-34
4.59E-95
9.75E-85
4.55E-87
3.33E-10
1.25E-82
1.34E-13
3.73E-09
1.00E+00
2.47E-05
3.20E-77
4.78E-91
2.64E-96
8.41E-98
1.39E-97
1.81E-47
5.89E-12
2.03E-07
3.80E-46
6.11E-02
1.00E+00
4.27E-07
1.71E-95
2.13E-29
4.82E-41
1.96E-38
2.54E-100 8.41E-152 8.48E-110 1.62E-111
2.34E-89
2.61E-90
1.00E+00
7.11E-67
2.53E-07
7.30E-17
1.11E-14
1.28E-120 5.28E-10
1.15E-122
8.74E-70
1.45E-105
1.03E-114
2.31E-08
1.00E+00
1.10E-13
6.45E-12
2.21E-12
5.49E-137 1.94E-25
2.62E-145 4.34E-148
1.50E-127
3.19E-128
4.82E-39
1.54E-116 1.00E+00
1.43E-06
1.33E-03
1.19E-57
1.26E-45
2.76E-68
2.46E-69
2.64E-113
2.22E-40
9.99E-01
1.67E-02
1.59E-84
2.20E-26
Dibutylether Chlorobenzene Cyclohexanone
8S
2.29E-06
Table S6. Output vectors of trained ANN based on sensing datasets obtained by sensor S4. Decane 9.94E-01 6.83E-03 2.21E-02 1.89E-20 8.85E-03 4.79E-34 3.13E-10 1.81E-69 2.86E-17 1.12E-23
Hexane Mesitylene Octane Dibutylether Chlorobenzene Cyclohexanone Decanol Ethanol Hexanol Octanol 3.12E-05 1.42E-30 5.23E-20 1.50E-28 4.16E-32 3.92E-05 1.01E-03 1.10E-07 1.13E-03 2.09E-04 9.99E-01 1.91E-06 3.88E-05 2.16E-12 1.66E-08 3.67E-50 1.03E-32 1.03E-66 1.91E-65 9.65E-66 3.39E-72 9.97E-01 4.42E-39 9.40E-07 6.13E-05 4.95E-68 1.85E-63 6.49E-84 5.65E-78 4.34E-79 6.59E-25 1.13E-24 1.00E+00 3.94E-24 5.33E-24 1.27E-12 7.11E-17 5.37E-51 9.72E-50 4.94E-50 1.09E-22 2.83E-04 4.87E-03 7.03E-01 2.08E-04 1.05E-07 8.08E-38 1.49E-55 1.60E-54 9.64E-55 1.14E-09 3.22E-03 1.79E-20 3.34E-04 9.99E-01 5.14E-05 2.37E-47 2.81E-16 3.18E-25 1.53E-23 1.16E-55 4.71E-13 1.77E-08 1.85E-09 2.80E-09 1.00E+00 3.05E-18 2.74E-04 9.88E-09 6.72E-08 1.93E-32 5.01E-68 2.85E-39 1.33E-67 2.70E-69 2.02E-44 9.99E-01 2.77E-07 4.72E-04 1.17E-04 3.67E-09 1.36E-20 4.05E-19 1.41E-18 8.58E-17 4.08E-13 3.69E-17 9.98E-01 1.11E-03 1.28E-02 2.38E-14 1.24E-17 2.76E-28 3.77E-19 1.15E-21 6.09E-21 4.46E-04 4.73E-03 9.99E-01 8.89E-03
9S
Table S7. Output vectors of trained ANN based on sensing datasets obtained by sensor S5. Decane 6.93E-01 5.31E-13 2.83E-11 2.21E-09 5.03E-04 4.50E-06 2.59E-14 3.27E-20 6.61E-13 3.68E-17
Hexane Mesitylene Octane Dibutylether Chlorobenzene Cyclohexanone Decanol Ethanol Hexanol Octanol 1.91E-09 1.07E-11 1.80E-09 3.43E-02 1.41E-15 3.29E-17 3.70E-02 1.61E-09 5.71E-09 1.16E-02 9.99E-01 2.20E-10 4.55E-12 2.52E-01 1.59E-01 3.22E-03 4.54E-36 2.04E-26 9.85E-26 8.92E-06 9.50E-12 7.65E-01 2.78E-02 7.87E-03 2.75E-12 6.84E-12 1.17E-02 5.87E-18 3.52E-18 2.02E-02 3.78E-02 3.21E-04 9.99E-01 2.22E-02 1.18E-08 3.67E-16 4.02E-19 1.07E-15 1.11E-15 3.33E-04 4.47E-34 1.66E-05 3.20E-34 9.87E-01 5.58E-05 1.09E-01 2.36E-45 4.77E-07 6.31E-07 3.27E-30 5.56E-24 1.09E-11 4.32E-24 2.51E-23 8.39E-01 2.30E-13 6.96E-37 9.48E-26 8.28E-26 6.96E-25 1.17E-08 3.15E-14 1.58E-08 3.79E-13 5.61E-14 9.97E-01 3.51E-02 3.74E-04 1.96E-04 2.71E-11 8.66E-22 6.86E-22 1.45E-21 8.76E-27 8.77E-19 2.94E-16 9.73E-01 2.79E-01 5.99E-02 9.76E-24 7.42E-22 1.34E-11 7.05E-22 4.33E-12 2.13E-13 9.94E-17 8.06E-12 7.91E-01 1.37E-20 9.49E-13 1.05E-04 9.02E-14 8.51E-05 8.98E-28 2.12E-20 2.93E-24 1.34E-06 3.91E-21 5.87E-01 1.85E-01
10S
Table S8. Output vectors of trained ANN based on sensing datasets obtained by sensor S6. Decane
Hexane Mesitylene
Octane
Dibutylether Chlorobenzene Cyclohexanone Decanol Ethanol Hexanol Octanol
9.67E-01 1.74E-27
2.30E-63
5.55E-54
8.66E-63
9.43E-43
1.14E-35
8.50E-58 1.16E-03 4.79E-58 1.04E-65
1.19E-17 3.90E-71
1.15E-17
4.69E-45
3.76E-34
5.27E-19
4.60E-26
3.34E-43 8.51E-89 5.61E-46 5.47E-29
1.19E-17 1.07E-15
9.45E-01
3.07E-15
4.89E-13
1.84E-18
1.05E-18
3.32E-15 1.04E-13 1.10E-14 1.38E-11
2.43E-60 2.97E-56
6.56E-60
5.16E-85
1.16E-81
1.20E-38
1.13E-31
8.04E-92 4.20E-11 1.46E-93 5.02E-75
1.05E-02 3.42E-37
1.31E-02
1.89E-37
7.53E-01
4.54E-11
3.07E-01
4.03E-39 1.18E-34 2.25E-42 1.37E-37
9.54E-11 1.57E-07
9.36E-11
1.03E-07
1.08E-05
5.45E-01
3.80E-11
9.32E-08 5.87E-05 3.34E-07 2.69E-04
2.28E-02 7.06E-05
2.14E-02
1.81E-01
1.31E-15
1.62E-02
1.51E-02
3.14E-17 8.77E-28 1.57E-01 3.83E-26
2.99E-19 2.22E-13
3.13E-19
2.80E-16
4.74E-09
1.86E-18
3.63E-18
9.30E-01 1.61E-03 5.75E-16 1.29E-03
4.29E-108 2.10E-06 2.80E-108 2.68E-12
3.61E-10
2.11E-107
3.49E-106
5.58E-09 6.26E-01 2.56E-04 9.39E-10
4.14E-12 1.84E-17
6.00E-38
4.38E-21
4.97E-24
1.07E-05 1.23E-22 8.72E-01 9.00E-05
2.92E-12
2.73E-07
11S
Table S9. Output vectors of trained ANN based on sensing datasets obtained by sensor S7. Decane
Hexane Mesitylene
Octane
Dibutylether Chlorobenzene Cyclohexanone Decanol Ethanol Hexanol Octanol
9.56E-01 5.85E-03
3.12E-13
2.17E-03
7.73E-17
8.04E-10
5.84E-42
1.86E-36 1.30E-40 1.57E-39 2.64E-02
4.18E-29 9.88E-01
4.09E-38
6.03E-23
7.55E-06
9.99E-40
4.13E-24
3.41E-54 5.76E-53 2.36E-40 8.79E-08
8.35E-02 2.41E-04
7.16E-01
9.92E-01
5.91E-05
9.08E-02
1.18E-10
6.90E-06 1.55E-11 9.80E-19 2.72E-04
1.51E-20 3.61E-02
2.17E-28
4.50E-21
8.92E-07
2.26E-27
3.66E-13
1.48E-33 2.38E-27 6.98E-13 6.86E-07
3.94E-19 9.72E-02
4.75E-18
7.66E-13
7.28E-01
7.13E-21
1.19E-02
6.97E-20 1.01E-19 6.96E-16 5.55E-07
5.54E-05 2.30E-39
2.81E-02
7.15E-10
8.93E-41
7.27E-01
7.65E-43
2.81E-05 8.45E-15 3.15E-34 3.77E-30
2.89E-26 1.10E-15
2.37E-20
1.12E-22
6.59E-09
1.19E-22
1.00E+00
2.01E-09 1.18E-05 6.84E-02 1.82E-18
1.23E-05 2.75E-07
5.01E-02
1.73E-03
9.26E-05
2.62E-03
2.33E-02
8.56E-01 4.09E-02 2.15E-06 4.35E-07
2.05E-05 5.91E-07
5.55E-06
1.73E-07
8.68E-07
4.54E-05
5.01E-04
2.28E-03 9.51E-01 7.99E-02 3.32E-06
2.22E-03 1.12E-04
1.99E-08
7.20E-08
4.04E-08
5.53E-06
5.86E-10
6.15E-10 1.64E-06 9.85E-01 8.32E-04
12S
REFERENCES: 1. 2. 3. 4.
Assad, O.; Leshansky, A. M.; Wang, B.; Stelzner, T.; Christiansen, S.; Haick, H. ACS Nano 2012, 6, 4702-4012. Wang, B.; Haick, H. ACS Appl. Mater. Interf. 2013, 5, 2289-2299. Wang, B.; Haick, H. ACS Appl. Mater. Interf. 2013, 5, 5748-5756. Wang, B.; Stelzner, T.; Dirawi, R.; Assad, O.; Shehada, N.; Christiansen, S.; Haick, H. ACS Appl. Mater. Interf. 2012, 4, 4251-4258.
13S
