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Highly Selective Sensing of C2H6O, HCHO, and C3H6O Gases by Controlling SnO2 Nanoparticle Vacancies Lingyue Liu, Shaoming Shu, Guozhu Zhang, and Shantang Liu ACS Appl. Nano Mater., Just Accepted Manuscript • DOI: 10.1021/acsanm.7b00150 • Publication Date (Web): 08 Jan 2018 Downloaded from http://pubs.acs.org on January 13, 2018

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ACS Applied Nano Materials

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Highly Selective Sensing of C2H6O, HCHO,

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and C3H6O Gases by Controlling SnO2

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Nanoparticle Vacancies

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Lingyue Liu, Shaoming Shu, Guozhu Zhang, Shantang Liu*

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Key Laboratory for Green Chemical Process of Ministry of Education and School of

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Chemistry and Environmental Engineering, Wuhan Institute of Technology,

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Xiongchu Avenue, Wuhan, 430073, China

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ACS Paragon Plus Environment

ACS Applied Nano Materials 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

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KEYWORDS: SnO2, Vacancies, defect type, sensors, selectivity

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ABSTRACT: In this study, we prepared SnO2 containing various types of defects by

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changing the calcination atmosphere. Positron annihilation spectroscopy and

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electron spin resonance show that oxygen vacancies (V•• ) are the predominant

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′′′′ •• ′′′′ species after calcination in air, while triple V V V vacancy associates are

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predominant after calcination in helium. The sensing performance indicates that

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SnO2 nanoparticles calcined in air, helium, and oxygen exhibit excellent sensing

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performance for ethanol, formaldehyde, and acetone gases, respectively. Based on

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the in-situ infrared spectroscopy, the sensitivity of SnO2 improves by reducing the

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objective gas to CO2. The relationship between the sensing selectivity and the defect

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type was investigated. According to the results, the sensing mechanisms are

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discussed in terms of the selective effects of different defects based on combining

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band theory. The present study paves the way for development of high-selectivity

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sensors.

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The presence of defects can decrease the coordination number of neighbouring

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atoms, which means that they have more active sites to participant in reactions.1

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Defects change the electronic structure and configuration of the crystal.2-3 Generally,

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the performance of gas sensors depends on the properties of the semiconductor

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material.4-6 Thus, the presence of defects can strongly affect the electronic structure

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and configuration of nanomaterials, which play important roles in tuning the activities

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and active species of the reactive sites, and consequently the catalytic and sensing

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properties.7-10 For example, Morante et al. investigated the effect of oxygen vacancies

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on the adsorption properties, and they found that the gas response mechanism in oxide

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nanocrystals is more complex than only size dependent.11 Guo et al. found that the

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′′ intensities of the donors (V•• and V ) and surface oxygen species (O2– and O2–)

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involved in the mechanism of gas sensing on different surfaces can lead to different

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gas-sensing abilities for NO2 gas.12 In addition, defects are essential for catalytic

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chemical reactions because the electronic configuration of the catalyst already

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′′′ •• ′′′ changed. For example, Xie et al. reported that the existence of the V V V vacancy

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associate not only enhanced the adsorption capacity but also effectively separated

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electron–hole pairs in ultrathin BiOCl nanosheets, thereby it significantly increased

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the solar-driven photocatalytic activity.8 Therefore, in deep investigation of the

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relationship between the defect type and the reaction is important.

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The preparation of materials, purity of raw materials, atmosphere, growth rate and

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annealing process have a great impact on the type and quantity of defects.2, 8, 13 The

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regulation of defects usually has the methods of ion doping, atmosphere calcining and

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reductant reduction.14-16 Among them, the atmosphere calcination has better

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regulation ability to the internal defect of the material. For example, Xie et al.

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obtained atomically thin In2O3 porous sheets with rich oxygen vacancies and poor 3



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oxygen vacancies, respectively, by fast-heating in an atmosphere of air and oxygen.16

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Costentin et al. reported that a new oxygen vacancies are formed after static heat

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treatment under inert or vacuum conditions.17 However, the relationship between

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calcination conditions and the formation of defects still needs more exploration.

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As one of the most promising candidates for applications based on semiconductors,

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tin dioxide (SnO2) has been intensively investigated in the fields of sensors,

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optoelectronics, and so forth.18-20 In addition, the unique characteristics of

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nanoparticles, such as the large number of defects resulting from the large surface

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area, mean that SnO2 nanoparticles could have excellent catalytic or sensing

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performance.21 Because adsorption is the most critical step in the semiconductor

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sensor process, formation of defects is crucial for enhancing the sensing performance,

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although the adsorption activities of different defect types in the same crystal are

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different.22 However, the relationship between the defect type of SnO2 and the gas

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sensor performance is still unclear.

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In this study, SnO2 nanoparticles were prepared by the hydrothermal method and

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then annealed under different atmospheres (air, He, and O2) to tailoring their defects.

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The relationship between the defect type of SnO2 and the gas selectivity was

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investigated. This work will pave the way for development and rational material

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design of volatile organic compounds (VOC) sensors. Furthermore, it provides a

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definite solution for obtaining sufficient sensing selectivity for future high-

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performance sensors.

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Figure 1. TEM and HRTEM of S-A (a, d), S-H (b, e) and S-O (c, f). Inset is the

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corresponding Inverse Discrete Fourier transform (IFFT) images of HRTEM images

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of three sample.

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The samples prepared by calcination in different atmospheres were analysed by X-

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ray diffraction (XRD). Pure tetragonal SnO2 (JCPDS 70-4177) was obtained by

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calcining in oxygen (S-O), air (S-A), and helium (S-H). The prepared samples are

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pure phase SnO2. The (110) and (101) peaks shift in the amplifying XRD patterns 5



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after calcination in air/He and the colour of the as-synthesized materials changes (see

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Figure S1 and Figure S2, ESI†), indicating that some SnO2 was reduced to Sn or low

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valence Sn (Sn(4−x)+) during calcination in air/He. The corresponding transmission

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electron microscopy (TEM) images show that all of the products consist of well-

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dispersed nanoparticles (Figure 1a, c, and e), and the diameters of the nanoparticles

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are about 11, 15, 10 nm for S-O, S-A, and S-H, respectively. The nitrogen adsorption

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and desorption type IV isotherms have distinct hysteresis loops (Figure S3), indicating

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that the nanoparticles have a loose aggregation state, which is consistent with the

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TEM observations. There are clear lattice fringes corresponding to tetragonal SnO2 in

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the high-resolution TEM (HRTEM) images of S-A, S-H, and S-O (Figure 1b, d, and f,

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respectively). Most importantly, the fast Fourier transform (FFT) images of the

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selected areas show that the crystallographic symmetry of the lattice dots belongs to

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SnO2 (see the inserts of Figure 1b, d and f). The d-spacings of tetragonal SnO2 were

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determined by inverse discrete FFT of the HRTEM images of S-H, S-A and S-O. The

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HRTEM image of S-O exhibits perfect continuous ordered lattice fringes, and the

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lattice fringes of 3.31 and 3.06 Å correspond to the (110) and (111) planes,

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respectively. Slightly disordered discontinuous lattices are observed for the

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nanoparticles in the HRTEM images of S-H and S-A, indicating the existence of a

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number of defects (Figure 1).23-24

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Figure 2. (a) ESR spectra, (b) PALS spectra and (c) O 1s and (d) Sn 3d XPS spectra

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of the as-prepared samples.

Table 1. Positron Lifetime Parameters of SnO2 Samples

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Sample

τ1 (ps)

I1 (%)

τ2 (ps)

I2 (%)

τ3 (ps)

I3 (%)

S-H

155.8

23.5760

229.4

75.7605

1942.6

0.6635

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S-A

156.1

22.5091

206.8

76.5163

1531.8

0.9746

S-O

156.9

77.9635

206.9

20.6991

1221.7

1.3374

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Electron spin resonance (ESR), which is a powerful tool to investigate unpaired

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electrons in materials, was used to characterize the vacancies of the as-prepared SnO2

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nanoparticles. From the ESR spectrum of S-O, there are no vacancies after calcination

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in O2 (Figure 2a). However, the ESR spectra of the SnO2 nanoparticles prepared in

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helium and air have a high intensity ESR signal at 3357 G. This can be attributed to

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the Zeeman effect of single electrons trapped by oxygen vacancies, demonstrating that

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rich oxygen-containing SnO2 was obtained by helium/air calcination.25 ESR can only

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characterize the defects of single ionization, so it is not sufficient for in-depth analysis

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of defects. The types and amounts of defects in semiconductors can strongly affect

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their properties. Therefore, both identification and quantification of defects are

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necessary for a comprehensive understanding of the semiconductor properties.

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Positron annihilation spectroscopy (PALS) is a very sensitive probe for atomic-scale

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defects in materials.26-28 The positron lifetime spectra of the SnO2 nanoparticles

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obtained in different calcination atmospheres are shown in Figure 2b. The three

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positron lifetime components resolved from the positron lifetime spectra using the

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PATTIT program are given in Table 1. The τ3 component (1220–1950 ps) is because

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of annihilation of positrons at interfaces present in the material. According to the

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theoretically calculated positron lifetimes (Table S1), the τ1 component (156 ps) can

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be attributed to positron annihilation in the bulk or V•• of SnO2 (Figure 2b). In S-A,

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the τ2 component (about 200–230 ps) can be assigned to Sn4+–oxygen vacancy

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′′′′ •• associates V•• (Figure 2b). Similarly, V V and the Sn4+–oxygen vacancy associates

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′′′′ •• ′′′′ V V V are present in S-H. The relative intensities of the positron lifetimes (Table

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1) give more information about the distribution of the defects because the relative

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intensities can quantify the defect contents with respect to some standard of the

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material. According to the PALS and ESR results, S-O is defect-free, oxygen

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′′′′ •• ′′′′ vacancies (V••) associates are the predominant species in S-A, and V V V vacancy

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associates are mainly present in S-H. In addition, the calculated positron density

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distributions of the different defects in SnO2 are shown in Figure S4. Almost all of the

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′′′′ •• ′′′′ positrons are trapped inside the Sn atom in V V V defect clusters, while there are

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′′′′ •• still some positrons outside the Sn atom in V V defect clusters.

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To better understand the effect of the type of defect on the surface chemical

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composition of the product, we performed X-ray photoelectron spectroscopy (XPS)

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measurements. Figure 2d shows the high-resolution Sn 3d XPS spectra of the as-

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prepared samples. The peaks in the Sn 3d spectra of all of the samples can be

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deconvoluted into groups. The two main peaks centred at about 497.3 and 487.2 eV

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can be assigned to 3d 3/2 and 3d 5/2 of Sn4+ in the SnO2 crystal, indicating that most

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of the Sn atoms are six-coordinated to O atoms (see the crystal structure of SnO2,

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Figure S5). The peaks centred at about 498.3 and 488.2 eV are associated with the

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low chemical state of Sn (Sn(4−x)+) induced by the decrease of the number of

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coordinated O atoms, indicated that SnO2 calcined in a helium atmosphere has oxygen

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vacancies.29 However, no obvious low chemical state of the Sn(4−x)+ signal is observed,

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showing that escape of oxygen led to a change in the chemical state of Sn atoms for

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S-H. The O 1s spectra of the products show that oxygen vacancies are present in S-H

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and S-A but only lattice oxygen is present in S-O (Figure 2d). The XPS results are

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consistent with the PALS and ESR results. The presence of defects can strongly affect

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the electronic structure and configuration of nanomaterials. This affects the reactive

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site properties, and hence the catalysis and gas sensing properties. In addition, the 9



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standard deviations of the particle sizes of S-O, S-A, and S-H are similar, suggesting

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that the three materials have identical morphologies with similar particle sizes.

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To investigate the selective gas sensing performance of SnO2 with different defects,

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the gas-sensing performances of the SnO2 NPs with different defects were

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investigated in terms of their capability to detect various reducing gases. The variation

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in the gas sensitivities of the SnO2 NPs at various temperatures are shown in Figure

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S6. The typical resistance curves measured at the optimum operating temperatures for

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100 ppm C3H6O, C2H6O, CO, NH3, CH3OH, C7H8, and HCHO are shown in Figure

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S7. All of the sensors clearly track the changes in the gas concentration. The

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resistance decreases/increases during supply/stoppage of the tested reducing gases.

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The selective sensing properties of the SnO2 NPs are shown in Figure 3a–c. The

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′′′′ •• ′′′′ pristine SnO2 NPs, SnO2 NPs with oxygen vacancies, and SnO2 NPs with V V V

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defect clusters have high responses for 100 ppm C3H6O, C2H6O, and HCHO gases,

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the response were 14.8, 103, and 20.5, respectively. For clarity, the real-time

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resistance and response curves of the SnO2 NPs are shown in Figure S8. The

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repeatability and long-term stability of the S-A, S-H, and S-O sensors are shown in

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Figure S9. Based on the above results, the gas-sensing capabilities, such as the

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response, selectivity, and response and recovery times, of the SnO2 NPs are enhanced.

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To directly visualize the chemical reactions of SnO2 with different defects, we

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performed in situ diffuse reflectance Fourier transform infrared (FTIR) spectroscopy

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to monitor the time-dependent changes of the functional groups on the SnO2 surface

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at their optimum operating temperatures. Figure 3d shows the infrared spectra of

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dehy-drated SnO2 with oxygen vacancies following oxidation of ethanol as a function

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of heating time. The infrared spectra are referenced to the clean dehydrated SnO2 with

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oxygen vacancy surface before adsorption of ethanol. The absorption band at 1358 10


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cm−1 can be attributed to the ν(C–H) bending mode, while the band at 1223 cm−1 is

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assigned to the ν(O–H) stretching mode.30 The band at 2381 cm−1 is ascribed to

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molecularly adsorbed CO2.31 This indicates that ethanol can be oxidised to CO2 in the

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presence of SnO2 with oxygen vacancies. As shown in Figure 3e, the vibration peak of

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C=O (2385 cm−1) increases, which is ascribed to the characteristic vibrational peak of

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CO2, and the other characteristic peaks decrease, indicating that formaldehyde

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′′′′ •• ′′′′ gradually decomposed to CO2 in the presence of SnO2 with V V V defect clusters.

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From Figure 3f, acetone changed to CO2 in the presence of pristine SnO2 under the

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same conditions. These results indirectly explain why SnO2 with different defects

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show higher selectivity for different gases.

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Figure 3. (a)-(c) Selective sensing properties and (d)-(f) in situ FTIR spectra for

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simulated gas sensitive conditions of the target gases over S-A, S-H, and S-O.

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Generally, the sensing behaviour of n-type oxide semiconductors can be explained

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based on radial modulation in the electron-depletion layer and potential barrier

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modulation. Oxygen species adsorbed on the surface of SnO2 NPs are n-type

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semiconductors and they capture electrons in the conduction band of SnO2, resulting

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in an electron-depleted SnO2 surface. When a gas is supplied, the gas molecules

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probably react with the pre-adsorbed oxygen species and form a volatile chemical

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compound. The captured electrons are then released back into the conduction band of

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SnO2, thinning the electron-depletion layer and decreasing the resistance of SnO2. To

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elucidate the reason for the different selective sensing performances of the samples

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with different types of defects, we analysed the band structures of SnO2 with different

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defects by ultraviolet–visible (UV–vis) diffuse reflectance spectroscopy, band XPS,

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and Mott–Schottky plots. Figure 4a shows the UV–vis diffuse reflectance spectra of

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the SnO2 samples calcined in different atmospheres. The calculated band gap values

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for S-O, S-H, and S-A are 2.54, 2.63, and 2.68 eV, respectively. Based on the Mott–

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Schottky plots of the samples (Figure 4c), the calculated flat band potentials of S-O,

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S-H, and S-A are 0.38, 2.07 and 0.92 eV vs. Hg/Hg2Cl2 (i.e., 0.62, 2.31 and 1.16 eV

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vs. the normal hydrogen electrode (NHE)), respectively. As a n-type semiconductor,

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the flat band potential is equal to the Fermi level. Generally, the bottom of the

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conduction band of an n-type semiconductor is more negative (about 0–0.2 eV) than

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the Fermi level (i.e., the flat band potential), which is dependent on the electron

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effective mass and carrier concentration. Therefore, the conduction band potentials

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(ECB) of S-O, S-H, and S-A are 0.38, 2.07 and 0.92 eV vs. NHE, respectively.

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Accordingly, the valence band potentials (EVB) of S-O, S-H, and S-A are 2.92, 4.7,

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and 3.6 eV, respectively, based on the empirical formula (Eg = EVB − ECB, where Eg is

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the band gap energy).24, 32 The band XPS spectra were also used to determine the band 12


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structures and band potentials (2.97 eV for S-O, 4.73 for S-H, and 3.64 eV for S-A),

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which are consistent with the calculated results from the Mott–Schottky plots (Figure

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4c). Based on the above discussion, the different defect types in SnO2 lead to different

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band structures. This may have a significant influence on the mechanism for gas

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selectivity. During the reaction, the VOC molecules are first immobilized on the

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surface of SnO2 by chemisorption. The target gas can then be reduced to CO2 gas if

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the reduction potential matches the conduction band of SnO2, which depends on the

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type of defects. For example, Kaar et al. found that the ethanol potential changes at

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different temperatures.33 If the reduction potential of ethanol matched that of the

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material, a redox reaction would occurre and the ethanol would converte into CO2.

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Therefore, the gas sensitive response changed. Because the reduction potentials of the

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different gases are diverse and SnO2 calcined in different atmospheres possesses

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different conduction band potentials, SnO2 has different selectivities for different

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VOC gases.

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In addition, there may be other factors that affect the selectivity of the sensor. For

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′′′′ •• ′′′′ example, the presence of V V V may increase the overall ionic potential of of

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materials which let the materials tightly connect to the adsorbed oxygen molecules

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(such as O2-, O- and O2-). Therefore, stronger Bronsted acid is required to carry away

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more adsorbed oxygen at equilibrium. The acidity of formaldehyde is stronger than

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which of the ethanol and acetone (pKa values for formaldehyde, ethanol, and acetone

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are 13.27, 15.5, and 19.3, respectively.)34 When the sensing material is exposed to the

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target gas, the formaldehyde molecules could expend more adsorbed oxygen and thus

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result in higher response at a relatively low temperature. In the presence of V•• the

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corresponding defect sites / states become the most beneficial ones for adsorption of

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target gas. In addition, each oxygen vacancy offers two electrons, giving S-A a larger 13



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number of electrons, which is helpful for formation of oxygen adsorbents. Once the

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sensor is exposed to the reducing gas molecules, the latter will be oxidized by surface-

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adsorbed ionizing oxygen species, resulting in a higher resistance. However, Ruan et.

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has explained the mechanism by which the target gas molecules can be detected with

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high selectivity is due to the distinction of the orbital energy of gases.35 When the

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value of lowest unoccupied molecule orbit (LUMO) energy is lower, the energy

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needed for the gas sensing reaction will reduce. It has been reported that the value of

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LUMO energy of ethanol, formaldehyde and acetone are 0.12572 eV, 0.21965 eV and

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0.20525 eV, respectively.35-36 Ethanol has the most powerful ability to capture

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electrons due to its lowest LUMO energy value. Therefore, the possibility of electron

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transfer between the ethanol molecules and surface of S-A NPs will be larger,

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resulting in the sensor being more sensitive to ethanol than acetone and formaldehyde.

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In the case of the defect-free SnO2 NPs, the S-O NPs adsorbs oxygen molecules in the

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air with a weak ability to adsorb oxygen in a small amount and responds poorly to

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each gas in theory. However, in our experiments, it responded to acetone with good

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selectivity. It is well-known that the sensing response is related to the adsorption and

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reaction of gas molecules on the sensing materials. 1) The response of materials to

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various gases is considered to have a great relationship with the polarity of the gas.

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Among them, the polarity of the detected gas is ethanol

Highly Selective Sensing of C - ACS Publications - American

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