Highly Selective Sensing of C - ACS Publications - American

Jan 8, 2018 - VSn⁗ vacancy associates are predominant after calcination in helium. The sensing ... and rational material design of volatile organic ...
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Letter

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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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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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