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Enhanced Gas Sensitivity and Sensing Mechanism of Network Structures Assembled from #-Fe2O3 Nanosheets with Exposed {104} Facets Yong Ma, Juan Yang, Yukun Yuan, Hua Zhao, Qian Shi, Fangjuan Zhang, Cuijin Pei, Bin Liu, and Heqing Yang Langmuir, Just Accepted Manuscript • DOI: 10.1021/acs.langmuir.7b00455 • Publication Date (Web): 24 Jul 2017 Downloaded from http://pubs.acs.org on July 26, 2017

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Enhanced Gas Sensitivity and Sensing Mechanism of Network Structures Assembled from α-Fe2O3 Nanosheets with Exposed {104} Facets

Yong Ma, † Juan Yang, † YukunYuan, Hua Zhao, Qian Shi, Fangjuan Zhang, Cuijin Pei, Bin Liu and Heqing Yang*

Shaanxi Key Laboratory for Advanced Energy Devices; Shaanxi Engineering Laboratory for Advanced Energy Technology; Key Laboratory of Macromolecular Science of Shaanxi Province, School of Materials Science and Engineering, Shaanxi Normal University, Xi’an, 710119, China.



These authors contributed equally to this work.

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ABSTRACT: Network structures assembled from -Fe2O3 nanosheets with exposed {104} facets were successfully prepared by heating Fe(NO3)3 solution containing polyvinyl pyrrolidone (PVP) in air. The -Fe2O3 nanosheets based network structures demonstrate significantly higher response to ethanol and triethylamine than -Fe2O3 commercial powders. The excellent sensing performances can be ascribed to the exposed (104) facet terminated with Fe atoms. A concept of the unsaturated Fe atoms serving as the sensing reaction active sites thus is proposed, and the sensing reaction mechanism is described at atomic and molecular level for the first time in detail. The concept of the surface metal atoms with dangling bonds serving as active sites can deepen understanding of the sensing and other catalytic reaction mechanisms and provides a new insight into the design and fabrication of highly efficient sensing materials, catalysts and photoelectronic devices.

KEYWORDS: -Fe2O3 nanosheets, {104} facets, network structures, unsaturated Fe atoms, gas sensing

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■ INTRODUCTION The physical and chemical properties of semiconductor nanocrystals are not only related to crystal size but also to crystal shape and exposed facets, and thus the design of semiconductor nanocrystals with controlled morphology and crystal-facets have attracted a great deal of attention.1 Hematite (-Fe2O3), an important member of the metal oxide family, is the most stable iron oxide with n-type semiconducting properties (Eg = 2.1 eV).2 A wide range of applications have been demonstrated for  -Fe2O3 nanostructured materials, such as field emitters,3,4 magnetic materials,5,6 photocatalysts,7-10 photoelectrochemical water splitting,11-14 lithium-ion batteries15-19 and dye-sensitized solar cells.20 Additionally, -Fe2O3 is considered as an ideal gas-sensing candidate owing to its low production cost, high stability and environmental compatibility.21-22 In this regard, nanorods,23 nanoropes,24 nanotubes,25 nanorings,26 nanospheres27 and flowerlike28 and hollow sea urchin-like architectures29 of -Fe2O3 have been employed to fabricate gas sensors for volatile-organic-compounds. It was found that the morphology of -Fe2O3 nanostructured materials significantly affects its gas-sensing properties. However, very little is known about the effect reason of morphology on gas-sensing performance. Recently, Geng et al found that the  -Fe2O3 nanoparallelepipeds with exposed facets of {012}, {01 4 } and { 2 10} show enhanced gas-sensing properties towards acetone and ethanol, compared with irregular  -Fe2O3 particles and commercial -Fe2O3 powders.30 Subsequently, it was reported that the rhombohedral  -Fe2O3 nanocrystals with six exposed {104} facets,31 the {113} faceted hexagonal 3

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bipyramids32 and the X-shaped  -Fe2O3 nanocrystals enclosed by {210} and {115} facets exhibited improved sensing performances.33 The superiority of the gas-sensing performances was attributed to the surface structure30 or the extraordinary ability of chemisorbing oxygen34, 35 of the exposed active facets. However, the detailed reason for enhanced sensing performance is not yet clear, and it is still a great challenge to fabricate -Fe2O3 nanocrystals with high percentage of clean reactive facets without capping agents. In addition, so far the network structures assembled from α-Fe2O3 nanosheets with exposed reactive facets have never been reported. In this paper, we reported on the fabrication of network structures assembled from  -Fe2O3 nanosheets with exposed {104} facets by a very simple fast combustion route. The as prepared  -Fe2O3 network structures demonstrate superior sensing performances for N(C2H5)3 and C2H5OH, compared with  -Fe2O3 commercial powders. The enhancement of sensing performances is attributed to the exposed (104) facet terminated with Fe atoms, we thus proposed a concept of the unsaturated Fe atoms with dangling bonds serving as sensing reaction active sites, and described the sensing mechanism.

■ EXPERIMENTAL SECTION Preparation of -Fe2O3 Network Structures The  -Fe2O3 nanosheets based network structures were synthesized by heating Fe(NO3)3 solution containing polyvinyl pyrrolidone (PVP) in air. The mixed solution was obtained by dissolving 1.010 g (2.5 mmol) of Fe(NO3)3·9H2O and 0.500 g PVP in 4

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5.0 mL of H2O. Typically, a Si wafer with a dimension of 1.0 × 1.0 cm was cleaned with deionized water and ethanol in an ultrasound bath for 10 min, respectively. The Fe(NO3)3 solution containing PVP was added dropwise on the Si substrate, and heated in a horizontal tube furnace at 650 ºC for 10 min. As a result a brick red product was observed on the Si substrate. Characterization of Materials The as-obtained samples were characterized by means of scanning electron microscopy (SEM), transmission electron microscopy (TEM), Atomic Force Microscope (AFM), powder X-ray diffraction (XRD) and X-ray photoelectron spectra (XPS). SEM images were obtained by a SU8000 field emission scanning electron microscope. TEM analysis was achieved by using a JEOL JEM-2100 transmission electron microscope. AFM analysis was done by means of a Bruker AXS Dimension ICON Atomic Force Microscope. The XRD patterns were recorded on a Rigaku

Smartlab diffractometer equipped with Cu Kα1 (λ=1.5406 Å) radiation. XPS spectra were obtained on a Kratos Axis ultra X-ray photoelectron spectrometer with an excitation source of Al Kα = 1486.7 eV. The Brunauer-Emmett-Teller (BET) specific surface area was measured on an America Micromeritics ASAP 2020 surface analytical instrument by nitrogen adsorption/desorption. Measurement of Gas Sensing Properties Gas sensitivity of the as-prepared  -Fe2O3 network structures was detected by a Weisheng WS-30A system. According to our previous work,36 the gas sensors were

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fabricated. The as prepared -Fe2O3 sensors were aged at 350 ºC for 7 d to improve the stability of the sensors. Response of the sensor to a test gas is defined as Ra/Rg, where Rg and Ra are the resistances of the Fe2O3 sensor in test gas and in clean air, respectively.

■ RESULTS AND DISCUSSION Morphology and Crystal Structure Figures 1 and 2 show SEM images and XRD pattern from the products prepared by heating Fe(NO3)3 solution containing PVP at 650 ºC for 10 min, respectively. The different magnification SEM images shown in Figure 1a-d indicate that the as-obtained products consist of network structures with the typical nanosheets of 1.0 to 2.3 μm in length, and 1 to 2.6 μm in width. The network structures are assembled from α-Fe2O3 nanosheets with a thickness of about 23-34 nm. There are some pores with the diameters of 2.2 to 13.4 nm on some nanosheets. The corresponding XRD pattern is shown in Figure 2. According to Joint Committee on Powder Diffraction Standards (JCPDS) card no. 33-0664, all the diffraction peaks are indexed as the -Fe2O3 with a hexagonal structure. Figure 3a shows TEM image of an isolated constituent  -Fe2O3 nanosheet. The nanosheet has about 2.2 μm in length, and 1.2 μm in width and 30 nm in thickness. The selected area electron diffraction (SAED) pattern and the high-resolution TEM (HRTEM) image from box in (a) are shown in Figure 3b and c, respectively. The SAED pattern is indexed as the [4 41] zone axis of single crystalline -Fe2O3 with a 6

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hexagonal structure. In HRTEM image in Figure 3c, the distance between the crystallographic planes was measured to be 0.25 nm, corresponding to the (110) lattice planes of  -Fe2O3 with the hexagonal structure. The TEM results reveal that the constituent -Fe2O3 nanosheet is single crystalline, is enclosed by {104} facets,37 and its crystal orientation schematic illustration is displayed in Figure 3d. Moreover, the AFM measurements shown in Figure 4 indicates that the thickness of the constituent  -Fe2O3 nanosheet is about 30 nm, which matched very well with the TEM and SEM data. The -Fe2O3 nanosheet is actually a multilayered structure, it is assembled from nanosheets with the thickness of 2.3 to 18 nm.

Gas Sensing Properties To obtain the optimum working temperature, the responses of the sensors based on the network structures assembled from -Fe2O3 nanosheets towards 100 ppm of C2H5OH and 100 ppm of N(C2H5)3 at different working temperatures were studied and the results are shown in Figure 5a-b. The electrical resistance value of the  -Fe2O3 nanosheets based network structures decreased as C2H5OH or N(C2H5)3 was injected into the test chamber. The variation in the electrical resistance is enhanced with increasing the working temperature. The maximum variation value was observed at 300 ºC, and it is decreased beyond the temperature. The optimal working temperature thus was set at 300 ºC for further sensing measurements. Figure 6a and b shows SEM image and XRD pattern of the  -Fe2O3 commercial powers. It is obvious that the -Fe2O3 commercial power consists of a large quantity 7

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of nanoparticles with irregular morphologies and the sizes of 100-500 nm. The gas sensing properties of the commercial  -Fe2O3 powders were investigated towards C2H5OH and N(C2H5)3, and compared with that of the  -Fe2O3 nanosheets network structures. Figure 7a and b displays response and recovery curves for the sensor made of the  -Fe2O3 nanosheets based network structures and the  -Fe2O3 commercial powders towards various concentrations of C2H5OH and N(C2H5)3 at 300 ºC, respectively. Upon the injection of C2H5OH or N(C2H5)3 resistance value of the sensors decreased suddenly, then increased rapidly and recovered to their respective initials value after the organic compound vapor was released. After many cycles, resistances of the sensors based on the  -Fe2O3 nanosheets network structures can recover their initial states, which reveals that the  -Fe2O3 sensors have good reversibility. Figure 7c-d shows response curves of the two kinds of sensors towards C2H5OH and N(C2H5)3, respectively. Obviously, for both C2H5OH and N(C2H5)3 vapors, the  -Fe2O3 nanosheets network structures have higher response than the  -Fe2O3 commercial powders. The results reaveal that the as-fabricated the  -Fe2O3 nanosheets network structures have excellent sensing performances. Figure 8a-b shows the N2 adsorption–desorption isotherm of the -Fe2O3 nanosheet network structures and commercial powders, respectively, and the insets are the relative Barrett–Joyner–Halenda (BJH) pore-size distribution plot. The isotherm profiles is indexed as type IV with a small hysteresis loop,38 and the hysteresis loops can be attributed to type H3 loops, revealing the presence of mesopores in two kinds

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of  -Fe2O3 samples.39,40 The pore size distribution for the  -Fe2O3 commercial powders and  -Fe2O3 nanosheets network structures peaked at ca. 35 and 40 nm, respectively, and their BET surface area is measured to be 12.6 and 16.7 m2g-1, respectively. To understand the difference in the sensing properties of the two types of sensors, the response of per unit surface area is examined in this work. Figure 8c-d shows the response of per unit surface area of the two types of  -Fe2O3 sensors towards 100 ppm of C2H5OH and 100 ppm of N(C2H5)3. Obviously, the normalized response value of the  -Fe2O3 nanosheets network structures is higher than that of the  -Fe2O3 commercial powder, indicating that the network structures assembled from  -Fe2O3 nanosheets with exposed {104} facets exhibit superior gas-sensing performance, compared with the -Fe2O3 commercial powders. For the metal oxide-based sensors, the variation of the electrical resistance is mainly related to the oxidation-reduction reaction of the chemisorbed oxygen with the test gas molecules taking place on the sensing material surface.41 Therefore, the sensing properties of the -Fe2O3 sensors is closely related to their adsorbing oxygen ability. XPS spectra of the  -Fe2O3 nanosheests network structures and commercial powders were measured, and the results are given in Figure 9. Figure 9a displays Fe 2p XPS spectra of the two kinds of -Fe2O3 samples. The binding energy of Fe 2p1/2 and 2p3/2 is identified at 724.2 and 710.6

eV, respectively,

34,42

and the satellite

peak is characteristic line of Fe3+ in Fe2O3.32,35 Figure 9b-c shows O 1s peaks from the two kinds of -Fe2O3 samples. It is very clear that each O 1s peak can be resolved into 9

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three Gaussian components centered at about 532 eV (OC), 531 (OV) and 530 (OL) respectively. The OC, OV and OL components are ascribed to chemisorbed oxygen species, O2- ions in oxygen-deficient regions and O2- ions in the  -Fe2O3 lattice, respectively.43 The relative percentages of the OC, OV and OL components estimated from the two kinds of  -Fe2O3 samples are listed in Table 1. It is found that the relative percentages of the OV and OC components follow the order of nanosheet network structures > commercial powders. It is reasonable to conclude that the enhancement of gas-sensing performances of the  -Fe2O3 nanosheet based network structures toward the both volatile organic compounds (VOCs) may arise from their extraordinary ability of chemisorbing oxygen and high percentages of oxygen vacancies. As for the crystal structure of -Fe2O3 with the hexagonal structure, in a typical crystal unit, each O atom is surrounded by four Fe atoms, whereas each Fe atom is bound to six O atoms.44,45 According to Ref,31 a schematic atomic structure of the a-Fe2O3 {104} facets is given in Figure 10a.31 It can be found that the exposed (104) facet is terminated with Fe atoms, the Fe atoms lie on the (104) surface in an unsaturated coordination form. We thus conclude that the unsaturated Fe atoms with dangling bonds on the (104) surface may serve as active sites for the sensing reaction. The a-Fe2O3 used is an n-type semiconductor, in which electrons are majority carriers.2 It is well known that oxygen vacancies in a-Fe2O3 generate non-contributing (free) electrons.46,47 The loss of oxygen necessarily produces the unsaturated Fe atoms with dangling bonds, we thus believe that the unsaturated Fe atoms can generate extra

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electrons and proposed a sensing mechanism at atomic and molecule level. In air, the unsaturated Fe atoms with dangling bonds on (104) surface of the constituent -Fe2O3 nanosheets can adsorb oxygen molecules due to the reducibility and deficiency of oxygen. The adsorbed oxygen molecules can capture free electrons in the constituent a-Fe2O3 nanosheets to form O2−. ( Figure 10b). The number of free electrons in a-Fe2O3 nanosheets decreases, and thus the a-Fe2O3 nanosheets based network structures sensors show a high resistance state. When the a-Fe2O3 sensor is exposed to triethylamine or ethanol vapor, the adsorbed oxygen molecules can be reduced by the ethanol or triethylamine, the captured electrons are released to form free electrons, and thus the electric resistance reduced drastically, as shown in Figure 10c. The -Fe2O3 nanosheets based network structures have higher density of the unsaturated Fe atom active sites, and demonstrate higher response towards ethanol or triethylamine, in comparison with -Fe2O3 commercial powders.

■ CONCLUSIONS In summary, network structures assembled from  -Fe2O3 nanosheets with exposed {104} facets have been successfully prepared by a fast combustion route. This approach to prepare -Fe2O3 network structures can be scaled up easily, and extended potentially to fabrication of other mental oxide network structures. The  -Fe2O3 nanosheets based network structures exhibit superior sensing performances in comparison with -Fe2O3 commercial powders. The enhancement in the gas sensing properties is mainly attributed to the higher density of the unsaturated Fe atoms on the

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exposed {104} facets. We thus proposed a concept of the unsaturated Fe atoms with dangling bonds serving as sensing reaction active sites, and described the sensing mechanism at atomic and molecule level. The concept of the surface unsaturated metal atoms serving as active sites should be promising and intriguing for understanding the mechanism of sensing and other catalytic reactions as well as designing and fabricating advanced sensing materials, catalysts and photoelectronic devices.

■ AUTHOR INFORMATION Corresponding Author *Fax: 0086-29-81530702. E-mail: [email protected]. Notes The authors declare no competing financial interest.

■ ACKNOWLEDGEMENTS This work was supported by the National Natural Science Foundation of China (Grant Nos. 21073116 and 21501116), and the Fundamental Research Funds for the Central Universities (GK 201601003 and GK 201703027).

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(22) Chen, H. M.; Zhao, Y. Q.; Yang, M. Q.; He, J. H.; Chu, P. K.; Zhang, J.; Wu, S. H. Glycine-Assisted Hydrothermal Synthesis of Peculiar Porous α-Fe2O3 Nanospheres with Excellent Gas-Sensing Properties. Analytica Chimica Acta 2010, 659, 266-273. (23) Tan, J. F.; Huang, X. T. Ultra-Thin Nanosheets-Assembled Hollowed-Out Hierarchical α-Fe2O3 Nanorods: Synthesis via an Interface Reaction Route and Its Superior Gas Sensing Properties. Sens. Actuators, B 2016, 237, 159-166. (24) Yan, S.; Wu, Q. S. A Novel Structure for Enhancing the Sensitivity of Gas Sensors - α-Fe2O3 Nanoropes Containing a Large Amount of Grain Boundaries and Their Excellent Ethanol Sensing Performance. J. Mater. Chem. A 2015, 3, 5982-5990. (25) Chen, J.; Xu, L. N.; Li, W. Y.; Gou, X. L. α-Fe2O3 Nanotubes in Gas Sensor and Lithium-Ion Battery Application. Adv. Mater. 2005, 17, 582-586. (26) Hu, X. L.; Yu, J. C.; Gong, J. M.; Li, Q.; Li, G. S. α-Fe2O3 Nanorings Prepared by a Microwave-Assisted Hydrothermal Process and Their Sensing Properties, Adv. Mater. 2007, 19, 2324-2329. (27) Wang, L. L.; Lou, Z.; Deng, J. N.; Zhang, R.; Zhang, T. Ethanol Gas Detection Using a Yolk-Shell (Core-Shell) α-Fe2O3 Nanospheres as Sensing Material. ACS Appl. Mater. Interfaces 2015, 7, 13098−13104. (28) Wang, L. L.; Fei, T.; Lou, Z.; Zhang, T. Three-Dimensional Hierarchical Flowerlike α-Fe2O3 Nanostructures Synthesis and Ethanol-Sensing Properties. ACS Appl. Mater. Interfaces 2011, 3, 4689-4694. (29)Zhang, F. H.; Yang, H. Q.; Xie, X. L.; Li, L.; Zhang, L. H.; Yu, J.; Zhao, H.; Liu, B. Controlled Synthesis and Gas-Sensing Properties of Hollow Sea Urchin-Like

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α-Fe2O3 Nanostructures and α-Fe2O3 Nanocubes, Sens. Actuators, B 2009, 141, 381-389. (30) Li, X. L.; Wei, W. J.; Wang, S. Z.; Kuai, L.; Geng, B. Y. Single-Crystalline α-Fe2O3 Oblique Nanoparallelepipeds: High-Yield Synthesis Growth Mechanism and Structure Enhanced Gas-Sensing Properties. Nanoscale 2011, 3, 718-724. (31) Liu, X. H.; Zhang, J.; Wu, S. H.; Yang, D. J.; Liu, P.; Zhang, H. M.; Wang, S. R.; Yao, X. D.; Zhu, G. S.; Zhao, H. J. Single Crystal α-Fe2O3 with Exposed {104} Facets for High Performance Gas Sensor Applications. RSC Adv. 2012, 2, 6178-6184. (32) Ouyang,

J.

J.;

Pei,

J.;

Kuang,

Q.;

Xie,

Z.

X.;

Zheng,

L.

S.

Supersaturation-Controlled Shape Evolution of α-Fe2O3 Nanocrystals and Their Facet-Dependent Catalytic and Sensing Properties. ACS Appl. Mater. Interfaces 2014, 6, 12505-12514. (33) Dou, Z. F.; Cao, C. Y.; Wang, Q.; Qu, J.; Yu, Y.; Song, W. G. Synthesis Self-Assembly and High Performance in Gas Sensing of X-shaped Iron Oxide Crystals. ACS Appl. Mater. Interfaces 2012, 4, 5698-5703. (34) Sun, L. Q.; Han, X.; Liu, K.; Yin, S.; Chen, Q. L.; Kuang, Q.; Han, X. G.; Xie, Z. X.; Wang, C. Template-Free Construction of Hollow α-Fe2O3 Hexagonal Nanocolumn Particles with an Exposed Special Surface for Advanced Gas Sensing Properties. Nanoscale 2015, 7, 9416-9420. (35) Chen, A. R.; Xu, L.; Zhang, X. J.; Yang, Z. M.; Yang, S. C. Improving Surface Adsorption via Shape Control of Hematite α‑Fe2O3 Nanoparticles for Sensitive Dopamine Sensors. ACS Appl. Mater. Interfaces 2016, 8, 33765-33774.

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(36) Wang, J. L.; Pei, C. J.; Cheng, L. J.; Wan, W. P.; Zhao, Q.; Yang, H. Q.; Liu, S. Z.(Frank). Responses of Three-Dimensional Porous ZnO Foam Structures to the Trace Level of Triethylamine and Ethanol. Sens. Actuators, B 2016, 223, 650-657. (37) Rodriguez, R. D.; Demaille, D.; Lacaze, E.; Jupille, J.; Chaneac, C.; Jolivet, J. P. Rhombohedral Shape of Hematite Nanocrystals Synthesized via Thermolysis of an Additive-Free Ferric Chloride Solution. J. Phys. Chem. C 2007, 111, 16866-16870. (38)Sun, B.; Horvat, J.; Kim, H. S.; Kim, W. S.; Ahn, J.; Wang, G. X. Synthesis of Mesoporous α-Fe2O3 Nanostructures for Highly Sensitive Gas Sensors and High Capacity Anode Materials in Lithium Ion Batteries. J. Phys. Chem. C 2010, 114, 18753-18761. (39) Condon, J. B. Surface Area and Porosity Determinations by Physisorption Measurements and Theory. 1st ed., Elsevier, Kidlington 2006, pp. 6-13. (40) Jing, Z. H.; Zhan, J. H. Fabrication and Gas-Sensing Properties of Porous ZnO Nanoplates. Adv. Mater. 2008, 20, 4547-4551. (41) Wu, Z. C.; Yu, K.; Zhang, S. D.; Xie, Y. Hematite Hollow Spheres with a Mesoporous Shell: Controlled Synthesis and Applications in Gas Sensor and Lithium Ion Batteries. J. Phys. Chem. C 2008, 112, 11307-11313. (42) Gao, Y.; Chambers, S. A. Heteroepitaxial Growth of α-Fe2O3, γ-Fe2O3 and Fe3O4 Thin Films by Oxygen-Plasma-Assisted Molecular Beam Epitaxy. J. Cryst. Growth 1997, 174, 446-454. (43) Dupin, J. C.; Gonbeau, D.; Vinatier, P.; Levasseur, A. Systematic XPS Studies of Metal Oxides Hydroxides and Peroxides. Phys. Chem. Chem. Phys. 2000, 2,

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1319-1324. (44) Chen, L. X.; Liu, T.; Thurnauer, M. C.; Csencsits, R.; Rajh, T. Fe2O3 Nanoparticle Structures Investigated by X-ray Absorption Near-Edge Structure, Surface Modifications, and Model Calculations. J. Phys. Chem. B 2002, 106, 8539-8546. (45) Jia, C. J., Sun, L. D.; Yan, Z. G.; You, L. P.; Luo, F.; Han, X. D.; Pang, Y. C.; Zhang, Z.; Yan, C. H. Single-Crystalline Iron Oxide Nanotubes. Angew. Chem. Int. Ed. 2005, 44, 4328-4333. (46) Gurlo, A.; Sahm, M.; Oprea, A.; Barsan, N.; Weimar, U. A p- to n-Transition on α-Fe2O3-Based Thick Film Sensors Studied by Conductance and Work Function Change Measurements. Sens. Actuators, B 2004, 102, 291-298. (47) Kim, H. S.; Jung, E. S.; Lee, W. J.; Kim, J. H.; Ryu, S. O.; Choi, S. Y. Effects of

Oxygen Concentration on the Electrical Properties of ZnO Films. Ceram Int. 2008, 34, 1097-1101.

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b

1 µm

25 µm

c

5 µm

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1 µm

500 nm

Figure 1. (a-d) Different magnification SEM images of the products synthesized by heating Fe(NO3)3 solution containing PVP at 650 oC for 10 min.

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(116)

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(104)

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60

70

Figure 2. XRD pattern of the products synthesized by heating Fe(NO3)3 solution containing PVP at 650 oC for 10 min. The stick pattern is the standard XRD pattern of -Fe2O3 powders with Cu Kα1 radiation (JPCDS card file no. 33-0664).

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a

a

c

b

d

Figure 3. (a) TEM image of a single constituent -Fe2O3 nanosheet, (b) and (c) SAED pattern and HRTEM image from box in (a), and (d) schematic illustration of crystal orientation of the -Fe2O3 nanosheet.

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a

c

-430 -440

9.98 nm

-450

17.18 nm

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2.29 nm

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Height (nm)

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18.33 nm

-440 -450

11.13 nm

-460 0

50

100

150

Distance (pm)

Figure 4. (a) AFM height and (b) phase images of the -Fe2O3 nanosheets. (c) and (d) The height profiles are taken along the lines 1 and 2. in (a), respectively.

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100

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0 40

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Time (s)

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Figure 5. (a) and (b) Temperature-dependent response curves of the  -Fe2O3 nanosheet network sensor to 100 ppm of C2H5OH and 100 ppm of N(C2H5)3.

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(024) (116) (018) (214) (300)

b

(113)

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Intensity (a.u.)

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(104) (110)

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50

2 Theta (deg.)

60

Figure 6. (a) SEM image and (b) XRD pattern of the -Fe2O3 commercial powers.

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ethanol

Resistance ( KΩ)

network structure

commercial power

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Resistance ( KΩ)

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6 4

9 6 3

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500

0

0

100

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400

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Concentration (ppm)

Figure 7. (a) and (b) Response and recovery curves (c) and (d) The response curves of the  -Fe2O3 network structures and commercial powers sensors to different concentrations of C2H5OH and N(C2H5)3 at 300oC, respectively

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c

8 6

0.020 0.015 0.010 0.005 0.000 0

20 40 60 Pore Size (nm)

80

4 0.0

400 300 200 100

0.2 0.4 0.6 0.8 1.0 Relative Pressure ( P/P0)

network structures commercial power

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Pore volume ( cm3STP/g)

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b

0.12 0.10 0.08 0.06 0.04 0.02 0.00 0

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0 0.0

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600 500

commercial power

network structures

400 300 200 100 0

0

Figure 8. (a) and (b) The nitrogen adsorption-desorption isotherm of the α-Fe2O3 commercial powers and network structures, respectively. The inset shows the corresponding BJH pore size distribution. (c) and (d) Responses of per unit surface area of the α-Fe2O3 networks structures and commercial power sensors to 100 ppm of C2H5OH and N(C2H5)3 at 300oC, respectively.

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Intensity (a.u.)

a

700

Intensity (a.u.)

b

526

c

Fe2p3/2

526

Fe2p1/2

satellite

network structure commercial power 710

720

730

Binding Energy (eV)

740

network structure OL

OV OC

528

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532

534

Binding Energy (eV)

536

commercial power OL

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OV OC

528

530

532

534

Binding Energy (eV)

536

Figure 9. (a) Fe 2p and (b)-(c) O 1s XPS spectra of α-Fe2O3 network structures and commercial powers.

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a

VOCs CO2+H2O (+N2)

b

O2

O2

O2

O2

O2

e-

e-

e-

e-

e-

c

O2

O2

O2

O2

O2

e-

e-

e-

e-

e-

in VOC vapor

in air

unsaturated Fe atom with dangling bonds

e- electron captured by O2

Figure 10. (a) Schematic structure for atom configuration on the (104) facets of α-Fe2O3. 31 Copyright 2012 The Royal Society of Chemistry. (b)-(c) Sensing reaction mechanism on theα-Fe2O3 (104) surface.

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Table 1.The relative percentages of the OL, OV and OC components estimated from the two kinds of -Fe2O3 samples

Sample network structures commercial powers

Oxygen species

Binding energy (eV)

Relative percentage (%)

OL (Fe−O) OV (vacancy) OC (chemisorbed) OL (Fe−O) OV (vacancy) OC (chemisorbed)

529.15 530.8 532.9 528.53 530.6 532.55

33.64 51.9 14.46 54.05 39.51 6.44

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