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Atomic species identification at the (101) anatase surface by simultaneous scanning tunnelling and atomic force microscopy.

Stetsovych O, Todorović M, Shimizu TK, Moreno C, Ryan JW, León CP, Sagisaka K, Palomares E, Matolín V, Fujita D, Perez R, Custance O - Nat Commun (2015)

Bottom Line: Methods for the accurate characterization of this reducible oxide at the atomic scale are critical in the exploration of outstanding properties for technological developments.Based on key distinguishing features extracted from calculations and experiments, we identify candidates for the most common surface defects.Our results pave the way for the understanding of surface processes, like adsorption of metal dopants and photoactive molecules, that are fundamental for the catalytic and photovoltaic applications of anatase, and demonstrate the potential of dynamic AFM-STM for the characterization of wide band gap materials.

View Article: PubMed Central - PubMed

Affiliation: 1] National Institute for Materials Science (NIMS), 1-2-1 Sengen, Tsukuba 305-0047, Japan [2] Charles University, Faculty of Mathematics and Physics, V Holešovičkách 2, Praha 8, Czech Republic.

ABSTRACT
Anatase is a pivotal material in devices for energy-harvesting applications and catalysis. Methods for the accurate characterization of this reducible oxide at the atomic scale are critical in the exploration of outstanding properties for technological developments. Here we combine atomic force microscopy (AFM) and scanning tunnelling microscopy (STM), supported by first-principles calculations, for the simultaneous imaging and unambiguous identification of atomic species at the (101) anatase surface. We demonstrate that dynamic AFM-STM operation allows atomic resolution imaging within the material's band gap. Based on key distinguishing features extracted from calculations and experiments, we identify candidates for the most common surface defects. Our results pave the way for the understanding of surface processes, like adsorption of metal dopants and photoactive molecules, that are fundamental for the catalytic and photovoltaic applications of anatase, and demonstrate the potential of dynamic AFM-STM for the characterization of wide band gap materials.

No MeSH data available.


Identification of surface defects at the TiO2(101) anatase surface.(a) Simultaneous AFM topographic (Z(Δf)) and (b) averaged tunnelling current (<It>) images showing a candidate for a subsurface oxygen vacancy defect. Images of a defect candidate to represent a surface hydroxyl group are displayed on panels (c,d). Duplicates of these experimental images with a superimposed model of the outer atomic layers of the TiO2(101) anatase surface are also shown. (e) Variation of the topographic signal along the line profiles in a and c. The combination of these experimental images and our theoretical predictions provides the necessary clues for the identification of these atomic defects (see text). Acquisition parameters are: fo=153,031 Hz, Δf=−50.0 Hz, A=107.1 Å, K=23.9 N·m−1, CPD=+800 mV, VBias=+1,000 mV, for a and b; and fo=159,989 Hz, Δf=−11.5 Hz, A=109.9 Å, K=27.3 N m−1, CPD=−180 mV, VBias=+550 mV, for c–e. Image dimensions for a and d are (5.0 × 3) nm2 and (3.0 × 2.4) nm2, respectively. Atomic models of optimal geometries and corresponding Tersoff–Hamann STM images for: (f) a subsurface oxygen vacancy (0.8 V); (g) a surface hydroxyl group (0.6 V) and (h) a water molecule attached to the surface (0.4 V). Dark areas in computed STM images in f and g appear near reduced  surface sites (white squares) associated with the defect formation. The dotted-line ellipse in f highlights the position of the subsurface oxygen vacancy. An atomic model of the surface has been superimposed to the calculated STM images.
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f5: Identification of surface defects at the TiO2(101) anatase surface.(a) Simultaneous AFM topographic (Z(Δf)) and (b) averaged tunnelling current (<It>) images showing a candidate for a subsurface oxygen vacancy defect. Images of a defect candidate to represent a surface hydroxyl group are displayed on panels (c,d). Duplicates of these experimental images with a superimposed model of the outer atomic layers of the TiO2(101) anatase surface are also shown. (e) Variation of the topographic signal along the line profiles in a and c. The combination of these experimental images and our theoretical predictions provides the necessary clues for the identification of these atomic defects (see text). Acquisition parameters are: fo=153,031 Hz, Δf=−50.0 Hz, A=107.1 Å, K=23.9 N·m−1, CPD=+800 mV, VBias=+1,000 mV, for a and b; and fo=159,989 Hz, Δf=−11.5 Hz, A=109.9 Å, K=27.3 N m−1, CPD=−180 mV, VBias=+550 mV, for c–e. Image dimensions for a and d are (5.0 × 3) nm2 and (3.0 × 2.4) nm2, respectively. Atomic models of optimal geometries and corresponding Tersoff–Hamann STM images for: (f) a subsurface oxygen vacancy (0.8 V); (g) a surface hydroxyl group (0.6 V) and (h) a water molecule attached to the surface (0.4 V). Dark areas in computed STM images in f and g appear near reduced surface sites (white squares) associated with the defect formation. The dotted-line ellipse in f highlights the position of the subsurface oxygen vacancy. An atomic model of the surface has been superimposed to the calculated STM images.

Mentions: Identification of adsorbates on the anatase (101) surface using STM manipulation techniques have been recently demonstrated42. The combination of dynamic AFM-STM experiments and quantum mechanical simulations supplies alternative means for the identification of point defects on the anatase (101) surface. Using first-principles calculations, we have analyzed the structures of common defects expected at the anatase surface, such as subsurface oxygen vacancies43 and hydroxyl groups, and identified the key features they should exhibit in the experimental images (Fig. 5).


Atomic species identification at the (101) anatase surface by simultaneous scanning tunnelling and atomic force microscopy.

Stetsovych O, Todorović M, Shimizu TK, Moreno C, Ryan JW, León CP, Sagisaka K, Palomares E, Matolín V, Fujita D, Perez R, Custance O - Nat Commun (2015)

Identification of surface defects at the TiO2(101) anatase surface.(a) Simultaneous AFM topographic (Z(Δf)) and (b) averaged tunnelling current (<It>) images showing a candidate for a subsurface oxygen vacancy defect. Images of a defect candidate to represent a surface hydroxyl group are displayed on panels (c,d). Duplicates of these experimental images with a superimposed model of the outer atomic layers of the TiO2(101) anatase surface are also shown. (e) Variation of the topographic signal along the line profiles in a and c. The combination of these experimental images and our theoretical predictions provides the necessary clues for the identification of these atomic defects (see text). Acquisition parameters are: fo=153,031 Hz, Δf=−50.0 Hz, A=107.1 Å, K=23.9 N·m−1, CPD=+800 mV, VBias=+1,000 mV, for a and b; and fo=159,989 Hz, Δf=−11.5 Hz, A=109.9 Å, K=27.3 N m−1, CPD=−180 mV, VBias=+550 mV, for c–e. Image dimensions for a and d are (5.0 × 3) nm2 and (3.0 × 2.4) nm2, respectively. Atomic models of optimal geometries and corresponding Tersoff–Hamann STM images for: (f) a subsurface oxygen vacancy (0.8 V); (g) a surface hydroxyl group (0.6 V) and (h) a water molecule attached to the surface (0.4 V). Dark areas in computed STM images in f and g appear near reduced  surface sites (white squares) associated with the defect formation. The dotted-line ellipse in f highlights the position of the subsurface oxygen vacancy. An atomic model of the surface has been superimposed to the calculated STM images.
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Related In: Results  -  Collection

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f5: Identification of surface defects at the TiO2(101) anatase surface.(a) Simultaneous AFM topographic (Z(Δf)) and (b) averaged tunnelling current (<It>) images showing a candidate for a subsurface oxygen vacancy defect. Images of a defect candidate to represent a surface hydroxyl group are displayed on panels (c,d). Duplicates of these experimental images with a superimposed model of the outer atomic layers of the TiO2(101) anatase surface are also shown. (e) Variation of the topographic signal along the line profiles in a and c. The combination of these experimental images and our theoretical predictions provides the necessary clues for the identification of these atomic defects (see text). Acquisition parameters are: fo=153,031 Hz, Δf=−50.0 Hz, A=107.1 Å, K=23.9 N·m−1, CPD=+800 mV, VBias=+1,000 mV, for a and b; and fo=159,989 Hz, Δf=−11.5 Hz, A=109.9 Å, K=27.3 N m−1, CPD=−180 mV, VBias=+550 mV, for c–e. Image dimensions for a and d are (5.0 × 3) nm2 and (3.0 × 2.4) nm2, respectively. Atomic models of optimal geometries and corresponding Tersoff–Hamann STM images for: (f) a subsurface oxygen vacancy (0.8 V); (g) a surface hydroxyl group (0.6 V) and (h) a water molecule attached to the surface (0.4 V). Dark areas in computed STM images in f and g appear near reduced surface sites (white squares) associated with the defect formation. The dotted-line ellipse in f highlights the position of the subsurface oxygen vacancy. An atomic model of the surface has been superimposed to the calculated STM images.
Mentions: Identification of adsorbates on the anatase (101) surface using STM manipulation techniques have been recently demonstrated42. The combination of dynamic AFM-STM experiments and quantum mechanical simulations supplies alternative means for the identification of point defects on the anatase (101) surface. Using first-principles calculations, we have analyzed the structures of common defects expected at the anatase surface, such as subsurface oxygen vacancies43 and hydroxyl groups, and identified the key features they should exhibit in the experimental images (Fig. 5).

Bottom Line: Methods for the accurate characterization of this reducible oxide at the atomic scale are critical in the exploration of outstanding properties for technological developments.Based on key distinguishing features extracted from calculations and experiments, we identify candidates for the most common surface defects.Our results pave the way for the understanding of surface processes, like adsorption of metal dopants and photoactive molecules, that are fundamental for the catalytic and photovoltaic applications of anatase, and demonstrate the potential of dynamic AFM-STM for the characterization of wide band gap materials.

View Article: PubMed Central - PubMed

Affiliation: 1] National Institute for Materials Science (NIMS), 1-2-1 Sengen, Tsukuba 305-0047, Japan [2] Charles University, Faculty of Mathematics and Physics, V Holešovičkách 2, Praha 8, Czech Republic.

ABSTRACT
Anatase is a pivotal material in devices for energy-harvesting applications and catalysis. Methods for the accurate characterization of this reducible oxide at the atomic scale are critical in the exploration of outstanding properties for technological developments. Here we combine atomic force microscopy (AFM) and scanning tunnelling microscopy (STM), supported by first-principles calculations, for the simultaneous imaging and unambiguous identification of atomic species at the (101) anatase surface. We demonstrate that dynamic AFM-STM operation allows atomic resolution imaging within the material's band gap. Based on key distinguishing features extracted from calculations and experiments, we identify candidates for the most common surface defects. Our results pave the way for the understanding of surface processes, like adsorption of metal dopants and photoactive molecules, that are fundamental for the catalytic and photovoltaic applications of anatase, and demonstrate the potential of dynamic AFM-STM for the characterization of wide band gap materials.

No MeSH data available.