Why Could the Nature of Surface Facets Lead to Differences in the

Subscriber access provided by the Henry Madden Library | California State University, Fresno

Article

Why Could the Nature of Surface Facets Lead to Differences in the Activity and Stability of Cu2O-based Electrocatalytic Sensors? Fabian A.C. Pastrian, Anderson G.M. da Silva, André H.B. Dourado, Ana P.L. Batista, Antonio G.S. de Oliveira-Filho, Jhon Quiroz, Daniela C de Oliveira, Pedro H. C. Camargo, and Susana Inés Córdoba De Torresi ACS Catal., Just Accepted Manuscript • DOI: 10.1021/acscatal.8b00726 • Publication Date (Web): 04 Jun 2018 Downloaded from http://pubs.acs.org on June 4, 2018

Just Accepted “Just Accepted” manuscripts have been peer-reviewed and accepted for publication. They are posted online prior to technical editing, formatting for publication and author proofing. The American Chemical Society provides “Just Accepted” as a service to the research community to expedite the dissemination of scientific material as soon as possible after acceptance. “Just Accepted” manuscripts appear in full in PDF format accompanied by an HTML abstract. “Just Accepted” manuscripts have been fully peer reviewed, but should not be considered the official version of record. They are citable by the Digital Object Identifier (DOI®). “Just Accepted” is an optional service offered to authors. Therefore, the “Just Accepted” Web site may not include all articles that will be published in the journal. After a manuscript is technically edited and formatted, it will be removed from the “Just Accepted” Web site and published as an ASAP article. Note that technical editing may introduce minor changes to the manuscript text and/or graphics which could affect content, and all legal disclaimers and ethical guidelines that apply to the journal pertain. ACS cannot be held responsible for errors or consequences arising from the use of information contained in these “Just Accepted” manuscripts.

is published by the American Chemical Society. 1155 Sixteenth Street N.W., Washington, DC 20036 Published by American Chemical Society. Copyright © American Chemical Society. However, no copyright claim is made to original U.S. Government works, or works produced by employees of any Commonwealth realm Crown government in the course of their duties.

Page 1 of 30 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

ACS Catalysis

Why Could the Nature of Surface Facets Lead to Differences in the Activity and Stability of Cu2O-based Electrocatalytic Sensors?

Fabián A.C. Pastrián,1 Anderson G. M. da Silva,1 André H.B. Dourado,1 Ana P. de Lima Batista,1 Antonio G.S. de Oliveira-Filho,2 Jhon Quiroz,1 Daniela C. de Oliveira,3 Pedro H.C. Camargo,1 Susana I. Córdoba de Torresi1*

1

Departamento de Química Fundamental, Instituto de Química, Universidade de São Paulo Av. Prof. Lineu Prestes, 748, 05508-000, São Paulo, SP, Brazil 2

Departamento de Química, Faculdade de Filosofia, Ciências e Letras de Ribeirão Preto, Universidade de São Paulo, 14040-901, Ribeirão Preto, SP, Brazil

3

Centro Nacional de Pesquisa em Energia e Materiais, Laboratório Nacional de Luz Síncrotron, Campinas, Brazil

F.A.C.P. and A.G.M.S contributed equally to this article.

*Corresponding author. E-mail: [email protected]

ACS Paragon Plus Environment

ACS Catalysis 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

Abstract

By a combination of theoretical and experimental design, we unraveled the effect of {111} and {100} surface facets on the electrocatalytic sensing activities and stabilities of metal oxides by employing Cu2O crystals as a model substrate and glucose as the analyte. We started by theoretically investigating the potential energy curves for the glucose interaction with the Cu2O {111} and {100} surface facets. We found that the glucose interaction energy was significantly higher for the {100} facets than the {111} facets. Then, we experimentally observed that their electrocatalytic sensing performance displayed shape-dependent behavior. While the catalytic activities followed the order cubes > cuboctahedrons > octahedrons, their stabilities showed the opposite trend. The higher catalytic activity enabled by the {100} facets is explained by their stronger interaction with glucose. On the other hand, the higher stability allowed by the {111} facets is justified by their lower concentration of oxygen vacancies and weaker interaction with O2 relative to those of the {100} surface.

Keywords: Cu2O, controlled synthesis, electrocatalysts, glucose sensors, activity, stability, oxygen vacancy.

1 ACS Paragon Plus Environment

Page 2 of 30

Page 3 of 30 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

ACS Catalysis

Introduction

Materials having well-defined surface facets hold great promise for the development of nonenzymatic electrocatalytic sensors.1–4 They allow the optimization of surface interactions with a target analyte, potentially leading to increased catalytic activity and selectivity.5–7 Among the materials employed in nonenzymatic electrocatalytic sensors, copper oxides (such as Cu2O) have been investigated due to their good performance, lower cost, and higher stabilities than enzymatic sensors.8–12 Even though the utilization of copper-based oxides has been described in electrocatalytic sensing, only a few studies have focused on the establishment of structureperformance relationships.13–16 As the control over the morphology has been shown to strongly affect their performances, it becomes intuitive to raise the following question: why does the exposure of specific surface facets strongly influence catalytic activities, selectivities, and stabilities? This understanding remains lacking, making it clear that the understanding of the interactions between particular surface facets and a target analyte remains challenging and crucial for clarifying the mechanisms underlying the observed performances. In this paper, by a combination of theoretical simulations and experimental investigations, we aimed to provide new insights into the mechanism responsible for the shapedependent performance in nonenzymatic electrocatalytic sensors. We employed glucose as a model analyte and Cu2O crystals displaying well-defined morphologies as a model substrate. Cu2O is attractive because, by applying similar experimental conditions, it is possible to


ACS Catalysis 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

generate crystals with well-defined surface facets and similar sizes, allowing a systematic investigation on the effect of shape on their performances.17–19 Results and Discussion

We started by performing DFT/PBE+D3(BJ)/def2-SVP calculations on the interaction between a glucose molecule and {100} or {111} facets in Cu2O, as shown in Figure 1. Figures 1A and 1B show the calculated potential energy curves for the nondissociative interaction between a rigid glucose molecule and the nonreconstructed surfaces of a rigid Cu2O cube (enclosed by {100} facets) or a rigid Cu2O octahedron (enclosed by {111} facets). The calculations indicate that the glucose interaction energy on the surface of Cu2O is significantly higher for the cubes than octahedrons, corresponding to 2.1 eV and 0.7 eV, respectively. Under the experimental conditions, the adsorbent and the surface exhibit relaxation/reconstruction.20,21 However, the results of the present DFT calculations are in agreement with the overall trends observed in previous studies reporting adsorption energies on reconstructed Cu2O supercell models in the presence and absence of defects.22–25 More details on the DFT calculations used throughout this work are found in the Supporting Information. The stronger interaction indicates that the adsorption of glucose molecules is more favorable on {100} than {111} surfaces (crystal planes with higher surface energy).26,27 Moreover, the energy values reported in this work can be seen as a lower bound to the adsorption energies since the presence of defects or relaxation would increase these values. This observation holds true for the O2 interaction energies we discuss later in the text.


Page 4 of 30

Page 5 of 30 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

ACS Catalysis

To experimentally probe the effect of the surface facets on glucose sensing, we synthetized Cu2O crystals displaying controllable morphologies that enable the exposure of these surface facets.18,28 We focused on Cu2O cubes, cuboctahedrons, and octahedrons displaying similar sizes, as shown by the SEM and TEM images in Figure 2. The Cu2O cubes were 298 ± 34 nm (Figure 2A and 2D), the cuboctahedrons were 311 ± 39 nm (Figure 2B and 2E), and the octahedrons were 302 ± 38 nm (Figure 2C and 2F). Figure S1 shows histograms of the size distribution for the cubes (Figure S1A), cuboctahedrons (Figure S1B), and octahedrons (Figure S1C). The HRTEM images (Figure 2G-I) confirmed that the Cu2O cubes were single crystalline and enclosed by {100} facets, that Cu2O cuboctahedrons were polycrystalline (mix of {100} and {111} facets), and that Cu2O octahedrons are single crystalline and enclosed by {111} facets. The XRD diffractograms of the Cu2O cubes, cuboctahedrons, and octahedrons (Figure S2) show welldefined peaks corresponding to the (110), (111), (100), (220), (311), and (222) crystallographic planes of the cubic structure of Cu2O.18,28 Interestingly, the intensity ratios between the (100) and the (111) peaks decreased as we transitioned from the cubes to the cuboctahedrons and octahedrons, which is in agreement with the HRTEM results. In the next step, we investigated the performance of the Cu2O cubes, cuboctahedrons, and octahedrons in the electrocatalytic detection of glucose, as shown in Figure 3. Figure 3A shows cyclic voltammograms (CVs) in absence of glucose for Cu2O crystals recorded at a scan rate of 10 mVs-1. The j/E potentiodynamic profiles corresponding to Cu2O crystals presented noticeable differences as a function of shape. More specifically, the redox peaks for Cu2O cubes were much more intense than those for cuboctahedrons and octahedrons. Moreover, a welldefined oxidation peak centered at 0.21 V was observed for the Cu2O cubes. Figure 3B shows 4 ACS Paragon Plus Environment

ACS Catalysis 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

the chronoamperometric curves obtained at 0.5 V in the presence of glucose for the cubes, cuboctahedrons, and octahedrons. The electrocatalytic detection activity followed the order cubes > cuboctahedrons > octahedrons. The detection limits obtained for the cubes, cuboctahedrons and octahedrons were 16, 60, and 165 nM, respectively. These values were determined from the graph shown in Figure 3C (signal-to-noise ratio = 3). The specific surface areas for the Cu2O cubes, cuboctahedrons, and octahedrons were similar (11, 15, 14 m2/g, respectively, as measured by the BET method). Therefore, the differences in the electrocatalytic activity should not be related to differences in the specific surface area (activity per surface sites). As a result, these results indicate that the nature of the surface facets strongly affected both the detection limit and electrocatalytic sensitivity towards glucose. In this case, {100} facets (in the cubes) led to improved electrocatalytic performances relative to {111} + {100} (cuboctahedron) and {111} (octahedron) facets. One of the major challenges in the nonenzymatic electrocatalytic detection of glucose is to eliminate the interfering responses generated by some endogenous species, such as ascorbic acid, dopamine, and uric acid.29,30 Therefore, we also investigated the selectivity, as depicted by the chronoamperometric curves measured in the presence of interferents shown in Figure 3D. The interferents tested were ascorbic acid (A.A.) and uric acid (U.A). We found that the Cu2O cubes displayed electrocatalytic responses only towards glucose detection, whereas the addition of the other species led to negligible effects on the anodic current. This result indicated that the cubes displayed good selectivity towards the electrocatalytic detection of glucose. Conversely, cuboctahedrons and octahedrons were not selective, and significant anodic currents were detected upon the addition of the interferents.


Page 6 of 30

Page 7 of 30 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

ACS Catalysis

It is important to note that a similar work has been reported by Tang and coauthors,31 who also employed Cu2O crystals with different morphologies to study the facet-dependent glucose electrocatalytic sensing activities of Cu2O crystals. Conversely, they found that Cu2O octahedrons presented a higher sensitivity, lower detection limit, and wider linear range than Cu2O cubes.31 We believe their opposite conclusions may be explained by the following reasons: (i) first of all, the authors employed Nafion as stabilizer of the electrode. This polymer is extensively used in electrochemistry but features many functionalities that would interfere with the activity, selectivity, and stability of the electrochemical sensors.32,33 We believe that by covering the surface of the electrode with Nafion, the effect caused by the (111) and (110) facets may not be clearly observed. Moreover, it is also important to emphasize that as Nafion is a charged polymer, this organic compound is also expected to affect the double layer structure.34 This effect may be one of the reasons for the different current-potential profiles obtained in the present work compared to the results reported by Tang et al,31 and (ii) the electrochemical results presented in the paper reported by Tang and coauthors were not normalized by the surface area or amount of Cu sites on the electrode, so the intensities of the currents and the sensitivity are expected to also be different. The optimization of the long-term stability of electrocatalytic sensors also presents an important challenge.35 It is well established that Cu2O may be partially oxidized to Cu2+ in the presence of air/dissolved oxygen.36–38 To verify the Cu2O stabilities as a function of shape, we performed control experiments under the same conditions described in Figure 3 but analyzed the glucose detection performances of Cu2O cubes and octahedrons after they had been stored for several days in aqueous suspensions (relative to their freshly prepared counterparts).


ACS Catalysis 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

Surprisingly, the catalytic activity and selectivity of the cubes decreased significantly as a function of time, as shown in Figure 4. The catalytic activities of the cubes on the 14th day after synthesis were similar to those of freshly prepared octahedrons. On the other hand, the catalytic sensitivity and selectivity of Cu2O octahedrons did not show a substantial change as a function of time. After 14 days, the octahedrons were only 10 % less active and selective than their freshly prepared analogues. Therefore, we suggest that a shape-dependent preferential oxidative process (Cu2O to CuO) may explain the differences in the electrocatalytic detection activities as a function of time. To verify this hypothesis, we probed the effect of time on the morphology of Cu2O cubes and octahedrons in aqueous suspensions. Figure 5A-F show HRTEM images of the Cu2O cubes as a function of the time that they had been stored in aqueous suspensions. The results confirmed the partial oxidation of Cu2O to CuO over time, as the formation of dendritic structures was detected (Figure 5A-F). This finding is also in agreement with the SEM images (Figure S3). The number and size of the formed branches also increased as a function of time. In addition to the morphological changes, the phase-contrast HRTEM results show that the individual branches formed at the particle surface were single crystalline with lattice fringes corresponding to the {111} spacing of CuO (Figure 5E-F), which indicates that the {100} spacing of Cu2O was converted to CuO branches during catalytic oxidation, leading to growth in the direction. The results of XRD analysis are also in agreement with these results (Figure S4). In this case, the diffractograms for the Cu2O cubes clearly indicate that the intensity ratios between the {100} and the {111} peaks are progressively decreased as a function of time. 18,28 We also performed a similar study on the Cu2O octahedrons, as shown in Figure 5H-M. HRTEM 7 ACS Paragon Plus Environment

Page 8 of 30

Page 9 of 30 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

ACS Catalysis

images indicated that the structure of the Cu2O octahedrons remained almost unaffected even after 14 days. In this case, the phase-contrast HRTEM results show the formation of several small islands of CuO nanoparticles (approximately 2-4 nm) at the Cu2O octahedron surface (Figure 5L-M). SEM images of Cu2O octahedrons on the 14th day also support these observations (Figure S5). This result may explain why the catalytic activities on the 14th day after the synthesis of the Cu2O cubes were similar to those of the Cu2O octahedrons on the 1st day. The morphological evolution of the cubes and octahedrons is in agreement with DFT calculations of the interaction of O2 with the Cu2O {100} and Cu2O {111} planes, as shown in Figure 5G and 5N, respectively. It can be observed that the nondissociative interaction energy of O2 on the Cu2O {100} surface is 1.4 eV larger than that on the Cu2O {111} surface. To provide further insights into the factors that led to the higher catalytic activities and lower stabilities of the Cu2O cubes, we performed spectroelectrochemistry coupled with in situ Fourier transform infrared spectroscopy in the presence of glucose, as shown in Figure S6. The spectra of the Cu2O crystals also presented marked differences as a function of shape. More specifically, the Cu2O cubes presented higher currents and intensities during all in situ FTIR measurements. The intense negative band at 972 cm-1 for the cubes is especially interesting, as the same negative band for the octahedrons was much less intense and broader and was shifted to 1070 cm-1.39 This region is related to adsorption/desorption processes of SDS (a stabilizing agent employed in the synthesis of Cu2O crystals)39. In this case, as an excess amount of SDS was employed during the synthesis, it would be expected to lead to a similar coverage, which is in agreement with the XPS results (Figure S7, Supporting Information). The Cu/S intensity ratios extracted from their XPS spectra indicated that the coverage on the Cu2O cubes 8 ACS Paragon Plus Environment

ACS Catalysis 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

and octahedrons were similar. On the other hand, because the desorption abilities of the {100} and {111} facets are different, the desorption process of SDS as function of Cu2O shape should also be different. This is in agreement with FTIR analyses performed in the absence and presence of glucose (Figure S8 in support information). The intense negative band at 972 cm-1 is suggested to be related to SDS desorption from the Cu2O surface.39 This proposal is also supported by the band at 1238 cm-1 for the Cu2O cubes, which is associated with the stretching modes of free sulfonate groups.39 The desorption of SDS from the surface of the Cu2O cubes is expected to be related to the oxidation mechanism of glucose, as indicated by the band at 1108 cm-1.40 In this case, glucose may strongly adsorb at the Cu2O cubes and then oxidize to gluconate (νasO-C-O),40 elevating the activities for glucose detection and increasing the desorption process of SDS from the cube surface. This may also contribute to their lower stabilities: a weaker interaction with O2 molecules at the Cu2O {111} facets relative to the Cu2O {100} facets may favor the better stabilities of the Cu2O octahedrons than the cubes, as shown in Figure 5, in agreement with the HRTEM results and DFT simulations. The oxidation of the Cu2O species to CuO is also supported by the band at 3580 cm-1, which is assigned to νOH bonded to Cu.39 To circumvent the lower stabilities of the Cu2O cubes in water suspensions associated with their partial oxidation to Cu2+ in the presence of air/dissolved oxygen, the protocol for preparing the electrodes was changed. Freshly prepared Cu2O nanocubes were centrifuged, then dried and stored under vacuum. Interestingly, the results indicated that under these conditions, the catalytic activity of the cubes on the 14th day after the synthesis was similar to that of freshly prepared cubes (Figure 6A). Their electrocatalytic responses also maintained high 9 ACS Paragon Plus Environment

Page 10 of 30

Page 11 of 30 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

ACS Catalysis

selectivity towards the glucose detection on the 14th day after synthesis, as the addition of other species had negligible effects on the oxidation current (Figure 6B). Therefore, the Cu2O cubes were demonstrated to be promising electrocatalytic sensors when stored under these conditions. Based on the morphological observations, control experiments, electrocatalytic results, and theoretical simulations, it is possible to infer that the detected variations in catalytic activity and stability could be explained based on the different exposed surface facets in the Cu2O crystals. In this study, the electrocatalytic activities increased significantly as the fraction of {100} surface facets increased. Conversely, the electrocatalytic stabilities decreased as the fraction of {100} surface facets in the Cu2O crystals increased. In this context, it is well established that the surface energies associated with different crystallographic planes follow the order γ(110) > γ(100) > γ(111).41,42 As the electron transfer from Cu2O to an adsorbed molecule should represent a crucial step for electrocatalytic detection, it is plausible that a stronger interaction of glucose with the Cu2O {100} surface facets favors the enhanced activities of the Cu2O cubes. In principle, the high selectivity of the {100} surface facets for glucose over ascorbate and urate anions (as all experiments were performed in basic pH) may also be explained based on the variations in the interaction energies. However, the calculations indicated that the glucose interaction energy on the {100} surface facets has a similar magnitude to that of ascorbate and urate anions (2.1, 2.5, and 2.4 eV for glucose and urate and ascorbate anions, respectively). Thus, it is possible that the higher selectivities are related to the charge distribution of the Cu2O cubes. The electrostatic potential map for a Cu2O cube (Figure S9) 10 ACS Paragon Plus Environment

ACS Catalysis 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

illustrates its charge distribution. In agreement with previous studies,43–45 the Cu2O cubes present a polar charge distribution. As the adsorption/desorption process of a molecule at the surface of Cu2O is considered a limiting step during the detection process, the presence of charged species such as the urate and ascorbate anions may represent a hindrance to the adsorption/desorption process on the cube nanoparticle. Conversely, as glucose is a neutral molecule even under basic conditions, it can interact with the polar Cu2O cube by dipole-dipole interactions. Finally, the electrocatalytic stabilities decreased as the fraction of {100} surface facets in the Cu2O crystals increased. Regarding stability, O2 is a key element in the electrocatalytic processes of adsorption, electron transfer, and subsequent chemical rearrangement.46,47 Defects at transition metal oxide surfaces such as oxygen vacancies play a major role in a variety of technological applications.48 In fact, under real conditions, metal oxide surfaces such as Cu2O are not always perfect, and the properties of most metal oxides, including surface reactivity, are closely related to the presence of surface vacancies, which has been a motivation of numerous studies of partially reduced oxide surfaces.48–50 For example, Zhang and coauthors reported that the calculated results concerning the presence of oxygen vacancies in {111} facets exhibit that there is strong chemical reactivity towards the dissociation of O2, which may subsequently improve their activities but decrease their stabilities.24 Interestingly, this observation agrees with the results of XPS analyses (Figure S10 and Table S1). In this case, three surface oxygen species could be clearly observed in the O 1s XPS spectra. The binding energy between 528.9 and 529.2 eV was characteristic of the lattice oxygen (denoted OL), the binding energy between 532.0 and 531.2 eV was assigned to oxygen vacancies or the surface oxygen


Page 12 of 30

Page 13 of 30 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

ACS Catalysis

ions (denoted Os), and the binding energy at approximately 533.0 eV was characteristic of adsorbed water (Ow) at the surface of catalyst.51 The Cu2O cubes displayed a much higher OS/OL ratio than the Cu2O octahedrons, indicating a higher concentration of oxygen vacancies for the cubes. Therefore, the higher stability enabled by the {111} facets may be justified by their lower concentration of oxygen vacancies and weaker interaction with O2 relative to the {100} surface. Conclusions

In summary, we performed a systematic theoretical and experimental investigation on the electrocatalytic sensing activities of Cu2O crystals as a function of their shape. We employed cubes, cuboctahedrons, and octahedrons as model substrates and glucose as the analyte and found that their catalytic activities, selectivities, and stabilities displayed shape-dependent behavior. While the activities and selectivities followed the order cubes > cuboctahedrons > octahedrons, their stabilities showed the opposite trend. The higher catalytic activity enabled by the {100} facets was explained by their stronger interaction with glucose relative to the {111} facets. On the other hand, the higher stability of Cu2O octahedrons could be explained based on the weaker interaction of O2 with the Cu2O {111} surface facets, which leads to lower reactivities in the formation of CuO. We believe that the results reported herein may provide important guidelines for the development of new electrocatalytic sensors displaying optimized properties. In the design of such sensors, the control of the shape plays an important role in the activity and stability for the nonenzymatic electrocatalytic detection of a wealth of molecules.

Supporting information


ACS Catalysis 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

Experimental details, additional histograms of particle size distributions, additional SEM images, XRD diffractograms, FTIR spectra, DFT simulations, and XPS results. This material is available free of charge via the Internet at http://pubs.acs.org

Acknowledgements

This work was supported by the São Paulo Research Foundation (FAPESP) (grant number 15/26308-7). S.I.C.T. and P.H.C.C. thank CNPq for their research fellowships. F.A.C.P., A.G.M.S., and A.H.B.D. thank CAPES, FAPESP, and CNPq for their fellowships. A.P.d.L.B. and A.G.S.d.O.F thank Grants #2015/22203-6 and #2015/11714-0 (FAPESP) and the support of the HighPerformance Computing of Universidade de São Paulo (HPC-USP)/Rice University (National Science Foundation Grant OCI-0959097). We thank the Brazilian Synchrotron Light Laboratory (LNLS) for the access to the XPS facility and the Laboratory of Structural Characterization (LCE/DEMa/UFSCar) for the general facilities.

References (1)

(2)

(3)

Chai, X.; Zhou, X.; Zhu, A.; Zhang, L.; Qin, Y.; Shi, G.; Tian, Y. A Two-Channel Ratiometric Electrochemical Biosensor for In Vivo Monitoring of Copper Ions in a Rat Brain Using Gold Truncated Octahedral Microcages. Angew. Chemie Int. Ed. 2013, 52, 8129–8133. Liu, M.; He, S.; Chen, W. Co3O4 nanowires supported on 3D N-doped carbon foam as an electrochemical sensing platform for efficient H2O2 detection. Nanoscale 2014, 6 , 11769–11776. Ling, P.; Lei, J.; Jia, L.; Ju, H. Platinum nanoparticles encapsulated metal-organic frameworks for the electrochemical detection of telomerase activity. Chem. Commun. 2016, 52, 1226–1229. 13 ACS Paragon Plus Environment

Page 14 of 30

Page 15 of 30 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

ACS Catalysis

(4)

(5)

(6) (7)

(8)

(9)

(10)

(11)

(12)

(13)

(14)

(15)

(16)

(17)

(18)

Yue, H. Y.; Huang, S.; Chang, J.; Heo, C.; Yao, F.; Adhikari, S.; Gunes, F.; Liu, L. C.; Lee, T. H.; Oh, E. S.; et al. ZnO Nanowire Arrays on 3D Hierachical Graphene Foam: Biomarker Detection of Parkinson’s Disease. ACS Nano 2014, 8, 1639–1646. Kong, L.; Ren, Z.; Zheng, N.; Du, S.; Wu, J.; Tang, J.; Fu, H. Interconnected 1D Co3O4 nanowires on reduced graphene oxide for enzymeless H2O2 detection. Nano Res. 2015, 8, 469–480. Meher, S. K.; Rao, G. R. Archetypal sandwich-structured CuO for high performance nonenzymatic sensing of glucose. Nanoscale 2013, 5, 2089–2099. Gao, Z.; Liu, J.; Chang, J.; Wu, D.; He, J.; Wang, K.; Xu, F.; Jiang, K. Mesocrystalline Cu2O hollow nanocubes: synthesis and application in non-enzymatic amperometric detection of hydrogen peroxide and glucose. CrystEngComm 2012, 14, 6639–6646. Guan, L.; Pang, H.; Wang, J.; Lu, Q.; Yin, J.; Gao, F. Fabrication of novel comb-like Cu2O nanorod-based structures through an interface etching method and their application as ethanol sensors. Chem. Commun. 2010, 46, 7022–7024. Huang, J.; Zhu, Y.; Yang, X.; Chen, W.; Zhou, Y.; Li, C. Flexible 3D porous CuO nanowire arrays for enzymeless glucose sensing: in situ engineered versus ex situ piled. Nanoscale 2015, 7, 559–569. Huang, J.; Zhu, Y.; Zhong, H.; Yang, X.; Li, C. Dispersed CuO Nanoparticles on a Silicon Nanowire for Improved Performance of Nonenzymatic H2O2 Detection. ACS Appl. Mater. Interfaces 2014, 6, 7055–7062. Zhao, Y.; Fan, L.; Zhang, Y.; Zhao, H.; Li, X.; Li, Y.; Wen, L.; Yan, Z.; Huo, Z. Hyper-Branched Cu@Cu2O Coaxial Nanowires Mesh Electrode for Ultra-Sensitive Glucose Detection. ACS Appl. Mater. Interfaces 2015, 7, 16802–16812. Zhu, Y.; Xu, Z.; Yan, K.; Zhao, H.; Zhang, J. One-Step Synthesis of CuO–Cu2O Heterojunction by Flame Spray Pyrolysis for Cathodic Photoelectrochemical Sensing of lCysteine. ACS Appl. Mater. Interfaces 2017, 9, 40452–40460. Meng, L.; Jiang, D.; Xing, C.; Lu, X.; Chen, M. Synthesis and size-dependent electrochemical nonenzymatic H2O2 sensing of cuprous oxide nanocubes. RSC Adv. 2015, 5, 82496–82502. Zhang, X.; Wang, G.; Liu, X.; Wu, J.; Li, M.; Gu, J.; Liu, H.; Fang, B. Different CuO Nanostructures: Synthesis, Characterization, and Applications for Glucose Sensors. J. Phys. Chem. C 2008, 112, 16845–16849. Lv, J.; Kong, C.; Hu, X.; Zhang, X.; Liu, K.; Yang, S.; Bi, J.; Liu, X.; Meng, G.; Li, J.; et al. Zinc ion mediated synthesis of cuprous oxide crystals for non-enzymatic glucose detection. J. Mater. Chem. B 2017, 5, 8686–8694. Yang, C.-J.; Lu, F.-H. Shape and Size Control of Cu Nanoparticles by Tailoring the Surface Morphologies of TiN-Coated Electrodes for Biosensing Applications. Langmuir 2013, 29, 16025–16033. Tsai, Y.-H.; Chanda, K.; Chu, Y.-T.; Chiu, C.-Y.; Huang, M. H. Direct formation of small Cu2O nanocubes, octahedra, and octapods for efficient synthesis of triazoles. Nanoscale 2014, 6, 8704–8709. Huang, W.-C.; Lyu, L.-M.; Yang, Y.-C.; Huang, M. H. Synthesis of Cu2O Nanocrystals from Cubic to Rhombic Dodecahedral Structures and Their Comparative Photocatalytic Activity. J. Am. Chem. Soc. 2012, 134, 1261–1267. 14 ACS Paragon Plus Environment

ACS Catalysis 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

(19) (20)

(21)

(22) (23) (24)

(25)

(26)

(27)

(28) (29)

(30)

(31) (32)

(33)

(34)

Tan, C.-S.; Hsu, S.-C.; Ke, W.-H.; Chen, L.-J.; Huang, M. H. Facet-Dependent Electrical Conductivity Properties of Cu2O Crystals. Nano Lett. 2015, 15, 2155–2160. Dourado, A. H. B.; De Lima Batista, A. P.; Oliveira-Filho, A. G. S.; Sumodjo, P. T. A.; Cordoba De Torresi, S. I. l-Cysteine electrooxidation in alkaline and acidic media: a combined spectroelectrochemical and computational study. RSC Adv. 2017, 7, 74927501. De Lima Batista, A. P.; Ornellas, F. R. CASSCF and MRMP2 investigation of the interaction of arsenic adatoms with carbon dimers on the diamond (100)-2 × 1 surface. Surf. Sci. 2015, 641, 159-165. Yu, X.; Zhang, X.; Tian, X.; Wang, S.; Feng, G. Density functional theory calculations on oxygen adsorption on the Cu2O surfaces. Appl. Surf. Sci. 2015, 324, 53–60. Le, D.; Stolbov, S.; Rahman, T. S. Reactivity of the Cu2O(100) surface: Insights from first principles calculations. Surf. Sci. 2009, 603, 1637–1645. Zhang, R.; Liu, H.; Zheng, H.; Ling, L.; Li, Z.; Wang, B. Adsorption and dissociation of O2 on the Cu2O(111) surface: Thermochemistry, reaction barrier. Appl. Surf. Sci. 2011, 257, 4787–4794. Min, L.; Zhang, J.-Y.; Yue, Z.; Fu-Yang, T.; Jiang, S. A density functional theory study on the adsorption of CO and O2 on Cu-terminated Cu2O(111) surface. Chinese Phys. B 2012, 21, 67302. Xia, Y.; Xiong, Y.; Lim, B.; Skrabalak, S. E. Shape-Controlled Synthesis of Metal Nanocrystals: Simple Chemistry Meets Complex Physics? Angew. Chemie Int. Ed. 2009, 48, 60–103. da Silva, A. G. M.; Rodrigues, T. S.; Wang, J.; Yamada, L. K.; Alves, T. V; Ornellas, F. R.; Ando, R. A.; Camargo, P. H. C. The Fault in Their Shapes: Investigating the SurfacePlasmon-Resonance-Mediated Catalytic Activities of Silver Quasi-Spheres, Cubes, Triangular Prisms, and Wires. Langmuir 2015, 31, 10272–10278. Kuo, C.-H.; Huang, M. H. Facile Synthesis of Cu2O Nanocrystals with Systematic Shape Evolution from Cubic to Octahedral Structures. J. Phys. Chem. C 2008, 112, 18355–18360. Zhu, Z.; Garcia-Gancedo, L.; Flewitt, A. J.; Xie, H.; Moussy, F.; Milne, W. I. A Critical Review of Glucose Biosensors Based on Carbon Nanomaterials: Carbon Nanotubes and Graphene. Sensors 2012, 12, 5996-6022. Liu, Y.; Zhang, Y.; Chen, J.; Pang, H. Copper metal-organic framework nanocrystal for plane effect nonenzymatic electro-catalytic activity of glucose. Nanoscale 2014, 6, 10989–10994. Tang, L.; Lv, J.; Kong, C.; Yang, Z.; Li, J. Facet-dependent nonenzymatic glucose sensing properties of Cu2O cubes and octahedra. New J. Chem. 2016, 40, 6573–6576. McGovern, M. S.; Garnett, E. C.; Rice, C.; Masel, R. I.; Wieckowski, A. Effects of Nafion as a binding agent for unsupported nanoparticle catalysts. J. Power Sources 2003, 115, 35– 39. Yang, C.; Srinivasan, S.; Bocarsly, A. B.; Tulyani, S.; Benziger, J. B. A comparison of physical properties and fuel cell performance of Nafion and zirconium phosphate/Nafion composite membranes. J. Memb. Sci. 2004, 237, 145–161. Lee, S. J.; Mukerjee, S.; McBreen, J.; Rho, Y. W.; Kho, Y. T.; Lee, T. H. Effects of Nafion impregnation on performances of PEMFC electrodes. Electrochim. Acta 1998, 43, 3693– 15 ACS Paragon Plus Environment

Page 16 of 30

Page 17 of 30 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

ACS Catalysis

(35)

(36)

(37) (38)

(39)

(40)

(41) (42)

(43) (44)

(45)

(46) (47) (48)

(49)

3701. Niu, X.; Li, X.; Pan, J.; He, Y.; Qiu, F.; Yan, Y. Recent advances in non-enzymatic electrochemical glucose sensors based on non-precious transition metal materials: opportunities and challenges. RSC Adv. 2016, 6, 84893–84905. Rodrigues, T. S.; da Silva, A. G. M.; Alves, R. S.; de Freitas, I. C.; Oliveira, D. C.; Camargo, P. H. C. Controlling Reduction Kinetics in the Galvanic Replacement Involving Metal Oxides Templates: Elucidating the Formation of Bimetallic Bowls, Rattles, and Dendrites from Cu2O Spheres. Part. Part. Syst. Charact 2017, 1700175. Soon, A.; Todorova, M.; Delley, B.; Stampfl, C. Thermodynamic stability and structure of copper oxide surfaces: A first-principles investigation. Phys. Rev. B 2007, 75, 125420. Hua, Q.; Shang, D.; Zhang, W.; Chen, K.; Chang, S.; Ma, Y.; Jiang, Z.; Yang, J.; Huang, W. Morphological Evolution of Cu2O Nanocrystals in an Acid Solution: Stability of Different Crystal Planes. Langmuir 2011, 27, 665–671. Frost, R. L.; Williams, P. a.; Martens, W.; Leverett, P.; Kloprogge, J. T. Raman spectroscopy of basic copper (II) and some complex copper (II) sulfate minerals : Implications for hydrogen bonding. Am. Mineral. 2004, 89, 1130–1137. Beden, B.; Largeaud, F.; Kokoh, K. B.; Lamy, C. Fourier transform infrared reflectance spectroscopic investigation of the electrocatalytic oxidation of d-glucose: Identification of reactive intermediates and reaction products. Electrochim. Acta 1996, 41, 701–709. Xia, Y.; Gilroy, K. D.; Peng, H.-C.; Xia, X. Seed-Mediated Growth of Colloidal Metal Nanocrystals. Angew. Chemie Int. Ed. 2017, 56, 60–95. da Silva, A. G. M.; Rodrigues, T. S.; Haigh, S. J.; Camargo, P. H. C. Galvanic replacement reaction: recent developments for engineering metal nanostructures towards catalytic applications. Chem. Commun. 2017, 53, 7135–7148. Shang, Y.; Guo, L. Facet-Controlled Synthetic Strategy of Cu2O-Based Crystals for Catalysis and Sensing. Adv. Sci. 2015, 2, 1500140. Zhang, D.-F.; Zhang, H.; Guo, L.; Zheng, K.; Han, X.-D.; Zhang, Z. Delicate control of crystallographic facet-oriented Cu2O nanocrystals and the correlated adsorption ability. J. Mater. Chem. 2009, 19, 5220–5225. Shang, Y.; Sun, D.; Shao, Y.; Zhang, D.; Guo, L.; Yang, S. A Facile Top-Down Etching To Create a Cu2O Jagged Polyhedron Covered with Numerous {110} Edges and {111} Corners with Enhanced Photocatalytic Activity. Chem. – A Eur. J. 2012, 18, 14261–14266. Park, S.; Boo, H.; Chung, T. D. Electrochemical non-enzymatic glucose sensors. Anal. Chim. Acta 2006, 556, 46–57. Wang, G.; He, X.; Wang, L.; Gu, A.; Huang, Y.; Fang, B.; Geng, B.; Zhang, X. Non-enzymatic electrochemical sensing of glucose. Microchim. Acta 2013, 180, 161–186. Ganduglia-Pirovano, M. V.; Hofmann, A.; Sauer, J. Oxygen vacancies in transition metal and rare earth oxides: Current state of understanding and remaining challenges. Surf. Sci. Rep. 2007, 62, 219–270. da Silva, A. G. M.; Rodrigues, T. S.; Slater, T. J. A.; Lewis, E. A.; Alves, R. S.; Fajardo, H. V; Balzer, R.; da Silva, A. H. M.; de Freitas, I. C.; Oliveira, D. C.; et al. Controlling Size, Morphology, and Surface Composition of AgAu Nanodendrites in 15 s for Improved Environmental Catalysis under Low Metal Loadings. ACS Appl. Mater. Interfaces 2015, 7, 25624–25632. 16 ACS Paragon Plus Environment

ACS Catalysis 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

(50)

(51)

da Silva, A. G. M.; Kisukuri, C. M.; Rodrigues, T. S.; Candido, E. G.; de Freitas, I. C.; da Silva, A. H. M.; Assaf, J. M.; Oliveira, D. C.; Andrade, L. H.; Camargo, P. H. C. MnO2 nanowires decorated with Au ultrasmall nanoparticles for the green oxidation of silanes and hydrogen production under ultralow loadings. Appl. Catal. B Environ. 2016, 184, 35–43. Yumitori, S. Correlation of C1s chemical state intensities with the O1s intensity in the XPS analysis of anodically oxidized glass-like carbon samples. J. Mater. Sci. 2000, 35, 139–146.


Page 18 of 30

Page 19 of 30 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

ACS Catalysis

Figure 1. (A-B) Calculated potential energy profiles for the interaction of glucose with the surface of Cu2O cubes (A, {100} surface facets) and octahedrons (B, {111} surface facets). Oxygen atoms are in red, and copper atoms are in brown.

Figure 2. SEM (A-C) and HRTEM (D-I) images of Cu2O cubes (A, D, and G), cuboctahedrons (B, E, and H), and octahedrons (C, F, and I).


ACS Catalysis 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

Figure 3. (A) j/E potentiodynamic profiles recorded at 0.01 Vs-1 in 0.1 molL-1 NaOH, (B) amperometric responses as a function of time (Eapp = 0.5 V), and (C) analytical curves (current as a function of the concentration of glucose) for Cu2O cubes, cuboctahedrons, and octahedrons employed as electrocatalytic sensors. (D) Chronoamperometric curves as a function of time for sensing the selectivity of Cu2O crystals in the presence of ascorbic and uric acids.


Page 20 of 30

Page 21 of 30 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

ACS Catalysis

Figure 4. Activity and selectivity for the electrocatalytic detection of glucose using freshly prepared Cu2O cubes and octahedrons relative to the same samples after they had been stored several days in aqueous suspensions.


ACS Catalysis 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

Figure 5. (A-F and H-M) HRTEM images of the morphological evolution as a function of time for Cu2O cubes (A-F) and octahedrons (H-M) after they had been stored in aqueous suspensions: (A and H) 1st day, (B and I) 3rd day, (C and J) 7th day, and (D and K) 14th day. (E and F) The individual branches formed at the Cu2O cube surface were single crystalline with lattice fringes corresponding to the {111} spacing of CuO. (L and M) The individual particles formed at the Cu2O octahedron surface (indicated by dashed squares in K) corresponded to the formation of CuO NPs (approximately 2-4 nm). (G and N) The calculated potential energy profile for the interaction of O2 molecule with the surface of Cu2O cubes (G, {100} surface facets) and octahedrons (N, {111} surface facets). 21 ACS Paragon Plus Environment

Page 22 of 30

Page 23 of 30 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

ACS Catalysis

Figure 6. (A) Analytical curves recorded in 0.1 molL-1 NaOH (Eapp = 0.5 V) and (B) chronoamperometric curves in the presence of interferents for the electrocatalytic detection of glucose using freshly prepared Cu2O cubes relative to the same sample after they had been stored for 14 days under vacuum.


ACS Catalysis 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

Graphical Abstract


Page 24 of 30

Page 25 of 30

ACS Catalysis

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


ACS Catalysis 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


Page 26 of 30

Page 27 of 30 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

ACS Catalysis


ACS Catalysis 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


Page 28 of 30

Page 29 of 30 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

ACS Catalysis


ACS Catalysis 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


Page 30 of 30

Why Could the Nature of Surface Facets Lead to Differences in the

Recommend Documents