Computational Method for Efficient Screening of Metal Precursors for

Feb 18, 2009 - Nanotechnology Research Institute, National Institute of Advanced Industrial Science and Technology (AIST), 807-1, Shuku-machi, Tosu, S...
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Ind. Eng. Chem. Res. 2009, 48, 3389–3397

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MATERIALS AND INTERFACES Computational Method for Efficient Screening of Metal Precursors for Nanomaterial Syntheses Yuuichi Orimoto,† Ayumi Toyota,† Takeshi Furuya,‡ Hiroyuki Nakamura,† Masato Uehara,† Kenichi Yamashita,† and Hideaki Maeda*,†,§,# Nanotechnology Research Institute, National Institute of AdVanced Industrial Science and Technology (AIST), 807-1, Shuku-machi, Tosu, Saga 841-0052, Japan; Nanotechnology Research Institute, National Institute of AdVanced Industrial Science and Technology (AIST), 1-1-1, Higashi, Tsukuba, Ibaraki 305-8565, Japan; Department of Molecular and Material Sciences, Interdisciplinary Graduate School of Engineering Sciences, Kyushu UniVersity, 6-1, Kasuga-Kouen, Kasuga, Fukuoka 816-8580, Japan; and Japan Science and Technology Agency (JST), CREST, 4-1-8 Hon-chou, Kawaguchi, Saitama, 332-0012, Japan

A density functional theory (DFT) based method is proposed for efficient screening of metal precursors for nanomaterial syntheses. For this study, we examined the effectiveness of our DFT approach for predicting bulk properties of precursor metal complexes, which is a key of our method. The DFT calculations were applied for a series of copper(II) β-diketonate complexes to estimate values related to complex stabilities reduction such as complex formation energies ∆E complex , total energy changes for two-electron reduction ∆E total , total complex and so on. The value of ∆E total was compared to the stability constant β2 collected from the relevant literature; ∆E reduction was compared with reduction potentials measured using cyclic voltammetry. Results total obtained from these comparisons revealed that simple DFT calculations predicted the trend of the complex stabilities that were determined experimentally as a bulk property. Our method can predict precursor properties and can greatly contribute to efficient precursor selection for nanomaterial synthesis. 1. Introduction Recently, nanoscale materials such as nanoparticles and thin films have increasingly attracted interest because of their technological potential; they have been investigated actively by many research groups,1-5 including our group.6-11 However, the control of nanomaterial synthesis is difficult and complicated because the synthesis is affected strongly by various factors such as metal precursors, solvents, and experimental conditions. A particularly important issue for obtaining preferable products in such syntheses is the selection (or design) of metal precursors because the stability of precursors is deeply related to nucleation timing in the material synthesis process; the selection strongly affects the final products. Therefore, the screening of metal precursors based on their stabilities is an important first step for controlling nanomaterial syntheses. Metal complexes have been used extensively as metal sources for the material syntheses.6-14 Many experimental and theoretical approaches to the selection (or design) of precursor metal complexes have been demonstrated.15-23 The decomposition of precursor complexes is considered an important reaction determining the quality of products in the material syntheses. Therefore, the understanding of the complex stability is expected to be important for selection of suitable precursors. The use of stability constants is useful for that purpose because numerous quantities of the constants have already been determined experimentally and reported in the literature and databases. However, such information does not cover all metal-ligand * To whom correspondence should be addressed. Tel.: +81-94281-3676. Fax: +81-942-81-3657. E-mail: [email protected]. † AIST, Kyushu. ‡ AIST, Tsukuba. § Kyushu University. # JST, CREST.

combinations and experimental conditions. That lack of data often complicates precursor selection. On the other hand, it is not practical to conduct new experiments for examining the stability constants before material syntheses because it is costly and time-consuming. An alternative means to determine the complex stability is a theoretical approach based on quantum chemical calculations. In particular, density functional theory (DFT) calculations have been widely used to calculate the electronic structures of metal complexes20-22,24-31 because the DFT method makes it possible to include electron correlation effects in the calculations with practical computational costs. For example, the metal-ligand bond energy of copper complexes was estimated using DFT calculations, and the dissociation reaction of the complex was discussed in relation to the chemical vapor deposition (CVD) of copper.24 More recently, DFT calculations were applied to precursor selection for atomic layer deposition (ALD) and CVD; the DFT results for a series of complexes were compared to results of film growth experiments.21 Furthermore, the redox properties of complexes have been well analyzed using DFT calculations.25,26,28-31 For those reasons, the DFT method is considered to be an effective approach for predicting complex stabilities for precursor selections. Although the DFT-based approach has been developed as described above, the precursor selection method has been insufficiently established. For material syntheses, the precursor selection method is expected to be efficient and can predict the essence of bulk properties. Our main goal is to establish a DFTbased method for efficient screening of precursor complexes for nanomaterial synthesis. A simple and general method is desirable for increased efficiency. Our method’s concept is presented in Figure 1: the screening of precursors is achieved using a rough precursor selection, with subsequent detailed

10.1021/ie800903h CCC: $40.75  2009 American Chemical Society Published on Web 02/18/2009

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The key of our concept is the effectiveness of DFT calculations for predicting the bulk properties of precursor complexes. Therefore, for the present study, we specifically examined the validity of DFT-based prediction of complex stabilities as the first step of our precursor selection method. In the present article, the DFT calculations are performed to estimate the stabilities of a series of Cu(II) β-diketonate complexes to compare them with complex stabilities which are determined experimentally as a bulk property. The Cu(II) β-diketonate complex is a suitable subject for our purpose because the complex has been widely used as a metal precursor in material syntheses and its properties are well studied.36-41 In the Results and Discussion section of this article, complex formation energies by DFT calculations are compared with stability constants obtained from the relevant literature. Indeed, both the energy change for an electron reduction and the energy level of lowest unoccupied molecular orbital (LUMO) are computed. They are compared with the electrochemically determined reduction potentials. Finally, our approach for prediction of complex stabilities will be discussed in relation to its effectiveness toward the efficient screening of precursors for nanomaterial syntheses. 2. Compounds

Figure 1. Flowchart showing the concept of computational screening of metal precursors for nanomaterial syntheses.

precursor selection. In the rough selection, we select a target complex, A, based on experimental data such as stability constants. Introduction of DFT calculations to this step is not easy because comparison of different types of complexes involves consideration of chelate effects, which have many complicated factors.32-35 In the detailed selection, DFT calculations are conducted to estimate the stability of the target complex, A, and complexes similar to A, i.e., A1, A2, etc. The design of complexes with different stabilities is achieved by substituent effects for ligands. For example, the electronic tuning of copper complexes using ligand fluorinations has been reported.25 The precursor stability table obtained in this step is used for selecting candidate precursors in nanomaterial syntheses.

Figure 2a portrays the structure of a Cu(II) β-diketonate complex: two β-diketonate ligands are coordinated to a copper atom, leading to two six-membered chelate rings. In the figure, R1 and R2 represent substituent groups in the ligands. Geometrical parameters B1, B2, and B3 respectively signify Cu-O, O-C, and C-C bond lengths in the chelate ring. Furthermore, B1′-B3′ are prepared in the case of R1 * R2. Parameter A is defined as the bond angle ∠O-Cu-O. Figure 2b shows a series of Cu(II) β-diketonate complexes studied in this paper: Cu(II) bis(2,4-pentanedionate), 1; Cu(II) bis(2,2,6,6-tetramethyl-3,5-heptanedionate), 2; Cu(II) bis(1,1,1trifluoro-2,4-pentanedionate), 3; Cu(II) bis(1,1,1-trifluoro-5,5dimethyl-2,4-hexanedionate), 4; Cu(II) bis(6,6,7,7,8,8,8-heptafluoro-2,2-dimethyl-3,5-octanedionate), 5; and Cu(II) bis (1,1,1,5,5,5-hexafluoro-2,4-pentanedionate), 6. For convenience, we also use a common name, Cu(II) acetylacetonate ()acac) for 1. Complexes 1-6 comprise only four substituent groups: methyl, -CH3; tert-butyl, -C(CH3)3; trifluoromethyl, -CF3; and

Figure 2. (a) Structure of copper(II) β-diketonate complex; (b) optimized structures (uB3LYP/BS1) for a series of Cu(II) β-diketonate complexes 1-6. R1 and R2 are substituent groups of β-diketonate ligands. B1, B2, and B3 respectively denote the Cu-O, O-C, and C-C bond lengths in the chelate ring. In addition, B1′-B3′ are prepared for the case of R1 * R2. Parameter A is the bond angle for O-Cu-O. The basis set, BS1, is described in the text.

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Figure 3. Free energy cycle for the decomposition of copper(II) acetylacetonate ()acac) 1. “REAC” denotes a “reaction” step in the cycle. The electrochemical-chemical (EC) reaction path is composed of REAC-1 and REAC-2, whereas the chemical-electrochemical (CE) reaction path is REAC-3 and REAC-4. REAC-1 and REAC-4 correspond to two-electron reductions; REAC-2 and REAC-3 are complex decompositions without electron reductions.

1,1,2,2,3,3,3-heptafluoropropyl, -(CF2)2CF3 groups. Complexes 1, 2, and 6 have the same substituent group (R1 ) R2), whereas 3-5 have different groups (R1 * R2). All the neutral complexes in Figure 2b are treated as open-shell systems with an odd number of electrons. 3. Methods 3.1. General Considerations. Figure 3 shows a Gibbs free energy cycle for a decomposition reaction of complex 1 including electron reduction, providing a neutral copper atom (Cu0) and two acetylacetonate ions (acac-). The REAC notation in the figure represents a reaction step involved in the energy cycle. In this work, the standard Gibbs free energy change, ∆G0, is considered for simplicity. An electron-reduction-induced decomposition, i.e., the sequential electrochemical-chemical (EC) reaction, has been proposed for 1.42,43 The EC reaction corresponds to the REAC-1 f REAC-2 path: REAC-1 is a twoelectron (2e) reduction of neutral complex 1; REAC-2 is the decomposition of negatively charged complex [Cu(acac)2]2-. We can also consider the chemical-electrochemical (CE) reaction corresponding to the REAC-3 f REAC-4 path. The path includes the decomposition of 1 with no electron reduction (REAC-3), followed by the 2e reduction of Cu2+ (REAC-4). In this work, we specifically addressed both the EC and CE reactions to investigate the stability of complexes comprehensively. In the present article, we omitted a one-electron (1e) reduction process for simplicity. The 1e process cannot be ignored for obtaining a more detailed description of the complex decomposition. However, the consideration of 2e process is sufficient for obtaining the feature of the complex decomposition and complex stabilities. Thus, we considered only the 2e process as the first step toward a simple and efficient precursor selection method. It should be noted that the LUMO level computed in section 4.4 is related to the 1e-reduction process. The standard Gibbs free energy change at the constant temperature T, ∆G0 ()∆H0 - T∆S0), can be described for each reaction step of the energy cycle as + ∆H0,others - T∆S01 ∆G01 ) ∆H0,reduction 1 1 ∆G02 ) -∆H0,complex + ∆H0,others - T∆S02 2 2 ∆G03 ) -∆H0,complex + ∆H0,others - T∆S03 3 3 ∆G04 ) ∆H0,reduction + ∆H0,others - T∆S04 4 4

(1)

where the subscript of each energy term denotes the number of the corresponding reaction step. In addition, ∆H0 and ∆S0 respectively denote the standard enthalpy and entropy changes. The ∆H0, complex and ∆H0, reduction respectively signify the standard enthalpy changes for a complex formation and 2e reduction. The complex decomposition is the inverse reaction of the

complex formation. Therefore, the enthalpy changes for REAC-2 and REAC-3 are expressed as -∆H0, complex. The ∆H0,others term includes the standard enthalpy changes for the solvation, dissolution, geometrical relaxations, and so on accompanying the reaction. We consider a comparison of the free energy changes among a series of Cu(II) β-diketonate complexes 1-6. These complexes have similar structures. For that reason, it can be assumed that the ∆H0,others term for each reaction step in eq 1 has a similar value within the comparison among the complexes. Moreover, the -T∆S0 term is expected to be similar among the complexes. Based on that assumption, in each reaction step of eq 1, the last two terms can be treated as a common constant value for all complexes. Therefore, the free energy changes for the EC (∆G0,EC) and CE (∆G0,CE) reaction paths are written as - ∆H0,complex + CEC ∆G0,EC ) ∆G01 + ∆G02 ≡ ∆H0,reduction 1 2 ∆G0,CE ) ∆G03 + ∆G04 ≡ -∆H0,complex + ∆H0,reduction + CCE 3 4

(2)

respectively. The CEC and CCE are constant values independent + ∆H0,others of a species of the complexes, where CEC ) ∆H0,others 1 2 0 0 0,others 0,others CE - T(∆S1 + ∆S2) and C ) ∆H3 + ∆H4 - T(∆S30 + ∆S40). For this study, the ∆H0, complex and ∆H0, reduction are estimated approximately using DFT calculations with the total energy change (∆E total) for an isolated molecule with no environment. Here, the total energy, E total, of a molecule is expressed as the sum of a self-consistent field (SCF) electronic energy and nuclear repulsion energy. Consequently, eq 2 can be rewritten as EC′ - ∆Ecomplex ∆G0,EC ≡ ∆Ereduction total,1 total,2 + C reduction ∆G0,CE ≡ -∆Ecomplex + CCE′ total,3 + ∆Etotal,4 EC′

(3)

CE′

where new constants C (C ) include thermal correction, etc., in addition to the CEC (CCE). Because the free energy changes for the EC and CE paths are expected to be equivalent in the energy cycle, i.e., ∆G0,EC ) ∆G0,CE, we can obtain the following equation from eq 3: complex reduction + C (4) - ∆Ecomplex ∆Ereduction total,2 ) -∆Etotal,3 + ∆Etotal,4 total,1

where constant C ()CCE′ - CEC′) is introduced. Equation 4 shows the relationship connecting the energy changes in the EC path and those in the CE path. 3.2. Computational Details. The DFT calculations were applied to obtain the electronic structures of Cu(II) β-diketonate complexes 1-6. These neutral complexes were calculated as open-shell systems using an unrestricted scheme of Becke’s three-parameter hybrid functional with the correlation functional of Lee, Yang, and Parr (uB3LYP).44-46 The spin-multiplicity “2”(doublet state) was chosen in these calculations. Regarding spin contamination, the 〈S2〉 values are within the range of 0.752-0.753 for all neutral complexes described in this work. To examine a basis set size dependency of the DFT results, the following four basis sets, BS1-BS4, were used. (a) BS1: The LanL2DZ basis set is used for all atoms treated in this work: Cu, H, C, O, and F atoms. In the basis set, the Los Alamos effective core potential plus DZ47-49 is adopted for the Cu atom, whereas the Dunning/Huzinaga valence double-ζ D95V50,51 is used for the H, C, O, and F atoms. (b) BS2: The LanL2DZ is used for the Cu atom, whereas the 6-31+G(d) basis set is adopted for the H, C, O, and F atoms. The 6-31+G(d) is a Pople-type double split-valence basis set including polarization and diffuse functions for the C, O, and F atoms.

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(c) BS3: The LanL2DZ is used for the Cu atom, whereas the 6-31++G(d,p) basis set is adopted for the H, C, O, and F atoms. In the 6-31++G(d,p) basis set, polarization and diffuse functions are added to the H atom in addition to the 6-31+G(d) basis set. (d) BS4: The LanL2DZ is used for the Cu atom, whereas the 6-311++G(d,p) basis set is adopted for the H, C, O, and F atoms. The 6-311++G(d,p) is a triple split-valence basis set including polarization and diffuse functions for H, C, O, and F atoms. It is noteworthy that the inclusion of Pople-type functions, i.e., 6-31+G(d), 6-31++G(d,p), and 6-311++G(d,p), drastically increases the computational cost because of the increment of the number of basis functions. For instance, the quantities of basis functions for complex 1 are 176, 302, 358, and 428 for BS1-BS4, respectively. The geometries of complexes 1-6 were fully optimized at the level of uB3LYP/BS1 without symmetry constraints. The uB3LYP/BS2 level of theory was also applied to geometry optimizations to examine the validity of uB3LYP/BS1 optimized geometries. In these calculations, fluoroalkyl chains in 5 are assumed to have a trans-zigzag conformation. Vibration frequency analyses were applied to confirm that each optimized structure has an energy potential minimum and no imaginary number frequency. in eqs 3 and 4 is defined as the total energy The ∆E complex total complex complex and ∆Etotal,3 change for the complex formation. The ∆Etotal,2 were respectively estimated as 20 ∆Ecomplex total,2 ) Etotal{[Cu(acac)2] } - Etotal{Cu } -

2Etotal{acac-} + BSSE2 2+ ∆Ecomplex total,3 ) Etotal{Cu(acac)2} - Etotal{Cu } 2Etotal{acac-} + BSSE3

(5)

where the notation E total{X} signifies the total energy of a component X. Furthermore, BSSE2 and BSSE3 respectively denote correction energies for the basis set superposition error (BSSE) in the REAC-2 and REAC-3. The BSSE was corrected using the counterpoise method.52,53 The ∆E reduction in eqs 3 and 4 is defined as the total energy total reduction is calculated change for the 2e-reduction reaction. The ∆Etotal,1 as ) Etotal{[Cu(acac)2]2-} - Etotal{Cu(acac)2} (6) ∆Ereduction total,1 The contribution of two electrons (2e-) to the energy change is ignored in eq 6 because the contribution is common among comparisons of complexes. In calculations of eqs 5 and 6, geometry relaxation effects accompanying the reactions were not considered to simplify our screening method. That is, the total energies of β-diketonate ligands in eq 5 were calculated by fixing its structure in the complex. Furthermore, the total energy of [Cu(acac)2]2- in eqs 5 and 6 was calculated based on the Cu(acac)2 optimized geometries; a doublet state was chosen for the spin multiplicity of [Cu(acac)2]2-. Furthermore, solvent effects were not included in these calculations. The inclusion of the solvent effects is necessary for more accurate predictions of the complex stabilities. However, a simple and efficient method without consideration of the effects is desirable for our purposes. and ∆E reduction are performed using Estimations of ∆E complex total total the four basis sets, uB3LYP/BS1-BS4, based on the uB3LYP/ BS1 or uB3LYP/BS2 optimized geometry. The notation “uB3LYP/BS4//uB3LYP/BS1” means that the geometry optimization is conducted at the level of uB3LYP/BS1; the electronic structure is calculated at the uB3LYP/BS4 level based

Table 1. Bond Lengthsa (in Å) and Bond Anglesa (in deg) in Complexes 1-6: (a) uB3LYP/BS1, (b) uB3LYP/BS2 Optimizations,b and (c) Experiments B1 (B1′)c

complex

B2 (B2′)c

B3 (B3′)c

A

(a) Calculations, uB3LYP/BS1b 1 2 3 4 5 6

1.949 1.942 1.946 (1.949) 1.944 (1.944) 1.944 (1.942) 1.948

1.308 1.310 1.301 (1.301) 1.302 (1.302) 1.301 (1.304) 1.293

1.414 1.414 1.395 (1.426) 1.394 (1.428) 1.429 (1.392) 1.405

90.7 90.2 90.3 90.1 90.0 89.7

(b) Calculations, uB3LYP/BS2b 1 2 3 4 5 6

1.954 1.948 1.953 (1.952) 1.952 (1.949) 1.948 (1.951) 1.953

1.277 1.278 1.271 (1.272) 1.272 (1.273) 1.272 (1.272) 1.265

1.407 1.408 1.391 (1.417) 1.391 (1.418) 1.419 (1.390) 1.400

92.0 91.3 91.7 91.4 91.4 91.4

(c) Experiments complex (ref) d

1 (57) 1 (58)e 2 (59)e 6 (60)e

B1

B2

B3

A

1.914, 1.912 1.914 1.916 1.919

1.264, 1.281 1.273 1.284 1.276

1.371, 1.400 1.402 1.399 1.392

93.2 92.3 93.7 90.6

a Geometrical parameters are assigned in Figure 2a. b Basis sets BS1 and BS2 are described in the text. c Parameters B1′-B3′ are omitted for complexes 1, 2, and 6, including the same substituent group (R1 ) R2). d X-ray crystal structure analysis. The table shows two nonequivalent bond lengths observed in the crystal. e Gas-phase electron diffraction.

on the uB3LYP/BS1 optimized geometry. On the other hand, the notation uB3LYP/BS2 means that both the electronic structure and geometry optimization calculations are performed at the same uB3LYP/BS2 level of theory. All calculations were performed using the Gaussian03 program package.54 The illustration in Figure 2b was created using software (GaussView, version 3.09; Gaussian Inc.).55 3.3. Collection of Stability Constants. The collection of stability constants β2 ()K1K2) for the copper(II) β-diketonate complexes was conducted using the IUPAC Stability Constants Database (SC-Database),56 where K1 and K2 represent the stepwise formation constants. For complexes 1-6, we could not collect stability constants under the specified experimental condition and method of measurement because of the lack of data. Therefore, we picked up data under conditions that the experiment was performed at around room temperature, 20-30 °C. Here, other experimental conditions such as ionic strength and solvents were not considered in the collection. The collected stability constants are listed in Table 2. 3.4. Cyclic Voltammetry Measurement. Copper(II) β-diketonate complexes 1, 2, 5, and 6 were characterized electrochemically using cyclic voltammetry (CV) measurements. These complexes were provided by Aldrich Chemical Co. Inc. and were used without further purification. A 2 mM copper complex of acetonitrile solution was prepared with 0.1 M tetrabutylammonium hexafluorophosphate, with Bu4N+PF6- as a supporting electrolyte. The supporting electrolyte was provided by Tokyo Chemical Industry Co. Ltd. For the CV measurements, we used a three-electrode system and a measuring device (ALS Electrochemical Analyzer Model 630C; BAS Inc.). The threeelectrode system consists of an electrochemical cell, a glassy carbon working electrode (surface area 0.0707 cm2), a Ag/Ag+ reference electrode, and a platinum wire counter electrode. The reference electrode includes an acetonitrile solution with 0.1 M tetrabutylammonium perchlorate: Bu4N+ClO4-.

Ind. Eng. Chem. Res., Vol. 48, No. 7, 2009 3393 Table 2. Stability Constants β2 as a Logarithm for Complexes 1-4 and 6a complex

log β2

ref

complex

log β2

ref

1

19.27 18.86 19.93 18.22 19.46 14.82 14.99 14.28 14.76 15.24 24.02 17.43 17.68 15.16 22.59

61 61 61 61 62 63 64 65 66 67 68 69 70 71 72

2

22.79 26.42

62 73

3

9.38 17.2 12.2

65 72 74

4

18.08

73

6

3.84

65

a Data were collected under conditions that the experiment was conducted at around room temperature, 20-30 °C.

The CV measurement was carried out at room temperature under Ar atmosphere. The scan speed 0.1 V · s-1 was chosen to determine the cathodic peak potential, Ecp, of the complexes. For this study, Ecp was defined as a cathodic peak with the largest intensity because the peak is expected to be related with reduction . On the 2e-reduction potential corresponding to the ∆Etotal,1 -1 other hand, the 0.001 V · s scan rate was used for determining the cathodic starting potential, Ecs, which corresponds to the potential from which an electron reduction starts. 4. Results and Discussion 4.1. Geometrical Features. As a first step for examining the reliability of our DFT-based calculations, the geometry of complexes predicted by DFT calculations was compared with experimental data. Table 1a,b lists the geometrical parameters of both the uB3LYP/BS1- and uB3LYP/BS2-optimized structures for complexes 1-6; the uB3LYP/BS1-optimized structures are depicted in Figure 2b. In all the complexes, the Cu and O atoms form a square planar structure. As the table shows, all the geometrical parameters are nearly equivalent, irrespective of the calculation level. The order of the O-C length (B2) was found to be 2 ≈ 1 > 4 ≈ 5 ≈ 3 > 6. The order has a connection to the magnitude of fluorinations to the substituent groups; the fluorinations are expected to accelerate the electron withdrawing from the other part of the complex. Table 1c lists the geometries of 1, 2, and 6 obtained through experimentation.57-60 It was found that our DFT results well agreed with the structures determined by X-ray diffraction57 and gas-phase electron diffraction.58-60 It was concluded from these results that the use of small basis set “BS1” is sufficient to predict the structures of the complexes. 4.2. Complex Formation Energy (Calculations) vs Stability Constants (Experiments). We investigated the relationship complex between the calculated complex formation energies ∆Etotal,3 and stability constants β2 for a series of Cu(II) β-diketonate complexes to confirm the validity of our computational prediccomplex values were calculated for complexes 1-6 tion. The ∆Etotal,3 using various levels of theory (see Figure 4a). The uB3LYP/ complex is 6 > 5 ≈ 3 ≈ 4 BS1 results show that the order of ∆Etotal,3 > 2 ≈ 1. Negative values in the graph correspond to energetic stabilizations attributable to the complex formation. Therefore, the order of the complex stability is 1 ≈ 2 > 4 ≈ 3 ≈ 5 > 6. This result exhibits the fluorination effects on the complex stability: complexes 1 and 2 with no fluorine atom show a larger

stabilization for the complexation than the other complexes. The complex stabilizations of 3-5 with fluorine atoms in a substituent group were smaller than those of 1 and 2. The smallest stabilization was found in 6, including fluorine atoms in both the substituent groups. It was concluded that the complex complex values is controlled by stabilization estimated using ∆Etotal,3 the magnitude of the fluorinations to the substituent groups. In addition, the results of 5 showed that the fluorination to the complex atoms far from the chelate rings does not affect the ∆Etotal,3 value. In contrast, the increment of complex stabilization attributable to the tert-butyl groups with electron-releasing properties was not clearly observed for 2, 4, and 5 in our calculations. To elucidate the basis set size effects, the uB3LYP/BS1 results were compared with the results obtained using larger basis sets: uB3LYP/BS2//uB3LYP/BS1, uB3LYP/BS3//uB3LYP/ BS1, uB3LYP/BS4//uB3LYP/BS1, uB3LYP/BS2, uB3LYP/ BS3//uB3LYP/BS2, and uB3LYP/BS4//uB3LYP/BS2 (see Figure 4a). All the results show a similar tendency of the complex complex formation energy, although the absolute magnitude of ∆Etotal,3 in the uB3LYP/BS1 results is slightly larger than that in other results, except for 6. Results showed that the trends of the complex ∆Etotal,3 converged with the rise of calculation level. Moreover, the use of the uB3LYP/BS2-optimized geometry does not complex change the conclusion on the trend of ∆Etotal,3 . It can be concluded that the uB3LYP/BS1 level calculation with low cost is sufficient to predict the complex formation energy. Table 2 presents stability constants β2 for complexes 1-4 and 6 as a logarithm collected from the relevant literature.61-74 To the best of our knowledge, the β2 value of 5 has not been found. The β2 values in Table 2 are also depicted in Figure 4b. The dispersion of the log β2 values is not small in each complex because data were measured under various experimental conditions. However, the approximate order of the log β2 values is obtainable as 2 > 1 > 4 > 3 > 6. complex By comparing the trend of ∆Etotal,3 (Figure 4a) with log β2 complex (Figure 4b), it was found that the ∆Etotal,3 well predicts the trend of stability constants; the only exception is the fact that the increment of complex stabilizations caused by the tert-butyl complex groups was not readily apparent in the ∆Etotal,3 results. 4.3. Energy Change for 2e Reduction (Calculations) vs Reduction Potential (Experiments). To examine the effectiveness of our calculations for predicting the complex stability for the electron reductions, the total energy change for 2e reduction reduction was investigated for a series of Cu(II) β-diketonate ∆Etotal,1 reduction complexes. For that purpose, the trend of ∆Etotal,1 is compared with the reduction potentials that were determined electrochemically using the CV measurements. The reduction potential (E) for a reversible reaction is expressed as E ) E0 + (RT/nF) ln(aOx/aRed) using the standard reduction potential (E0), where R, T, n, and F respectively represent the universal gas constant, temperature, the number of electrons transferred, and the Faraday constant. The aOx and aRed respectively indicate the activities of oxidative and reductive species. Regarding the comparison among the Cu(II) β-diketonate complexes, the difficulties exist because of the variety of the mechanism of electrochemical reactions, the reaction reversibility, the deviation from standard state, and so on. To simplify comparisons among the complexes examined in this work, the reduction potential E via CV measurements is compared directly with the total energy change for the 2e reduction reduction ∆Etotal,1 , which comes from ∆G10 related to the standard reduction potential E0.

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complex Figure 4. (a) Complex formation energy ∆Etotal,3 (in hartrees) for complexes 1-6, as estimated by various levels of DFT calculations, and (b) stability constants β2 as a logarithm for complexes 1-4 and 6. The notation of the calculation levels in panel a is described in the text. The stability constants are referred from the relevant literature. The log β2 values for the plots are listed in Table 2.

Figure 5. (a) Correlation between a cathodic peak potential Ecp (in volts vs Ag/Ag+, 0.1 V · s-1 scan rate) and total energy change for two-electron reduction reduction ∆Etotal,1 , and (b) correlation between a cathodic starting potential Ecs (in volts vs Ag/Ag+, 0.001 V · s-1 scan rate) and β-LUMO energy for complexes 1, 2, 5, and 6. Both uB3LYP/BS1 (closed circles) and uB3LYP/BS4//uB3LYP/BS1 (open squares) results are shown. The notation of calculation levels is described in the text. Solid and broken supporting lines are used, respectively, to denote uB3LYP/BS1 and uB3LYP/BS4//uB3LYP/BS1 results. reduction The total energy change for 2e reduction ∆Etotal,1 was estimated for complexes 1, 2, 5, and 6 at the levels of uB3LYP/ BS1 and uB3LYP/BS4//uB3LYP/BS1 (see Figure 5a). The reduction is 1 ≈ 2 > 5 > 6 in figure shows that the order of ∆Etotal,1 both levels of theory. The order corresponds to the relative complex stability for the electron reductions. On the other hand, the cathodic peak potential Ecp, having the largest peak intensity, was determined by the CV measurement (scan speed V ) 0.1 V · s-1) as -1.34, -1.35, -0.98, and -0.91 V (vs Ag/Ag+) for 1, 2, 5, and 6, respectively. Figure 5a also shows the Ecp results. The electron affinity of the complex becomes larger with increasing Ecp. In other words, the complex stability for the electron reductions becomes larger with the decrease of the Ecp value. Therefore, the order of the complex stability for the 2e reduction was obtained from the Ecp results as 2 ≈ 1 > 5 > 6. reduction and Ecp results Furthermore, the trend of both the ∆Etotal,1 shows fluorination effects. Figure 5a portrays the relationship reduction and Ecp. An approximately linear between the ∆Etotal,1 relationship between them was found in both calculation levels reduction . In the graph, the difference of the calculation for ∆Etotal,1 level engenders the difference in the incline of the supporting reduction and Ecp line. However, only the linearity between the ∆Etotal,1 is important here to know the trend of the complex stability for electron reduction from the computational predictions. 4.4. LUMO Energy (Calculations) vs Reduction Potential (Experiments). Because the complex stability for the electron reduction is also related to the energy level of the lowest unoccupied molecular orbital (LUMO), the LUMO levels of the Cu(II) β-diketonate complexes were compared with the trend of reduction potentials obtained from CV measurements.

We calculated the LUMO energy of complexes 1, 2, 5, and 6 at the levels of uB3LYP/BS1 and uB3LYP/BS4//uB3LYP/ BS1 (see Figure 5b). Here, LUMO indicates β-LUMO because R-spin and β-spin molecular orbitals are treated differently in the spin-unrestricted scheme of the DFT calculations. It was confirmed from the DFT results that β-LUMO energy is always lower than the corresponding R-LUMO energy in all the complexes. The order of the LUMO energy level is 2 ≈ 1 > 5 > 6 in both the calculation levels. The LUMO order corresponds to the complex stability for a one-electron (1e) reduction because the β-LUMO level can be occupied by only one electron. The cathodic starting potential Ecs was determined by the CV measurement using the scan speed of V ) 0.001 V · s-1 (see Figure 5b). It is considered that the LUMO energy level has a connection to Ecs rather than Ecp because the β-LUMO energy is expected to connect with the initial 1e process of the 2ereduction reaction. The Ecs was determined as -0.79, -0.82, -0.75, and -0.65 V (vs Ag/Ag+), respectively, for 1, 2, 5, and 6. Therefore, the order of the complex stability for the 1e-reduction process was 2 > 1 > 5 > 6. This order resembles that of Ecp except for the fact that the electron-releasing effects of tert-butyl groups were observed clearly in the Ecs results. Figure 5b shows a good linear relationship between the LUMO energy and Ecs for both calculation levels. 4.5. Complex Formation Energy (Calculations) vs Energy Change for 2e Reduction (Calculations). In this subsection, complex the relationship between the complex formation energy ∆Etotal,3 reduction and the energy change for 2e reduction ∆Etotal,1 is considered based on eq 4. For that purpose, first, we compared the energy reduction complex terms of the EC path in eq 4, i.e., the ∆Etotal,1 and -∆Etotal,2

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Figure 6. (a) Total energy change for each reaction step in the EC path as a relative value to that of complex 1 (uB3LYP/BS1), and (b) correlation between the total energy change for REAC-1 and that for REAC-3 for complexes 1-6 (uB3LYP/BS1). Herein, REAC-1, REAC-2, REAC-1 + REAC-2, and REAC-3 reduction complex reduction complex complex respectively correspond to the ∆Etotal,1 , -∆Etotal,2 , {∆Etotal,1 - ∆Etotal,2 }, and -∆Etotal,3 . The basis set, BS1, is described in the text.

terms. These energy terms for complexes 1-6 are depicted in Figure 6a as a value relative to complex 1 (uB3LYP/BS1). In the graph, REAC-1, REAC-2, and REAC-1+REAC-2 respecreduction complex , -∆Etotal,2 , tively represent the relative values of the ∆Etotal,1 reduction complex and {∆Etotal,1 - ∆Etotal,2 }. Results showed that the trend of reduction complex - ∆Etotal,2 } values (REAC-1 + REAC-2) among the {∆Etotal,1 reduction term (REAC-1) the complexes was controlled by the ∆Etotal,1 complex rather than by the -∆Etotal,2 term (REAC-2): the trend of the reduction term is more dominative in the EC path as far as a ∆Etotal,1 comparison of relative energy changes among the complexes. Next, we consider the energy terms of the CE path in eq 4, complex reduction reduction and ∆Etotal,4 terms. The ∆Etotal,4 term is i.e., the -∆Etotal,3 expected to be the same value irrespective of the species of complexes because the term corresponds to the 2e reduction of complex term plays a dominant role in Cu2+. Therefore, the -∆Etotal,3 the CE path for the comparison. The results shown on the EC and CE paths as described above reduction complex show that a good connection between ∆Etotal,1 and ∆Etotal,3 terms is expected considering eq 4. In fact, an approximate linear reduction complex (REAC-1) and -∆Etotal,3 (REACrelationship between ∆Etotal,1 3) terms was obtained for complexes 1-6 (uB3LYP/BS1), as complex depicted in Figure 6b, which implies that the trend of ∆Etotal,3 reduction can be predicted by ∆Etotal,1 results to a certain degree; in reduction complex results can be predicted by ∆Etotal,3 contrast, the ∆Etotal,1 results. This relationship can reduce computational costs. The linear relationship in Figure 6b mainly results from the small complex reduction to the trend of the {∆Etotal,1 contribution of -∆Etotal,2 complex } value in the EC path. It should be noted that not all ∆Etotal,2 reduction and systems should show such linear relation between ∆Etotal,1 complex complex -∆Etotal,3 terms because the contribution of -∆Etotal,2 depends on the target complex in question. In general, the stability of metal complexes is strongly controlled by the chelate effects, as described in the Introduction. For this study, we sought to predict a complex stability using reduction complex theoretically determined ∆Etotal,1 and ∆Etotal,3 , although we investigated a special case such as the comparison among similar complexes. It is worth mentioning that the simple DFT calculations well predicted the trend of the complex stability as a bulk property. Results further showed that the uB3LYP/ BS1 level calculations with low computational cost are sufficient for predicting the complex stability. Computational costs in DFT calculations depend strongly on the number of basis functions. Therefore, the use of small uB3LYP/BS1 basis set enables us to conduct systematic and exhaustive predictions of complex stabilities in our screening method. We will illustrate again our concept for computational precursor selection for nanomaterial syntheses (see Figure 1).

In our concept, the screening of precursors is achieved by two selection steps; a rough precursor selection and detailed precursor selection. The detailed selection is further divisible into steps for making a precursor stability table and proposal of candidate precursors. The following procedures are included in these steps. (i) Rough precursor selection. In rough selection, we select a target complex (e.g., A) from among complexes of various types A, B, C, D, E, etc., as shown in the figure. The selection in this step is conducted based on experimental data such as stability constants. It should be noted that the use of DFT calculations to this step is not easy because of the chelate effects. (ii) Making precursor stability table. In the detailed selection, DFT calculations are performed to estimate the stability of the target complex, A, and a series of complexes similar to A, i.e., A1, A2, etc. These complexes are designed systematically based on the structure of complex A. In this step, similar complexes are selected to omit entropy, solvent effects, etc. from the comparison of complex stabilities. This enables us to compare the complex stability mainly based on the substituent effects on their electronic structures. The design of complexes with different stabilities is achieved mainly by small changes of electronic structures attributable to substituent effects for ligands such as “ligand fluorinations”. By sorting the complexes according to the predicted stability, we can obtain a table for the precursor stability. (iii) Proposal of candidate precursors. The precursor stability table in step (ii) is used for selecting candidate precursors providing desirable products in the syntheses of nanomaterials (for example, nanoparticles, thin films, and so on). The selection is conducted based on experimental information about the relationship between the stability of precursors and the quality of products, which is obtained from reports in the relevant literature, small-scale “test” material syntheses, etc. Useless precursors are screened from the viewpoint of stability, and candidate precursors for nanomaterial syntheses can be abstracted from the table. Consequently, the candidate precursors are given as a “small” table according to their stability. It is expected that the table enables us to tune precursor stability in nanomaterial syntheses and although the accuracy of the DFT prediction should be carefully considered, it can help to identify the best result in the syntheses. The key to this concept is the effectiveness of DFT-based predictions for complex stabilities. Thus, it can be concluded that our DFT results concerning complex stabilities in this article are valuable for the precursor selection method.

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Our prediction method has potential applications not only for precursor selections but also to select reducing agents, surfactants, etc. in material syntheses. Such an overall computational selection method is expected to lead to rapid acquisition of preferred nanomaterials with low cost. For future studies, we will apply the prediction method to the material syntheses as a next step toward the efficient screening of metal precursor for nanomaterial syntheses. 5. Conclusion As a first step toward the efficient screening of metal precursor in nanomaterial syntheses, DFT calculations were conducted for prediction of the complex stability for a series of copper(II) β-diketonate. In the calculations, similar β-diketonate ligands were compared to suppress indistinct chelate effects, which make it possible to discuss the complex stability based mainly on the electronic states of the complexes. The were estimated for the complex formation energies ∆E complex total complexes using DFT calculations. Then they were compared with stability constants β2 collected from the relevant literature. well predicted the trend of β2 Results show that the ∆E complex total values. Furthermore, the energy change for two-electron reducand the LUMO energy were calculated for the tion ∆E reduction total complexes. They were compared with reduction potentials characterized by cyclic voltammetry measurements. A good (or LUMO) linear relationship was found between the ∆E reduction total and the reduction potentials. Although the DFT calculations were simply conducted for an isolated molecule with no environment, results showed that our computational method can well predict the trend of the complex stability as a bulk property. These results demonstrate the effectiveness of our method for predicting the properties of precursors, thereby supporting efficient precursor selections for the syntheses of nanomaterials. Acknowledgment This research was supported by JST, CREST. The computation was mainly carried out using the computer facilities at Research Institute for Information Technology, Kyushu University. Literature Cited (1) Hyeon, T. Chemical synthesis of magnetic nanoparticles. Chem. Commun. 2003, 927. (2) Daniel, M.-C.; Astruc, D. Gold Nanoparticles: Assembly, Supramolecular Chemistry, Quantum-Size-Related Properties, and Applications toward Biology, Catalysis, and Nanotechnology. Chem. ReV. 2004, 104, 293. (3) Yin, Y.; Alivisatos, A. P. Colloidal nanocrystal synthesis and the organic-inorganic interface. Nature 2005, 437, 664. (4) Burda, C.; Chen, X.; Narayanan, R.; El-Sayed, M. A. Chemistry and Properties of Nanocrystals of Different Shapes. Chem. ReV. 2005, 105, 1025. (5) Park, J.; Joo, J.; Kwon, S. G.; Jang, Y.; Hyeon, T. Synthesis of Monodisperse Spherical Nanocrystals. Angew. Chem., Int. Ed. 2007, 46, 4630. (6) Wang, H.; Nakamura, H.; Uehara, M.; Miyazaki, M.; Maeda, H. Preparation of titania particles utilizing the insoluble phase interface in a microchannel reactor. Chem. Commun. 2002, 1462. (7) Nakamura, H.; Yamaguchi, Y.; Miyazaki, M.; Maeda, H.; Uehara, M.; Mulvaney, P. Preparation of CdSe nanocrystals in a micro-flow-reactor. Chem. Commun. 2002, 2844. (8) Nakamura, H.; Yamaguchi, Y.; Miyazaki, M.; Uehara, M.; Maeda, H.; Mulvaney, P. Continuous Preparation of CdSe Nanocrystals by a Microreactor. Chem. Lett. 2002, 1072. (9) He, S.; Kohira, T.; Uehara, M.; Kitamura, T.; Nakamura, H.; Miyazaki, M.; Maeda, H. Effects of Interior Wall on Continuous Fabrication of Silver Nanoparticles in Microcapillary Reactor. Chem. Lett. 2005, 34, 748.

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ReceiVed for reView June 9, 2008 ReVised manuscript receiVed December 22, 2008 Accepted January 15, 2009 IE800903H