M Hennes

V Schuler

X Weng

J Buchwald

D Demaille

Y Zheng

F Vidal

Growth of vertically aligned nanowires in metal -oxide nanocomposites: Kinetic Monte-Carlo modeling versus experiments

We employ kinetic Monte-Carlo simulations to study the growth process of metal -oxide nanocomposites obtained via sequential pulsed laser deposition. Using Ni -SrTiO 3 as a model system, we reduce the complexity of the computational problem by choosing a coarse-grained approach mapping Sr, Ti and O atoms onto a single effective STO pseudo-atom species. With this Ansatz, we scrutinize the kinetics of the sequential synthesis process, governed by alternating deposition and relaxation steps, and analyze the self-organization propensity of Ni atoms into straight vertically aligned nanowires embedded in the surrounding STO matrix. We finally compare the predictions of our binary toy model with experiments and demonstrate that our computational approach captures fundamental aspects of self-assembled nanowire synthesis. Despite its simplicity, our modeling strategy successfully describes the impact of relevant parameters, like concentration or laser frequency, on the final nanoarchitecture of metal -oxide thin films grown via pulsed laser deposition.

Introduction

Vertically aligned metal -ceramic nanocomposites constitute a new material class characterized by the presence of metallic nanopillars embedded in a planar oxide matrix. As a consequence of their very large heterointerface as well as their anisotropic optical, magnetic and electrical properties, these hybrid structures can be considered promising candidates for technological applications in various fields ranging from plasmonics [START_REF] Kabashin | Plasmonic nanorod metamaterials for biosensing[END_REF][START_REF] Yao | Optical negative refraction in bulk metamaterials of nanowires[END_REF] , spintronics [START_REF] Piraux | Templategrown NiFe/Cu/NiFe nanowires for spin transfer devices[END_REF] and catalysis [START_REF] Kawasaki | Photoelectrochemical water splitting enhanced by self-assembled nanopillars embedded in an oxide semiconductor photoelectrode[END_REF] to ultrahigh density magnetic data storage [START_REF] Yang | Preparation and magnetic property of Fe nanowire array[END_REF][START_REF] Qin | Magnetic force microscopy of magnetic domain structure in highly ordered co nanowire arrays[END_REF] .

For development of novel vertical nanocomposites, pulsed laser deposition (PLD) synthesis relying on self-organized growth has recently emerged as a novel technique, complementing conventional methods such as electrodeposition into prestructured templates [START_REF] Kawai | Magnetic properties of anodic oxide coatings on aluminum containing electrodeposited Co and Co-Ni[END_REF][START_REF] Masuda | Ordered metal nanohole arrays made by a two-step replication of honeycomb structures of anodic alumina[END_REF][START_REF] Fert | Magnetic nanowires[END_REF] . On the one hand, self-assembly based procedures avoid cumbersome intermediate steps and permit to create arrays of ultrathin nanowires (d < 5 nm) with extremely high densities (ρ > 10 11 /cm 2 ). On the other hand, the metallic and oxide phases exhibit vertical epitaxial coupling, which is especially interesting when dealing with magnetic nanocomposites. Indeed, pronounced differences in lattice parameters between the ma-trix and the metallic nanoinclusions paves the way for magnetic anisotropy control via strain engineering [START_REF] Schuler | Huge metastable axial strain in ultrathin heteroepitaxial vertically aligned nanowires[END_REF] and synthesis of artificial multiferroics [START_REF] Yao | Magnetoelectric coupling across the interface of multiferroic nanocomposites[END_REF][START_REF] Huang | New epitaxy paradigm in epitaxial self-assembled oxide vertically aligned nanocomposite thin films[END_REF] .

Obviously, the design of application-optimized composites requires precise control of their nanoarchitecture. The inter-wire spacing must be carefully tuned to achieve a compromise between high areal density and detrimental magnetic dipole-dipole interactions. At the same time, accurate adjustment of the nanowire radius is required, as it intrinsically limits the thermal stability of the encoded magnetic information. In addition, it also plays a crucial role in determining the final strain state of the nanowire [START_REF] Schuler | Huge metastable axial strain in ultrathin heteroepitaxial vertically aligned nanowires[END_REF] .

A variety of parameters influencing the structure of vertically aligned nanocomposites has been identified in recent years. The temperature [START_REF] Zheng | Selfassembled growth of BiFeO 3 -CoFe 2 O 4 nanostructures[END_REF] and deposition frequency [START_REF] Huang | Self-assembled Co-BaZrO 3 nanocomposite thin films with ultra-fine vertically aligned Co nanopillars[END_REF] were for example found to have a strong impact on the diameter of embedded nanocolumns grown via PLD. However, while the number of experimental studies dealing with magnetic metal -oxide VANs increases steadily [START_REF] Huang | Self-assembled Co-BaZrO 3 nanocomposite thin films with ultra-fine vertically aligned Co nanopillars[END_REF][START_REF] Mohaddes-Ardabili | Self-assembled single-crystal ferromagnetic iron nanowires formed by decomposition[END_REF][START_REF] Vidal | Mechanism of localization of the magnetization reversal in 3 nm wide Co nanowires[END_REF][START_REF] Francisco | Combinatorial growth and anisotropy control of selfassembled epitaxial ultrathin alloy nanowires[END_REF][START_REF] Su | Self-assembled magnetic metallic nanopillars in ceramic matrix with anisotropic magnetic and electrical transport properties[END_REF][START_REF] Schuler | Growth and magnetic properties of vertically aligned epitaxial CoNi nanowires in (Sr, Ba)TiO 3 with diameters in the 1.8 -6 nm range[END_REF] , there has been little progress in the theoretical description of the growth process. The details of the mechanisms giving rise to self-organized, matrix-embedded wire arrays remain poorly understood.

In the present work, we therefore scrutinize synthesis of hybrid metal-oxide thin films from an experimental, as well as from a theoretical perspective. On the one hand, we use a lattice kinetic Monte-Carlo (KMC) Ansatz to analyze the growth of hybrid Ni -SrTiO 3 (Ni -STO) thin films. By choosing a coarse-grained approach, which only takes Ni and matrix pseudo-atoms into consideration, we obtain a simple and powerful toy-model which allows for an atomic-scale description of the initial stages of STOembedded Ni nanopillar growth and permits to link synthesis parameters to the final nanocomposite structure. On the other hand, we employ sequential PLD, to grow Ni -STO thin films on STO(001) substrates and compare experimental results with predictions from our simulations. In addition, we also scrutinize various related metal-perovskite nanocomposites, like Ni -(Sr,Ba)TiO 3 and CoNi -(Sr,Ba)TiO 3 and analyze to what extent the present simulation results can be generalized to these material systems.

The paper is structured as follows: We start by giving a detailed presentation of our KMC simulation results. We then turn to our experimental findings and discuss these results with respect to our KMC data and available literature results. We finally close with a summary and outlook.

Results and discussion

KMC simulation results

Sequential PLD is based on laser ablation using a set of interchangeable targets, resulting in alternate deposition of different atomic species and ensuing thin film growth on a substrate placed in vicinity of the plasma plume [START_REF] Francisco | Combinatorial growth and anisotropy control of selfassembled epitaxial ultrathin alloy nanowires[END_REF][START_REF] Schuler | Growth and magnetic properties of vertically aligned epitaxial CoNi nanowires in (Sr, Ba)TiO 3 with diameters in the 1.8 -6 nm range[END_REF] (Fig. 1a). In the present simulation study, we focus on Ni -SrTiO 3 nanocomposite synthesis relying on alternating addition of matrix constituents to the substrate surface, i.e., Sr, Ti and O atoms, described by a single effective matrix species (STO) in our KMC approach, and Ni atoms, respectively. A detailed description of our simulation strategy is given in the Methods part of the present paper. Closer analysis of these results allows to give a simple qualitative description of the growth process. After addition of Ni to the substrate, surface diffusion of single atoms results in formation of islands, as illustrated in Fig. 1b(i). During the subsequent steps, encompassing further relaxation due to target change induced waiting time as well as matrix atom deposition, Ostwald-ripening occurs at the surface. Small islands dissolve, releasing Ni atoms which attach to larger, energetically favored structures, as seen by comparing Fig. 1b(i) and (ii) or Fig. 1b(iii) and (iv). On the other hand, deposition of coarse-grained STO pseudo-atoms results in simultaneous matrix growth. At 870 K, Ni surface diffusion is fast enough to prevent vertical kinetic trapping, i.e., covering of Ni atoms by the surrounding oxide. Successive layerwise stacking of Ni islands eventually leads to formation of straight and dense columns, buried in the surrounding STO matrix, as can be seen in Fig. 1b(viii). As shown in Fig. 1c, temperature plays a key role during this process. Varying T from 700 K to 790 K, we observe that low temperature growth results in a cluster-like nanocomposite structure. Nanopillar formation is clearly suppressed, which can be attributed to the reduced mobility of Ni atoms. With increasing temperature, the length of the nanoinclusions increases. While at 700 K, the average metal structure height h equals 4.5 monolayers (ML), yielding an aspect ratio close to one, increasing T from 730 K to 760 K and 790 K results in h ≈ 6.5, 8.5, 15 ML, respectively. The transition temperature from cluster or rod-like to pure nanowire-growth with percolating metallic structures crossing the entire thin film (i.e., fulfilling the condition h = N z , N z being the average thin film thickness) was determined to be T c ≈ 820 K in the present simulations.

a) b) c) τ R n STO n Ni t E ν = 10 Hz τ R substrate: SrTiO 3 (001) N× { } ≡ N × (n STO | n Ni ) (i) (ii) (iii) (iv) (v) (vi) (vii) (viii) T = 700 K T = 730 K T = 760 K T = 790 K
To facilitate comparison with experimental work, simulations with varying ratio of Ni to STO-atom deposition steps n Ni /n STO were performed, resulting in a change of the thin film composition (T = 820 K, N x × N y = 80 × 80). As exemplified in Fig. 2a, gradual increase of n Ni for constant n STO (n STO = 12) resulted in a monotonic increase of the average wire diameter. In contrast, the wire density remained unaffected with average value ρ = N nanowire N x N y a 2 ≈ 8 ± 1 • 10 11 /cm 2 derived from the number of nanowires N nanowire in the simulation cell, a being the typical cubic unit lattice parameter (a ≈ a STO / √ 2). A similar behavior was obtained when simulating sequences with varying n STO (while keeping n Ni = 3), as shown in exemplary configurations in Fig. 2b,c,d,e. Despite the large variation of n STO , the number of wires in the simulation cell remained constant while their diameters decreased significantly with increasing n STO values.

To gain further insight into the dynamics of the initial stages of the growth process, we analyzed the evolution of the Ni island number N i at the surface of the thin film during the first deposition sequence (ν = 10 Hz, T = 820 K, N x × N y = 128 × 128). Fig. 3a shows N i (t) calculated for various n Ni values (keeping n STO = 12). While N i is clearly largest for high n Ni /n STO ratios, it reaches an almost constant value towards the end of the sequence, with relative differences in island number dropping below 20%. This is additionally illustrated in the inset of Fig. 3a, where the island density ρ is shown as a function of n Ni . While for 7.2 s simulation time, the value of ρ saturates rapidly, it keeps growing linearly as a function of n Ni when the total length of the sequence is de- Again, it is instructive to analyze the number of Ni islands N i present at the surface during the initial growth stages to understand how this behavior emerges from the interplay of deposition and relaxation phases. Fig. 3b shows the results of simulation runs where N i (t) has been computed for a 3 × (6 | 1) sequence and its 1×(18 | 3) counterpart (T = 820 K, N x × N y = 128 × 128). In order to obtain comparable total simulation times, the 1×(18 | 3) sequence has been complemented by additional relaxation time. All results were averaged over five different runs, to gain better statistics. As was already observed in Fig. 3a, the island number increases dramatically immediately after deposition. Between two subsequent deposition steps, N i then sharply decreases as a function of time, which is due to Ni atom diffusion and island coalescence. However, the relaxation behavior of both systems differs significantly. Indeed, the larger amount of metal atoms added at once to the system during a (18 | 3) sequence leads to a higher number of islands during early relaxation, when compared to a single (6 | 1) sequence -in agreement with the previous part of the discussion (Fig. 3a). As a direct consequence of a larger number of target exchange moves, the total growth time resulting from a 3×(6 | 1) protocol exceeds by far the one of its 1 × (18 | 3) counterpart. Thus, in a single (18 | 3) sequence, the system is given significantly less time for Ostwald ripening, which eventually explains the higher amount of islands at the end of the sequence and the aforementioned difference in final nanowire densities. Allowing further relaxation after completion of a (18 | 3) sequence (keeping the total number of atoms in the system constant) reveals that

N (18|3) i (3τ (6|1) ) ≈ N (6|1) i (τ (6|1)
), which suggests that the matrix atoms have only little impact on Ni island coalescence when considering sub-ML deposition.

Taken together, these findings show that sequential PLD can give rise to different growth regimes, which will depend on the specific setup design, growth protocol and nanocomposite materials: (i) short relaxation times or, equivalently, low surface mobility of the segregating metal atoms (Ni in our present study), will give rise to an increase of ρ with n metal /n oxide . In contrast, in a system with (ii) large relaxation times or high metal atom mobility, an increase of n metal will result in a larger nanocolumn diameter at constant density. In addition, our modeling approach highlights that sequences of (n • n metal | n • n oxide )-type can be used as a strategy to tune nanowire diameters and densities, while simultaneously keeping the metal/oxide ratio constant.

Modeling vs. experiments

Having presented a qualitative analysis of the main mechanisms governing nanocomposite growth, we now turn to a comparison of our KMC modeling approach with experiments. As reported in our previous studies, PLD-based sequential deposition of Ni and SrTiO 3 on SrTiO 3 (001) substrates was shown to result in phase separation and growth of vertically aligned metallic Ni nanowires [START_REF] Schuler | Huge metastable axial strain in ultrathin heteroepitaxial vertically aligned nanowires[END_REF] . In the present paper, we present additional results on Ni -SrTiO 3 nanocomposite synthesis and focus on the impact of concentration on the final nanowire morphology, diameters and densities. these experiments, the number of Ni deposition steps was kept constant, while n STO was successively doubled. As can immediately be inferred from the micrographs, the metal/oxide ratio has a strong impact on the nanowire diameter: high n Ni /n STO ratios clearly give rise to larger nanowires. We thus retrieve the trend that was identified in our KMC simulations, where the nanowire diameter grew monotonically as a function of n Ni /n STO . We also find good qualitative agreement concerning the shape of the embedded nanowires. Indeed, their straight morphology and complete absence of kinks or pronounced diameter modulations, is perfectly compatible with our KMC predictions (Fig. 4d).

In addition to the nanowire size and morphology, we determined the porosity of each sample, defined as the nanowire/matrix surface ratio in a projection perpendicular to the thin film surface. The results are plotted in Fig. 4e. We observe a similar behavior in Ni -STO as well as CoNi -SBTO systems, a linear increase of p with n (Co)Ni /n S(B)TO characterizing pure columnar growth. As the porosity is directly linked to the nanowire areal number density ρ and radius r via p = ρπr 2 , we conclude that the nanowire diameter must obey d ∝ ρ -1/2 (n (Co)Ni /n S(B)TO ) 1/2 . For the synthesis protocols used in our experiments, our KMC simulations predict an almost constant nanowire density for all Ni -STO samples ( ρ ≈ 8 • 10 11 cm -2 ). This is indeed what we observe in our experiments, in Ni -STO ( ρ = 5.1 ± 1.1 • 10 11 cm -2 ) but also in CoNi -SBTO thin films ( ρ = 3.4 ± 0.4 • 10 11 cm -2 ), which display a very similar behavior. As a result, a simple relationship linking concentration and nanowire diameter is eventually obtained: d ∝ (n (Co)Ni /n S(B)TO ) 1/2 , as shown Fig. 4f.

Although our modeling approach is focused on metal-oxide nanocomposite growth, it is interesting to compare the present results with earlier studies on oxide -oxide nanocolumnar thin films, where experimental information concerning the relationship between final nanoarchitecture and growth conditions is available. In BiFeO 3 -CoFe 2 O 4 thin film synthesis [START_REF] Zheng | Selfassembled growth of BiFeO 3 -CoFe 2 O 4 nanostructures[END_REF] , the diameter of embedded CoFe 2 O 4 structures was found linked to the growth rate ν via d ∝ ν-1/2 . This was also reported in Smdoped CeO 2 -SrTiO 3 vertical heteroepitaxial nanocomposites [START_REF] Cho | Self-assembled oxide films with tailored nanoscale ionic and electronic channels for controlled resistive switching[END_REF] .

In the present study, the same result is retrieved in a growth regime where ρ is independent of n (Co)Ni /n S(B)TO . Indeed, when keeping n (Co)Ni fixed, d ∝ ν-1/2 immediately follows from d ∝ ρ -1/2 (n CoNi /n S(B)TO ) 1/2 when thin film growth is dominated by S(B)TO atom addition (p 1). However, as has been put forward in an earlier part of this work, it must be emphasized that very different growth conditions can be encountered. For example, self-organization of Co wires in CeO 2 via sequential PLD resulted in nanocomposites with constant wire diameter and decreasing wire density when increasing the number of shots on the CeO 2 target 21 , which might suggest a significantly different surface mobility of Co atoms on CeO 2 surfaces. The scaling relations identified in the present metal-perovskite systems, which also apply to some extent to selected oxide-oxide nanocomposites, will thus not necessarily remain valid in other types of nanocolumnar metal-oxide thin films.

Another difficulty encountered when trying to compare the present results with earlier work on vertically aligned nanocomposites arises from the fact that most studies described in literature rely on single target PLD-growth for nanocomposite synthesis [START_REF] Kawasaki | Photoelectrochemical water splitting enhanced by self-assembled nanopillars embedded in an oxide semiconductor photoelectrode[END_REF][START_REF] Huang | Self-assembled Co-BaZrO 3 nanocomposite thin films with ultra-fine vertically aligned Co nanopillars[END_REF][START_REF] Su | Self-assembled magnetic metallic nanopillars in ceramic matrix with anisotropic magnetic and electrical transport properties[END_REF] . To close this gap, we conducted additional simulations where Ni and STO pseudo-atoms were deposited simultaneously and not sequentially. Fig. 5a and5b show exemplary results from simulations performed with varying n Ni /n STO ratios (ν = 10 Hz, T = 820 K, N x × N y = 80 × 80). At first sight, the system exhibits a behavior which appears to correspond to our findings based on sequential synthesis. We indeed observe growth of nanowires with rather straight morphology and our results demonstrate that an increase of n Ni /n STO yields a larger average nanowire diameter. However, careful analysis of the data indicates that the wire den- sity does not stay constant when changing n Ni /n STO . While the small system sizes used in our simulations impede an improvement of the statistics and make a reliable analysis of nanowire densities difficult, we found evidence supporting an increase of ρ with the amount of Ni atoms in the system. This might be traced back to shorter relaxation steps, when compared to sequential PLD, as has been discussed in a previous part of this paper. Indeed, without any intermediate relaxation, as introduced artificially during sequential growth, the laser frequency ν imposes the typical time scale during which the system evolves with constant number of Ni atoms. A variation of ν should therefore have a measurable impact on the synthesis process and the final structure of the nanocomposite.

To test this hypothesis, we performed various simulations based on a single target growth scheme, reducing the frequency by a factor of 5. Fig. 5c shows a representative configuration resulting from simulation runs using ν = 2 Hz (T = 820 K, N x × N y = influences the resulting nanocomposites, yielding a significant increase of the wire diameter when lowering the frequency. This finding has very recently been reported in PLD-based growth of Co -BaZrO 3 thin films, where the laser frequency was used to tune the magnetic properties of the resulting thin films [START_REF] Huang | Self-assembled Co-BaZrO 3 nanocomposite thin films with ultra-fine vertically aligned Co nanopillars[END_REF] . However, our simulations also indicate that a reduction of the frequency leads to a concomitant reduction of ρ. The present work demonstrates how the introduction of additional relaxation steps (inherent to sequential growth) can be used as a simple, yet powerful strategy to circumvent these problems and decouple ρ and d to eventually achieve an increased control of the final nanocomposite architecture.

Conclusions

In this study, we presented a coarse-grained lattice KMC approach which we employed to model sequential PLD growth of metaloxide nanocomposites. Using Ni -SrTiO 3 as a model system, we analyzed the initial stages of growth and were able to identify key parameters affecting the final nano-architecture of the thin film. We showed that synthesis at lower temperatures resulted in phase separated composites characterized by small Ni nanoinclusions, with aspect ratio close to one, embedded in a STO matrix. Increasing the growth temperature favorized the growth of rods and, above 820 K, eventually resulted nanowires spanning from the bottom of the thin film to its surface. We highlighted that systematically raising n Ni /n STO during each cycle, yielded an increased average nanowire diameter, while the overall wire density remained constant. Careful analysis of the growth procedure allowed to show how this behavior emerged from the subtle interplay of deposition and relaxation phases. Control of the relaxation time between deposition steps was thus identified as a key requirement to accurately tune the nanowire size and density. On an atomic level, our KMC approach is far from grasping the details and subtleties of metal-oxide interactions (e.g. strain induced effects, surface reconstructions, defects) and we did not strive for an exhaustive quantitative treatment of the problem. However, when comparing our findings with experimental results, we observed reasonable qualitative agreement with respect to the evolution of wire density and diameter upon changes in the synthesis parameters. We therefore conclude that, despite its shortcomings, our simulation approach provides a robust scheme to understand key issues affecting nanowire self-assembly and lays the groundwork for future studies aiming at a more elaborate description of the growth of metal -oxide nanocomposites.

Methods

Kinetic Monte-Carlo

KMC results presented in this work rely on an implementation of the residence time algorithm proposed by Bortz [START_REF] Bortz | A new algorithm for Monte Carlo simulation of ising spin systems[END_REF] . To simplify computations, Ni -SrTiO 3 nanocomposite growth resulting from sequential addition of Sr, Ti, O and Ni atoms to the surface of the thin film was approximated by a binary system, composed of Ni and STO pseudo-atoms atoms only. All simulations were performed on a rigid lattice with N x × N y sites and in plane periodic boundary conditions. The lattice was chosen as simple cubic, i.e. each effective atom having four in plane nearest neighbors, which reflects the fourfold symmetry of (001) SrTiO 3 planes when the composite is growing in [001] direction. Differences in lattice parameters and resulting misfit strains were neglected.

Only two major processes were included into our KMC simulations: (i) simultaneous addition of N Ni or N STO atoms to the surface of the growing thin film and (ii) their subsequent diffusion. Desorption of the deposited objects as well as chemical reactions were not taken into consideration. Regarding (i), the number of deposited atoms was varied with simulation cell size and adapted such as to closely match experimental conditions (during PLD growth, approximately 25 deposition events were required on average to achieve single ML deposition). Additionally, we took into account the different deposition yields from single pulses on the two targets: laser ablation on SrTiO 3 was found to generate roughly four times the number of Ni atoms. Atom deposition was treated as a process where (x, y) coordinates on the surface were chosen at random. With respect to (ii), we only included surface diffusion in our simulations. Every atom could jump from its current position to one of the four nearest neighbor adjacent sites. Volume diffusion was neglected: any atom at position (x, y, z) covered by another atom at (x, y, z + 1) remained immobile. However, vertical or "climbing"-moves were explicitely incorporated, with atoms at position (x, y, z) allowed to step up to position (x, y + 1, z + 1) whenever an atom was present at position (x, y + 1, z). The jump of an effective atom of type l at lattice site (x i , y i , z i ) to one of its nearest neighbors at (x f , y f , z f ) is a thermally activated event. Transition state theory allows to compute transition rates from knowledge of energy barriers separating initial and final states via

⊗ • • Br -site ⊗ •To -sites FH -site • To -site a) b) e) c) d) f) g) h) i) j) k) 1 2 3 4 A ≡ 1 B C D E 2 3 4 5 ≡ 1' 2' 3' 4' 5' × 1' × 2' × 3' • 1' • 2' • 3' • 1 • 2 • 3 • A • B • C • 1 • 2 • 3
k = k 0 e -E B /k B T (1)
with k B , T , k 0 and E B being the Boltzmann constant, temperature, jump frequency (k 0 ≈ 10 13 Hz) and barrier energy, respectively. In a binary system, diffusion of single atoms on a planar surface then requires determination of 2 3 parameters E l/k→ j , with atomic species k at (x i , y i , z i -1) and j at (x f , y f , z f -1), as depicted in Fig. 6. Additionally, nearest neighbors in plane impact the barrier energy. In the present work, we modeled this behavior by using simple pair interaction terms [START_REF] Mouton | The early stage of formation of self-organized nanocolumns in thin films: Monte Carlo simulations versus atomic-scale observations in Ge-Mn[END_REF] , summed over the atom types at nearest neighbor sites

∆E l = ∑ n (i) m ∆E lm -∑ n ( f ) m ∆E lm (2) Here, n (i)
m is the number of next neighbors of type m (m ≡ Ni, STO) surrounding the starting position of the diffusional move in plane (sites 1, 2, 3 in Fig. 6), n ( f ) m indicates the number of mtype next neighbors around the arrival site (4, 5, 6 in Fig. 6). The final barrier energy of a diffusing l-type atom thus reads, E B = E l/k→ j + ∆E l . Energies E l/k→ j and in-plane corrections ∆E lm used in the present work as an input for KMC simulations are listed in Table 1.

Diffusion barrier heights relating to pure Ni -Ni and effective STO -STO interactions were directly deduced from literature. E STO/STO→STO determination remained somewhat arbitrary, due to the coarse-grained nature of our approach (resulting from mapping of Sr, Ti and O atoms onto a single STO species). However, available data revealed little spread and no pronounced dependency on the surface termination was reported. To reduce the number of free parameters and further simplify the calculations, we assigned the same energy to all STO pseudo-atom moves: induce segregation in our binary model system. We therefore chose a rather small, yet non-zero in-plane interaction energy E = 0.1 eV between Ni and STO pseudo-atoms.

E STO/STO→STO = E STO/STO→Ni = E STO/Ni→Ni = E STO/Ni→STO

Density functional theory

We employed density functional theory (DFT) calculations to identify Ni-addatom minimum energy sites and minimum energy paths on planar SrTiO 3 (001) surfaces. All calculations were performed using the Quantum Espresso software package [START_REF] Giannozzi | Quantum espresso: a modular and opensource software project for quantum simulations of materials[END_REF] with ultrasoft pseudopotentials and PBE exchange correlation [START_REF] Perdew | Generalized gradient approximation made simple[END_REF][START_REF] Zhang | Comment on "generalized gradient approximation made simple[END_REF] . The kinetic energy cutoff was set to 35 Ry while the charge density cutoff was chosen fourteen times as high. The integration over the Brillouin zone was performed with a 3 × 3 × 1 Monkhorst-Pack mesh [START_REF] Hendrik | Special points for Brillouin-zone integrations[END_REF] . The simulation cell employed in our study consisted of a single STO-cube with volume 3a STO 0 × 3a STO 0 × 3a STO 0 (a STO 0 = 3.923 Å) and periodic boundary conditions in plane, combined with 3a 0 vacuum inserted in z to create (001) surfaces (Fig. 7a and Fig. 7c). Plan-views of the different surface configurations scrutinized in the present work are shown in Fig. 7b and Fig. 7d. In a first computational step, all SrTiO 3 surfaces were structurally relaxed using the BFGS algorithm [START_REF] Broyden | The convergence of a class of double-rank minimization algorithms 1. general considerations[END_REF][START_REF] Fletcher | A new approach to variable metric algorithms[END_REF][START_REF] Goldfarb | A family of variable-metric methods derived by variational means[END_REF][START_REF] David | Conditioning of quasi-newton methods for function minimization[END_REF] until the force components on every atom were less than 10 -4 Ry/a 0 and changes in the total energy were found smaller than 10 -5 Ry. In a second step, we placed a single Ni atom at various canonical positions (e.g. on top of oxygen atoms or at bridge positions between two oxygen atoms). Keeping the bottom layer fixed, we then performed a geometry optimization by minimizing the energy of the system within a spin-polarized calculation scheme. To compute the height of the energy barriers, we used a climbing image nudge elastic band (NEB) simulation scheme [START_REF] Henkelman | A climbing image nudged elastic band method for finding saddle points and minimum energy paths[END_REF] . The simulations were considered to be converged, when the abolute value of the force orthogonal to the path was lower than 0.05 eV/Å. In Fig. 7e all height with respect to the FH position amounts to E = 2.65 eV). The final move towards the global minimum eventually requires crossing a smaller barrier with E = 0.55 eV. In addition to moves connecting global minima, we checked that Ni atoms can also evolve between local minima (Fig. 7i1' and Fig. 7j5'), which involves a slightly modified diffusional path, with similar energy barrier of 1.77 eV (Fig. 7k).

) c) d) f) g) h) i) j) k) 1 2 3 4 A ≡ 1 B C D E 2 3 4 5 ≡ 1' 2' 3' 4' 5' × 1' × 2' × 3' • 1' • 2' • 3' • 4' • 5' • 1 • 2 • 3 • 4 • 5 • A • B • C • D • E • • 2 • 3 • 4 O Sr Ti Ni
Due to mapping of Sr, Ti and O onto a single pseudo-atom species, our KMC model is not able to differentiate between Aand B-site terminations. Considering that SrO surfaces were shown to be thermodynamically more stable than their TiO 2 counterparts [START_REF] Demkov | Investigating alternative gate dielectrics: A theoretical approach[END_REF][START_REF] Zhang | Steps on the (001) SrTiO3 surface[END_REF] , and in absence of any experimental evidence describing immobilization or trapping of single Ni atoms on the surface during growth, we eventually chose E Ni/STO→STO = 1 eV, a parameter value close to DFT results describing Ni diffusion on a SrO-terminated surface.

Thin film synthesis

Ni -SrTiO 3 , Ni -(Sr,Ba)TiO 3 as well as CoNi -(Sr,Ba)TiO 3 nanocomposites were grown via sequential pulsed laser deposition using a qudrupled Nd:YAG laser with λ = 266 nm (Quantel) operated at 10 Hz with typical fluences 1 J/cm 2 < F < 3 J/cm 2 . For sample synthesis, NiO, CoO and SrTiO 3 targets were used in a reductive environment (P < 10 -6 mbar). Atomic deposition was carried out on SrTiO 3 (001) substrates (SurfaceNet GmbH) heated to T ≈ 650 • C. Compositional tuning of the nanocomposite was achieved by changing the ratio of laser shots on the NiO, CoO and SrTiO 3 target, respectively. The notation N×(n STO | n (Co)Ni ) is used in the present work to describe series of N sequences with n (Co)Ni shots on the NiO and CoO targets followed by n STO shots on the SrTiO 3 target (see [START_REF] Francisco | Combinatorial growth and anisotropy control of selfassembled epitaxial ultrathin alloy nanowires[END_REF][START_REF] Schuler | Growth and magnetic properties of vertically aligned epitaxial CoNi nanowires in (Sr, Ba)TiO 3 with diameters in the 1.8 -6 nm range[END_REF] for a detailed description). A typical time of τ R = 3 s was required to switch between the targets. After completing nanocomposite growth, the surface of the thin film was eventually covered with an additional matrix layer of several nm thickness to prevent oxidation under ambient conditions. High-Resolution Transmission Electron Microscopy data were ac-

Fig. 1b shows

  Fig.1bshows a series of representative KMC results illustrating early stage system configurations during sequential PLD-based nanocomposite growth (T = 870 K, N x × N y = 50 × 50). In this simulation, a (18 | 3) sequence has been used, i.e., 18 STO followed by 3 Ni deposition events. The system states after repetition of N = 1, 2, 3, 5 and 10 of these sequences are depicted in Fig.1b(ii), (iv), (vi), (vii) and (viii) respectively. Additionally, Fig.1b(i),(iii) and (v) show intermediate configurations during the first, second and third sequence after Ni and before STO deposition.

Fig. 1 aFig. 1 a

 11 Fig. 1 a) Schematics depicting s-PLD based thin film growth with sequential ablation from 2 different targets. b) Early stages of na modeled with KMC, Ni atoms are shown in red, STO pseudo-atoms in blue. c) Impact of growth temperature on Ni nanoinclusion m

Fig. 2 3 Fig. 2

 232 Fig. 2 Nanocomposite structure as a function of the nNi/nSTO ratio: a) average nanowire diameter in lattice units (l.u.) as a function of nNi (nSTO = 12) and b), c), d), e) variation of nSTO (keeping nNi = 3).

Fig. 3 Fig. 3

 33 Fig. 3 Evolution of the total Ni island number Ni as a function of time at the surface of the growing thin film: a) for nNi = 3 (blu nNi = 5 (green), nNi = 6 (red, dashed). Inset: Island density as a function of nNi computed for t = 3 s (green crosses) and t = 7.2 s (p island number as a function of time: single (18 | 3) sequence with subsequent relaxation (orange curve), three (6 | 1) sequences ( and total island number at the end of a single (18 | 3) sequence, without additional relaxation time (black dots)

  Fig. 4a, b, c show HR-TEM plan-views of Ni -STO samples where the growth sequence has been systematically varied. In

  : n Ni = const. CoNi -SBTO: n SBTO = const.

Fig. 4 7 Fig. 4

 474 Fig. 4 Metal-oxide nanocomposites grown via s-PLD: a), b), c) HR-TEM plan-views of Ni -STO nanocomposites. d) Cross sectional HR-TE micrograph of a Ni-SBTO thin film with a buried Ni nanowire giving rise to characteristic Moiré patterns. e) porosity and f) nanowire diameter as function of n (Co)Ni /n S(B)TO and (n (Co)Ni /n S(B)TO ) 1/2 as well as linear fits (Ni: blue, dashed line, CoNi: orange, solid line).

Fig. 5 Fig. 5

 55 Fig. 5 KMC simulation of nanocomposite growth from a single target: a) at ν = 10 Hz and 4 at% Ni in the nanocomposite, b) changing and finally, c) reducing the laser frequency to ν = 2 Hz.

Fig. 6

 6 Fig. 6 Determination of energy barriers using an exemplary diffusion move: a) a Ni atom on a top Ni site diffuses to a top ST final position is marked with a cross for better visibility (Ni atoms are shown in red, STO pseudo-atoms in blue). In the pres atom sites marked with solid contour line are relevant for energy barrier height determination. b) Corrections ∆E to the energy b neighbors at initial and final sites (labeled 1, 2, 3 and 4, 5, 6, respectively).

Fig. 7

 7 Fig. 7 Summary of the DFT results obtained in the present study. a) Simulation cell employed for analysis of diffusion on SrO b) plan-view of a SrO-terminated (A-site) surface. c) Simulation cell employed for analysis of diffusion on TiO2-terminated sur

Fig. 6

 6 Fig. 6 Determination of energy barriers using an exemplary diffusion move: a) a Ni atom on a top Ni site diffuses to a top STO site (Ni/Ni→STO), the final position is marked with a cross for better visibility (Ni atoms are shown in red, STO pseudo-atoms in blue). In the present model, only neighbor atom sites marked with solid contour line are relevant for energy barrier height determination. b) Corrections ∆E to the energy barrier arise from in-plane neighbors at initial and final sites (labeled 1, 2, 3 and 4, 5, 6, respectively).

  . Due to lack of literature values, Ni -SrTiO 3 interaction energies had to be assessed by performing preliminary KMC and DFT calculations. Based on experimental evidence reporting 3D island creation for Ni deposited on SrTiO 3 31 (reflecting the high interface energy of the system), we determined E Ni/Ni→STO by performing KMC simulations for different values of this parameter and scrutinized the onset of isolated vertical Ni structures growth (islands with more than 1 ML thickness) when depositing sub-monolayer quantities of Ni on the surface. For determination of E Ni/STO→STO , DFT calculations were undertaken, which will be described in detail in the next paragraph. We used E Ni/STO→STO = E Ni/STO→Ni , a similar simplification as the one employed for STO pseudo-atom diffusion. Finally, ∆E Ni-STO was determined by considering the requirements ∆E Ni-STO < ∆E Ni-Ni and ∆E Ni-STO < ∆E STO-STO to

  and Fig. 7f the lowest energy paths for Ni migration on the SrO-and TiO 2 -terminated STO(001) surfaces are shown. For every NEB simulation, we used five images, which were connected by appropriate polynomial interpolation. For Ni migration on SrO terminated surfaces, we found one major saddle point (E = 0.67 eV), located half way between two slightly asymmetric top-O positions, as shown in Fig. 7g. A small intermediate energy barrier is considered of minor importance for the present surface diffusion analysis. For Ni diffusion on TiO 2 terminated site, we identified different paths, which are shown in Fig. 7h-k. The first path connects two global minima corresponding to a Ni atom located in a FH-oxygen position (Fig. 7h) with a barrier height of E = 2.37 eV. A second competing path with almost identical maximum saddle point energy is shown in (Fig. 7i-j). Here, the Ni atom crosses a first saddle point (E = 1.4 eV) reaching a local minimum configuration with twofold oxygen coordination (Fig. 7i5 and Fig. 7j1'), where one of the O-atoms is slightly pushed out of the surface plane. In a second step, the Ni atom leaves this twofold coordinated site and moves into a top-O configuration, a diffusional step with energy barrier height of E = 1.8 eV (the over-J o u r n a l N a me , [ y e a r ] , [ v o l . ] , 1-10 | 7 atom sites marked with solid contour line are relevant for energy barrier height determination. b) Corrections ∆E to the energy barrier arise from in-plane neighbors at initial and final sites (labeled 1, 2, 3 and 4, 5, 6, respectively).

Fig. 7 7 Fig. 7

 777 Fig. 7 Summary of the DFT results obtained in the present study. a) Simulation cell employed for analysis of diffusion on SrO-terminated surfaces and b) plan-view of a SrO-terminated (A-site) surface. c) Simulation cell employed for analysis of diffusion on TiO 2 -terminated surfaces and d) plan-view of a TiO 2 -terminated (B-site) surface. Energy of the system as a function of the normalized reaction coordinate (n.r.c) for Ni diffusion on e) SrO-terminated and f) TiO 2 -terminated STO(001) surfaces. g) Diffusion path of a Ni atom on A-site surfaces (energies labeled 1 → 2 → 3 → 4 in e) from left to right). On TiO 2 terminated surfaces, different paths with similar saddle point energies were identified: h) Diffusion from FH to FH sites, corresponding energy curve labeled dark blue (dashed) in f). i) and j) show Ni diffusion paths from FH to FH sites, with an intermediate local minimum resulting from an oxygen atom "lift-up move", corresponding energies labeled in f) 1 → 2 → 3 → 4 → 5 (for the path shown in i), from left to right) and 1 → 2 → 3 → 4 → 5 (for the path shown in j), from left to right). Finally, k) alternative oxygen "lift-up move" characterized by a similar saddle point energy (labeled in f) with blue crosses).

Table 1

 1 Energy barriers and next neighbor energy values used for KMC simulations as well as literature references and DFT results from the present study (highlighted with a star ). All values are given in eV.

		KMC		Literature values & DFT
	E Ni/Ni→Ni	0.65		0.645 24 , 0.631 25
	E Ni/Ni→STO	1.3		-
	E Ni/STO→STO	1.0	Ni / SrO	0.67
			Ni / TiO 2	2.37 , 1.8 , 1.4 , 0.55
	E STO/STO→STO	0.5		0.6 26 , 0.97 27 , 0.3 28
			O/SrO:	0.53, 0.64 29 , 0.81 30
			O/TiO 2 :	0.68 30
			Sr/SrO:	0.77, 0.83 29
	∆E Ni-Ni	0.35		0.325 24 , 0.383 25
	∆E Ni-STO	0.1		-
	∆E STO-STO	0.7		0.5 28

J o u r n a l N a me , [ y e a r ] , [ v o l . ] ,

1-10 J o u r n a l N a me , [ y e a r ] , [ v o l . ] ,

[START_REF] Kabashin | Plasmonic nanorod metamaterials for biosensing[END_REF][START_REF] Yao | Optical negative refraction in bulk metamaterials of nanowires[END_REF][START_REF] Piraux | Templategrown NiFe/Cu/NiFe nanowires for spin transfer devices[END_REF][START_REF] Kawasaki | Photoelectrochemical water splitting enhanced by self-assembled nanopillars embedded in an oxide semiconductor photoelectrode[END_REF][START_REF] Yang | Preparation and magnetic property of Fe nanowire array[END_REF][START_REF] Qin | Magnetic force microscopy of magnetic domain structure in highly ordered co nanowire arrays[END_REF][START_REF] Kawai | Magnetic properties of anodic oxide coatings on aluminum containing electrodeposited Co and Co-Ni[END_REF][START_REF] Masuda | Ordered metal nanohole arrays made by a two-step replication of honeycomb structures of anodic alumina[END_REF][START_REF] Fert | Magnetic nanowires[END_REF][START_REF] Schuler | Huge metastable axial strain in ultrathin heteroepitaxial vertically aligned nanowires[END_REF]

1-10 J o u r n a l N a me , [ y e a r ] , [ v o l . ] ,

quired with a JEOL JEM 2100F equipped with a field-emission gun (FEG) and operated at 200 kV.

Acknowledgements

We are indebted to F. Breton for skillful help with the PLD setup, J.-M. Guigner of IMPMC (CNRS-UPMC) is acknowledged for providing access to the TEM facilities. M. Hennes acknowledges financial support from the French Embassy in Berlin ("Service pour la Science et la Technologie") and Campus France. We thank the Center for Information Services and High Performance Computing (ZIH), TU Dresden for providing computing time. This work has been funded in parts by the LabEx Matisse (projects ANR-11-IDEX-0004-02/10-LABX-0067 -MATISSE)

Conflicts of interest

There are no conflicts of interest to declare


Tasneem Imam

Justine S Gibson

Suman Das Gupta

Mohammad Foysal

Shetu B Das

Md Ahasanul Hoque

Guillaume Fournié

Joerg Henning
email: j.henning@uq.edu.au

Social and cognitive factors influencing commercial chicken farmers' antimicrobial usage in Bangladesh

Adapting the Social Cognitive Theory framework, we conducted a cross-sectional study on 137 commercial chicken farms in Bangladesh to investigate factors influencing the behaviour of farmers towards the application of antimicrobials to their birds. Almost all farmers used antimicrobials to treat poultry diseases, while 38.6% also were using them to promote healthy growth of chickens and 10.2% to increase egg production or improve meat quality. Using Structural Equation Modeling (SEM), we identified that inappropriate usage of antimicrobials (behaviour) was strongly driven by farmers' short-term goals to maintain the health of their chickens in a production cycle (β = 0.813, p = 0.029), rather than long-term concerns. Farmers' perception about their ability to control antimicrobial administration based on their skills and opportunities (self-efficacy) marginally influenced the shortterm goals of antimicrobial usage (β = 0.301, p = 0.073). The results of this study can be used to develop targeted education programs for farmers, to reduce the application of antimicrobials in their poultry flocks.

Antimicrobial resistance is considered as a global threat to human health [START_REF] Balsalobre | An overview of antimicrobial resistance and its public health significance[END_REF] and action plans to tackle this problem have been developed by the World Health Organisation (WHO) [START_REF]Global Action Plan on Antimicrobial Resistance[END_REF] . To investigate the awareness towards antimicrobial resistance among public health and agriculture experts as well as policymakers, WHO conducted a survey of 9772 participants from 12 countries (China, Vietnam, India, Indonesia, Egypt, Sudan, Russian Federation, Siberia, Barbados, Mexico, Nigeria and South Africa) between September and October 2015 [START_REF] Who | Antibiotic Resistance: Multi-country Public Awareness Survey[END_REF] . About 57% of the respondents indicated that 'there is not much people like them can do to stop resistance development' and 44% believed that 'resistance is only a problem for those who take antimicrobials regularly' . The report also highlighted that people of lower income countries are less aware of antimicrobial resistance compared to people of higher income countries [START_REF] Who | Antibiotic Resistance: Multi-country Public Awareness Survey[END_REF] .

Inappropriate use of antimicrobials in food animals has contributed to the emergence of antimicrobial resistance [START_REF] Löhren | Guide to Antimicrobial Use in Animals[END_REF] . Misconceptions about antimicrobial usage are common among farmers, and disease occurrence due to poor biosecurity [START_REF] Raasch | Association between antimicrobial usage, biosecurity measures as well as farm performance in German farrow-to-finish farms[END_REF] and a lack of strategic vaccinations 6 might influence farmers' behaviour towards antimicrobial applications. For example, some farmers believe that antimicrobials could improve the immunity of chickens and, that antimicrobial usage for disease prevention or growth promotion may not result in antimicrobial resistance [START_REF] Nuangmek | Knowledge, attitudes and practices toward antimicrobial usage: A cross-sectional study of layer and pig farm owners/managers in Chiang Mai, Lamphun, and Chonburi provinces, Thailand[END_REF] . Furthermore, some farmers believe that antimicrobials should be administered without veterinarians' advice [START_REF] Nuangmek | Knowledge, attitudes and practices toward antimicrobial usage: A cross-sectional study of layer and pig farm owners/managers in Chiang Mai, Lamphun, and Chonburi provinces, Thailand[END_REF] and that preventive usage of antimicrobial is more important than improving biosecurity [START_REF] Rimi | Biosecurity conditions in small commercial chicken farms, Bangladesh 2011-2012[END_REF] . Other perceptions of farmers are that antimicrobials can be prescribed by traders [START_REF] Masud | Drivers of antibiotic use in poultry production in Bangladesh: Dependencies and dynamics of a patron-client relationship[END_REF] , that the use of multiple antimicrobials is important to control diseases on farms [START_REF] Nuangmek | Knowledge, attitudes and practices toward antimicrobial usage: A cross-sectional study of layer and pig farm owners/managers in Chiang Mai, Lamphun, and Chonburi provinces, Thailand[END_REF] , that antimicrobial usage on food animals does not have any impact on human health [START_REF] Martino | Farmers' attitudes towards antimicrobial use and awareness of antimicrobial resistance: A comparative study among turkey and rabbit farmers[END_REF] and that antimicrobials can be used without adhering to withdrawal periods [START_REF] Xu | Antibiotic use in chicken farms in northwestern China. Antimicrob[END_REF] .

The decision-making process of farmers to implement or to not implement appropriate management practices is complex and different approaches have been used to analyse farmer's behaviours and the factors associated with these behaviours. The knowledge, attitude, and practice (KAP) approach has been applied in the context of antimicrobial usage [START_REF] Nuangmek | Knowledge, attitudes and practices toward antimicrobial usage: A cross-sectional study of layer and pig farm owners/managers in Chiang Mai, Lamphun, and Chonburi provinces, Thailand[END_REF][START_REF] Hu | Knowledge, attitude, and practice with respect to antibiotic use among Chinese medical students: A multicentre crosssectional study[END_REF][START_REF] Kalam | Knowledge, attitudes, and common practices of livestock and poultry veterinary practitioners regarding the AMU and AMR in Bangladesh[END_REF] . KAP studies are popular as they are easy to design, less time consuming and less costly than in-depth qualitative studies [START_REF] Stone | The use and misuse of surveys in international development: An experiment from Nepal[END_REF][START_REF] Launiala | How much can a KAP survey tell us about people's knowledge, attitudes and practices? Some observations from medical anthropology research on malaria in pregnancy in Malawi[END_REF] . However, KAP approaches has been criticized by social scientists as the behaviour of a person represents interlinked characteristics of this person's knowledge, beliefs, emotions and values, which are not as easily captured in responses to separate individual questions in a KAP questionnaire [START_REF] Launiala | How much can a KAP survey tell us about people's knowledge, attitudes and practices? Some observations from medical anthropology research on malaria in pregnancy in Malawi[END_REF] . Furthermore, knowledge (which is a key component evaluated in KAP studies) is only one of many factors that influence how people seek to address a problem; thus, a direct relationship between knowledge and behaviour cannot be assumed. To change behaviour, extension and intervention programmes need to address additional factors ranging from sociocultural to environmental and economic components, which are usually not captured in KAP studies [START_REF] Smith | On the limited utility of KAP-style survey data in the practical epidemiology of AIDS, with reference to the AIDS epidemic in Chile[END_REF][START_REF] Cleland | A critique of KAP studies and some suggestions for their improvement[END_REF][START_REF]The Shortcoming of KAP Studies[END_REF][START_REF]The Shortcoming of KAP Studies[END_REF][START_REF] Andrade | Designing and conducting knowledge, attitude, and practice surveys in psychiatry: Practical guidance[END_REF] .

On the other hand, theoretical concepts such as the Health Belief Model 21 , Theory of Reasoned Action 22 , Theory of Planned Behaviour [START_REF] Ajzen | The theory of planned behaviour: Reactions and reflections[END_REF] and Protection Motivation Theory 24 and Social Cognitive Theory [START_REF] Bandura | Health promotion by social cognitive means[END_REF][START_REF] Bandura | Social Foundations of Thought and Action: A Social Cognitive Theory[END_REF] represent applied psychological frameworks that do allow to comprehensively analyse behaviours and factors influencing them [START_REF] Bandura | Health promotion by social cognitive means[END_REF] . The 'Social Cognitive Theory' in particular has been used to describe social and cognitive factors that impact human behaviour [START_REF] Bandura | Health promotion by social cognitive means[END_REF][START_REF] Bandura | Social Foundations of Thought and Action: A Social Cognitive Theory[END_REF] . This framework has also been used to study populations in which interventions of 'healthier habits' were introduced. For example, it has been applied to describe how technological innovations can change the behaviour of diabetic people [START_REF] Bandura | Health promotion by social cognitive means[END_REF] , how vocational services for people with psychiatric disorders can be improved [START_REF] Fabian | Social cognitive theory of careers and individuals with serious mental health disorders: Implications for psychiatric rehabilitation programs[END_REF] , how web-based learning systems for students can be enhanced [START_REF] Wang | The application of social cognitive theory to web-based learning through NetPorts[END_REF] , and how behaviour relating to physical activities can be improved [START_REF] Oyibo | Social cognitive determinants of exercise behavior in the context of behavior modeling: A mixed method approach[END_REF] . This framework has also been applied to investigate farmers' behaviour towards water conservation [START_REF] Yazdanpanah | Predicting farmers' water conservation goals and behavior in Iran: A test of social cognitive theory[END_REF] and to explore the usage of climate forecasts to make decisions about crop management [START_REF] Jaberi | Analysis the role of Psychological factors on intention to apply environmental and meteorological information by farmers in Dehloran Town (The combined application of social cognition theory and technology acceptance Model)[END_REF] .

Therefore, we considered the 'Social Cognitive Theory' as a flexible and applied psychological framework to evaluate the behaviour of commercial farmers towards administration of antimicrobials in their chicken flocks.

Results

The study population included 137 commercial layer and broiler chicken farmers operating in Chattogram, Bangladesh, with 83 farmers raising broiler chickens and 54 laying hens. Most broiler (98.8%, 82/83) and all layer farmers (100.0%, 54/54) were male. Most layer farmers (61.1%, 33/54) and about half of the broiler farmers (49.4%, 41/83) had ≥ 10 years of farming experience. More layer famers (92.6%, 50/54) had a secondary level of education compared to broiler farmers (78.3%, 65/83) [START_REF] Imam | A cross-sectional study of antimicrobial usage on commercial broiler and layer chicken farms in Bangladesh[END_REF] .

Frequency statistics of all the responses collected on a five-point Likert scale for each 'observed variable' under the 'latent constructs' are presented in Table S1, while the frequency statistics of the responses for each 'observed variable' maintained in the final Structural Equation Model (SEM) under the 'latent constructs' (behaviour, selfefficacy and goals) are shown in Table 1. The behaviour of farmers to use antimicrobials in their chicken flocks was the outcome 'latent construct' .

Behaviour. About half (51.1%, 70/137) of farmers either agreed or strongly agreed that they used an increased dose of antimicrobials when they observed more chicken getting sick or dying (Table 1). About a third of farmers (32.8%, 45/137) acknowledged to stock a range of antimicrobials on their farms even if there was no need to use them.

Self-efficacy.

The majority of farmers (94.8%, 130/137) indicated that an enforcement of stronger laws is needed to reduce antimicrobial usage. Most farmers (84.6%, 116/137) also indicated that they would invest time and money to further improve farm hygiene and biosecurity to reduce the usage of antimicrobials on their farms. Goals. Almost all farmers (99.3%, 136/137) highlighted that antimicrobials help chickens to recover from disease. About a third (38.6%, 53/137) of farmers mentioned that antimicrobials promote a healthy growth of chickens, while a small proportion of them (10.2%, 14/137) indicated that antimicrobials help to increase the egg production or improve the quality of the chicken meat.

Structural Equation Modeling (SEM)

Using confirmatory factor analysis (CFA) in the measurement part of the SEM, no significant association was identified for any of the 'observed variables' with the latent construct socio-structural factors (p > 0.05). Therefore, the latent construct socio-structural factors was not included in the structural part of the SEM. Using path analysis in the structural part of the SEM, the latent constructs outcome expectations, goals, selfefficacy, and behaviour (as the outcome variable) were considered. The latent construct outcome expectations did not significantly (p = 0.501) influence farmers' behaviour to use antimicrobials on their farms and was therefore excluded.

The final SEM path is shown in Fig. 1. The results indicate that behaviour of commercial chicken farmers to increase the usage of antimicrobials or to have a range of antimicrobials available for usage on farms, increased with their (short-term) goals to improve the health of their chickens (β = 0.813, p = 0.029). Self-efficacy had a marginal impact on the goals of farmers to the health of their chickens (β = 0.301, p = 0.073), and had no significant direct impact on behaviour of farmers related to antimicrobial usage.

Overall, the data fit the model well (χ 2 = 8.724, p = 0.647; RMSEA < 0.01, CFI = 1.000, SRMR = 0.045).

Discussion

To the best of our knowledge, this is the first published research study that used the 'Social Cognitive Theory' framework to explore social and cognitive factors influencing farmers' behaviour towards antimicrobial administration on commercial chicken farms.

Overall, this study found that farmers' behaviour is primarily directed by their behavioural goals. Commercial chicken farmers were concerned about disease occurrence in their chicken flocks, and farmers' goals to maintain the health of their chickens was driving their use of antimicrobials. These results may explain the large number of antimicrobials applied on these farms [START_REF] Imam | A cross-sectional study of antimicrobial usage on commercial broiler and layer chicken farms in Bangladesh[END_REF] and might help to eludicate similar high usages reported from other Asian countries such as India, Nepal, Thailand, China and Sri Lanka [START_REF] Goutard | Antimicrobial policy interventions in food animal production in South East Asia[END_REF] .

Bandura highlighted that individual goals are considered 'effective' in adapting habits. For example, goals were the most important determinant in developing healthy behaviours such as stopping smoking, reducing weight and performing exercise [START_REF] Alexy | Goal setting and health risk reduction[END_REF] . Our study highlighted that farmers created 'short-term' attainable goals [START_REF] Bandura | Health promotion by social cognitive means[END_REF] , by focussing mainly on poultry health outcomes and thereby immediate benefits in the current production cycle. Indeed, AbbreviaƟons ( Beh, SEff and Goal ) represent individual statements in the quesƟonnaire for which responses were captured in the interview (see Table S1 for more details). recurrent beneficial feedback [START_REF] Bandura | Social Foundations of Thought and Action: A Social Cognitive Theory[END_REF] from antimicrobial administration over multiple production cycles might have 'psychologically' shaped farmers' behaviour towards inappropriate antimicrobial application. On the contrary, people only tend to change their behaviour when the outcome of their behavioural set goals is dissatisfactory [START_REF] Wood | Task Complexity as a moderator of goal effects: A meta-analysis[END_REF] . Thus, the administration of antimicrobials could be considered as a 'comfortable and convenient' solution for farmers (which might therefore be a behaviour that farmers are unwilling to change) as antimicrobials are readily available over-the-counter without a prescription [START_REF] Goutard | Antimicrobial policy interventions in food animal production in South East Asia[END_REF] or directly through feed and chick traders [START_REF] Masud | Drivers of antibiotic use in poultry production in Bangladesh: Dependencies and dynamics of a patron-client relationship[END_REF] while being easily applied to chickens through feed or drinking water [START_REF] Diarra | Antibiotics in Canadian poultry productions and anticipated alternatives[END_REF] . Farmers' intentions of executing rather 'short-term' goals have been also illustrated by the fact, that farmers' responses under outcome expectations, which represent more 'long-term' goals (and concerns), did not influence their behavioural pattern towards antimicrobial usage.

According to the 'Social Cognitive Theory' , goals are determined by self-efficacy [START_REF] Bandura | Health promotion by social cognitive means[END_REF] . In consistency with this theory, we found that self-efficacy marginally impacted farmers' goals regarding antimicrobial application. It has been described previously that self-efficacy influences peoples' thinking [START_REF] Bandura | Effect of perceived controllability and performance standards on self-regulation of complex decision making[END_REF] and thereby their goal setting to demonstrate an actual behaviour [START_REF] Holman | Perceived self-efficacy in self-management of chronic disease[END_REF][START_REF] Plotnikoff | Physical activity and Social Cognitive Theory: A test in a population sample of adults with type 1 or type 2 diabetes[END_REF] . We found that most farmers were willing to invest time and money to improve farm biosecurity and they were also in support of strict laws to limit antimicrobial usage.

Previous research has highlighted that poultry farmers in Bangladesh are unable to control disease occurrences themselves through the administration of antimicrobials [START_REF] Kabir | Prevalence of poultry diseases in Gazipur district of Bangladesh[END_REF] , but also that antimicrobials are frequently administered to chickens in the absence of clinical signs (24.8% of farms) and without adhering to withholding periods (83.3% of layer and 36.1% of broiler farms) [START_REF] Imam | A cross-sectional study of antimicrobial usage on commercial broiler and layer chicken farms in Bangladesh[END_REF] . Therefore, farmers ability to perform a desired behaviour, of reduced antimicrobial usage, requires adequate training, demonstration, and reinforcement [START_REF] Bandura | Health promotion by social cognitive means[END_REF] .

We did not identify 'observed variables' that significantly influenced the latent construct 'socio-structural factors', which was therefore not included in the final model. It could have been the case that 'socio-structural factors' were not sufficiently described by the recorded 'observed variables and other variables might need to be considered in future research. For example, 'socio-structural factors' might be related to the availability of vaccinations for chickens [START_REF] Alders | Challenges and constraints to vaccination in developing countries[END_REF] , the influence of representatives from pharmaceutical companies on farmers [START_REF] Masud | Drivers of antibiotic use in poultry production in Bangladesh: Dependencies and dynamics of a patron-client relationship[END_REF] , lack of financial capital [START_REF] Mengesha | Biophysical and the socio-economics of chicken production[END_REF] or the opinions of neighbouring farmers [START_REF] Manyi-Loh | Antibiotic use in agriculture and its consequential resistance in environmental sources: Potential public health implications[END_REF] . Also, due to the cross-sectional nature of this research, we could not confirm (for example through observations) the reported behaviour of farmers, so a validation of the hypothesized causal relationships between 'latent constructs' could not be performed. A qualitative data collection approach with in-depth interviews would be helpful to explore the identified behaviour of farmers in more detail.

Overall, the research presented here highlighted the short-term goal oriented behaviour of commercial poultry farmers in Bangladesh. These observations are valuable for policy makers for designing extension programs aiming to implement behaviour changes in regard to antimicrobial administration. However, behaviours of individuals are generally difficult to modify [START_REF] Kanfer | Motivation and cognitive abilities: An integrative/aptitude^treatment interaction approach to skill acquisition[END_REF] and innovative strategies are required. WHO has developed a guide for Tailoring Antimicrobial Resistance Programmes (TAP) in order to determine perceived barriers and drivers of behaviour change [START_REF] Who | The Fight Against Antimicrobial Resistance: Benefits from Behavioural Insights[END_REF][START_REF] Schreijer | Tailoring AMR strategies (TAP): When knowledge is not enough[END_REF] . Behavioural insights specialists working within the TAP highlighted the importance of cultural and social contexts for changing the behaviour of target populations [START_REF] Who | The Fight Against Antimicrobial Resistance: Benefits from Behavioural Insights[END_REF] . Lessons from the TAP are useful for designing programs to change the behaviour of poultry farmers in Bangladesh. For example, farmers are less likely to know the generic names of antimicrobials and they are more familiar with the trade names [START_REF] Nuangmek | Knowledge, attitudes and practices toward antimicrobial usage: A cross-sectional study of layer and pig farm owners/managers in Chiang Mai, Lamphun, and Chonburi provinces, Thailand[END_REF] . Therefore, it is important that extension programs consider the knowledge and social background of Bangladeshi poultry farmers, and that effective and cultural-sensitive communication approaches are developed and applied. There are some existing initiatives in Bangladesh under which training of poultry farmers could be delivered. For example, the Department of Livestock Services (DLS) has set-up the Upazila to Community (U2C) initiative, which aims to empower women in rural communities to improve livestock production and disease control [START_REF] Dls | One Health in Action: DLS Initiatives on AMR/AMU[END_REF] . Furthermore, the Bangladesh AMR Response Alliance (BARA) was created to involve both government agencies and private health professionals to ensure responsible use of antimicrobials at the community level [START_REF] Dls | One Health in Action: DLS Initiatives on AMR/AMU[END_REF] . Tapping into these existing community networks would provide opportunities to deliver training on poultry diseases, biosecurity practices and antimicrobial usage, and overall improve poultry production and might be helpful to change the short-term goal oriented behaviour of commercial chicken farmers.

Materials and methods

The 'Social Cognitive Theory' framework. The 'factors' or components of the 'Social Cognitive Theory' framework are self-efficacy, goals, outcome expectations and socio-structural factors, which directly or indirectly influence behaviour [START_REF] Bandura | Health promotion by social cognitive means[END_REF] . Figure 2 depicts the hypothesized paths or relationships between individual factors and how they regulate, or impact behaviour as described by Bandura in 2004 [START_REF] Bandura | Health promotion by social cognitive means[END_REF] .

While self-efficacy measures the ability of people to successfully overcome challenges to perform a behaviour, outcome expectations measure the expected favourable and unfavourable effects of the behaviour including positive and negative self-evaluative reactions [START_REF] Bandura | Health promotion by social cognitive means[END_REF] . Goals, which include short-term attainable objectives guide people's actions [START_REF] Bandura | Health promotion by social cognitive means[END_REF] , while socio-structural factors represent the perceived facilitators and obstacles that influence a behaviour [START_REF] Bandura | Health promotion by social cognitive means[END_REF] . Bandura emphasized the importance of self-efficacy to directly influence behaviour of humans, but also to influence the other factors [START_REF] Bandura | Health promotion by social cognitive means[END_REF] .

We have conceptualized these 'factors' of the 'Social Cognitive Theory' in relation to farmer's behaviour in administering antimicrobials to their chicken flocks and defined these 'factors' as follows:

1. Perceived self-efficacy relates to the belief of farmers that they could control the usage of antimicrobials based on their own assessment of their skills and opportunities. For example, the statement 'I believe that stronger laws and enforcement of the law are needed to reduce antimicrobial usage' belongs to self-efficacy.

2. Outcome expectations relates to farmers' perceived benefits from using antimicrobials and the effect that antimicrobial administration will have on poultry health, production and human health. An example for an outcome expectation would be the statement ' Antimicrobial residues in chicken meat will not harm humans' . 3. Goals represent achievable short-term objectives that encourage farmers to administer antimicrobials. ' Antimicrobials help to increase egg production or improve the quality of the chicken meat' is an example statement for Goals. 4. Socio-structural factors are perceived external facilitators and impediments that encourage or deter farmers to use antimicrobials. 'I am bound to take advice from feed traders because I owe them money (they provide day old chicks, antimicrobials, and feed)' illustrates a statement for socio-structural factors.

Study design.

A cross-sectional study was used to collect data on farmers' usage and perception of administering antimicrobials to their layer and broiler chicken flocks in the Chattogram district of Bangladesh. The Chattogram district was selected because it is a centre for commercial chicken production in Bangladesh [START_REF] Moyen | A large-scale study of a poultry trading network in Bangladesh: Implications for control and surveillance of avian influenza viruses[END_REF] . First, a sampling frame of 1,748 commercial chicken farms in this district was developed with the help of the Bangladesh District Livestock Services (DLS), feed and chick traders, pharmaceutical representatives, and government and private practitioners [START_REF] Gupta | Patterns of Avian Influenza A (H5) and A (H9) virus infection in backyard, commercial broiler and layer chicken farms in Bangladesh[END_REF] . From this sampling frame, 140 commercial chicken farmers from 8 upazilas (sub-districts) selected using simple random sampling (using syntax RANDBETWEEN in Microsoft Excel). Farmers were interviewed between February and May 2019 and 137 of these 140 farmers reported of using antimicrobials and these 137 farmers were in the further analysis. Further details about the sampling approach are provided in [START_REF] Imam | A cross-sectional study of antimicrobial usage on commercial broiler and layer chicken farms in Bangladesh[END_REF] .

Questionnaire.

A structured questionnaire was developed to collect data on 'factors' of the 'Social Cognitive Theory' framework. Each 'factor' was evaluated by a series of statements (' observed variables') for which farmers provided responses on a 5-point Likert scale: 'Strongly disagree' , 'Disagree' , 'Do not know' , ' Agree' , and 'Strongly agree' .

Data analysis.

Structural Equation Modeling (SEM) was used to analyse the dataset. The SEM is comprised of two parts, a measurement and a structural part [START_REF] Beaubien | Principles and practice of structural equation modeling[END_REF] . In the measurement part of the SEM, statements (or 'observed variables') are used to build each of the separate 'factors' according to 'Social Cognitive Theory' . These 'factors' are termed 'latent constructs' in SEMs. Confirmatory Factor Analysis (CFA) was then applied to identify which of the 'observed variables' would be included in each 'latent construct' . In the structural part of the SEM, path analysis was used to describe the relationship between the causal 'latent constructs' (i.e. self-efficacy, outcome expectations, goals, and socio-structural factors) and how they impacted the outcome 'latent construct' behaviour (which represented the behaviour of farmers towards antimicrobial usage on their farms). To ensure all 'observed variables' are scaled in the same direction [START_REF] Ajzen | Action Control: From Cognition to Behaviour[END_REF] , some of the original responses were recoded. The conceptual framework with all collected 'observed variables' informing each 'latent construct' and the relationships between 'latent constructs' is displayed in Fig. S1.

A p-value ≤ 0.05 was selected as cut-off to include 'observed variables' under each of the 'latent constructs' in the CFA and a p-value ≤ 0.1 was selected as cut-off to maintain 'latent constructs' in the path analysis.

The overall model fit was assessed by the chi-square (χ) 2 statistic with a p-value < 0.05 as an indicator of good fit [START_REF] Hu | Cutoff criteria for fit indexes in covariance structure analysis: Conventional criteria versus new alternatives[END_REF] . The root mean square error of approximations (RMSEA) was also used, with values < 0.05 indicating a good fit and values up to 0.08 indicating an acceptable fit [START_REF] Browne | Alternative ways of assessing model fit[END_REF] . Furthermore, the comparative fit index (CFI) with

Figure 1 .

 1 Figure 1. Final Structural Equation Model describing farmers' behaviour towards antimicrobial administration on commercial chicken farms in Chattogram, Bangladesh that is based on the 'Social Cognitive Theory' framework 25 . 'Observed variables' are presented in rectangles and the 'latent constructs' are presented in ovals. Both 'd' and 'e' represent errors of measurements, while 'z' represents the residuals of the latent constructs.

Figure 2 .

 2 Figure 2. Hypothesized Structural Equation Modeling paths describing farmers' behaviour towards the administration of antimicrobials in commercial chicken flocks in Chattogram, Bangladesh.

Table 1 .

 1 Percentage (N) of responses to statements ('observed variables') provided by commercial layer and broiler chicken farmers in Chattogram, Bangladesh. Abbreviations in brackets (Beh, SEff and Goal) represent individual statements in the questionnaire for which responses were captured in the interview (see TableS1for more details). *Recoded for analysis.

		Strongly disagree Disagree	Do not know Agree	Strongly agree
	Statement	% (N)	% (N)	% (N)	% (N)	% (N)
	Behaviour
	I am increasing the dosage of antimicrobials when I am experiencing more chicken getting sick or dying (Beh1)*	5.1 (7)	43.8 (60)	0.0 (0)	48.9 (67)	2.2 (3)
	I always have a range of antimicrobials available on my farm, even if I do not used them all (Beh3)*	5.8 (8)	61.3 (84)	0.0 (0)	32.8 (45)	0.0 (0)
	Self-efficacy
	I believe that stronger laws and enforcement of the law are needed to reduce antimicrobial usage (SEff3)	0.0 (0)	0.0 (0)	5.1 (7)	47.4 (65)	47.4 (65)
	I would invest time and money to further improve farm hygiene and biosecurity to reduce the usage of antimicrobial on my farm (SEff4)	0.0 (0)	10.9 (15)	4.4 (6)	64.2 (88)	20.4 (28)
	Goals
	Antimicrobials lead to a healthy growth of chickens (Goal1)*	3.6 (5)	55.5 (76)	2.2 (3)	32.8 (45)	5.8 (8)
	Antimicrobials help chickens to recover from disease (Goal2)*	0.0 (0)	0.0 (0)	0.7 (1)	87.6 (120) 11.7 (16)
	Antimicrobials help increasing egg production or improving the quality of the chicken meat (Goal3)*	5.1 (7)	73.0 (100) 11.7 (16)	8.0 (11)	2.2 (3)

Scientific Reports | (2023) 13:572 | https://doi.org/10.1038/s41598-022-26859-8

Acknowledgements

We are grateful to the farmers for participating in the research. Also, we thank the Chattogram Veterinary and Animal Sciences University (CVASU) research team for helping with the data collection. We also acknowledge the support provided by GF, MH, and JH through the UKRI GCRF One Health Poultry Hub (Grant no. BB/ S011269/1), which represents 1 out of 12 interdisciplinary research hubs funded under the UK government's Grand Challenge Research Fund Interdisciplinary Research Hub initiative.

Funding

This field data collection was supported by the BALZAC research program (Behavioural adaptations in live poultry trading and farming systems and zoonoses control in Bangladesh, BB/L018993/1), a joint research initiative between the Biotechnology and Biological Sciences Research Council, the Defence Science and Technology Laboratory, the Department for International Development, the Economic and Social Sciences Research Council, the Medical Research Council, and the Natural Environment Research Council. TI was supported by an Australia Awards Scholarship.

Data availability

The raw data supporting the conclusions of this research will be made available upon request by the first author of this publication, Tasneem Imam (t.imam@uq.edu.au).

www.nature.com/scientificreports/ values > 0.95 indicating very good fit and ≥ 0.90 an acceptable fit [START_REF] Hu | Cutoff criteria for fit indexes in covariance structure analysis: Conventional criteria versus new alternatives[END_REF] was also applied. In addition, standard root mean square residuals (SRMR) values ≤ 0.05 were considered indicative of a close-fitting model while values between 0.05 up to 0.10 were suggesting acceptable fit [START_REF] Pituch | Applied Multivariate Statistics for the Social Sciences: Analyses with SAS and IBM's SPSS 6th edn[END_REF] . Descriptive data analysis was conducted in STATA 16 (StataCorp®, 2019) while the SEM was developed using AMOS 27 (IBM® SPSS® Amos™ 27, 2020).

Ethics approval.

Human Ethics Approval for the interviews was obtained from the University of Queensland Institutional Human Ethics Committee on the 7 December 2018 (Approval number: 2018002266). The outlined research with farmers was carried out in accordance with relevant guidelines and regulations (Declaration of Helsinki) and informed consent was obtained from all participants (none of the participants was under 18 years of age).

Author contributions

J.H., G.F., and M.H. designed the research study and obtained the funding for the field research. The questionnaire was developed by TI with inputs from J.H., J.G., and S.G. The data collection strategy was developed by J.H., G.F., M.H., T.I., and S.G. Data collection was conducted by M.F. and S.D. T.I. and S.G. conducted data analysis under the guidance of J.H., G.F., and J.G. T.I. prepared the initial draft, figures, tables, and Supplementary Materials, with edits provided by J.H. and J.G. All authors have read, contributed to, and approved the final version of the manuscript.

Competing interests

The authors declare no competing interests.

Additional information

Supplementary Information

The online version contains supplementary material available at https:// doi. org/ 10. 1038/ s41598-022-26859-8.

Correspondence and requests for materials should be addressed to J.H.

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