Quantitative Differences in Sulfur Poisoning Phenomena over

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Quantitative Differences in Sulfur Poisoning Phenomena over Ru and Pd: An attempt to deconvolute geometric and electronic poisoning effects using model catalysts Amy Kolpin, Glenn Jones, Simon Jones, Weiran Zheng, James Cookson, Andrew P.E. York, Paul John Collier, and Shik Chi Edman Tsang ACS Catal., Just Accepted Manuscript • DOI: 10.1021/acscatal.6b02765 • Publication Date (Web): 06 Dec 2016 Downloaded from http://pubs.acs.org on December 8, 2016

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Quantitative Differences in Sulfur Poisoning Phenomena over Ru and Pd: An attempt to deconvolute geometric and electronic poisoning effects using model catalysts Amy Kolpin,a Glenn Jones,b Simon Jones,a Weiran Zheng,a James Cookson,b Andrew P.E. York,b Paul J. Collier,b Shik Chi Edman Tsang,a* a

Wolfson Catalysis Centre, Department of Chemistry, University of Oxford, Oxford, OX1 3QR, UK b

Johnson Matthey Technology Centre, Blount’s Court, Sonning Common, Reading, RG4 9NH

*Correspondence: [email protected]. ABSTRACT: Sulfur poisoning over noble metal catalysts has traditionally been regarded as very complex and precluding from easy rational understanding due to the problems of interference from using different supports, inability of controlling coverage due to non-uniform metal particle size, intrinsic size/shape effect of metal component, etc. Here, high quality PVP polymer-supported ruthenium and palladium model nanocatalysts using without solid support are equivalently modified with pre-adsorbed mercaptoethanol over a range of surface concentrations in order to compare sulfur poisoning effects on the two important noble metals commonly used in industry. A typical consecutive hydrogenation reactions of alkyne to alkene and then to alkane is studied under mild reaction conditions in the liquid phase. The first stage alkyne hydrogenation is well-known to be surface insensitive due to strong adsorption of alkyne on both metals. However the second stage, surface sensitive hydrogenation/isomerisation of weakly adsorbed alkenes are highly influenced by perturbations in metal surface electronic states induced by sulfur adsorbates. Using a combination of 13C NMR, FTIR measurements of chemisorbed CO, kinetic products analysis and DFT calculations, the electronic and geometric components of sulfur poisoning can be assigned in near quantitative manner for the first time, over these two metal nanocatalysts. It is found that this sulfur adsorbate dwells preferentially on terrace sites for both metals at high coverage, causing deactivation by surface site blockage for the alkyne hydrogenation. The adsorbate can also deplete electron density from the metal surface (mixing with higher vacant band states of sulfur). As a result, reduction in adsorption strength for alkenes in the second stage hydrogenation, leading to deactivation by electronic effects, is observed. This component is shown to contribute more significantly to the total deactivation for palladium (electron rich metal) than ruthenium (electron poor metal). At 60% sulfur coverage on Pd, the electronic contribution to surface adsorption can be totally cancelled out. This work clearly shows that the differing nature of metals can result in very different degrees of geometric and electronic deactivation upon sulfur adsorption over 2-3nm size range without any interference from solid support, particle size/shape variations, giving important insights to develop more sulfur tolerant catalysts in future. Keywords: metal nanoparticle, sulpfur poison, surface sensitive, deactivation, hydrogenation 1

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INTRODUCTION

In current industrial practise, catalysts are involved in the production of over 60% of all chemicals, and 90% of chemical processes rely on catalysts in some way1,2. However, billions of dollars are lost every year due to reactor shutdown and catalyst replacement as a result of deactivation processes3. Some of this cost is unavoidable, as all industrial catalysts will eventually need to be replaced, but this decay is often dramatically accelerated due to catalyst deactivation from reactant stream contaminants3,4. Poisoning is one of the most costly and complicated deactivation mechanisms to understand given the wide range of potential poisons (such as the group VA to VIIA elements, small molecules such as CO and NH3, and numerous heavy metals) and the wide range of reactions affected (including ammonia synthesis, hydrogenation/dehydrogenation reactions, steam reforming, methanol synthesis, and oxidation of CO and hydrocarbons)5. Classically regarded as a strong catalyst poison, sulfur appears to exhibit a more subtle and complicated interaction with a range of catalytic systems upon closer examination. The term “poison” actually only carries an operational definition based on perceived negative interactions between a specific poison, catalytic system, and set of reaction conditions3. While the negative impacts of sulfur poisoning are well documented in the literature, such as the serious and irreversible loss in the activity of nickel-based methanation catalysts6–8, a growing number of reports exist highlighting the potentially beneficial influence of sulfided catalysts in controlling reaction activities and selectivities. Marshall et al. recently demonstrated a dramatic increase in selectivity for hydrogenation of epoxybutene over palladium catalysts modified by thiolate selfassembled monolayers (SAM’s)9. Thus, the modification effects induced by sulfur adsorption are still unclear, but may represent a structural or electronic modification to the fundamental physiochemical properties of these materials3. In the past, research has often focused on a two-pronged approach for the investigation of catalyst deactivation. From a component level, theoretical modelling and ultrahigh vacuum studies provide a wealth of detailed information on the fundamental interactions between poisons and the metal surface, allowing for comparisons to be drawn across systems. Literature reports detail theoretical studies of sulfur adsorption on a range of transition metals including W10, Mo11, Rh11,12, Ru13, Pd14,15, Pt16, Cu17, and Ni18. However, limitations on theoretical modelling still exist and such results often prove difficult to apply to complex reaction systems19. The systemlevel approach focuses on observations of poisoning under reaction conditions, often through observing losses in catalytic activity and/or selectivity. However, in this case, the wide range of reaction conditions limit intra system comparisons as the effects of experimental inconsistencies on metal-sulfur interactions cannot be excluded. For example, examination of sulfur poisoning of ruthenium catalysts often employs harsh reaction conditions of high temperatures and pressures20. As such, there is a need for a novel combination of experimental techniques operating under mild conditions over careful ‘model’ materials to allow for direct comparison of the fundamental effects of sulfur modification across catalytic systems with minimal experimental variation. This research seeks to elucidate and compare the specific electronic and structural effects of sulfur poisoning on model polymer-supported palladium and ruthenium catalytic systems for the first time under carefully controlled and comparable conditions without potential inferences from using solid support and promotor and with no significant variation in particle size/shape, etc. CO chemisorption, in addition to analysis of 3-hexyn-1-ol hydrogenation as a test reaction &

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adsorption characterization by these effects.

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C NMR and finally modelling are combined to demonstrate

RESULTS AND DISCUSSION

Polyvinylpyrolidone (PVP) supported palladium and ruthenium nanoparticles were synthesized as model catalysts by a polyol reduction method similar to that reported by Yan et al21a. In order to achieve compatible systems with minimal variation in support and particle size, PVP polymer (with typical weak binding to the metal nanoparticle surface) and reduction method were kept constant across the syntheses. PVP can control the growth of metal particles from metal precursor into defined size due to weak and dynamic binding through its pyrolidone pendant groups on freshly created metal surfaces in solution. The rigidity and bulkiness of the adsorbed polymer leaves a large number of surface sites free from the polymer interaction and the encapsulated PVP can also be totally or partially replaced by silica or stronger binders (i.e. S ligands, CO)21b. TEM image in Fig. 1a shows 2.0 nm of near cubooctahedral particles with narrow size distribution for Ru(PVP). Fig. 2a shows 2.7 nm of Pd(PVP) particles with similar particle distribution. However, these Pd particles seem to be embedded and interconnected with some unfolded PVP polymers particularly after sulphur treatment (lighter contrast than metal nanoparticles). Fig. 3 show the enlarged bright field HRTEM and HADDF (STEM) images of selected Pd crystals, indeed cubooctahedral particles are embedded in non-crystalline PVP. According to the model of van Hardeveld and Hartog22, a cubooctahedral shaped particle gives approximate statistics of 46% of the particle as surface atoms, 35% of the surface atoms in low coordinate sites, and 65% of the surface as terraces. Mercaptoethanol (MEA) was selected as a model sulfur poison and systematic modification of the two catalysts was carried out to give desired levels of coverage up to 236% of the theoretical surface. Transmission electron microscopy (TEM and HRTEM) and X-ray powder diffraction (XRD) of the modified particles shows neither any significant sample aggregation, size or morphological changes or formation of bulk sulphide (Fig. 1b, Fig. 2b and Fig. S1 and Fig. S2), and EDX analysis indeed shows a corresponding increase in sulfur content across the range of theoretical surface coverages, proving the validity of the model to these two systems (Table 1). There were various sources of errors in the estimation of M:S ratios in the EDX analyses. However, for the higher loadings, the significant deviations of observed values from expected values are noted and they might be due to the dynamic nature of adsorption of MEA in solution. Once the sample was dried in solid form for the EDX analysis the static coverage was not as high as that in solution.

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(a)

(b)

Fig. 1 TEM image of (a) Ru(PVP) 2.0 nm with corresponding size distribution; (b) TEM image of MEA modified Ru(PVP) at 90% surface coverage. (a)

(b)

Fig. 2. TEM image of (a) Pd(PVP) 2.7 nm with corresponding size distribution; (b) TEM image of MEA modified Pd(PVP) at 30% surface coverage showing unfolding of PVP.

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(a)

(b)

Fig. 3 (a) HRTEM (bright field image) and (b) HADDF (STEM) image showing a cubooctahedral Pd crystal embedded in non-crystalline PVP. It is noted that corresponding bright field image was less capable than dark field image of differentiating Pd nanocrystals from the PVP. Table 1 Summary of EDX results for M:S molar ratios of PVP supported metal catalysts where M is Pd or Ru and Nd stands for not determined. M:S Expected 1:0.14 1:0.41 1:0.55 1:1.10

Pd:S Measured 1:0.16 Nd 1:0.44 1:0.80

Ru:S Measured 1:0.14 1:0.45 1:0.54 Nd

Geometric Modification Fourier Transform Infrared Spectroscopy (FTIR) of adsorbed CO at high concentration is a widely reported technique for determining surface features of metallic nanoparticles23,24. As such, the geometric effects of modification by the selected sulfur poison (MEA) at progressive surface coverages were investigated using FTIR of CO adsorbed on the Pd(PVP) and Ru(PVP) model catalysts under a dilute flowing stream of CO gas (5%) in a closed chamber.

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(i)

------ 0% Coverage ------ 4% Coverage ------ 12% Coverage ------ 30% Coverage

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Terraces: Low CN sites 2.8: 1 1.5: 1 1.3: 1 1.1: 1

------ 0% Coverage ------ 4% Coverage ------ 12% Coverage ------ 30% Coverage

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Terraces: Low CN sites 8.4: 1 5.4: 1 4.6: 1 Nd

0.5 0.2 0.4 Absorbance

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0.3 0.2

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Fig. 4A FTIR of CO chemisorbed on (i) Ru(PVP) and (ii) Pd(PVP) progressively modified with MEA. Ratios between corrected peak intensities for terrace and low coordinate sites are shown in insets.

Fig. 4B Vibrational frequency for the bridging CO peak at increasing surface coverages by MEA for both Pd(PVP) and Ru(PVP). 6


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In the case of CO adsorbed on Ru(PVP), three bands are observed at 2050 cm-1, 1999 cm-1, and 1950 cm-1 assigned to the ligand binding in a mono, multi, and bridged configuration25. These binding modes are correlated to CO adsorbed on low-coordinate (mono and multi) and terrace (bridge) surface sites, respectively at low coverage25. Comparisons between the relative intensities of these bands with progressive sulfur modification allows for determination of coverage-dependent site selectivity of the model poison provided that a low CO coverage is maintained (a high CO coverage may lead to the formation of mono CO on terrace sites). As shown in Fig. 4A(i), progressive surface coverage by MEA results in a general decrease in intensity for peaks corresponding to adsorbed CO (sulphur is stronger adsorbate than CO). Normalization of peak areas to the mono- and multi-carbonyl peaks demonstrates a clear loss in intensity for the band corresponding to terrace bound species, with available terrace: lowcoordinate sites decreasing from 3.2 : 1 in the unpoisoned sample to 1.3 : 1 at 30% surface coverage. This clearly illustrates a geometric preference for binding of the model poison to extended terraces on the catalyst surface for the given size of the Ru nanoparticle. When the same CO adsorption measurements are performed on Pd(PVP) with progressive surface coverage of sulfur up to 30%, two adsorption bands are observed at 2022 cm-1 and 1929 cm-1 corresponding to linearly and bridge-bound CO adsorbed to low-coordinate and terrace sites, respectively (higher degree of back donation from electron richer Pd than Ru rendering the νCO at longer wavenumber)24. Normalization to the linearly bound species again shows a steady decrease in intensity for bridge bound CO confirming the same geometric preference for the model poison to deactivate terrace sites on the palladium surface (Fig. 4A(ii) of comparable particle sizes as that of Ru. This finding is in agreement with the results of Marshall et al., who demonstrated the formation of stable assemblies of short-chain alkanethiols similar to our chosen poison on the extended palladium surface9 overcoming a preference for binding to more energetically favorable low coordinate sites26. There is another possibility that terraces and low-coordinate sites are poisoned to a comparable extent, but the formation of mono CO becomes favoured on the poisoned terrace sites to account for the decrease in terraces: low CN sites (Fig. 4A(i) and (ii)). However, if poisoning of the catalyst causes CO to preferentially adsorb to terrace sites in a linear fashion, we should expect to see a shift in the adsorption energy because the coordination of the metal atom where the CO adsorbs upon would be different (low coordinated, higher energy sites on corners versus higher coordinated, low energy sites on terraces). This peak shift would be evident regardless of MEA’s electronic influence on the catalyst. However, both Pd and Ru show no significant shift in energy of the linearly bound CO, we have therefore discounted this possibility. In addition, CO is a strong surface adsorbate which was apparently unable to displace the preadsorbed MEA on both metal surfaces indicating the strong poisoning effect of the sulfur molecule. Thus, these observed structural poisoning effects for selective blockage of terrace sites are very similar for both model metal catalysts. However, the competitive adsorption experiments were unable to allow further differentiation of low indexed terrace sites due to poor resolution at variable CO coverages (such as (111), (100), (110)) despite the fact that Ru exhibits hexagonal close packed (hcp) structure while Pd exhibits face centre cubic (fcc) structure. Previous work has demonstrated FTIR of CO adsorption to be an effective technique for investigating electronic modification of the metal surface by examining the degree of CO adsorption band shift24. It is apparent that a more significant degree of red shift of the CO adsorption peaks over Pd than Ru is clearly noted from Fig. 4B (shifting from 1929 to 1869 cm-1 7


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with a total of 40 cm-1 red shift for the bridged CO mode on Pd upon 30% sulfur coverage). Interestingly, there is only a slight red shift in the adsorption peaks for example, the bridged mode for CO is moved gradually from 1950 to 1945 cm-1 (5 cm-1 red shift) when 30% of sulfur is covered on the Ru surface for the similar particle size. However, geometric effects must be discounted in order to accurately determine electronic modification of the catalyst as surface coverage can also have a strong effect on band frequency. Such a shift can be partly due to the decreased CO surface coverage as dipole-dipole interactions between these adjacent adsorbate molecules become disrupted (despite the use of dilute CO gas)27. In order to discern the dipoledipole interaction from electronic contribution 30% 13CO/70% 12CO surface adsorption was studied (see Fig. S4 and Fig. S5). A maximum shift of 10.4 cm-1 would be expected over 30% sulfur coverage due to dipole-dipole coupling effect hence the greater red shift observed from experiment clearly suggests that there is a significant electronic contribution in the case of Pd (donating of lone pair electrons from sulfur to d-band of Pd via adsorption). Thus, the above studies provide an assessment of the structural and electronic components of sulfur poisoning for the two metal nanocatalysts. Clearly, both Ru(PVP) and Pd(PVP) particles take up the MEA molecules with preferable adsorption on their terrace sites and Pd(PVP) particles seem to undergo a much stronger electronic change to its surface sites than that of Ru(PVP) upon the initial 30% MEA surface coverage for the comparable particle size without any interference from using conventional solid support.

Electronic Modification For further assessing the degree of electronic influence on adsorbate between the two metal surfaces, high resolution solution state 13C-labelled Nuclear Magnetic Resonance (13C-NMR) was employed to investigate the electronic effects of progressive surface coverage by the model poison on the colloid metal particles. In accordance with the method published by Tedsree et al., 13 C labelled formic acid was employed as an adsorption probe and changes in chemical shift relative to dioxane were monitored to reflect electronic modification of the catalyst surface 28.

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166.3

Palladium

166.2 Chemical Shift (ppm)

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Unbound formic acid

166.1 166.0

Ruthenium

165.9 165.8 165.7 165.6 165.5 0

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Fig. 5 Chemical shift of chemisorbed formic acid with increasing surface coverage by MEA for Pd(PVP) and Ru(PVP) plotted along with the chemical shift for unbound formic acid. The results in Fig. 5 demonstrate a progressive average downfield shift for 13C-formic acid chemisorbed to the MEA pre-treated Pd(PVP) samples (indirect chemical shift due to monitoring 13 C through 13CHO2-M interaction to reduce the knight-shift peak broadening effect) compared to the unbound formic acid form despite a degree of exchange of bound and unbound forms. Similar to the CO probe, 13C-formic acid was still unable to displace the MEA poison from its strong surface-sulphur interaction otherwise no chemical shift was anticipated (Fig. 3). The average chemical shift of the probe decreases steadily from 166.17 ppm to 165.58 ppm with increasing sulfur coverage. It has been reported that the back donation of electrons from metal to adsorbed formic acid molecule should strengthen the adsorption of the molecule leading to a higher chemical shift value (electron depletion from 13C)28. However, the progressive decrease in chemical shift for bound formic acid at high sulfur converges implies the surface band mixing of sulfur with Pd (p-d) can lower the d-band centre29 which overrides the increase in back donation due to the interaction of the sulfur lone pair with the metal surface (see Fig. 4)28. It is interesting to note that the chemical shift value of formic acid converges with that of the free form at approximately 55-60% sulfur coverage (no further change in chemical shift values beyond this coverage), indicating this surface coverage may be sufficient to fully deactivate the palladium surface (electronic withdrawal from the Pd) with further adsorption of sulfur only resulting in geometric modification (a dynamic equilibrium adsorption of the molecule is expected at high coverages). In stark contrast, progressively higher sulfur coverages on Ru(PVP) create no significant change in chemical shift value for the whole range of sulfur coverage. The chemical shift value of adsorbed formic acid is still higher than that of unbound formic acid indicative a favourable adsorption with no significant electronic modification of the ruthenium sites by the model poison for the same degree of surface coverage. This information agrees with the CO adsorption experiment in Fig. 4 that there is almost no change in the νCO on Ru surface despite the variation in sulfur coverage. The difference in electronic sensitivity of the two metals is likely due to differences in their d-band electronic structure. Density Functional Theory (DFT), summarized by the d-band centre and electron filling models, has been successfully used to model various chemisorption systems. The closer the d-band centre is to the Fermi level of a metal, the higher the adsorption energy. Additionally, electron poorer elements (elements on the 9


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left hand side of periodic table with fewer d-band electrons) favour stronger adsorption30. The dband centre position of Ru is higher than Pd with decreased electron filling (Ru -1.41 eV and Pd -1.83 eV), hence offering a higher degree of formic acid adsorption (σ interaction). However, the higher degree of d-band filling in Pd encourages back donation of electrons to formic acid (π interaction) as stated, giving overall stronger adsorption than Ru (higher chemical shift value). Indeed, in a comparative study of palladium, platinum, and rhodium, Rodriguez et al. demonstrated the importance of metal d-band position and filling and the influence of surface adsorption14. They found that metals with more complete d-band filling, like palladium experience a much greater reduction in d-band population and density of states near the Fermi level due to sulfur adsorption than those metals like rhodium where the d-band is less full. This effect is clearly observed in this study through the upfield perturbation in the chemical shift value for Pd suggesting the weakening of formic acid adsorption (electron depletion from the shift of d-band centre) due to the presence of adsorbed sulfur. As a metal with one electron less than rhodium, extension of this argument to ruthenium suggests sulfur poisoning will have little effect on its d-band properties relative to palladium. Thus, a clear and important outcome of this work is that electron rich palladium is more sensitive to electronic modification by sulfur poisoning than electron poor Ru over the comparable particle size range of 2-3nm with no solid support. With 55-60% sulfur coverage (electron withdrawal) the electronic back donation from the Pd surface to the formic acid adsorption can be cancelled out. Thus, the present material models enable us to assess the degree in a near quantitative manner.

Scheme 1 General mechanism for consecutive hydrogenation of 3-hexyn-1-ol (also see Scheme S1). The sensitivities of ruthenium and palladium to structural and/or electronic modifications by sulfur determined by FTIR and 13C NMR can be verified using the typical catalytic hydrogenation of 3-hexyn-1-ol as a model test reaction. A general simplified mechanism for the reaction is given by Scheme 1, where cis-3-hexen-1-ol is the initial product (or intermediate) due to cis addition of hydrogen atoms to the triple bond via the metal surface, followed by further hydrogenation or isomerisation of this intermediate to other products (also see Scheme S1). Notice that the adsorption energy on metal surface for alkyne is much higher than alkene due to stronger π* interaction (dominated by electronic interaction). As a result, the hydrogenation of alkyne to alkane takes place in a stepwise manner 30.

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R² = 0.9376

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Fig. 6 (a) Hydrogen uptake profile of 3-hexyn-1-ol conversion over MEA modified Ru(PVP). Half & full uptakes occur at 60 mL and 120 mL of H2, respectively, corresponding to consumption of 1 and 2 molar equivalents of H2; This is an apparent induction period over the more surface oxidation-prone Ru sample, as shown in the figure, presumably hydrogen activation is required before alkyne hydrogenation activity can take place. (b) Compiled TOFs for the first half hydrogenation from 3-hexyn-1-ol to 3-hexen-1-ol over MEA modified Ru(PVP). Conditions: 2.5 mmol reagent, 2.5 µmol metal catalyst in EtOH, 40 ˚C, 15 bar H2 (Ru). Table 2 TOF calculated for the rate of hydrogenation of 3-hexyn-1-ol over Ru(PVP) over surface sites at various MEA coverage levels (refer to Fig. 6(a))

Surface Coverage by MEA (%) 12% 24% 30% 35% 47% 59%

TOF (min-1) 9.1 5.6 4.1 3.4 2.0 0.5

The initial first stage partial hydrogenation for 3-hexyn-1-ol over the ruthenium catalyst is progressively attenuated with increasing sulfur coverage until near total deactivation is achieved by the model poison (Fig. 6a). An almost linear deactivation response with increased surface coverage indicates blockage of the metal active sites for the alkyne hydrogenation (Fig. 6b), demonstrating the strongly adsorbed sulfur molecules compete favourably with the alkyne but do not seem to interfere with the alkyne adsorption strength on Ru (geometric deactivation by sulfur adsorption, see Table 2). About 50% of the initial activity was lost at about 30% S coverage. It is noted that the relative adsorption strength of alkyne versus alkene is not large for Ru. This means 11


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that the reaction does not proceed exclusively by the distinct two-step process as that of Pd (see later). As such, the hydrogenation of alkyne could be measured, but since alkene is being formed and consumed throughout this step it wasn’t possible to measure the rate of 2nd hydrogenation step (alkene to alkane) for this process.

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200 150 100

R² = 0.9999

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Fig. 7 (a) Hydrogen uptake profile of 3-hexyn-1-ol conversion over MEA modified Pd(PVP). Half & full uptakes occur at 60 mL and 120 mL of H2, respectively, corresponding to consumption of 1 and 2 molar equivalents of H2; (b) Compiled TOFs for the second half hydrogenation from 3-hexen-1-ol to 1-hexanol over MEA modified Pd(PVP). Conditions: 2.5 mmol reagent, 2.5 µmol metal catalyst in EtOH, 40 ˚C, 3 bar H2 (Pd). Table 3 TOF and inflection points (point of maximum cis-3-hexen-1-ol concentration) calculated for the hydrogenation of 3-hexyn-1-ol over Pd(PVP) at various MEA coverage levels (refer to Fig. 8) It is noted that, there may have significant errors at our high MEA coverages since they may compete with PVP as well as reactants for adsorption sites. Surface Coverage by MEA (%) 0% 12% 30% 58% 89% 118% 236%

1st step (alkyne hydrogenation) TOF (min-1) 128.6 117.4 127.7 119.6 133.1 146.0 123.4

2nd step (alkene hydrogenation) Inflection point (min) 67.3 68.8 66.6 72.1 69.5 103.9 267.5

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However, it is interesting to note that the first stage hydrogenation rate for 3-hexyn-1-ol to 3hexen-1-ol over Pd is extremely fast (reflected by stronger surface adsorption demonstrated by NMR) and is independent of sulfur coverage, demonstrating the alkyne adsorption is likely to be stronger than the model poison at their given concentrations, see Fig. 7a (also Table 3 and Fig 8). In fact, analysis of conversion for the starting alkyne over Pd(PVP) shows no relationship between coverage and activity below 89% surface coverage, suggesting the alkyne molecules are indeed highly effective at displacing the model poison below monolayer coverage (most MEA molecules were retained in filtered solution) due to relatively stronger adsorption (compare Table 2 and 3). The estimated TOF values for the high coverage cases (146.0 min-1 and 123.4 min-1 for 118% and 236% coverages, respectively) are also very similar to the unmodified catalyst (128.28 min-1) (Table 3). Analysis of reaction kinetics similarly shows no significant effect on the rate constant for conversion of alkyne to cis-alkene (k1) regardless of coverages (Table 2 and 3). Similar analysis for the production and further conversion of the cis product (Fig. 8, Table 4) over Pd(PVP) shows high initial selectivity (>94%) is maintained at all coverages with no relationship to the level of poisoning, confirming modification with MEA does not influence the initial hydrogenation step for alkyne to cis-alkene conversion where the adsorption of alkyne with π interaction with metal is well-known to be strong over electron rich metals, i.e. Pd.

Fractional Composition

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0% 12% 30% 59% 89% 118% 236%

1 0.9 0.8 0.7 0.6 0.5 0.4 0.3 0.2 0.1 0 0

100

200

Table 4. Selectivity for cis-3-hexen-1-ol measured at the calculated inflection point (1st equivalent H2 uptake) between the production and conversion steps. Surface Coverage by MEA (%) 0 12 30 59 89 118 236

Cis-3-hexen-1-ol selectivity 98.5% 94.6% 97.9% 95.4% 95.9% 94.8% 94.0%

300

Time (min)

Fig. 8 Production and subsequent conversion of cis-3-hexen-1-ol by progressively poisoned Pd(PVP) expressed as a fractional composition of the total reactant/products. Time at the inflection point is normalized for all curves.

To ensure the stabilizing polymer PVP did not create artefacts in such observation and the relevancy to other supported Ru and Pd catalysts, MEA modifications over commercial carbonsupported Ru and Pd catalysts of similar particle sizes (refer to TEM images in Fig S3) to our model systems were performed. As seen from Fig. 9, the same hydrogenation profiles are obtained despite the use of different support. There is no change in the rate for the first stage hydrogenation of the cis-3-hexyn-1-ol. However, the second stage hydrogenation of corresponding cis-3-hexene-1-ol to 1-hexanol is sensitive to MEA modifications where at above 74% S coverages, the deactivation rates slow down progressively. This clearly suggests that 13


ACS Catalysis

there are fundamental differences of Ru and Pd nanoparticle surfaces towards sulphur modification.

(b) 5% Pd on C (Type 87L)

(a) 6% Ru on C 80 120

Ru/C 0% MEA Ru/C 7% MEA Ru/C 18% MEA Ru/C 21% MEA

60 50

100 H2 Uptake (mL)

70 H2 Uptake (mL)

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40 30

80 Pd 87L 15% MEA Pd 87L 0% MEA Pd 87L 37% MEA Pd 87L 74% MEA Pd 87L 147% MEA Pd 87L 294% MEA

60 40

20 20

10

0

0 0

100

200 Time (min)

300

0

100

200

300

Time (min)

Fig. 9. Hydrogen uptake profiles of 3-hexyn-1-ol conversion over MEA modified (a) commercial 6% ruthenium on activated carbon and (b) 5% palladium on carbon (Type 87L). Half- and fulluptakes occur at approximately 60 mL and 120 mL of H2, respectively, corresponding to consumption of 1 and 2 molar equivalents of H2. Conditions: 2.5 mmol reagent, 2.5 µmol metal catalyst in EtOH, 40 ˚C, 3 bar H2 (Pd) and 15 bar H2 (Ru). Notice that the same response profiles as for PVP stabilized metals are obtained (1st stage hydrogenation of alkyne over Ru is sulfur coverage dependent but virtually independent with respect to Pd).

We attribute the stronger adsorption of alkyne over the sulfur poison on the Pd over Ru surface to extensive back donation of electrons from the Pd metal to π* systems on top of σ interaction (Ru gives stronger σ interaction than Pd) of this adsorbate where the electron richer Pd is thus more effective than the electron poorer Ru metal surface30. Thus, an interesting outcome derived from these experiments is that electron rich metallic surfaces could become more sulfur tolerant under a reaction stream if the π systems of substrates are tackled. However, Fig. 7b shows the profile subtly changes in the second stage of hydrogenation of cis-3-hexen-1-ol to 1-hexanol, the extent of which decreases steadily with coverage but is never fully inhibited (Table 3). The adsorption strength of cis-3-hexen-1-ol was estimated to be 220 times lower than the alkyne (and similar to all other reactants), which is consistent with literature values (adsorption equilibrium constant for butyne-diol is approximately 105 times greater than those for hydrogenation products)30. As a result, the competitive adsorption of sulfur this time becomes more significant for further reactions of cis-3-hexen-1-ol to products for the palladium surface at near completion of the 3-hexyn-1-ol conversion30. Interestingly, according to the Fig. 7b, the deactivation response with increased surface coverage over Pd decreases in a non-linear manner in a stark contrast to the case of Ru suggesting the physical blockage of the metal active sites for the 14


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ACS Catalysis

alkyne hydrogenation is not the sole mechanism. There is more than 70% reduction in the initial activity for 30% S coverage on Pd (cf. 50% in the case of Ru). The change in profile in the TOF values resembles with the NMR measurements (Fig. 5) with a sharp turning point at 55-60% sulfur coverage. Beyond this point the deactivation progressively slows down (7(b)). Analysis of reaction kinetics also shows a clear decrease in rate constants associated with further hydrogenation (kfull) or isomerization (kisom) of the cis-product with increasing coverage, with corresponding increases in the ratios of partial alkyne hydrogenation (ksemi) to these processes (Table 5). The key question is whether the observed deactivation is due to geometric sites blockage by sulfur (similar to the case of Ru) or a combination of geometric and electronic deactivations as reflected by the NMR.

Table 5. Summary of kinetic rate constants for the simplified hydrogenation of 3-hexyn-1-ol over Pd(PVP) where kn is in units of molsub molcat-1 min-1, ksemi = k1, kfull = k2 + k5 and kisom = k3 + k4 according to Scheme 1 (further more kinetic details provided in Scheme S1, Fig. S6 and Table S1). Surface Coverage by MEA (%) k1 k2 k3 k4 k5

Σksemi/Σkfull Σksemi/Σkisom Σkfull/Σkisom

0%

12%

30%

58%

236%

58.14

54.95

57.23

50.67

53.30

79.95 191.70 65.75 91.19

70.21 169.14 50.31 92.34

43.50 87.83 56.83 38.16

22.39 77.37 162.06 0.00

2.17 77.53 686.66 0.00

0.34

0.34

0.70

2.26

24.62

0.23

0.25

0.40

0.21

0.07

0.66

0.74

0.56

0.09

0.00

According to the mechanism proposed by Ulan et al., cis/trans isomerization occurs through the non-stereoselective, reversible addition of a single H via an alkyl intermediate, whereas double bond hydrogenation occurs first through progressive bond shift toward decreasingly stable alkenes, resulting in a highly-reactive terminal alkene which is subsequently reduced to produce the saturated alkane31 (Fig. S7 and Fig. S8). This progressive bond shift occurs through rapid πallyl inter-conversions which are known to be very sensitive to surface energy and surface geometry31. If the adsorption of sulfur only results in metal site blockage due to structural effects, one would expect that the product distribution would not be altered. However, if the adsorption of sulfur can electronically influence the underlying metal sites, then changes in product selectivity should be observed. For Pd, a strong relationship is observed between the derived kinetic rate constant ratios of Σkfull/Σkisom and the level of sulfur coverage. Similarly, effects of sulfur modification on reactions cis-3-hexen-1-ol over Pd were monitored via ratios of cis/trans isomerization versus complete hydrogenation to 1-hexanol for comparison to Ru. It is interesting to note only a slight decrease in hydrogenation to isomerisation ratios (1.4 to 1.1) in the case of Ru(PVP) (Fig. 10a) despite significant attenuation in the substrate activity (>2/3 activity loss) at 50-60% surface coverage. The loss in activity over sulfur poisoned Ru surfaces can again be attributed to deactivation by coverage of sulfur on active metallic sites (geometric effect). On the other hand, Pd(PVP) shows a marked decrease in hydrogenation: isomerization 15


ACS Catalysis

ratios at equivalent surface coverages by the model poison (Fig. 10a and 10b), indicating that palladium is significantly more sensitive to the electronic effects of sulfur poisoning than ruthenium for the alkene hydrogenation/isomerization (Table S2). Following the conclusion from the NMR experiments that electron density of Pd is depleted by sulfur adsorption, increasing coverage weakens alkene adsorption, shifting the mechanism toward isomerisation to transalkene rather than the fully hydrogenated, thermodynamic product which requires stronger and longer alkene adsorption. Additionally, the results show a levelling off in the hydrogenation: isomerisation ratio after reaching 59% surface coverage in almost quantitative agreement with the results from 13C NMR (Fig. 5) and TOF analysis (Fig. 7(b), Table 3). This strongly suggests that at higher coverage than this critical value deactivation becomes geometrically controlled, leading to loss in activity but with no change in selectivity.

1.80

1.45

1.60

1.25

1.40

1.05

1.20

0.85

1.00

0.65

Palladium

0.80

0.45

Ruthenium

0.60

0.25

0.40

0.05 0

10

20

30

40

50

Ratio hydrogenation: isomerisation

(b) Ratio hydrogenation:isomerisation (Ru)

(a) Ratio hydrogenation:isomerisation (Pd)

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2.0 1.8 1.6 1.4 1.2 1.0 0.8 0.6 0.4 0.2 0.0 0

50

100

150

200

250

% Surface Coverage

% Surface Coverage

Fig. 10 Ratios of hydrogenation: isomerisation for the hydrogenation of 3-hexyn-1-ol for (a) Ru(PVP) (y-axis right) and Pd(PVP) (y-axis left) at MEA surface coverages below 60% and (b) Pd(PVP) at MEA surface coverages up to 236%.

Theoretical considerations: The structures for Ru and Pd with 0.25 monolayer (ML) of S atoms surface modification that were used for DFT calculations, are shown in Fig. 11. Fig. 12 illustrates the corresponding projected density of states for each of our systems. Initially we can consider the charge transfer between S and the two metals (Table 6). Accordingly, there is twice as much charge transfer from Ru to S as from Pd to S. This may be indicative of a more ionic interaction in the case of Ru. However, Bader analysis of both Pd and Ru also show fluctuations of +/- 0.03 electrons with or without S atoms in the surface slab, showing that there is no significant oxidation/reduction occurring on the metal atoms. According to the ∆DOS pictures in Fig. 13, we can see charge relocation from metal bands due to the S interactions. This picture is corroborated in Fig. 13 where we present d-band DOS difference plots (∆DOS=DOS TM/S – DOS clean TM) for the two 16


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ACS Catalysis

PGM atoms adjacent to the S atom (i.e. d-band DOS for the clean and doped PGM along with ∆DOS). If we integrate the ∆DOS we can see that once we reach the fermi level there is negligible loss or gain of electrons in the occupied states. Fig. 14 illustrates in more detail the influence of S and the structural effects to the two metals. As expected due to S being on the surface there is negligible structural influence on the d-band. However when we adsorb S we can see that for Ru the interaction is weak and across the whole d-band, whereas for Pd there is significant depletion in DOS near the Fermi level and the formation of a bonding interaction at the tail of the d-band. These results are similar to Rodriguez et al. who showed the difference of electronic depletion between Rh and Pd14. In an attempt to further understand the bond formation between S and Pd or Ru, Fig. 15 (a and b) was constructed. Here the evolution of the bonding is chartered, moving the S atom from a distance to its equilibrium distance at the surface (∆d 6, 2.5, 2.5, 0.5, 0 Å) for Ru (0001) and Pd (111) respectively. What this shows is the strong interaction of Pd at the Fermi-level and the formation of almost discrete bonding and anti-bonding peaks, we see the bonding interaction falls below the d-band of Pd. However for Ru the interaction is much more smeared out and the formation of a bonding orbital actually falls within the lower half of the occupied d-band, this gives rise to rehybridization and a much more delocalised interaction. Further insight into the electronic nature of the S/Pd interaction can be found in Table 7, where the d band width and center position of Pd with and without S adsorbed are calculated. What can clearly be seen is that the Pd d-band center shifts down by (-0.7 eV) and broadens (+0.3 eV) due to interaction with the S p-orbitals, this leads to an electron stabilisation that results in reduced activity of the surface. On the other hand, the Ru d-band center shifts down by only (-0.3 eV) and broadens (+0.06 eV) when S is adsorbed. Thus, the lack of significant charge transfer (Table 6) and depletion of electrons from Fermi level by the d band center downshift and broadening (Table 7) in the case of Pd clearly indicate more covalent type interaction than Ru, leading to electronic deactivation of the metal in the presence of S adsorbate, as observed by our experiments. (a)

(b)

Fig. 11 Top view of (a) Ru (0001); (b) Pd (111) with 0.25 ML S (yellow) on surface

17


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(a)

Page 18 of 27

(b)

Fig. 12: Projected density of states plots (a and b), for the surfaces shown in Fig 11. Blue represents d-orbital, red S s-orbital and green, S p-orbital. Grey shows the M d-band for the clean surface.

(a)

(b)

Fig. 13: Density of states difference plots, a (Ru) and b (Pd) (DOSmetal with adsorbate -DOSclean metal) for the surface shown in Fig. 11, Shaded blue: occupied states of the clean surface, shaded red: occupied states of the metal with S adsorbate, shaded green: the change in occupied states upon S adsorption. Notice that the integral of the change in occupied states approaches zero, indicating that there is minimal charge transfer to the transition metal atoms. 18


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ACS Catalysis

(a)

(b)

Fig. 14: Density of states for (a) Ru surface atom, green: fully relaxed system with no S adsorped, red S adsorbed on the surface, blue the frozen geometry of the Ru/S system with the S removed (as an indicator of the influence of lattice distortion due to S); (b) Pd surface atom during S adsorption, green: fully relaxed system with no S adsorped, red S adsorped at the surface, blue the frozen geometry of the Pd/S system with the S removed (as an indicator of the influence of lattice distortion due to S). In conjunction with Figure 3 it is clear the loss of density at the Fermi level is not due to charge transfer, but rather the redistribution of charge density due to the covalent bonding interaction with S. (a)

(b)

Fig. 15: Plot showing the evolution of the bonding interaction as S is brought towards (a) Ru (0001) surface from the gas-phase. Blue Ru d-orbitals, Red S p-orbitals; (b) Pd (111) surface from the gas-phase. Blue Pd d-orbitals, Red S p-orbitals

19


ACS Catalysis

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Table 6: Bader Charge Analysis for Dopant Species on Ru(0001) and Pd(111)

S

Ru

Pd

-0.4

-0.2

Table 7: d-band centre analysis, centre (width) / eV for Ru(0001) and Pd(111) Ru

Pd

S

-2.2(1.8)

-2.4(1.5)

Clean

-1.9(1.74)

-1.7(1.2)

From an application perspective, catalytic partial hydrogenation of alkynes to alkenes is a key transformation in industrial organic synthesis32. It is established that a solid catalyst containing Pd in the presence of hydrogen is the most preferable choice over stoichiometric chemical reagents and homogeneous catalysts in terms of green chemistry and reusability of the catalysts. However, the surface of unmodified supported Pd metal is highly unselective, which will lead to over-hydrogenation to undesired alkanes. Lindlar catalysts with Pb and quinoline additives to modify the Pd sites have been demonstrated to be versatile and effective and are still frequently used despite their discovery over 60 years. However, handling toxic Pb(OAc)2 during catalyst preparation, leaching of surface doped Pb in the presence of substrates or products with multifunctional groups (such as drug candidates or biomass molecules), poor selectivity and limited catalyst robustness begin to restrict them from wider and new applications32. Thiophene and related sulphur compounds have been employed intensively by Iglesia, Marshal, Ponec and others in the past to modify Pd catalysts3,9,33 and very recently, subsurface ‘carbon’ and ‘boron’ atoms were studied, which were also considered for a long time to be typical "poisons" for Pd. There is a growing body of studies showing their promotional effects34. Here, we show surface adsorption of sulfur molecules on electron richer Pd nanoparticles could greatly alter the electronic properties while electron poorer Ru does not show much effect. In the case of alkyne hydrogenation, this can improve the selectivity towards desirable alkene products by partially ‘poisoning’ the Pd metal surface. CONCLUSION

Sulfur poisoning over noble metal catalysts has traditionally been regarded as very complex and precluding from rational understanding. Although there have been practical works in literature to address the ‘sulfur poisoning’ effect over supported metal catalysts, the problems of interference from using different supports, inability of controlling coverage due to non-uniform metal particle size, intrinsic size/shape effect of metal component render the elucidation difficult at an atomic level.

20


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ACS Catalysis

The present assignments of metal sites blockage on PVP stabilized unsupported metal nanoparticles, without much atom mobility or scrambling on the surface at near room temperature (30-40oC), with confidence are mainly attributed to the fine tailored control of high quality metal colloid size, careful rate analysis, high CO FTIR diagnosis value coupled with an NMR measurement using formic acid. In addition, HRTEM/STEM confirms the use of high quality uniform cubooctahedral metal particle as a unique material model to elucidate the sulphur effects in semi- and near quantitative manner. In this paper, we have particularly employed simple consecutive hydrogenation reactions for alkyne to alkane via alkene in the liquid phase. The first stage alkyne hydrogenation is surface structurally insensitive and the second hydrogenation/isomerisation is highly adsorbate dependent. Using spectroscopic and NMR characterization techniques, the components of sulfur poisoning over model palladium and ruthenium nanocatalysts have been quantitatively assessed. Even without solid support, 2.0 nm ruthenium has been clearly shown to be relatively insensitive to the electronic components of poisoning, with geometric effects playing a predominant role due to its electron poorer properties. In contrast 2.7nm palladium with comparable particle size was seen to be highly sensitive to both electronic and geometric effects of poisoning, with competitive adsorption and d-band centre and filling alterations inducing significant changes in catalytic activity and selectivity for the partial hydrogenation of 3-hexyn-1-ol. However, 55-60% of sulfur coverage on the 2.7nm Pd nanoparticle can completely remove the electronic contribution in the 3-hexyne hydrogenation reaction, switching the deactivation to geometric blockage dependence. From our DFT calculations, we show clearly that the S adsorption on palladium indeed is clearly sensitive to electronic modification than that of ruthenium. As a result, electron rich palladium catalysts could be tuned to be more sulfur tolerant depending on the relative competitive adsorption of alkyne substrate, sulfur and added modifiers. The electron depleting effect due to the alteration of d-band centre of Pd by d-p mixing with sulfur atom which is generally interpreted as ‘poisoning’ from a negative perspective that could greatly attenuate the adsorption strength of adsorbate in combination with the metal site blockage. On the other hand, this can also be taken as a positive perspective in the case for partial reacted product where sequential surface overreaction of the adsorbate (alkenes) can be discouraged hence enhancing selectivity.

EXPERIMENTAL SECTION

Synthesis of Pd(PVP) PVP supported Pd nanoparticles were prepared by a polyol reduction method. Briefly, 240 mg (2.148 mmol) of 40K molecular weight (MW) PVP was dissolved in 30 mL of ethylene glycol, followed by 56 mg (0.2142 mmol) of Pd(NO3)2·2H2O. The solution was stirred extensively and then heated at 120˚C for 2 hours, reducing Pd2+ to form dark brown colloidal nanoparticles. Once the reaction was complete, the nanoparticles were precipitated using centrifugation with a mixture of acetone and hexanes and washed with acetone a further 2 times before being left to dry in air. Once dry, the nanoparticles were redispersed in ethanol to yield a colloidal solution. Synthesis of Ru(PVP) PVP supported Ru nanoparticles were prepared by a polyol reduction method. Briefly, 240 mg (2.148 mmol) of 40K MW PVP was dissolved in 30 mL of diethylene glycol, followed by 50 mg 21


ACS Catalysis

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Page 22 of 27

(0.2023 mmol) of RuCl3·3H2O. The solution was stirred extensively and then heated at 160˚C for 2 hours, reducing Ru3+ to form dark brown colloidal nanoparticles. Once the reaction was complete, the nanoparticles were precipitated using centrifugation with acetone and washed a further 2 times before being left to dry in air. Once dry, the nanoparticles were redispersed in ethanol to yield a colloidal solution. Modification with Mercaptoethanol Modification of colloidal catalysts by mercaptoethanol (MEA) was achieved by combining a determined volume of the colloidal nanoparticle dispersion with an ethanolic solution of MEA calculated to give the desired surface coverage over theoretical exposed surface sites for given average size of cubooctahdral particle according to the model of van Hardeveld and Hartog22. Modified samples were sonicated for 30 minutes and allowed to age for 24 hours before characterizations and testing were carried out. Modification of commercial catalysts by MEA was achieved by first sonicating the supported catalyst (typically 25 mg) in 6 mL of ethanol for 1 hour until the sample was well-dispersed. An ethanolic solution of MEA was then added at a volume calculated to give the desired level of surface coverage. Samples were sonicated for a further 4 hours and then stirred for 24 hours before being transferred to a 100 ˚C oven overnight to remove the solvent. Hydrogenation of 3-hexyn-1-ol by Pd(PVP) Hydrogenation of 3-hexyn-1-ol by Pd(PVP) was carried out in a HEL Chemscan reactor. 5 mL of 3-hexyn-1-ol (0.5 M, 2.5 mmol) and dioxane (0.5 M, 2.5 mmol) in ethanol and 0.6 mL of colloidal Pd(PVP) (0.5 mM, 2.5 µmol) were added to a glass reaction vessel in the haste alloy reactors. Hydrogenation was carried out under 3 bar H2 at 40 ˚C. Hydrogen uptake was monitored and samples taken after the reaction was stopped were analysed by GC. For kinetic measurements, hydrogenation of 3-hexyn-1-ol by Pd(PVP) was carried out in a sealed 3-neck round bottom flask. 50 mL of 3-hexyn-1-ol (3 M, 15 mmol) and 1,4-dioxane (3 M, 15 mmol) in ethanol was bubbled with H2 gas at a rate of 30 mL min-1 for 15 minutes under rapid stirring. The reaction temperature was controlled at 30˚C using a water bath. 2 mL of colloidal Pd(PVP) nanoparticles (4 µmol metal catalyst) in ethanol were injected and samples of approximately 0.3 mL were taken at regular intervals throughout the reaction. Samples were analysed by GC. Hydrogenation of 3-hexyn-1-ol by Ru(PVP) Hydrogenation of 3-hexyn-1-ol by Ru(PVP) was carried out in a HEL Chemscan reactor. 5 mL of 3-hexyn-1-ol (0.5 M, 2.5 mmol) and dioxane (0.5 M, 2.5 mmol) in ethanol and 0.6 mL of colloidal Ru(PVP) (0.5 mM, 2.5 µmol) were added to a glass reaction vessel in the haste alloy reactors. Hydrogenation was carried out under 15 bar H2 at 40 ˚C. Hydrogen uptake was monitored and samples taken after the reaction was stopped were analysed by GC. Hydrogenation of 3-hexyn-1-ol by carbon supported commercial catalysts 22


Page 23 of 27

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ACS Catalysis

Hydrogenation of 3-hexyn-1-ol by carbon supported commercial catalysts was carried out in a HEL Chemscan reactor. 5 mL of 3-hexyn-1-ol (0.5 M, 2.5 mmol) and dioxane (0.5 M, 2.5 mmol) in ethanol and 2.5 µmol of metal catalyst (4.2 mg 6% ruthenium on activated carbon or 5.3 mg 5% palladium on carbon Type 87L) were added to a glass reaction vessel in the hastelloy reactors. Hydrogenation was carried out at 40 ˚C under 15 bar H2 for the ruthenium catalysts and 3 bar H2 for the palladium catalysts. Hydrogen uptake was monitored and samples taken after the reaction was stopped were analysed by GC. TOFs calculations The activity in term of substrate conversion per unit time was derived from above. However, for the TOF estimation, one would need to normalize against the exposed metal surface sites. It is challenging for colloidal systems as standard techniques, such as chemisorption measurements or CO stripping cyclic voltammetry, could be inhibited by the polymer support21. In order to best address these challenges, an alternative theoretical approach was employed for the determination of surface area for the model Pd(PVP) and Ru(PVP) catalysts. Based on the average particle size demonstrated by TEM, surface statistics were calculated assuming spherical nanoparticles with surface packing densities of 1.27 x 1019 atoms m-2 (Pd) and 1.60 x 1019 atoms m2 (Ru). Approximate calculations of atom distribution statistics give 46% of the particle as surface atoms for Pd (theoretical SA 185 m2 g(Pd)-1) and 63% for Ru (theoretical SA 243 m2 g(Ru)-1). The errors of TOF were estimated to be within +/- 0.1 min-1. In general, precious group metals display excellent rate for hydrogen adsorption and dissociation on their surface. The TOF and kinetic constants measurements for alkyne and alkene were taken with the assumption that hydrogen adsorbs readily to the metal surface and dissociates immediately so hydrogen adsorption is not a rate limiting step. This is supported by the large difference in the rates between alkyne and alkene over the same metal surface. Should the rate limiting step is on hydrogen adsorption, no rate differentiation for alkyne and alkene is achieved. Formic acid 13C NMR NMR measurements of chemisorbed 13C formic acid were performed by dissolving a sample of the PVP supported nanoparticles with approximately 0.2 mmol metal content in 500 µL of D2O. Thiol modification was conducted as outlined previously. 13C labelled formic acid (1 M, 200 µL) was added followed by 10 µL 1,4-dixoan as an internal standard. The sample was then sonicated for 30 minutes before the 13C NMR spectrum was measured. All spectra were recorded on a Varian Mercury 300 MHz Spectrometer with 2000 scans and a 5 sec recycle delay and peak shifts were normalized to dioxane. The errors of chemical shift value were estimated to be within +/- 0.05 ppm upon repeated measurements for a given sample by NMR. Kinetic Modelling Experimental profiles for the hydrogenation of 3-hexyn-1-ol were fitted using a Langmuir Hinshelwood kinetic model in order to determine rates for the various reaction pathways. Kinetic measurement data presented in the text of this paper was obtained using a simplified set of rate equations (Figure 16a) based on Scheme 1 while a full kinetic profile using an expanded set of 23


ACS Catalysis

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Page 24 of 27

rate equations (Figure 16b) based on a kinetic model is presented in Scheme S1. Fits to experimental data using the expanded rate equations were excellent (Fig. S6 and Table S1), and there was good agreement between trends calculated from both models.

(a)

݀‫ܣ‬ = −ߠ஺ ݇ଵ ݀‫ݐ‬

݀‫ܣ‬ = −ߠ஺ (݇ଵ + ݇଺ ) ݀‫ݐ‬

(b)

݀‫ܤ‬ = ݇ଵ ߠ஺ + ݇ସ ߠ஼ − ߠ஻ (݇ଶ + ݇ଷ ) ݀‫ݐ‬

݀‫ܤ‬ = ݇ଵ ߠ஺ + ݇ସ ߠ஼ − ߠ஻ (݇ଶ + ݇ଷ + ݇଻ ) ݀‫ݐ‬

݀‫ܥ‬ = ݇ଷ ߠ஻ − ߠ஼ (݇ସ + ݇ହ ) ݀‫ݐ‬

݀‫ܥ‬ = ݇଺ ߠ஺ + ݇ଷ ߠ஻ − ߠ஼ (݇ସ + ݇ହ + ଼݇ ) ݀‫ݐ‬

݀‫ܧ‬ = ݇ଶ ߠ஻ + ݇ହ ߠ஼ ݀‫ݐ‬

݀‫ܦ‬ = ݇଻ ߠ஻ + ଼݇ ߠ஼ − ݇ଽ ߠ஽ ݀‫ݐ‬

ߠ௜ =

‫ܭ‬௜ ܲ(௜) 1+

݀‫ܧ‬ = ݇ଶ ߠ஻ + ݇ହ ߠ஼ + ݇ଽ ߠ஽ ݀‫ݐ‬

஺ ‫׬‬ா ‫ܭ‬௜ ܲ(௜)

ߠ௜ =

‫ܭ‬௜ ܲ(௜) ஺

1 + ‫׬‬ா ‫ܭ‬௜ ܲ(௜)

Figure 16. Rate equations for the hydrogenation of 3-hexyn-1-ol corresponding to (a) the simplified reaction mechanism presented in the text of the paper and (b) the detailed mechanism presented in the SI where A = 3hexyn-1-ol, B = cis-3-hexen-1-ol, C = trans-3-hexen-1-ol, D = bond shifted alkenes, E = 3-hexanol, Ki = adsorption constant of species i, P(i) = equilibrium concentration of species i, and θi = probability of a surface site being occupied by species i.

A root mean square error (RMSE) is determined by the model based on mismatch between the calculated and experimental concentration profiles where the lower the output error value, the better the agreement between the data sets. (Note: the output error value is not a percentage deviation between calculated and experimental profiles). A least squares method was used to derive the unknown rate constants. A RMSE cost function, f, was defined to quantify the mismatch between the experimental and calculated reaction profiles

f =

1 n − nk

ns

∑ i =1

([ P ]

− [ Pi ]cal )

2

i exp

[ Pi ]exp

where n = number of experimental data points, nk = number of rate constants to be fit, and ns = number of species. The calculation renders to a non-linear least squares optimization of the unknown rate constants (depending on the model used) to minimize f. The calculated rate constant k was treated as a constant in the optimization calculation. The SIMPLEX method was

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utilized for this purpose35. All calculations were performed using Matlab (R2013b) in a Linux cluster. Theoretical Methodology Density functional theory calculations were carried out using the grid based projector augmented wave code (GPAW)36. Bulk lattice parameters for fcc-Pd (a=3.99 Å) and hcp-Ru(a=2.74 Å, c=4.31 Å) were obtained using the planewave cut-off of 1100 eV, monkhorst-pack k-point mesh of 8x8x6 for Ruthenium and 8x8x8 for Palladium. PAW potentials were used to describe the core electrons and the electron-electron interaction was described using the RPBE functional37. Surface slabs were subsequently prepared for Ru(0001) and Pd(111) consisting of 4 atomic layers with a vacuum gap of 12Å, with back two layers frozen in the bulk positions and the two top most layers allowed to relax. The calculations for the surfaces were run using finite difference mode with GPAW, using a grid spacing of 0.18 Å (which is equivalent to a planewave cutoff of 1100 eV). All calculations used a Fermi-Dirac smearing of 0.1 eV. Structural relaxations were converged to 0.05 eVÅ2. Two subsets of structural models were examined for the surface S doping. The structures subsequently used for the electronic structure analysis are shown in Fig. 10. Electronic structure analysis was carried out using the Atomic Simulation Environment38 in conjunction with topological analysis using the Bader charge analysis code39. TEM and EDX TEM was performed using a JEOL 2010 microscope operating at 200 kV. EDX analysis was performed with the same microscope equipped with an Oxford Instruments LZ5 windowless EDX spectrometer. HAADF STEM was performed at Birmingham University on a JEOL 2100 aberration-corrected microscope operating at 200 kV. Samples for TEM/EDX analysis were prepared by dispersing a small amount of material (typically 1 mg) in approximately 1 mL of ethanol. One drop of this dispersion was placed onto a copper grid (holey carbon supported on copper, 400 mesh) and the solvent evaporated in air prior to analysis. Average particle size distributions were calculated from the measurement of at least 200 individual particles. ASSOCIATED CONTENT

Supporting Information (SI) contains further details in synthesis, testing, characterisation of all above materials and with information on data treatments. This material is available free of charge via the Internet at http://pubs.acs.org.” AUTHOR INFORMATION Corresponding Author [email protected]

ACKNOWLEDGMENT

The financial support of this work from the EPSRC research council of UK and Johnson Matthey (JM) are acknowledged. AK acknowledges the financial support for her DPhil study at the Oxford University, UK from JM through Johnson Matthey Technology Centre at Sonning Common, Reading, UK. REFERENCES

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Geometric and Electronic Deactivation of Pd surface (green) modified with sulfur atoms (yellow) in hydrogenation of 3-hexyne-1-ol

Suggested TOC .

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Quantitative Differences in Sulfur Poisoning Phenomena over

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