Spatiotemporal catalytic dynamics within singlenanocatalysts revealed by single-molecule microscopy
Peng Chen,* Xiaochun Zhou,† Nesha May Andoy,‡ Kyu-Sung Han,§Eric Choudhary, Ningmu Zou, Guanqun Chen and Hao Shen
This review discusses the latest advances in using single-molecule microscopy of fluorogenic reactions
to examine and understand the spatiotemporal catalytic behaviors of single metal nanoparticles of
various shapes including pseudospheres, nanorods, and nanoplates. Real-time single-turnover kinetics
reveal size-, catalysis-, and metal-dependent temporal activity fluctuations of single pseudospherical
nanoparticles (o20 nm in diameter). These temporal catalytic dynamics can be related to nanoparticles’
dynamic surface restructuring whose timescales and energetics can be quantified. Single-molecule
super-resolution catalysis imaging further enables the direct quantification of catalytic activities at
different surface sites (i.e., ends vs. sides, or corner, edge vs. facet regions) on single pseudo 1-D and
2-D nanocrystals, and uncovers linear and radial activity gradients within the same surface facets. These
spatial activity patterns within single nanocrystals can be attributed to the inhomogeneous distributions
of low-coordination surface sites, including corner, edge, and defect sites, among which the distribution
of defect sites is correlated with the nanocrystals’ morphology and growth mechanisms. A brief
discussion is given on the extension of the single-molecule imaging approach to catalysis that does not
involve fluorescent molecules.
1. Introduction
Nanoscale particles are among the most important catalysts.1–3
They can be of diverse material compositions, such as metals,oxides, and sulfides, and they catalyze a wide range of trans-formations including oxidation, reduction, (de)hydrogenation,carbon–carbon or carbon–heteroatom bond coupling and cleavagereactions.3–8 Their catalytic versatility makes them widely applicablein petroleum processing, fine chemical synthesis, energy con-version, and pollutant removal.
It is thus important to characterize the catalytic activity ofnanoparticles for any reaction of interest, but it is challenging.The first contributor to this challenge is the ubiquitous hetero-geneity among nanoparticles,9 where individual nanoparticlesdiffer in size, shape, and thus the exact number and types of surfacesites. Second, even on a single nanoparticle, different types ofsurface sites are present, such as corner, edge, and facet sites,
and their structural features depend significantly on the nano-particle’s morphology. Third, when the nanoparticles are suffi-ciently small, their structural dynamics can occur at a timescalecomparable to that of the catalytic turnovers, including overallmorphology changes and nanoscale surface restructuring;10–21
these structural dynamics would give rise to temporal evolutionsof catalytic properties that also differ from one nanoparticle toanother. In order to address these challenges, a direct approachis to study catalytic reactions of nanoparticles at the single-particle level, in real time, and in a spatially resolved manner.
Single-molecule fluorescence microscopy has recently provedto be effective for this type of studies. By using fluorogeniccatalytic reactions and imaging the fluorescence signal of aproduct, one can follow the reactions in real time on a singlenanoparticle at single-turnover resolution under steady-statereaction kinetics. This approach was initially developed to studycatalysis by single enzyme molecules,22–27 and was later imple-mented by Hofkens to study heterogeneous catalysis on layeredhydroxide microcrystals,28 by Majima to study metal oxidesemiconductors29 and by us to study metal nanoparticles.30
Several recent reviews31–41 cover these early and later studieson a number of heterogeneous catalytic systems. New studiescontinue to emerge.42–48 Relatedly, single-molecule fluorescenceimaging has been used to track molecular motion in porousmaterials and on surfaces, which is relevant to heterogeneouscatalysis.49–52
Department of Chemistry and Chemical Biology, Cornell University, Ithaca,
† Present address: Suzhou Institute of Nano-Tech and Nano-Bionics, ChineseAcademy of Sciences, 398 Ruoshui Rd, Suzhou Industrial Park, Suzhou, Jiangsu215123, P.R. China.‡ Present address: Department of Cell Biology, Harvard Medical School, Boston,MA 02115, USA.§ Present address: Icheon branch, Korea Institute of Ceramic Engineering andTechnology, Icheon, Gyeonggi, 467-843, Republic of Korea.
Wide-field imaging of single-molecule fluorescence alsoenables nanometer-precision localization of the individualproduct molecules.53–55 This localization allows resolving reac-tions on a single catalyst beyond the diffraction-limited opticalresolution,41,42,46,47,56–58 i.e., super-resolution, in a way directlyanalogous to (f)PALM/STORM and other related super-resolutiontechniques based on single-molecule detection.59–64
This review discusses the latest advances in single-moleculeimaging of nanocatalysis from our group. The discussionfocuses on the spatiotemporal catalytic dynamics within singlenanocatalysts, which were obtained by combining real-time
single-turnover kinetics, super-resolution catalysis imaging,and correlation with electron microscopy of catalyst structures.The catalysts included pseudospherical nanoparticles andshaped nanocrystals made of Au or Pt. Interested readers arealso referred to the review papers cited above for other relatedstudies using single-molecule microscopy. A forthcomingreview article65 from us will discuss other techniques, includingelectrochemistry,66–72 surface plasmon resonance spectroscopy,73–78
scanning probe microscopy,79–81 scanning transmission X-raymicroscopy,82,83 and tip-enhanced Raman spectroscopy,84 that havebeen applied to study catalysis by single nanoparticles.
Peng Chen is the Peter J. W. Debye Professor of Chemistry at CornellUniversity. He received his BS from Nanjing University, China, in1997 and obtained his PhD with Prof. Edward Solomon inbioinorganic/physical inorganic chemistry from Stanford Universityin 2004. He then did postdoctoral research in single-moleculebiophysics with Prof. Sunney Xie at Harvard University, beforestarting at Cornell in 2005. His current research focuses on single-molecule imaging of nanocatalysis and bioinorganic chemistry.He has received a Dreyfus New Faculty award, a NSF Career award,a Sloan Fellowship, and a Paul Saltman Award.Eric Choudhary received his BS in 2008 and MS in 2009 fromRensselaer Polytechnic Institute. He is currently a graduate studentwith Prof. Peng Chen working on single-molecule fluorescenceimaging of nanoscale catalysis.Ningmu Zou obtained his BS in Chemistry from Nanjing University,
China, in 2011. He is currently a graduate student at Cornell University in the Department of Chemistry and Chemical Biology, workingon single-nanoparticle catalysis in Prof. Peng Chen’s group.Guanqun Chen received his BS in polymer materials and engineering from Zhejiang University, China, in 2011. He is currently a graduatestudent in Prof. Peng Chen’s group in the Department of Chemistry and Chemical Biology at Cornell University. His research is aboutsingle-molecule fluorescence imaging of metal nanoparticle catalysis.Hao Shen obtained his BS in Chemistry from Nanjing University, China, in 2007. He is currently a graduate student in Prof. Peng Chen’sgroup in the Department of Chemistry and Chemical Biology at Cornell University. His research is on single-molecule study ofelectrocatalysis by carbon nanotubes and other carbon-based materials.
(left to right): Guanqun Chen, Hao Shen, Ningmu Zou,Eric Choudhary, and Peng Chen
Xiaochun Zhou
Xiaochun Zhou obtained his PhDin Physical Chemistry from theChinese Academy of Sciencesin 2007, and worked as apostdoctoral fellow in theDepartment of Chemistry andChemical Biology at CornellUniversity on single-nanoparticlecatalysis in Prof. Peng Chen’slab from 2008 to 2013. He iscurrently a professor in theSuzhou Institute of Nano-Techand Nano-Bionics, ChineseAcademy of Sciences. His interests
include catalysis from microns to the atomic scale, decompositionof formic acid to high quality hydrogen and optimization of thinlayer electrodes.
Nesha May Andoy
Nesha May Andoy obtained herBS in Chemistry from theUniversity of the Philippines in2001 and her PhD in Chemistryfrom Cornell University in 2010working on single moleculestudies of metalloregulator–DNAinteractions, bioinorganic enzymo-logy, and nanoscale catalysis inProf. Peng Chen’s group. Currently,she is a postdoctoral fellow atHarvard Medical School studyingclathrin-coated pit assemblyusing single-molecule fluorescencetechniques.
2. Real-time single-nanoparticlecatalysis at single-turnover resolutionSingle-nanoparticle catalysis at single turnover resolution
Using wide-field total-internal-reflection fluorescence microscopyand a microfluidic reactor (Fig. 1A and B), we have studied catalysisby metal nanoparticles in two fluorogenic reactions: a reductiveN-deoxygenation reaction and an oxidative N-deacetylationreaction, both generating the fluorescent molecule resorufin(Fig. 1C). Fig. 2A is a wide-field fluorescence image of thecatalytic products generated from single 6 nm pseudosphericalAu nanoparticles in the N-deoxygenation reaction.30 Individualcatalytic reactions on a single nanoparticle are reported by theprobabilistic fluorescence bursts at a localized spot on the image,which is best presented in the corresponding fluorescence inten-sity vs. time trajectory (Fig. 2B). In this trajectory, each suddenintensity jump from the background marks a catalytic productformation event; each sudden intensity drop marks a productdesorption event; and each off–on cycle represents a singlecatalytic turnover on a single nanoparticle. Owing to the micro-scopic nature of single-molecule processes, the reaction eventsare stochastic, i.e., the occurrence of each catalytic productformation and desorption event is probabilistic. As a result,toff and ton, the two waiting times, are probabilistic, but theirstatistical properties, such as averages and distributions, aredefined by the underlying reaction kinetics.
Temporal catalytic dynamics of small nanoparticles
The single-turnover catalysis trajectory immediately allowed theexamination of temporal catalytic behaviors of a single nano-particle under steady-state reaction conditions. Strikingly, thetime-binned turnover rate of a single nanoparticle fluctuatessignificantly (e.g., Fig. 3A inset for a 6 nm Au nanoparticle30),suggesting temporal fluctuations of single-nanoparticle catalyticactivity, a phenomenon termed ‘‘dynamic disorder’’ in chemicalkinetics. Although more intuitive, this time-binned turnover rateas in Fig. 3A inset is not a reliable representation of temporalactivity fluctuations because of the probabilistic nature of singleturnover events and the limited turnover events binned in eachdata point. A reliable and quantitative representation is theautocorrelation function of the waiting times85,86 (e.g., Ct-off(m),
the autocorrelation function of toff, where m is the event indexin a single-turnover catalysis trajectory; Fig. 3A).30 The expo-nential decay of this autocorrelation function unambiguouslyreflects the temporal fluctuations of the single-nanoparticleactivity, and the exponential time constant gives the timescaleof the activity fluctuations.
This temporal activity fluctuation of a single Au nanoparticle isattributable to the nanoparticle’s dynamic surface restructuringthat is coupled to catalytic kinetics. The timescale of the activityfluctuation here reflects the timescale of the underlying surfacerestructuring dynamics. Fundamentally, the dynamic surfacestructure of a nanoparticle results from its nanometer dimen-sion, which renders it higher surface energy and lower restruc-turing activation energy compared with its bulk counterpart,and it can be observed directly by electron microscopy andother techniques.10–21,87–89 During catalysis, the continuallychanging adsorbate–surface interactions can further inducesurface reconstruction. Consistently, the activity fluctuationbecomes faster when the catalytic turnover rate increases(e.g., through increasing reactant concentrations), and thefluctuation slows down when the size of the nanoparticleincreases (Fig. 3B).90 By analyzing the size- and catalysis-dependentactivity fluctuations using a thermodynamic model,90 we obtainedthe activation energy and the rate of spontaneous surface restruc-turing, both of which show a clear size dependence as expected(Fig. 3C). With increasing size to about 40 nm, the activation
Kyu-Sung Han obtained his PhDfrom the Department of MaterialsScience and Engineering at KoreaAdvanced Institute of Science andTechnology (KAIST) in 2008, anddid a postdoctoral research inProf. Peng Chen’s group at CornellUniversity until 2012. He iscurrently a senior researcher atthe Korea Institute of CeramicEngineering and Technology(KICET), working on nanoscalematerials and catalysis.
Kyu-Sung Han
Fig. 1 Experimental scheme of single-molecule microscopy of fluoro-genic catalytic reactions on single nanoparticles. (A) Schematic of usingfluorogenic catalytic reaction, surface immobilized catalysts, and total-internal-reflection (TIR) laser excitation for imaging catalysis by singlenanoparticles. (B) Schematic of a prism-based TIR fluorescence micro-scope and a microfluidic reactor cell made between a slide and a coverslip.Note that the sample direction is upside down here relative to that in A.(C) Two fluorogenic catalytic reactions utilized in the studies reviewedhere. (A) adapted from Xu et al.30 (B) adapted from Chen et al.39 withpermission from The Royal Society of Chemistry.
energy saturates to about 5 kcal mol�1, while the rate of sponta-neous restructuring slows down to about 10�2 to 10�3 s�1,corresponding to a timescale of 102 to 103 s.90 Further theoreticalanalysis of this single-nanoparticle temporal catalytic dynamicssuggests that the underlying fluctuations occur in a more con-certed manner across all surface sites on a nanoparticle, ratherthan independently at localized individual sites.91
Moreover, the timescale of this restructuring is expected to bedependent on the catalyst material. Compared with Au nano-particles of the same size, single 4.6 nm Pt nanoparticles showsignificantly slower temporal fluctuations of their activity withinthe same range of catalytic turnover rates (Fig. 3D),45 consistentwith Pt being a more thermodynamically stable metal than Au.92
Regardless of the catalytic reaction being the N-deoxygenation orthe N-deacetylation reaction (Fig. 3D), the activity fluctuationrate of single Pt nanoparticles is the same, which is consistentwith the observation that the underlying dynamic surface restruc-turing is inherent to the nanoparticle, rather than determinedby the catalytic reaction. The activity fluctuation rate of Pt nano-particles is also independent of the catalytic turnover rate(Fig. 3D), indicating that the catalysis-induced contribution totheir dynamic surface restructuring is insignificant.
3. Spatially resolved activity patternswithin single shaped nanocrystalsSuper-resolution imaging of single-nanoparticle catalysis
Wide-field imaging of single-molecule fluorescence enablesthe localization of a molecule’s position down to nanometeraccuracy.53,54 This is typically done by fitting the fluorescence
point spread function with a 2D Gaussian function (Fig. 2C). Byapplying this localization analysis, one can immediately map thelocations of individual fluorescent catalytic products on a singlenanoparticle at super-optical resolution. For a 6 nm pseudosphericalAu nanoparticle, its apparent size from the locations of catalyticproduct molecules cannot resolve its physical dimension because ofthe limited spatial resolution (Fig. 4A). However, if the particle islarge enough, for example a B200 nm pseudospherical Au@mSiO2
particle, the apparent size from the product locations matchesclosely the particle’s physical dimension from SEM (Fig. 4B). Usingthis super-resolution catalysis imaging approach, we extracted theapparent sizes for a series of pseudospherical Au and Au@mSiO2
particles (Fig. 4C). For larger particles, their apparent sizes areessentially the same as their true physical sizes from TEM. Withdecreasing particle size to o40 nm, the apparent sizes from super-resolution catalysis imaging overestimate the true sizes and reach alimit value of about 15–40 nm, which reflects the resolution limit ofthis approach.
Site-specific catalytic activity on single shaped nanocrystals
We further applied the nanometer localization method to mapcatalytic reactions on two types of shaped nanocrystals: Au nanorods
Fig. 2 Single-nanoparticle catalysis at single-turnover resolution. (A) Single-molecule fluorescence image of product molecules on 6 nm pseudosphericalAu nanoparticles in catalyzing the N-deoxygenation reaction. (B) Segment ofthe fluorescence intensity trajectory from the fluorescence spot marked by thearrow in (A). (C) 3-D plot of a typical fluorescence image of a single resorufinproduct molecule (each pixel B 267 nm). The center position of this moleculecan be localized to nanometer accuracy. Inset: the corresponding fluores-cence image; the red cross marks the center position. (A) and (B) adapted fromXu et al.30 (C) adapted from Zhou et al.46
Fig. 3 Temporal catalytic dynamics of single nanoparticles. (A) Autocorrelationfunction of toff from a single 6 nm Au nanoparticle in catalyzing theN-deoxygenation reaction at a saturating reactant concentration. The solid lineis an exponential fit. Inset: the corresponding time-binned turnover rate of thisnanoparticle vs. time. Each data point is an average of 10 turnover events.(B) Surface restructuring rate (r, which is equivalent to the activity fluctuationrate) dependence on the single-nanoparticle turnover rate (v) and the nano-particle diameter (d) for pseudospherical Au nanoparticles. The meshed surfaceis a fit using a thermodynamic model.90 (C) Size dependence of the activationenergy (DEsp) and the rate (rsp) of spontaneous dynamic surface restructuring ofpseudospherical Au nanoparticles. The gray shades denote the approximateerrors. (D) Dependence of the activity fluctuation rate on the single-nanoparticleturnover rate of 4.6 nm Pt and Au nanoparticles in catalyzing theN-deoxygenation and/or the N-deacetylation reaction. (A) adapted from Xuet al.30 (B) and (C) adapted from Zhou et al.90 (D) adapted from Han et al.45
Copyright 2010 and 2012 American Chemical Society.
and nanoplates, both encapsulated in mesoporous silica of tensof nanometer thickness (i.e., Au@mSiO2 nanorods and nano-plates, Fig. 5A and B). The mSiO2 coating was necessary tostabilize the nanocrystals’ morphology and prevent their aggre-gation after removing their capping ligands for catalysis; thesecapping ligands were essential for achieving shape control insynthesizing these nanocrystals,93–96 but were detrimental forcatalysis. The mesopores were large enough to allow reactantsto access the Au surface readily so that mass transport did notlimit the catalytic kinetics.46,47
Fig. 5C and D show the maps of reaction products on a singleAu@mSiO2 nanorod and a single Au@mSiO2 nanoplate in catalyz-ing the N-deacetylation and N-deoxygenation reaction, respectively,overlaid on their respective SEM structural contour or SEM image.By analyzing these results at various reactant concentrations, wewere able to determine the specific catalytic rate constants forAu@mSiO2 nanorods or the specific turnover rates for Au@mSiO2
nanoplates at sub-particle resolution (Fig. 5E and F).The spatially resolved catalytic activity immediately revealed the
site-specific activities on these two types of nanocrystal catalysts.
For nanorods, the two ends are in general more active thantheir side facets (Fig. 5E).46 For nanoplates, their corner regionsare the most active, followed by their edge regions and thentheir flat facets (Fig. 5F).47 These site-specific activity patternscan be understood by assuming that the catalytic active sitesare low-coordination surface sites, which include corner andedge atoms and defects sites, and which are often more activedue to their coordination unsaturation.1,11 For nanorods, theirends have in general higher percentages of low-coordinationsites than their side facets. For nanoplates, the percentages oflow-coordination sites are the highest in the corner regions,lower in edge regions, and the lowest on the top flat facets.A recent study by Katz et al.97 further supports that for theN-deoxygenation reaction, the low-coordination sites on Aunanoparticles are the catalytic active sites.
Catalytic activity gradient within the same facets on a singlenanocrystal
Spatially resolved catalysis imaging at the nanometer scale alsoenabled the examination of catalytic activity at different loca-tions within the same surface facets on a single nanocatalyst.Surprisingly, we observed that the specific catalytic activity is
Fig. 4 Super-resolution imaging of single-nanoparticle catalysis. (A) 2-Dhistogram of catalytic product locations from a single 6 nm pseudo-spherical Au nanoparticle in catalyzing the N-deoxygenation reaction.The FWHM of the histogram is B30 nm, bigger than the physical size ofthe nanoparticle. (B) 2-D histogram of catalytic product locations from asingle B200 nm pseudospherical Au@mSiO2 particle in catalyzing theN-deacetylation reaction. The FWHM of this histogram is about the sameas its diameter from its SEM image (inset). (C) Correlation between the TEMouter-diameter and the apparent size from the super-resolution catalysisimaging across a series of pseudospherical Au and Au@mSiO2 particles.The apparent sizes were extracted from the super-resolution catalysisimaging via three different analysis methods (i.e., model fit, Gaussian fit,and Log Gaussian fit); see ref. 48 for details. Figures adapted from Zhouet al.48 Copyright 2013 American Chemical Society.
Fig. 5 Site-specific catalytic activity on single shaped nanocrystals. (A andB) TEM images of a Au nanorod (A) and a nanoplate (B) encapsulated inmesoporous silica. (C) 2-D histogram of catalytic product locations on asingle Au@mSiO2 nanorod in catalyzing the N-deacetylation reaction. Thered line is the structural contour of the nanorod from its SEM image. Thewhite lines divide the nanorod into 6 segments. (D) Locations of catalyticproducts mapped onto the SEM image of a single Au@mSiO2 nanoplate.Each dot is a product molecule. The product locations are color-codedbased on their regions: corners (green), edges (blue), and top facets (red).(E) Specific catalytic rate constant k of each segment of the nanorod in (C).(F) Specific catalytic turnover rate v for the three types of regions of thenanoplate in (D). (A), (C), and (E) adapted from Zhou et al.46 (B), (D), and (F)adapted from Andoy et al.47 Copyright 2013 American Chemical Society.
not only non-constant but also shows consistent gradientswithin the same surface facets on a single nanocatalyst. For aAu@mSiO2 nanorod, a pseudo-1-D nanocatalyst, the specificactivity along the length of its side facets shows a lineargradient in catalyzing the N-deacetylation reaction: highest inthe middle and decaying gradually toward its two ends (Fig. 6Aand B; and Fig. 5E as well).46 For a Au@mSiO2 nanoplate,a pseudo-2-D nanocatalyst, the specific activity within its flatfacets shows a radial gradient in catalyzing the N-deoxygenationreaction: highest in the center and decaying gradually towardits periphery (Fig. 6D and E).47 For individual Au@mSiO2
nanorods, the specific activity at the center of the nanorod canbe a factor of ten larger than the extrapolated specific activity forperfect side facets.46
These catalytic activity gradients within the same surfacefacets of a single nanocatalyst are attributable to the underlying
density gradients of surface defect sites, whose low-coordinationrenders them the catalytic active sites as described earlier. Thesedensity gradients of surface defects likely arise from the decayinggrowth rates during the solution-phase syntheses of the Aunanorods and nanoplates via seeded growth. The Au nanorodsgrow linearly from a seed93–95,98 and the Au nanoplates arebelieved to grow radially96,99–102 to form 1-D and 2-D nanostructures,respectively. However, their growth rate is not constant withtheir increasing length or size, and instead, the rate decaysgradually. This decaying growth rate has been determinedexperimentally for Au nanorods by Hafner et al.103—withincreasing length, the growth rate of a nanorod decays linearlyuntil the rate becomes zero when the growth stops. Therefore,there is a gradient of growth rate from the middle toward thetwo ends for a nanorod, and a similar one is expected from thecenter toward the periphery for a nanoplate. These growth rategradients would lead to surface defect density gradients,as faster crystal growth rates tend to result in more crystaldefects,104 giving rise to the specific activity gradients we observedexperimentally.
Interestingly, the magnitudes of the specific activity gradi-ents show size dependence. The longer or larger the nanorod/nanoplate is, the smaller the specific activity gradient it exhibits(Fig. 6C and F).46,47 This trend indicates that for longer or largernanorods/nanoplates, their surface defect densities have shal-lower gradients from the center toward their ends/periphery.These shallower gradients further suggest slower decays of theirseeded growth rates during the syntheses of the longer or largernanorods/nanoplates, which contribute to their eventual sizes.
The discovery of specific catalytic activity gradients withinthe same crystal facets on pseudo-1-D and pseudo-2-D nano-crystals has broad implications for studying and understandingthe catalytic activity of nanocrystal catalysts. This discoveryreinforces the importance of surface defects in determiningthe catalytic properties of metal surfaces, as well known in thesurface science of heterogeneous catalysts.1,105,106 For shape-controlled colloidal nanocrystals, for which facet information isoften used to explain activity, it is challenging to determinetheir surface defects, and the spatial distribution of defects isstrongly affected by the nanocatalysts’ growth pattern andsynthesis procedure. But it is imperative to consider them,so one can better use the knowledge from surface science tounderstand their activities.
Owing to the wide-field imaging format, the super-resolutionimaging approach to nanoparticle catalysis can be scaled upreadily to screen the activity of a large number of catalystparticles in parallel. We recently demonstrated this scalability,where quantitative activity can be obtained at the single-particlelevel that enables identification of high activity particles.48 Fig. 7Ashows the super-resolution catalysis image of B1000 particles froma mixture of pseudospherical 21@42 and 102@32 nm Au@mSiO2
Fig. 6 Catalytic activity gradients within the same facets. (A) 2-D histogramof catalytic product locations on a single Au@mSiO2 nanorod in catalyzingthe N-deacetylation reaction. The red line is the SEM structural contourof the nanorod. The white lines separate out the two ends. (B) Dependenceof the specific turnover rate on location at every B20 nm segment alongthe length of the nanorod in (A). The specific turnover rate shows a lineargradient from the middle toward the two ends. (C) Dependence of the linearactivity gradient bL on the nanorod length L. (D) Locations of productmolecules overlaid on top of the SEM image of a single Au@mSiO2
nanoplate. The top facet is divided into radial segments from the centertoward the periphery; the product locations in different segments arecolored differently. The product molecules residing in the corner and edgeregions are not plotted here. (E) Dependence of the specific turnover ratesof radial segments on r2, where r is the distance along the center-to-cornervector of the nanoplate. (F) Dependence of the radial activity gradient bR onthe nanoplate radius R, which is defined along the center-to-corner vector.(A)–(C) adapted from Zhou et al.46 (D)–(F) adapted from Andoy et al.47
particles in catalyzing the reductive N-deoxygenation reaction,in direct correlation with their SEM image (Fig. 7B). Individualparticles are clearly resolved, even within aggregates, and withquantitative activity information (i.e., their rates of turnovers).For example, particle 1 is clearly more active than particle 2(Fig. 7A inset), even though they are similar in size (Fig. 7Binset). Statistical distribution can be readily obtained amongthe large number of particles, for example for particle activityand size (Fig. 7C), where the two subpopulations are clearlyresolvable in the corresponding 2-D histogram (Fig. 7D). Thisstatistical analysis not only immediately shows the generaltrend (i.e., large particles are more active on a per-particlebasis), but also identifies outliers: some smaller particles showsignificantly higher activities (e.g., particle 3, Fig. 7C), whereassome larger ones show lower activities (e.g., particle 7, Fig. 7C).This direct identification of catalyst activity at the single-particlelevel is exciting, because one can now pinpoint the particle ofdesired activity for subsequent structural characterizations,although our structural characterization is currently just at theSEM level, which is insufficient to identify the structural basis ofactivity differences.
We have also demonstrated this parallel screening of a largenumber of pseudospherical particles in catalyzing the oxidativeN-deacetylation reactions, as well as of particles that have amixture of different shapes. With motorized fluorescence micro-scopes and larger camera formats, this screening approach canbe scaled up significantly to identify highly active particlesamong many thousands, which can then be selected for sub-sequent high-resolution structural and compositional analysis,for example using high-resolution electron microscopy.107 Coupled
with combinatorial or parallel synthesis of catalysts,108–116
one can envision that this approach can be powerful forassessing catalyst preparation processes and the performanceof resulting catalysts. The information can then be fed back tothe next round of catalyst synthesis and optimization, whichwould accelerate the discovery and development of new orbetter catalysts.
5. Concluding remarks
The single-molecule fluorescence microscopy approach isgenerally applicable for studying chemical catalysis,37,39
electrocatalysis,35,39 and photocatalysis.38 The approach isamenable to any catalyst material, such as metals, metal oxides,and metal sulfides, and to a wide range of catalyst sizes, suchas nano, micro, or bulk dimensions, or even small moleculecatalysts.117 This approach certainly has limitations, such asthe requirement of fluorescent molecules, as discussed in detailin our previous review.39 However, the chemical transforma-tions to be studied are not limited; for example the tworeactions in Fig. 1C represent two distinct chemical transforma-tions. Other fluorogenic reactions are available too (e.g., trans-esterification28 and nitro reduction41 reactions). With cleversynthetic chemistry, one can design reactant molecules thatundergo the desired chemical transformations to generate afluorescent product molecule.118
Moreover, it may not even be necessary to design fluorogenicreactions in order to evaluate the activity of catalysts in aparticular chemical transformation at the single-particle level.
Fig. 7 Parallel activity screening of a mixture of 21@42 nm and 102@32 nm Au@mSiO2 particles. (A) Super-resolution catalysis image (i.e., 2-D histogramof catalytic product locations) of B1000 particles in catalyzing the reductive N-deoxygenation reaction. Inset: a zoom-in. (B) SEM image of the same setof particles as in (A) with a zoom-in inset. (C) Scatter plot of individual catalyst particles against their respective SEM diameters and rates of turnovers (v, ins�1 particle�1 in log scale) from (A) and (B). Each point represents one particle. Insets: SEM images of selected particles. (D) Contour plot of the 2-Dhistogram of (C). Figure adapted from Zhou et al.48 Copyright 2013 American Chemical Society.
In our study of screening a large number of catalyst particles,48
we showed that the catalytic activities of Au and Au@mSiO2
particles in the fluorogenic N-deoxygenation reaction are linearlycorrelated with those in the reduction of nitrophenol (Fig. 8A).A linear activity correlation was also observed between theN-deacetylation reaction and the oxidation of hydroquinone(Fig. 8B). These correlations demonstrate that for the non-fluorogenic nitrophenol reduction and hydroquinone oxidationreactions (both are standard model reactions for evaluatingcatalysts119), we can use the two fluorogenic probe reactions inFig. 1C to obtain equivalent information in evaluating the catalystactivity. This correlation approach can be broadly applied tomany other catalytic reactions—one just needs to establish theircorrelations with a fluorogenic reaction using conventionalensemble measurements before applying the single-moleculefluorescence microscopy approach.
The single-nanoparticle catalysis measurements also makeit straightforward to correlate catalysis with single-nanoparticlestructural studies using, for example, electron and X-ray micro-scopy.67,102 One-to-one correlation with SEM can be readilyperformed (for example in ref. 46–48, 77, and 120). Correlationbetween optical microscopy and TEM can also be achieved (e.g.,in ref. 121 and 122). However, many challenges still remain.One of them is the resolution limit. Single-molecule fluorescencedetection based super-resolution microscopy has so far a fewnanometer resolution to the best, which is an order of magnitudeworse than the atomic resolution available in electron microscopyfor structural characterization. Another is the limited time resolu-tion, ms at best, which cannot resolve the actual chemical trans-formations that occur at sub-picosecond timescales. Chemicalinformation from fluorescence is also limited; here single-moleculevibrational spectroscopy via surface enhanced Raman scattering(SERS) can be a complementary and powerful approach.123–128
In combination with other detection methods, as well as othermanipulation methods such as electrical or optical manipulations,one can access a plethora of information towards understandingthe structure–activity correlations of catalysts.
Acknowledgements
We thank the Department of Energy (DE-FG02-10ER16199),Army Research Office (W911NF0910232), and National ScienceFoundation (CBET-1263736) for funding the research reviewedhere. We also thank the former members of the Chen group fortheir scientific contributions.
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