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Scanning transmission electron microscopy andits application to the study of nanoparticlesand nanoparticle systems

Jingyue Liu*

Monsanto Company, U1E, 800 North Lindbergh Boulevard, St Louis, MO 63167, USA

*E-mail: jingyue.liu@monsanto.com

............................................................................................................................................................................................................................................

Abstract Scanning transmission electron microscopy (STEM) techniques can

provide imaging, diffraction and spectroscopic information, either

simultaneously or in a serial manner, of the specimen with an atomic

or a sub-nanometer spatial resolution. High-resolution STEM imaging,

when combined with nanodiffraction, atomic resolution electron energy-

loss spectroscopy and nanometer resolution X-ray energy dispersive

spectroscopy techniques, is critical to the fundamental studies of

importance to nanoscience and nanotechnology. The availability of

sub-nanometer or sub-angstrom electron probes in a STEM instrument,

due to the use of a field emission gun and aberration correctors, ensures

the greatest capabilities for studies of sizes, shapes, defects, crystal and

surface structures, and compositions and electronic states of nanometer-

size regions of thin films, nanoparticles and nanoparticle systems. The

various imaging, diffraction and spectroscopy modes available in a

dedicated STEM or a field emission TEM/STEM instrument are reviewed

and the application of these techniques to the study of nanoparticles and

nanostructured catalysts is used as an example to illustrate the critical

role of the various STEM techniques in nanotechnology and nanoscience

research.............................................................................................................................................................................................................................................

Keywords electron microscopy, STEM, Z-contrast microscopy, nanodiffraction,

SEM, EELS, EDS, Auger, nanoparticle, supported catalyst, surface............................................................................................................................................................................................................................................

Received 23 December 2004, accepted 13 March 2005, online 25 August 2005............................................................................................................................................................................................................................................

Introduction

Advanced electron microscopy techniques, especially

scanning transmission electron microscopy (STEM) tech-

niques, are indispensable for characterizing interfaces

and defects, nanodevices, nanoparticles and catalysts, and

other nanosystems. The single most important feature of a

STEM instrument is its versatility: atomic resolution images,

diffraction patterns from nanometer regions and nanometer-

scale spectroscopy data can be obtained either simultan-

eously or sequentially from the same region of the specimen.

The availability of the various imaging, diffraction, and

spectroscopy techniques within a single instrument makes

STEM the most powerful microscope for characterizing

the physicochemical nature of nanoscale systems.

When an electron nanoprobe interacts with a specimen

inside a STEM instrument, a variety of electron, electro-

magnetic and other signals can be generated. Figure 1 shows

a schematic diagram illustrating the common signals that

are used in a dedicated STEM instrument. All these signals

can be used to form images or diffraction patterns of the

specimen or can be analyzed to provide spectroscopic

information. For example, by collecting high-angle scattered

electrons with an annular detector, high-angle annular

dark-field (HAADF) images (also called Z-contrast images)

can be formed to provide information about structural

variations across the sample on an atomic level. Electron

energy-loss spectroscopy (EELS), which is based on theDedicated to the memory of the late Professor John M. Cowley.

� The Author 2005. Published by Oxford University Press Journal of Electron Microscopy 54(3): 251–278 (2005)on behalf of Japanese Society of Microscopy. All rights reserved. doi:10.1093/jmicro/dfi034For permissions, please email: journals.permissions@oxfordjournals.org

energy analysis of the inelastically scattered electrons, can

provide information on the electronic structure, oxidation

states, and chemical composition on an atomic or sub-

nanometer scale. X-ray energy dispersive spectroscopy

(XEDS) can give quantitative data describing changes of

elemental composition associated with inhomogeneous

structures of the sample. The combination of XEDS and

EELS with HAADF imaging technique can provide detailed

information on the composition, chemistry, and electronic

and crystal structure of nanoscale systems with atomic

resolution and sensitivity. By collecting or analyzing sec-

ondary electron (SE) and Auger electron (AE) signals

emitted from the specimen surface, we can extract informa-

tion about the surface topography or surface composition

of the specimen. By positioning an electron nanoprobe

at the area of interest, coherent electron nanodiffraction

(CEND) patterns from individual nanocomponents can be

acquired to provide multitudinous information on the

nanostructure of the specimen. The powerful combination

of high-resolution imaging with nanospectroscopy and

nanodiffraction techniques has proved invaluable in solving

a plethora of materials problems, including challenging

industrial problems.

Professor John M. Cowley dedicated >30 years of his

research effort to exploring, developing and establishing

various imaging, diffraction and spectroscopic techniques

that can be practiced in a dedicated STEM instrument. Using

a heavily modified HB5 STEM instrument from VG Micro-

scopes, Ltd of England (see Fig. 2), Professor Cowley

investigated the various modes of high-resolution STEM

imaging [1–41], developed optical systems for conveniently

recording nanodiffraction patterns, and established the

nanodiffraction technique as a viable alternative to invest-

igate the structures of nanoscale systems including small

Fig. 1 Schematic diagram illustrates the various signals generated inside a scanning transmission electron microscope that can be used to

form high-resolution images, nanodiffraction patterns or spectra of the region-of-interest. X-ray energy dispersive spectroscopy (XEDS);

Auger electron spectroscopy (AES) and scanning Auger microscopy (SAM); secondary electron spectroscopy (SES) and secondary electron

microscopy (SEM); annular dark-field (ADF) and high-angle annular dark-field (HAADF); coherent electron nano-diffraction (CEND);

parallel electron energy-loss spectroscopy (PEELS); bright-field (BF) and dark-field (DF).

252 J O U R N A L O F E L E C T R O N M I C R O S C O P Y , Vol. 54, No. 3, 2005

particles, surfaces and biological systems [4–8,42–66].

Throughout his experimental research activities at Arizona

State University, Professor Cowley steadfastly explored

various avenues, including holography, atomic focuser and

diffraction imaging in recent years to improve resolution

in STEM. Not only did he develop theories for various

imaging and diffraction techniques but he also applied these

new methods to the structural study of surfaces and

interfaces, small particles and supported catalysts, localized

defects and disordering, carbon nanotubes and many other

nanosystems.

The incorporation of atomic resolution STEM techniques

into the newer generation field-emission TEM instruments

[67–69] and the revival of the experimental dedicated STEM

instruments, especially the ones incorporating the aberration

correctors or monochromators [70–77], clearly demon-

strated the increasing acceptance and the power of STEM

techniques that Professor Cowley had been championing for

the last 30 years. The recent achievement of sub-angstrom

resolution imaging [72,73,76] and atomic scale spectroscopy

[74,75] in Cs-corrected STEM instruments will undoubtedly

further enhance and expand the impact of STEM techniques

on nanoscience research. Professor Cowley recently stated:

‘STEM is finally coming into age and will soon become

mainstream’.

There have been many reports, in the last decade or so, on

atomic resolution HAADF imaging and EELS techniques as

well as the application of these techniques to the study of

interfaces and defects [69,78–81], quantum dots [82], and

nanoparticles and supported catalysts [83–90]. Most of these

studies, however, focused primarily on the HAADF and

EELS techniques and capabilities. While the combination of

these two atomic resolution techniques has proved to be

extremely powerful for solving materials problems (espe-

cially interface structures), other imaging, diffraction and

spectroscopic techniques readily available in a STEM instru-

ment can provide complementary and unique information

on the specimen of interest. In this paper, we review some

recent developments of the various STEM techniques, which

are pioneered by Professor John M. Cowley, with a focus

on applying these techniques to the fundamental study of

nanoparticles and nanoparticle systems.

Fig. 2 The heavily modified VG HB-5 scanning transmission electron microscope of which Professor John M. Cowley used at Arizona

State University for all his experimental research work. The black box (indicated by the arrow) contained the unique optical system that

transfers the light to the various photomultipliers (PMs) and the low-light sensitivity TV camera. The ADF images were formed by positioning

a light-absorbing mask in the center of the optical system. In the late 1980s, we used to use a US coin of a penny, a dime or a quarter as

the mask of the diffraction pattern and were able to independently vary the inner and outer collection angles of the ADF detector. Other

configured STEM detectors were also tried by masking the various parts of the diffraction pattern displayed on the optical system inside the

black box.

J. Liu STEM of nanoparticles and surfaces 253

STEM imaging: shadow image,projection microscopy and electronRonchigrams

The simplest form of imaging in a STEM instrument is

shadow imaging (also called point projection microscopy).

Projection microscopy was proposed as early as 1939 by

Morton and Ramberg [91]. In a projection microscope, the

greatly magnified shadow of an object can be obtained

by using the quasi-radial propagation of a point or small

electron source with the object inside the beam path; it is

essentially a lensless microscope based on the radial pro-

pagation of an electron beam from a point source. The

magnification of the shadow image on the observation

screen is determined by the ratio of the distance between

the observation screen and the point source to the distance

between the object and the point source. Magnifications of

106–107 can be easily achieved when the object-to-point

source distances are in the range of �10 nm.

The use of a small electron source originating from a field-

emission gun in a STEM instrument guarantees the complete

coherence of the convergent electron nanoprobe imping-

ing onto the specimen. In contrast to conventional high-

resolution TEM (HRTEM) imaging, the individual incident

rays of different angles within the coherent convergent

nanoprobe can interfere with each other; the diffraction of

the coherent beam by the specimen and the interference

among the incident and diffracted beams can result in

complicated forms of shadow images. In fact, in his original

paper on holography, Gabor [92] proposed that a very small

source of electrons should be placed close to a thin object

to form a highly magnified shadow image that could be

regarded as a hologram; with the correction of the lens

aberrations, the object could be reconstructed thereby result-

ing in much improved image resolution. To accomplish what

Gabor proposed, a high-brightness, ultra-stable, small elec-

tron source is needed; the availability of a nanoprobe in a

dedicated STEM or field emission TEM/STEM instrument

makes this proposal more feasible now. Some early experi-

mental results explored the practicality of this reconstruc-

tion process [14]. The principal difficulty of employing this

in-line STEM holography, however, originates from finding

suitable ways of separating the conjugated images [14,27].

With the incorporation of Cs-correctors [70] or the use of

high-brightness nanotips [93], which provide near-point

sources, and the availability of high dynamic-range CCD

cameras and fast computers, Gabor’s proposal should

become more practical and greatly improved resolution

should be achievable by reconstructing the objects from

in-line holograms.

When a small electron probe interacts with a thin

specimen in a STEM instrument, the high-energy incident

electrons are scattered. The amplitude distribution of the

transmitted electrons at the far-field can be described by a

wave function C(K,X). The variable K is a 2-D vector in

the reciprocal space with |K| ¼ 2sin(y/2)/l (where y is the

scattering angle and l is the wavelength of the incident

electrons) and X designates the electron probe position on

the specimen. When the electron probe is scanned across the

specimen, variations of C(K,X) carry information about the

electron beam–specimen interactions. If the wave function

C(K,X) of the transmitted high-energy electrons can be

determined, we can extract structural information about the

specimen. It is, however, not possible to directly measure

C(K,X); instead, the intensity distribution of the trans-

mitted electrons is observed on the detector plane, which

is located at a large distance from the specimen, I(K,X) ¼|C(K,X)|2. The wave function C(K,X), to first-order

approximation, can be expressed as:

C K,Xð Þ ¼ Q Kð Þ * T Kð Þexp�i2pK ·Xð Þ½ � ð1Þ

where Q(K) is the Fourier transform of the transmission

function, q(x), of the specimen and the * symbol represents

convolution. The transfer function of the microscope, T(K),

is given by:

T Kð Þ ¼ A Kð Þexp �iw Kð Þf g ð2Þ

where the aperture function, A(K), is given by:

A Kð Þ ¼1 for K<K0

0 for K>K0

8<: ð3Þ

where K0 is the cut-off wave-vector determined by the

aperture size of the probe-forming lens. The aberration

function of the objective lens, w(K), is approximated by (for a

non-corrected objective lens):

w Kð Þ ¼ � pDlK2 þ 0:5pCsl3K4 ð4Þ

where D is the defocus value of the electron probe and Cs is

the spherical aberration coefficient of the objective lens. In

the phase object approximation [24], the specimen trans-

mission function q(x) can be approximated as:

q xð Þ ¼ exp�isf xð Þð Þ ð5Þ

where s¼ p/(lE0) is the interaction constant, E0 is the

accelerating voltage and f(x) is the projected specimen

potential along the incident beam direction.

The amplitude distribution of the coherent incident probe

is represented by:

P Rð Þ ¼ZT Kð Þexp�i2pK ·Rð ÞdK ð6Þ

The amplitude distribution of the incident probe, P(R), is

determined by the Fourier transform of T(K), which is

determined by the aperture function A(K) and the aberra-

tion function w(K) of the objective lens. The probe size,

therefore, depends on the spherical aberration coefficient

of the objective lens, the wavelength of the incident elec-

trons, the size of the objective aperture and the defocus

value of the electron beam. The integral in eq. (6),

unfortunately, cannot be done analytically and must be

obtained numerically. In practice, the spherical aberration

coefficient of the objective lens and the wavelength of the

254 J O U R N A L O F E L E C T R O N M I C R O S C O P Y , Vol. 54, No. 3, 2005

incident electrons are not variables during an experiment;

the operator, however, can manipulate the size and shape of

the coherent electron nanoprobe by varying the size of the

objective aperture and the defocus value of the electron

beam.

If no objective aperture or a very large objective aperture

is used, then the stationary incident probe can be very large

depending on the defocus value of the electron beam.

Images formed in this way in the back focal plane are similar

to low magnification TEM images. Depending on the sign of

the electron beam defocus, the image magnification can be

positive or negative and the image contrast can be reversed.

This imaging mode can be conveniently used for the initial

survey of specimen features or for monitoring the specimen

movement when specimen tilt is required. Note that out-of-

focus shadow images are projection images observed in the

back-focal diffraction plane with a stationary electron beam.

When the third-order spherical aberration is dominant,

as in the round lenses used in electron microscopes, the

projection image of the specimen placed close to the position

of the minimum diameter of the incident probe, as illustrated

in Fig. 3a, is greatly distorted due to the aberrations of the

objective lens. For paraxial rays (e.g. the ray #4 in Fig. 3a),

the beam crossover is after the specimen so that the

magnification of the central part of the projection image is

high but negative (region 4 in Fig. 3b). For marginal rays

(e.g. the ray #1 in Fig. 3a), the crossover is before the

specimen so that for the outer part of the projection image

the magnification is high but positive (region 1 in Fig. 3b).

For a particular set of rays (e.g. the ray #2 in Fig. 3a), the

beam crossover is right at the specimen level so that the

magnification of the projection image of that specimen

region becomes infinity (region 2 in Fig. 3b). Taking into

account of the 3-D nature of the rays and the specimen, we

can deduce that there is one radius of infinite tangential

magnification (labeled as T in Fig. 3b) and another radius of

infinite radial magnification (labeled as R in Fig. 3b).

Note that in the shadow image of Fig. 3b the image

magnification changes continuously along the radius from

the optical axis. Furthermore, each point in the image can be

described by a wave vector K and its intensity I(K,X) is

determined by the wave function C(K,X) given in eq. (1).

The effect of the beam defocus on the final image can be

more appreciated if we imagine that instead of changing

Fig. 3 Schematic diagram (a) illustrates the effect of spherical aberration of the probe-forming lens on the crossover of the STEM probe.

Shadow images of amorphous carbon film at under-focus (b), near-focus (c) and over-focus (d). The tangential (T) and radial (R) circles of

infinite magnification are clearly discernible in (b). The circle in (c) indicates the optimum angular size of the objective aperture to be used for

high-resolution imaging.

J. Liu STEM of nanoparticles and surfaces 255

the beam defocus we move the specimen along the optical

axis (see Fig. 3a). For example, when the sample is posi-

tioned right below the paraxial crossover, shadow images of

amorphous materials similar to Fig. 3d can be obtained. All

the points in the shadow image have a negative magnifica-

tion and the contrast of the features is reversed (e.g. heavy

scatterers appear bright).

At close to the Gaussian defocus, a position called fusiform

focus (uniform focus) [94] exists; the position of this fusiform

focus is between the paraxial focus and the marginal one.

For a thin amorphous film, an almost featureless disc appears

in the center of the shadow image when the specimen is at

the fusiform focus position as shown in Fig. 3c. The angular

size of the disc is determined by the lens aberrations (pri-

marily third-order spherical aberrations for non-corrected

lenses) and the wavelength of the incident electrons.

The smaller the Cs value of the microscope, the larger the

featureless disc.

The presence of the almost featureless disc in shadow

images of amorphous materials proves to be very useful for

the practical operations of a STEM instrument. First, the

center of the disc defines the coma-free optical axis of the

electron beam so that it can be used as the reference for

alignment of other components [6,7,12,13,68]. Second, the

size of the disc defines the optimum aperture size that should

be used to form the smallest electron nanoprobe. Electrons

arriving at the specimen from larger incident angles (outside

the circle in Fig. 3c) do not contribute to the central peak of

the coherent electron nanoprobe; instead, they add to the

oscillating tails, thereby broadening the electron nanoprobe.

Accordingly, if one desires to have most of the electrons

confined to the smallest central peak, then one should

allow only the electrons with incident angles smaller than

the one defined by the circle in Fig. 3c to enter the objective

aperture. For high-resolution annular dark-field (ADF)

imaging, however, an objective aperture with an angular

size larger than the optimum angle is sometimes used in

order to have a narrower central peak of the electron probe

(at a larger under-focus value), thereby providing higher

image resolution at the expense of the image contrast [25].

Another important use of the shadow image of amorphous

materials is to correct the axial astigmatism in the STEM

imaging mode. If the objective lens has astigmatism, the

circular symmetry of the featureless disc or the circle of

infinite magnification is distorted. The degree and direction

of the distortion are determined by the lens astigmatism.

Similar to the use of a tableaux of diffractograms for

astigmatism correction in a HRTEM instrument, shadow

images of amorphous materials can be effectively used to

correct these aberrations. Figure 4 shows a set of shadow

images of the same region of an amorphous carbon film

demonstrating the use of shadow images to correct the

astigmatism of the probe-forming system. Shadow images

can also be used to monitor the instabilities of the micro-

scope and the specimen; instabilities well below 0.1 nm can

be easily discerned in near-focus shadow images.

Correlation of shadow images, obtained from different

probe positions, can provide the exact magnification of the

selected points in the shadow images. The quantification of

the local magnifications in a large portion of the shadow

image provides an avenue to calculate the axial aberration

coefficients and other parameters that control the per-

formance of the probe-forming systems. The availability of

high-sensitivity CCD detectors and fast desktop computers

makes it now possible to quickly auto-tune Cs-correctors

based on the shadow images [71]. The effective use of

shadow imaging to properly align and tune the electron

optical system clearly contributes significantly to achieve

resolution improvement in STEM instruments by using

Cs-correctors [73].

When the specimen is a thin, crystalline material and

when the beam is aligned along a zone axis or in a direction

for systematic diffraction, the shadow image of a set of

parallel lattice planes is distorted by the lens aberrations

to give a set of loops or serpentine fringes. Such fringes are

also known as Ronchi fringes or Ronchigrams in honor of

Ronchi who observed such fringes when a diffraction grating

was placed near the focus of a large telescope mirror and

who correlated the presence of such fringes to the lens

aberrations [94]. Typical Ronchi fringes in electron shadow

images of crystalline materials are shown in Fig. 5. Similar

to the discussion of shadow images of amorphous materials,

the distortion of the straight lattice planes, especially near

focus, is caused by the lens aberrations. The distortion is

smaller for large defocus values and for lenses that have

smaller Cs values. The Ronchi fringes in the electron

Ronchigrams should have the exact symmetry as that

of the crystal in that particular orientation. Thus, one can

use the electron Ronchigrams to correct astigmatism, to

align the microscope and to center the objective aperture.

Measurements of the dimensions of the fringe features

in electron Ronchigrams of thin crystals can provide

accurate values of the spherical aberration coefficient of

the objective lens and the exact focus value of the electron

probe [13]. The electron Ronchigrams obtained at the

under-focus (Fig. 5a), near-focus (Fig. 5b) and over-focus

(Fig. 5c) settings have very different forms, which provide a

simple and convenient way to align and tune the electron

optical system and to orient the crystalline specimen region

of interest.

Large under-focus electron Ronchigrams of zone axis

crystals can provide a readily interpretable image of the

crystal lattice. Figure 5d shows such an electron Ronchigram

of a GaAs crystal oriented along the [011] zone axis. Fringes

representing the crystal lattice spacings can be seen in all

directions near the optical axis. At large angles, the fringes

are distorted because of the spherical aberration of the

objective lens. Their distortion, as a function of angle from

the coma-free optical axis, is circularly symmetric and their

intensity distribution can be affected by the beam alignment

with the exact zone-axis of the crystal. With the use of the

aberration correctors in a STEM instrument, the regions of

256 J O U R N A L O F E L E C T R O N M I C R O S C O P Y , Vol. 54, No. 3, 2005

interpretable image of the crystal lattices in the under-focus

electron Ronchigrams should be significantly enlarged.

Therefore, high-resolution information of local regions can

be extracted from the point projection microscopy images.

The resolution obtainable in this projection microscopy

mode should be comparable to that of the scanned STEM

images.

STEM imaging: convergent beamelectron diffraction and bright-fieldand dark-field high-resolution imaging

When an objective aperture is used to limit the large-angle

rays entering the objective lens, convergent beam electron

diffraction (CBED) patterns are formed on the detector

plane. If the specimen is a thin crystal oriented along a

principal zone-axis, instead of shadow images or electron

Ronchigrams as discussed above, a CBED pattern consisting

of sets of convergent beam discs is obtained as schematically

illustrated in Figs 6a (side view) and 6b (top view). Each

diffraction disc subtends the same semi-angle a, which is

determined by the angular size of the objective aperture, at

the specimen. If a > yB (yB is the Bragg diffraction angle of

the diffracting planes), then the convergent beam diffraction

discs overlap as shown in Fig. 6c. For thin, perfect crystals,

the electron intensity within non-overlapping regions (e.g.

the region indicated by numeral 1 in Fig. 6b) is independent

of the probe position and the aberrations of the probe-

forming lens [4,5]. The electron intensity within regions

where discs do overlap depends on the probe position, the

lens aberrations and the defocus values of the objective lens.

The intensity modulations in regions of overlapping discs are

caused by coherent interference of high-energy electrons

that have different incidence-beam directions (different

incident wave vector Ki) but that are scattered into the same

direction (the same final wave vector Kf) by the crystal.

Fig. 4 A set of shadow images of an amorphous carbon film illustrates the use of shadow images to correct the astigmatism of the

probe-forming lens, to find the coma-free optical axis, and to determine the defocus value of the electron beam.

J. Liu STEM of nanoparticles and surfaces 257

The formation of interference fringes in the overlapping

regions is purely caused by the coherent nature of the

convergent electron nanoprobe.

If a detector is used to collect the signal in the diffraction

plane, then a STEM image is formed when the electron

nanoprobe is scanned across the specimen. Depending on

the detector configuration and positioning, various forms of

STEM images can be generated; the image interpretation,

the achievable resolution and the contrast mechanisms of the

acquired STEM image are determined by the shape and

the size of the detector. In STEM imaging, in addition to

the probe size, detector function is the other most important

variable.

For a fixed probe position X at the sample, the intensity

distribution of the transmitted electrons on the diffraction

observation screen is given by I(K,X) ¼ |C(K,X)|2. The

observed image intensity, I(X), as a function of the beam

position X, is given by:

I Xð Þ ¼ZD Kð ÞjC K,Xð Þj2 dK ð7Þ

where D(K) is the transmission function of the detector.

The detector function, D(K), plays the most important role

in determining the nature of STEM imaging. For example, if

D(K) � 1 for all scattering angles, the STEM image is formed

by collecting all the high-energy electrons penetrating

through a thin specimen. If the backscattering and the

electron absorption effects by the sample are negligible,

then, the image intensity I(X) should not vary with the

beam position X at all because of the conservation of

the total number of the high-energy electrons. Therefore,

no contrast will be observed in the STEM image, and

no information about the specimen can be inferred. When

the specimen becomes thicker, however, the absorption

and backscattering of high-energy electrons become appre-

ciable so that an absorption contrast should be observable.

(The imaging theory of backscattered electrons may be

applicable here.)

On the other hand, If D(K) ¼ d(K) or d(K � G) where G

is a reciprocal lattice vector, then eq. (7) reduces to: I(X) ¼|C(0, X)|2 or |C(G, X)|2. This is the same form as for BF or

DF TEM imaging with parallel illumination. If a very small

Fig. 5 Electron Ronchigrams of a GaAs crystal at under-focus (a), near-focus (b) and over-focus (c). Under-focus electron Ronchigram of a

GaAs crystal oriented along the [011] zone axis shows 2-D lattice fringes (d). Electron Ronchigrams of (a)–(d) were obtained (recorded on a

tape) on the VG HB-5 STEM shown in Fig. 2. For comparison, image (e) shows an electron Ronchigram of a silicon crystal obtained (recorded

on a CCD camera) on the JEOL 2010F TEM/STEM.

258 J O U R N A L O F E L E C T R O N M I C R O S C O P Y , Vol. 54, No. 3, 2005

detector is positioned at any point in the overlapping regions

of the diffraction discs, lattice fringes should be obtained by

scanning the electron probe across the specimen. Two-

dimensional lattice fringes can be obtained by positioning

the STEM detector at a point where three or more non-

systematic diffraction discs overlap. These multiple-beam

interference regions are labeled as numeral 3 (three-beam

interference) and numeral 4 (four-beam interference) in

Fig. 6b. High-resolution BF STEM images can, therefore, be

interpreted exactly as those of HRTEM images. Figure 6d

shows such a BF STEM lattice image of a titania nanoparticle;

the inset in Fig. 6d is the corresponding diffractogram of

the high-resolution BF STEM image. Nanoparticles of

titania are used in many commercial applications, including

industrial catalysts, paints, coatings and fillings in fibers.

High-resolution dark-field STEM images can be easily

obtained by moving the detector to a point outside the

directly transmitted disc. For example, a 2-D DF STEM lattice

image can be obtained by shifting the STEM detector to

position D, which is labeled in Fig. 6b. DF STEM

imaging technique is useful for identifying small particles

in supported metal catalysts, defects in extended crystals and

different phases in polycrystalline nanophase materials.

Similar to the tilted dark-field imaging in HRTEM,

DF STEM technique can provide higher image resolution

under optimum conditions [4,5].

The contrast of high-resolution STEM images varies with

the displacement of the STEM detector. The movement of

the STEM detector corresponds to beam tilt in TEM. In

STEM, however, the relative shift of the BF detector is easily

accomplished by deflecting the whole diffraction pattern

with the use of scanning coils. Unlike beam tilt in TEM, the

movement of scanning coils does not perturb the optical

alignment of the STEM microscope. Thus, the contrast of

specific features of a sample can be conveniently enhanced

or reduced by shifting the position of the STEM detector

Fig. 6 Schematic diagrams show the formation of convergent electron beam diffraction patterns with overlapping disks: (a) side view and (b)

top view. The numerals in (b) indicates the number of overlapping diffraction discs in that region of the diffraction plane. Coherent

convergent electron beam diffraction pattern from a GaAs crystal oriented along the [011] zone axis (c) shows the overlapping discs. Bright-

field STEM image of a TiO2 nanoparticle (d) shows 2-D lattice fringes and the corresponding diffractogram is shown in the inset.

J. Liu STEM of nanoparticles and surfaces 259

without the complication of misaligning or realigning

the microscope. This method is useful for imaging highly

inhomogeneous samples, especially for identifying small

particles or for imaging inter-phase interfaces with enhanced

chemical sensitivity. The disadvantage of both the BF and

DF STEM imaging modes is that most of the transmitted

electrons are not utilized.

STEM imaging: large-angle bright-fieldand ADF imaging

The phase contrast of BF STEM images rapidly decreases

with the increase of the detector size. By applying the

Principle of Reciprocity [1], we can deduce that the increase

of the detector size in STEM is equivalent to the increase in

the illumination convergence angle in TEM. The use of large

convergence angles of illumination in TEM pushes the first

crossover of the contrast transfer function to higher values

and causes a rapid damping of high frequency oscillations.

Interpretable image resolution can be improved at the

expense of image contrast.

If the STEM detector is increased to just coincide with the

disc of the directly transmitted electrons, i.e. D(K) ¼ A(K),

imaging theory suggests that, with a phase object approx-

imation, the image intensity can be approximated by the

method of Cowley [24]:

IBF Xð Þ ¼ 1� 2 1� cos sf Xð Þð Þ½ � * jt Xð Þj2 ð8Þ

where sf(X) is the projected potential along the beam

direction and s is the interaction constant. In a weak phase

object approximation cos(sf(X)) � 1 � 0.5(sf(X))2, thus:

IBF Xð Þ ¼ 1� sf Xð Þ2 * jt Xð Þj2Þ�

ð9Þ

This is a form of incoherent imaging: the phase contrast is

washed out and the image resolution is determined by the

probe current distribution inside the sample.

For dynamical diffraction in crystalline materials, the

above consideration is not valid and complicated calculations

need to be considered. Note that eq. (9) suggests that with

the increase of the detector size, the STEM image, within the

weak phase object approximation, changes from coherent

imaging to completely incoherent imaging. Furthermore,

the image formed by a large angle BF (LABF) detector, as

represented by eq. (9), is not a linear image anymore with

respect to the specimen potential. The image resolution

achievable in LABF images should be at least double that

of the point-detector BF STEM image or, by the Principle of

Reciprocity, that of the HRTEM image.

In practice, the relative size of the STEM detector can be

continuously varied by changing the strength of the post-

specimen or projector lenses (see Fig. 7). If all the directly

transmitted electrons and a large portion of the scattered

electrons are collected to form the STEM image, then, the

dominant phase contrast, usually visible in BF STEM images,

is significantly suppressed [25,84]. The contrast of LABF

images is predominantly due to absorption effect, weak

diffraction effect, plus an electron channeling effect; it is less

sensitive to the change of beam defocus, sample thickness, or

the Fresnel effects at interfaces or surfaces [25]. For crystals

with principal zone-axes aligned in the incident beam

direction, the diffraction and phase contrast are significantly

reduced in LABF images; but the image resolution is

improved [25].

To understand the contrast characteristics and the

resolution of LABF STEM images, we can rewrite eq. (7) as:

IðXÞ ¼Z

DLABF Kð Þ þ DADF Kð Þ½ �jC K,Xð Þj2 dK

¼ ILABF Xð Þ þ IADF Xð Þ ð10Þ

The diffraction plane is divided into two complementary

parts: a bright field detector and the corresponding ADF

detector (see Fig. 7). If we assume that the specimen is thin

enough so electron backscattering and absorption is negli-

gible, then:

ILABF Xð Þ þ IADF Xð Þ � 1 and ILABF Xð Þ ¼ 1� IADF Xð Þð11Þ

Therefore, the LABF image is complementary to the

corresponding ADF image obtained with an inner collection

Fig. 7 Schematic diagram illustrates the geometric arrangement of

BF, ADF and HAADF detectors. The parameter y represents the

collection (semi-) angle of the BF detector; a1 and a2 are the inner

and outer collection (semi-) angle of the ADF detector, respectively;

b1 and b2 are the inner and outer collection (semi-) angle of

the HAADF detector, respectively. These collection angles can be

changed by varying the strength of the post-specimen projector

lenses.

260 J O U R N A L O F E L E C T R O N M I C R O S C O P Y , Vol. 54, No. 3, 2005

angle as large as that of the LABF detector. LABF images can

be interpreted in the same way as the corresponding ADF

images: improvement in image resolution, increased atomic

number sensitivity and less dependence on sample thick-

ness. For thin specimens, the contrast of the LABF image

could be lower than that of the corresponding ADF image

since most of the directly transmitted electrons do not carry

specimen information. In practice, this large background

signal, however, can be easily subtracted by adjusting the

brightness and contrast controls of the STEM detector.

By collecting electrons scattered outside the central beam

in the diffraction pattern (see Fig. 7), an ADF image of the

sample is formed. In fact, atomic resolution imaging was

first achieved in STEM by using an ADF detector to collect

all the electrons scattered by heavy atoms supported on an

ultra-thin, light-element substrate [95]. ADF images of thin

crystals of Ti2Nb10O29, giving an image resolution much

better than that of the corresponding BF STEM images,

were obtained by Professor Cowley in the early 1980s [11].

For various reasons, this powerful high-resolution imaging

mode, however, was not pursued aggressively by the

research group at Arizona State University until the late

1980s [20,84].

The ADF imaging mode, however, has its drawbacks.

Because of the low collection angle of the ADF detector,

strong dynamical diffraction effects from crystalline materi-

als obscure its compositional sensitivity; this is especially

severe if one wants to detect small metal particles in

supported metal catalysts. The contrast of ADF images of

supported metal catalysts critically depends on the size of the

inner collection angle, a1 (see Fig. 7), of the ADF detector.

For imaging metal particles supported on a thick substrate,

the contrast of the metal particles can change from dark, to

almost none, then to bright with the increase of the inner

collection angle of the ADF detector [20]. This angular-

filtering effect is more useful if an annular ring detector is

used, which will be discussed later.

STEM imaging: HAADF imaging orZ-contrast microscopy

The diffraction effects in ADF images of crystalline materials

can be greatly suppressed by increasing the inner collection

angle of the ADF detector beyond the Bragg reflections so

that only high-angle scattered electrons contribute to the

collected signal (see Fig. 7) [96]. This imaging mode is called

HAADF or Z-contrast microscopy. The inner collection angle,

b1, is the most critical parameter in determining the nature

of the HAADF images; the outer collection angle, b2, is

generally made large enough to collect more high-angle

scattered signals.

In HAADF imaging, the diffraction and phase contrast is

significantly suppressed and the compositional sensitivity is

recovered; but, the signal strength is greatly reduced. The

development of HAADF imaging technique has proved very

successful for characterizing small particles and supported

metal catalysts with sub-nanometer or atomic resolution

and high compositional sensitivity [83–85,90]. Small metal

or alloy nanoparticles in high surface-area supports can be

easily revealed in HAADF images. Figure 8a, for example,

shows a high-resolution HAADF image of a g-alumina

supported PdCu alloy catalyst, clearly revealing the size

and spatial distribution of the PdCu nanoparticles. In this

particular industrial catalyst, the alloy nanoparticles as small

as 0.5 nm in diameter can be revealed in the HAADF images

with high contrast and visibility, thus making it possible to

reliably extract information on the size and spatial distribu-

tion of subnanometer nanoparticles in commercial catalysts.

Both the size and spatial distributions of metal particles in

supported metal catalysts are important parameters that

determine the activity, selectivity and stability of commercial

catalysts. This type of information cannot be obtained from

any other characterization technique.

Figures 8b and 8c show high-resolution HAADF images

of a Au/TiO2 catalyst precursor material, clearly revealing

clusters of Au-containing species anchored onto the titania

surface. Individual Au atoms as well as Au clusters and

nanoparticles are revealed in the same image; the revelation

of the co-existence of both individual Au atoms/ions and

clusters/patches of Au-containing species on the titania

surface is valuable for understanding the interaction

between the Au compounds and the surface sites or defects

present on the TiO2 nanoparticle support. Oxygen vacancies

on the titania surface are believed to be the anchor sites for

the precursor molecules and may act as the nucleation

centers during the catalyst reduction process [97]. This type

of atomic scale insight into the catalyst precursor material

and how it interacts with the support surface is critical to

developing nanostructured industrial catalysts with desired

performances.

The high atomic-number sensitivity of HAADF images can

be utilized to differentiate clusters or nanoparticles in mixed

metal or alloy catalysts. For example, Fig. 9a shows a HAADF

image of a model catalyst consisting of mixed Pt and Pd

nanoparticles, clearly revealing the Pt nanoparticles with a

much higher intensity. The quantitative interpretation of the

image contrast, however, is not straightforward. Figure 9b

shows intensity line scans across a Pd and a Pt particle of

similar size. The ratio of the peak intensity of the Pt particle

to that of the Pd particle is �1.8—far smaller than the ratio

of (ZPt/ZPd)2 � 2.9—if we assume that the same number of

atoms along the beam direction for both the Pt and Pd

nanoparticles is measured. The difference between the

measured and the expected values could originate from

the different shapes of the particles or could be due to inter-

mixing of Pt and Pd in the particles. Even if the nanoparticles

have exactly the same size and shape, the effect of electron

channeling can modify the intensity ratio between the

two particles if they are not oriented along exactly the

same direction with respect to the electron beam. The effect

of electron channeling and poor signal-to-noise ratio

makes it difficult to extract quantitative information on the

J. Liu STEM of nanoparticles and surfaces 261

composition of mixed metal or alloy nanoparticles, especially

in supported metal/alloy catalysts.

Intensity analysis of HAADF images of metal nanoparticles

in supported catalysts has been reported [83]. In practical

industrial catalysts, however, it is difficult to determine the

shapes or shape distributions of the metal nanoparticles

because of the various errors introduced during the analysis

process (e.g. background subtraction, poor signal-to-noise

ratio, etc.) and the effect of electron channeling, especially

for larger particles, on the integrated intensity of individual

nanoparticles cannot be predicted or avoided. It is still an

extremely challenging task to extract statistically meaningful

data on the size distribution of metal or alloy nanoparticles

in industrial heterogeneous catalysts. Quantitative correla-

tion of size distributions of metal nanoparticles in a suppor-

ted metal catalyst to its performance, which is extremely

important for catalyst optimization processes, is difficult,

if not impossible, to obtain. Quantitative and statistically

meaningful information on the shape distribution of metal

nanoparticles in supported metal catalysts, which can be

important in determining the catalyst’s selectivity, has not

yet been reported.

When the nanoparticles become much smaller, for

example, clusters of a few to about a hundred atoms, the

Fig. 8 HAADF image of a Pd-Cu/g-alumina alloy nanocatalyst shows the size and spatial distribution of the Pd–Cu alloy nanoparticles as well

as the pore structure and morphology of the g-alumina support (a). HAADF image of a 5wt%Au/TiO2 catalyst precursor material shows the

presence of Au clusters and nanoparticles (b) as well as individual Au atoms (c) anchored onto the titania surface.

262 J O U R N A L O F E L E C T R O N M I C R O S C O P Y , Vol. 54, No. 3, 2005

effect of electron channeling may not be significant. In this

particular case, the HAADF image intensity may be linearly

dependent on the sample thickness or the total number of

atoms that the electron probe encounters. Thus, it is possible

to determine the 3-D shape of nanoclusters if one can use

the integrated intensity of individual single atoms as an

internal calibration. For example, Fig. 10a shows an atomic

resolution HAADF image of a small Pt cluster. Individual

Pt atoms (indicated by the white arrows) were also revealed

in the image. Figure 10b shows an intensity profile across the

center of the small cluster, revealing that the distance

between the center atomic column and the nearest neigh-

bors is �0.14 nm. Intensity analysis of the individual atomic

columns showed that some atomic columns contain three

Pt atoms along the electron beam direction while others

contain only two Pt atoms. Image instabilities caused by both

external and internal interferences and the sample move-

ment made it difficult to acquire high-quality images with

good signal-to-noise ratio. Environmental control, sample

stability and signal strength are the most challenging issues if

one wants to routinely obtain high-quality, atomic resolu-

tion HAADF images of small clusters or nanoparticles and to

perform quantitative intensity analysis of the individual

clusters or nanoparticles.

The use of Cs-correctors has made it possible to signific-

antly improve the resolution of HAADF images and to

greatly increase the effective probe current [73]. Thus, the

location of single dopant atoms or promoter species can now

be observed with clarity, providing structural information

on the relationship between single dopant atoms and the

substrate [90]. Structural promoters of single atoms and

detailed structures of small nanoparticles and quantum dots

can now be investigated with a sub-angstrom resolution

[82,90]. The wide availability of Cs-corrected STEM or TEM/

STEM instruments will undoubtedly enhance our under-

standing of the structure and physicochemical properties of

small particles and clusters. It is now possible to study the

atomic structure and chemistry of metal or alloy nano-

clusters in a dedicated STEM or field emission TEM/STEM

instrument. The direct imaging of the surface arrangement

of different atoms in bimetallic or multimetallic clusters can

provide extremely valuable information for understanding

the performance, especially the selectivity, of nanocluster

catalysts and for synthesizing nanocatalysts with desired

performances.

The nature of the signals collected by the HAADF detector

has been extensively investigated [18,98–112]. The contrast

Fig. 10 Atomic resolution HAADF image of a small Pt cluster and

individual Pt atoms in a model nanocatalyst (a) and the intensity

line scan across the small cluster (b). Using the intensity of the

individual Pt atoms (indicated by the white arrows) as an internal

calibration, the atomic layers (indicated by the numerals) in the

cluster can be deduced.

Fig. 9 HAADF image of a model catalyst consisting of Pt and Pd

nanoparticles on a carbon support (a) and an intensity linescan

across a Pd and a Pt nanoparticle of similar size (b). Pure Pt

nanoparticles can be easily differentiated from the Pd nanoparticles.

Electron channeling effect complicates quantitative interpretation

of the observed contrast.

J. Liu STEM of nanoparticles and surfaces 263

characteristics of incoherent HAADF imaging include:

(i) high atomic-number sensitivity—approaching Z2, (ii) less

dependence on beam defocus and sample thickness,

(iii) absence of proximity effects at interfaces or surfaces

and (iv) higher image resolution. For thin samples, the

image intensity is linearly proportional to the sample

thickness; the electron channeling effect in crystalline

materials, however, significantly modifies this relationship.

The imaging theory of both HRTEM and BF STEM is a

coherent, linear imaging theory: phase contrast and dynam-

ical diffraction effect dominate the image contrast. For ADF

imaging, however, the detector always detects interferences

among the scattered waves and the directly transmitted

beam may not reach the detector; ADF imaging is thus a

non-linear imaging technique. The degree of coherence in

ADF images varies with the size of the inner collection angle.

For a phase object, the inner collection angle modulates a

coherence envelope given by the Airy function that is the

Fourier transform of the corresponding LABF detector.

Within this spatial envelope, the electrons scattered by

the spatially separated scatterers can interfere with each

other. The extent of the lateral envelope is inversely

proportional to the size of the inner collection angle of the

ADF detector. Therefore, increasing the inner collection

angle decreases the spatial extent of the coherence envelope.

When the coherence envelope becomes much narrower

than the distance between the neighboring scatterers, these

scatterers can be treated as independent scattering centers;

the primary electrons are then scattered incoherently.

The strength of the high-angle scattering, which gives the

HAADF imaging signal, depends on several parameters

including (i) large angle elastically scattered electrons,

(ii) phonon scattered electrons and (iii) multiply scattered

electrons. The imaging theory of HAADF microscopy follows

that of incoherent imaging: the high-angle scattered elec-

trons can be treated as being scattered by independent

scattering centers. The lateral coherence of the scattered

electrons is almost completely suppressed because of detector

geometry (averaging effect) and thermal diffuse (phonon)

scattering. The columnar coherence of the scattered elec-

trons is significantly reduced because of phonon scattering

although a small residue of the coherence still exists along

the incident beam direction [103–113].

For zone-axis crystals, high-energy electrons may prefer-

entially travel along paths of low-energy potentials in the

sample. This phenomenon is called the electron channeling

in crystalline materials [113]. The propagation of a coherent

convergent electron probe inside a perfect crystal in the

zone-axis channeling condition has been widely investigated

[31,99,113,114]. Remarkable electron focusing effects can

occur under channeling conditions. In fact, the focusing

action of the potential field of a single heavy atom or rows

of atoms extending through a thin crystal can be used to

significantly improve the resolution limits of modern elec-

tron microscopes [31]. The imaging properties of atomic

focusers have been investigated and resolutions of better

than 0.05 nm should be achievable in a STEM instrument

with a probe size of �0.4 nm [32,33,35]. By using carbon-

nanoshells as the atomic focusers, ultra-high-resolution

images have been obtained and individual tungsten atoms

with a size of �0.06 nm have been observed in diffraction

images by Professor Cowley [35,36,38,39].

The penetration of the incident electrons is different

for probes focused onto atomic columns of different species.

The channeling effect of a convergent probe is important

in interpreting high-resolution HAADF images of crystals

oriented in principal zone-axes. Phonon scattering, plus

the channeling effect, forms the basis of atomic resolution

HAADF imaging of crystalline materials. Because of the

effect of electron channeling and dechanneling on the high-

angle scattered electrons small perturbations of the potential

field can be manifested in HAADF images. For example, it

is possible to distinguish the location of individual atoms

within, or on the surface of, a substrate. This technique has

been effectively utilized to image the location of individual

Sb dopant atoms within a silicon crystal [115].

In the incoherent imaging limit, the image contrast

becomes a pure ‘number contrast’: the total number of

high-angle scattered electrons determines the image intens-

ity at that pixel. Thus, HAADF images can be viewed as the

convolution of the intensity distribution of the incident

probe with appropriate cross-sections for high-angle scatter-

ing processes. Since high-angle scattering processes are

highly localized, the resolution of HAADF images is neces-

sarily determined by the size of the incident coherent

electron probe. For crystalline materials, the image resolu-

tion may depend on the channeling or atomic focusing

conditions of the specimen.

With coherent, convergent beam illumination, the intens-

ity distribution of the incident probe, I0(X), rather than the

vaguely defined probe size, is usually used to describe the

performance of a STEM instrument. The form of I0(X)

strongly depends on the size of the objective aperture, the

spherical aberration coefficient of the objective lens, the

beam defocus value, the energy of the incident electrons

and the instability of the microscope. The ‘optimum’ probe

sizes in a STEM instrument depend on the selected imaging

and analytical modes. With the use of smaller objective

apertures, which is usually used for nanodiffraction, the

intensity distribution of the electron probe does not vary

appreciably with the change of beam defocus. On the other

hand, with the use of larger objective apertures, such as

those used in high-resolution STEM imaging, the intensity

distribution within the electron probe becomes increasingly

sensitive to the change of beam defocus. For high-resolution

imaging of zone-axis crystals, it is desirable to use an

objective aperture larger than the optimum aperture and

to work at an under-focus value slightly larger than the

Scherzer focus in order to improve image resolution without

introducing complications in interpreting the image [25].

For imaging small particles, however, the high-resolution

imaging condition may not be desirable since the large

264 J O U R N A L O F E L E C T R O N M I C R O S C O P Y , Vol. 54, No. 3, 2005

probe tails complicate the measurement of the particle size.

A top-hat or Gaussian probe may be more appropriate for

determining the size distributions of isolated individual

nanoparticles. To determine the shapes and the surface

atomic arrangements of small nanoparticles supported on

high-surface-area supports is still a difficult task. Significant

improvement in image resolution and probe current by

using aberration correctors have made it possible to study

the exact shapes and surface atomic arrangements of small

particles and quantum dots [82]. Electron beam-induced

modifications of the specimen, however, may become an

important issue for determining the true surface structure of

small clusters and nanoparticles.

The high atomic-number sensitivity, the incoherent

imaging characteristics, the higher image resolution achiev-

able and the intuitive relationship to the specimen make

HAADF imaging the most powerful STEM imaging tech-

nique for characterizing interfaces and defects, nanoparticles

and nanoparticle systems and other nanoscale systems.

STEM imaging: thin annular detectorand other configured detectors

As shown in Fig. 7, the central beam of the diffraction

pattern can be expanded, by the use of post-specimen or

projector lenses, to overlap the inner edge of the ADF

detector. A thin ring at the outer edge of the directly

transmitted beam, plus a small portion of the scattered

beams, can be collected to form an image of the specimen.

A specially designed thin annular detector (TAD) with only

�10% difference between the inner and outer collection

angle can be used to form images that carry unique

information about the specimen [29]. The TAD can be

used to form bright-field (TADBF) or dark-field (TADDF)

images, depending on the size of the inner-collection angle

with respect to the convergence angle of the incidence

probe. By applying the Principal of Reciprocity, this imaging

mode is equivalent to hollow-cone illumination imaging

in TEM. Detailed treatment of the imaging process suggests

that the resolution of TADBF images can be significantly

improved [28,29].

The TAD imaging modes take advantage of selecting the

range of desired frequencies that give higher image resolu-

tion and excluding the lower frequencies that contribute to

the background signal. The TAD may also be used to collect

signals of small angle scattering to produce images of

amorphous materials or light element particles. For example,

carbon nanoparticles supported on amorphous silica can be

detected with good contrast [29]. The image contrast due

to strain fields near defects, interfaces and surfaces can be

enhanced in TAD images. Magnetic domains or domain

boundaries may also be revealed in TAD images with high

spatial resolution. The combination of TAD with HAADF

imaging technique can be very effective in examining

both heavy-element and light-element nanoparticles with

atomic-scale resolution.

Other specially configured detectors can be constructed

to increase image resolution, to enhance image contrast or

to extract unique information about certain features of the

specimen. For example, circular detectors splitting into

halves or quadrants have been used to study magnetic fields

or magnetic domain structures of thin films and small

particles [116,117]. Complex configured detectors have

also been explored for increasing image resolution or for

enhancing image contrast. For example, using the optical-

lens-transfer system shown in Fig. 2, the Cowley group at

Arizona State University explored the possibility of forming

images by excluding all the Bragg diffraction spots from

thin crystals or by using only electrons that are scattered

into certain regions of the diffraction plane. It is, however,

difficult to perform these experiments using physical masks.

The use of high dynamic-range CCD cameras and faster

computers to record the diffraction patterns at each pixel

has made it possible to perform various diffraction-imaging

configurations.

With configured STEM detectors, we can rewrite

eq. (10) as:

Ii Xð Þ ¼Z Kiþ1

Ki

Di Xð ÞjC K,Xð Þj2 dK ð12Þ

Xi

Z Kiþ1

Ki

Di Kð ÞjC K,Xð Þj2 dK � 1 ð13Þ

where the summation is over the whole diffraction plane.

The resolution and contrast of the STEM images is then

dependent on the configuration of the configured STEM

detector. By selecting the frequency or the direction of the

wave vector in the diffraction plane, a plethora of imaging

modes can be used to extract complementary or unique

information about the specimen.

By digitally recording the whole diffraction pattern with

energy (E) discrimination for each pixel (probe position X)

on the sample, a 5-D function I(K, X, E) can be generated.

All information about the specimen can be extracted by

off-line processing of these digitally stored, energy-selected

diffraction patterns. By selecting certain portion(s) of the

scattered electrons as an input signal, various types of

images can be formed to give information about the

structure and the chemistry of the sample with atomic

resolution. This process, however, needs a tremendous

amount of computer work, fast image-acquisition systems,

a large collection of data, and a high stability of the

microscope and the specimen. Alternatively, reconstruction

of the wave function in amplitude and phase can be

accomplished by analyzing 4-D functions in the diffrac-

tion space. Initial attempts, using the technique of ptycho-

graphy [118], on super-resolution STEM imaging has been

successful [119,120]. An image resolution better than

0.14 nm has been achieved on an STEM with a nominal

resolution of only 0.42 nm [120].

With the rapid advancement in the image acquisition

systems, faster desk-top computers, specially designed

J. Liu STEM of nanoparticles and surfaces 265

microscope environments and the use of pulsed electron

beams, we should be able to efficiently use the various

signals available in a STEM instrument with minimum

exposure of delicate specimens to the electron beam. STEM

techniques will become more critical to the fundamental

studies of nanoscale systems and will contribute significantly

to the new era of nanotechnology and nanoscience research.

STEM imaging: secondary and Augerelectron microscopy and scanningreflection electron microscopy ofsurfaces

In a STEM instrument, the specimen is usually placed inside

the pole pieces of a highly excited objective lens. The emitted

secondary electrons first experience a strong magnetic field

before being collected by an SE detector. Owing to the effect

of this magnetic field, an emitted SE spirals in a cyclotron

orbit with a radius R that depends on the energy and the

emission angle of the SE as well as the strength of the mag-

netic field. After spiraling out of the bores of the objective

lens, secondary electrons are collected by an SE detector

through a transverse electric field. Because of the effect of

the magnetic field on the trajectory of the emitted secondary

electrons, the SE collection efficiency in a STEM instru-

ment is high. The collection efficiency of low-energy

electrons can be further enhanced by the use of electron

‘parallelizers’ located inside the bores of the objective lens

[121,122]. The energy distribution of the collected secondary

electrons can be analyzed by an electron spectrometer.

Secondary electron spectroscopy can be used to investi-

gate the energy distribution of secondary electrons from

different materials, to measure the work function of solid

specimens, and to study the charging effects of non-

conducting materials.

Sub-nanometer surface details can be observed in

high-resolution SE images [16,17]. This implies that the

generation processes of secondary electrons are localized

to within 1 nm or less. It was first pointed out [17] and

later experimentally proved [123] that the generation of

secondary electrons is directly related to large-angle inelastic

scattering of the high-energy incident electrons. There exist

large momentum transfer mechanisms during the inelastic

scattering processes such as Umklapp (high-momentum,

low-energy transfer processes) or phonon-assisted electron

excitation processes. Inelastic scattering events involving

these processes are highly localized. The resolution obtain-

able in SE images is currently limited to �0.5 nm.

Small particles are often observed with a bright contrast

in high-resolution SE images; Fig. 11 shows a set of high-

resolution SE images of metal particles supported on various

oxides, revealing the high-spatial resolution and good image

contrast of small nanoparticles. The particle contrast in SE

images can be parameterized by the ratio of the particle

radius (R) to the average escape-depth (L) of the collected

secondary electrons. If R/L < 1, the brightness of a particle

increases with the size of the particle and the image intensity

has a maximum at the center of the particle. If R/L > 1, the

particle intensity slowly increases with the size of the particle

and the highest image intensity is approximately at a

distance d ¼ (R � L) from the center of the particle. For

very large particles, the particle contrast evolves into the

edge-brightness contrast commonly observed in SE images.

Although the resolution of SE images is comparable to the

size of the incident probe, it is impossible to extract

information about the shape of nanoparticles with sizes

less than the escape depth of the collected secondary

electrons. Therefore, we cannot extract information about

detailed surface morphology of very small particles. We can

obtain, however, useful information about the relative

locations of nanoparticles with respect to the surface

topography of the supports. Detailed discussions on the

origin of small particle contrast and the resolution achievable

in SE images have been reported previously [124].

The production of Auger electrons is essentially similar to

that of low-energy secondary electrons; the initial excitation

produced by the inelastic scattering of the incident electrons

decays to generate a low-energy electron that can escape

into the vacuum. In contrast to the diffusion of secondary

electrons, Auger electrons must escape from the specimen

surface without losing any energy in order to be registered as

Auger peak signals. The reason that Auger electron spectro-

scopy is a surface-sensitive technique lies in the intense

inelastic scattering that occurs for electrons in this energy

range; only Auger electrons generated from the outmost

atomic layers of a solid can survive to be ejected and

registered as Auger electrons. Most of the emitted Auger

electrons are produced within a very short distance from

the sample surface, typically 0.3–3 nm.

In a STEM instrument, Auger electrons, emitted from

either the entrance or the exit surface of a specimen, can

be collected and analyzed by a cylindrical mirror analyzer

(CMA) or a concentric hemispherical analyzer (CHA)

electron spectrometer. Because of the high energy and

high brightness of the incident electrons, the employment

of magnetic ‘parallizers’, and the use of thin specimens in a

STEM instrument, high-quality Auger electron spectra can

be acquired with extremely high peak-to-background

ratios [125–127]. Figure 12a shows a high-energy resolution

Auger electron spectroscopy (AES) spectrum of clean silver

nanoparticles supported on a small MgO crystal; the silver

MNN doublet is clearly resolved. Figure 12b shows the

corresponding oxygen KLL Auger peak from the same

specimen area. Surface compositional analysis of individual

nanoparticles is essential for understanding the activity and

selectivity of industrial bimetallic or multi-component cata-

lysts used in a variety of chemical processes. The overall

composition of these individual nanoparticles can usually be

obtained by XEDS. It is, however, extremely difficult to

extract information about preferential surface segregation

or aggregation of individual components in nanoparticles

of different sizes. Because of the high-surface sensitivity of

266 J O U R N A L O F E L E C T R O N M I C R O S C O P Y , Vol. 54, No. 3, 2005

Auger electrons, it is possible to determine qualitatively

and, in some cases, quantitatively, the surface composition

of nanoparticles consisting of multiple components. High-

spatial resolutionAuger electron spectra can provide informa-

tion about the surface enrichment of specific elements and

information about how this enrichment varies with the size

of the nanoparticles.

For electron transparent specimens, typically used in

STEM instruments, an image resolution <1 nm can be

achieved [125–127] in scanning Auger microscopy (SAM)

images. Silver nanoparticles <1 nm in diameter and contain-

ing as few as 15 silver atoms have been detected [125].

Figures 12c and 12d show, respectively, Ag and O maps of an

Ag/MgO model catalyst, clearly revealing the high-spatial

resolution of Auger elemental maps, obtainable in dedica-

ted STEM instruments. The resolution in SAM images

depends on several sample- and instrument-related effects.

The sample-related effects include: (i) surface topography,

(ii) escape depth of the collected Auger electrons, (iii)

contribution from backscattered electrons and (iv) localiza-

tion of the Auger electron generation processes. The last

factor sets the ultimate resolution limit that will be achiev-

able in SAM images. Since the primary inelastic scattering

processes involve excitation of inner-shell electrons, the

generation of Auger electrons is highly localized. With thin

specimens and high-energy incident electrons, the contri-

bution from backscattered electrons should be negligible; it

may, however, degrade the image resolution and affect the

image contrast of bulk samples. The instrument-related

effects include: (i) the intensity distribution of high-energy

electron probes, (ii) the collection efficiency of the emitted

Auger electrons and (iii) the instability of the STEM

microscopes. At present, the instrument-related factors set

the limits of obtainable resolution to �1 nm in Auger peak

Fig. 11 High-resolution secondary electron images of Ag (a) and Fe (b) nanoparticles on MgO smoke crystals and Ag nanoparticles on

a-alumina powders (c) and Pd nanoparticles on g-alumina crystals (d). Small metal clusters and nanoparticles on oxide supports are clearly

revealed with high resolution and bright contrast.

J. Liu STEM of nanoparticles and surfaces 267

images of thin specimens. The minimum detectable mass in

high-spatial resolution SAM images is <3� 10�21 g [125].

Scanning reflection electron microscopy (SREM) is

another technique that can be used to examine surface

details of bulk crystals. In SREM, the electron nanoprobe is

scanned over the surface with a grazing angle and a selected

part of the resulting diffraction pattern [a convergent-beam

high-energy electron diffraction (CBRHEED) pattern] is used

to form an image of the specimen surface [23]. Surface steps,

dislocations and other types of defects on the surfaces of bulk

crystals can be imaged with high contrast and resolution.

CBRHEED, scanning reflection EELS and XEDS techniques

can be used to provide information on the surface structure,

composition and even electronic states of bulk crystals [23].

If a HAADF detector is used, then the resulting high-

resolution surface image depends strongly on the atomic

number of the elements present on the specimen surface

and the phase contrast and dynamical diffraction effects are

greatly suppressed [23]. Similar to transmission HAADF

imaging, high-resolution detail of atom rows along which

the electrons can be channeled and atomic scale information

on the surface defects should be obtainable.

STEM diffraction: CEND

The advantage of STEM is that the electron beam can be

stopped at any point of interest on a sample and diffraction

or spectroscopy can be performed at that point with an

atomic or nanometer scale resolution. As discussed earlier,

CBED patterns can be formed in the observation screen

and the size of the diffraction discs is determined by the

convergence angle of the incident probe (see Fig. 6). These

CBED patterns are, however, different from those obtained

in a TEM. First, the sizes of the electron probes are usually

�1 nm in diameter, much smaller than those obtainable

in TEM; thus, the diffraction patterns obtained in STEM are

Fig. 12 Auger electron spectra of (a) Ag MNN and (b) O KLL peaks of an Ag/MgO model catalyst. Auger maps of silver and oxygen are shown

in (c) and (d), respectively. Auger electron spectra and scanning Auger microscopy images were obtained from the UHV STEM-MIDAS

(Microscope for Imaging, Diffraction, and Analysis of Surfaces) housed at Arizona State University.

268 J O U R N A L O F E L E C T R O N M I C R O S C O P Y , Vol. 54, No. 3, 2005

usually called micro- or nano-diffraction patterns. Second,

the use of a field emission gun warrants the coherent nature

of a convergent nanoprobe: the illuminating aperture is

filled with completely coherent radiation and the final probe

entering the specimen can be treated as perfectly coherent.

In contrast, the illuminating aperture in conventional TEM

is considered incoherently filled and the illumination is

treated as completely incoherent.

CEND is the only technique that gives full diffraction

information about individual nanoparticles. Diffraction

patterns from the various parts of a nanoparticle can be

obtained to provide information about the structure as well

as the morphology of the nanoparticle.

For a perfect, thin crystal (no thickness variation, no

defects, no bending), there are no differences in the

diffraction patterns that are obtained with either a coherent

or an incoherent electron beam provided the diffraction discs

do not overlap (a < yB in Fig. 6a). This is a consequence of

the Bragg law: for each incident direction, only scattering

through mutiples of the Bragg angle is allowed; thus,

electrons with different incident beam directions cannot

interfere with each other although the incident electron

probe is completely coherent. If the crystal is thicker, the

intensity distribution within the diffraction discs may become

non-uniform, with sets of lines, bands or complicated

shapes. This is mostly due to dynamical diffraction effects

giving a variation of the incident and diffracted beam

intensities as a function of the incidence angle. If we ignore

the fine-details, CEND patterns of perfect crystals can be

treated the same way as those generated by an incoherent

electron beam with a nanometer-size probe.

For crystals containing defects (edges and bending,

stacking faults and dislocations, thickness variations, etc.)

elastic scattering from these defects can coherently interfere

with each other or with the Bragg-diffracted electrons.

Diffraction patterns, characteristic of the unique nature of

the defects, can be observed. For thicker or strongly scatter-

ing samples, any discontinuity in the sample can have some

observable effect on the CEND patterns. For example, when

a small electron beam scans across a straight edge of a MgO

cube aligned along the [001] zone-axis, first the central

transmitted disc shows strong streaking towards the crystal;

then diffraction spots appear at non-Bragg positions (Fig. 13).

Fine structures in these CEND patterns change rapidly with

the movement of the probe position. The streaking of the

central transmitted spot is attributable to the influence of the

crystal inner potential. The interference among waves

arriving from different incident beam directions gives rise

to perturbations of the Bragg diffraction spots. When only

part of the incident probe is positioned inside the MgO

crystal, electrons with different incident directions interact

with different parts of the crystal. The scattered electrons

interfere with each other to give a diffraction pattern

characteristic of the beam position and that part of the

specimen. Simulations using dynamical electron diffraction

theory show that the intensity distributions in CEND

patterns are sensitive to the surface or the defect structures

of the specimen [128]. A surface channeling effect may

also be responsible for the fine features observed in

CEND patterns from straight edges of small crystals; in this

case, the diffraction pattern can be treated as the combina-

tion of transmission and reflection high-energy electron

diffraction.

When the incident probe is positioned near the edge of

a crystal, CEND discs may show annular rings or splitting of

diffracted spots [47], which are clearly shown in Fig. 13.

Internal discontinuities, such as fault planes, out-of-phase

boundaries and thin layer precipitates, may give character-

istic structures in their corresponding CEND patterns. For

example, CEND patterns from antiphase domain bound-

aries in ordered alloys show spot splitting of superlattice

reflections [49]. It is, however, impossible to make accurate

measurements of lattice parameters in CEND patterns

because of the large sizes of the diffraction spots. An error

of 5% or higher than that is common in determining lattice

constants of small particles by the CEND technique, and

much larger errors can frequently occur because of coherent

interference effects.

It is important to correlate the characteristic features of

CEND patterns to particle properties, such as the structure

of the particle, the nature of defects within the particle, or

the shape and size of the particle. A frequently observed

characteristic feature is the splitting of diffraction spots

along certain crystallographic directions of a small

particle. Figure 14 shows a set of CEND patterns that were

obtained from different positions on a small Au cubocta-

hedral particle, demonstrating the various features of

CEND patterns from nanoparticles. The spot splitting

Fig. 13 CEND patterns from a MgO cube oriented along the [001] zone axis. From left to right: the electron beam was moved toward the

MgO crystal. The spot streaking and splitting are unique characteristics of coherent electron nanodiffraction resulting from the discontinuities

at the specimen surface.

J. Liu STEM of nanoparticles and surfaces 269

in non-overlapping CEND patterns is attributable to the

coherent nature of electrons diffracting from an abrupt

discontinuity of the scattering potential at particle edges. It is

also observed that the spot splitting is related to the

geometric forms of the diffracting particles; some splitting

occurs in a well-defined crystallographic direction. Depend-

ing on the probe position relative to the center of the

particle, annular rings may be observed (see diffraction

pattern 3 in Fig. 14). CEND patterns are sensitive to edges,

thickness variations and facets; the 3-D information of

nanoparticles is reflected in their CEND patterns. Analysis

of CEND patterns at each pixel element of a nanoparticle

should provide detailed information about the 3-D structure

of small clusters and nanoparticles.

Dynamical simulations reveal that for a particle that has

facets smaller than the size of the incident probe, the

incident electrons may interact with several facets of the

small particle [128]. The thickness of the particle may vary

rapidly even within a region of only �1 nm in diameter.

The electron probe effectively interacts with the ‘particle

morphology’ under illumination. The intensity variations of

the splitting spots are related to the probe positions with

respect to the particle facets and are related to the length of

the facets along the incident beam direction. The direction of

spot streaking or splitting is directly related to specific edges

or facets of a small particle (Fig. 14). Furthermore, the

intensity profiles across the splitting spots vary with the

types of particle wedges. In principle, it is possible to deduce

the 3-D structure of nanoparticles by quantitatively analyz-

ing the intensity distributions of their CEND patterns. Before

this technique can be effectively and reliably utilized to

extract the rich information coded in CEND patterns of

small particles, many experimental difficulties, such as

particle stability, contamination and accurate control of

beam defocus, have to be overcome.

When metal atoms aggregate from the vapor phase or in a

liquid, they usually form a crystal, having shapes of regular

pentagonal bi-prisms or icosahedra. Their internal structure

Fig. 14 CEND patterns obtained at different positions of a small Au cuboctahedral nanoparticle. These nanodiffraction patterns contain

information on the 3-D shape of the Au nanoparticle (see text for detailed discussions).

270 J O U R N A L O F E L E C T R O N M I C R O S C O P Y , Vol. 54, No. 3, 2005

is a complex arrangement of 5 or 20 twinned components.

Large metal particles of cuboctahedron, decahedron,

icosahedron and other multiple-twinned structures can be

examined in HRTEM images [129,130]. For particles

with sizes <2 nm in diameter, however, it is difficult to

unambiguously determine their shape by imaging tech-

niques. CEND technique can provide information about the

shape of clean, metallic nanoparticles. For example, a large

portion of clean silver nanoparticles with sizes <3 nm

in diameter was observed to give unique CEND patterns

exhibiting 5-fold-symmetry. Figure 15a shows such a CEND

pattern and Fig. 15c shows a simulated CEND pattern of a

small icosahedron with the incident beam direction along

the 5-fold symmetry axis. The simulated pattern closely

matches the experimental one. Figures 15b and 15d show,

respectively, experimental and simulated CEND patterns of a

small icosahedral Ag nanoparticle oriented along its 3-fold

axis. Although the general features are similar between

the experimental and the simulated CEND patterns, quant-

itative comparison has not yet been performed. These small

particles are not stable under intense electron beam irradi-

ation and their structure fluctuates rapidly during observa-

tion. Detailed quantitative analyses of digitally recorded

CEND patterns will provide information on the shape of,

as well as the defective structure in, small nanoparticles.

Simulations of CEND patterns of various shapes of nano-

particles should provide insight into the nature of CEND

from nanoparticles or other nanosystems.

CEND technique has been applied to the study of defects

[49,50], supported catalysts [55,56,89], structure of carbon

nanotubes [59,60], and biological systems [63–65]. The

recent application of using coherent beams of small diameter

for deriving the structure of double-walled carbon nano-

tubes with high resolution and contrast clearly demon-

strated the potential of employing coherent nanoprobes to

extract structural information of periodic or non-periodic

objects [131].

STEM nanospectroscopy:XEDS and EELS

XEDS is now routinely used, in TEM, SEM or STEM

instruments, to identify unknown phases or to obtain

information on the spatial distribution of certain phases of

interest. In a modern FEG TEM/STEM instrument, XEDS

can be conveniently used to analyze the features revealed

Fig. 15 CEND patterns obtained from small Ag icosahedral nanoparticles along the 5-fold symmetry axis (a) and the 3-fold symmetry axis (b);

the corresponding simulated patterns are shown in (c) and (d), respectively.

J. Liu STEM of nanoparticles and surfaces 271

in HAADF images by stopping the incident probe at any

point of interest. With the recent development of image

and spectrum acquisition systems, both qualitative and

quantitative information on the composition of individual

nanocomponents can be obtained. The availability of faster

computers for automation and online data analysis make it

possible to analyze extremely complex nanoscale systems

and to quickly diagnose their basic composition.

One of the most useful techniques for understanding

the behavior of bimetallic nanoparticles and for guiding

the development of industrial bimetallic catalysts is the

composition-size plot method developed by the Lyman’s

group [132,133]. The composition-size plots can provide the

compositional profiles of the individual bimetallic nano-

particles or clusters; they reveal whether the compositions of

individual nanoparticles vary with their sizes or with their

relative locations with respect to the catalyst support. When

ultramicrotomed samples are used, this method can quant-

itatively map out how the compositional profiles vary within

the supports, the treatment conditions, or the preparation

procedures. The composition-size plot method can also be

applied to studying the compositional evolution of indi-

vidual bimetallic nanoparticles during the catalytic reactions.

Figure 16 shows examples of how the composition-size

plots are used to provide information on the nature of

bimetallic catalysts and how the information can be used to

develop new synthesis strategies in order to obtain particular

structures that give desired performances. Figure 16a is a

composition-size plot obtained from a 2wt%Pd1wt%Cu/

g-Al2O3 bimetallic catalyst. Each data point represents the

composition of that individual bimetallic nanoparticle. The

nanoparticles selected for analysis are located at different

regions of the catalyst powders. The plot shows that the

composition of the individual Pd–Cu nanoparticles does not

vary much with the size of the particles; but they do change

significantly with the location of the individual particles.

Further analysis of the corresponding HAADF images

show that the compositional variations of the individual

Pd–Cu nanoparticles revealed in Fig. 16a are related to the

macro- and nano-structure of the g-Al2O3 aggregates/

powders. Therefore, the metal precursor deposition pro-

cesses have to be modified in order to obtain bimetallic

nanoparticles with a uniform composition throughout the

catalyst powders.

Figure 16b shows another example of studying bimetallic

catalysts. The composition-size plot clearly shows that

the composition of the individual Pd–Ni particles in a

5wt%Pd1wt%Ni/TiO2 bimetallic catalyst changes signific-

antly with the sizes of the individual nanoparticles and also

varies with their relative locations with respect to the

substrate structure: smaller particles contain more Pd and

larger particles contain more Ni. This observation can be

explained if Pd preferentially segregates to the particle

surface or if Pd-rich particles do not sinter as much during

the catalyst preparation processes. By changing the synthesis

procedures, the composition-size profile can be modified.

Comparison of composition-size plots to the catalyst’s

performance can provide important information on the

synthesis–structure–performance relationships.

In practical applications to developing industrial catalysts,

hundreds of data points in each composition-size plot are

usually needed to provide statistically meaningful data of the

catalyst of interest. In developing industrial catalysts, in

order to optimize the synthesis protocols to make a potential

commercial catalyst tens or even hundreds of catalysts will

have to be tested and analyzed; this is time consuming and

extremely expensive. Automated analyses and faster data

acquisition systems are highly desired for wide applications

of the composition-size plot method for solving challenging

nanoscale materials problems.

A consequence of using small electron probes to achieve

high-spatial resolution is that the X-ray signal originates

from a much smaller volume; thus, a weaker signal is

collected and longer acquisition times are usually needed

to obtain statistically meaningful data points. Specimen-drift

correction, either manually or automatically, is usually

required for obtaining statistically meaningful X-ray signals

when very small particles are analyzed. Nevertheless, XEDS

Fig. 16 Composition-size plots of (a) 2wt%Pd1wt%Cu/g-Al2O3 and

(b) 5wt%Pd1wt%Ni/TiO2 bimetallic catalysts. These composition-

size plots of bimetallic nanoparticles provide critical information

on the synthesis–structure–performance relationships of nanostruc-

tured bimetallic or multiphase heterogeneous catalysts.

272 J O U R N A L O F E L E C T R O N M I C R O S C O P Y , Vol. 54, No. 3, 2005

can detect the presence of just a few atoms if the analyzed

volume is small enough. With the recent development of

Cs-correctors for dedicated STEM instruments, the total probe

current can be significantly increased, thereby providing

higher counts of the collected X-ray signals. Future devel-

opment that focuses on significantly improving the X-ray

collection efficiency and reduction of beam-induced modi-

fications (e.g. by using pulsed electron beam) can have a

profound impact on the fundamental understanding of

bimetallic nanoparticles or quantum dots.

Elemental maps can provide valuable information on

the 2-D elemental distributions; they are especially useful

for characterizing multiphase materials. Electron–specimen

interaction processes and the effective generation volume

of the X-rays determine the ultimate resolution of X-ray

mapping of nanophase materials. In practice, however,

the extremely low counts of the collected X-ray signal

from small nanoparticles and specimen drifting limit the

achievable resolution in X-ray elemental maps. A statistically

meaningful elemental map requires longer acquisition time

that in turn requires the use of automatic drift correction

or ultra-stable microscopes and samples. Higher-resolution

maps, however, are needed to determine the degree of

surface segregations, which may be accomplished by using

Cs-correctors to reduce the probe size but still having enough

beam current. Automatic specimen-drift correction may also

have to be used to reduce specimen-drifting effect. The

conditions for optimum X-ray mapping include: (i) high

beam current within a small probe size, (ii) high X-ray

collection efficiency and (iii) long acquisition times per pixel

if automatic specimen-drift correction techniques are used.

Figure 17 shows XEDS spectra and the elemental maps of

a 5wt%Pd1wt%Ni/TiO2 catalyst, clearly revealing that the

individual nanoparticles dispersed onto the TiO2 powders

contain both Pd and Ni. The elemental distribution within

each individual Pd–Ni bimetallic nanoparticles, especially

Fig. 17 XEDS spectra from a Pd–Ni alloy nanoparticle (darker line) and from the TiO2 support (lighter line) of a 5wt%Pd3wt%Ni/TiO2

bimetallic catalyst. Elemental maps of Ni, Pd and Ti show the distribution of Pd and Ni across the TiO2 support.

J. Liu STEM of nanoparticles and surfaces 273

within the small nanoparticles, however, is not revealed in

these elemental maps. Information on the surface segrega-

tion of individual Pd–Ni bimetallic nanoparticles, which

is most important for understanding the performance of

bimetallic nanocatalysts, cannot be extracted from Fig. 17.

Electron energy-loss signals carry detailed information

on the composition, chemistry and electronic structure of

nanoparticles with atomic resolution and sensitivity. The

combination of atomic resolution HAADF imaging with

EELS has already proved extremely valuable for extracting

atomic-scale information on the composition and electronic

structure of various materials systems [74,75,78–80,86–89,

134,135]. The combination of EELS with HAADF in a STEM

instrument significantly extends the usefulness of STEM in

solving challenging nanoscale or atomic scale materials

problems.

It is important to understand the effect of the electronic

structure of the interfacial regions between the metal nano-

particles and the support on the catalytic performances of

supported catalysts. Since catalytic reactions usually involve

bonding and electron transfer processes, the electronic

properties of the metal–support interfacial regions can play

a critical role in determining surface adsorption and electron

transfer processes. Furthermore, the interfacial regions may

also act as active sites during the catalytic reactions since

these regions may have a structure that represents neither

the metal nanoparticles nor the support. Knowledge of the

atomic and electronic structure of the interfaces can help

us better understand the performance of heterogeneous

catalysts.

Recently, atomic resolution EELS and HAADF techniques

have been applied to the study of nanophase Sn(Sb)O2

catalysts [86], reduction behavior of metal nanoparticles

in alumina-supported Pd catalysts [87] and the alloying

behavior of supported Pd–Cu bimetallic catalysts [88]. These

preliminary investigations already showed that atomic

resolution EELS, together with HAADF imaging technique,

can provide valuable information on the fundamental

understanding of the electronic structure as well as surface

composition of the individual nanoparticles and their inter-

actions with the support.

Figure 18a shows a HAADF image and Fig. 18b shows the

corresponding EELS spectra that were obtained from the

different regions labeled in 18a, respectively. The sample is a

Pd–Ni/TiO2 bimetallic catalyst. The EELS spectra suggest that

the bimetallic particle can be described by the ‘grape’ model:

a thin skin of pure Pd layer encapsulates a Pd–Ni alloy core.

This type of structure may have profound effect on the

adsorption and catalytic properties of bimetallic catalysts.

The knowledge of preferential surface segregation of indi-

vidual bimetallic nanoparticles is critical to designing sup-

ported bimetallic catalysts and to an understanding of their

performance. Knowing how the preferential surface segrega-

tion of individual bimetallic nanoparticles depends on the

particle size, composition and the catalyst preparation

methods, one can make significant progress in tuning the

properties of supported bimetallic catalysts to achieve high

selectivity and activity. The concept of binding-energy

engineering in developing heterogeneous catalysts refers

to tuning the molecular adsorption and dissociation behav-

ior of nanoparticles by controlling their sizes, atomic

structure, shape, surface and bulk composition, and interface

structures.

Figure 18 also shows that strong metal support inter-

actions occurred during the catalyst preparation processes;

TiOx species had migrated to the surfaces of the Pd–Ni alloy

nanoparticle. Detailed analyses of the EELS spectra revealed

that the TiOx species covered the whole surface of this

particular Pd–Ni alloy particle. The coverage of TiOx species

on metal or alloy nanoparticles depend on the precursor

species, catalyst treatment, properties of the particle surface,

and the interfacial properties between the metal/alloy

Fig. 18 HAADF image of a 5wt%Pd1wt%Ni/TiO2 bimetallic catalyst

shows a Pd–Ni alloy nanoparticle in contact with the TiO2 support

(a). (b) EELS spectra, obtained from the corresponding points of

the Pd–Ni alloy nanoparticle shown in (a), show that the Pd is

preferentially segregated to the surface of the alloy nanoparticle.

The spectra also reveal the presence of TiOx species across the surface

of the Pd–Ni alloy nanoparticle.

274 J O U R N A L O F E L E C T R O N M I C R O S C O P Y , Vol. 54, No. 3, 2005

particles and the support. The metal–support interaction

profoundly affects the adsorption behavior of the metal or

alloy nanoparticles.

EELS technique can be used to analyze individual atomic

columns or single atoms located either inside or on the

surface of a substrate [74]. With the use of Cs-correctors

to form sub-angstrom probes, it is expected that atomic

resolution EELS can be performed on a wide variety of

materials to provide chemical and electronic structure of the

elements of interest. Further incorporation of monochro-

mators in the field emission TEM/STEM instruments [77]

will significantly enhance the power of atomic resolution

EELS in studying nanoparticles and nanoparticle systems;

and information on the fine electronic structure of nano-

particles and nanoclusters may provide a better under-

standing of the selectivity of heterogeneous catalysts.

Concluding remarks

In this paper, we discussed the recent development of

STEM techniques and illustrated their applications by using

nanoparticles and nanostructured catalysts as examples.

The various imaging, spectroscopy and diffraction tech-

niques can now be realized in both the dedicated STEM

and the modern FEG TEM/STEM instruments and can be

successfully applied to the study of nanoparticles or other

nanoscale systems. The combination of the various STEM

techniques significantly expands the usefulness of electron

microscopy in solving critical problems in nanoscience and

nanotechnology.

The use of Cs-correctors and monochromators in the

next-generation electron microscopes will undoubtedly

make STEM techniques indispensable for understanding

the fundamental properties of materials at a nanometer or

subnanometer scale. The realization of sub-angstrom elec-

tron probes in STEM instruments makes it possible for us to

explore the nature of nanoparticles and other nanoscale

systems with unprecedented imaging and spectroscopy

tools. Advanced STEM techniques will undoubtedly make

significant contribution to the recent explosive research

activities in nanoscience and nanotechnology. The intrinsic

nature of high-spatial resolution techniques, however, poses

the most significant challenge for the electron microscopy

community: how to obtain statistically meaningful data

with high-throughput and automation. With the rapid

development of novel microscope designs, super fast com-

puters, significantly improved signal acquisition systems and

innovative image analysis algorithms, it is expected that

statistically meaningful data should be routinely obtainable

with user-friendly, high-throughput and automated high-

resolution electron microscopes.

AcknowledgementsThe author is deeply indebted to Professor John M. Cowley for his

continuous mentoring and coaching for over 20 years, especially for his

tireless training of the author in mastering the various STEM techniques

and for his encouragement in applying these powerful STEM techniques

to solving challenging industrial problems.

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