Solid-state chemical sensors: Atomistic models and research trends

167

Sensors crndActuators, 16 (1989)

167 - 193

SOLID-STATE CHEMICAL RESEARCH TRENDS*

SENSORS:

WOLFGANG

ATOMISTIC

MODELS AND

GijPEL

Institute of Physical and Theoretical D-7400 Tiibingen (F.R.G.) (Received December 31,1987;

Chemistry,

University of

Tiibingen,

accepted June 10,1988)

Abstract a brief survey about thermodynamically and kinetically controlled sensing mechanisms, atomistic models and research trends of solid-state chemical sensors are discussed. Future work will involve new techniques of interface analysis, controlled two-dimensional physical chemistry at interfaces, new materials, new technologies, new microstructured devices and pattern recognition approaches. After

presenting

1. Introduction Solid-state chemical sensors are used to monitor concentrations of particles, such as gas molecules or ions in solution. Figure 1 shows a typical example for a characteristic ‘key-lock’ situation, which may be used to detect molecules selectivelyin a mixture of many others by choosing a sensor surface that adsorbs specifically only one type of molecules [l]. Instead of the conductivity changes monitored here, changes of other sensor properties may also be used to detect particles by making use of their specific surface or bulk reactions. Typical sensing mechanisms will be discussed in Section 2. Typical results obtained on ‘prototype sensors’ will be presented in Section 3. Details about experimental aspects to chamcWixe sensing mechanisms on an atomistic scale by means of modern tools of interface analysis applied to new sensor materials will be presented in Section 4. Future trends will also be discussed in this Section. A brief outlook is given in Section 5.

*Invited paper presented at EUROSENSOR ‘87, First European Conference on Sensors and their Applications, Cambridge, U.K., September 22 - 24,1987. 0260-6874/89/$3.60

0 Elsevier Sequoia/Printed in The Netherlands

168 Free parliclr

Adsortmd iom

Fig. 1. Schematic presentation of Aid-gas interactions leading to changes in the sensor property ‘G’ (compare Table I). This particular example showa donor (‘electron in’) or acceptor {‘electron out’) type of charge transfer between the adrorption complex and the bulk of a semiconductor. Heire, electron transfer between the acborption complex and the conduction band of the semiconductor may be monitored by conductivity changes of the solid. Circles indicate surface atom ckters of different sizes, which may be considered to represent the adsorption complex and which may be calculated theoretically (compare Figs. 4 and 6). For details, see [l 1.

2.1. Survey Characteristic sensor properties ‘G’ monitored by different types of solid-etate chemical sensors are list&d in Table 1. For details of the sensor designs, the reader is referred to an extensive literature (see, e.g. [2 - 111 and references therein). In the design of solid-state chemical sensors, we would like this sensor property ‘G’ to be a partition function, with its value only depending on partial pressures J+ (or concentrations) and temperatures 2’ independent of the history of the sensor.We also try to optimize sensitivitiesand selectivities with respect to one component (i) of the molecules. This corresponds to a predominant influence of one derivative (dG/dpf) in Table 2. This Table also indicates schematicallyour basic understanding about driving forces (thermodynamics) and rates (kinetics) of sensor-gas interactions with the free enthalpy or Gibb’s energy G as the driving force. Changes AG during (w5118or action are given by the compromise bekpesn changes in the enthalpy U (or inner energy AU and mechanical work ApV) and changes in the enthalpy AS. We expect adsorption effects to be favoured at low temperatures and to be negligible at high temperatures. Intrinsic point defects such as vacancies or interstitial atoms of the sensor itself show the opposite temperature dependence. Since many chemical sensors operate in a medium temperature range, we generally have to consider that both influences compete.

169 TABLE

1

Characteristic sensor properties ‘G’ as monitored by different types of chemical sensors Liquid state electrolyte sensors: Voltages V, currents I, conductivities 0. Solid-state electrolyte sensors: Voltages V, currents I. Electronic conductivity sensors: Conductivities 0. Field-effect sensor: Potentials 4. Dielectric

sensor:

Capacities C. Calorimetric sensors: Heat of adsorption or reaction qgd or B& Optochemical and photometric sensor: Optical constants E as a function of frequency v. Mass-sensitive sensor: Mass M of adsorbed particles.

There is a link between spectroscopically or theoretically available information about the quantum structures (characterized by specific energies ES) of chemical sensors before and after their interaction with molecules and the corresponding phenomenological sensor properties. The latter are monitored in practical sensor devices under thermodynamically and/or kinetically controlled conditions. This link is given by the partition function Q and statistical thermodynamics. This concept leads, e.g., to adsorption isotherms, i.e., surface coverages 8 = f(P)== conotfor one component in the gas phase. The concept may be extended to describe coadsorption phenomena by surface excess quantities and to describe the kinetics of solid/gasinteractions in the framework of Eyring’s theory [ 11. 2.2. Phenomenology Particles may physisorb at lower temperatures and, after overcoming a characteristic activation energy, chemisorb. A specific example of an acceptor-type interaction with an n-type semiconductor is shown in Fig. 2. Chemisorption leads to a decreased surface (index s) conductivity Aulr~Chem, an increased band bending eAVs, and generally also to a change in the electron affinity Ax. At elevated temperatures these chemisorbed molecules may interact with point defects in the bulk. Bulk defects are characterized by donor levels En and acceptor levels EA, respectively. Coulomb attractive forces, for instance, between negatively-charged molecules with an acceptor level Em at the surface and positively-charged donor states in the bulk may lead to diffusion (‘electron&ration’) and annealing of bulk defects. As a result, drifts are observed in the conductivity of oxide semiconductors, e.g.,

170 TABLE

2

Survey on the prerequisites for reproducible sensor action (l), driving forces and kinetics of sensor/molecule interactions (2), phenomenological thermodynamics of general sensor/ molecule interactions (3), and link between coverages 8, free enthalpies G and spectroscopic data Ei characterizing the atomistic structure of sensor surfaces and interfnces (4). For further details, aee text 1. Needed: sensor property

‘G’ = partition function dT

and

f

dG=0

2. Why sensor/molecule

intern&on ? How

fast?

* driving forces

AG = 0 thermodynamic equilibrium

free enthalpy G

AG < 0 reaction possible

(“driving force”)

AGrAGrd

large: slow reaction small: fast reaction

reactionpath 111111) 3. Why ‘G’ and not simply ‘energy’! *

Thermodynamics:

AG = AH-

TAS =

A( U + pV) - TAS

Examples : Adsorption 3

AU(m) favoured at T = 0 K

< o

AS<0

desorption at T > 0, if ITAS I > IAHI Point defects AU(U) -3 negligible at T = 0 K

> 0

A&!.J>O

favoured at high T, if ITAS I > IAH I 4. G ++ energies El of electrons, phonons, plasmons, . . . ? 3 Statistical thermodynamics: Ei +f Q = c i

exp(-Ei/kT)

* G = -kT

In Q -

a Z9ln V

* 8 = f(P)TeeOMt

etc.

during the acceptor-type chemisorption of O2 or N02. Results on this phenomenon are discussed in more detail in Section 3.1. The evaluation of chemisorption data is shown in a survey in Table 3 [l]. Binary oxides are the most common sensor materials. For simplification of the presentation, only this class of materials is considered in this Table.

171

Fig. 2. Schematic presentation of electronic charge transfer during the adsorption of an electron acceptor molecule (Xd)“at an n-type semiconductor. Here, ED is a bulk donor and EA 8 bulk acceptor level, X*v8 is the physisorption precurs~ r state and Xm the molecule in the gas phase. Valence and conduction band edges are denoted by Ev and EC, respectively. EF is the Fermi level [ 11. Further explanations are given in the text.

TABLE

3

Evaluation of chemisorption data (survey, after [ 1 J)

Experimental

data

sResulfs nbr 6%

-

EFh

Ax

“<#YE

T)

so

Helmholtz eqn. :

Ads. Thermodyn. :

Model parameters Fermi statistics

Poisson eqn. :

ND

eVf3 P” Q I- Qss 8 z Q,&qr,*

(EC - EDJ, (EC - %J

Fermi statistics:

Bad TDS theory: B&,

B”,

m

E ss --EF Thermodynamic and electronic structure of intrinsic bulk defects

Thermodynamic and electronic structure of extrinsic surface defects

Kinetics of adsorption and desorption, adsorption equilibria

172

Under thermodynamically controlled conditions, the volume structure and hence the conductivity.ob and mobility &, are determined by the temperature and partial pressure of O2 (compare the example in Fig. 8). Subsequently, the concentration nb of electronic charges and the position (Ec Ev)b of the bulk Fermi level can be calculated by using temperaturedependent data on conductivities cb and mobilities &,. During the measurement of these parameters, any concentration changes of the bulk defects have to be avoided. The bulk defects must be ‘frozen-in’, so that oh(T) and &,( 2’) are determined by the temperature-dependent effective ionization of defect levels at a constant concentration of these defects. The temperature dependence of IIb is then characterized by a minimum set of differently charged donor (and/or also acceptor), defect states with their individual concentrations NDtA) and characteristic energetic positions relative to the conduction band (Ec -En&. These model parameters describe the temperature-dependent position of the Fermi level EF and the concentration of free electrons nb in the bulk (compare also Fig. 2). These parameters make possible the calculation of the band bending eAV, as a function of changes in surface conductivities Aa, by means of the Poisson equation. In high-temperature solid oxide sensors, defect concentrations are adjusted unequivocally by oxygen partial pressures and temperatures. Hence, the bulk electronic conductivity may be used as a monitor of the oxygen partial pressure. Figure 3 illustrates that the bulk may contain donor (here Vo) as well as acceptor (here 0,) states, both of which may be singly and doubly ionized. Their concentration is determined by the partial pressure of oxygen. Surface defects Vos’ may occur with enhanced concentrations per unit area if compared with bulk defects. In solid-state electrolytes such as stabilized ZrO,, the contribution from the bulk ionic (02-) conductivity to the overall conductivity predominates. These solid-state electrolyte sensors may therefore be used as potentiometric or amperometric sensors to monitor oxygen. At low-temperatures, bulk defect structures are often frozen-in. Solidstate sensors can therefore be designed that make use of characteristic changes of the surface (not bulk) conductivity AuolCh’PI upon chemisorption.

A%)them

= AATeps, n + APep,

p = uo

The change in surface conductivity of the sheet conductance. = R-‘L2A-1 on

-

U,d

(1)

AuoJchem is determined by the deviation (2)

from the flat-band situation for which u. = ubd holds. Here d is the homogeneous thickness of a rectangular thin film sample of resistance R with the sensing outer surface A and the distance 1 between the two electrodes coating the two sides of the sensor. The value Au(l)chem contains contributions from mean mobilities pr, nc,) of electrons (holes) with concentrations AN( AP) per unit area in the space charge layer. To a first approximation, the values ~s,,C,j are often assumed to be identical to the corresponding bulk value

173

00 E”.,

E,,iOJ

-

! / !/

2.5 p

I

3.2 lV

(b)

b

I

i

14&I

co;1

I

1

1

-z

r1vm

F'ig, 3. Geometric (a) and electronic structure (b) of a typical binary oxide (such as ZnO) with surface oxygen vacancies Vos" and bulk defecte V, and’ O,, respectively. The latter determine the transport properties of oxygen during sensor pretreatment at high temperatures and, because of the different charges of singly- and doubly-ionized defects at ED~ and EAT, the temperature-dependent Fermi-level of the bulk. Typical surface defects, the concentration of which depends on the oxygen atmosphere, are oxygen vacancies Vos" and chemisorbed 02- [ 123. Further details are given in the text.

pb, nlPj. The surface excess concentrations AN(D) of electrons (holes) formed upon chemisorption lead to deviations from the flat-band situation, i.e., to eAVs # 0 in Fig. 2. Generally the variations in the sheet conductance may contain both, changes in bulk as well as in surface contributions. If bulk contributions are negligible and hole conduction can be ignored (as is the case for many n-type semiconductor materials), AN is deduced from A%) them. The known electronic structure of the bulk makes it possible to solve the Poisson equation and hence to determine the band bending eAVs and the charge per unit area Q, in the space charge layer. The latter is identical to the negative charge Q, per unit area in surface states E, (compare Fig. 2). From this, the partial charge 6 can be calculated, which is formally attributed to the chemisorption complex 6=

Qrslen~s~ad

(3)

The surface concentration of adsorbed species ntsjadis usually determined in independent thermal desorption spectroscopy (TDS) experiments. In TDS,

174

we determine mass-spectrometricallythe rate -dn,,jPd/dt of particles desorbing from the surface. Assuming the value & to be given by Fermi statistics, we determine the electronic level E, that is formally attributed to the chemisorption state relative to the position of the Fermi level at the surface 6%~ - EF)* A comparison of experimentally determined work function changes (e.g., from Kelvin-probe measurements) with band bending eA Vs leads to an estimation of electron affinity changes Ax from A# = -A(eVs)

+ Ax + A(&

- EF)b

(4)

if variations in the bulk Fermi level position A(& - &?)b can be neglected. An estimation of the dipole moment paa formally attributed to electron affinity changes is possible by using the equation Ax = e( rz,eO)-l padntsjad From thermal desorption experiments we also determine the adsorption isotherms ntsjad (P, 2’) ( i.e., the number of adsorbed particles per unit area ntsjad or their coverage f3) and from this the heat of adsorption per mole -ad

Q

16)

The TDS theory makes possible the determination of molar activation energies of desorption gdee, corresponding entropies of desorption fide8 and reaction orders of desorption m. The tilde (-) indicates molar quantities. The initial sticking cdefficient 8, is determined, e.g., from conductivity changes dAo(,) chem/dt extrapolated to zero coverage. The parameters 6, pad, So, qad, Ed’*, g des and rn characterize specific sensor-gas interactions for one specific molecule. In coadsorption experiments, corresponding excess parameters can be defined [24]. These parameters make it possible to characterize and understand atomistically the phenomenologically observed changes in conductivities, work functions, or masses during gas exposure to the sensor. As mentioned above, these simple evaluations only hold for constant concentration of defects in the bulk. At elevated temperatures, variations of bulk defect concentrations have to be considered and may even be made use of in high-temperature sensor devices. At even higher temperatures, bulk phase transitions of the sensor have to be considered also, which again depend on temperature and partial pressures. All physical parameters (see G ‘ ’ in Table 1) or reversibly functioning bulk sensors may also be described phenomenologically by excess parameters [ 241. 2.3. Theory The different solid-molecule interactions may be calculated, e.g., in a cluster approach with a typical example shown in Fig. 4. Here, the COz chemisorption is simulated at an oxide surface. This leads to characteristic changes in the dipole moment perpendicular to the surface (explaining pad) and effective surface states E, (explaining 6). The latter can be determined

z

Ii

Y X

(b) Fig. 4. Fkesultson cluster calculations simulating CO* chemisorption at an oxide surface. The surface is simulated by divalent Be and 0 atoms in the outer layer and by ‘embedding’ monovalent subsurface F and Li atoms, which produce the surface atom reconstruction AZ, Geometry and charge distributions (in units of elementary charges indicated in circles) are shown of (a) free CO2 molecules, (b) the free surface and (c) the surface after formation of a CO1 adsorption complex. Thii complex may e&y capture an additional elec tron, which explains the acceptor-type bonding of CO2 on, e.g., ZnO(1010) (compare Fig. 13). For details, see [l] and [13]. the highest occupied electronic level of a cluster containing One more electron than the neutral cluster to simulate the excess negative charge of the acceptor complex. The formation of this complex is characterized W 8 change in the total energy (explaining G *‘). From calculations of the total energies along reaction coordinates, the activation energy j!?deM(ad), the activation entropy SdeMad)of desorption (or adsorption), and the sticking coefficient Se may also be estimated. Intrinsic surface defects may lead to donor or acceptor states in the band gap and hence change the sensor properties drastically. A typical example is shown in Fig. 5. Under chemically reducing conditions, many oxides show donor-type surface defects, which act as catalytically active sites and are extremely important in understanding sensor and catalytic properties of oxides. An alternative theoretical approach to describing electronic properties is possible in calculations of band structures. Typical examples and results shown in Fig. 6 may be compared with results in Fig. 5. In both cases the determination is possible of geometric structures and electronic states with detailed information about the origin of corresponding atomic wave functions. from

3. Reeults for prototype sensor’ 3.1. Chamcteristic tempemture mnges Typical temperature ranges of sensor-gas interactions are shown in Fig. 7. Depending on temperature and partial pressures, sensors may be

176

Fig. 5. Cluster configuration of titanium (black) and oxygen atoms (open circles) simulating a Ti02(110) surface. An oxygen vacancy, indicated by a dotted circle at O(9), produces a donor-type defect level in the band gap between EV and EC. This level contains Ti(1) atomic wave functions only. The total and the ‘D(l) local population of molecular orbitah N(E) (corresponding to the density of states DOS in Fig. 6) is shown on the right. For details, see [ 141. .

t .________--~

.II____....~..’ X

-6

;” -4

-2

Q

Energy

Fc 2

4

6

8

(eV)

Fig. 6. Bulk density of states (DOS) of TiOz, together with partial oxygen (0) and titenium (Ti) densities of states. Oxygen DOSs are decomposed into O,, ,,,x orbital contributions and Ti partial DO& are decomposed into sub-bands of ec and hgsymmetry. The hatched areas indicate schematically the defect-induced band-gap state (compare Fig. 6). For details, see [ 15 3.

177

PO2I orb.

Bulk Defecta

F_ Physisorption

wt.1

Surface

Chemisorption I

Fig.

TIKI 7. Characteristic temperature ranges for sensor-gas interactions, which show up in

characteristic thermodesorption (TDS) peak maxima Pop of molecular oxygen during a linear temperature rise of the sample. In this particular example, ZnO(1010) surfaces were investigated. Curve c corresponds to desorption of non-ideally bound surface oxygen and is only observed during the firet heating of a cleaved single crystal. The hatched area of curve d characterizes predo minant 02 desorption during formation of VOS at the eurface. For details, see [ 16 ].

‘i- -2.4C

-1.4

-1.0

-0.6

-0.2

Lg(P/bar) Fig. 8. High-temperature bulk conductivity u of SnO2 samplea as determined from complex impedance spectroscopy at different temperatures T and oxygen partial pressures P 1173.

designed with their measuring principle based upon physisorption, chemisorption, surface, or bulk defect reactions. An example of the operating conditions of a bulk-defect sensor is shown in Fig. 8. Here, 6110~is used as an oxygen sensor by measuring the

178

electronic conductivity (J.In measurements of complex impedances at different frequencies, the various surface, interface and contact contributions to the overall conductivity can be senarated. The bulk values make possible the determination of bulk- defect corkentrations and their identification from the power law of conductivity changes: =b

-

PO,

-l/m

(7)

The experimental value m = 6 corresponds to doubly ionized oxygen vacanties Vo2+ in the bulk [ 17 1. With immobile ‘frozen-in’ oxygen vacancies in the bulk at low temperatures, Sn02 may be used as a chemisorption sensor, with a typical example shown in Fig. 9. These Sn02 thin films are excellent NO2 sensors, provided that the NO2 partial pressure is not too high and the O2 partial pressure is not too low. If the latter conditions are not fulfilled, chemisorbed NO2 decomposes and forms O*- ions, which move and react in the strong electrical field near the surface with oxygen vacancies Vo2+ in the lattice. The latter effect causes drifts in the overall conductivity, because free electrons are trapped during the reactions 0, + 2e _I+

O,*- --+

O*- + VO*+ ---+

OL

@I

with 0, as oxygen atoms formed during decomposition of chemisorbed NO2 at the surface and Oi as lattice oxygen in the bulk (for simplification, we

Fig. 9. Characteristic chemisorption effects in surface conductivity changes Au, which may be used to monitor quantitatively traces of NO2 in the ppb range with SnO2 thin films at T = 400 K under atmospheric pressure conditions [ 18 1.

179

_A-’

I

r-

Film

-O’

ill mcuum

Thickness

Fig. 10. Characteristic sheet conductivities uo as a fun&&n of film thickness d of PbPc thin fiis. The drastic change in the slope indicates a bulk effect during 02 interaction. Surface effects, showing up as changes in the axis intercept AU of the 00 data extrapolated to film thickness zero, sre insignificant for this solid/gas system [ 191.

have neglected partial charges or different ionization states of 0,, 02- and V 02+9 which depend on the different experimental conditions). An example of how to separate surface and bulk contributions to the overall sensing effect is shown in Fig. 10. Here, the sheet conductivity cl0 of PbPc thin films is plotted as a function of film thickness d before and after exposing the sensor to oxygen. From the change in slope, we deduce an O2 bulk effect. Corresponding interaction with NO2 leads to a change in the axis intercept for a constant slope of these curves. This clearly identifies the NO2 interaction with PbPc to be a surface effect. Figure 11 shows characteristic interaction steps as a function of z, i.e., as a function of distance from the sensor surface for the particular example of 02/oxide interactions. The results were obtained from investigations of thermodynamically and kinetically controlled solid-gas interactions. The investigations also included a spectroscopic identification of the different species involved. The diagram shows different minima and activation barriers between these minima, which have to be overcome in kinetically controlled

180 Wke-

sur fuce -

+gas

Fii. 11. Characteristic interaction step between oxygen and the thermodynamically most stable surfaces of ZnO and TiOz as characterized by the potential energy Epd attributed to the different reactions listed in the lower part as a function of didance z from the aurface. %(,,I denotes oxygen at ideal (surface) lattice sites [l]. For details, see text.

solid-gas interaction steps. If, in addition, the temperaturedependent entropy contributions are also taken into consideration, we can determine unequivocally the temperatures and partial pressures for specific sensor actions and hence can optimize this sensor to operate as a physisorption, chemisorption, surface- or bukdefect oxygen detector. In the next step of a systematic approach to design reliable sensors, the interaction of other gases than O2 with the same sensor surface has to be investigated individually. For each gas this leads to similar results to those shown in Fig. 11. In a third step, coadsorption phenomena have to be investigated for different concentrations and temperatures of those different gases, which are expected in a realistic sensor environment. This leads to similar results to those of Fig. 11. However, the characteristic features now also depend on the partial pressures, or more precisely on the chemical potentials of the different components in the gas phase [24]. If operating conditions of our sensors are not optimized cafefully for just one predominant interaction step, or if the different minima shown schematically in Fig. 11 are not separated clearly enough from each other, different interaction steps may occur simuItaneou.sIy.If the time constants of competing interaction steps become slow but not negligible, this leads

181

to the well-known difficulties in designing reproducible and reversibly acting sensors. 3.2. Spectroscopic studies The prerequisite for an atomistic understanding of the thermodynamics and kinetics of sensor-gas interactions is the spectroscopic identification of the different surface species involved. An example is shown in Fig. 12. Here, the physisorption and chemisorption steps of COz on ZnO(lOi0) are monitored by means of ultraviolet photoemission (UPS) experiments. In these experiments, photons induce the emission of electrons from the valence band range of the sensor. Characteristic changes are observed upon COz interaction. For comparison, the molecular orbitals (MOs), determined from UPS on free COz molecules, are also shown in Fig. 12. They explain the MOs of weakly bound ‘physisorbed’ COz. An identification of the CO, chemisorption complex is possible by comparing these UPS results with results on electronic structures as derived from MOs in the cluster calculations described in Section 2.3. After characterizing spectroscopically the different interaction steps including physisorption, chemisorption, surface and bulk defects, characteristic temperature ranges can be determined experimentally for the existence

(a)

*‘if 10

IS

0

5

NIEt S”

q

40, I, (b)

,5

‘“i”T (c)

u

15

*’

i.pJ l V t0

10 -

”

5

‘*

;i,

5

0

E,-E,leV

Fig. 12. Spectroscopic identification of adsorption co_mplexes on solid-state sensors. In this particular example, changes AN(E) in the ZnO(1010) valence band (TJPS difference spectra) are shown (a) after physiaorption of CO,, (b) after chemiaorption of CO2, with (c) corresponding to a UPS spectrum N(E) of free CO2 molecules (Lp. is the ionization potential of the different molecular orbitals 1 ng, 1 ma etc.). The excess concentration of photoemitted electrons &V(E) is plotted as a function of electron binding energy Eb referred to the valence band edge Ev ([ 1 ] and [20]). Details are given in the text.

Physisofpbm I 100

I 300

-p(ion

1 500

8 700

w

d8frfs -

T/K

Fig. 13. Characteristic adsorption complexes at the ‘prototype’ oxide surface ZnO(loi0) with different temperature ranges, which are important to understand the CO sensing mechanism and the catalytic activity for CO2 formation upon CO exposure [21]. Details are given in the text.

of different adsorption species. Typical results are shown in Fig. 13 for the particular example of ZnO(lOi0) surfaces interacting with CO, O2 and C02. 3.3. Gas-sensing and catalysis An interesting correlation between catalytic activity and sensor properties of oxide sensors can be deduced from the following two pictures. In Fig. 14 the rate B of catalytic CO2 formation is shown as a function of temperature with a characteristic maximum in the temperature range between stable chemisorption species and stable point defects on ZnO(lOi0) (compare Fig. 13). Figure 15 shows a similar maximum of the sensor sensitivity. Here, the response of the sensor during catalytic oxidation of CO is monitored by measuring concentrations of free electrons in the conduction band. Evidently, sensing properties and catalytic activities are correlated. Characteristic differences between optimizing chemical sensors and optimizing catalysts result from the fact that catalysts are usually exposed to few molecules only and are optimized to produce a particular product selectively. Chemical sensors, however, are usually exposed to a large variety of different molecules and should at best detect only one of these molecules. Drastic changes of surface properties ‘G’ have to be optimized in chemical sensor research and development work, whereas the reaction rates have to be optimized in corresponding heterogeneous catalysis work, In both cases, however, long-term stability is a significant goal.

183

0

r

t O.ClS

alni

0.W

0.02

1.5

2.0

2.5

KI

TEMPERATURE T: TillO' K-II Fig. 14. Rate B of catalytic CO2 formation (numbers of CO2 molecules formed per CO molecule hitting the surface) as a function of temperature for various partial pressure ratios Po,/Pco. For details, see [21].

Fig, 16. Sensitivity in relative changes of conductivities AG/Go as a function of temperature for CO interaction with SnOz polycryatalline 8ensors of different bulk dopings. For details, see [22].

4. Future trends A few aspects of future trends in the development of solid-state chemical sensors will now be summarized. 4.1. New techniques of interface analysis In the past, solid-state chemical sensors have been optimized only empirically. The few examples investigated in more detail and discussed above demonstrate that systematic research may lead to better sensor devices. This approach requires experimental methods of surface and interface analysis, some of which are listed in Table 4. Some of these methods can be applied, both under ultrahigh vacuum and under high-pressure or liquidelectrolyte conditions, with transfer vesselsto move the samples between the different experimental set-ups. It would be desirable to have all these experimental methods available in only one experimental set-up. This would, e.g., make it possible to study quantitatively the influence of the different probes such as photons, electrons, atoms or ions used in these techniques on the interfacial properties. The methods listed in Table 4 do, however, require the construction of at least three independent experimental set-ups with typical machines shown schematically in Figs. 16 - 18.

184 TABLE

4

Experimental methods of surface and interface analysis used to study solid&ate chemical sensors

1. Geometric

armngement

SEM (SPA) LEED TISTIMS (S)EDX (S)ESD ISS 2, Elemental

of atoms

scanning electron microscopy spot profile analysis in low-energy electron diffraction scanning Auger microscopy (scanning) secondary ion mass spectrometry (scanning) energy dispersive X-ray analysis (scanning) electron stimulated desorption ion scattering spectroscopy

composition,

contaminations

AEX

Auger electron spectroscopy (incl. depth profiles)

;MsS ( S)EDX TDS (S)SIMS ISS

(monochromatic) X-ray photoemission spectroscopy thermodesorption spectroscopy

3. Electronic

structure

(W-S

of core and vaknce band levels

(polarization and angle-resolved) ultraviolet photoemission spectroscopy energy loss spectroscopy

(PAR)UPS ELS AES 4. Dynamic HRELS or EELS (FT)IR

structure,

vibrations

high resolution electron energy loss spectroscopy (Fourier transform ) infrared spectroscopy

5. Coverage of adsorbed particles, sticking mass differences TDS (S)ESD

coefficients

&%PS 6. Bond stabilities of desorp tio n TDS (MWS HRELS B

of particles

measurements of reaction heats

7. Electrical properties:

particles, @T, VI cI(T, v) Ac, & A+, Ax AC Ae.m.f.

I

at sensor surfaces, heats of reaction, energies and entropies

volume doping, partial charges and dipole moments voltages and currents in electrochemical cells, . . .

of adsorbed

temperature and frequency dependent conductivity and mobility conductivity and mobility variations during interaction of particles with the sensor surface, a&sequent TDS change in work function and electron affinity capacity variations measurements of potential differences and currents

185

mm-_-

B!V

!pFF

!gjjyb

i

I

A~.Ae.pl

I Jo’

dcao

hr.1

.1 Au,A~,TDS. gas dmw. LEE0 i ~~~~tOr.

!IWlx?s.U~S.IEf; t)A-m, EELS.lSf.CLS, Ao. A*, IDS, ~8 hnr. thannr war. I up* drprs

Fii. 16. Experimental set-up to prepare, modify and study solid-&ate gas sensors thermodynamically or kinetically controlled under high preswre and under ultrahigh vacuum (UHV) conditions [ 11.

Detailed information about the quantum structures of sensors and adsorbates is obtained in the set-up shown in Fig. 16. In this machine, information concerning the geometric arrangement, elemental composition, electronic structure, dynamic structure, coverage and bond stabilities as well as electrical properties is obtained with averaged results integrated over an area of typically 2 X2 mm2. This area is determined by the diameter of the exciting beams or apertures of the detectors in the different spectrometers. If in addition the specific influence of grain boundaries or surface segregation has to be studied and taken into consideration, high spatial resolution is desirable for all spectroscopies, even though the energetic resolution in the determination of quantum structures may be poor if compared to the resolution of the instruments shown in Fig. 16. This compromise to gain high spatial resolution requires an experimental set-up as shown in Fig. 17. Grain boundaries play an important role, e.g., in temperature- and pressuredependent segregation phenomena on SnOz thick-film samples, ZrOl high temperature ceramic sensors etc. Organic molecules or hydrogen cannot be determined unequivocally with any of these techniques shown in Figs. 16 and 17. The detection of hydrogen as well as the characterization of large organic molecules, e.g., in biosensor devices, is possible with secondary ion mass spectroscopy (SIMS), which may also be used in the scanning mode (SWIMS). A typical experimen-

186 @ -600

System

Adapter

Preparation-Chamber

Trm8pxtl’mssurm 140 bu)Prwrlum mu)c#8 Hqh

SEM.SAM.(S)EDX.(S)ESD.ISS.AES

Evaporators, Thickness Monitors, Shutters, Aa = f(u). A 4. Rheed

Fig. 17. Experimental set-up to prepare and modify eolid-state chemical sensors and to measure their elemental distribution at the surface and in the bulk with high q~&ial rebolution by means of SEM, SAM, SEDX and SESD [23]. Further details are given in the text.

tal set-up is shown in Fig. 18. Here, changes in the surface atom composition and electronic structures can be monitored simultaneouslywith XPS and UPS. In order to move samples between the different chambers shown schematically in Figs. 16 - 13 without uncontrolled contamination from the ambient air, UHV sample transfer vessels are used. This allows the sample modification and preparation to be done under controlled conditions. Results may then be compared with results from systematically ‘contaminated’ samples or with results from samples that have been used under practical application conditions and have been introduced to the spectrometers through fast entry locks. 4.2. Tiuodimensiunal physical chemistry at interfaces Improved atomistic understanding about the driving forces for chemical reactions is required. Some examples have been discussed already in Sections 2 and 3. The concept of designing solid-state chemical sensors based upon basic science knowledge is summarized in Table 6. 4.3. New materials A list of ‘new materials’ for chemical sensors is given in Table 6. The study of semiconductors in particular is important for hybrid devices in

137

Analysis-Chamber

Preparation-Chamber

bnenIr#rnnlm

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kN_h m-&r-.-l

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Evaporators. Shutters.

0

m c

m

Thickness A Acs = f(w).

(cb+l

Monitors,

a,. Rheed

Q

FtiSU+krvo*retbll frmuf*mm

0.5 p

,CS)SIMS.SED.TDS.XPS.UPS.(LEED)

I

Fig. 18. Experimental set-up to prepare and modify solid-state chemicals sensors, to measure the spatial distribution of hydrogen atoms and to determine organic molecules by means of SSIMS. Simultaneously, the surface elemental composition may be monitored with 2WS and UPS [ 231. Further details are given in the text.

which chemical sensors are designed by selectively coating modified semiconductor devices. The latter are produced by conventional technologies of microelectronics (Si, . . .) or optoelectronics (Gas, InP, . . .). In this context, an atomistic understanding about stabilities of interface chemical and electronic states is of particular importance. The ‘classical’ gas sensors are based upon oxides with specific metal dopmgs. In this context, more detailed studies are of particular interest for perovskites or the new oxide superconductor materials, which may also be used as chemical sensors. Solid-state electrolytes are used in miniaturized ‘microionic’ devices. This requires reproducible high-temperature treatment and the optimization of sensor materials, contacts and reference electrodes. Metal organic compounds, some of which are also interestingmolecular electronic devices, provide a fascinating class of new materials, since they make possible the modification of specific adsorption sites within one molecule. Different membranes are often required to avoid sensor contamination or to gain specific selectivity.

188 TABLE 5 Basic science and design concepts for solid-state chemical sensors

1. Identify spectroscopically and eearch for thermodynamically 1 .l. Structures of clean surfaces

controlled

1.2. Physisorption 1.3. Chemisorption 1.4. Formation of intrinsic defects (a) surface defects only (b) bulk defects in equilibrium with surface defects 1.5. Bulk phase transitions 2. Study

the influence of dopants 2 .I. Surface doping only

2.2. Bulk doping in equlibrium with surface doping (segregation equilibria) 3. Study

coadsorption

phenomena

4. Study the kinetics of geneml soiid/gas (liquid) intemctione pretreatment8

after various sample

5. Choose different forms of substrates 5 -1. Single crystals 5.2. 5.3. 5.4. 5.5. 5.6.

Thin films Thick films Ceramics Polycrystalline and amorphous materials Structured electronic and ionic thin- and thick-fib

6. Compare results from ‘cheap’ techniques

of practical

devices

importance

with speckoncopic

techniques 6.1. ‘Cheap’: V, i, 0, 9, c, $‘*, p*-,

m, E (see Table 1) 6.2. Spectroscopic: XPS, TIM, AES, EELS, SIMS, . . . (see Table 4)

In designing biosensors, the immobilization of enzyme systems is of particular interest (Fig. 19). 4.4. New technologies of these materials Each material requires specific technologies to prepare well-defined sensor structures such as the different thin-film and thick-film deposition techniques with and without electron or photon assistance, hot isostatic pressing (HIP) of ceramic materials, Langmuh-Blodgett film preparation, thermal decomposition of organic materials etc. Packaging of sensor devices with new materials and the compatibility of these materials with sensoractive materials is of particular importance. 4.5. Microstructured devices A variety of new sensor devices make use of the possibility of microstructuring devices. Recent trends are to combine electrochemistry with modified field-effect tram&or gates, to combine catalysts and microstructured semiconductor sensors, to combine catalysts and optoelectronic devices, and to design microelectronic and mixed conducting composite

189 TABLE

6

Materials for chemical Bermor 1. Semiconductors Si, G&s, InP, . . . 2. Oxides without and with specific metal dopings Si02, A1203, Sn&, Ti02, ZnO, Rho,, CupO, SrTiOs, oxide superconductors, . . . 3. Optimized heterogeneowr catalysts Substrates: A&03, SiOz, TiO,, . . . Chemical modifications: Oxides of Rh, Ce, MO, Cr, Co, . . . Promotors: Pt, Rh, Ru, Ni, Pd, . . . 4. Solid-&ate electrolytes ZrO2, CeO2, LaF3, &alumina, NASICON, AgK, AgCl, . . . contacts : Ft , . . . Reference electrodes Ni/NiO, Pd/PdO,, Pd/PdH,, WOsH,, . . . 5. (Metal-) organic compound8 Pb, Ru, . . . phthalocyanines, porphyrins, donor/acceptor complexes, silicon-organic compounds, Langmuir-3lodgett fii, polypyrrole, . . . 6. Mem banes 7. Enzyme systems, antibodies, receptor8 (proteins) Organelles, Mkroorgani8m8, Animal and plant cells (tkues)

Adsorption

Caratant Banding

fi!?stJ& Crosslinking

Emaddinp

in a Hotrix

Pig. 19. Schematic drawing of different waya to immobilize biocatalpti

(enzymes).

devices. The next trend is to combine chemical sensor devicee with other (e.g., mechanical, thermal, . ..) microstructured sensor devices, e.g., for medical or automobile applicatione.

190

4.6. Pattern recognition Figure 20 shows the principle of pattern recognition in which nonselective, reproducible sensors with crosscontaminations are used to deterT

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Pattern Accognition

Fig. 20. Pattern recognition and chemical sensing.

i

191 Ni

7 CO+H,

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-

1 CH,+H~~

Methane

1

h-t-Oxide Fe.

Co

-

Catalyst

Fig. 21. Different catalysts known from the synthesis of organic molecules starting with CO and Hz may be used to detect these organic molecules by using these cataIy8t.sand CO and/or Hz chemical sensors in pattern recognition devices.

mine the composition of different gases (lower part). Instead of using different sensor elements, one may also use the same sensor element and different catalysts, with particular examples shown in Fig. 21. The combination of catalysts, sensors and selective diffusion barriersof membranes will lead to a variety of future pattern recognition designs. This concept is of particular interest in simulating detection principles of our human senses. Our nose, as an example, has only a few receptors. By using our brain with its sophisticated pattern recognition capability, a wide spectrum of different odours can be detected and memorized. 5. Outlook Using modern tools of interface analysis, an atomistic understanding can be obtained of the driving forces for sensor-gas interactions. Thermodynamics, kinetics, and interface spectroscopy are the main components of interface technology as the future key-technology. These components are not only important for developments in the field of (bio-)chemical sensors, but also in other fields of application, some of which are indicated in Fig. 22. Therefore our technological know-how and understandingof ‘new materials’ and their interface phenomena in chemical sensor applications will also contribute to future developments in these other fields and vice versa.

References W. Giipel, Chemisorption and charge transfer at semiconductor surfaces: Implications for designing gas sensors, Progr. Surfiie Sci, 20 (1986) 9. J. Janata and R. J. Huber, Solid State Chemical Seneots, Academic Press, New York, 1986. A. P, F. Turner, I. Karube and G. S. WiIson, Bi’oeerrcrora:Fundumentab und Applications, Oxford University I%=, Oxford, 1987. D. Schuetxle, R. Hammerle and J. W. Butler, Fundamental and applications of chemical sensors, Amen’can Chemical Society Symp. Series, 309, Washingtan, DC, 1986. W. Giipel, Development of chemical sensors: Empirical art or systematic research, Tech. Me-n, 52 (2) (1986) 47; (3) (1986) 92; (6) (1986) 176. Proc. let Int. Meet. on Chem. Sen#orr, Fukuoka, Japnn, 1983.

Proc. 2nd Int. Meet. on Chem. Seneom, Bodeaux,

France. 1986.

192

SINW

CRYSTALS

Naalc#sTALLlWE LAYERS

WELL-llEFlm0 LAYER SY!ZEMS

*)*#pHoos MATERIALS PcKYcRYsTALLl* IAYERS

WELL - OEFINED lNTERFAcEs l

’ COMPLEXITY

”

OF THE STRUCTURE

-

Fig. 22. Basic science and practical applications of new materials. The importance of tbermodynamice, kinetics and interface spectroscopic analysis is illustrated in an overview representing the prea~ure and complexity gaps. Material8 investigated in the other fields of applications indicated here may aleo be used to design new chemical sensors, and vice versa.

8 P#‘oc. 3rd Int. Confi

on Sol&State Selurors ad Actuatora {Tnznuducela ‘85). Philadelphia, PA, I986. 9 Proc. 4th Int. Meet. on Solid-State Senaom and Actuators (Wanaducela ‘87). Tokyo, 1987. 10 W. Heywang, Senrrorik, Springer Verlag, Berlin, 1984. 11 P. Rofos, Industrielte Metwtechnik, Vulkan-Verlag, Baael, 1984. 12 W. Giipel and U. Lamps, Influence of defects on the electronic structure of zinc oxide surfaces, Phycr. Rev. B, 22 (12) (1980) 6447 and refa. therein. 13 W. Gijpel and G. Rocker, Localized and delocaliied charge transfer during adsorption on semi~onductora: Experiments and clueter calculations on the prototype surface ZnO(lOlO), J. Vat. Sci. Technol.. 21 (2) (1982) 389. 14 M, Tukada, H. Adachi and C. Satoko, Clu&r caiculation~~of electronic and geometric etructures of oxide aurfaixq Rogr. Surface Sci., 14 (1983) 113. 16 S. Munnix and M. Schmeitr, Theoretical calculation of surface electronic band structures of SnOp and TiO2, Phys. Rev. B, 30 (1984) 2202. 16 W. Giipel, Oxygen Meraction of atoichiometric and nonstoichiometrk ZnO priematic surfaces, Surface Set, 62 (1977) 166. of the bulk defect chemistry of polycrystalline 17 J. Metier and W. Giipel, Invedigations tin IV-oxide, J. Sola State Chem., 72 (1988) 293. 18 K. D. Schierbaum, H. D. Wiemhiifer and W. Gijpel, Defect structure and eenaing mechanism of Sn02 gas sensors: Comparative electrical and spectroscopic results, hoc. 6th Int. Conf. on Solid State Ion& Garmisch-Partenkirchen, F.R.G., 1987 and Solid State Ion&, in preae.

193 19 H. D. Wiemhiifer, H. Mockert, D. Schmeisuer and W. Giipel, Activation of low temperature oxygen sensors by selective coating with lead-phthalocyanine, Proc. 4th Int. Gonf. on SolidState Sensors and Actuators (Transducers ‘87), Tokyo, 1987, p. 686 and submitted to Sensors and Actuators. 20 W. GGpel, R. S. Bauer and G. V. Hansson, Ultraviolet photoemission studies of chemisorption and point defect formation of ZnO non-polar surfaces, Surface ScL, 99 (1980) 138. 21 P. Easer, R. Feierabend and W. Giipel, Comparative study on the reactivity of polycrystalline and single crystal ZnO surfaces: Catalytic oxidation of CO, Ber. Bunsengee. Phye. Chem., 85 (1981) 447. 22 S. J. Gentry and T. A. Jones, The role of catalysis and solid state gas sensors, Sensors and Actuators, 10 (1986) 141. 23 W. Gijpel, D. Schmeisser and H. D. Wiemhiifer, Multimethod interface analysis of solid state chemical sensors: Studies of prototype inorganic and organic sensor materials, Proc. ECASIA ‘8 7, Stuttgart, F.R.G.. 198 7. 24 W. Giipel, Oberflichenphyeik (Textbook), Teubner-Verlag Stuttgart, in press; K. D. Schierbaum, R. Kowalkoweki and W. Giipd, Multicomponent gas analysis: An analytical chemistry approach applied to SnOz-based sensors, submitted to Sensors and

Actuutors.

Biography Wolfgung G6peZ received his Ph.D. from the University of Hannover in 1971. After visiting scientist positions at the Xerox Palo Alto (CA), Xerox Webster (NY) and IBM Watson (NY) Research Centers he was appointed as Full Professor of Physics at the Center of Surface and Submicron Analysis, Bozeman (MT). Since 1983 he has been the Director of the Institute of Physical and Theoretical Chemistry at the University of Tiibingen, with research interests in interface properties of new materials for chemical semom, catalysts, molecular electronic and microelectronic devices.