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Electron mobility
Electron mobility
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In solid-state physics, the electron mobility characterizes how quickly an electron can move through a metal or semiconductor when pushed or pulled by an electric field. There is an analogous quantity for holes, called hole mobility. The term carrier mobility refers in general to both electron and hole mobility.

Electron and hole mobility are special cases of electrical mobility of charged particles in a fluid under an applied electric field.

When an electric field E is applied across a piece of material, the electrons respond by moving with an average velocity called the drift velocity, . Then the electron mobility μ is defined as

Electron mobility is almost always specified in units of cm2/(Vs). This is different from the SI unit of mobility, m2/(Vs). They are related by 1 m2/(V⋅s) = 104 cm2/(V⋅s).

Conductivity is proportional to the product of mobility and carrier concentration. For example, the same conductivity could come from a small number of electrons with high mobility for each, or a large number of electrons with a small mobility for each. For semiconductors, the behavior of transistors and other devices can be very different depending on whether there are many electrons with low mobility or few electrons with high mobility. Therefore mobility is a very important parameter for semiconductor materials. Almost always, higher mobility leads to better device performance, with other things equal.

Semiconductor mobility depends on the impurity concentrations (including donor and acceptor concentrations), defect concentration, temperature, and electron and hole concentrations. It also depends on the electric field, particularly at high fields when velocity saturation occurs. It can be determined by the Hall effect, or inferred from transistor behavior.

Introduction

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Drift velocity in an electric field

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Without any applied electric field, in a solid, electrons and holes move around randomly.[clarification needed] Therefore, on average there will be no overall motion of charge carriers in any particular direction over time.

However, when an electric field is applied, each electron or hole is accelerated by the electric field. If the electron were in a vacuum, it would be accelerated to ever-increasing velocity (called ballistic transport). However, in a solid, the electron repeatedly scatters off crystal defects, phonons, impurities, etc., so that it loses some energy and changes direction. The final result is that the electron moves with a finite average velocity, called the drift velocity. This net electron motion is usually much slower than the normally occurring random motion.

The two charge carriers, electrons and holes, will typically have different drift velocities for the same electric field.

Quasi-ballistic transport is possible in solids if the electrons are accelerated across a very small distance (as small as the mean free path), or for a very short time (as short as the mean free time). In these cases, drift velocity and mobility are not meaningful.

Definition and units

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The electron mobility is defined by the equation: where:

  • E is the magnitude of the electric field applied to a material,
  • vd is the magnitude of the electron drift velocity (in other words, the electron drift speed) caused by the electric field, and
  • μe is the electron mobility.

The hole mobility is defined by a similar equation: Both electron and hole mobilities are positive by definition.

Usually, the electron drift velocity in a material is directly proportional to the electric field, which means that the electron mobility is a constant (independent of the electric field). When this is not true (for example, in very large electric fields), mobility depends on the electric field.

The SI unit of velocity is m/s, and the SI unit of electric field is V/m. Therefore the SI unit of mobility is (m/s)/(V/m) = m2/(Vs). However, mobility is much more commonly expressed in cm2/(V⋅s) = 10−4 m2/(V⋅s).

Mobility is usually a strong function of material impurities and temperature, and is determined empirically. Mobility values are typically presented in table or chart form. Mobility is also different for electrons and holes in a given material.

Derivation

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Starting with Newton's second law: where:

  • a is the acceleration between collisions.
  • F is the electric force exerted by the electric field, and
  • is the effective mass of an electron.

Since the force on the electron is −eE:

This is the acceleration on the electron between collisions. The drift velocity is therefore: where is the mean free time

Since we only care about how the drift velocity changes with the electric field, we lump the loose terms together to get where

Similarly, for holes we have where Note that both electron mobility and hole mobility are positive. A minus sign is added for electron drift velocity to account for the minus charge.

Relation to current density

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The drift current density resulting from an electric field can be calculated from the drift velocity. Consider a sample with cross-sectional area A, length l and an electron concentration of n. The current carried by each electron must be , so that the total current density due to electrons is given by: Using the expression for gives A similar set of equations applies to the holes, (noting that the charge on a hole is positive). Therefore the current density due to holes is given by where p is the hole concentration and the hole mobility.

The total current density is the sum of the electron and hole components:

Relation to conductivity

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We have previously derived the relationship between electron mobility and current density Now Ohm's law can be written in the form where is defined as the conductivity. Therefore we can write down: which can be factorised to

Relation to electron diffusion

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In a region where n and p vary with distance, a diffusion current is superimposed on that due to conductivity. This diffusion current is governed by Fick's law: where:

  • F is flux.
  • De is the diffusion coefficient or diffusivity
  • is the concentration gradient of electrons

The diffusion coefficient for a charge carrier is related to its mobility by the Einstein relation. For a classical system (e.g. Boltzmann gas), it reads: where:

For a metal, described by a Fermi gas (Fermi liquid), quantum version of the Einstein relation should be used. Typically, temperature is much smaller than the Fermi energy, in this case one should use the following formula: where:

  • EF is the Fermi energy

Examples

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Typical electron mobility at room temperature (300 K) in metals like gold, copper and silver is 30–50 cm2/(V⋅s). Carrier mobility in semiconductors is doping dependent. In silicon (Si) the electron mobility is of the order of 1,000, in germanium around 4,000, and in gallium arsenide up to 10,000 cm2/(V⋅s). Hole mobilities are generally lower and range from around 100 cm2/(V⋅s) in gallium arsenide, to 450 in silicon, and 2,000 in germanium.[1]

Very high mobility has been found in several ultrapure low-dimensional systems, such as two-dimensional electron gases (2DEG) (35,000,000 cm2/(V⋅s) at low temperature),[2] carbon nanotubes (100,000 cm2/(V⋅s) at room temperature)[3] and freestanding graphene (200,000 cm2/(V⋅s) at low temperature).[4] Organic semiconductors (polymer, oligomer) developed thus far have carrier mobilities below 50 cm2/(V⋅s), and typically below 1, with well performing materials measured below 10.[5]

List of highest measured mobilities [cm2/(V⋅s)]
Material Electron mobility Hole mobility
AlGaAs/GaAs heterostructures 35,000,000[2] 5,800,000[6]
Freestanding graphene 200,000[4]
Carbon nanotubes 79,000[7][8]
Cubic boron arsenide (c-BAs) 1,600[9]
Crystalline silicon 1,400[1] 450[1]
Polycrystalline silicon 100
Metals (Al, Au, Cu, Ag) 10–50
2D material (MoS2) 10–50
Organics 8.6[10] 43[11]
Amorphous silicon ~1[12]

Electric field dependence and velocity saturation

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At low fields, the drift velocity vd is proportional to the electric field E, so mobility μ is constant. This value of μ is called the low-field mobility.

As the electric field is increased, however, the carrier velocity increases sublinearly and asymptotically towards a maximum possible value, called the saturation velocity vsat. For example, the value of vsat is on the order of 1×107 cm/s for both electrons and holes in Si. It is on the order of 6×106 cm/s for Ge. This velocity is a characteristic of the material and a strong function of doping or impurity levels and temperature. It is one of the key material and semiconductor device properties that determine a device such as a transistor's ultimate limit of speed of response and frequency.

This velocity saturation phenomenon results from a process called optical phonon scattering. At high fields, carriers are accelerated enough to gain sufficient kinetic energy between collisions to emit an optical phonon, and they do so very quickly, before being accelerated once again. The velocity that the electron reaches before emitting a phonon is: where ωphonon(opt.) is the optical-phonon angular frequency and m* the carrier effective mass in the direction of the electric field. The value of Ephonon (opt.) is 0.063 eV for Si and 0.034 eV for GaAs and Ge. The saturation velocity is only one-half of vemit, because the electron starts at zero velocity and accelerates up to vemit in each cycle.[13] (This is a somewhat oversimplified description.[13])

Velocity saturation is not the only possible high-field behavior. Another is the Gunn effect, where a sufficiently high electric field can cause intervalley electron transfer, which reduces drift velocity. This is unusual; increasing the electric field almost always increases the drift velocity, or else leaves it unchanged. The result is negative differential resistance.

In the regime of velocity saturation (or other high-field effects), mobility is a strong function of electric field. This means that mobility is a somewhat less useful concept, compared to simply discussing drift velocity directly.

Relation between scattering and mobility

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Recall that by definition, mobility is dependent on the drift velocity. The main factor determining drift velocity (other than effective mass) is scattering time, i.e. how long the carrier is ballistically accelerated by the electric field until it scatters (collides) with something that changes its direction and/or energy. The most important sources of scattering in typical semiconductor materials, discussed below, are ionized impurity scattering and acoustic phonon scattering (also called lattice scattering). In some cases other sources of scattering may be important, such as neutral impurity scattering, optical phonon scattering, surface scattering, and defect scattering.[14]

Elastic scattering means that energy is (almost) conserved during the scattering event. Some elastic scattering processes are scattering from acoustic phonons, impurity scattering, piezoelectric scattering, etc. In acoustic phonon scattering, electrons scatter from state k to k', while emitting or absorbing a phonon of wave vector q. This phenomenon is usually modeled by assuming that lattice vibrations cause small shifts in energy bands. The additional potential causing the scattering process is generated by the deviations of bands due to these small transitions from frozen lattice positions.[15]

Ionized impurity scattering

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Semiconductors are doped with donors and/or acceptors, which are typically ionized, and are thus charged. The Coulombic forces will deflect an electron or hole approaching the ionized impurity. This is known as ionized impurity scattering. The amount of deflection depends on the speed of the carrier and its proximity to the ion. The more heavily a material is doped, the higher the probability that a carrier will collide with an ion in a given time, and the smaller the mean free time between collisions, and the smaller the mobility. When determining the strength of these interactions due to the long-range nature of the Coulomb potential, other impurities and free carriers cause the range of interaction with the carriers to reduce significantly compared to bare Coulomb interaction.

If these scatterers are near the interface, the complexity of the problem increases due to the existence of crystal defects and disorders. Charge trapping centers that scatter free carriers form in many cases due to defects associated with dangling bonds. Scattering happens because after trapping a charge, the defect becomes charged and therefore starts interacting with free carriers. If scattered carriers are in the inversion layer at the interface, the reduced dimensionality of the carriers makes the case differ from the case of bulk impurity scattering as carriers move only in two dimensions. Interfacial roughness also causes short-range scattering limiting the mobility of quasi-two-dimensional electrons at the interface.[15]

Lattice (phonon) scattering

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At any temperature above absolute zero, the vibrating atoms create pressure (acoustic) waves in the crystal, which are termed phonons. Like electrons, phonons can be considered to be particles. A phonon can interact (collide) with an electron (or hole) and scatter it. At higher temperature, there are more phonons, and thus increased electron scattering, which tends to reduce mobility.

Piezoelectric scattering

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Piezoelectric effect can occur only in compound semiconductor due to their polar nature. It is small in most semiconductors but may lead to local electric fields that cause scattering of carriers by deflecting them, this effect is important mainly at low temperatures where other scattering mechanisms are weak. These electric fields arise from the distortion of the basic unit cell as strain is applied in certain directions in the lattice.[15]

Surface roughness scattering

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Surface roughness scattering caused by interfacial disorder is short range scattering limiting the mobility of quasi-two-dimensional electrons at the interface. From high-resolution transmission electron micrographs, it has been determined that the interface is not abrupt on the atomic level, but actual position of the interfacial plane varies one or two atomic layers along the surface. These variations are random and cause fluctuations of the energy levels at the interface, which then causes scattering.[15]

Alloy scattering

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In compound (alloy) semiconductors, which many thermoelectric materials are, scattering caused by the perturbation of crystal potential due to the random positioning of substituting atom species in a relevant sublattice is known as alloy scattering. This can only happen in ternary or higher alloys as their crystal structure forms by randomly replacing some atoms in one of the sublattices (sublattice) of the crystal structure. Generally, this phenomenon is quite weak but in certain materials or circumstances, it can become dominant effect limiting conductivity. In bulk materials, interface scattering is usually ignored.[15][16][17][18][19]

Inelastic scattering

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During inelastic scattering processes, significant energy exchange happens. As with elastic phonon scattering also in the inelastic case, the potential arises from energy band deformations caused by atomic vibrations. Optical phonons causing inelastic scattering usually have the energy in the range 30-50 meV, for comparison energies of acoustic phonon are typically less than 1 meV but some might have energy in order of 10 meV. There is significant change in carrier energy during the scattering process. Optical or high-energy acoustic phonons can also cause intervalley or interband scattering, which means that scattering is not limited within single valley.[15]

Electron–electron scattering

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Due to the Pauli exclusion principle, electrons can be considered as non-interacting if their density does not exceed the value 1016~1017 cm−3 or electric field value 103 V/cm. However, significantly above these limits electron–electron scattering starts to dominate. Long range and nonlinearity of the Coulomb potential governing interactions between electrons make these interactions difficult to deal with.[15][16][17]

Relation between mobility and scattering time

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A simple model gives the approximate relation between scattering time (average time between scattering events) and mobility. It is assumed that after each scattering event, the carrier's motion is randomized, so it has zero average velocity. After that, it accelerates uniformly in the electric field, until it scatters again. The resulting average drift mobility is:[20] where q is the elementary charge, m* is the carrier effective mass, and τ is the average scattering time.

If the effective mass is anisotropic (direction-dependent), m* is the effective mass in the direction of the electric field.

Matthiessen's rule

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Normally, more than one source of scattering is present, for example both impurities and lattice phonons. It is normally a very good approximation to combine their influences using "Matthiessen's Rule" (developed from work by Augustus Matthiessen in 1864):

where μ is the actual mobility, is the mobility that the material would have if there was impurity scattering but no other source of scattering, and is the mobility that the material would have if there was lattice phonon scattering but no other source of scattering. Other terms may be added for other scattering sources, for example Matthiessen's rule can also be stated in terms of the scattering time: where τ is the true average scattering time and τimpurities is the scattering time if there was impurity scattering but no other source of scattering, etc.

Matthiessen's rule is an approximation and is not universally valid. This rule is not valid if the factors affecting the mobility depend on each other, because individual scattering probabilities cannot be summed unless they are independent of each other.[19] The average free time of flight of a carrier and therefore the relaxation time is inversely proportional to the scattering probability.[15][16][18] For example, lattice scattering alters the average electron velocity (in the electric-field direction), which in turn alters the tendency to scatter off impurities. There are more complicated formulas that attempt to take these effects into account.[21]

Temperature dependence of mobility

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Typical temperature dependence of mobility[22]
Si Ge GaAs
Electrons ∝T −2.4 ∝T −1.7 ∝T −1.0
Holes ∝T −2.2 ∝T −2.3 ∝T −2.1

With increasing temperature, phonon concentration increases and causes increased scattering. Thus lattice scattering lowers the carrier mobility more and more at higher temperature. Theoretical calculations reveal that the mobility in non-polar semiconductors, such as silicon and germanium, is dominated by acoustic phonon interaction. The resulting mobility is expected to be proportional to T −3/2, while the mobility due to optical phonon scattering only is expected to be proportional to T −1/2. Experimentally, values of the temperature dependence of the mobility in Si, Ge and GaAs are listed in table.[22]

As , where is the scattering cross section for electrons and holes at a scattering center and is a thermal average (Boltzmann statistics) over all electron or hole velocities in the lower conduction band or upper valence band, temperature dependence of the mobility can be determined. In here, the following definition for the scattering cross section is used: number of particles scattered into solid angle dΩ per unit time divided by number of particles per area per time (incident intensity), which comes from classical mechanics. As Boltzmann statistics are valid for semiconductors .

For scattering from acoustic phonons, for temperatures well above Debye temperature, the estimated cross section Σph is determined from the square of the average vibrational amplitude of a phonon to be proportional to T. The scattering from charged defects (ionized donors or acceptors) leads to the cross section . This formula is the scattering cross section for "Rutherford scattering", where a point charge (carrier) moves past another point charge (defect) experiencing Coulomb interaction.

The temperature dependencies of these two scattering mechanism in semiconductors can be determined by combining formulas for τ, Σ and , to be for scattering from acoustic phonons and from charged defects .[16][18]

The effect of ionized impurity scattering, however, decreases with increasing temperature because the average thermal speeds of the carriers are increased.[14] Thus, the carriers spend less time near an ionized impurity as they pass and the scattering effect of the ions is thus reduced.

These two effects operate simultaneously on the carriers through Matthiessen's rule. At lower temperatures, ionized impurity scattering dominates, while at higher temperatures, phonon scattering dominates, and the actual mobility reaches a maximum at an intermediate temperature.

Disordered Semiconductors

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Density of states of a solid possessing a mobility edge, .

While in crystalline materials electrons can be described by wavefunctions extended over the entire solid,[23] this is not the case in systems with appreciable structural disorder, such as polycrystalline or amorphous semiconductors. Anderson suggested that beyond a critical value of structural disorder,[24] electron states would be localized. Localized states are described as being confined to finite region of real space, normalizable, and not contributing to transport. Extended states are spread over the extent of the material, not normalizable, and contribute to transport. Unlike crystalline semiconductors, mobility generally increases with temperature in disordered semiconductors.

Multiple trapping and release

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Mott later developed[25] the concept of a mobility edge. This is an energy , above which electrons undergo a transition from localized to delocalized states. In this description, termed multiple trapping and release, electrons are only able to travel when in extended states, and are constantly being trapped in, and re-released from, the lower energy localized states. Because the probability of an electron being released from a trap depends on its thermal energy, mobility can be described by an Arrhenius relationship in such a system:

Energy band diagram depicting electron transport under multiple trapping and release.

where is a mobility prefactor, is activation energy, is the Boltzmann constant, and is temperature. The activation energy is typically evaluated by measuring mobility as a function of temperature. The Urbach Energy can be used as a proxy for activation energy in some systems.[26]

Variable Range Hopping

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At low temperature, or in system with a large degree of structural disorder (such as fully amorphous systems), electrons cannot access delocalized states. In such a system, electrons can only travel by tunnelling for one site to another, in a process called variable range hopping. In the original theory of variable range hopping, as developed by Mott and Davis,[27] the probability , of an electron hopping from one site , to another site , depends on their separation in space , and their separation in energy .

Here is a prefactor associated with the phonon frequency in the material,[28] and is the wavefunction overlap parameter. The mobility in a system governed by variable range hopping can be shown[27] to be:

where is a mobility prefactor, is a parameter (with dimensions of temperature) that quantifies the width of localized states, and is the dimensionality of the system.

Measurement of semiconductor mobility

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Hall mobility

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Hall effect measurement setup for holes
Hall effect measurement setup for electrons

Carrier mobility is most commonly measured using the Hall effect. The result of the measurement is called the "Hall mobility" (meaning "mobility inferred from a Hall-effect measurement").

Consider a semiconductor sample with a rectangular cross section as shown in the figures, a current is flowing in the x-direction and a magnetic field is applied in the z-direction. The resulting Lorentz force will accelerate the electrons (n-type materials) or holes (p-type materials) in the (−y) direction, according to the right hand rule and set up an electric field ξy. As a result there is a voltage across the sample, which can be measured with a high-impedance voltmeter. This voltage, VH, is called the Hall voltage. VH is negative for n-type material and positive for p-type material.

Mathematically, the Lorentz force acting on a charge q is given by

For electrons:

For holes:

In steady state this force is balanced by the force set up by the Hall voltage, so that there is no net force on the carriers in the y direction. For electrons,

For electrons, the field points in the −y direction, and for holes, it points in the +y direction.

The electron current I is given by . Sub vx into the expression for ξy,

where RHn is the Hall coefficient for electron, and is defined as

Since

Similarly, for holes

From the Hall coefficient, we can obtain the carrier mobility as follows:

Similarly,

Here the value of VHp (Hall voltage), t (sample thickness), I (current) and B (magnetic field) can be measured directly, and the conductivities σn or σp are either known or can be obtained from measuring the resistivity.

Field-effect mobility

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The mobility can also be measured using a field-effect transistor (FET). The result of the measurement is called the "field-effect mobility" (meaning "mobility inferred from a field-effect measurement").

The measurement can work in two ways: From saturation-mode measurements, or linear-region measurements.[29] (See MOSFET for a description of the different modes or regions of operation.)

Using saturation mode

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In this technique,[29] for each fixed gate voltage VGS, the drain-source voltage VDS is increased until the current ID saturates. Next, the square root of this saturated current is plotted against the gate voltage, and the slope msat is measured. Then the mobility is: where L and W are the length and width of the channel and Ci is the gate insulator capacitance per unit area. This equation comes from the approximate equation for a MOSFET in saturation mode: where Vth is the threshold voltage. This approximation ignores the Early effect (channel length modulation), among other things. In practice, this technique may underestimate the true mobility.[30]

Using the linear region

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In this technique,[29] the transistor is operated in the linear region (or "ohmic mode"), where VDS is small and with slope mlin. Then the mobility is: This equation comes from the approximate equation for a MOSFET in the linear region: In practice, this technique may overestimate the true mobility, because if VDS is not small enough and VG is not large enough, the MOSFET may not stay in the linear region.[30]

Optical mobility

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Electron mobility may be determined from non-contact laser photo-reflectance technique measurements. A series of photo-reflectance measurements are made as the sample is stepped through focus. The electron diffusion length and recombination time are determined by a regressive fit to the data. Then the Einstein relation is used to calculate the mobility.[31][32]

Terahertz mobility

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Electron mobility can be calculated from time-resolved terahertz probe measurement.[33][34] Femtosecond laser pulses excite the semiconductor and the resulting photoconductivity is measured using a terahertz probe, which detects changes in the terahertz electric field.[35]

Time resolved microwave conductivity (TRMC)

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A proxy for charge carrier mobility can be evaluated using time-resolved microwave conductivity (TRMC).[36] A pulsed optical laser is used to create electrons and holes in a semiconductor, which are then detected as an increase in photoconductance. With knowledge of the sample absorbance, dimensions, and incident laser fluence, the parameter can be evaluated, where is the carrier generation yield (between 0 and 1), is the electron mobility and is the hole mobility. has the same dimensions as mobility, but carrier type (electron or hole) is obscured.

Doping concentration dependence in heavily-doped silicon

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The charge carriers in semiconductors are electrons and holes. Their numbers are controlled by the concentrations of impurity elements, i.e. doping concentration. Thus doping concentration has great influence on carrier mobility.

While there is considerable scatter in the experimental data, for noncompensated material (no counter doping) for heavily doped substrates (i.e. and up), the mobility in silicon is often characterized by the empirical relationship:[37] where N is the doping concentration (either ND or NA), and Nref and α are fitting parameters. At room temperature, the above equation becomes:

Majority carriers:[38]

Minority carriers:[39]

These equations apply only to silicon, and only under low field.

See also

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References

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Revisions and contributorsEdit on WikipediaRead on Wikipedia
from Grokipedia
Electron mobility, denoted as μn\mu_n, is a fundamental parameter in that quantifies the ease with which electrons drift through a conductor or under the influence of an applied , defined as the ratio of the drift vdv_d to the strength EE, given by μn=vd/E\mu_n = v_d / E. The typical units for electron mobility are cm²/V·s, reflecting its measurement of velocity per unit field. In semiconductors, electron mobility plays a critical role in determining electrical conductivity and device performance, as it directly influences the Jn=nqμnEJ_n = n q \mu_n E, where nn is the concentration and qq is the . For instance, in at , mobility is approximately 1350 cm²/V·s, significantly higher than hole mobility at 480 cm²/V·s, enabling faster electron transport in n-type materials. High electron mobility is essential for applications in high-speed electronics, such as field-effect transistors and solar cells, where materials like exhibit values exceeding 8000 cm²/V·s due to reduced . Electron mobility is primarily limited by scattering mechanisms, including interactions with lattice phonons, ionized impurities, and defects, which reduce the mean free time between collisions and thus lower μn\mu_n. dependence is notable, with mobility decreasing at higher temperatures due to increased , though this effect is less pronounced in heavily doped semiconductors. In two-dimensional materials like , mobilities can reach over 200,000 cm²/V·s at low temperatures, highlighting opportunities for strain engineering and doping to enhance performance in next-generation devices.

Fundamentals

Definition and Units

Electron mobility, denoted as μe\mu_e or simply μ\mu, quantifies the ease with which electrons respond to an applied in a solid material, such as a metal or . It serves as the proportionality constant between the average vdv_d of electrons and the electric field strength EE, formally defined by the relation vd=μeEv_d = \mu_e E. This definition captures the directed motion of charge carriers superimposed on their random thermal motion, providing a key parameter for understanding electrical transport properties. The concept originated in early 20th-century as part of the , a classical theory of conduction in metals proposed by Paul Drude in 1900. In this model, s are treated as a free gas interacting with the ionic lattice, where mobility arises from the balance between accelerating electric forces and collisional scattering. The term "mobility" derives from its representation of the electrons' freedom of movement, distinguishing it from fixed lattice ions. A parallel quantity, hole mobility μh\mu_h, applies to positive charge carriers (holes) in semiconductors, which behave as if moving oppositely to s; in materials like , μh\mu_h is typically about one-third of μe\mu_e due to differences in effective mass and scattering. In the (SI), electron mobility has dimensions of area per volt-second, yielding m²/(V·s), which emerges dimensionally from (m/s) divided by (V/m). For practical applications in physics, the cgs-derived unit cm²/(V·s) is prevalent, where values for electrons in range up to approximately 1400 cm²/(V·s) at , and 1 m²/(V·s) equals 10⁴ cm²/(V·s). This unit choice facilitates comparison with experimental data on carrier transport.

Drift Velocity and Derivation

In the presence of an applied electric field E\mathbf{E}, charge carriers such as electrons in a semiconductor or metal experience a net directed motion superimposed on their random thermal velocities. The thermal velocity arises from the random kinetic energy due to temperature, typically on the order of 10710^7 cm/s for electrons at room temperature, resulting in no net current without a field. In contrast, the drift velocity vd\mathbf{v}_d is the average velocity acquired by the ensemble of electrons in response to the field, directed opposite to E\mathbf{E} for electrons due to their negative charge, and is much smaller in magnitude under typical conditions. This steady-state drift arises from a balance between the accelerating electric force and the decelerating effect of events with lattice vibrations, impurities, or other obstacles. The electric force on an is [e](/page/E!)E-[e](/page/E!) \mathbf{E} (where [e](/page/E!)>0[e](/page/E!) > 0 is the magnitude), imparting an a=([e](/page/E!)/m)E\mathbf{a} = - ([e](/page/E!) / m^*) \mathbf{E}, with mm^* as the effective mass accounting for band structure effects in the solid. introduces a frictional drag, approximated in the relaxation time model as a momentum loss term proportional to the velocity, with relaxation time τ\tau representing the average time between collisions. In equilibrium, this balance yields the drift velocity vd=([e](/page/E!)τ/m)E\mathbf{v}_d = - ([e](/page/E!) \tau / m^*) \mathbf{E}. To derive this formally, start with the semiclassical equation of motion for the average electron velocity v\mathbf{v}: mdvdt=eEmvτ,m^* \frac{d\mathbf{v}}{dt} = -e \mathbf{E} - \frac{m^* \mathbf{v}}{\tau}, where the second term on the right models the exponential decay of momentum toward zero after each scattering event, assuming carriers lose their drift momentum upon collision. For steady-state conditions, dv/dt=0d\mathbf{v}/dt = 0, so eE=mvdτ    vd=eτmE.-e \mathbf{E} = \frac{m^* \mathbf{v}_d}{\tau} \implies \mathbf{v}_d = -\frac{e \tau}{m^*} \mathbf{E}. The electron mobility μn\mu_n is defined as the proportionality constant between vd|\mathbf{v}_d| and EE, giving μn=eτ/m\mu_n = e \tau / m^*, such that vd=μnE\mathbf{v}_d = -\mu_n \mathbf{E}. This derivation relies on the relaxation time approximation from the Boltzmann transport equation, where τ\tau is taken as constant. The model assumes low where the linear response vdEv_d \propto E holds, an isotropic material with uniform , and neglect of or other external influences that could alter carrier trajectories.

Transport Relations

Relation to Current Density

The drift current density arises from the collective motion of electrons under an applied electric field, directly linking microscopic electron mobility to macroscopic charge transport in materials such as semiconductors and metals. When an electric field E\mathbf{E} is applied, electrons experience a drift velocity vd=μE\mathbf{v}_d = -\mu \mathbf{E}, where μ\mu is the electron mobility (positive by convention), leading to a net current due to the imbalance in electron flow. The resulting drift current density for electrons is expressed as Jd=neμE,\mathbf{J}_d = n e \mu \mathbf{E}, where nn is the electron number density and ee is the elementary charge (1.602×10191.602 \times 10^{-19} C). This formula quantifies how efficiently electrons contribute to current flow, with higher mobility yielding greater current for a given field and carrier density. From experimental measurements of current density under controlled conditions, electron mobility can be determined by rearranging the relation: μ=JdneE,\mu = \frac{J_d}{n e E}, assuming isotropic conditions and known nn and EE. This inversion is particularly useful in device characterization, where applied fields generate measurable currents to infer material properties. In the context of Ohm's law, J=σE\mathbf{J} = \sigma \mathbf{E} (with σ\sigma as electrical conductivity), the drift current forms the primary contribution in low-field regimes for extrinsic semiconductors, bridging microscopic carrier dynamics to the material's overall resistive behavior. For anisotropic materials, such as certain or layered semiconductors where electron transport varies by direction due to band structure asymmetry, the scalar mobility is replaced by a second-rank mobility tensor μij\mu_{ij}. The drift current density then takes the vector form Jd,i=nejμijEj,J_{d,i} = n e \sum_j \mu_{ij} E_j, capturing direction-dependent responses; for example, in hexagonal like derivatives, μxx\mu_{xx} may differ significantly from μzz\mu_{zz}. This tensorial description is essential for modeling transport in non-cubic lattices, ensuring accurate predictions of current flow in devices exploiting .

Relation to Electrical Conductivity

In the classical Drude model of electrical conduction in metals, the electrical conductivity σ\sigma is directly related to electron mobility μ\mu through the formula σ=neμ\sigma = n e \mu, where nn is the electron density and ee is the elementary charge. This expression arises from the drift velocity of electrons under an applied electric field, where the average drift speed vd=μEv_d = \mu E leads to a current density J=nevd=neμEJ = n e v_d = n e \mu E, and thus σ=J/E=neμ\sigma = J / E = n e \mu. The model, proposed by Paul Drude in 1900, treats conduction electrons as a classical gas subject to random scattering, with mobility μ=eτ/m\mu = e \tau / m incorporating the relaxation time τ\tau between collisions and the electron mass mm. For semiconductors, the relation extends to account for both electrons and holes: the total conductivity is σ=e(nμe+pμh)\sigma = e (n \mu_e + p \mu_h), where nn and pp are the electron and hole densities, respectively, and μe\mu_e and μh\mu_h are their respective mobilities. In intrinsic semiconductors, n=p=nin = p = n_i, simplifying to σ=eni(μe+μh)\sigma = e n_i (\mu_e + \mu_h), while in extrinsic cases, one carrier type dominates, such as σenμe\sigma \approx e n \mu_e for n-type materials. This formulation highlights how mobility influences charge transport efficiency, with higher μ\mu values yielding greater σ\sigma and correspondingly lower resistivity ρ=1/σ\rho = 1/\sigma, enabling better electrical performance in devices. The dependence on effective mass mm^* further explains variations across materials: in the quantum mechanical refinement, μ1/m\mu \propto 1/m^*, as the effective mass accounts for lattice interactions in band structures, replacing the free electron mass in Drude's original expression./Solar_Basics/C._Semiconductors_and_Solar_Interactions/II._Conduction_in_Semiconductors/4%3A_Carrier_Drift_and_Mobility) Drude's classical approach was refined in 1928 by Arnold Sommerfeld using Fermi-Dirac statistics, which better describes the Pauli exclusion principle for degenerate electron gases in metals, while Felix Bloch's band theory incorporated periodic lattice potentials to validate the conductivity-mobility link quantum mechanically. These advancements preserved the core relation σ=neμ\sigma = n e \mu but provided a more accurate foundation for understanding material-specific behaviors.

Relation to Electron Diffusion

In semiconductors, the diffusion current arises from the random thermal motion of charge carriers, leading to a net flow from regions of higher concentration to lower concentration. For electrons, this is expressed as Jdiff=eDnJ_{\text{diff}} = -e D \nabla n, where ee is the , DD is the diffusion coefficient, and nn is the electron concentration. This component of current is distinct from but contributes to the total transport under non-uniform conditions. The Einstein relation connects the diffusion coefficient DD to the electron mobility μ\mu through D=kTeμD = \frac{kT}{e} \mu, where kk is Boltzmann's constant and TT is the absolute temperature. This relation is derived by considering , where the net current is zero, balancing the drift current due to a built-in and the due to a concentration gradient. In equilibrium, the carrier concentration follows n=n0exp(eUkT)n = n_0 \exp\left(-\frac{eU}{kT}\right), leading to n=ekTnU\nabla n = -\frac{e}{kT} n \nabla U, and setting the total j=eμn(U)eDn=0j = e \mu n (-\nabla U) - e D \nabla n = 0 yields the Einstein relation. Thermoelectric effects, such as the Seebeck effect, rely on this relation, as the SS, which measures the voltage generated by a , incorporates the ratio D/μ=kT/eD / \mu = kT / e to describe the -driven separation of carriers. In non-degenerate semiconductors, SS for electrons is approximately S=ke(EcEFkT+A)S = -\frac{k}{e} \left( \frac{E_c - E_F}{kT} + A \right), where AA accounts for , and the Einstein relation ensures consistency between thermal and mobility in the underlying transport equations. The standard Einstein relation applies to non-degenerate semiconductors, where carrier statistics follow Maxwell-Boltzmann distributions. For degenerate cases, such as heavily doped materials where the enters the conduction band, generalizations incorporate Fermi-Dirac integrals, modifying the relation to D=kTeμF1/2(η)F1/2(η)D = \frac{kT}{e} \mu \frac{\mathcal{F}_{1/2}(\eta)}{\mathcal{F}_{-1/2}(\eta)}, where η\eta is the reduced and Fj\mathcal{F}_j are Fermi-Dirac integrals.

Examples

In Traditional Semiconductors and Metals

In traditional semiconductors, electron mobility values provide a benchmark for carrier transport in established materials used in . For intrinsic at 300 K, the electron mobility is approximately 1400 cm²/(V·s), dominated by in lightly doped conditions. exhibits higher mobility, with μ_e ≈ 3900 cm²/(V·s) in its intrinsic form at room temperature. , a III-V compound , shows even greater values, around 8500–8800 cm²/(V·s) for intrinsic material, enabling faster device speeds compared to . In metals, electron mobility is generally much lower due to the high of conduction electrons (n ≈ 10^{22}–10^{23} cm^{-3}), despite high electrical conductivity. For , a prototypical conductor, μ_e ≈ 43 cm²/(V·s) at , limited primarily by electron-electron and electron-phonon interactions. These mobility values are sensitive to material purity, where impurities introduce that reduces μ_e, and to , with causing a decrease as rises.
MaterialElectron Mobility (cm²/(V·s))Conditions
Silicon (Si)1400Intrinsic, 300 K
Germanium (Ge)3900Intrinsic, room T
GaAs8500–8800Intrinsic
Copper (Cu)43Bulk, room T

In High-Mobility and Emerging Materials

High electron mobility in emerging materials arises primarily from minimized scattering events, such as reduced phonon interactions in two-dimensional (2D) structures and defect-free interfaces achieved through encapsulation or precise engineering techniques. These materials surpass traditional semiconductors by enabling faster charge transport, which is crucial for next-generation devices requiring high-speed performance and mechanical flexibility. In , hexagonal boron (hBN) encapsulation has enabled record room-temperature electron mobilities exceeding 150,000 cm²/(V·s) at carrier densities around 10¹¹ cm⁻², limited mainly by acoustic . This advancement, reported in 2025, stems from proximity screening that suppresses charge inhomogeneities and , preserving the intrinsic ballistic transport properties of graphene. Such high mobilities position graphene for applications in high-electron-mobility transistors (HEMTs) operating at terahertz frequencies. Transition metal dichalcogenides like MoS₂ exhibit electron mobilities of approximately 100–500 cm²/(V·s), significantly enhanced by strain engineering that modulates band structure and reduces intervalley . Studies from 2020–2025 demonstrate that uniaxial tensile strain in flexible substrates can boost on-state currents and mobilities up to 185 cm²/(V·s) in field-effect transistors, leveraging the material's direct bandgap for optoelectronic integration. These properties support scalable 2D HEMTs for low-power, high-frequency . Organic semiconductors, particularly 2D conjugated coordination polymers such as Cu₃BHT formed via covalent bonding of benzenehexathiol linkers, achieve exceptional mobilities approaching 2,000 cm²/(V·s) for hot carriers at , as measured by time-resolved terahertz in 2025 developments. This ultrafast transport, enabled by crystalline lattices with minimal torsional defects, outperforms conventional organic polymers and enables efficient hot-electron harvesting. These materials are ideal for , including wearable sensors and bendable displays, due to their solution-processability and mechanical compliance. GeSn alloys in thin films have demonstrated electron mobilities over 1,500 cm²/(V·s) at (300 ) in strain-relaxed compositions like Ge₀.₈₈Sn₀.₁₂, grown by , with values reaching 6,200 cm²/(V·s) at 50 . The incorporation of tin shifts the conduction band minimum to the Γ-valley, reducing effective mass and , which is vital for photodetectors and lasers in mid-IR applications. These alloys bridge compatibility with direct-bandgap tunability for photonic integrated circuits.

High-Field Behavior

Electric Field Dependence

In the low-electric-field regime, typically below approximately 10 kV/cm in , electron mobility remains constant and independent of the applied strength EE, as the average vdv_d is linearly proportional to EE via vd=μEv_d = \mu E, with scattering rates dominated by equilibrium conditions. At higher fields, non-linear emerges, and the effective mobility μ(E)\mu(E) decreases with increasing EE, transitioning from a constant value to a field-dependent form. This behavior arises because the linear relation breaks down when carrier energies exceed , leading to enhanced . The primary mechanism for this mobility reduction is the hot electron effect, where electrons accelerate in the , gaining far above the lattice (often reaching effective temperatures of several thousand ). These hot electrons interact more strongly with the lattice, particularly through optical emission, which has an threshold of around 40–60 meV in common semiconductors; this increases the rate and limits net acceleration, causing μ(E)\mu(E) to decline. In extreme cases, the dependence can manifest logarithmically due to the exponential tail of the carrier distribution, though the 1/E proportionality often dominates in the saturation approach. Empirical models capture this transition effectively. A common form is μ(E)=μ01+(μ0Evsat)β,\mu(E) = \frac{\mu_0}{1 + \left( \frac{\mu_0 E}{v_\mathrm{sat}} \right)^\beta}, where μ0\mu_0 is the low-field mobility, vsatv_\mathrm{sat} is the saturation (typically 107\sim 10^7 cm/s), and β\beta is an empirical exponent ranging from 1 to 2, reflecting the sharpness of the transition. This model, derived from time-of-flight measurements, fits experimental data across temperatures and fields. Material-specific variations highlight the dependence's sensitivity. In gallium arsenide (GaAs), with μ08500\mu_0 \approx 8500 cm²/V·s, the characteristic field for mobility reduction (Ecvsat/μ01E_c \approx v_\mathrm{sat}/\mu_0 \sim 1 kV/cm) is lower than in silicon (Si), where μ01400\mu_0 \approx 1400 cm²/V·s yields Ec7E_c \sim 7 kV/cm, despite comparable vsatv_\mathrm{sat}; thus, GaAs exhibits a stronger field dependence, with mobility dropping more rapidly at moderate fields due to its higher baseline mobility amplifying hot electron scattering onset. In GaAs, β2\beta \approx 2 often provides a better fit to account for multivalley transfer effects enhancing the non-linearity.

Velocity Saturation

In high electric fields, the drift velocity of electrons in semiconductors approaches a limiting value called the saturation velocity, vsatv_{\text{sat}}, beyond which further increases in field strength do not accelerate the carriers proportionally. This phenomenon arises because energetic electrons ("hot electrons") frequently emit optical phonons to dissipate excess energy, capping the average velocity at around 10710^7 cm/s in typical semiconductors. At these high fields, the conventional low-field mobility μ\mu no longer applies directly, as the drift velocity vdv_d becomes field-independent and equal to vsatv_{\text{sat}}. Instead, an effective mobility μeff=vsat/E\mu_{\text{eff}} = v_{\text{sat}} / E is used, where EE is the , reflecting the sublinear relationship between and field in this regime. This effective mobility decreases inversely with EE, impacting device performance in high-speed . The Gunn effect, discovered in the early 1960s, exemplifies consequences of high-field behavior involving velocity overshoot, where electron velocity initially exceeds expectations before saturating, leading to negative differential resistance in materials like GaAs due to intervalley scattering. Saturation velocities vary by material: approximately 10710^7 cm/s in silicon and GaAs, but higher at about 2×1072 \times 10^7 cm/s in indium phosphide (InP), influencing choices for high-frequency applications.

Scattering Mechanisms

Phonon and Lattice Scattering

Phonon scattering arises from the interaction between electrons and lattice vibrations in , serving as a primary intrinsic limiter of electron mobility in semiconductors. These vibrations manifest as phonons—quantized modes of lattice oscillation—that couple to electrons through electron-phonon interactions, disrupting carrier motion and reducing the . At elevated temperatures, the population of phonons increases according to the Bose-Einstein distribution, intensifying scattering events and thereby decreasing mobility. This mechanism is particularly relevant in high-purity materials where extrinsic scattering is minimized, and it establishes the fundamental temperature-dependent baseline for transport properties. Acoustic scattering, involving low-energy longitudinal and transverse modes, predominates at lower s and is mediated by the deformation potential, which quantifies the band-edge shift due to lattice dilation or shear. This interaction is an elastic process, conserving energy while changing momentum, as the energy is much smaller than typical carrier energies. Within the Boltzmann transport equation framework, the mobility limited by acoustic s scales as μacT3/2\mu_{ac} \propto T^{-3/2}, stemming from the linear increase in occupation number with and the energy dependence of the scattering rate. For instance, in materials like or , this leads to a characteristic decrease in mobility as rises from cryogenic levels. Optical phonon scattering becomes increasingly dominant at higher temperatures, where the higher-energy optical modes (typically 10-50 meV) facilitate inelastic processes that absorb or emit discrete quanta. This occurs in both polar and non-polar forms: polar optical , prevalent in ionic semiconductors like GaAs, arises from the long-range Coulombic Fröhlich interaction due to relative ionic displacements, while non-polar optical relies on short-range deformation potential similar to acoustic modes but involving optical frequencies. The dependence varies; polar optical often yields an exponential form for mobility at low temperatures due to the activation over the energy barrier, transitioning to power-law behaviors such as μopT1/2\mu_{op} \propto T^{-1/2} or T3/2T^{-3/2} in the high-temperature , whereas non-polar optical more consistently follows μopT1/2\mu_{op} \propto T^{-1/2}. These processes limit mobility more severely above , as the occupation factor nqkT/ωopn_q \approx kT / \hbar \omega_{op} grows, enhancing rates. The relaxation time τph\tau_{ph} for phonon scattering, derived from solutions to the Boltzmann transport equation, encapsulates these interactions; for acoustic phonons, τph1/(kT)\tau_{ph} \propto 1/(kT) in the equipartition regime, reflecting the proportionality of the scattering rate to the thermal phonon density. This temperature scaling directly underlies the observed mobility dependences, as mobility μeτ/m\mu \propto e \langle \tau \rangle / m^*, where τ\langle \tau \rangle averages over the carrier distribution. At 300 K, a typical reference temperature for room-temperature device operation, phonon scattering sets intrinsic mobilities on the order of 10310^3 to 10410^4 cm²/V·s in conventional semiconductors like Si or GaN, though values vary with material-specific coupling strengths and phonon spectra.

Ionized Impurity Scattering

Ionized impurity scattering arises from the electrostatic interaction between conduction s and charged dopant ions in semiconductors, becoming the dominant mobility-limiting mechanism in moderately to heavily doped materials at low s. Unlike , which increases with , ionized impurity scattering decreases as rises due to enhanced electron velocities and screening effects. This process is particularly relevant in n-type or p-type semiconductors where dopants are ionized, creating fixed positive or negative charges that deflect electrons via long-range forces. The is a Rutherford-like , modified by the semiconductor's constant ε, which reduces the potential strength compared to . The bare potential between an and an ionized impurity of charge Ze is V(r) = \frac{Z e^2}{4 \pi \epsilon_0 \epsilon r}, where ε_0 is the , but this is screened by surrounding free carriers and lattice polarization. The Brooks-Herring model provides a widely used quantum-mechanical treatment of this , assuming a Debye-Hückel screened potential of the form V(r)=Ze24πϵ0ϵrexp(rλD),V(r) = \frac{Z e^2}{4 \pi \epsilon_0 \epsilon r} \exp\left(-\frac{r}{\lambda_D}\right), where λ_D is the Debye screening length. This model derives the scattering rate using Born approximation, leading to an ionized impurity mobility μ_{ii} that scales as μ_{ii} \propto \frac{T^{3/2}}{N_i \ln(1 + \gamma)}, where N_i is the ionized impurity density, T is temperature, and γ involves the ratio of electron energy to screening energy; the logarithmic term accounts for small-angle scattering dominance. The T^{3/2} dependence reflects faster averaging over the potential at higher thermal velocities. This approach is applicable for low to moderate doping where screening is effective. For higher impurity densities, where the Debye screening assumption breaks down due to overlapping impurity potentials, the Conwell-Weisskopf approximation offers an alternative. It employs a hard-sphere cutoff at a distance related to the average impurity spacing, rather than exponential screening, yielding a mobility μ_{ii} \propto \frac{T^{3/2}}{N_i \ln(1 + \beta^2) - \beta^2}, where β incorporates screening parameters. This formulation better captures scattering in dense, degenerate cases but overestimates rates at low densities compared to Brooks-Herring. Screening effects are central to both models, governed by the Debye length λ_D = \sqrt{\frac{\epsilon_0 \epsilon k_B T}{e^2 n}}, where n is the free carrier density and k_B is Boltzmann's constant. This length scale represents the distance over which the electric field of an impurity is shielded by mobile charges; λ_D increases with temperature (∝ √T) and decreases with carrier density (∝ 1/√n), leading to weaker screening and potentially stronger long-range scattering at low T or low n. In doped semiconductors, typical λ_D values range from 1-10 nm at room temperature for n ~ 10^{17}-10^{19} cm^{-3}, significantly influencing mobility in devices like transistors.

Interface, Alloy, and Other Scattering

Interface scattering, particularly scattering, significantly limits electron mobility in devices like MOSFETs where electrons are confined near material interfaces. In such structures, fluctuations in the interface plane perturb the electron wavefunction, leading to relaxation. The mobility limited by scattering, μ_sr, is inversely proportional to the product of the square of the root-mean-square roughness height Δ and the correlation length Λ of the roughness, expressed as μ_sr ∝ 1/(Δ² Λ). This dependence arises because larger Δ increases the perturbation strength, while longer Λ affects the spatial spectrum of events, both enhancing the scattering rate. For typical MOSFETs, Δ values around 0.2-0.5 nm and Λ ≈ 1-2 nm can reduce effective mobility by orders of magnitude compared to bulk values, emphasizing the need for atomically smooth interfaces in advanced devices. Alloy scattering becomes prominent in compound semiconductors with mixed compositions, such as ternary alloys like Al_x Ga_{1-x} As, where random fluctuations in atomic arrangement create potential barriers for electrons. These compositional disorder potentials scatter electrons via short-range interactions, with the scattering potential often modeled using the virtual crystal approximation. The alloy-limited mobility μ_alloy scales inversely with the disorder x(1-x), which peaks at x=0.5 for maximum alloying effect, as μ_alloy ∝ 1/[x(1-x)]. In p-type Al_x Ga_{1-x} As with doping around 2×10^{17} cm^{-3}, this mechanism can reduce hole mobility from approximately 150 cm²/V·s at x=0 to below 90 cm²/V·s at x=0.5, highlighting its role in limiting transport in heterostructures like HEMTs. The strength of alloy scattering is characterized by a potential on the order of 0.5 eV, influencing device performance in and high-speed transistors. Piezoelectric scattering occurs in non-centrosymmetric crystals like GaAs, where lattice strain from acoustic s generates electric fields that couple to electrons via the piezoelectric effect. This mechanism is particularly relevant at low s and moderate carrier densities, where it competes with deformation potential . The piezoelectric-limited mobility μ_pz follows a dependence of μ_pz ∝ T^{-1/2}, as the rate increases with thermal population while the matrix element scales with wavevector. In bulk GaAs, this contributes to overall mobility reductions at cryogenic s, with theoretical models showing continued decline unlike saturation in other processes; experimental validations confirm this behavior in high-purity samples. For two-dimensional electron gases in GaAs heterostructures, piezoelectric can dominate acoustic limited transport, affecting high-mobility applications. Other scattering mechanisms, such as electron-electron interactions, further influence mobility through inelastic processes like and plasma oscillations. In semiconductors, electron-electron scattering redistributes momentum within the carrier ensemble but relaxes it via phonon-assisted events or collective plasma excitations, particularly in degenerate systems. The resulting mobility μ_ee scales as μ_ee ∝ T^{3/2} / n, where n is carrier density, reflecting increased collision rates with and screening effects at higher densities. In GaAs at carrier concentrations around 10^{16} cm^{-3}, this can reduce total mobility by up to 10% at 80 K, especially when combined with polar optical or impurity scattering, though it is less dominant than phonon mechanisms at . These rates are computed using , which provides the transition probability 1/τ = (2π/ℏ) |M|^2 g(E_f), where |M| is the matrix element, g(E_f) the density of final states at the , linking microscopic interactions to macroscopic relaxation times τ that determine mobility via μ = e τ / m^*.

Temperature and Material Dependencies

Temperature Dependence

Electron mobility in semiconductors exhibits a pronounced dependence governed by the interplay of mechanisms. In pure or lightly doped materials, where acoustic dominates, mobility decreases with increasing according to the power-law relation μTm\mu \propto T^{-m} with mm typically between 1.5 and 2.5, reflecting enhanced lattice vibrations that impede carrier motion. In contrast, heavily doped semiconductors under impurity-limited conditions show mobility increasing with , approximately μT1.5\mu \propto T^{1.5}, as improves carrier screening of ionized impurities. At low temperatures (below ~100 ), ionized impurity prevails, causing mobility to rise sharply with due to higher carrier velocities and screening effects that reduce the effective rate, following μT3/2\mu \propto T^{3/2} in the Brooks-Herring model. As rises (above ~200 ), overtakes, leading to a decline in mobility as carriers interact more frequently with s. This transition manifests in experimental log-log plots of mobility versus , where samples display an initial upward slope (impurity regime) followed by a downward trend ( regime), with peak mobilities around 500-1500 cm²/V·s at intermediate temperatures (e.g., 100-200 ) for doping levels of 10^{16}-10^{18} cm^{-3}. Similar behavior is observed in , where log-log plots reveal phonon-limited mobility scaling as μT1.5\mu \propto T^{-1.5} at higher temperatures, yielding values from ~35,000 cm²/V·s at 77 to ~8500 cm²/V·s at 300 in lightly doped samples. In emerging two-dimensional materials like and MoS₂, recent studies (2020-2025) indicate a weaker dependence, attributed to reduced and suppressed in low dimensions, with mobilities often remaining above 1000 cm²/V·s up to 400 under phonon-limited conditions.

Matthiessen's Rule

Matthiessen's rule originated in the 1860s from the work of Augustus Matthiessen, who studied the electrical conductivities of pure metals and alloys to understand how impurities and temperature affect resistivity. In its original form for metals, the rule posits that the total electrical resistivity ρtotal\rho_{\text{total}} is the sum of a temperature-independent residual component due to impurities ρresidual\rho_{\text{residual}} and a temperature-dependent ideal component ρideal(T)\rho_{\text{ideal}}(T), such that ρtotal(T)=ρresidual+ρideal(T)\rho_{\text{total}}(T) = \rho_{\text{residual}} + \rho_{\text{ideal}}(T). This empirical relation arose from Matthiessen's extensive measurements on over 200 alloys, aiming to establish standards for electrical resistance amid contemporary rivalries in and . The rule was later extended to semiconductors in the context of , where electron mobility μ\mu inversely relates to resistivity via ρ=m/(ne2τ)\rho = m / (n e^2 \tau) and μ=eτ/m\mu = e \tau / m^* (with τ\tau the relaxation time, mm^* the effective mass, nn the carrier density, and ee the charge). For constant carrier density, the additivity of resistivities translates to the reciprocal additivity of mobilities from independent mechanisms. In semiconductors, Matthiessen's rule is expressed as 1μtotal=i1μi,\frac{1}{\mu_{\text{total}}} = \sum_i \frac{1}{\mu_i}, where μi\mu_i is the mobility limited by the ii-th scattering mechanism, such as phonons or impurities. Equivalently, in terms of relaxation times for uncorrelated processes, 1τtotal=i1τi.\frac{1}{\tau_{\text{total}}} = \sum_i \frac{1}{\tau_i}. The rule holds under the assumption that scattering mechanisms are independent and do not interfere, allowing simple superposition of their rates. However, it breaks down when scatterers exhibit strong correlations or interactions, such as in or where competing mechanisms alter individual rates. For instance, in Ga0.47_{0.47}In0.53_{0.53}As , deviations up to 20% arise due to the failure of reciprocal additivity in the presence of . This framework finds practical application in analyzing experimental electron mobility data, particularly by decomposing total mobility into contributions from distinct mechanisms like and ionized impurity . In Ga1x_{1-x}Alx_xAs alloys, for example, the rule enables accurate fits to Hall mobility measurements across compositions at , isolating lattice and impurity effects with errors below 10%. Such separations aid in material optimization for devices like transistors, though corrections are needed at low temperatures where deviations increase.

Doping Concentration Effects

In lightly doped semiconductors, electron mobility remains relatively high and is dominated by lattice scattering, but as doping concentration (N_d) increases into the moderate range (typically 10^{16} to 10^{18} cm^{-3}), ionized impurity scattering from donor ions causes mobility to decrease approximately as 1/N_d, reflecting the enhanced interactions between carriers and fixed charges. This dependence arises from the quantum-mechanical treatment of scattering probabilities in the Brooks-Herring approximation, where the relaxation time scales inversely with the impurity density under screened conditions. In heavily doped , electron mobility (μ_e) drops significantly to values below 100 cm²/(V·s) for N_d exceeding 10^{19} cm^{-3}, primarily due to degeneracy effects where the penetrates into the conduction band and increased from clustering. Degeneracy alters carrier distribution, confining electrons to higher energies near the (E_F), leading to enhanced rates; in this regime, mobility scales approximately with degeneracy factors and density, as derived in dopant-specific models. Empirical models, such as that developed by et al., provide fits for these behaviors in across concentrations up to 10^{20} cm^{-3} and temperatures from 250 to 500 , capturing the transition from non-degenerate to degenerate transport. Recent advancements in nanoscale devices, such as FinFETs, reveal further mobility reductions due to high local doping concentrations in channels or extensions, exacerbating and quantum confinement effects beyond bulk models; for instance, in ultra-scaled nanosheet FETs with N_d ~10^{19} cm^{-3}, effective μ_e can fall 20-30% lower than bulk predictions owing to these integrated mechanisms. Updated empirical fits incorporating nanoscale , building on Arora's framework, have been proposed in the 2020s to account for these deviations in device simulations.

Mobility in Disordered Systems

Multiple Trapping and Release

In amorphous semiconductors, electron mobility is frequently governed by the multiple trapping and release () model, in which carriers excited into extended states above the mobility edge experience repeated trapping in localized tail states and subsequent thermal release back into the extended states. This mechanism dominates transport in materials lacking long-range order, such as hydrogenated (a-Si:H), where the localized states arise from structural disorder in the band tails. The MTR framework, originally formulated to explain dispersive time-of-flight experiments, assumes rapid trapping compared to transport in extended states, with release rates determined by thermal activation over energy barriers associated with trap depths. The effective mobility μeff\mu_\mathrm{eff} under this model is reduced from the untrapped extended-state mobility μ0\mu_0 by the fraction of time carriers spend in delocalized states, expressed as μeff=μ0fc\mu_\mathrm{eff} = \mu_0 f_c, where fcf_c represents the proportion of carriers in the conduction band. For a distribution of trap depths, fcf_c is influenced by the and profile of localized states, typically leading to a thermally activated behavior where μeffexp(Et/kT)\mu_\mathrm{eff} \propto \exp(-E_t / kT), with EtE_t denoting the characteristic trap depth and kTkT the . This activation arises because deeper traps require higher temperatures for efficient release, limiting the average carrier velocity under an applied field. In practical applications, such as a-Si:H-based solar cells, the MTR model accounts for the observed low effective electron mobilities, typically ranging from 1 to 10 cm²/(V·s) at 300 K, which constrain device efficiency but enable cost-effective thin-film fabrication. These values reflect the balance between extended-state and in tail states with depths around 0.1–0.2 eV, as verified through drift-mobility measurements.

Variable Range

In highly disordered systems, such as amorphous semiconductors or doped organics, electron transport at low temperatures occurs primarily through phonon-assisted hopping between localized states near the , rather than extended-state conduction. This (VRH) mechanism arises because electrons are strongly localized due to disorder, forming a tail of states in the bandgap. To minimize the required for hopping, electrons do not jump to nearest-neighbor sites but instead select optimal paths that balance spatial distance and energy mismatch, effectively trading off (more available distant states) against energy barriers for thermally activated transitions. Nevill F. Mott developed the foundational model for VRH in , assuming a constant near the and phonon-assisted transitions governed by Miller-Abrahams rates. In this framework, the conductivity follows σ=σ0exp[(T0T)1/4]\sigma = \sigma_0 \exp\left[ -\left( \frac{T_0}{T} \right)^{1/4} \right], where T0=18kBN(EF)ξ3T_0 = \frac{18}{k_B N(E_F) \xi^3} incorporates the N(EF)N(E_F) at the EFE_F, the localization radius ξ\xi, and Boltzmann's constant kBk_B. Since carrier density nn remains roughly constant at low temperatures in these insulating regimes, the electron mobility μ\mu scales as μσne1Texp[(T0T)1/4]\mu \propto \frac{\sigma}{n e} \propto \frac{1}{T} \exp\left[ -\left( \frac{T_0}{T} \right)^{1/4} \right], reflecting the temperature-dependent hopping probability and factors. This T1/4T^{-1/4} exponent is characteristic of three-dimensional systems and has been widely observed in experiments on amorphous materials. Subsequent refinements by Efros and Shklovskii in 1975 accounted for electron-electron interactions, which deplete states near the due to the Coulomb gap—a soft gap of width Δe2/κξ\Delta \approx e^2 / \kappa \xi in the , where κ\kappa is the constant. In interacting systems, this leads to a modified VRH conductivity σ=σ0exp[(TEST)1/2]\sigma = \sigma_0 \exp\left[ -\left( \frac{T_{ES}}{T} \right)^{1/2} \right], with TES=e24πϵ0κkBξT_{ES} = \frac{e^2}{4\pi \epsilon_0 \kappa k_B \xi}, and a corresponding mobility μexp[(TEST)1/2]/T1/2\mu \propto \exp\left[ -\left( \frac{T_{ES}}{T} \right)^{1/2} \right] / T^{1/2}. The T1/2T^{-1/2} form dominates at sufficiently low temperatures where the Coulomb interaction energy exceeds the Mott hopping energy scale, often observed as a crossover from Mott to Efros-Shklovskii behavior in doped samples. In practical examples, VRH governs transport in doped , where disorder from molecular packing localizes carriers, yielding electron mobilities below 10310^{-3} cm²/(V·s) at cryogenic temperatures (e.g., below 100 ). Similarly, in chalcogenide glasses like Ge-Sb-S alloys, low-temperature conduction follows Mott VRH across wide ranges (10–300 ), with mobilities in the 10410^{-4}10310^{-3} cm²/(V·s) regime due to extended hopping networks in the localized state tail. These systems highlight VRH's role in enabling finite, albeit low, conductivity in deeply insulating materials without delocalization.

Measurement Techniques

Hall Effect Mobility

The Hall effect provides a direct method to measure electron mobility in semiconductors by exploiting the on charge carriers in a . When a current II flows through a sample of thickness tt in the presence of a BB, a transverse Hall voltage VHV_H develops across the sample, given by VH=IBnetV_H = \frac{I B}{n e t} for electrons, where nn is the carrier density and ee is the . The Hall coefficient RHR_H, defined as RH=VHtIBR_H = \frac{V_H t}{I B}, equals 1ne-\frac{1}{n e} for electrons, allowing independent determination of nn from the measurement. Hall mobility μH\mu_H is then calculated as μH=RHσ\mu_H = |R_H| \sigma, where σ\sigma is the electrical conductivity obtained from separate resistivity measurements. For practical implementation, especially in thin-film or arbitrary-shaped samples, the Van der Pauw geometry is widely used, employing four ohmic contacts placed at the periphery of the sample. The procedure involves measuring the longitudinal voltage VxV_x across one pair of contacts under current II (with B=0B = 0) to determine , followed by applying BB and measuring the transverse Hall voltage VHV_H across the orthogonal pair, often with field and current reversals to eliminate offsets like thermoelectric voltages. The Hall mobility is then approximated as μH=VHVxB\mu_H = \frac{V_H}{V_x B}, with corrections applied for non-ideal geometries using Van der Pauw equations to ensure accuracy. This method requires no precise knowledge of sample dimensions beyond thickness for bulk interpretation. A key advantage of Hall effect measurements is the ability to separately extract carrier density nn and mobility μH\mu_H, providing insights into both doping and mechanisms without assumptions about material uniformity. However, limitations arise in inhomogeneous samples, where spatial variations in carrier density or thickness can distort the Hall voltage, leading to erroneous μH\mu_H values that do not represent average bulk properties. In uniform semiconductors with high-quality ohmic contacts and controlled conditions, the technique achieves accuracy of approximately ±5%\pm 5\% for mobility determination.

Field-Effect Mobility

Field-effect mobility (μFE\mu_{FE}) is a key parameter extracted from the drain current-gate voltage (IDI_D-VGV_G) characteristics of field-effect transistors (FETs), reflecting carrier transport in the channel under gate modulation. This method is widely used in MOSFETs and thin-film transistors to evaluate device performance, as it directly relates to transconductance and output conductance in different operating regimes. The extraction relies on the gradual channel approximation, which assumes a uniform potential drop along the channel for long-channel devices. In the linear region, applicable at low drain-source voltages (VDVGVTV_D \ll V_G - V_T) where the channel exhibits ohmic , μFE\mu_{FE} is derived from the : μFE=LWCoxVDIDVG\mu_{FE} = \frac{L}{W C_{ox} V_D} \frac{\partial I_D}{\partial V_G} Here, LL and WW are the channel length and width, CoxC_{ox} is the per unit area, and ID/VG\partial I_D / \partial V_G is obtained from the slope of the IDI_D-VGV_G curve at constant low VDV_D. This formula assumes constant mobility and neglects short-channel effects, providing a low-field measure of transport. In the saturation regime, at higher VD>VGVTV_D > V_G - V_T where the channel pinches off near the drain, μFE\mu_{FE} is extracted using the saturation current: μFE=2LWCoxID,sat(VGVT)2\mu_{FE} = \frac{2 L}{W C_{ox}} \frac{I_{D,sat}}{(V_G - V_T)^2} This expression stems from the square-law model for long-channel devices but accounts for velocity saturation in shorter channels, where carriers reach a maximum velocity (vsatv_{sat}) under high lateral fields, reducing the apparent μFE\mu_{FE} compared to low-field values. The linear regime probes uniform low-field conditions, while saturation reveals high-field limitations, with velocity saturation becoming prominent in sub-micron channels. Accurate extraction in saturation requires corrections for series contact resistance, which can overestimate μFE\mu_{FE} by up to a factor of 2 if unaddressed; methods such as the transfer length model or analysis of channel-length dependence are employed to isolate intrinsic channel mobility from contact contributions. In MOSFETs, μFE\mu_{FE} for electrons typically ranges from 200 to 600 cm²/V·s in the linear regime, but values are often 40-50% lower than Hall mobilities due to Coulomb scattering from interface traps at the Si/SiO₂ boundary, which overestimate inversion charge in capacitance-based corrections. Similarly, in 2D material FETs like MoS₂ or WSe₂, μFE\mu_{FE} (e.g., 10-100 cm²/V·s) is interface-limited by substrate and dielectric scattering, frequently much lower than bulk or Hall-measured mobilities in exfoliated flakes. These discrepancies highlight μFE\mu_{FE}'s sensitivity to surface effects in gated structures.

Advanced Optical and Time-Resolved Methods

Advanced optical and time-resolved methods provide non-contact approaches to probe electron mobility by exciting carriers with light pulses and monitoring their transient response, offering insights into intrinsic transport properties without interference. These techniques are particularly valuable for studying ultrafast dynamics in materials where traditional electrical methods are challenging due to contacts or thin geometries. The time-of-flight (TOF) method involves photoexcitation of charge carriers near one in a sample under an applied , followed by measurement of the transit time t\transt_{\trans} for carriers to reach the opposite , yielding mobility via μ=d2Vt\trans\mu = \frac{d^2}{V t_{\trans}}, where dd is the sample thickness and VV is the applied voltage. This technique, pioneered for amorphous semiconductors, reveals drift mobilities by analyzing decay signals, distinguishing between dispersive and non-dispersive transport regimes. TOF is widely used for , where it quantifies field-dependent mobilities on the order of 1–10 cm²/(V·s). Terahertz (THz) employs broadband THz pulses to probe carrier dynamics, fitting transmission or reflection spectra to the to extract mobility as μ=eτm\mu = \frac{e \tau}{m^*}, with ee the charge, τ\tau the relaxation time, and mm^* the effective . Time-resolved variants, such as optical-pump THz-probe, track photoinduced changes in conductivity on timescales, enabling separation of intraband processes. This approach has been instrumental in characterizing semiconductors and nanostructures, providing frequency-dependent mobility values up to thousands of cm²/(V·s) in high-quality samples. Time-resolved microwave conductivity (TRMC) measures the change in reflectivity or absorption following a photoexcitation , quantifying transient Δσ\Delta \sigma to derive an effective mobility Σμ\TRMC=ΔσeΔn\Sigma \mu_{\TRMC} = \frac{\Delta \sigma}{e \Delta n}, where ee is the and Δn\Delta n the photoinduced carrier density. Developed for studying charge generation and recombination in photoconductive materials, TRMC is sensitive to one-dimensional or anisotropic , yielding sum mobilities Σμ\Sigma \mu that reflect the product of quantum efficiency and mobility. It excels in assessing bulk properties of powdered or thin-film samples without geometric constraints. These methods offer key advantages for investigating thin films, , and two-dimensional (2D) materials, where contact fabrication can introduce artifacts or limit accessibility. In organics and perovskites, they enable mobility assessments in non-ideal morphologies, often revealing higher intrinsic values than electrical techniques due to avoidance of trapping at interfaces. Recent applications (2020–2025) in 2D materials, such as and transition metal dichalcogenides, have demonstrated contactless mobilities exceeding 10^5 cm²/(V·s) via THz , highlighting ballistic and enabling optimization for high-speed electronics.

References

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