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Variable Range Hopping Transport

Updated 24 January 2026
  • Variable range hopping is a charge transport mechanism in disordered systems that relies on phonon-assisted tunneling over variable distances to overcome spatial decay and energy barriers.
  • The model optimizes hopping paths by balancing wavefunction overlap decay with thermally activated energy differences, leading to characteristic temperature-dependent conductivity laws.
  • This framework underpins experimental analyses in amorphous oxides, granular superconductors, and low-dimensional systems, providing practical estimates of localization length and density of states.

The variable range hopping (VRH) mechanism describes charge or quasiparticle transport in strongly localized, disordered systems, where electronic states near the Fermi level are not extended but spatially localized. Instead of simple thermally activated nearest-neighbor hopping, VRH involves phonon-assisted tunneling over variable spatial ranges to energetically favorable sites, optimizing the trade-off between decay of wavefunction overlap and thermally accessible energy differences. This framework underlies non-metallic conduction in a wide array of materials including amorphous oxides, granular superconductors (via vortex hopping), disordered two-dimensional electron systems, topological insulators, and functionalized graphene. The VRH phenomenology encompasses classic Mott VRH, Coulomb-gap-modified Efros–Shklovskii VRH, extensions to AC fields, spin-selective hopping, and recent approaches that model crossover between Arrhenius and Mott regimes using integral formulations.

1. Theoretical Foundations of Variable Range Hopping

The foundational result of VRH theory, established by N.F. Mott, asserts that in strongly disordered insulators at sufficiently low temperatures, the electrical conductivity takes the form

σ(T)=σ0exp ⁣[(T0/T)1/(d+1)]\sigma(T) = \sigma_0\,\exp\!\left[-(T_0/T)^{1/(d+1)}\right]

where:

  • σ0\sigma_0 is a weakly TT-dependent prefactor,
  • T0T_0 is the characteristic (Mott) temperature,
  • dd is the effective spatial dimension,
  • TT is temperature.

The exponent $1/(d+1)$ directly encodes system dimensionality: $1/4$ for 3D, $1/3$ for 2D, and $1/2$ for 1D. For dd-dimensional systems with exponential localization length ξ\xi and density of states at the Fermi level N(EF)N(E_F), the characteristic temperature is (Jenderka et al., 2013, Shukla et al., 2021, Annadi et al., 2013)

T0=βkBN(EF)ξdT_0 = \frac{\beta}{k_B N(E_F) \xi^d}

with β\beta a numerical constant (e.g., $21.2$ in 3D, $13.8$ in 2D). This result arises from optimizing between the spatial decay of wavefunction overlaps exp(R/ξ)\sim \exp(-R/\xi) and the thermal activation probability for an energy difference εexp(Δε/kBT)\varepsilon \sim \exp(-\Delta\varepsilon/k_B T), under the constraint that a target state is available within a combined spatial and energy shell of volume approximately one (i.e., N(EF)RdΔε1N(E_F) R^d \Delta\varepsilon \sim 1) (Faggionato, 2018).

In systems where Coulomb interactions open a soft gap in the density of states near the Fermi level, the Efros–Shklovskii (ES) VRH regime replaces the Mott exponent with $1/2$ in all dimensions: σ(T)exp ⁣[(TES/T)1/2]\sigma(T) \sim \exp\!\left[-(T_{ES}/T)^{1/2}\right] with TESe2/(4πεε0kBξ)T_{ES} \sim e^2/(4\pi\varepsilon\varepsilon_0 k_B \xi), as demonstrated in FIB-fabricated Bi2_2Se3_3 (Bhattacharyya et al., 2017) and lithiated MoS2_2 (Papadopoulos et al., 2018).

2. Microscopic Mechanism: Hop Optimization and Dimensional Dependence

VRH emerges from the competition between two exponentially suppressive factors:

  • Spatial decay: Overlap between two localized states separated by distance Rexp(2R/ξ)R \sim \exp(-2R/\xi),
  • Energy mismatch: Phonon absorption/emission probability for intersite energy difference Δε\Delta\varepsilon, exp(Δε/kBT)\exp(-\Delta\varepsilon/k_B T).

The optimal hopping length RoptR_{\text{opt}} minimizes the sum of exponents [2R/ξ]+[Δε/(kBT)][2R/\xi] + [\Delta\varepsilon/(k_B T)] subject to the percolation constraint. The optimization yields hopping distances that grow as temperature decreases, enabling transport through rare low-resistance paths (Faggionato, 2018).

A general result is: Ropt(T)(ξkBTN(EF))1/(d+1)R_{\text{opt}}(T) \sim \left(\frac{\xi}{k_B T N(E_F)}\right)^{1/(d+1)} and the associated optimal energy

Δεopt(T)1N(EF)Roptd\Delta\varepsilon_{\text{opt}}(T) \sim \frac{1}{N(E_F) R_{\text{opt}}^d}

These relationships have been experimentally extracted by direct fits of resistivity or conductivity versus temperature and have been validated in granular superconducting films (vortex VRH)(Percher et al., 2017), magnetic Zintl semiconductors EuIn2_2P2_2 (Tolinski et al., 2024), and oxide interfaces (Annadi et al., 2013).

3. Extensions, Crossover Regimes, and Integral VRH Models

Standard VRH with discrete Arrhenius and Mott regimes neglects the smooth crossover observed in real materials. The Integral Variable Range Hopping (IVRH) model (Qin et al., 15 Jan 2026) replaces ad hoc regime boundaries by a single physically motivated integral over all possible hopping distances: σ(T)=AR0exp ⁣[2αRβD0V(R)kBT]dR\sigma(T) = A \int_{R_0}^\infty \exp\!\left[ -2\alpha R - \frac{\beta}{D_0 V(R) k_B T} \right] dR where V(R)V(R) encodes the system geometry (e.g., πR2\pi R^2 for 2D, 4π3R3\frac{4\pi}{3} R^3 for 3D) and the energy penalty is dynamically determined by the effective density of accessible states in each volume. The IVRH integral reduces to Arrhenius or Mott limits at high or low temperatures, respectively, with smooth interpolation in the crossover regime. Monte Carlo simulation validates this form and reveals reduced parameter variance and robust extraction of physically meaningful quantities such as the localization length (Qin et al., 15 Jan 2026).

4. Experimental Signatures and Parameter Extraction

The operational test of VRH is the observation of linear dependence in plots of lnρ\ln \rho (or lnσ\ln \sigma) versus T1/(d+1)T^{-1/(d+1)} over extended temperature ranges. Extracted slopes yield T0T_0, which, with an independent estimate of N(EF)N(E_F), provides the localization length ξ\xi (Jenderka et al., 2013, Shukla et al., 2021, Rudra et al., 2019). Representative values are:

  • T0105108T_0 \sim 10^5-10^8 K in transition-metal oxides and disordered thin films,
  • ξ0.13\xi \sim 0.1-3 nm, in agreement with interatomic or nanoscale distances.

The dimensionality is generally established by the value of the characteristic exponent, with 3D ($1/4$) found in thick granular films and bulk nanocrystalline samples (Jenderka et al., 2013, Shukla et al., 2021, Rudra et al., 2019), 2D ($1/3$) at oxide interfaces and nanowires (Annadi et al., 2013, Bhattacharyya et al., 2017), and 1D ($1/2$) in EFros–Shklovskii and strictly one-dimensional systems (Faggionato, 2018, Faggionato et al., 2016, Sano et al., 2024). Deviations from the Mott exponent signal, for example, power-law localized impurity states rather than exponential (as established for graphene with resonance-state impurities) (Liang et al., 2012).

Other transport measurements provide corroborating evidence:

  • Magnetotransport: Negative magnetoresistance scaling as T1T^{-1} or quadratic in field, characteristic of interference effects in VRH (Annadi et al., 2013, Tolinski et al., 2024).
  • Impedance spectroscopy: Crossover between Arrhenius and VRH in Nyquist plots, dielectric relaxation, and modulus formalisms (Rudra et al., 2019).
  • Spectroscopic signatures: Raman phonon lifetimes and FWHM anomalies correlating with crossover into the VRH regime (Tolinski et al., 2024).
  • AC response and scaling: Universal scaling of σ(ω)/σ(0)=F(ω/[Tσ(0)])\sigma(\omega) / \sigma(0) = F(\omega / [T \sigma(0)]) as illustrated by dynamical Monte Carlo (Bergli et al., 2014).

5. Modifications: Coulomb Gap, Power-law Localization, and Memory Effects

Efros–Shklovskii VRH modifies the Mott scenario by considering the suppression of the density of states near the Fermi level, leading to the characteristic exponent $1/2$ and the appearance of the interaction energy scale in TEST_{ES}. This has been experimentally confirmed in topological insulator nanowires (Bhattacharyya et al., 2017) and strongly disordered MoS2_2 (Papadopoulos et al., 2018).

In systems where localized states decay as a power law rather than exponentially—such as adatom-doped graphene—the temperature dependence of conductivity becomes a pure power law, σ(T)Tη\sigma(T) \sim T^{\eta}, where η\eta is directly related to the decay exponent (Liang et al., 2012).

Memory effects, specifically dynamical correlations in occupation numbers of localized sites, introduce subleading exponential corrections to the Mott law through a two-color percolation problem; this effect subtly alters the prefactor and can manifest in experimental deviations from VRH fits (Agam et al., 2014).

6. Generalizations: Vortex Hopping, Spin Selectivity, and Field-Driven Transport

The VRH paradigm extends to non-electronic quasiparticle transport. In disordered superconducting films, vortex dynamics analogously undergo 2D Mott VRH among random pinning sites, leading to a resistance minimum below which hyperbolic cooling reveals VRH-type exponential temperature dependence (Percher et al., 2017).

Spin-dependent VRH arises in chiral systems such as DNA, where spin–phonon coupling mediated by chiral phonon vorticity yields universal T3/2T^{-3/2} laws for spin polarization in 1D VRH chains (Sano et al., 2024).

Under strong external fields, 1D Mott VRH becomes a mathematically tractable nonequilibrium random walk with rigorously established criteria for ballisticity and sub-ballisticity; sharp transitions in the drift velocity as a function of field bias and environmental disorder are demonstrated (Faggionato et al., 2016, Faggionato, 2018).

7. Thermoelectric, Nonlinear, and Multi-parameter Extensions

Thermoelectric response in VRH systems is determined by the interplay of the spectral conductivity and the statistical distribution of hopping parameters. Recent works show that allowing for an energy-dependent localization length ξ(ε)\xi(\varepsilon) consistent with Anderson localization scaling theory modifies the Seebeck coefficient's low-temperature scaling to S(T)Td/(d+1)S(T) \sim T^{d/(d+1)}, contrasting with the noninteracting prediction S(T)T(d1)/(d+1)S(T) \sim T^{(d-1)/(d+1)} (Yamamoto et al., 2022).

Nonlinear transport in VRH, arising from high applied fields or current densities, modifies the hopping statistics and requires integral or advanced percolation approaches to capture transitions from regime-to-regime and parameter extraction (Qin et al., 15 Jan 2026).

Table: VRH Parameters in Model Systems

System/Material Dim. T0T_0 (K) ξ\xi (nm) Characteristic Regime Reference
Na2_2IrO3_3 thin films 3D 10510^5-10810^8 0.74–4.7 Mott VRH (exp 1/4) (Jenderka et al., 2013)
Iron pyrite (FeS2_2) films 3D 10510^5-10610^6 0.9–2.7 Mott VRH, NNH crossover (Shukla et al., 2021)
Bi2_2Se3_3 nanowires 2D 10110^1-10310^3 0.5–20 Efros–Shklovskii (ES) VRH (exp 1/2) (Bhattacharyya et al., 2017)
Pr2_2ZnMnO6_6 electrodes 3D 5.4×1075.4\times10^7 0.1 NNH (high T)/Mott VRH (low T) (Rudra et al., 2019)
NdAlO3_3/SrTiO3_3 interface 2D not stated not stated Mott VRH (exp 1/3), negative MR (Annadi et al., 2013)
DNA (spin VRH) 1D not stated 1–5 Chiral phonon–induced, exp 1/2 (Sano et al., 2024)

References

  • "Mott Variable Range Hopping and Weak Antilocalization Effect in Heteroepitaxial Na₂IrO₃ Thin Films" (Jenderka et al., 2013)
  • "Universal scaling form of AC response in variable range hopping" (Bergli et al., 2014)
  • "Evidence of robust 2D transport and Efros-Shklovskii variable range hopping in disordered topological insulator (Bi2Se3) nanowires" (Bhattacharyya et al., 2017)
  • "Charge Carrier Transport in Iron Pyrite Thin Films: Disorder Induced Variable Range Hopping" (Shukla et al., 2021)
  • "Vortex Variable Range Hopping in a Conventional Superconducting Film" (Percher et al., 2017)
  • "Evidence of variable range hopping in the Zintl phase EuIn2P2" (Tolinski et al., 2024)
  • "Existence of nearest-neighbor and variable range hopping in Pr₂ZnMnO₆ oxygen-intercalated pseudocapacitor electrode" (Rudra et al., 2019)
  • "Efros-Shklovskii variable range hopping and nonlinear transport in 1T/1T^{\prime}-MoS2_{2}" (Papadopoulos et al., 2018)
  • "Memory effects, two color percolation, and the temperature dependence of Mott's variable range hopping" (Agam et al., 2014)
  • "Evolution of variable range hopping in strongly localized two dimensional electron gas at NdAlO3/SrTiO3 (100) heterointerfaces" (Annadi et al., 2013)
  • "Thermoelectric Effect in Mott Variable-Range Hopping" (Yamamoto et al., 2022)
  • "Integral Variable Range Hopping for Modeling Electrical Transport in Disordered Systems" (Qin et al., 15 Jan 2026)
  • "The velocity of 1D Mott variable range hopping with external field" (Faggionato et al., 2016)
  • "Chirality-induced spin selectivity by variable-range hopping along DNA double helix" (Sano et al., 2024)
  • "1D Mott variable-range hopping with external field" (Faggionato, 2018)
  • "Impurity State and Variable Range Hopping Conduction in Graphene" (Liang et al., 2012)
  • "Poole-Frenkel effect and Variable-Range Hopping conduction in metal / YBCO resistive switching devices" (Schulman et al., 2015)
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