Deep-level transient spectroscopy (DLTS) is a well-established technique for characterizing defects in bulk semiconductors, providing information on defect energy levels, concentrations, and capture cross-sections. However, its application to low-dimensional systems such as quantum wells, nanowires, and two-dimensional materials presents unique challenges due to their reduced active volumes, high surface-to-volume ratios, and the prevalence of surface-dominated defect states. Adapting DLTS for these materials requires careful modifications to the methodology while maintaining the core principles of the technique.

In bulk semiconductors, DLTS relies on the analysis of capacitance transients induced by majority or minority carrier emission from deep-level defects. The standard implementation assumes a uniform depletion region and a defect concentration that is negligible compared to the doping density. These assumptions break down in low-dimensional systems, where the active region may be confined to a few nanometers, and surface or interface states can dominate the electrical response.

For quantum wells, the primary challenge lies in the limited thickness of the active region, which complicates the formation of a conventional depletion zone. Traditional DLTS measurements require a sufficiently large depletion width to generate a measurable capacitance transient, but in quantum wells, the well itself may be thinner than the depletion region of the surrounding barrier material. One solution is to use heterostructure designs where the quantum well is embedded within a wider-bandgap matrix, allowing the depletion region to extend into the barriers while still probing defects within the well. Differential DLTS can also be employed, where the signal from the quantum well is isolated by subtracting the response of the barrier material. Additionally, optical DLTS (ODLTS) can be useful, as it enables selective excitation of carriers within the well, bypassing the need for a deep depletion region.

Nanowires introduce further complications due to their one-dimensional geometry and high surface area. The conventional parallel-plate capacitance measurement is ill-suited for nanowires, as their small cross-sectional area results in extremely low absolute capacitance values. To address this, specialized geometries such as gate-all-around field-effect transistors (FETs) can be used, where the nanowire serves as the channel and the gate modulates the depletion region. Transient measurements are then performed on the channel conductance rather than the capacitance, a method sometimes referred to as conductance DLTS (G-DLTS). This approach allows for the extraction of defect parameters by analyzing the time-dependent conductance recovery after a filling pulse. Another challenge in nanowires is the high density of surface states, which can obscure bulk defects. Surface passivation techniques, such as atomic layer deposition of dielectric coatings, can help mitigate this issue by reducing the contribution of surface traps to the transient signal.

Two-dimensional materials, such as transition metal dichalcogenides (TMDCs) and graphene, present a different set of challenges. Their atomically thin nature means that the active volume is minimal, and defects are often localized at the surface or interface with substrates or dielectrics. Conventional DLTS struggles with these materials due to the lack of a significant depletion region and the dominance of interface states. One adaptation involves using FET structures with the 2D material as the channel, similar to the nanowire case, but with additional considerations for the electrostatic gating efficiency. The transient response of the drain current can be analyzed to extract defect parameters, though care must be taken to account for the strong influence of charge traps in the surrounding dielectric. Another approach is photo-DLTS, where optical excitation generates carriers directly in the 2D material, and the resulting photocurrent transients are analyzed. This method avoids the need for a traditional depletion region and can provide insights into both bulk and interface defects.

A common issue across all low-dimensional systems is the limited active volume, which reduces the absolute signal magnitude and increases the relative contribution of noise. To improve sensitivity, lock-in amplification techniques can be employed, or the measurements can be performed at lower temperatures to slow carrier emission rates and enhance the signal-to-noise ratio. Additionally, pulsed filling techniques must be carefully optimized to ensure that the defect states are adequately populated without inducing artifacts from high injection conditions.

The interpretation of DLTS data in low-dimensional systems also requires adjustments. In bulk materials, the standard analysis assumes a uniform defect distribution and a well-defined depletion width, but in nanostructures, defects may be localized at interfaces or surfaces, and the electric field can vary significantly over short distances. Numerical simulations of the electrostatic potential and carrier dynamics are often necessary to accurately model the transient response and extract defect parameters. For example, in quantum wells, the confinement potential can alter the emission kinetics of carriers from defect states, requiring corrections to the standard Arrhenius analysis used in DLTS.

Despite these challenges, adapted DLTS techniques have successfully characterized defects in low-dimensional materials. In quantum wells, DLTS has been used to identify deep levels associated with impurities or alloy disorder, providing insights into non-radiative recombination pathways. For nanowires, G-DLTS has revealed the presence of bulk and surface traps that influence carrier mobility and recombination lifetimes. In 2D materials, transient conductance measurements have uncovered defect states at the interface with dielectrics, which are critical for understanding device hysteresis and instability.

The continued development of DLTS adaptations for low-dimensional materials will be essential for advancing their application in electronics and optoelectronics. By refining measurement techniques and analysis methods, researchers can overcome the limitations imposed by reduced dimensionality and surface effects, enabling a deeper understanding of defect physics in these systems. Future directions may include the integration of in situ microscopy techniques to correlate electrical measurements with structural defects or the use of machine learning to automate the analysis of complex transient data.

In summary, while traditional DLTS must be significantly modified for quantum wells, nanowires, and 2D materials, these adaptations enable valuable insights into defect behavior that are critical for optimizing material performance. The key lies in tailoring the measurement geometry, excitation methods, and data analysis to account for the unique properties of low-dimensional systems while preserving the fundamental principles of DLTS.