Photoinduced Band-Edge Carrier Traps

• Photoinduced band-edge carrier traps are defect-induced states near semiconductor band edges that capture electrons or holes under illumination, altering recombination processes.
• Advanced methods like TR-ARPES, DLTS, and time-resolved photoluminescence quantify trap energies, densities, and kinetics to evaluate carrier dynamics.
• Controlling these traps via passivation, encapsulation, and device engineering is crucial for enhancing photoluminescence efficiency and overall optoelectronic performance.

Photoinduced band-edge carrier traps are localized electronic states—typically associated with structural defects, impurities, vacancies, or interface states—in the forbidden gap near the conduction or valence band edges of semiconductors. Upon illumination, these traps dynamically capture photoexcited electrons or holes, altering carrier dynamics, modifying recombination pathways, and governing optoelectronic device performance. Their energetic position, cross section, density, and trapping–detrapping kinetics determine the balance between radiative and non-radiative recombination, directly impacting photoluminescence efficiencies, carrier lifetimes, quantum yields, and photovoltaic or photoresponse characteristics across a wide range of materials systems.

1. Physical Origins and Microscopic Nature

Band-edge carrier traps are introduced via a variety of structural or chemical perturbations:

• Vacancy and Impurity Defects: Shallow traps in ZnO arise from native donors or hydrogen-related centers (activation energies 11–23 meV), while deep mid-gap states in MoSe₂, WSe₂, and PdSe₂ are primarily due to chalcogen vacancies or substitutional oxygen/oxide species, e.g. Se–O, WOₓ, or O@Mo–vacancy complexes (Ton-That et al., 2015, Chen et al., 2017, Crimmann et al., 4 Jan 2026, Abdul-Aziz et al., 29 Oct 2025).
• Surface and Interface States: High surface-to-volume ratio nanostructures, such as Si nanowires and perovskite nanocrystals, present a dense spectrum of surface trap states—arising from dangling bonds, undercoordinated atoms, or adsorbed species—that can be tuned via functionalization or passivation (Dan, 2014, Ye et al., 2024).
• Complexes in Alloys: In boron-doped GaN, complex vacancy pairs (VN–VGa) act as deep recombination centers, their charge states controlled via shallow-donor-mediated photoionization (Kierdaszuk et al., 2023).
• Controlled Photochemical Processes: Exposing TMD monolayers (e.g., WSe₂) to ambient oxygen and light leads to the photoinduced formation of oxide and vacancy-related traps that modulate photoluminescence lifetimes and intensities (Crimmann et al., 4 Jan 2026).

These traps can either localize at the band edge (shallow traps), in the mid-gap (deep traps), or be distributed as a tail of states (Urbach tail, band tails). Their chemical and spatial distribution defines capture rates and cross sections.

2. Experimental Detection and Characterization

A variety of experimental techniques have been developed to resolve, quantify, and distinguish band-edge carrier traps:

• Time- and Angle-Resolved Photoemission Spectroscopy (TR-ARPES): Enables real-time mapping of band-edge dynamics, relaxation, and the formation of Wannier excitons, and can correlate the lack of self-trapping to the absence of additional band replicas or anomalous k-space broadening (Qi et al., 16 Aug 2025, Abdul-Aziz et al., 29 Oct 2025).
• Deep Level Transient Spectroscopy (DLTS & Q-DLTS): Cyclically fills and empties traps in depletion regions, measuring emission rates and deducing activation energies and densities (e.g., 11, 22, 23 meV in ZnO) (Ton-That et al., 2015).
• Carrier-Resolved Photo-Hall Effect: Utilizes varying light intensity and temperature to map the photo-Hall conductivity σ_PH versus electrical conductivity σ, extracting trap density N_t and energy E_t directly from hyperbola-shaped curves, efficiently determining full carrier and trap properties without junction-based perturbations (Gunawan et al., 2024).
• Time-Resolved Photoluminescence (TRPL), Ultrafast Pump-Probe, and Pump-Push Photocurrent Spectroscopies: Track the population and release dynamics of traps, separating radiative and trap-limited nonradiative decays with sub-picosecond resolution. Optical de-trapping directly measures trap energies and coupling (Bakulin et al., 2013, Chen et al., 2017, Ye et al., 2024).
• Electron Paramagnetic Resonance (EPR): Detects metastable, photoinduced paramagnetic center populations, such as the VN–VGa complex in BGaN, and tracks their annihilation via Arrhenius fits (Kierdaszuk et al., 2023).
• Optoelectronic Transient Response and Single-Defect Measurements: Surface-trap densities down to single-trap limits are accessed via silicon nanowire conductance transients and single-NV-center photonic gating (Dan, 2014, Lozovoi et al., 2023).

These methods, often combined with ab initio calculations (DFT, perturbation theory), provide quantitative measures of activation barriers, cross sections, densities (ranging from ∼10⁹–10¹² cm⁻² for nanowire states up to 10¹⁷ cm⁻³ for colloidal QD films), and emission rates.

3. Kinetic Models and Trap Dynamics

Trap-filling and release are governed by coupled rate equations, typically framed in the generalized Shockley–Read–Hall (SRH) formalism:

• Population Dynamics:

$$\frac{d n}{dt} = -C_n n [N_T - n_t] + e_n n_t - R_{rad}(n,p)$$

$\frac{d n_t}{dt} = C_n n [N_T - n_t] - e_n n_t$

where n is band carrier population, n_t is trap occupancy, C_n is the capture coefficient, e_n is the emission rate, and R_rad covers radiative decay (Chen et al., 2017).

• Trap-Assisted Recombination:

For distributed or multi-level states, each band of traps can have occupancy and recombination rates tracked discretely within numerical simulation, as implemented in tools like AMPS (Liu et al., 2019).

• Hot Carrier and Sequential Trapping:

In halide perovskite nanocrystals, coupled populations for hot (n_H), cold (n_C), and trapped (n_T) electrons incorporate both phonon-mediated and trap-mediated relaxation rates, capturing multi-ps dynamics and the competition between phonon-bottleneck effects and trap short-circuiting (Ye et al., 2024).

• Simple Two-Rate Lifetimes:

In TMD monolayers, the lifetime τ and steady-state photoluminescence I are simply related by:

$\tau = \frac{1}{k_r + k_{nr}}$

$I = k_r N_0 \tau$

where k_r is the radiative decay rate and k_{nr} (trap-induced non-radiative) includes both intrinsic and trap density-dependent components (Crimmann et al., 4 Jan 2026).

4. Quantitative Parameters and Physical Impact

A summary of experimentally determined parameters for photoinduced band-edge traps in key material systems:

Material/System	Trap Energy (E_t)	Trap Density (N_t)	Capture Cross Section (σ)	References
ZnO (bulk, H-doped)	11, 22, 23 meV	10¹⁵–10¹⁶ cm⁻³	≈4×10⁻¹⁷ cm²	(Ton-That et al., 2015)
WSe₂ monolayer	midgap, band edge	up to 10¹¹ cm⁻² (laser-induced)	~10⁻⁵ ns⁻¹ (rate per trap)	(Crimmann et al., 4 Jan 2026)
PbS QD films	0.2 (shallow), 0.3–0.5 (deep) eV	10¹⁶–10¹⁷ cm⁻³	(mid-IR detrap, semi-quantitative)	(Bakulin et al., 2013)
MoSe₂ (O@Mo vacancy)	≈0.8 eV below CBM	10¹⁷ cm⁻³	≈2×10⁻¹⁷ cm²	(Chen et al., 2017)
Si nanowire (surface)	−	10⁹–10¹² cm⁻²/eV (energy-resolved)	−	(Dan, 2014)
CsPbBr₃ NCs	0.67 eV below CBM (deep)	10¹⁶–10¹⁷ cm⁻³	k_{H→T} ~0.3–1 ps⁻¹	(Ye et al., 2024)
PdSe₂ (vacancy trap)	0.2–0.4 eV below CBM	10¹²–10¹³ cm⁻²	≈10⁻¹⁵ cm²	(Abdul-Aziz et al., 29 Oct 2025)
BGaN (shallow donors)	30 meV below CBM	10¹⁷–10¹⁸ cm⁻³	≲10⁻¹⁸ cm² (photo-EPR limit)	(Kierdaszuk et al., 2023)

The rates of capture, emission, and recombination define photoluminescence efficiencies, hot-carrier cooling times (modifying hot-phonon bottleneck and Auger recombination), transient surface photovoltages, response times in photodetectors, and voltage losses in photovoltaics.

5. Material- and Device-Level Consequences

• Carrier Lifetimes and Photoluminescence Quantum Yield (PLQY): In WSe₂, photoinduced traps dramatically shorten the excited-state lifetime (from ∼3.2 ns to ∼0.8 ns under laser exposure), with the PL intensity directly proportional to τ across hundreds of samples, confirming overwhelmingly trap-limited emission (Crimmann et al., 4 Jan 2026).
• Competing Radiative and Nonradiative Channels: Even shallow traps (e.g., ZnO, 11–23 meV) can dynamically store/release carriers, modulating excitonic emission with temperature. In gas-sensing or temperature-tunable optoelectronics, these effects may be exploited or need to be passivated (Ton-That et al., 2015).
• Solar Cells and Photodetectors: Trap-assisted recombination reduces open-circuit voltage and fill factor, with deep traps acting as non-radiative centers and distributed band tails degrading charge collection. Accurate device models, such as AMPS, explicitly include graded band-edge forces and localized trap spectra, and highlight the need for chemical and interface optimization to control trap populations (Liu et al., 2019).
• Hot Carrier Devices: In halide perovskite nanocrystals, traps dictate the fate of hot carriers by providing ultrafast, non-radiative cooling pathways that bypass the hot phonon bottleneck, strongly constraining hot-carrier extraction for next-generation photonic devices. Only “defect tolerant” materials with shallow traps (e.g., CsPbI₃) preserve slow hot-carrier cooling (Ye et al., 2024).
• Surface Potential and Band Bending: In layered quantum materials (PdSe₂), trap filling induces transient surface photovoltages (SPV) up to 67 meV, with lifetimes ∼60 ps governed by the trapping and recombination kinetics at vacancy sites (Abdul-Aziz et al., 29 Oct 2025).

6. Mitigation, Engineering, and Measurement Strategies

Effective control of photoinduced band-edge carrier traps is central to high-performance optoelectronics:

• Passivation: Surface functionalization and chemical passivation (e.g., shorter bifunctional ligands in QDs, superacid or thiol treatment in TMDs) reduce the density of undercoordinated and oxide-related traps (Bakulin et al., 2013, Crimmann et al., 4 Jan 2026).
• Encapsulation and Environmental Control: Exposure to air and light creates new traps in sensitive materials (e.g., WSe₂, halide perovskites). Encapsulation or inert-atmosphere processing suppresses photooxidation and maintains intrinsic PLQY (Crimmann et al., 4 Jan 2026, Ye et al., 2024).
• Device Design: Grading of doping and band-offsets, interface engineering using ultrathin dielectrics, and spatial distribution of traps can shift their impact to less critical regions, as modeled quantitatively in multi-level drift–diffusion simulators (Liu et al., 2019).
• Advanced Measurement: Carrier-resolved photo-Hall and single-defect measurement techniques resolve trap energies and densities in operando, enabling targeted optimization without junction-induced artifacts (Gunawan et al., 2024, Lozovoi et al., 2023, Dan, 2014).

7. Perspectives and Outstanding Challenges

While the suppression of photoinduced band-edge carrier trapping is essential for maximizing device efficiency, their deterministic engineering—either to facilitate desired recombination (e.g., single-photon sources) or to dynamically control emission properties—remains an active field. There is ongoing need to:

• Precisely distinguish between intrinsic and extrinsic traps (self-trapping vs. defect-mediated).
• Develop reliable, non-invasive, high-throughput measurement techniques, including photo-Hall hyperbola fitting and nanoscale-sensitivity optoelectronic probes.
• Extend defect-tolerance concepts from band-edge to hot-carrier and multi-exciton regimes, informing the synthesis of new quantum-confined and hybrid materials.
• Incorporate comprehensive trap modeling—encompassing spatial distribution, energetic spread, and correlated occupation—into device simulations for predictive design.

Band-edge carrier traps under photoexcitation thus play a dual role: as a fundamental limitation for radiative efficiency and as a tunable degree of freedom in advanced photonics, quantum technologies, and energy conversion systems (Qi et al., 16 Aug 2025, Ton-That et al., 2015, Kierdaszuk et al., 2023, Chen et al., 2017, Dan, 2014, Bakulin et al., 2013, Lozovoi et al., 2023, Abdul-Aziz et al., 29 Oct 2025, Gunawan et al., 2024, Crimmann et al., 4 Jan 2026, Liu et al., 2019, Ye et al., 2024).