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All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Ultrafast Oxygen Conduction in Sillén Oxychlorides

Oxygen ion conductors are crucial for enhancing the efficiency of various clean energy technologies, including fuel cells, solid oxide air batteries, electrolyzers, membranes, sensors, and more. In this study, a structure-similarity analysis of ≈62k oxygen-containing compounds identified the MBi 2 O 4 X (M = rare-earth element, X = halogen element) family as promising candidates for fast oxygen transport. Among these, LaBi 2 O 4 Cl is found as an ultrafast oxygen conductor with an ultralow migration barrier of 0.1 eV based on ab initio studies. Its 2D layered structure, featuring a “triple fluorite” layer, supports diffusion of both oxygen vacancies and interstitials. In addition to vacancy diffusion with a 0.1 eV barrier, ab initio studies show interstitial diffusion exhibits a modest barrier of 0.6–0.8 eV. Frenkel pairs are found to be the dominant defects in intrinsic LaBi 2 O 4 Cl, facilitating significant vacancy-mediated oxygen diffusion at elevated temperatures. With 2.8% oxygen vacancies, LaBi 2 O 4 Cl is predicted to achieve a conductivity of 0.3 S/cm at 25 °C in a single crystal. Experimental synthesis and characterization of polycrystalline LaBi 2 O 4 Cl and Sr-doped LaBi 2 O 4 Cl revealed conductivity exceeding that of YSZ and LSGM below 400 °C, with lower activation energies, achieving a total conductivity of 0.1−0.2 mS/cm at 300 °C. Here, while these results confirm its potential of fast oxygen transport, we suggest further experimental optimization of LaBi 2 O 4 Cl, including aliovalent doping and microstructure refinement, could significantly enhance its performance, facilitating fast oxygen conduction approaching room temperature.

Defects↗
DOE OSTI2025

The Crucial Role of Vacancy Concentration in Enabling Superatomic Diffusion in Lithium Intermetallics

Anode-free solid-state Li batteries promise significant increases in energy densities compared to current commercial batteries that rely on liquid electrolytes. Major challenges persist in controlling morphological evolution during the plating and stripping of lithium metal at the anode current collector. Elemental additives that alloy with lithium have been found to modify the plating and stripping behavior of lithium. Many alloying elements form intermetallics with lithium and the mobility of Li through these intermetallics is believed to have an important effect on morphological evolution. This study shows that Li transport coefficients through intermetallics span a wide range in values, with the B32 LiAl intermetallic predicted to have a Li tracer diffusion coefficient as high as 10 –6 cm 2 /s at room temperature, which is 8 orders of magnitude larger than that of isostructural B32 LiZn. This work demonstrates the crucial role of vacancy concentration in controlling the mobility of Li atoms through intermetallics. While the migration barriers for Li-vacancy exchanges in both LiAl and LiZn are remarkably low, the superatomic conductivity in LiAl is shown to arise from the unique electronic structure of the B32 LiAl compound, which favors high concentrations of vacancies.

25 ENERGY STORAGE↗
DOE OSTI2025

Defect-Mediated Diffusion Pathways in Spodumene Accelerate Lithium Transport

Lithium extraction from naturally occurring α-spodumene is hindered by poor lithium diffusivity, necessitating high-temperature phase transformation to a low-density β polymorph. Although β spodumene exhibits up to 5 orders of magnitude higher lithium-ion diffusivity, both phases have diffusion activation energies between 0.8 and 1 eV, indicating that polymorph density is not the controlling factor over diffusivity. We show that aluminum vacancies facilitate lithium-ion diffusion in α-spodumene by reducing the migration barrier from 2.4 to 0.9 eV. Bond valence site energy and nudged elastic band calculations show a new lithium local minimum site which promotes a one-dimensional percolation network by reducing the lithium intersite distance from 4.5 Å to 2.9 Å. However, aluminum vacancies are energetically unfavorable to percolate through the whole structure, resulting in very low net lithium diffusivity and highlighting the critical role of nonstoichiometric defects in facilitating lithium transport in rigid aluminosilicate structures.

Chemical structure↗
DOE OSTI2025

Stationary Oxygen Vacancy Construction toward a Superior-Performance Ultrahigh Nickel Single-Crystal Cathode

Oxygen vacancies exert a complex and profound influence on the layered cathodes, especially those with ultrahigh nickel content. They can facilitate lithium-ion transport and enhance electronic conductivity, while aggressive oxygen vacancy formation causes structural degradation and electrolyte decomposition. Herein, taking ultrahigh nickel single-crystal LiNi 0.92 Co 0.06 Mn 0.02 O 2 (SC-Ni92) as a model material, we propose a pinning strategy to harness the benefits of oxygen vacancies while mitigating their detrimental effects. Through a carefully controlled thermal process, both oxygen vacancies and pinning atoms are successfully introduced into the surface region. The resulting anchored oxygen vacancies, capitalizing on their inherent advantages, improve conductivity and lithium-ion diffusion. Simultaneously, the neighboring pinning atoms effectively increase the migration barrier and suppress the adverse effects of these vacancies, including electrolyte decomposition and structural degradation during long-term electrochemical cycling. Consequently, oxygen vacancy-anchored single-crystal LiNi 0.92 Co 0.06 Mn 0.02 O 2 (SC-Ni92-OV) demonstrates significantly improved high-voltage electrochemical performance, with 86.16% capacity retention after 200 cycles at 4.6 V and 1 C in a half-cell and 90.71% after 300 cycles at 4.5 V and 1 C in a full cell. Furthermore, this study not only provides valuable insights into the chemistry of oxygen vacancy but also introduces a viable strategy for leveraging oxygen vacancies to achieve stable high-voltage performance in ultrahigh nickel single-crystal cathodes.

defects in solids↗
DOE OSTI2025

The Dynamical Role of Optical Phonons and Sublattice Screening in a Solid-State Ion Conductor

Solid-state electrolytes (SSEs) require ionic conductivities that are competitive with liquid electrolytes to realize applications in all-solid-state batteries. Although candidate SSEs have been discovered, the underlying mechanisms enabling superionic conduction (>1 mS cm –1 ) remain elusive. In particular, the role of ultrafast lattice dynamics in mediating ion migration, which involves couplings between ions, phonons, and electrons, is rarely explored experimentally at their corresponding time scales. To investigate the complex contributions of coupled lattice dynamics on ion migration, we modulate the charge density occupations within the crystal framework and then measure the time-resolved change in impedance on picosecond time scales for a candidate SSE, Li 0.5 La 0.5 TiO 3 (LLTO). Upon perturbation, we observe enhanced ion migration at ultrafast time scales. The respective transients match the time scales of optical and acoustic phonon vibrations, suggesting their involvement in ion migration. We further computationally evaluate the effect of a charge transfer from the O 2p to the Ti 3d band on the electronic and physical structure of LLTO. We hypothesize that the charge-transfer excitation distorts the TiO 6 polyhedra by altering the local charge density occupancy of the hopping site at the migration pathway saddle point, thereby causing a reduction in the migration barrier for the Li + hop. We rule out the contribution of photogenerated electron carriers and laser heating. Overall, our investigation introduces a new spectroscopic tool to probe fundamental ion hopping mechanisms transiently at ultrafast time scales, which has previously only been achieved in a time-averaged manner or solely via computational methods.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Systematic softening in universal machine learning interatomic potentials

Machine learning interatomic potentials (MLIPs) have introduced a new paradigm for atomic simulations. Recent advancements have led to universal MLIPs (uMLIPs) that are pre-trained on diverse datasets, providing opportunities for universal force fields and foundational machine learning models. However, their performance in extrapolating to out-of-distribution complex atomic environments remains unclear. In this study, we highlight a consistent potential energy surface (PES) softening effect in three uMLIPs: M3GNet, CHGNet, and MACE-MP-0, which is characterized by energy and force underprediction in atomic-modeling benchmarks including surfaces, defects, solid-solution energetics, ion migration barriers, phonon vibration modes, and general high-energy states. The PES softening behavior originates primarily from the systematically underpredicted PES curvature, which derives from the biased sampling of near-equilibrium atomic arrangements in uMLIP pre-training datasets. Our findings suggest that a considerable fraction of uMLIP errors are highly systematic, and can therefore be efficiently corrected. We argue for the importance of a comprehensive materials dataset with improved PES sampling for next-generation foundational MLIPs.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Prediction of vacancy defect diffusion paths in high entropy alloys via machine learning on molecular dynamics data

Identifying the diffusion path of point defects is a critical step in understanding their evolution and the mechanisms of related phenomena. Defect diffusion occurs at small length and time scales, with impacts on material properties that may continue to evolve over ns to μs, ms, and the continuum scale (s, min, etc., and cm, m, etc.). The time scale accessible to molecular dynamics (MD) simulations is limited by small step sizes, typically in the fs range. Thus, surrogate models of MD simulations through machine learning (ML)-based algorithms are of great interest, especially for complex systems such as high entropy alloys (HEAs). In this work, dynamics governing vacancy migration in HEA were approximated with graph convolutional network (GCN) models as ansatzes for kinetic Monte Carlo (KMC) rate catalogs. Network design considered that diffusion in crystalline solids generally depends on interactions between defects and their immediate neighbor atoms. Graphs represented the vacancy surroundings, MD-generated trajectories provided training and comparison datasets, and unsupervised GCN models approximated interatomic dynamics governing vacancy migration in HEAs as ansatzes for KMC. A proof-of-concept model trained on MD data for the Fe, Ni, Cr, Co, and Cu HEA environment was used with two different neighbor interactions to assess the feasibility of training a GCN to predict vacancy defect transition rates in the HEA environment. The resulting setup rapidly generated MD-formatted synthetic trajectories based on dynamics learned from the MD training set, with a time acceleration of roughly two orders of magnitude and a similar diffusion coefficient to MD observations. Additionally, Nudged Elastic Band (NEB) calculations were performed on randomly generated FeNiCrCoCu HEA structures to determine vacancy migration barriers across nearest-neighbor sites. Transition probabilities for each jump, categorized by atomic type, were extracted from these calculations. NEB-based and GCN-based approaches led to similar outcomes.

Reimer, C↗
DOE OSTI2025

Defect modeling in semiconductors: the role of first principles simulations and machine learning

Abstract Point defects in semiconductors dictate their electronic and optical properties. Vacancies, interstitials, substitutional defects, and defect complexes can form in the semiconductor lattice and significantly impact its performance in applications such as solar absorption, light emission, electronics, and catalysis. Understanding the nature and energetics of point defects is essential for the design and optimization of next-generation semiconductor technologies. Here, we provide a comprehensive overview of the current state of research on point defects in semiconductors, focusing on the application of density functional theory (DFT) and machine learning (ML) in accelerating the prediction and understanding of defect properties. DFT has been instrumental in accurately calculating defect formation energies, charge transition levels, and other defect-related properties such as carrier recombination rates and lifetimes, and ion migration barriers. ML techniques, particularly neural networks, have emerged as powerful tools for enabling rapid prediction of defect properties at DFT-accuracy in order to overcome the expense of using large supercells and advanced functionals. We begin this article with a discussion of different types of point defects and complexes, their impact on semiconductor properties, and the experimental and DFT approaches typically used for their characterization. Through multiple case studies, we explore how DFT has been successfully applied to understand defect behavior across a variety of semiconductors, and how ML approaches integrated with DFT can efficiently predict defect properties and facilitate the discovery of new materials with tailored defect behavior. Overall, the advent of ‘DFT+ML’ promises to drive advancements in semiconductor technology, catalysis, and renewable energy applications, paving the way for the development of high-performance semiconductors which are defect-tolerant or have desirable dopability.

Rahman, Md Habibur (ORCID:000000027705984X)↗
DOE OSTI2025

Toward machine learning interatomic potentials for modeling uranium mononitride

Uranium mononitride (UN) is a promising accident-tolerant fuel because of its high fissile density and high thermal conductivity. In this study, we developed the first machine learning interatomic potentials for reliable atomic-scale modeling of UN at finite temperatures. We constructed a training set using density functional theory (DFT) calculations that was enriched through an active learning procedure, and two neural network potentials were generated. Both potentials successfully reproduce key thermophysical properties of interest, such as temperature-dependent lattice parameter, specific heat capacity, and bulk modulus. We also evaluated the energy of stoichiometric defect reactions and defect migration barriers and found close agreement with DFT predictions, demonstrating that our potentials can be used for modeling defects in UN. Additional tests provide evidence that our potentials are reliable for simulating diffusion, noble gas impurities, and radiation damage.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2025

Optical properties of vacancies in aluminum oxide (𝛼−Al 2 ⁢O 3 ) from first principles

We employ first-principles calculations based on hybrid density functional theory to investigate the structural and optical properties of the oxygen vacancy (𝑉 O ) and aluminum vacancy (𝑉 Al ) in 𝛼−Al 2 ⁢O 3 , the most stable (corundum) phase of alumina. Our calculations facilitate the identification of experimental excitation and luminescence spectra with specific electronic transitions at the vacancy sites. The absorption line shape for excitation of an electron at 𝑉$^0_O$ to the conduction-band minimum (CBM) is in excellent agreement with the 6.1 eV band detected by optical absorption spectroscopy, and we find that the 5.9 eV absorption band is generated by an internal electron transition at 𝑉$^0_O$. We confirm that the slowly decaying 3.0 eV emission band of the 𝐹 center is due to a triplet-singlet transition at 𝑉$^0_O$. Our calculations also reveal that the 4.8 eV/5.4 eV absorption and 3.8 eV emission bands assigned to the 𝐹 + center are generated by internal transitions at 𝑉$^{+1}_O$. The line shape for the excitation of an electron from 𝑉$^{+1}_O$ to the CBM agrees well with an absorption band at 6.4 eV, while the recombination of an electron with 𝑉$^{+2}_O$ also produces luminescence around 3.8 eV, but with a considerably broader line shape. For Al vacancies, we confirm that the most prevalent configuration in 𝛼−Al 2 ⁢O 3 is a split-vacancy configuration 𝑉 Al,s , and we calculate migration barriers for different directions in the corundum crystal. We predict absorption and emission spectra for the excitation and recombination of an electron localized at 𝑉$^{−3}_{Al}$ and 𝑉$^{−3}_{Al,s}$ sites with the CBM. The line shapes of the two 𝑉 Al configurations overlap and are considerably broader than the spectra corresponding to 𝑉 O .

36 MATERIALS SCIENCE↗
DOE OSTI2026

Lithium–Divertor Interactions and Helium/Hydrogen Trapping in Lithiated Metals (Final Technical Report)

The goal of this project was to develop a fundamental understanding of helium and hydrogen behavior in lithium, both in bulk and at interfaces with tungsten, in order to inform the design of lithium based plasma facing components for fusion devices. Over the course of the award, the project produced the first comprehensive, peer reviewed dataset describing helium energetics, migration behaviors, and defect interactions in lithium. The research demonstrated that helium behaves in ways not previously observed in any other body centered cubic (BCC) metal: its interstitial configurations are more stable than substitutional ones, and its migration barriers are extraordinarily low, in some cases more than an order of magnitude below those in tungsten or iron. These discoveries reveal that helium in lithium diffuses so rapidly that its transport may be dominated by translational motion rather than the vibrationally activated mechanisms that underpin conventional solid state diffusion. This work lays a scientific foundation for understanding gas retention, bubble formation, and wall evolution in lithium based fusion environments and provides new computational tools, most notably a newly developed Li–He interatomic potential, for advancing future modeling efforts.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Effect of microstructure and neutron irradiation defects on deuterium retention in SiC

Retention of hydrogen isotopes is a critical concern for operating fusion reactors as retained tritium both activates components and removes scarce fuel from the fuel cycle. Radiation-induced displacement damage in SiC influences the retention of hydrogen isotopes compared to pristine SiC. Deuterium retention in neutron irradiated high purity SiC has been compared to different microstructures of non-irradiated high purity SiC using thermal desorption spectroscopy after gas charging and low energy ion implantation. Experimental results show lower deuterium retention in single crystal SiC than in polycrystal SiC indicating that grain boundaries are key trapping features in unirradiated SiC. Deuterium is released at lower temperatures in neutron irradiated polycrystal SiC compared to pristine polycrystal SiC, suggesting weaker trapping by radiation-induced defects compared to grain boundary trapping sites in the pristine materials. Low energy ion implantation caused a high deuterium release temperature, highlighting the sensitivity of deuterium release behaviour to radiation defect characteristics. First principles calculations have been conducted to identify energetically favourable trapping sites in SiC at the H ABc V Si and H TSi V C complexes, and migration barriers between interstitial sites. This helps interpret experimental results and derive effective diffusivity of hydrogen isotopes in SiC in the presence of vacancies.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Diffusion of acceptor dopants in monoclinic 𝛽−Ga 2⁢ O 3

𝛽−Ga 2 ⁢O 3 is a promising material for next-generation power electronics because of its ultrawide band gap and high critical breakdown voltage. However, realizing its full potential requires precise control over dopant incorporation and stability. In this work, we use first-principles calculations to systematically assess the diffusion behavior of eight potential deep-level substitutional acceptors (Au, Ca, Co, Cu, Fe, Mg, Mn, and Ni) in 𝛽−Ga 2 ⁢O 3 . We consider two key diffusion mechanisms: (i) interstitial diffusion under nonequilibrium conditions relevant to ion implantation, and (ii) trap-limited diffusion (TLD) under near-equilibrium thermal annealing conditions. Our results reveal a strong diffusion anisotropy along the 𝑏 and 𝑐 axes, with dopant behavior governed by competition between diffusion and incorporation (or dissociation) activation energies. Under interstitial diffusion, Ca$^{2+}_{i}$ and Mg$^{2+}_{i}$ show the most favorable combination of low migration and incorporation barriers, making them promising candidates for efficient doping along the 𝑏 and 𝑐 axes, respectively. In contrast, Au$^{+}_{i}$ diffuses readily, but exhibits an incorporation barrier that exceeds 5 eV, rendering it ineffective as a dopant. From a thermal stability perspective, Co$^{2+}_{i}$ shows poor activation but high diffusion barriers, which may suppress undesirable migration at elevated temperatures. Under trap-limited diffusion, the dissociation of dopant-host complexes controls mobility. Mg$^{2+}_{i}$ again emerges as a leading candidate, exhibiting the lowest dissociation barriers along both axes, whereas Co$^{2+}_{i}$ and Fe$^{2+}_{i}$ display the highest barriers, suggesting improved dopant retention under thermal stress. In conclusion, our findings guide dopant selection by balancing activation and thermal stability, essential for robust semi-insulating substrates.

Defects↗
DOE OSTI2025

Ab Initio Design of High-Entropy Thermal/ Environmental Barrier Coatings

Next generation thermal/environmental barrier coatings (TEBC) require carefully balancing various properties including phase stability, thermal conductivity, coefficient of thermal expansion (CTE), mechanical properties, and resistance against hot corrosion and water vapor recession. This work mainly focuses on rapid design of cost-effective high entropy rare-earth disilicates and aluminum garnets to protect SiC-based ceramic matrix composites and nickel-based superalloys in the hot section of gas turbine engines using density functional theory methods. Our calculations identify several low-cost high entropy TEBC exhibiting ultralow thermal conductivity at 1500 K and desirable CTE while maintaining good mechanical properties, including Er1/2Y3/4Yb3/4Si2O7, Gd1/4Er1/4Y3/4Yb3/4Si2O7, Eu1/4Er1/4Y3/4Yb3/4Si2O7, and (Y1/4Gd1/4Er1/4Yb1/4)3Al5O12. This work also aims to gain fundamental understanding of oxygen diffusion in model disilicates. Minimizing oxidizer (such as water vapor and oxygen) permeability through the EBC layer can significantly decrease the growth rate of thermally grown oxide and extend the service life of the coating system. Oxygen diffusion mechanisms including formation energy of defects under varying oxygen conditions and defect migration energy barriers will be presented.

coefficient of thermal expansion↗
DOE OSTI2024

Sliceable, Moldable, and Highly Conductive Electrolytes for All-Solid-State Batteries

All-solid-state batteries (ASSBs) require solid electrolytes with high ionic conductivity, stability, and deformability for optimal energy and power density. Here, we developed lithium-deficient lithium yttrium bromide (LYB) solid electrolytes, Li 3–x YBr 6–x (0 ≤ x ≤ 0.50), using a comelting method with controlled lithium deficiency. These electrolytes exhibit favorable mechanical properties such as high moldability and sliceability. The Li 2.65 YBr 5.65 composition has an ionic conductivity of 4.49 mS cm –1 at 25 °C and an activation energy of 0.28 eV. Compared to Li 3 YBr 6 , Li 2.65 YBr 5.65 demonstrates improved rate performance and cycling stability in ASSBs. High-resolution X-ray diffraction confirms the formation of the LYB phase with a C2/m space group. Structural analysis reveals increased cation disorder and larger polyhedral volumes for x > 0 in Li 3–x YBr 6–x , contributing to reduced Li + migration energy barriers. Bond valence site energy calculations and molecular dynamics simulations reveal enhanced 3D lithium-ion transport. NMR spectroscopy further highlights increased Li + dynamics and impurity elimination.

Poudel, Tej P. [Florida State Univ., Tallahassee, ↗
DOE OSTI2025

Industrializable interlayer with catalytic conversion of dead lithium for Ah–level Nickel–rich lithium metal batteries

The growth of lithium (Li) dendrites and the accumulation of dead Li (i.e., Li metal regions which are electronically disconnected from the current collector) significantly undermine the safety and performance of Li metal batteries. This study employs kilogram-scale atomic layer deposition technology to construct zinc oxide with a preferential (002) crystal orientation, which homogeneously forms on commercial carbon nanotube papers. Our approach emphasizes the importance of achieving a moderate Li adsorption energy and low Li migration energy barriers to suppress Li dendrite growth. In this work, we introduce the concept of "catalytic" effect for dead Li reconversion, as validated through time-of-flight secondary ion mass spectrometry, leading to a Li plating/stripping efficiency of 99.89%. The Ah-level Li metal pouch cells with high-nickel positive electrodes achieve a specific energy of 380 Wh kg -1 (based on the mass of the whole pouch cell) and demonstrate stable cycling under demanding conditions. Analysis of the cycled pouch cells confirms the structural integrity and provides insights into the mechanism of the dead Li "catalytic" conversion.

Shen, Huasen [Jianghan University, Wuhan (China)]↗
DOE OSTI2025

Development of interatomic potential and effect of ordering on defect properties in CrMnV

Developing materials that can withstand extreme environments, such as high radiation doses and elevated temperatures, is crucial for next-generation particle accelerators, including the 2.4 MW Long-Baseline Neutrino Facility. High-Entropy Alloys have emerged as promising candidates for beam window materials due to their superior mechanical strength, corrosion resistance, and radiation tolerance. In this study, we focus on the Cr–Mn–V alloy system, developing and employing machine-learning interatomic potentials (MLIPs) to investigate the formation of an ordered phase and its influence on defect properties. Using hybrid Monte Carlo-Molecular Dynamics simulations, we observe the formation of a B2-ordered phase at lower temperatures, consistent with Density Functional Theory (DFT) predictions. Ordered structures display a bimodal distribution of migration energies and reduced mean square displacement values, indicating suppressed vacancy diffusion. Our results also show that the migration energy barrier varies based on the atomic species, with Mn and V exhibiting the highest and lowest average barriers, respectively. These findings suggest that atomic ordering inhibits defect mobility, potentially enhancing the radiation resistance of CrMnV alloys. The validated MLIP provides a reliable framework for simulations that are faster than traditional DFT while maintaining the accuracy required to study defect and ordering properties.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Self‐Trapped Hole Migration and Defect‐Mediated Thermal Quenching of Luminescence in α‐ and β‐Ga 2 O 3

Gallium oxide (Ga 2 O 3 ) is a promising ultrawide bandgap semiconductor for next-generation power electronics and optoelectronic devices. Here, temperature-dependent and polarization-resolved photoluminescence excitation spectroscopy data, complemented by hybrid-functional first-principles calculations, are presented, and a microscopic model is derived that explains the interplay of hole migration, defect trapping, and carrier recombination at defects underlying thermal quenching phenomena in α- and β-Ga 2 O 3 . In α-Ga 2 O 3 , the UV emission is attributed to self-trapped holes, while the blue luminescence arises from defect-related processes, including gallium split vacancies and their defect complexes. Calculations reveal an energy barrier of 88 meV for self-trapped hole migration in α-Ga 2 O 3 , consistent with activation energies from temperature-dependent photoluminescence. This enables efficient trapping by defects, enhancing blue luminescence and quenching UV emission. In β-Ga 2 O 3 , a higher migration barrier of 0.36 eV reduces the defect trapping, allowing the UV self-trapped hole emission to remain intense, with blue luminescence emerging only at elevated temperatures. These results establish a direct link between self-trapped hole migration, defect trapping, and thermal quenching of emission in both phases. The insights advance the understanding of carrier dynamics in ultrawide bandgap oxides and may guide defect engineering for high-performance functional devices.

Hajizadeh, Nima [Leibniz-Institut im Forschungsver↗