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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 163 records · Page 9
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Quantum simulation of charge and exciton transfer in multi-mode models using engineered reservoirs

Quantum simulation enables studies of open-system dynamics in non-perturbative regimes by programming electronic, vibrational, and environmental interactions on comparable energy scales. Trapped ions offer this capability, combining spins, phonons, and tunable dissipation on one platform. We demonstrate an open-system quantum simulation of charge and exciton transfer in a multi-mode linear vibronic coupling model. Using tailored spin-phonon interactions with reservoir engineering, we emulate a system with two dissipative vibrational modes coupled to donor and acceptor sites and track its non-equilibrium dynamics. We continuously tune the system from the charge transfer regime to the vibrationally assisted exciton transfer regime and find that degenerate modes enhance transfer rates at large energy gaps, while non-degenerate modes activate pathways that reduce the energy-gap dependence. Thus, the presence of one additional vibration introduces interfering pathways and reshapes non-perturbative excitation transfer. Our results establish a scalable, hardware-efficient route to simulate vibronic processes with engineered environments.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2021

Computational Fermi Level Engineering and Doping-Type Conversion of Mg:Ga 2 O 3 via Three-Step Synthesis Process

Gallium oxide (Ga 2 O 3 ) is being actively explored for electronics that can operate at high power, temperature, and frequency as well as for deep-ultraviolet optoelectronics and other applications due to its ultra-wide bandgap (UWBG) and low projected fabrication cost of large-size and high-quality crystals. Efficient n-type doping of monoclinic beta-phase of Ga 2 O 3 has been achieved, but p-type doping faces fundamental obstacles due to compensation, deep acceptor levels, and the polaron transport mechanism of free holes. However, aside from the challenges of achieving p-type conductivity, plenty of opportunity exists to engineer the position of the Fermi level for improved design of Ga 2 O 3 -based devices. We use first-principles defect theory and defect equilibrium calculations to simulate a three-step growth-annealing-quench synthesis protocol for hydrogen-assisted Mg doping in ß-Ga 2 O 3 . The simulations take into account the gas phase equilibrium between H 2 , O 2 , and H 2 O, which determines the H chemical potential. We predict Ga 2 O 3 doping-type conversion to a net p-type regime after growth under reducing conditions in the presence of H2 followed by O-rich annealing, which is a similar process to Mg acceptor activation by H removal in GaN. For equilibrium annealing with re-equilibration of compensating O vacancies, there is an optimal temperature that maximizes the Ga 2 O 3 net acceptor density for a given Mg doping level; the acceptor density is further increased in the non-equilibrium annealing scenario without re-equilibration. After quenching to operating temperature, the Ga 2 O 3 Fermi level drops below mid-gap down to about 1.5 eV above the valence band maximum, creating a significant number of uncompensated neutral Mg Ga 0 acceptors. The resulting free hole concentration in Ga 2 O 3 is very low even at elevated operating temperature (~10 8 cm -3 at 400°C) due to the deep energy level of these Mg acceptors, and hole conductivity is further impeded by the polaron hopping mechanism. However, the Fermi-level reduction and suppression of free electron density in this doping-type converted (NA>ND) Ga 2 O 3 material are important for improved designs of Ga 2 O 3 electronic devices. These results illustrate the power of computational predictions not only for new materials but also for their synthesis science.

36 MATERIALS SCIENCE↗
DOE OSTI2022

A multisite decomposition of the tensor network path integrals

Tensor network decompositions of path integrals for simulating open quantum systems have recently been proven to be useful. However, these methods scale exponentially with the system size. This makes it challenging to simulate the non-equilibrium dynamics of extended quantum systems coupled with local dissipative environments. In this work, we extend the tensor network path integral (TNPI) framework to efficiently simulate such extended systems. The Feynman–Vernon influence functional is a popular approach used to account for the effect of environments on the dynamics of the system. In order to facilitate the incorporation of the influence functional into a multisite framework (MS-TNPI), we combine a matrix product state (MPS) decomposition of the reduced density tensor of the system along the sites with a corresponding tensor network representation of the time axis to construct an efficient 2D tensor network. The 2D MS-TNPI network, when contracted, yields the time-dependent reduced density tensor of the extended system as an MPS. The algorithm presented is independent of the system Hamiltonian. We outline an iteration scheme to take the simulation beyond the non-Markovian memory introduced by solvents. Applications to spin chains coupled to local harmonic baths are presented; we consider the Ising, XXZ, and Heisenberg models, demonstrating that the presence of local environments can often dissipate the entanglement between the sites. We discuss three factors causing the system to transition from a coherent oscillatory dynamics to a fully incoherent dynamics. The MS-TNPI method is useful for studying a variety of extended quantum systems coupled with solvents.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Electronic heat generation in semiconductors: Non-equilibrium excitation and evolution of zone-edge phonons via electron–phonon scattering in photo-excited germanium

We investigate experimentally and using first-principles theory the generation of phonons and the relaxation of carriers on picosecond timescales across the Brillouin zone of photo-excited Ge by inter-valley electron–phonon scattering. The phonons generated are typical of those generated in semiconductor devices, contributing to the accumulation of heat within the material. We simulate the time-evolution of phonon populations, based on first-principles band structure and electron–phonon and phonon–phonon matrix elements, and compare them to data from time-resolved x-ray diffuse scattering experiments, performed at the Linac Coherent Light Source x-ray free-electron laser facility, following photo-excitation by a 50 fs near-infrared optical pulse. We show that the intensity of the non-thermal x-ray diffuse scattering signal, which is observed to grow substantially near the L-point of the Brillouin zone over 3–5 ps, is due to phonons generated by scattering of carriers between the Δ and L valleys. These phonons have low group velocities, resulting in a heat bottleneck. With the inclusion of phonon decay through 3-phonon processes, the simulations also account for other non-thermal features observed in the x-ray diffuse scattering intensity, which are due to anharmonic phonon–phonon scattering of the phonons initially generated by electron–phonon scattering.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2023

Nucleation-mediated reshaping of facetted metallic nanocrystals: Breakdown of the classical free energy picture

Shape stability is key to avoiding degradation of performance for metallic nanocrystals synthesized with facetted non-equilibrium shapes to optimize properties for catalysis, plasmonics, and so on. Reshaping of facetted nanocrystals is controlled by the surface diffusion-mediated nucleation and growth of new outer layers of atoms. Here, Kinetic Monte Carlo (KMC) simulation of a realistic stochastic atomistic-level model is applied to precisely track the reshaping of Pd octahedra and nanocubes. Unexpectedly, separate constrained equilibrium Monte Carlo analysis of the free energy profile during reshaping reveals a fundamental failure of the classical nucleation theory (CNT) prediction for the reshaping barrier and rate. Why? Nucleation barriers can be relatively low for these processes, so the system is not locally equilibrated before crossing the barrier, as assumed in CNT. This claim is supported by an analysis of a first-passage problem for reshaping within a master equation framework for the model that reasonably captures the behavior in KMC simulations.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Out of time order correlation of the Hubbard model with random local disorder

The out-of-time-order correlator (OTOC) serves as a powerful tool for investigating quantum information spreading and chaos in complex systems. We present a method employing non-equilibrium dynamical mean-field theory and coherent potential approximation combined with diagrammatic perturbation on the Schwinger–Keldysh contour to calculate the OTOC for correlated fermionic systems subjected to both random disorder and electron interaction. Furthermore, our key finding is that random disorder enhances the OTOC decay in the Hubbard model for the metallic phase in the weakly interacting limit. However, the current limitation of our perturbative solver restricts the applicability to weak interaction regimes.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2025

Foundations of magnetohydrodynamics

In this tutorial, a derivation of magnetohydrodynamics (MHD) valid beyond the usual ideal gas approximation is presented. Non-equilibrium thermodynamics is used to obtain conservation equations and linear constitutive relations. When coupled with Maxwell's equations, this provides closed fluid equations in terms of material properties of the plasma, described by the equation of state and transport coefficients. These properties are connected to microscopic dynamics using the Irving–Kirkwood procedure and Green–Kubo relations. Symmetry arguments and the Onsager–Casimir relations allow one to vastly simplify the number of independent coefficients. Importantly, expressions for current density, heat flux, and stress (conventionally Ohm's law, Fourier's law, and Newton's law) take different forms in systems with a non-ideal equation of state. The traditional form of the MHD equations, which is usually obtained from a Chapman–Enskog solution of the Boltzmann equation, corresponds to the ideal gas limit of the general equations.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2026

Intense cavitation-assisted electric discharge as a promising tool for water treatment

This study investigates interrelations between one-electrode Cavitation-Assisted Electric Discharge (CAED), two-electrode CAED, and recently discovered Intense CAED (I-CAED). The one-electrode CAED is a self-triggered nanosecond discharge with pulse energy in the micro-Joule range, which can be generated even by a DC voltage. I-CAED consists of a non-equilibrium part within a low-pressure cavitating region and a micro-spark traversing a liquid film. We hypothesize that CAED propagates from the high-voltage electrode as an ionization wave through bubbles of saturated vapor. Subsequently, the streamer-like discharges in the bubbles may form a continuous plasma channel. Inside the cavitating region, the plasma is strongly non-equilibrium, providing an ideal environment for generating chemically unstable species such as hydrogen peroxide (H 2 O 2 ). Plasma of I-CAED spark is characterized by high electron density and near-thermal equilibrium, emitting a continuous ultraviolet spectrum. The combination of these different discharge parts makes I-CAED in water a highly effective tool for the Advanced Oxidation Process, particularly in water disinfection. Experimentally demonstrated Electric Energy per Order value for disinfection of E. coli-contaminated water is as low as 0.135 ± 0.035 kWh/m 3 /order. Estimates show that the implementation of “dry electrodes” configuration reduces the erosion rate of the electrode material by at least one order of magnitude. Spectral analysis reveals that the continuum emission generated by I-CAED in proximity to metal electrodes deviates from the spectra of discharges spatially decoupled from the electrodes. We assume that this spectral divergence is attributable to blackbody-like emission originating from metallic nanoparticles form during the electrode's erosion process.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Cosmic neutrino decoupling and its observable imprints: insights from entropic-dual transport

Abstract Very different processes characterize the decoupling of neutrinos to form the cosmic neutrino background (CνB) and the much later decoupling of photons from thermal equilibrium to form the cosmic microwave background (CMB). The CνB emerges from the fuzzy, energy-dependent neutrinosphere and encodes the physics operating in the early universe in the temperature rangeT∼ 10 MeV toT∼ 10 keV. This is the epoch where beyond Standard Model (BSM) physics, especially in the neutrino sector, may be influential in setting the light element abundances, the necessarily distorted fossil neutrino energy spectra, and other light particle energy density contributions. Here we use techniques honed in extensive CMB studies to analyze the CνB as calculated in detailed neutrino energy transport and nuclear reaction simulations of the protracted weak decoupling and primordial nucleosynthesis epochs. Our moment method, relative entropy, and differential visibility approach can leverage future high precision CMB and light element primordial abundance measurements to provide new insights into the CνB and any BSM physics it encodes. We demonstrate that the evolution of the energy spectrum of the CνB throughout the weak decoupling epoch is accurately captured in the Standard Model by only three parameters per species, a non-trivial conclusion given the deviation from thermal equilibrium and the impact of the decrease of electron-positron pairs. Furthermore, we can interpret each of the three parameters as physical characteristics of a non-equilibrium system. Though the treatment presented here makes some simplifying assumptions including ignoring neutrino flavor oscillations, the success of our compact description within the Standard Model motivates its use also in BSM scenarios. We further demonstrate how observations of primordial light element abundances can be used to place constraints on the CνB energy spectrum, deriving response functions that can be applied for general deviations from a thermal spectrum. Combined with the description of those deviations that we develop here, our methods provide a convenient and powerful framework to constrain the impact of BSM physics on the CνB.

Astronomy & Astrophysics↗
DOE OSTI2023

Self-consistent and detailed opacities from a non-equilibrium average-atom model

Modern density functional theory (DFT) is a powerful tool for accurately predicting self-consistent material properties such as equations of state, transport coefficients and opacities in high energy density plasmas, but it is generally restricted to conditions of local thermodynamic equilibrium (LTE) and produces only averaged electronic states instead of detailed configurations. We propose a simple modification to the bound-state occupation factor of a DFT-based average-atom model that captures essential non-LTE effects in plasmas—including autoionization and dielectronic recombination—thus extending DFT-based models to new regimes. Finally, we then expand the self-consistent electronic orbitals of the non-LTE DFT-AA model to generate multi-configuration electronic structure and detailed opacity spectra. This article is part of the theme issue ‘Dynamic and transient processes in warm dense matter’.

36 MATERIALS SCIENCE↗
DOE OSTI2021

QCD thermalization: Ab initio approaches and interdisciplinary connections

Heavy-ion collisions at BNL's Relativistic Heavy Ion Collider and CERN's Large Hadron Collider provide strong evidence for the formation of a quark-gluon plasma, with temperatures extracted from relativistic viscous hydrodynamic simulations shown to be well above the transition temperature from hadron matter. Outstanding problems in QCD include how the strongly correlated quark gluon matter forms in a heavy-ion collision, its properties off-equilibrium, and the thermalization process in the plasma. In this work, we review the theoretical progress in this field in weak coupling QCD effective field theories and in strong coupling holographic approaches based on gauge-gravity duality. We outline the interdisciplinary connections of different stages of the thermalization process to non equilibrium dynamics in other systems across energy scales ranging from inflationary cosmology, to strong field QED, to ultracold atomic gases, with emphasis on the universal dynamics of non-thermal and hydrodynamic attractors. We survey measurements in heavy-ion collisions that are sensitive to the early non-equilibrium stages of the collision and discuss the potential for future measurements. We summarize the current state-of-the art in thermalization studies and identify promising avenues for further progress.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2022

Computational Fluid Dynamics Modeling of Low Temperature Ignition Processes From a Nanosecond Pulsed Discharge at Quiescent Conditions

Recent interest in nonequilibrium plasma discharges as sources of ignition for the automotive industry has not yet been accompanied by the availability of dedicated models to perform this task in computational fluid dynamics (CFD) engine simulations. The need for a low-temperature plasma (LTP) ignition model has motivated much work in simulating these discharges from first principles. Most ignition models assume that an equilibrium plasma comprises the bulk of discharge kernels. LTP discharges, however, exhibit highly nonequilibrium behavior. In this work, a method to determine a consistent initialization of LTP discharge kernels for use in engine CFD codes like CONVERGE is proposed. The method utilizes first principles discharge simulations. Such an LTP kernel is introduced in a flammable mixture of air and fuel, and the subsequent plasma expansion and ignition simulation is carried out using a reacting flow solver with detailed chemistry. Finally, the proposed numerical approach is shown to produce results that agree with experimental observations regarding the ignitability of methane-air and ethylene-air mixtures by LTP discharges.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2024

HydraGNN_Predictive_GFM_2024 - Ensemble of predictive graph foundation models for ground state atomistic materials modeling

We provide the ensemble of fifteen pre-trained graph foundation models (GFMs) for atomistic materials modeling applications. Each one of the fifteen GFMs has been trained on five open-source datasets that (once aggregated) amount to over 154 million atomistic structures, which cover over two-thirds of the natural elements of the periodic table and that comprises a broad set of organic and inorganic compounds. This vast set of atomistic structures comprises ground state configurations that are dynamically stable (i.e., equilibrated structures with atomic forces approximately close to zero values) as well as dynamically unstable structures (i.e., non-equilibrium structures with non-negligible non-zero values of atomic forces). The ensemble of datasets aggregated does NOT include excited states. The datasets have been curated to remove atomistic structures with spectral norm of the force tensor above 100 eV/angstrom. Moreover, a linear term of the energy was computed for each dataset using a linear regression model that uses the chemical concentration of each natural element as regressor. The linear term predicted by the linear regression model has been subtracted from each original energy value to perform a re-alignment of the energy values across different electronic structures approximation theories performed to generate the diverse multi-source, multi-fidelity datasets. The folder "ADIOS_files" contains the set of pre-processed datasets in Adaptable I/O System (ADIOS) format (https://www.exascaleproject.org/research-project/adios/) that have been used for the development and training of GFMs in this work. The "ADIOS_files" directory contains 6 sub-directories named as follows: - ANI1x-v3.bp - MPTrj-v3.bp - OC2020-20M-v3.bp - OC2020-v3.bp - OC2022-v3.bp - qm7x-v3.bp Each sub-directory contains the pre-processed datasets converted in Adaptable I/O System (ADIOS) format (https://www.exascaleproject.org/research-project/adios/) that have been used to the development, training, and performance testing of the ensemble go predictive graph foundation models. Each GFM was developed using HydraGNN (https://github.com/ORNL/HydraGNN) as underlying graph neural network (GNN) architecture. The multi-task learning (MTL) capability of HydraGNN was used to simultaneously train the GFMs on labeled values for direct predictions of energy (a total system property of an atomistic structure that measures the chemical stability) and atomic forces (an atomic level property of an atomistic structure that measures the dynamical stability). The hyper parameters of the GFM have been tuned using scalable hyperparameter optimization (HPO) algorithms implemented in the software DeepHyper (https://github.com/deephyper/deephyper). The pre-training of each HPO trial was performed using distributed data parallelism (DDP) to scale the training across 128 compute nodes of the exascale OLCF supercomputer Frontier. Each HPO trial was trained only for 10 epochs and an early stopping was performed to avoid wasting significant computational resources on GNN architectures that were clearly underperforming. For each HPO trial, the 'omnistat' tool developed by (AMD Research - Advanced Micro Device) was used to measure the total energy consumption in kWh. The ensemble of GFMs was obtained by selecting the fifteen best performing HPO trials. Four models have been selected for their clear advantage in accuracy, and these are the GFMs with IDs 229, 156, 147, 260. Additional eleven models have been selected based on judicious balance between accuracy and energy consumption needed for training, and these are the GFMs with IDs 165, 78, 137, 1, 175, 171, 181, 67, 179, 167, 351. Each selected GFM of the ensemble was continued to cumulate a total of at most 30 epochs. In some cases, the total number of epochs actually performed was les than 30 due to two combined factors: (1) the size of the GFM (i.e., the number of model parameters to train) and (2) the total wall-clock time for which the computational resources could be allocated on OLCF-Frontier. The "Ensemble_of_models" directory contains 15 sub-directories named as follows: - gfm_0.229 - gfm_0.156 - gfm_0.147 - gfm_0.260 - gfm_0.165 - gfm_0.78 - gfm_0.137 - gfm_0.1 - gfm_0.175 - gfm_0.171 - gfm_0.181 - gfm_0.67 - gfm_0.179 - gfm_0.167 - gfm_0.351 Each one of these sub-directories refers to one of the fifteen HPO trials that have been selected to continue the pre-training with at most 30 epochs. With each sub-directory associated with a specific HPO trial, the following files can be found: - config.json: file for argument parsing to develop and train an HydraGNN architecture - gfm_0.ID_epoch_N.pk: file with model parameters for HPO ID trial after N epochs of training The ensemble of fifteen GFM architectures was used for (1) ensemble averaging to stabilize the predictions of energy and atomic forces after pre-training for post-processing analysis and (2) ensemble uncertainty quantification (UQ). The code used to develop, pre-train, and load the pre-trained models for post-processing analysis is available on the ORNL-GitHub at the following link: https://github.com/ORNL/HydraGNN/tree/Predictive_GFM_2024

36 MATERIALS SCIENCE↗
DOE OSTI2025

Applying deep learning methods to develop new models of molecular charge transfer, nonadiabatic dynamics, and nonlinear spectroscopy in the condensed phase

Photon- and field-induced charge transfer has central importance in the generation and storage of electricity, the novel properties of materials, photo-induced catalysis, and electro-optic activity (e.g., photovoltaic cells, fuel cells, and organic chromophores for use in optical fibers and light-emission diodes). These non-equilibrium electronic and chemical transformations are probed by ultrafast, nonlinear spectroscopies. Accurate simulations play a crucial role in our ability to understand, optimize, and control these transformations. This project applies modern deep learning and machine learning (ML) methods to dramatically improve models of electronic dynamics, electronic-nuclear dynamics, and spectroscopic measurements for improved simulations of chemistry in complex environments, far from equilibrium phenomena, and processes in extreme environments, such as materials exposed to strong or resonant fields. This project develops accurate neural net models that go beyond predictive capability to also provide new insight into the fundamental physics underlying electron and nuclear dynamics. To achieve its objectives, this project explores and develops customized versions of high-capacity deep learning algorithms/models. These techniques are developed with an emphasis on fundamental chemical insight, not just predictive accuracy, to assist the development of the next generation of quantum simulation methods.

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

Understanding Mechanisms of Selective Crystal Nucleation and Growth Using In Situ Electron Microscopy

Separation processes are essential for purifying and isolating critical materials, but are challenging due to the natural tendency of systems to mix. This project explores far-from-equilibrium separation methods using external electric and magnetic fields to drive selective nucleation and crystal growth. Using in situ electrochemical transmission electron microscopy (TEM), we observed ion transport and crystallization behavior under applied electric fields. We found that ions migrate toward the working electrode, where nucleation preferentially occurs. These findings advance our understanding of non-equilibrium separation mechanisms and support the development of efficient, sustainable methods for extracting critical materials from unconventional domestic sources.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Technical note: A modified formulation of dynamic energy budget theory for faster computation of biological growth

Abstract. The mass conservation equation in the presence of boundary fluxes and chemical reactions from non-equilibrium thermodynamics is used to derive a modified dynamic energy budget (mDEB) model. Compared to the standard dynamic energy budget (sDEB) model (Kooijman, 2009), this modified formulation does not place the dilution effect in the mobilization kinetics of reserve biomass, and it maintains the partition principle for reserve mobilization dynamics for both linear and non-linear kinetics. Overall, the mDEB model shares most features with the sDEB model. However, for biological growth that requires multiple nutrients, the mDEB model is computationally much more efficient by not requiring numerical iterations for obtaining the specific growth rate. In an example of modeling the growth of Thalassiosira weissflogii in a nitrogen-limiting chemostat, the mDEB model was found to have almost the same accuracy as the sDEB model while requiring almost half of the computing time of the sDEB model. Since the sDEB model has been successfully applied in numerous studies, we believe that the mDEB model can help improve the modeling of biological growth and the associated ecosystem processes in various contexts.

Tang, Jinyun↗
DOE OSTI2021

Computational Fermi Level Engineering and Doping-Type Conversion of Ga2O3 Via Three-Step Processing

Ga2O3 is being actively explored for power electronics, and other applications due to its ultra- wide bandgap and low projected fabrication cost of high-quality crystals. N-type doping of Ga2O3 can be achieved and tuned, but p-type doping faces fundamental obstacles. Successful engineering of Ga2O3 based devices requires critical control of doping density, Fermi level position, providing opportunities for predictive process simulation. We use first-principles defect equilibrium calculations to simulate a 3-step growth- annealing-quench protocol for hydrogen assisted Mg doping in Ga2O3, taking into account the hydrogen- oxygen-water gas phase equilibrium. We predict type conversion to a net p-type regime following O-rich annealing after growth under reducing conditions in the presence of H2. We show that there is an optimal temperature that maximizes the net acceptor density during the equilibrium annealing step for a given Mg doping level. Quenching of non-equilibrium annealed samples then results in a Fermi level EF below mid-gap down to about EV +1.5 eV, creating a significant number of uncompensated neutral MgGa0 acceptors. This type converted Ga2O3 can create significant built-in field in a p-n junction with an adjoining n-type material and could enable vertical MOSFETs.

CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSICS,M↗
DOE OSTI2021

Computational Fermi Level Engineering and Doping-Type Conversion of Ga2O3 Via Three-Step Processing

Ga2O3 is being actively explored for power electronics, deep-ultraviolet optoelectronics, and other applications due to its ultra-wide bandgap and low projected fabrication cost of large-size and high-quality crystals. N-type doping of Ga2O3 can be achieved and tuned, but p-type doping faces fundamental obstacles due to deep character of acceptor levels and polaron transport of resulting holes. However, successful engineering of Ga2O3 based devices requires critical control of doping density, Fermi level position, and free carrier concentration, providing opportunities for predictive process simulation. We use first-principles defect theory and defect equilibrium calculations to simulate a 3-step growth-annealing-quench protocol for hydrogen assisted Mg doping in Ga2O3, taking into account the hydrogen-oxygen-water gas phase equilibrium. We predict type conversion to a net p-type regime following O-rich annealing after growth under reducing conditions in the presence of H2. This process is similar to the Mg acceptor activation by H removal in GaN. We show that there is an optimal temperature that maximizes the net acceptor density during the equilibrium annealing step for a given Mg doping level. Quenching of non-equilibrium annealed samples then results in a Fermi level EF below mid-gap down to about EV +1.5 eV, creating a significant number of uncompensated neutral MgGa0 acceptors. The resulting free hole concentration in quenched samples is very low (109 – 1012 cm-3) due to deep energy level of these Mg acceptors, but this type converted Ga2O3 material can create a significant built-in field in a p-n junction with an adjoining n-type material. Additionally, the electron concentration is greatly suppressed in such acceptor-doped Ga2O3, which could enable the use as a current blocking layer to fabricate normally-off (enhancement-mode) vertical Ga2O3 based metal-oxide-semiconductor field effect transistors (MOSFETs), and as a guard ring for edge termination in MOSFETs and Schottky barrier diodes (SBDs) with increased breakdown voltage.

CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSICS,M↗