Modular High Temperature Gas-Cooled Reactor: Licensing Part II
Past US HTGRs and Licensing Approaches
11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
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Modular High Temperature Gas-Cooled Reactor: Accident Analysis
Licensing Modernization Project (LMP) Risk Informed Approach Selection of Licensing Basis Events (LBEs) Frequency-Consequence Target LBE Cumulative Risk Targets Structures, Systems, and Components (SSC) Safety Categories Classification Evaluation of Defense in Depth (DID) Use of Probabilistic Risk Assessment (PRA) in LMP Process PRA Policy Statement American Nuclear Society (ANS) Non-Light-Water Reactor (non-LWR) PRA Standard
11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
Divergent controls of soil organic carbon between observations and process-based models
Abstract The storage and cycling of soil organic carbon (SOC) are governed by multiple co-varying factors, including climate, plant productivity, edaphic properties, and disturbance history. Yet, it remains unclear which of these factors are the dominant predictors of observed SOC stocks, globally and within biomes, and how the role of these predictors varies between observations and process-based models. Here we use global observations and an ensemble of soil biogeochemical models to quantify the emergent importance of key state factors – namely, mean annual temperature, net primary productivity, and soil mineralogy – in explaining biome- to global-scale variation in SOC stocks. We use a machine-learning approach to disentangle the role of covariates and elucidate individual relationships with SOC, without imposing expected relationships a priori . While we observe qualitatively similar relationships between SOC and covariates in observations and models, the magnitude and degree of non-linearity vary substantially among the models and observations. Models appear to overemphasize the importance of temperature and primary productivity (especially in forests and herbaceous biomes, respectively), while observations suggest a greater relative importance of soil minerals. This mismatch is also evident globally. However, we observe agreement between observations and model outputs in select individual biomes – namely, temperate deciduous forests and grasslands, which both show stronger relationships of SOC stocks with temperature and productivity, respectively. This approach highlights biomes with the largest uncertainty and mismatch with observations for targeted model improvements. Understanding the role of dominant SOC controls, and the discrepancies between models and observations, globally and across biomes, is essential for improving and validating process representations in soil and ecosystem models for projections under novel future conditions.
58 GEOSCIENCES↗
In Situ Catalytic Fast Pyrolysis using Red Mud Catalyst: Impact of catalytic fast pyrolysis temperature and biomass feedstocks
Catalytic fast pyrolysis (CFP) has been considered as a very promising approach for converting lignocellulosic biomass into higher-quality bio-oils followed by hydrotreating to produce fuelrange products. A reactive, robust, and low-cost catalyst is required to drive the CFP process. Red mud, a side-product produced during the refining of bauxite to alumina, appears to be an effective catalyst for in situ CFP of biomass. In this paper, we report the impact of CFP reaction temperature on the conversion of a pinyon juniper feedstock to bio-oils using red mud as the catalyst and then to fuel-range hydrocarbons by hydrotreating of the produced bio-oil. The yield and quality of the CFP bio-oil produced and the yield and quality of hydrotreated final products were determined. When the CFP process temperature was lowered from 450 to 400ºC, the bio-oil yield increased with minimal differences in the oxygen content, hydrogen-to-carbon ratio, water content, etc. In addition, CFP bio-oils at both temperatures were processed in a single-stage continuous hydrotreater without reactor plugging during the testing period (i.e., ~100 hours on stream). The yield of CFP bio-oil produced at 400ºC was lower than the yield at 450ºC. However, the overall yield, from biomass to hydrocarbon fuel, was still higher for CFP processing at 400ºC than for processing at 450ºC. This indicates the potential for enhancing overall carbon efficiency, including CFP processing and hydrotreating, by employing red mud catalysts for biomass pyrolysis and tuning the CFP parameters. Detailed analysis of bio-oil and hydrotreated products showed a lower content of lignin-derived species in both samples. Furthermore, CFP processing of three different biomass feedstocks corroborated red mud catalyst development for producing improved quality bio-oil and, when combined with hydrotreating, for the production of fuel range hydrocarbons.
Santosa, Daniel M.↗
Solvent-free and low temperature synthesis of chalcogenide Na superionic conductors for solid-state batteries
Sodium chalcogenide ionic conductors are attractive candidates as solid electrolytes (SEs) in solid-state Na metal batteries. They show the advantages of high ionic conductivity of 10 –4 –10 –2 S cm –1 at room temperature and great chemical stability in air. However, simple, efficient, and scalable approaches for the synthesis of chalcogenide solid electrolytes (SEs) are required. In this work, we report a solvent-free mixing to form dry intermediate products, which are subjected to different treatments (electron-beam assisted method or low temperature heating (≤150 °C)) to produce pure phase of Na 3 SbS 4-y Se y (0 ≤ y < 2) chalcogenides. Heavy Se-doping in Na 3 SbS 4 results in the tetragonal-to-cubic phase transition as well as a significant change of Sb-S bonding in Raman spectra. Among all chalcogenide SEs, Na 3 SbS 3 Se showed the highest ionic conductivity of 3.75 × 10 –4 S cm –1 at room temperature, 47% higher than that of pristine Na 3 SbS 4 . Moreover, the Se-dopant also enhanced the electrochemical stability towards Na metal in solid-state batteries. The solid-state Na||FeS 2 battery with Na 3 SbS 3 Se SE displayed long-term cycling ability up to 1,000 cycles within the voltage window of 1.0–2.7 V and retained a specific capacity of 105 mAh g –1 after 600 cycles. As a result, this technique promotes the practical applications of chalcogenide SEs in solid-state batteries.
25 ENERGY STORAGE↗
Preliminary Design of Reactor Cavity Cooling System for a Horizontal Compact HTGR
The Horizontal Compact High Temperature Gas Reactor (HC-HTGR) is being designed by a multi-disciplinary team of nuclear, mechanical, and structural engineers under the support of a DOE-NE Advanced Reactor Demonstration Program’s Advanced Reactor Concepts-20 (ARC-20) award. The objective of this ARC-20 project is to deliver a conceptual design for the proposed MIGHTR in 3 years and support its commercialization as a safe and low-cost HTGR. Argonne National Laboratory (Argonne) is responsible for the design and analysis of the reactor cavity cooling system (RCCS) as a safety system for passive decay heat removal of the reactor concept. This report documents the preliminary design study of the RCCS for the HC-HTGR. It includes the establishment of the design requirements, a high-level design study by initial scoping calculations, and preliminary performance calculations of the HC-HTGR RCCS design. Design requirements for the HC-HTGR RCCS have been established to guide preliminary design activities and scoping performance calculations. Initial scoping calculations including estimation of the water inventory, estimation of HVAC thermal capability, and a parametric study on loop dimensions by standalone RCCS analysis. Based on scoping calculation results, a set of baseline dimensions of the HC-HTGR RCCS was derived. A water panel modeling approach was investigated to explore various potential design options for the water panel under consideration for the HC-HTGR RCCS using RELAP5-3D. A test case study was performed to assess the prediction capability of two modeling approaches. The results were compared with CFD simulations conducted in constant RPV temperature and heat flux boundary conditions. It confirms the capability of the RELAP5-3D modeling approach to include all important heat transfer mechanisms expected in the HC-HTGR RCCS operation conditions. Then, a reference RELAP5-3D model for the 1/8 th of a compartment of the preliminary design of the HC-HTGR RCCS was developed. A preliminary performance analysis was conducted to evaluate single-phase natural circulation performance with different top tank temperature values and panel conduction performance in various operation conditions. From single-phase natural circulation performance analysis, the system operation mode was investigated in normal operating and limiting design conditions. It showed operation mode in a subcooled state with a proper top tank water cooling system. Parasitic heat loss by both internal air flow and RCCS was estimated, showing it satisfies maintaining below target maximum heat loss of the HC-HTGR RCCS. From the panel conduction performance analysis, two candidate materials for the riser tube such as carbon steel and stainless steel were compared in the thermal performance of HC-HTGR RCCS. From a single water panel test compared with CFD simulation results, it was confirmed that the current capability of the RELAP5-3D modeling approach for the water panel predicts the thermal conduction of two different materials of the water panel. Then, system-level thermal performance analysis was performed for 1/8 th of the compartment of the preliminary HC-HTGR RCCS design. It was first observed that the current preliminary HC-HTGR RCCS design had minimal impact on the overall thermal performance of the water panel by changing pipe material from carbon steel to stainless steel. From Argonne’s effort on the ongoing water-based NSTF testing program, several considerations other than the thermal performance point of view were addressed to be considered in selecting pipe materials.
21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
Controlling surface adatom kinetics for improved structural and optical properties of high indium content aluminum indium nitride
A non-traditional, for AlInN, method of controlling adatom kinetics and a low temperature growth condition were employed to improve the quality of high indium content aluminum indium nitride films. Metal-rich surfaces were used to enhance adatom mobility and compensate for the low growth temperature (Tsub ≤ 400 °C) effect of reducing surface diffusion lengths. The metal-rich approach resulted in 12 times lower x-ray diffraction full-width at half-maximum rocking curve figures of merit when compared to literature. In addition to promising photoluminescence emission, these results indicate improved structural quality over other reported approaches. AlInN films with ∼70% indium content were characterized via x-ray diffraction, atomic force microscopy, and photoluminescence spectroscopy with each technique indicating an optimal growth temperature of 350 °C. Al0.3In0.7N grown above 400 °C exhibited phase separation and a reduction in quality, while samples grown colder were predominantly single-phase and displayed improved photoluminescence at ∼1.45 eV. The photoluminescence spectra suggest emission from quantum wire-like structures with dimensions ranging from 15 to 18 nm. These low-temperature, metal-rich findings for high indium content AlInN are promising for future long-wavelength III-nitride optical devices.
Engel, Zachary (ORCID:0000000205021981)↗
Electronic band contraction induced low temperature methane activation on metal alloys
The catalytic conversion of methane under mild conditions is an appealing approach to selectively produce value-added products from natural gas. Catalysts which can chemisorb methane can potentially overcome challenges associated with its high stability and achieve facile activation. Although transition metals can activate C–H bonds, chemisorption and low-temperature conversion remain elusive on these surfaces. The broad electronic bands of metals can only weakly interact with the methane orbitals, in contrast to specific transition metal oxide and supported metal cluster surfaces which are now recognized to form methane σ-complexes. Here, we report methane chemisorption can, remarkably, occur on metal surfaces via electronic band contraction and localization from metal alloying. From a broad screening including single atom and intermetallic alloys in various substrates, we find early transition metals as promising metal solutes for methane chemisorption and low-temperature activation. These findings demonstrate a combinatorial diversity of possible candidates in earth abundant metal alloys with this attractive catalytic behavior.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
A new approach to both high safety and high performance of lithium-ion batteries
We present a novel concept to achieve high performance and high safety simultaneously by passivating a Li-ion cell and then self-heating before use. By adding a small amount of triallyl phosphate in conventional electrolytes, we show that resistances of the passivated cells can increase by ~5×, thereby ensuring high safety and thermal stability. High power before battery operation is delivered by self-heating to an elevated temperature such as 60°C within tens of seconds. The present approach of building a resistive cell with highly stable materials and then delivering high power on demand through rapid thermal stimulation leads to a revolutionary route to high safety when batteries are not in use and high battery performance upon operation.
36 MATERIALS SCIENCE↗
Leveraging visible and near-infrared spectroelectrochemistry to calibrate a robust model for Vanadium(IV/V) in varying nitric acid and temperature levels
Spectroelectrochemistry and optimal design of experiments can be used to rapidly build accurate models for species quantification and enable a greater level of process awareness. Optical spectroscopy can provide vital elemental and molecular information, but several hurdles must be overcome before it can become a widely adopted analytical method for remote analysis in the nuclear field. Analytes with varying oxidation state, acid concentration, and fluctuating temperature must be efficiently accounted for to minimize time and resources in restrictive hot cell environments. The classic one-factor-at-a-time approach is not suitable for frequent calibration/maintenance operations in this setting. Therefore, a novel alternative was developed to characterize a system containing vanadium(IV/V) (0.01–0.1 M), nitric acid (0.1–4 M), and varying temperatures (20–45 °C). Here, spectroelectrochemistry methods were used to acquire a sample set selected by optimal design of experiments. This new approach allows for the accurate analysis of vanadium and HNO 3 concentration by leveraging UV–Vis–NIR absorption spectroscopy with robust and accurate chemometric models. The top model's root mean squared error of prediction percent values were 3.47%, 4.06%, 3.40%, and 10.9% for V(IV), V(V), HNO 3 , and temperature, respectively. These models, efficiently developed using the designed approach, exhibited strong predictive accuracy for vanadium and acid with varying oxidation states and temperature using only spectrophotometry, which advances current technology for real-world hot cell applications. Additionally, Nernstian analysis of the V(IV/V) standard potential was performed using traditional absorbance methods and multivariate curve resolution (MCR). The successful tests demonstrated that MCR Nernst tests may be valuable in highly convoluted spectral systems to better understand the redox processes' behavior.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
In-pile thermal conductivity of uranium dioxide at low burnup
In-pile thermal conductivity of uranium dioxide (UO 2 ) was investigated at low burnup levels (<0.2 kWd/kg-UO 2 ) to elucidate the concurrent effects of the fission damage and the thermal recovery. In-pile experiments were performed in the Halden reactor. The fuel centerline and the cladding temperatures were measured during the experiments, and the power level of specially designed test rodlets were also monitored. The uncertainty of the pellet-cladding gap's thermal resistivity was minimized with a liquid-metal bond, while comparable measurements were made in reference test rodlets without liquid metal bonding. The experimental data were analyzed using the inverse heat transfer approach. The heat conduction equation was solved by applying the measured temperature of the cladding as a boundary condition, and the calculated fuel centerline temperature was compared with the measured fuel centerline temperature to determine the relative matrix resistivity. Results showed that the in-pile matrix resistivity, the phonon-lattice interaction terms of the thermal conductivity, was ~1.5–2.5 times higher than its unirradiated value due to fission-induced damage. Finally, the in-pile annealing caused a significant recovery of the matrix resistivity, and the amount of recovery increased from ~20 to ~33%, while the annealing temperature increased from 700 to 1,000 °C.
11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
Path Integral Monte Carlo Simulations of Iron Plasmas (Final Technical Report)
This documents is the final technical report for our grant entitled "Path Integral Monte Carlo Simulations of Iron Plasmas" that focused on developing path integral Monte Carlo (PIMC) computer simulations. This techniques will be developed to study plasmas composed of heavier elements including iron and other third row elements. Equations of state (EOS) and transport properties will be derived in the regime of warm dense matter (WDM) and dense plasmas where existing first-principles methods cannot be applied. While standard density functional theory (DFT) has been used to accurately predict the structure of many solids and liquids up to temperatures on the order of 100,000 K, this method is not applicable at much higher temperature because the number of partially occupied electronic orbitals reaches intractably large numbers or the use of finite-temperature free energy functionals in orbital-free DFT introduces an uncontrolled approximation. Here we focus on PIMC methods that become more and more efficient with increasing temperatures and still include all electronic correlation effects. In this approach, electronic excitations increase the efficiency rather than reduce it. While it had commonly been assumed this method could only be applied to elements without core electrons, we showed that PIMC with free-particle nodes works well for first-row elements (PRL 108 (2012) 115502). Most recently, we extended the applicability range of all-electron PIMC to second-row elements by adopting localized nodal surfaces (PRL 115 (2015) 176403). To simulate third-row elements efficiently under WDM conditions, we propose a new method to remove core electrons by introducing pseudo-nodes. We explain our approach step by step and present preliminary results. We focus our method development on getting PIMC simulations of iron to work because of its fundamental importance for WDM and astrophysics. Then we move on to krypton and copper-doped beryllium, a ICF ablator material. We plan to continue working on key second-row material such as Na, Mg, MgO, Al, silica, and silicon-doped plastic ablators. Our collaborators at LLNL, will use our PIMC EOS data both as comparisons to existing semi-empirical, EOS-generating schemes, and as input for continuum radiation hydrodynamics simulations. We will establish an efficient pipeline from PIMC to macroscopic continuum studies of materials response. An emphasis will be placed on benchmarking such methods for plasmas of heavy elements at the very high temperatures (~100 eV) and low densities that are generated when Hohlraum radiation heats the ablator material in indirect drive laser experiments. Results from changes to the EOS will be of immeasurable importance to the designers at the National Ignition Facility (NIF) and at other facilities. Starting with our EOS of Cu-doped Be, our second collaborator at LLE, will perform real-time simulations of laser fusion experiments at the Omega laser and at the NIF to determine how sensitive the compression path depends on the ablator EOS. Since our collaborator also has experience in performing orbital-free DFT calculations, we propose to compare predictions from this method with PIMC results. In joint publications, we plan to analyze the accuracy of different free-energy functionals in order to understand why existing orbital-free DFT calculations do not predict compression peaks along the shock Hugoniot curve that we see with PIMC. The peaks are caused by the ionization of various electron shells. Their accurate characterization is important to compare with experimental results. We will break new ground by developing PIMC techniques that can simulate iron and all other third row elements in the plasma and WDM regimes. We introduce the concept of pseudo-nodes for the efficient treatment of the core-electrons. The EOS and transport properties will be derived and published online in the form of a new WDM database. Our PIMC EOS calculations will benchmark and possibly replace semi-analytical EOS tables like QEOS or SESAME, which will impact the hydrocode simulation community and will affect the design of NIF targets. Our PIMC results will help to improve the accuracy of orbital-free DFT simulations.
70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
Quantum Chemistry-Driven Machine Learning Approach for the Prediction of the Surface Tension and Speed of Sound in Ionic Liquids
Ionic liquids (ILs) have unique solvent properties and have thus garnered significant interest. However, exhaustive experimental determination of the physicochemical properties of ILs is unrealistic due to the large structural diversity of anions and cations, their high cost, the requirements of elevated temperature and pressure, and the time required. To circumvent these experimental costs, computational approaches to accurately calculate these properties have emerged. Here in the present study, we present a demonstration of two machine learning (ML) models for the prediction of two critical IL physical properties, the surface tension and the speed of sound, across a wide range of temperatures and pressures. The models make use of molecular descriptors derived from the COSMO-RS, a quantum chemical-based model. The ML models show excellent agreement with experimental observations, with an R2 value of 0.96–0.99 and RMSE of 1.71 mN/m and 16.12 m/s for the surface tension and speed of sound, respectively. This work paves the way for the development of COSMO-RS-informed ML models for the prediction of IL properties which can help to further optimize and accelerate technology development for ILs.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
Command of active and responsive elastomers by topological defects and patterns
The project resulted in the development of stimuli-responsive elastomer coatings formed by photopolymerized liquid crystal molecules. The molecular orientation of the liquid crystal elastomers is coupled to rubber-like elasticity. The project developed an approach to produce complex patterns of molecular orientation in elastomers by employing photopatterning technique based on plasmonic metamasks that convert unpolarized incoming light into a transmitted light beam with spatially-varying linear polarization. The polarization-modulated light beam aligns the film of azodye molecules, which serves as the substrate for liquid crystal elastomer coating. The alignment of the azodye molecules follows the polarization pattern with a phase shift of the alignment direction by 90 degrees. The azodye substrate imposes orientation of molecules in the adjacent liquid crystal layer which is preserved after the monomers are polymerized into a liquid crystal elastomer. By using differently aligned substrates one could produce various patterns of molecular orientation in the elastomer, which dictate the mechanical properties of the elastomers and their response to external stimuli such as temperature, humidity, and ultraviolet irradiation. In particular, the predesigned molecular orientation produces deterministically defined topography response of the liquid crystal coatings, in which their free surface changes from flat to either locally elevated or locally compressed, depending on whether the pre-inscribed molecular orientation is predesigned with a splay or bend deformation. The research established that the mechanism of this deterministic relation between the dynamic topography and pre-inscribed molecular orientation is rooted in the change of the tensorial order parameter that characterizes the degree of orientational order, and in the contraction/expansion of polymer molecules in response to the order parameter changes. In particular, lowering the order causes contraction of polymer globules. The work demonstrated that the dynamic topography of elastomer coatings with three-dimensional pattern of orientational order includes up and down motion of the material (along the normal to the coating) and also shifts in lateral directions. We demonstrate that the deterministic relationship between the orientational patterns and variations of coatings’ profile is caused by forces that are mathematically equivalent to active forces in the system of “pullers” or “pushers” in active matter, demonstrating universality of the out-of-equilibrium behavior. The project resulted in theoretical models that predictively describe the dynamic response of coatings. The topography of liquid crystal elastomers is sensitive to stimuli such as temperature, ultraviolet irradiation, and humidity. The applicability of the patterned approach to produce dynamic coatings was expanded from nematic elastomers to their smectic counterparts. The project combined a battery of imaging techniques to unveil the dynamic properties of the coatings, ranging from the state-of-the-art dynamic holographic microscopy to fluorescent confocal polarizing microscopy and polscope microscopy. The research uncovered potential applications of dynamic elastomer coatings, such as control placement of colloidal particles, engineering of living tissues with alignment patterns of cells that follow the orientational order of elastomer coatings. The approach developed in the project can be used to design programmable dynamic coatings with functionalities that mimic biological tissues such as skin.
36 MATERIALS SCIENCE↗
Microstructural Modeling of the α + β Phase in Ti-6Al-4V: A Diffusion-Based Approach
Complex heat treatment operations and advanced manufacturing processes such as laser or electron-beam welding will see the metallic workpiece experience a considerable range of temperatures and heating/cooling rates. These intrinsic conditions will have a significant bearing upon the microstructure of the material, and in turn upon the thermo-mechanical properties. In this work, a diffusion-based approach to model the growth and shrinkage of precipitates in the alpha + beta field of the common titanium alloy Ti-6Al-4V is established. Further, the numerical model is extended using a JMA-type approach to explore the dependency of the beta-transus temperature on extremely high heating rates, whereby dissolution alone is too slow to accurately describe the alpha to beta-phase transformation. Experimental heat treatments at rates of 5, 50, and 500 °C/s were performed, and metallographic analysis of the samples was used to validate the numerical modeling framework predictions for lamellar shrinkage, while data from the literature has been used to evaluate the numerical modeling framework for the growth of equiaxed microstructures. The agreement between measurements and numerical predictions was found to be good.
36 MATERIALS SCIENCE↗
Enumeration as a Tool for Structure Solution: A Materials Genomic Approach to Solving the Cation-Ordered Structure of Na 3 V 2 (PO 4 ) 2 F 3
While powder diffraction methods are routinely utilized to optimize structural models for compounds whose crystal structures are known, the determination of unknown structures is far more challenging. When the unknown structure is large, structure solution can become a virtually intractable problem using standard structure solution methodologies, especially when the space group cannot be unambiguously resolved. One such system is the promising Na-ion battery cathode material Na 3 V 2 (PO 4 ) 2 F 3 whose high temperature and room temperature structures were previously solved, but whose more complex low-temperature structure could not be determined. Here, a novel materials genomic approach is demonstrated for the solution of the unknown 100 K structure of Na 3 V 2 (PO 4 ) 2 F 3 in which enumeration methods are first used to generate a large number (~3,000) of trial structures based on plausible orderings of Na ions and then automated Rietveld refinements are carried out to optimize each of these trial structures. Based on both the analysis of the ensemble of optimized trial structures and the density functional theory energy minimization of selected trial structures, the 100 K structure of Na 3 V 2 (PO 4 ) 2 F 3 is best described as belonging to the space group A2 1 am with unit cell dimensions of a = 9.01928(4), b = 27.1379(1), c = 10.73307(5). The 100 K unit cell has a large volume of 2627.07(2) Å 3 with Z = 12 and 33 independent crystallographic sites (9 Na, 3 V, 3 P, 12 O, and 6 F) that is 3x and 6x larger than the room- and high-temperature polymorphs of this phase, respectively. Finally, the novel methods described here will be generally applicable for the solution of the complex cation-ordered structures that commonly occur for battery materials.
36 MATERIALS SCIENCE↗
Computational Insights into Phase Equilibria Between Wide-Gap Semiconductors and Contact Materials
Novel wide-band-gap semiconductors are needed for next-generation power electronics, but there is a gap between a promising material and a functional device. Finding stable (metal) contacts is one of the major challenges that is currently dealt with mainly via trial and error. Herein, we computationally investigate the thermochemistry and phase coexistence at the junction between three wide-gap semiconductors, ..beta..-Ga2O3, GeO2, and GaN, and possible contact materials. The pool of possible contacts includes 47 elemental metals and a set of 4 common, n-type transparent conducting oxides (ZnO, TiO2, SnO2, and In2O3). We use first-principles thermodynamics to model the Gibbs free energies of chemical reactions as a function of gas pressure (pO2/pN2) and equilibrium temperature. We deduce whether a semiconductor/contact interface will be stable at relevant conditions or a chemical reaction between them is to be expected, possibly influencing the long-term reliability and performance of devices. We generally find that most elemental metals tend to oxidize or nitridize and form various interface oxide/nitride layers. Exceptions include select late- and post-transition metals and, in the case of GaN, also the alkali metals, which are predicted to exhibit stable coexistence, although in many cases at relatively low gas partial pressures. Similar is true for the transparent conducting oxides, for which, in most cases, we predict a preference toward forming ternary oxides when in contact with ..beta..-Ga2O3 and GeO2. The only exception is SnO2, which we find to form stable contacts with both oxides. Finally, we show how the same approach can be used to predict gas partial pressure vs temperature phase diagrams to help direct synthesis of ternary compounds. We believe these results provide a valuable guidance in selecting contact materials to wide-gap semiconductors and suitable growth conditions.
contact materials↗
Stoichiometry dependent properties of cerium hydride: An active learning developed interatomic potential study
Cerium hydride has a variety of interesting properties, including a known lattice contraction and densification with increasing hydrogen content. However, precise stoichiometric control is not experimentally straightforward and ab initio approaches are not computationally feasible for many properties such as melting and low temperature diffusion. Therefore, we develop a machine-learned interatomic potential for cerium hydride that is valid for H to Ce ratios from 2.0 to 3.0. A query-by-committee active learning approach is used to develop the training set. Leveraging classical molecular dynamics simulations, we assess a range of properties and provide fundamental mechanisms for the trends with stoichiometry. Finally, a majority of the properties follow the trend of lattice contraction, being governed by the stronger lattice binding induced by adding octahedral atoms.
36 MATERIALS SCIENCE↗