Work function and surface stability of tungsten-based thermionic electron emission cathodes

Materials that exhibit a low work function and therefore easily emit electrons into vacuum form the basis of electronic devices used in applications ranging from satellite communications to thermionic energy conversion. W-Ba-O is the canonical materials system that functions as the thermionic electron emitter used commercially in a range of high power electron devices. However, the work functions, surface stability, and kinetic characteristics of a polycrystalline W emitter surface are still not well understood or characterized. In this study, we examined the work function and surface stability of the eight lowest index surfaces of the W-Ba-O system using Density Functional Theory methods. We found that under the typical thermionic cathode operating conditions of high temperature and low oxygen partial pressure, the most stable surface adsorbates are Ba-O species with compositions in the range of Ba0.125O to Ba0.25O per surface W atom, with O passivating all dangling W bonds and Ba creating work function-lowering surface dipoles. Wulff construction analysis reveals that the presence of O and Ba significantly alters the surface energetics and changes the proportions of surface facets present under equilibrium conditions. Analysis of previously published data on W sintering kinetics suggests that fine W particles in the size range of 100-500 nm may be at or near equilibrium during cathode synthesis, and thus may exhibit surface orientation fractions well-described by the calculated Wulff construction

Predicting the thermodynamic stability of perovskite oxides using machine learning models

Perovskite materials have become ubiquitous in many technologically relevant applications, ranging from catalysts in solid oxide fuel cells to light absorbing layers in solar photovoltaics. The thermodynamic phase stability is a key parameter that broadly governs whether the material is expected to be synthesizable, and whether it may degrade under certain operating conditions. Phase stability can be calculated using Density Functional Theory (DFT), but the significant computational cost makes such calculation potentially prohibitive when screening large numbers of possible compounds. In this work, we developed machine learning models to predict the thermodynamic phase stability of perovskite oxides using a dataset of more than 1900 DFT-calculated perovskite oxide energies. The phase stability was determined using convex hull analysis, with the energy above the convex hull (Ehull) providing a direct measure of the stability. We generated a set of 791 features based on elemental property data to correlate with the Ehull value of each perovskite compound. For classification, the extra trees algorithm achieved the best prediction accuracy of 0.93 (+/- 0.02), with an F1 score of 0.88 (+/- 0.03). For regression, leave-out 20% cross-validation tests with kernel ridge regression achieved the minimal root mean square error (RMSE) of 28.5 (+/- 7.5) meV/atom between cross-validation predicted Ehull values and DFT calculations, with the mean absolute error (MAE) in cross-validation energies of 16.7 (+/- 2.3) meV/atom. We further validated our model by predicting the stability of compounds not present in the training set and demonstrated our machine learning models are a fast and effective means of obtaining qualitatively useful guidance for a wide-range of perovskite oxide stability, potentially impacting materials design choices in a variety of technological applications.Comment: 32 pages, 6 figures, 5 table

Materials Discovery of Stable and Nontoxic Halide Perovskite Materials for High-Efficiency Solar Cells

Two critical limitations of organic-inorganic lead halide perovskite materials for solar cells are their poor stability in humid environments and inclusion of toxic lead. In this study, high-throughput density functional theory (DFT) methods are used to computationally model and screen 1845 halide perovskites in search of new materials without these limitations that are promising for solar cell applications. This study focuses on finding materials that are comprised of nontoxic elements, stable in a humid operating environment, and have an optimal bandgap for one of single junction, tandem Si-perovskite, or quantum dot-based solar cells. Single junction materials are also screened on predicted single junction photovoltaic (PV) efficiencies exceeding 22.7%, which is the current highest reported PV efficiency for halide perovskites. Generally, these methods qualitatively reproduce the properties of known promising nontoxic halide perovskites that have either been experimentally evaluated or predicted from theory. From a set of 1845 materials, 15 materials pass all screening criteria for single junction cell applications, 13 of which have not been previously investigated, such as (CH3NH3)0.75Cs0.25SnI3, ((NH2)2CH)Ag0.5Sb0.5Br3, CsMn0.875Fe0.125I3, ((CH3)2NH2)Ag0.5Bi0.5I3, and ((NH2)2CH)0.5Rb0.5SnI3. These materials, together with others predicted in this study, may be promising candidate materials for stable, highly efficient, and non-toxic perovskite-based solar cells

Nanoscale Voltage Enhancement at Cathode Interfaces in Li-ion Batteries

Interfaces are ubiquitous in Li-ion battery electrodes, occurring across compositional gradients, regions of multiphase intergrowths, and between electrodes and solid electrolyte interphases or protective coatings. However, the impact of these interfaces on Li energetics remains largely unknown. In this work, we calculated Li intercalation-site energetics across cathode interfaces and demonstrated the physics governing these energetics on both sides of the interface. We studied the olivine/olivine-structured LixFePO4/LixMPO4 (x=0 and 1, M=Co, Ti, Mn) and layered/layered-structured LiNiO2/TiO2 interfaces to explore different material structures and transition metal elements. We found that across an interface from a high- to low-voltage material the Li voltage remains constant in the high-voltage material and decays approximately linearly in the low-voltage region, approaching the Li voltage of the low-voltage material. This effect ranges from 0.5-9nm depending on the interfacial dipole screening. This effect provides a mechanism for a high-voltage material at an interface to significantly enhance the Li intercalation voltage in a low-voltage material over nanometer scale. We showed that this voltage enhancement is governed by a combination of electron transfer (from low- to high-voltage regions), strain and interfacial dipole screening. We explored the implications of this voltage enhancement for a novel heterostructured-cathode design and redox pseudocapacitors

Origins of Large Voltage Hysteresis in High Energy-Density Metal Fluoride Lithium-Ion Battery Conversion Electrodes

Metal fluoride and oxides can store multiple lithium-ions through conversion chemistry to enable high energy-density lithium-ion batteries. However, their practical applications have been hindered by an unusually large voltage hysteresis between charge and discharge voltage-profiles and the consequent low energy efficiency (< 80%). The physical origins of such hysteresis are rarely studied and poorly understood. Here we employ in situ X-ray absorption spectroscopy (XAS), transmission electron microscopy (TEM), density-functional-theory (DFT) calculations, and galvanostatic intermittent titration technique (GITT) to first correlate the voltage profile of iron fluoride ($FeF_3$), a representative conversion electrode material, with evolution and spatial distribution of intermediate phases in the electrode. The results reveal that, contrary to conventional belief, the phase evolution in the electrode is symmetrical during discharge and charge. However, the spatial evolution of the electrochemically active phases, which is controlled by reaction kinetics, is different. We further propose that the voltage hysteresis in the $FeF_3$ electrode is kinetic in nature. It is the result of Ohmic voltage drop, reaction overpotential, and different spatial distributions of electrochemically-active phases (i.e. compositional inhomogeneity). Therefore, the large hysteresis can be expected to be mitigated by rational design and optimization of material microstructure and electrode architecture to improve the energy efficiency of lithium-ion batteries based on conversion chemistry

The Challenges of Nuclear Learning in South Asia

Published as a contributed paper for "Nuclear Learning in South Asia: The Next Decade" (2014).The sustainability of strategic stability in South Asia remains of the highest importance to U.S. national security policy. The South Asian Nuclear Learning project was accordingly conceived to examine the region’s nuclear experiences after the 1998 tests. The end of the first decade (1998-2008) represented a good starting point. Later, the project expanded to further analyze the nuclear learning curve in the next decade, when security environment and technological innovations undertook major shifts. The National Nuclear Security Administration sponsored this research, which involved selected scholars and experts from Pakistan, India and United States. Some of these contributors also helped shape their state’s nuclear decisions in the earlier period following the nuclear tests