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The conclusions of the application of first principles model to spacecraft operations are: the first principles of Bi-phasic electrode presented model provides an explanation for many behaviors on voltage fading on LEO cycling.
We examine the accuracy of density prediction by the first principles model Thermosphere Ionosphere Electrodynamics General Circulation Model (TIEGCM) developed by the National Center for Atmospheric Research and compare it to the accuracy of three empirical models: Jacchia 71, the Naval Research Laboratory Mass Spectrometer Incoherent Scatter Extended 2000 (NRLMSIS), Jacchia 1971, and Jacchia-Bowman 2008. Comparisons are made for three large storms: the October 2003 storm, the March 2013 storm, and the March 2015 storm. To evaluate the accuracy of these models we use tracking data for nine space objects in low Earth orbit. Additionally, we evaluate the accuracy of the TIEGCM and NRLMSIS with data from high precision accelerometers on the Challenging Minisatellite Payload (CHAMP) and Gravity field and Circulation Explorer (GOCE) satellites. The goal is to assess the use of a first principles model as a potential tool for forecasting satellite drag during large magnetic storms. For the storms considered, we found the TIEGCM, JB2008, and NRLMSIS models to be substantially more accurate than the Jacchia 71 model. The accuracies of the TIEGCM and JB2008 models were similar, but overall, the TIEGCM was more accurate. We found smaller differences for TIEGCM versus CHAMP than for NRLMIS for the Halloween Storm, and smaller differences than results published for JB2008 and the assimilative model HASDM. The empirical models are at present more practical for operational purposes, but the TIEGCM, developed as a research model, with a greater focus on operational use offers the potential for improved utility during stressing conditions.
We investigate W–ZrC interfaces using first-principles calculations based on the density functional theory. There have been theoretical and experimental studies exploring W–ZrC interfaces, however, the debate regarding the most stable interface continues to persist. In this study, we systematically simulated various W–ZrC interfaces merging W and ZrC surfaces with different orientations. Subsequently, we evaluated their stabilities and explained the corresponding stabilities in terms of the nature of bonding and charge-transfer processes at the interface. We find ZrC(111)–W(110) is the most stable interface with higher adhesive energy than the other interfaces. The additional stability associated with the ZrC(111)–W(110) results from significant interface reconstruction. Three layers of W and ZrC adjacent to the interface are involved in the charge-transfer process leading to stronger ionic bonds in ZrC(111)–W(110) as compared to the other potential candidate: ZrC(100)–W(100). The C and W atoms are found to be displaced from their symmetric position during the reconstruction process at the interface to facilitate stronger bonds with shorter W–C and W–Zr bonds in ZrC(111)–W(110) as compared to ZrC(100)–W(100). This leads to stronger covalent bonds in ZrC(111)–W(110) than that in ZrC(100)–W(100). Therefore, we conclude that the stronger covalent and ionic forces in ZrC(111)–W(110) than those in ZrC(100)–W(100) are responsible for making ZrC(111)–W(110) to be the most stable interface. In conclusion, this study addresses the long-standing question of the most stable W–ZrC interface and derives a number of implications for other W-transition metal carbide interfaces which are potential candidates for improving the mechanical properties of plasma facing materials.
To begin, thermoelectric effects, measured by the Seebeck coefficients, refer to the phenomena in which a temperature difference or gradient imposed across a thermoelectric material induces an electrical potential difference or gradient, and vice versa, enabling the direct conversion of thermal and electric energies. All existing first-principles calculations of Seebeck coefficients have been based on the Boltzmann kinetic transport theory. In this work, we present a fundamentally different method for the first-principles calculations of Seebeck coefficients without using any assumptions of the electron-scattering mechanism, being in contrast to the traditional theory by Cutler and Mott that shows the dependence of the Seebeck coefficient on the scattering mechanisms. It is shown that the Seebeck coefficient is a well-defined thermodynamic quantity that can be determined from the change in the chemical potential of electrons induced by the temperature change and thus can be computed solely based on the electronic density of states through first-principles calculations at different temperatures. The proposed approach is demonstrated using the prototype PbTe and SnSe thermoelectric materials.
Small metal clusters are of fundamental scientific interest and of tremendous significance in catalysis. These nanoscale clusters display diverse geometries and structural motifs depending on the cluster size; a knowledge of this size-dependent structural motifs and their dynamical evolution has been of longstanding interest. Given the high computational cost of first-principles calculations, molecular modeling and atomistic simulations such as molecular dynamics (MD) has proven to be an important complementary tool to aid this understanding. Classical MD typically employ predefined functional forms which limits their ability to capture such complex size-dependent structural and dynamical transformation. Neural Network (NN) based potentials represent flexible alternatives and in principle, well-trained NN potentials can provide high level of flexibility, transferability and accuracy on-par with the reference model used for training. A major challenge, however, is that NN models are interpolative and requires large quantities (similar to 10 4 or greater) of training data to ensure that the model adequately samples the energy landscape both near and far-from-equilibrium. A highly desirable goal is minimize the number of training data, especially if the underlying reference model is first-principles based and hence expensive. In this work, we introduce an active learning (AL) scheme that trains a NN model on-the-fly with minimal amount of first-principles based training data. Our AL workflow is initiated with a sparse training dataset (similar to 1 to 5 data points) and is updated on-the-fly via a Nested Ensemble Monte Carlo scheme that iteratively queries the energy landscape in regions of failure and updates the training pool to improve the network performance. Using a representative system of gold clusters, we demonstrate that our AL workflow can train a NN with similar to 500 total reference calculations. Using an extensive DFT test set of similar to 1100 configurations, we show that our AL-NN is able to accurately predict both the DFT energies and the forces for clusters of a myriad of different sizes. Our NN predictions are within 30 meV/atom and 40 meV/angstrom of the reference DFT calculations. Moreover, our AL-NN model also adequately captures the various size-dependent structural and dynamical properties of gold clusters in excellent agreement with DFT calculations and available experiments. We finally show that our AL-NN model also captures bulk properties reasonably well, even though they were not included in the training data.
A multi-tiered cost analysis is performed to estimate full costs of a nuclear power plant (NPP) based on sodium-cooled fast reactor (SFR) technology. To address the lack of fully transparent cost estimations from past undertakings for NPPs, we have developed a detailed and first-principles-based cost estimate for a generalized SFR NPP. Our intent is to achieve a high degree of transparency with our cost assumptions and develop a cost model that is flexible and easily extendable to variations in NPP design and other nuclear reactor types. Furthermore, we strive to achieve a clear organization of costs and complete identification of key cost drivers based on first principles. To this end, the cost results of our analysis as given in Table 24 and Table 25 are organized and categorized into a code of accounts (COA) under development at Idaho National Laboratory (INL). Varying degrees of first-principles methods are employed, such as design for manufacture and assembly® (DFMA® ), to elucidate costs in all process levels of the plant equipment, buildings and site structures, personnel, and other miscellaneous but significant cost elements. These approaches have been successfully applied in past cost analysis projects and are designed to enable rapid and flexible cost estimation. Application of these techniques for evaluating NPP costs is similar in concept to the full, detailed estimation of construction and fabrication costs determined in a later stage of NPP development. Note that our approach tries to avoid use of other past analysis results and data such as those from the legacy Energy Economic Data Base (EEDB) Program, as these resources are based on historical NPP costs and thus may not be indicative of new reactor technologies or construction and fabrication/manufacturing techniques. However, we provide a comparison of our SFR NPP cost results in Table 90 against those included in the EEDB for a representative pressurized water reactor (PWR).
Recently, first-principles calculations based on density functional theory have been widely used to predict the temperature-dependent infrared spectrum of polar materials, but the calculations are usually limited to the harmonic frequency (0 K) and three-phonon scattering damping for the zone-center infrared-active optical phonon modes, and fail to predict the high-temperature infrared optical properties of materials such as sapphire (α–Al 2 O 3 ), GaAs, TiO 2 , etc., due to the neglect of high-order phonon scattering damping and phonon frequency shift. In this work, we implemented first-principles calculations to predict the temperature-dependent infrared dielectric function of polar materials by including four-phonon scattering and phonon frequency shift. The temperature-dependent phonon damping by including three- and four-phonon scattering as well as the phonon frequency shift by including cubic and quartic anharmonicity and the thermal expansion effect are calculated based on anharmonic lattice dynamics method. The infrared dielectric function of α–Al 2 O 3 is parameterized, and then the temperature-dependent infrared optical reflectance is determined. We find that our predictions agree better with the experimental data than the previous density functional theory-based methods. Lastly, this work will help to effectively predict the thermal radiative properties of polar materials at elevated temperature, which is generally difficult to measure, and will enable predictive design of new materials for radiative applications.
A predictive model based on first principles calculations has been proposed to study the solid–liquid equilibria comprising of metal complexes and ionic liquids.
Here, we present a consistent first-principles methodology to study both direct and phonon-assisted Auger-Meitner recombination (AMR) in indirect-gap semiconductors that we apply to investigate the microscopic origin of AMR processes in silicon. Our results are in excellent agreement with experimental measurements and show that phonon-assisted contributions dominate the recombination rate in both n-type and p-type silicon, demonstrating the critical role of phonons in enabling AMR. We also decompose the overall rates into contributions from specific phonons and electronic valleys to further elucidate the microscopic origins of AMR. Our results highlight potential pathways to modify the AMR rate in silicon via strain engineering.
A comprehensive thermochemical database is constructed based on high–throughput first-principles phonon calculations of over 3000 atomic structures in limited concentrations in Ni, Fe, and Co alloys involving a total of 26 elements including Al, B, C, Cr, Cu, Hf, La, Mn, Mo, N, Nb, O, P, Re, Ru, S, Si, Ta, Ti, V, W, Y, and Zr, providing thermochemical data largely unavailable from existing experiments. Here, the database can be employed to predict the equilibrium phase compositions and fractions directly from first-principles by minimizing the chemical potential of a multicomponent system with a fixed overall chemical composition and a fixed temperature. It is applied to the additively manufactured nickel-based IN718 superalloy to analyze the phase evolution with temperature. IN718 is known for its great performance in tensile, fatigue, creep, and rupture strength, combined with easy fabrication and corrosion resistance. In particular, we successfully predicted the formation of L1 0 -FeNi, γ’-Ni 3 (Fe,Al), α-Cr, δ-Ni 3 (Nb,Mo), γ”-Ni 3 Nb, and η-Ni 3 Ti at low temperatures (below 680 K), γ’-Ni 3 Al, δ-Ni 3 Nb, γ”-Ni 3 Nb, α-Cr, and γ-Ni(Fe,Cr,Mo) at intermediate temperatures (between 680 and 1140 K), and δ-Ni 3 Nb and γ-Ni(Fe,Cr,Mo) at high temperatures (above 1140 K) in IN718. These predictions are validated by EDS mapping of compositional distributions and corresponding identifications of phase distributions. The database is expected to be a valuable source for future thermodynamic analysis and microstructure prediction of alloys involving the 26 elements.
In “Interfacial structures and acidity constants (pKa) of goethite from first principles molecular dynamics simulations,” authors Y. Zhang, X. Lui, J. Cheng, and X. Lu apply First Principles molecular dynamics (FPMD, also called Density Functional Theory MD, DFT/MD, or ab initio MD, AIMD), to evaluable the complete set of acidity constants (pK a ) of the hydroxyl groups on the most prominent goethite crystal facets. The pK a of these OH and OH$^+_2$ groups are compared with available data from the multisite complexation (MUSIC) model traditionally used to estimate pK a on mineral surfaces. The authors have presented eloquent rationale for the importance and implications of understanding goethite acidity constants in room temperature geochemistry settings. In this paper, I focus on the computational aspects, the strengths of FPMD, and its possibilities.
Highlights: • Oxygen adsorption behavior on Nb{sub 3}Si(111) is studied by using first-principles. • O atom tends to be adsorbed on the NbSi bridge site. • The capacity of oxidation follow the order of Cr > Al > Si. • Cr can improve the Nb{sub 3}Si’s oxidation resistance because of Cr d-orbital effect. - Abstract: The oxidation resistance plays an important role in high-temperature ceramics. Although transition metal silicides exhibit the better oxidation behavior, the improvement of oxidation resistance is still a great challenge for their applications. Here, we apply first-principles calculations to investigate the oxidation mechanism and the influence of alloying elements (Cr and Al) on the oxidation resistance of Nb{sub 3}Si(111) surface. The calculated results show that the O atom is adsorbed on the NbSi-bridge site because of the charge interaction between O-2p state, Si-3p state and Nb-4d state. We further find that Cr-doping is more thermodynamically stable than that of Al-doping. In particular, the capacity of oxidation resistance follows the order of Cr > Al > Si. Finally, we conclude that Cr-doping can effectively improve the oxidation resistance of Nb{sub 3}Si(111) surface. The calculated electronic structure shows that Cr d-orbital plays a crucial role in oxidation resistance.
The vibrational thermal conductances (G) across GaN-AlN interfaces are computed using a nonequilibrium Green's function formalism in the harmonic limit with bulk and interfacial interatomic force constants (IFCs) fully from density functional theory. Several numerical methods and supercell configurations are employed to examine the sensitivity of G to variances of IFCs. In particular, the effects of supercell size, the enforcement of symmetry constraints, and truncation of IFCs near the interface, and atomic relaxation on phonon transmission and conductance are explored. Our fully first-principles calculations are compared with common approximations and measured G values inferred from thermal conductivity measurements for GaN-AlN superlattices. Here, our calculated value, G~300MWm -2 K -1 , is nearly half that from measurements. This discrepancy is critically analyzed in terms of the physical assumptions of the calculations and the derivation of the experimental values. This work provides guidelines to determine “physically correct” sets of interfacial IFCs from first principles for thermal conductance calculations using minimal computational resources. It also contributes toward developing predictive calculations and a more complete picture of thermal conduction across interfaces, a step toward first-principles multiscale thermal transport.
The Kubo–Greenwood equation, in combination with the first-principles Korringa–Kohn–Rostoker coherent potential approximation (KKR-CPA) can be used to calculate the DC residual resistivity of random alloys at T = 0 K. We implemented this method in a multiple scattering theory based ab initio package, MuST, and applied it to the ab initio study of the residual resistivity of the high entropy alloy Al x CoCrFeNi as a function of x. The calculated resistivities are compared with experimental data. We also predict the residual resistivity of refractory high entropy alloy MoNbTaV x W. Furthermore, the calculated resistivity trends are also explained using theoretical arguments.
The formation possibility of (Hf 0.2 Zr 0.2 Ta 0.2 Nb 0.2 Ti 0.2 )C high-entropy ceramic (HHC-1) was first analyzed by the first-principles calculations, and then, it was successfully fabricated by hot-pressing sintering technique at 2073 K under a pressure of 30 MPa. The first-principles calculation results showed that the mixing enthalpy and mixing entropy of HHC-1 were -0.869 ± 0.290 kJ/mol and 0.805R, respectively. The experimental results showed that the as-prepared HHC-1 not only had an interesting single rock-salt crystal structure of metal carbides but also possessed high compositional uniformity from nanoscale to microscale. By taking advantage of these unique features, it exhibited extremely high nanohardness of 40.6 ± 0.6 GPa and elastic modulus in the range from 514 ± 10 to 522 ± 10 GPa and relatively high electrical resistivity of 91 ± 1.3 μΩ·cm, which could be due to the presence of solid solution effects.
A material’s interaction with light is highly relevant in the design of nanoelectronic devices such as photodiodes, solar cells, photocatalytic cells, phototransistors, and photodetectors. The interaction of a material with light can be altered by mechanical deformation. Fine tuning of the optical properties can be achieved by mechanical bending that alters the electronic structure. Optical properties strongly depend on band gaps, therefore any alteration in the band structure results in a changed optical response of the material. The impact of bending was explored in this project. The goal of this project was to assess the impact of mechanical bending of two-dimensional transition metal dichalcogenides on their optoelectronic properties, using first-principles methods. These first-principles approximations are largely built upon many-body theory for the optical properties of magnetic and topological nanoribbons. GW-BSE is standard for optical absorption, but it is less practical for collective excitations as it was shown in model systems. Time-dependent density functional theory, however, has better promises for collective excitations in low-dimensional materials.
Scattering of carriers with ionized impurities governs charge transport in doped semiconductors. However, electron interactions with ionized impurities cannot be fully described with quantitative first-principles calculations, so their understanding relies primarily on simplified models. Here we show an ab initio approach to compute the interactions between electrons and ionized impurities or other charged defects. It includes the short- and long-range electron-defect (e-d) interactions on equal footing and allows for efficient interpolation of the e-d matrix elements. Here we combine the e-d and electron-phonon interactions in the Boltzmann transport equation to compute the carrier mobilities in doped silicon over a wide range of temperature and doping concentrations, seamlessly spanning the defect- and phonon-limited transport regimes. The individual contributions of the defect- and phonon-scattering mechanisms to the carrier relaxation times and mean-free paths are analyzed. Our method provides a powerful tool to study electronic interactions in doped materials. It broadens the scope of first-principles transport calculations, enabling studies of a wide range of doped semiconductors and oxides with application to electronics, energy, and quantum technologies.
Optically active spin defects in solids are promising platforms for quantum technologies. In this work, we present a first-principles framework to investigate intersystem crossing processes, which represent crucial steps in the optical spin-polarization cycle used to address spin defects. Considering the nitrogen-vacancy center in diamond as a case study, we demonstrate that our framework effectively captures electron correlation effects in the calculation of many-body electronic states and their spin-orbit coupling and electron-phonon interactions, while systematically addressing finite-size effects. We validate our predictions by carrying out measurements of fluorescence lifetimes, finding excellent agreement between theory and experiments. The framework presented here provides a versatile and robust tool for exploring the optical cycle of varied spin defects entirely from first principles.