How can we ground Frontiers Models for Biological Research to Domain Knowledge, First Principles, and Constraints?
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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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First Principle based Thermal Conductivity Modeling of Metal Alloys with Applications on Uranium Alloys
Thermal conductivity is an important materials property related to heat transport, which is essential to many applications, ranging from thermoelectrics to nuclear reactor materials. High- quality thermal conductivity data is critical to these materials and their associated technologies, including the nuclear fuel materials like traditional oxide fuels and metallic uranium (U) fuels, e.g. U-Zr and U-Mo alloys. And thermal conductivity modeling is widely used to interpolate or extrapolate experimental data, to obtain high-quality thermal conductivity data over wide temperature and composition range, and to understand the impacts of different factors including defects and microstructures. However, a general thermal conductivity model for metal alloys which can work regrading different phase components is still missing. Also, for U alloys, a thermal conductivity model working with different phases is needed. Therefore, in this work, we developed thermal conductivity models for metal alloys, based on ab-initio calculations, semi-classical physics rules, and limited experimental data. The goals of these models are to help obtain high- quality thermal conductivity data within a little experimental input as possible, have models that are extendable to varying microstructures, including different types of irradiation effects, and provide mechanistic understanding of heat transfer in the modeled alloys. In this work, our model solves several challenges in the development. The DFT-BTE approach is applied to decrease the reliance on experimental data and make the model extendable to composition changes and defects. A practical and efficient way to combine the DFT inputs with physics rules is pointed out in this work too. A staged approach, which starts from simple cases of elemental metals, then extends to solid solutions, different compound phases, and multi-phase mixtures, is presented to work with the metal alloys in different phase components. Our models are demonstrated respectively on aU for elemental metal model, on U-Zr and U-Mo alloys in aU temperature range for multi-phase mixture model, on high-temperature U-Zr, U-Nb, and U-Mo alloys in the body-centered cubic phase for concentrated solid solution model, and on irradiated U-Mo alloys for irradiated metal alloy model. All models show great agreement with experimental data. In these demonstrations, our model shows its advantages compared to previous empirical fitting model. Our model requires fewer experimental data, due to the inputs from DFT. The quantitative insights into the different physical factors are provided in our model, as it incorporates the electron and phonon scattering mechanisms. Our model also can be extended to incorporate the contributions of point defects, grain boundaries, and noble gas bubbles, to integrate their effects on heat transfer. This model can serve as both a foundation for understanding the more complex thermal conductivity of realistic U alloy fuels and a useful tool to guide further modeling of thermal conductivity to aid materials and device design.
11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
Optical Response and Transport in Condensed and Warm Dense Matter from First Principles
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Robinson, Brian Patrick [Sandia National Laborator↗
Validation of High-Resolution CFD Method for Slosh Damping Extraction of Baffled Tanks
Determination of slosh damping is a very challenging task as there is no analytical solution. The damping physics involve the vorticity dissipation which requires the full solution of the nonlinear Navier-Stokes equations. As a result, previous investigations and knowledge were mainly carried out by extensive experimental studies. A Volume-Of-Fluid (VOF) based CFD program developed at NASA MSFC was applied to extract slosh damping in a baffled tank from the first principle. First, experimental data using water with subscale smooth wall tank were used as the baseline validation. CFD simulation was demonstrated to be capable of accurately predicting natural frequency and very low damping value from the smooth wall tank at different fill levels. The damping due to a ring baffle at different liquid fill levels from barrel section and into the upper dome was then investigated to understand the slosh damping physics due to the presence of a ring baffle. Based on this study, the Root-Mean-Square error of our CFD simulation in estimating slosh damping was less than 4.8%, and the maximum error was less than 8.5%. Scalability of subscale baffled tank test using water was investigated using the validated CFD tool, and it was found that unlike the smooth wall case, slosh damping with baffle is almost independent of the working fluid and it is reasonable to apply water test data to the full scale LOX tank when the damping from baffle is dominant. On the other hand, for the smooth wall, the damping value must be scaled according to the Reynolds number. Comparison of experimental data, CFD, with the classical and modified Miles equations for upper dome was made, and the limitations of these semi-empirical equations were identified.
Yang, H. Q.↗
Validation of High-Resolution CFD Method for Slosh Damping Extraction of Baffled Cryogenic Propellant Tanks
Propellant slosh is a potential source of disturbance critical to the stability of space vehicles. The slosh dynamics are typically represented by a mechanical model of a spring-mass-damper. This mechanical model is then included in the equation of motion of the entire vehicle for Guidance, Navigation and Control analysis. A Volume-Of-Fluid (VOF) based Computational Fluid Dynamics (CFD) program developed at MSFC was applied to extract slosh damping in the baffled tank from the first principle. First the experimental data using water with sub-scale smooth wall tank were used as the baseline validation. It is demonstrated that CFD can indeed accurately predict low damping values from the smooth wall at different fill levels. The damping due to a ring baffles at different depths from the free surface was then simulated, and fairly good agreement with experimental measurement was observed. Comparison with an empirical correlation of Miles equation is also made.
Yang, H. Q.↗
Gravitational Potential and Non-relativistic Lagrangian in Modified Gravity with Varying G
We have recently shown that the baryonic Tully-Fisher (BTF) and Faber-Jackson (BFJ) relations imply that the gravitational "constant" G in the force law vary with acceleration alpha as 1/alpha . Here we derive the converse from first principles. First we obtain the gravitational potential for all accelerations and we formulate the Lagrangian for the central-force problem. Then action minimization implies the BTF/BFJ relations in the deep MOND limit as well as weak-field Weyl gravity in the Newtonian limit. The results show how we can properly formulate a nonrelativistic conformal theory of modified dynamics that reduces to MOND in its low-acceleration limit and to Weyl gravity in the opposite limit. An unavoidable conclusion is that alpha-0 , the transitional acceleration in modified dynamics, does not have a cosmological origin and it may not even be constant among galaxies and galaxy clusters.
Christodoulou, Dimitris M.↗
Origin of the magnetic and orbital ordering in α-Sr 2 CrO 4
Motivated by recent experimental progress in transition metal oxides with the K 2 NiF 4 structure, in this study we investigate the magnetic and orbital ordering in α-Sr 2 CrO 4 . Using first principles calculations, first we derive a three-orbital Hubbard model, which reproduces the ab initio band structure near the Fermi level. The unique reverse splitting of t 2g orbitals in α-Sr 2 CrO 4 , with the 3d 2 electronic configuration for the Cr 4+ oxidation state, opens up the possibility of orbital ordering in this material. Using real-space Hartree-Fock for multi-orbital systems, we constructed the ground state phase diagram for the two dimensional compound α-Sr 2 CrO 4 . We found stable ferromagnetic, antiferromagnetic, antiferro-orbital, and staggered orbital stripe ordering in robust regions of the phase diagram. Furthermore, using the density matrix renormalization group method for two-leg ladders with the realistic hopping parameters of α-Sr 2 CrO 4 , we explore magnetic and orbital ordering for experimentally relevant interaction parameters. Again, we find a clear signature of antiferromagnetic spin ordering along with antiferro-orbital ordering at moderate to large Hubbard interaction strength. We also explore the orbital-resolved density of states with Lanczos, predicting insulating behavior for the compound α-Sr 2 CrO 4 , in agreement with experiments. Finally, an intuitive understanding of the results is provided based on a hierarchy between orbitals, with d xy driving the spin order, while electronic repulsion and the effective one dimensionality of the movement within the d xz and d yz orbitals driving the orbital order.
36 MATERIALS SCIENCE↗
Scaling Ensembles of Data-Intensive Quantum Chemical Calculations for Millions of Molecules
Deep learning models are efficient computational tools that can accelerate the inverse design of molecules with desired functional properties by generating predictions at a fraction of the time required by traditional quantum chemical approaches. To ensure that a model maintains accuracy and transferability across broad regions of the chemical space explored during the inverse design, it must be trained on massively large volumes of simulation data. This requires running large-scale ensemble quantum chemical calculations on high-performance computing (HPC) systems for data collection. However, the efficient execution of such large ensemble calculations and the management of large volumes of output data require tools that can judiciously utilize computational resources and manage metadata overhead on the file system. Therefore, we present a high-performance, scalable, ensemble management framework for performing data-intensive quantum chemical electronic structure calculations for organic molecules. This framework provides abstractions to plug different ab initio, first principles, and first principles-based semi-empirical methods and executes them efficiently at large scale on HPC systems. It dynamically distributes tasks to resources and uses tiered storage for managing large collections of files. We employed this framework to process over ten million organic molecules and generate open-source datasets that provide UV-vis absorption spectra by running time-dependent density-functional tight-binding calculations. It is the largest database containing molecular optical spectra that were simulated with quantum chemical methods in a consistent manner.
Mehta, Kshitij↗
Toward first principles-based simulations of dense hydrogen
Accurate knowledge of the properties of hydrogen at high compression is crucial for astrophysics (e.g., planetary and stellar interiors, brown dwarfs, atmosphere of compact stars) and laboratory experiments, including inertial confinement fusion. There exists experimental data for the equation of state, conductivity, and Thomson scattering spectra. However, the analysis of the measurements at extreme pressures and temperatures typically involves additional model assumptions, which makes it difficult to assess the accuracy of the experimental data rigorously. On the other hand, theory and modeling have produced extensive collections of data. They originate from a very large variety of models and simulations including path integral Monte Carlo (PIMC) simulations, density functional theory (DFT), chemical models, machine-learned models, and combinations thereof. At the same time, each of these methods has fundamental limitations (fermion sign problem in PIMC, approximate exchange–correlation functionals of DFT, inconsistent interaction energy contributions in chemical models, etc.), so for some parameter ranges accurate predictions are difficult. Recently, a number of breakthroughs in first principles PIMC as well as in DFT simulations were achieved which are discussed in this review. Here we use these results to benchmark different simulation methods. We present an update of the hydrogen phase diagram at high pressures, the expected phase transitions, and thermodynamic properties including the equation of state and momentum distribution. Furthermore, we discuss available dynamic results for warm dense hydrogen, including the conductivity, dynamic structure factor, plasmon dispersion, imaginary-time structure, and density response functions. We conclude by outlining strategies to combine different simulations to achieve accurate theoretical predictions that are based on first principles.
70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
Ab initio calculation of X-ray and related core-level spectroscopies: Green's function approaches
X-Ray and related spectroscopies are powerful probes of atomic, vibrational, and electronic structure. In order to unlock the full potential of such experimental techniques, accurate and efficient theoretical and computational approaches are essential. Here we review the status of a variety of first-principles and nearly first principles techniques for X-ray spectroscopies such as X-ray absorption, X-ray emission, and X-ray photoemission, with a focus on Green's function based methods. In particular, we describe the current state of multiple scattering Green's function techniques available in the FEFF10 code and cumulant Green's function techniques for including the effects of many-body electronic excitations. Furthermore, illustrative examples are shown for a variety of materials and compared with other theoretical and experimental results.
75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
ComDMFT v.2.0: Fully self-consistent ab initio GW+EDMFT for the electronic structure of correlated quantum materials
ComDMFT is a parallel computational package designed to study the electronic structure of correlated quantum materials from first principles. Our approach is based on the combination of first-principles methods and dynamical mean field theories. In version 2.0, we implemented fully-diagrammatic GW+EDMFT from first-principles self-consistently. In this approach, correlated electrons are treated within full GW+EDMFT and the rest are treated within full-GW, seamlessly. Further, this implementation enables the electronic structure calculation of quantum materials with weak, intermediate, and strong electron correlation without prior knowledge of the degree of electron correlation.
75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
Thermodynamics of MgO Atomic Layer Deposition Surface Reactions
The realities of atomic layer deposition (ALD) surface reactions often deviate from the simple ligand exchange frequently used to illustrate the technique. A detailed understanding of these reactions is necessary to develop greater surface synthetic control including chemical selectivity for patterning or to target defects. Here, the thermodynamics of surface reactions relevant to MgO ALD were investigated using pyroelectric calorimetry to measure the time-resolved heat generation. These reactions show exothermic heat generation of 0.12 mJ/cm 2 and 0.15 mJ/cm 2 for alternating Mg(CpEt) 2 and H 2 O reactions, respectively. The total reaction heat closely matches the standard reaction enthalpy for bulk MgO, supplemented with first-principles molecular calculations. First-principles models further reveal that while simple ligand exchange is favorable during surface reactions, the required increase in Mg-coordination number from two in the precursor to six in bulk MgO requires additional coverage-dependent surface reactions, which depend on the availability and stability of proximal surface hydroxyls.
36 MATERIALS SCIENCE↗
A physical model for earthquakes. III - Thermodynamical approach and its relation to nonclassical theories
An earthquake theory based on fundamental thermodynamical considerations was developed using two principles. The first principle is that physical systems, including fault systems, tend toward a state of minimal Helmholtz free energy, which corresponds to static equilibrium. The second postulate is that, if the system is not at minimal free energy, thermodynamic forces arise which drive the system back toward a minimum. According to this theory, the propagation of a fracture, or the formation of a slip on a frictional surface, are manifestations of the physics which attempt to return the system to minimal free energy. It is shown that the process of return to minimal free energy by the system corresponds to the production of entropy, thereby rendering the process irreversible.
Rundle, John B.↗
Fast and accurate machine learning prediction of phonon scattering rates and lattice thermal conductivity
Abstract Lattice thermal conductivity is important for many applications, but experimental measurements or first principles calculations including three-phonon and four-phonon scattering are expensive or even unaffordable. Machine learning approaches that can achieve similar accuracy have been a long-standing open question. Despite recent progress, machine learning models using structural information as descriptors fall short of experimental or first principles accuracy. This study presents a machine learning approach that predicts phonon scattering rates and thermal conductivity with experimental and first principles accuracy. The success of our approach is enabled by mitigating computational challenges associated with the high skewness of phonon scattering rates and their complex contributions to the total thermal resistance. Transfer learning between different orders of phonon scattering can further improve the model performance. Our surrogates offer up to two orders of magnitude acceleration compared to first principles calculations and would enable large-scale thermal transport informatics.
36 MATERIALS SCIENCE↗
Machine learning guided search for energetically favorable metal borocarbide ternary compounds
In this work, we employ machine-learning (ML) combined with first principles calculations to efficiently search for the energetically favorable metal borocarbide (M-B-C) ternary compounds with M being the group 1–3 metal elements. Using a crystal graph convolutional neural network (CGCNN) ML approach followed by first-principles calculations, we predicted 47 energetically favorable stable and metastable ternary Na-B-C, Ca-B-C, and La-B-C ternary compounds with their decomposition energy (E d ) below or within 100 meV/atom from the currently known convex hulls. Phonon spectra and electronic structures of the 14 energetically favorable stable structures are also investigated by first-principles calculations. By substituting the metal atoms in the 29 energetically favorable non-equivalent template structures of Na (Ca, La)-B-C with other group 1–3 elements in the periodic table, we further obtain 22 stable structures and 52 metastable structures (E d ≤100 meV/atom with respect to the known convex hulls) for Li-B-C, K-B-C, Rb-B-C, Mg-B-C, Sr-B-C, Ba-B-C, Sc-B-C and Y-B-C ternary compounds. New convex hulls including our newly predicted stable ternary structures and the known stable structures are constructed for the M-B-C systems. The results obtained by our ML guided first-principles calculations enrich our knowledge in the structure and energy landscape of metal borocarbide ternary compounds and provide useful guidance for further experimental synthesis and discovery.
36 MATERIALS SCIENCE↗
Assessment of empirical interatomic potential to predict thermal conductivity in ThO 2 and UO 2
Computing vibrational properties of crystals in the presence of complex defects often necessitates the use of (semi-)empirical potentials, which are typically not well characterized for perfect crystals. In this study we explore the efficacy of a commonly used embedded-atomempirical interatomic potential for the U x Th 1- x O 2 system, to compute phonon dispersion, lifetime, and branch specific thermal conductivity. Our approach for ThO 2 involves using lattice dynamics and the linearized Boltzmann transport equation to calculate phonon transport properties based on second and third order force constants derived from the empirical potential and from first-principles calculations. For UO 2 , to circumvent the accuracy issues associated with first-principles treatments of strong electronic correlations, we compare results derived from the empirical interatomic potential to previous experimental results. It is found that the empirical potential can reasonably capture the dispersion of acoustic branches, but exhibits significant discrepancies for the optical branches, leading to overestimation of phonon lifetime and thermal conductivity. The branch specific conductivity also differs significantly with either first-principles based results (ThO 2 ) or experimental measurements (UO 2 ). These findings suggest that the empirical potential needs to be further optimized for robust prediction of thermal conductivity both in perfect crystals and in the presence of complex defects.
75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
Trajectory Engineering with Modular Patched Conics for Entry Systems and TPS (TEMPEST)
Brief Presenter Biography (35 word limit): Bohdan Wesely is an Aerospace Engineer in the Entry Systems and Technology Division at Ames. He has worked on a variety of projects for NASA including integrated TPS (thermal protection system) flight hardware deliveries and testing services for commercial partners. Introduction: TEMPEST is a new trajectory analysis framework that is designed to fill the gap between dedicated flight mechanics tools and aerothermal and TPS sizing tools. The project started as an SJSU master’s thesis and has since evolved into a general conceptual design tool capable of studying a wide variety of entry problems. Development is ongoing in the Entry Systems and Technology Division at NASA ARC. Why TEMPEST: Space missions involving entry into a planetary atmosphere involve a series of unique requirements across multiple disciplines. Whether it is traditional entry descent and landing (EDL), or aerocapture, the vehicle must navigate to its target landing location or orbit state, and the TPS must protect the payload during entry. The design process typically involves iterative handoffs between various flight mechanics, flow solver, and material response level tools. During the early conceptual phase, a wide variety of feasible trajectories are simulated in a Monte Carlo scenario which broadly satisfy the mission or landing requirements. Next, computational fluid dynamics (CFD), direct simulation Monte Carlo (DSMC), and other flow solver analyses are performed at various key trajectory points to generate an aero-database, heating and TPS design requirements also emerge at this stage. At this point, with updated aerodynamics from the various flow solvers, trajectories can be re-run, this in turn can change the required freestream conditions for the CFD tools, and as a project progresses, these analyses converge, and uncertainty is reduced. However, there is always a “hand-off” occurring between two inherently coupled phenomena. Analysis Description: One of the goals with TEMPEST is to use a variety of first principles estimation methods coupled with an atmosphere model to predict vehicle aerothermodynamics across the entire flight regime while propagating a 3 or 6 degree of freedom (DoF) trajectory. Aerodynamics methods include modified Newtonian, Maxwell and Cercignani- Lampis-Lord (CLL) for continuum, transitional, and free molecular flow regimes. Aerothermodynamics include boundary layer and reference enthalpy methods, and Mutation++ for non-equilibrium chemistry modeling. TEMPEST is also capable of stitching multiple trajectory segments together to study mission scenarios like multi-pass aerocapture and aero-gravity assists. Most of the program is implemented in MATLAB using modern system objects, it relies on several C++ shared libraries for supporting tools like Gmsh, the Global Reference Atmospheric Model (GRAM), and Mutation++. The various first principles aerothermal estimation methods are discretized across either a structured axisymmetric panel mesh or an unstructured tri-mesh generated from an open-source tool such as Gmsh, this allows solutions on the same mesh to be compared across tools such as CB-Aero. CFD Coupling. A physics-aware, gaussian process CFD anchoring scheme is proposed to adjust the various first principles methods as a CFD database is populated. One goal for this anchoring module is to inform the project where CFD should be run. Full knowledge of the entire trajectory, atmosphere, and aerothermodynamics allows for easier identification of high sensitivity areas and uncertainty quantification. While the first principles effects are well known and proven accurate in existing tools such as CB- Aero and Cart3D, a physics aware CFD anchoring scheme increases tool credibility across a project lifecycle. Material Response Modeling. Correct TPS sizing is critical for optimizing mass for science payloads and ensuring mission success. The process typically involves a thermal analysis along the trajectory with surface heating environments as a boundary condition. Several design constraints are maximum bondline temperature and maximum recession with various margining techniques. The material response tool FIAT, developed out of NASA Ames, is currently being integrated into the TEMPEST environment. TPS recession, shape change, mass loss, and mass property alteration are all factors that can perturb an entry trajectory. For missions like Mars 2020, recession was minimal and was safely handled separately as a post process. For missions such as Jupiter Galileo with a high TPS mass fraction or asteroid entries, recession plays a major role. The proposed fully coupled scheme is to use an epoch-based approach where the trajectory integration is halted after a recession threshold, the energy balance and FIAT are solved at each panel, the mesh, aerodynamics, and mass properties are updated, and the trajectory continues. Several computational tradeoffs have been made during the development of TEMPEST to limit the cost of a single trajectory and preserve its utility as a conceptual, rapid iteration tool. Conclusion: Development of TEMPEST is ongoing and the project is still in its infancy. This talk aims to showcase its unique capabilities to support future NASA entry systems missions.
Bohdan O Wesely↗
Distinguishing Thermal Fluctuations from Polaron Formation in Halide Perovskites
Recent angle-resolved photoelectron spectroscopy (ARPES) measurements of the hole effective mass in CsPbBr$_3$ revealed an enhancement of $\sim$50 % compared to the bare mass computed from first principles for CsPbBr$_3$ at $T = 0 K$. This large enhancement was interpreted as evidence of polaron formation. Employing accurate finite-temperature first-principles calculations, we show that the calculated hole effective mass of CsPbBr$_3$ at $T = 300 K$ can explain experimental results without invoking polarons. Thermal fluctuations are particularly strong in halide perovskites compared to conventional semiconductors such as Si and GaAs, and cannot be ignored when comparing with experiment. We not only resolve the debate on polaron formation in halide perovskites, but also demonstrate the general importance of including thermal fluctuations in first-principles calculations for strongly anharmonic materials.
36 MATERIALS SCIENCE↗