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At least 937 records · Page 52
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Effects of cluster expansion on the locations of phase transition boundary as a first step to quantify uncertainty in first principles statistical mechanics framework

Predicting phase diagrams from first principle calculations eliminates the need of tedious experimental trials and errors. Fully automating first principle phase diagram calculations without any sort of human intervention has been a long daunting task and troubling scientific communities for decades. This grand problem remains not fully resolved, largely due to the vastly high-dimensional parameter space associated with density functional theory, cluster expansion, lattice Monte Carlo, and the substantial uncertainty propagating through a set of complex simulations. As a first step to tackle this grand problem, we reported a first demonstration of how sensitive phase boundary locations can be to various cluster expansion fittings and input DFT training data. To the best knowledge of the authors, this study reported the first ever attempt to quantify uncertainty in first principles statistical mechanics framework. In addition, a semi-automated phase transition detection algorithm has been devised in this paper to deal with the associated statistical errors and uncertainties from Monte Carlo method and its predecessor DFT calculations and cluster expansions. This algorithm has been applied in a classical cluster expansion Mg-Cd binary alloy system to detect phase transitions at various locations of phase diagram using different cluster expansions to demonstrate its predictive power and quantify uncertainties. The results suggested that using Chebyshev basis function shifted the transition locations toward the dilute solid solution phase and expanded the phase stability of concentrated ordered phases to wider composition range. The addition of perturbed defect configurations into training data set lowered the order-disorder transition temperature to be away from true transition temperature, suggesting the transition nature is indeed configurational disorder dominated rather than defect assisted. Finally, we found that the weighting has negligible effect on the transition locations, except for the case of using Chebyshev basis function to fit all non-weighted configurations that can be susceptible to Monte Carlo sampling hysteresis.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Phase Equilibrium of Water with Hexagonal and Cubic Ice Using the SCAN Functional

Machine learning models are rapidly becoming widely used to simulate complex physicochemical phenomena with ab initio accuracy. Here, we use one such model as well as direct density functional theory (DFT) calculations to investigate the phase equilibrium of water, hexagonal ice (Ih), and cubic ice (Ic), with an eye toward studying ice nucleation. The machine learning model is based on deep neural networks and has been trained on DFT data obtained using the SCAN exchange and correlation functional. We use this model to drive enhanced sampling simulations aimed at calculating a number of complex properties that are out of reach of DFT-driven simulations and then employ an appropriate reweighting procedure to compute the corresponding properties for the SCAN functional. This approach allows us to calculate the melting temperature of both ice polymorphs, the driving force for nucleation, the heat of fusion, the densities at the melting temperature, the relative stability of ices Ih and Ic, and other properties. We find a correct qualitative prediction of all properties of interest. In some cases, quantitative agreement with experiment is better than for state-of-the-art semiempirical potentials for water. Furthermore, our results also show that SCAN correctly predicts that ice Ih is more stable than ice Ic.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Trifluoromethylated Phenanthroline Ligands Reduce Excited-State Distortion in Homoleptic Copper(I) Complexes

Herein, we report the synthesis and excited-state dynamics for a series of homoleptic copper(I) trifluoromethylated phenanthroline complexes with two, three, and four trifluoromethyl functional groups. Our analysis of the steady-state absorbance and emission, transient-absorption spectroscopy, and electronic-structure-theory calculations results enable in-depth analysis of the pseudo-Jahn–Teller distortion inhibition from increased steric hindrance of the trifluoromethyl functional group relative to the prototypical dimethyl phenanthroline complex. Surprisingly, our results demonstrate that the greatest degree of pseudo-Jahn–Teller distortion inhibition is achieved with trifluoromethylation of only the 2 and 9 positions by an unusual combination of steric hindrance and stabilization of a nondistorted 1 MLCT manifold observed by transient kinetic lifetimes and optimized excited-state structures. The intersystem-crossing (ISC) lifetime for the 2,9-bis(trifluoromethyl)-1,10-phenanthroline Cu(I) complex is 69 ps, while the triplet excited-state lifetime and emission quantum yield are 106 ns and 4 × 10 –3 , respectively. Further trifluoromethylation of the phenanthroline yields a greater σ bond inductive withdrawing force on the phenanthroline nitrogens, ultimately resulting in weaker coordination to the copper. Last, the surprising success of the 2,9-bis(trifluoromethyl)-1,10-phenanthroline Cu(I) complex by adjusting both ligand sterics and electronic properties outlines a new strategy for developing long-lived Cu(I) charge-transfer complexes.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Revealing the Configuration and Conformation of Surface Organometallic Catalysts with DNP-Enhanced NMR

Although single-site, supported organometallic catalysts were designed with homogeneity in mind, little is strictly known about their atomic-level structure and uniformity. This is in large part due to the inability of conventional characterization tools to provide structural information with adequate resolution and range for this purpose. In this work, we show that dynamic nuclear polarization (DNP)-enhanced solid-state nuclear magnetic resonance (NMR) enables the measurement of distances between the surface and individual carbons, making it possible to orient complexes and molecules on surfaces. We use this approach to determine the orientation and configuration of naturally 13 C-abundant acetate and supported organoiridium(III) pincer complex, both supported on γ-Al 2 O 3 . By combining solid-state NMR and extended X-ray absorption fine structure spectroscopy (EXAFS) experiments with periodic density functional theory (DFT) calculations, we are able to determine the three-dimensional arrangement of ligands around the metal center and thereby identify the structure of the supported complex at a resolution reminiscent of that associated with single-crystal diffractometry.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

When Do Extended Physics-Informed Neural Networks (XPINNs) Improve Generalization?

Physics-informed neural networks (PINNs) have become a popular choice for solving high-dimensional partial differential equations (PDEs) due to their excellent approximation power and generalization ability. Recently, extended PINNs (XPINNs) based on domain decomposition methods have attracted considerable attention due to their effectiveness in modeling multiscale and multiphysics problems and their parallelization. However, theoretical understanding of their convergence and generalization properties remains unexplored. In this study, we take an initial step towards understanding how and when XPINNs outperform PINNs. Specifically, for general multilayer PINNs and XPINNs, we first provide a prior generalization bound via the complexity of the target functions in the PDE problem and a posterior generalization bound via the posterior matrix norms of the networks after optimization. Moreover, based on our bounds, we analyze the conditions under which XPINNs improve generalization. Concretely, our theory shows that the key building block of XPINN, namely, the domain decomposition, introduces a tradeoff for generalization. On the one hand, XPINNs decompose the complex PDE solution into several simple parts, which decreases the complexity needed to learn each part and boosts generalization. On the other hand, decomposition leads to less training data being available in each subdomain, and hence such a model is typically prone to overfitting and may become less generalizable. Empirically, we choose five PDEs to show when XPINNs perform better than, similar to, or worse than PINNs, hence demonstrating and justifying our new theory.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Medial packing and elastic asymmetry stabilize the double-gyroid in block copolymers

Triply-periodic networks are among the most complex and functionally valuable self-assembled morphologies, yet they form in nearly every class of biological and synthetic soft matter building blocks. In contrast to simpler assembly motifs – spheres, cylinders, layers – networks require molecules to occupy variable local environments, confounding attempts to understand their formation. Here, we examine the double-gyroid network phase by using a geometric formulation of the strong stretching theory of block copolymer melts, a prototypical soft self-assembly system. The theory establishes the direct link between molecular packing, assembly thermodynamics and the medial map, a generic measure of the geometric center of complex shapes. We show that “medial packing” is essential for stability of double-gyroid in strongly-segregated melts, reconciling a long-standing contradiction between infinite- and finite-segregation theories. Additionally, we find a previously unrecognized non-monotonic dependence of network stability on the relative entropic elastic stiffness of matrix-forming to tubular-network forming blocks. The composition window of stable double-gyroid widens for both large and small elastic asymmetry, contradicting intuitive notions that packing frustration is localized to the tubular domains. This study demonstrates the utility of optimized medial tessellations for understanding soft-molecular assembly and packing frustration via an approach that is readily generalizable far beyond gyroids in neat block copolymers.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Enabling Large-Scale Condensed-Phase Hybrid Density Functional Theory Based Ab Initio Molecular Dynamics. 1. Theory, Algorithm, and Performance

By including a fraction of exact exchange (EXX), hybrid functionals reduce the self-interaction error in semilocal density functional theory (DFT) and thereby furnish a more accurate and reliable description of the underlying electronic structure in systems throughout biology, chemistry, physics, and materials science. However, the high computational cost associated with the evaluation of all required EXX quantities has limited the applicability of hybrid DFT in the treatment of large molecules and complex condensed-phase materials. To overcome this limitation, we describe a linear-scaling approach that utilizes a local representation of the occupied orbitals (e.g., maximally localized Wannier functions (MLWFs)) to exploit the sparsity in the real-space evaluation of the quantum mechanical exchange interaction in finite-gap systems. In this work, we present a detailed description of the theoretical and algorithmic advances required to perform MLWF-based ab initio molecular dynamics (AIMD) simulations of large-scale condensed-phase systems of interest at the hybrid DFT level. We focus our theoretical discussion on the integration of this approach into the framework of Car–Parrinello AIMD, and highlight the central role played by the MLWF-product potential (i.e., the solution of Poisson’s equation for each corresponding MLWF-product density) in the evaluation of the EXX energy and wave function forces. We then provide a comprehensive description of the exx algorithm implemented in the open-source Quantum ESPRESSO program, which employs a hybrid MPI/OpenMP parallelization scheme to efficiently utilize the high-performance computing (HPC) resources available on current- and next-generation supercomputer architectures. Furthermore, this is followed by a critical assessment of the accuracy and parallel performance (e.g., strong and weak scaling) of this approach when AIMD simulations of liquid water are performed in the canonical (NVT) ensemble. With access to HPC resources, we demonstrate that exx enables hybrid DFT-based AIMD simulations of condensed-phase systems containing 500–1000 atoms (e.g., (H₂O)₂₅₆) with a wall time cost that is comparable to that of semilocal DFT. In doing so, exx takes us one step closer to routinely performing AIMD simulations of complex and large-scale condensed-phase systems for sufficiently long time scales at the hybrid DFT level of theory.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS1996

A viscoelastic higher-order beam finite element

A viscoelastic internal variable constitutive theory is applied to a higher-order elastic beam theory and finite element formulation. The behavior of the viscous material in the beam is approximately modeled as a Maxwell solid. The finite element formulation requires additional sets of nodal variables for each relaxation time constant needed by the Maxwell solid. Recent developments in modeling viscoelastic material behavior with strain variables that are conjugate to the elastic strain measures are combined with advances in modeling through-the-thickness stresses and strains in thick beams. The result is a viscous thick-beam finite element that possesses superior characteristics for transient analysis since its nodal viscous forces are not linearly dependent an the nodal velocities, which is the case when damping matrices are used. Instead, the nodal viscous forces are directly dependent on the material's relaxation spectrum and the history of the nodal variables through a differential form of the constitutive law for a Maxwell solid. The thick beam quasistatic analysis is explored herein as a first step towards developing more complex viscoelastic models for thick plates and shells, and for dynamic analyses. The internal variable constitutive theory is derived directly from the Boltzmann superposition theorem. The mechanical strains and the conjugate internal strains are shown to be related through a system of first-order, ordinary differential equations. The total time-dependent stress is the superposition of its elastic and viscous components. Equations of motion for the solid are derived from the virtual work principle using the total time-dependent stress. Numerical examples for the problems of relaxation, creep, and cyclic creep are carried out for a beam made from an orthotropic Maxwell solid.

Johnson, Arthur R.↗
DOE OSTI2021

Anharmonic theory of superconductivity in the high-pressure materials

Electron-phonon superconductors at high pressures have displayed the highest values of critical superconducting temperature Tc on record, now rapidly approaching room temperature. Despite the importance of high-P superconductivity in the quest for room-temperature superconductors, a mechanistic understanding of the effect of pressure and its complex interplay with phonon anharmonicity and superconductivity is missing, as numerical simulations can bring only system-specific details, clouding out key players controlling the physics. In this work, we develop a minimal model of electron-phonon superconductivity under an applied pressure which takes into account the anharmonic decoherence of the optical phonons. We find that T c behaves nonmonotonically as a function of the ratio Γ/ω 0 , where Γ is the optical phonon damping and ω 0 is the optical phonon energy at zero pressure and momentum. Optimal pairing occurs for a critical ratio Γ/ω 0 when the phonons are on the verge of decoherence (“diffusonlike” limit). Our framework gives insights into recent experimental observations of T c as a function of pressure in the complex BCS material TlInTe 2 .

36 MATERIALS SCIENCE↗
DOE OSTI2021

Self-Assembly of Metallo-Supramolecules with Dissymmetrical Ligands and Characterization by Scanning Tunneling Microscopy

Asymmetrical and dissymmetrical structures are widespread and play a critical role in nature and life systems. In the field of metallo-supramolecular assemblies, it is still in its infancy for constructing artificial architectures using dissymmetrical building blocks. Herein, we report the self-assembly of supramolecular systems based on two dissymmetrical double-layered ligands. With the aid of ultra-high-vacuum, low-temperature scanning tunneling microscopy (UHV-LT-STM), we were able to investigate four isomeric structures corresponding to four types of binding modes of ligand LA with two major conformations complexes A. The distribution of isomers measured by STM and total binding energy of each isomer obtained by density functional theory (DFT) calculations suggested that the most abundant isomer could be the most stable one with highest total binding energy. Lastly, through shortening the linker between inner and outer layers and the length of arms, the arrangement of dissymmetrical ligand LB could be controlled within one binding mode corresponding to the single conformation for complexes B.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

About the Complex Natural and Engineered Systems Pillar

Los Alamos National Laboratory is a world leader in applying multi-disciplinary science to complex systems within the Complex Natural and Engineered Systems (CNES) challenge areas. Our search for solutions requires science and technology innovation, as well as an integrated experiment, theory, and modeling and simulation approach. Our research and development spans from improving engineered systems such as nuclear weapons and the power grid, to understanding the interface of human and engineered systems from the subsurface to space, to studying how complex natural systems such as disease and climate impact humanity.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2024

Catalytic Resonance Theory: Forecasting the Flow of Programmable Catalytic Loops

Chemical transformations on catalyst surfaces occur through series and parallel reaction pathways. These complex networks and their behavior can be most simply evaluated through a three-species surface reaction loop (A* to B* to C* to A*) that is internal to the overall chemical reaction. Application of an oscillating dynamic catalyst to this reactive loop has been shown to exhibit one of three types of behavior: (1) a positive net flux of molecules about the loop in the clockwise direction, (2) a negative net flux of molecules about the loop in the counterclockwise direction, or (3) negligible flux of molecules about the loop at the limit cycle of reaction. Three-species surface loops were simulated with microkinetic modeling to assess the reaction loop behavior resulting from a catalytic surface oscillating between two or more catalyst surface energy states. Selected input parameters for the simulations spanned an 11-dimensional parameter space using 127 688 different parameter combinations. Their converged limit cycle solutions were analyzed for their loop turnover frequencies, the majority of which were found to be approximately zero. Classification and regression machine learning models were trained to predict the sign and magnitude of the loop turnover frequency and successfully performed above accessible baselines. Notably, the classification models exhibited a baseline weighted F1 score of 0.49, whereas trained models achieved weighted F1 scores of 0.94 and 0.96 when trained on the parameters used to define the simulations and derived rate constants, respectively. The trained models successfully predicted catalytic loop behavior, and interpretation of these models revealed all input parameters to be important for the prediction and performance of each model.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS1981

Solution of complex nonlinear problems by a generalized application of the method of base and comparison solutions with applications to aerodynamics problems

A theory for obtaining approximate solutions to nonlinear problems whose exact solutions require the use of large computational procedures is described. The technique represents in some respects a generalization of the method of base and comparison solutions for flows depending on a parameter. For the generalized problem, the input variable is no longer a parameter but a function that is incremented over its entire domain. After performing calculations for a base configuration and a small number of variations of it, solutions for a large class of configurations can be obtained by forming linear combinations of the solution increments. For a restricted class of problems, approximate solutions can be obtained for general variations of a base configuration by using a function-space derivative estimate obtained from a base solution and a single variation.

Barger, R. L.↗
DOE OSTI2025

Speciation and diffusive dynamics in hydrated grain boundaries of complex oxide Gd2Ti2O7

Abstract Grain boundaries in polycrystalline materials significantly affect their properties, such as ionic transport, corrosion, and chemical durability. The pyrochlore compound (Gd 2 Ti 2 O 7 ) is employed as a model for complex oxides and is known for its diverse applications, including nuclear waste immobilization. Density functional theory-based first-principles molecular dynamics simulations were performed at different temperatures on the hydrated grain boundary system. The results show extensive transformations within the grain boundaries among hydrous water species (OH − , H 2 O, and H 3 O + ). The temperature dependence of self-diffusion coefficients follows Arrhenius behavior, with an activation energy of 35.9 kJ/mol for hydrogen and 46.3 kJ/mol for oxygen. The lifetime of OH − is about three to four times longer than that of H 2 O at temperatures from 800 to 2100 K, suggesting the greater stability of OH − over H 2 O, a unique characteristic of the grain boundaries. The estimated lifetime of the hydrous species decreases as the temperature increases, with an activation energy of 9.9 kJ/mol for OH − and 13.4 kJ/mol for H 2 O. While Gd 3 + is more mobile than Ti 4+ , both the Gd 3 + and Ti 4+ cations are orders of magnitude less mobile than the water species. The results suggest that water species are much more mobile within grain boundaries than in the bulk crystal and have the potential to penetrate deep into polycrystalline materials through grain boundaries, leading to grain boundary degradation and dissolution. The different mobilities of cations in complex oxides can lead to leaching of certain cations and incongruent dissolution during the chemical weathering of Earth and industrial materials.

B. Ghosh, Dipta↗
NASA NTRS1972

On the performance of infrared sensors in earth observations

The performance of infrared sensing systems is dependent upon the radiative properties of targets in addition to constraints imposed by system components. The unclassified state-of-the-art of infrared system performance figures is reviewed to indicate the relevance to system performance of target radiative properties. A theory of rough surface scattering is developed which allows the formulation of the reflective characteristics of extended targets. The thermal radiation emission from extended targets is formulated on the basis of internal radiation characteristics of natural materials and the transmissive scattering effects at the surface. Finally, the total radiative characteristics may be expressed as functions of material properties and incident and received directions, although the expressions are extremely complex functions and do not account for the effects of shadowing or multiple scattering. It is believed that the theory may be extended to include these effects and to incorporate the local radii of curvature of the surface.

Johnson, L. F.↗
DOE OSTI2020

“Lagrangian disks” in M-theory

While the study of bordered (pseudo-)holomorphic curves with boundary on Lagrangian submanifolds has a long history, a similar problem that involves (special) Lagrangian submanifolds with boundary on complex surfaces appears to be largely overlooked in both physics and math literature. We relate this problem to geometry of coassociative submanifolds in G 2 holonomy spaces and to Spin(7) metrics on 8-manifolds with T 2 fibrations. As an application to physics, we propose a large class of brane models in type IIA string theory that generalize brane brick models on the one hand and 2d theories T[M 4 ] on the other.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2021

Generalising G 2 geometry: involutivity, moment maps and moduli

We analyse the geometry of generic Minkowski N = 1, D = 4 flux compactifications in string theory, the default backgrounds for string model building. In M-theory they are the natural string theoretic extensions of G2 holonomy manifolds. In type II theories, they extend the notion of Calabi-Yau geometry and include the class of flux backgrounds based on generalised complex structures first considered by Graña et al. (GMPT). Using E 7(7) × $\mathbb{R}$ + generalised geometry we show that these compactifications are characterised by an SU(7) ⊂ E 7(7) structure defining an involutive subbundle of the generalised tangent space, and with a vanishing moment map, corresponding to the action of the diffeomorphism and gauge symmetries of the theory. The Kähler potential on the space of structures defines a natural extension of Hitchin’s G 2 functional. Using this framework we are able to count, for the first time, the massless scalar moduli of GMPT solutions in terms of generalised geometry cohomology groups. It also provides an intriguing new perspective on the existence of G 2 manifolds, suggesting possible connections to Geometrical Invariant Theory and stability.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2026

Long-Range Fit: A Software Package for the Representation and Study of Long-Range Molecular Interactions

Describing intermolecular forces is fundamental to modeling and predicting the behavior of molecular systems. In particular, long-range molecular interactions─with electrostatic, induction, and dispersion as the main components─play a critical role, especially for low-temperature and low-density regimes. Long-range interactions are often described through perturbation theory, representing the electronic charge distribution via a multipolar series of the moments and polarizability tensors corresponding to each molecule. However, while the theory is well established, obtaining the resulting analytical expressions (and their practical implementation) constitutes a highly complex and system-dependent task. To address this challenge, we developed long-range-fit (LRF), an interactive and user-friendly software package designed to automate the generation and fitting of long-range interaction terms for arbitrary molecules in nondegenerate (ground or excited) electronic states. We have derived and implemented all terms up to 15th order, without approximations, via a spherical tensor representation, with symmetry adaptation to all molecular point-group symmetries. The resulting potential energy surface is compatible with most representations of the close interaction region.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗