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NASA NTRS2019

Physically-Informed Artificial Neural Networks for Atomistic Modeling of Materials

A new approach is presented for the development of classical interatomic potentials using physically-informed neural networks (PINN) combined with an analytical bond-order atomic interaction model. Due to the strong physical underpinnings, the PINN potentials demonstrate much better transferability than the existing machine-learning potentials while drastically improving the accuracy in comparison with traditional potentials. PINN potentials can be constructed for both metallic and covalent materials in a unified manner. A number of applications of PINN potentials to large-scale molecular dynamics and Monte Carlo simulations and calculation of thermal and mechanical properties of diverse materials are demonstrated. Some of the specific materials systems include silicon and aluminum, as well as alloys and compounds. Computational aspects of PINN potentials are discussed and future developments in this field are outlined.

J Hickman↗

NASA NTRS1980

Time correlation functions in classical dense fluids

The velocity autocorrelation functions and memory functions of dense classical fluids may be directly obtained from the static radial distribution function g(r) in an approximate way. Following the Mori projection operator formalism, the memory functions may be related to the fluctuating force correlation. At low densities, these functions may be evaluated by following the trajectories of particle pairs in the interatomic potential. At higher densities, the force correlation functions can be evaluated approximately from particle pair trajectories via the potential of the mean force. The results for argon fluids at various densities and temperatures agree satisfactorily with the molecular dynamics and the Enskog values. The decrease of the diffusion coefficient with density is partly due to the nature of g(r) which reflects the stronger clustering of atoms at higher densities.

Tsang, T.↗

NASA NTRS2021

Molecular Dynamics Investigation of the Structural and Mechanical Properties of Off-Stoichiometric Epoxy Resins

Molecular dynamic (MD) simulations were performed to compute the mechanical properties of off-stoichiometric epoxy resins as a function of hardener/epoxy mixture ratio (r). Properties were characterized in relation to their microscopic structures. Such resins have been used recently for adhesive-free bonding of large-scale composite structures using the co-curing-ply method. In this process, two partially precured composite panels with hardener-poor (HP) off-stoichiometric resins are coupled with ply(ies) of complementary hardener-rich (HR) formulations and then cured simultaneously. This bonding process has the potential to produce reliable and certifiable composite joints without the need for additional fasteners, which are often required for many conventional bonding methods because even small amounts of contamination can cause a weak bond. The reflow and mixing of the HP/HR resin in this bonding process result in a joint with no discernable interface that should not be susceptible to surface contamination. However, incomplete mixing of the two offset resins may result in chemical heterogeneity of the cured polymeric joint. Thus, different r values may be obtained across the joint. Classical MD simulations were performed to compute the Young’s modulus of polymers with different r values and correlate their properties to network structures. High stiffness was associated with molecular packing due to chemical crosslinking, leading to a single network structure. Moreover, the networks became denser as the ratio approached the stoichiometric value r = 1. Thus, the r = 1 systems were single clusters, with high stiffness, high molecular weight, and a high degree of crosslinking. Structural properties such as radius of gyration and mean square displacement were determined to investigate the variation in the stiffness with respect to r. This MD simulation study was validated with experimental measurements.

Chang Woon Jang↗

NASA NTRS1973

A general relaxation theory of simple liquids

A relatively simple relaxation theory to account for the behavior of liquids under dynamic conditions was proposed. The general dynamical equations are similar in form to the phenomenological relaxation equations used in theories of viscoelasticity, however, they differ in that all the coefficients of the present equations are expressed in terms of thermodynamic and molecular quantities. The theory is based on the concept that flow in a liquid distorts both the radial and the velocity distribution functions, and that relaxation equations describing the return of these functions to their isotropic distributions, characterizing a stationary liquid, can be written. The theory was applied to the problems of steady and oscillatory shear flows and to the propagation of longitudinal waves. In all cases classical results are predicted for strain rates, and an expression for the viscosity of a liquid, simular to the Macedo-Litovitz equation, is obtained.

Merilo, M.↗

NASA NTRS1984

Lubrication of Machine Elements

The understanding of hydrodynamic lubrication began with the classical experiments of Tower and Petrov. Reynolds used a reduced form of the Navier-Stokes equations and the continuity equation to generate a second order differential equation for the pressure in the narrow, converging gap of a bearing contact. Such a pressure enables a load to be transmitted between the surfaces with very low friction since the surfaces are completely separated by a film of fluid. In such a situation it is the physical properties of the lubricant, notably the dynamic viscosity, that dictate the behavior of the contact. The understanding of boundary lubrication is normally attributed to Hardy and Doubleday. In boundary lubrication it is the physical and chemical properties of thin films of molecular proportions and the surfaces to which they are attached that determine contact behavior. The lubricant viscosity is not an influential parameter. Research is devoted to a better understanding and more precise definition of other lubrication regimes between these extremes. One such regime, elastohydrodynamic lubrication, occurs in nonconformal contacts, where the pressures are high and the bearing surfaces deform elastically. In this situation the viscosity of the lubricant may raise considerably, and this further assists the formation of an effective fluid film. The science of these three lubrication regimes (hydrodynamic, elastohydrodynamic, and boundary) are described and the manner in which this science is used in the design of machine elements is examined.

Hamrock, Bernard J.↗

NASA NTRS1994

Statistical mechanics in biology: how ubiquitous are long-range correlations?

The purpose of this opening talk is to describe examples of recent progress in applying statistical mechanics to biological systems. We first briefly review several biological systems, and then focus on the fractal features characterized by the long-range correlations found recently in DNA sequences containing non-coding material. We discuss the evidence supporting the finding that for sequences containing only coding regions, there are no long-range correlations. We also discuss the recent finding that the exponent alpha characterizing the long-range correlations increases with evolution, and we discuss two related models, the insertion model and the insertion-deletion model, that may account for the presence of long-range correlations. Finally, we summarize the analysis of long-term data on human heartbeats (up to 10(4) heart beats) that supports the possibility that the successive increments in the cardiac beat-to-beat intervals of healthy subjects display scale-invariant, long-range "anti-correlations" (a tendency to beat faster is balanced by a tendency to beat slower later on). In contrast, for a group of subjects with severe heart disease, long-range correlations vanish. This finding suggests that the classical theory of homeostasis, according to which stable physiological processes seek to maintain "constancy," should be extended to account for this type of dynamical, far from equilibrium, behavior.

Non-NASA Center↗

NASA NTRSDate not supplied

A window on the composition of the early solar nebula: 2014MU69, Pluto, and Phoebe

The initial chemical composition of any solar nebula will depend upon the degree to which 1) organic and ice components form on dust grains, 2) organic and molecular species form in the gas phase, 3) organics and ices are exchanged between the gas and solid state, and 4) the precursor and newly formed (more complex) materials survive and are modified in the developing planetary system. Infrared and radio observations of star-forming regions reveal that complex chemistry occurs on icy grains, sometimes before stars even form. Additional processing, through the protosolar disk and within the solar nebula further modifies most, but probably not all, of the initial materials. In fact, the modern Solar System still carries a fraction of its interstellar inheritance [Alexander et al., 2017]. Here we focus on three examples of small bodies in our Solar System, each containing chemical and dynamical clues to its origin and evolution: the small, cold-classical Kuiper Belt object (KBO) 2014MU69 , Pluto and Saturn’s moon, Phoebe. The New Horizons flyby of 2014 MU69 has given the first view of an unaltered body composed of material originally in the solar nebula at ~45 AU. The spectrum reveals methanol ice (not commonly found), a possible detection of water ice (Stern et al. 2019). Pluto’s internal and surface inventory of volatiles and complex organics, together with active geological processes including cryo-volcanism, indicate a surprising level of activity on a body in the outermost region of the Solar System, and the fluid that emerges from subsurface reservoirs may contain material inherited from the solar nebula (Cruikshank et al. 2019). Meanwhile, Saturn's captured moon, Phoebe, carries high D/H in H2O [Clark et al. 2018)], and complex organics (Cruikshank et al. 2008), both consistent with its formation in, and inheritance from, the outer solar nebula. Together, these objects provide windows on the origin and evolution of our Solar System and constraints to be considered in future chemical and physical models of PPDs. The Spitzer Space telescope discovered the ring of dust around Saturn that emanated from the bombardment of Phoebe in the recent past, dislodging primitive Solar System material from deep within that satellite. In addition, Spitzer has provided detailed studies of the chemistry of star forming regions where methanol and other ices are readily observed. As a result of these and other observations, protoplanetary disk models are beginning to combine both dynamical and chemical complexities into their codes, resulting in new insights for exoplanetary systems.

Yvonne J. Pendleton↗

NASA NTRS1998

A Synthesis of Fluid Dynamics and Quantum Chemistry for the Design of Nanoelectronics

In 1959, during a famous lecture entitled "There's Plenty of Room at the Bottom", Richard Feynman focused on the startling technical possibilities that would exist at the limit of miniaturization, that being atomically precise devices with dimensions in the nanometer range. A nanometer is both a convenient unit of length for medium to large sized molecules, and the root of the name of the new interdisciplinary field of "nanotechnology". Essentially, "nanoelectronics" denotes the goal of shrinking electronic devices, such as diodes and transistors, as well as integrated circuits of such devices that can perform logical operations, down to dimensions in the range of 100 nanometers. The thirty-year hiatus in the development of nanotechnology can figuratively be seen as a period of waiting for the bottom-up and atomically precise construction skills of synthetic chemistry to meet the top-down reductionist aspirations of device physics. The sub-nanometer domain of nineteenth-century classical chemistry has steadily grown, and state-of-the-art supramolecular chemistry can achieve atomic precision in non-repeating molecular assemblies of the size desired for nanotechnology. For nanoelectronics in particular, a basic understanding of the electron transport properties of molecules must also be developed. Quantum chemistry provides powerful computational methods that can accurately predict the properties of small to medium sized molecules on a desktop workstation, and those of large molecules if one has access to a supercomputer. Of the many properties of a molecule that quantum chemistry routinely predicts, the ability to carry a current is one that had not even been considered until recently. "Currently", there is a controversy over just how to define this key property. Reminiscent of the situation in high-Tc superconductivity, much of the difficulty arises from the different models that are used to simplify the complex electronic structure of real materials. A model-independent approach has been proposed, that sacrifices the plentiful molecular orbitals and Bloch functions of conventional approaches, for a single three-dimensional observable quantity, the electron momentum density Pi(sub rho). This quantity is simply the probability of any electron having momentum rho, multiplied by the total number of electrons in the system (the position of the electron is uncertain). We have explored the utility of this new approach in providing a fundamental understanding of the electron transport properties of molecules that have provi been nominated as candidates for components in the design of nanoelectronics; phenylene-ethynylene oligomers. Some of the molecular systems that have been studied are sketched below.

MacDougall, Preston J.↗

NASA NTRS2016

Evaluation of Methods for Molecular Dynamics Simulation of Ionic Liquid Electric Double Layers

We investigate how systematically increasing the accuracy of various molecular dynamics modeling techniques influences the structure and capacitance of ionic liquid electric double layers (EDLs). The techniques probed concern long-range electrostatic interactions, electrode charging (constant charge versus constant potential conditions), and electrolyte polarizability. Our simulations are performed on a quasi-two-dimensional, or slab-like, model capacitor, which is composed of a polarizable ionic liquid electrolyte, [EMIM][BF4], interfaced between two graphite electrodes. To ensure an accurate representation of EDL differential capacitance, we derive new fluctuation formulas that resolve the differential capacitance as a function of electrode charge or electrode potential. The magnitude of differential capacitance shows sensitivity to different long-range electrostatic summation techniques, while the shape of differential capacitance is affected by charging technique and the polarizability of the electrolyte. For long-range summation techniques, errors in magnitude can be mitigated by employing two-dimensional or corrected three dimensional electrostatic summations, which lead to electric fields that conform to those of a classical electrostatic parallel plate capacitor. With respect to charging, the changes in shape are a result of ions in the Stern layer (i.e. ions at the electrode surface) having a higher electrostatic affinity to constant potential electrodes than to constant charge electrodes. For electrolyte polarizability, shape changes originate from induced dipoles that soften the interaction of Stern layer ions with the electrode. The softening is traced to ion correlations vertical to the electrode surface that induce dipoles that oppose double layer formation. In general, our analysis indicates an accuracy dependent differential capacitance profile that transitions from the characteristic camel shape with coarser representations to a more diffuse profile with finer representations.

Haskins, Justin B.↗

NASA NTRS2019

High-Performance Computing Optimization for Aladyn – Adaptive Neural Network Molecular Dynamics Mini-Application

This report provides a description and performance evaluation of the optimization techniques for high performance computing (HPC) implementation of the open source Computational Materials mini-application Aladyn (https://github.com/nasa/aladyn). Aladyn is a basic molecular dynamics code written in FORTRAN 2003, which is designed to demonstrate the use of adaptive neural networks (ANNs) in atomistic simulations. The role of ANNs is to efficiently reproduce the very complex energy landscape resulting from the atomic interactions in materials with the accuracy of the more expensive quantum mechanics-based calculations. The ANN is trained on a large set of atomic structures calculated using the density functional theory (DFT) method. While achieving orders of magnitude faster computational performance than DFT, the ANN-based approach was still very computationally demanding compared to the conventional approach of using empirically fitted energy functions. After its initial development, Aladyn was evaluated and optimized by experts at the NASA Advanced Supercomputing (NAS) division to exploit modern supercomputer architectures. The code has been optimized for execution on multicore central processing units (CPUs), including Intel® Skylake microarchitecture, and on graphic accelerators, such as Nvidia® V100 graphic processing units (GPUs), using Open Multi-Processing (OpenMP) and Open Accelerators (OpenACC) programming interfaces. The optimization achieved a speedup of 4.7 times the baseline version on CPU performance and an additional 2.4 times on CPU+GPU performance. Atomistic computer simulations are a fundamental tool in materials research to model material properties form physics-based first principles. Atomic interaction, governed by Quantum Mechanics (QM) require sophisticated and highly computationally demanding mathematical models to calculate [1]. Classical methods use approximate functional forms, empirically fitted through a set of variable parameters to emulate atomic energies as direct functions of atomic coordinates [2]. While empirical potentials are computationally much simpler, allowing simulations of large-scale systems of up to a trillion (1012) atoms [3], they are substantially less accurate compared to quantum calculations and applicable only to very specific atomic configurations or predefined crystallographic phases. A recently suggested approach is to use heuristic machine learning methods [4], such as those based on Adaptive Neural Networks (ANNs) to predict atomic energies, after being trained on a sufficiently large database of QM-calculated structures [5,6]. This approach reduces significantly the computational complexity, allowing for simulations of orders of magnitude larger systems compared to QM-based methods without compromising accuracy. Still, compared to classical methods using empirical energy functions, ANN methods remain two- to three orders of magnitude more computationally demanding. Hence, the computational cost of simulations, together with the need for extensive training of ANNs, still makes the practical implementation of ANN-based methods quite challenging. The purpose of the Aladyn mini-application software [7], available as open source at https://github.com/nasa/aladyn, is to be a testbed for exploring possible optimization strategies to develop highly scalable parallel algorithms for ANN-based atomistic simulations. Aladyn is aimed at utilizing the architecture of the high-end modern highperformance computing (HPC) hardware based on multicore central processing units (CPUs) equipped with graphic processing unit (GPU) accelerators. Specifically, the goal is to optimize the performance on a single HPC compute node, before implementing scaling to multi-node parallelization using message passing interface (MPI). At the same time, the open source code of Aladyn can serve as a training model for students and professors in academia.

Yamakov, Vesselin I.↗

NASA NTRS2005

Growth from Solutions: Kink dynamics, Stoichiometry, Face Kinetics and stability in turbulent flow

1. Kink dynamics. The first segment of a polygomized dislocation spiral step measured by AFM demonstrates up to 60% scattering in the critical length l*- the length when the segment starts to propagate. On orthorhombic lysozyme, this length is shorter than that the observed interkink distance. Step energy from the critical segment length based on the Gibbs-Thomson law (GTL), l* = 20(omega)alpha/(Delta)mu is several times larger than the energy from 2D nucleation rate. Here o is tine building block specific voiume, a is the step riser specific free energy, Delta(mu) is the crystallization driving force. These new data support our earlier assumption that the classical Frenkel, Burton -Cabrera-Frank concept of the abundant kink supply by fluctuations is not applicable for strongly polygonized steps. Step rate measurements on brushite confirms that statement. This is the1D nucleation of kinks that control step propagation. The GTL is valid only if l* <Dk/vk, the diffusion path of a kink that has diffusivity Dk and average growth velocity vk. This is equivalent to supersaturations sigma less than approx. alpha/2l*, where alpha is the building block size. For lysozyme, sigma much less than (1%). Conventionally used interstep distance generated by screw dislocation, 19(omega)alpha/Delta(mu) should be replaced by the very different real one, approx.4l*. 2. Stoichiometry. Kink, and thus step and face rates of a non-Kossel complex molecular monocomponent or any binary, AB, lattice was found theoretically to be proportional to 1/(zeta(sup 1/2) + zeta(sup - 1/2)), where zeta = [B]/[A] is the stoichiometry ratio in solution. The velocities reach maxima at zeta = 1. AFM studies of step rates on CaOxalate monohydrate (kidney stones) from aqueous solution was found to obey the law mentioned above. Generalization for more complex lattice will be discussed. 3. Turbulence. In agreement with theory, high precision in-situ laser interferometry of the (101) KDP crystal face shows step bunching if solution flows parallel to the step flow. The bunch height increases with the distance the bunch travels, i.e. with the face size. However, when the flow rate, u, increases, at u greater than approx. 1 m / s , the average step bunch height decreases as 1/u. The pheonomenon is attributed to the turbulent rather than laminar viscous boundary layer where diffusivity Dt = 0.5u(sub tau),y, i.e. increases linearly with the distance y from the solid face. Friction velocity, u(sub tau) approx. u(sup 7/8). Dramatically larger rate of the mass/heat transport within the turbulent, as compared to the laminar, viscous layer will be discussed.

Chernov, A. A.↗

NASA NTRS2012

Ground-Based Centimeter, Millimeter, and Submillimeter Observations of Recent Comets

Comets provide important clues to the physical and chemical processes that occurred during the formation and early evolution of the Solar System, and could also have been important for initiating prebiotic chemistry on the early Earth [I]. Comets are comprised of molecular ices, that may be pristine interstellar remnants of Solar System formation, along with high-temperature crystalline silicate dust that is indicative of a more thermally varied history in the protosolar nebula [2]. Comparing abundances of cometary parent volatiles, and isotopic fractionation ratios, to those found in the interstellar medium, in disks around young stars, and between cometary families, is vital to understanding planetary system formation and the processing history experienced by organic matter in the so-called interstellar-comet connection [3]. In the classical picture, the long-period comets probably formed in the nebular disk across the giant planet formation region (5-40 AU) with the majority of them originating from the Uranus-Neptune region. They were subsequently scattered out to the Oort Cloud (OC) by Jupiter. The short-period comets (also known as ecliptic or Jupiter Family Comets - JFC) reside mainly in the Edgeworth-Kuiper belt where they were formed. Given the gradient in physical conditions expected across this region of the nebula, chemical diversity in this comet population is to be expected [4,5]. We have conducted observations of comets I 03P/Hartley 2 (JFC) and C/2009 PI (Garradd) (OC), at primarily millimeter and submillimeter wavelengths, to determine important cosmogonic quantities, such as the ortho:para ratio and isotope ratios, as well as probe the origin of cometary organics and if they vary between the two dynamic reservoirs.

Milam, S. N.↗

NASA NTRS1993

Hypersonic panel flutter in a rarefied atmosphere

Panel flutter is a form of dynamic aeroelastic instability resulting from the interaction between motion of an aircraft structural panel and the aerodynamic loads exerted on that panel by air flowing past one of the faces. It differs from lifting surface flutter in the sense that it is not usually catastrophic, the panel's motion being limited by nonlinear membrane stresses produced by the transverse displacement. Above some critical airflow condition, the linear instability grows to a limit cycle . The present investigation studies panel flutter in an aerodynamic regime known as 'free molecule flow', wherein intermolecular collisions can be neglected and loads are caused by interactions between individual molecules and the bounding surface. After collision with the panel, molecules may be reflected specularly or reemitted in diffuse fashion. Two parameters characterize this process: the 'momentum accommodation coefficient', which is the fraction of the specularly reflected molecules; and the ratio between the panel temperature and that of the free airstream. This model is relevant to the case of hypersonic flight vehicles traveling at very high altitudes and especially for panels oriented parallel to the airstream or in the vehicle's lee. Under these conditions the aerodynamic shear stress turns out to be considerably larger than the surface pressures, and shear effects must be included in the model. This is accomplished by means of distributed longitudinal and bending loads. The former can cause the panel to buckle. In the example of a simply-supported panel, it turns out that the second mode of free vibration tends to dominate the flutter solution, which is carried out by a Galerkin analysis. Several parametric studies are presented. They include the effects of (1) temperature ratio; (2) momentum accommodation coefficient; (3) spring parameters, which are associated with how the panel is connected to adjacent structures; (4) a parameter which relates compressive end load to its value which would cause classical column buckling; (5) a parameter proportional to the pressure differential between the front and back faces; and (6) initial curvature. The research is completed by an investigation into the possibility of accounting for molecular collisions, which proves to be infeasible given the speeds of current mainframe supercomputers.

Resende, Hugo B.↗