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From end of intro: ...We would like to show that for certain problems in systems and control theory, there exist algorithms for which corresponding (xi) can be viewed as a certain measure of robustness, e.g., stability margin.
The focal area of this white paper is learning from complex data through the use of AI techniques and AI-derived model components. Specifically, we advocate for research programs to develop knowledge-guided AI (KGAI) in the Earth and Environmental Systems sciences (EESS) as a basic research paradigm that is separate from (but supports) any specific Earth system model, modeling components, and modeling workflows, and even separates from specific hypothesis-driven questions about individual Earth system processes.
Quantum tunneling plays a fundamental role in many chemical reactions, particularly proton transfer processes. Ring polymer instanton theory offers a practical framework for computing tunneling rates in complex molecular systems. However, applying the ring polymer instanton method with a potential energy surface generated on-the-fly using electronic structure calculations can be computationally demanding. Here, in this work, we present a new efficient implementation of the ring polymer instanton method by combining the Line Integral Nudged Elastic Band (LI-NEB) approach with Gaussian Process Regression (GPR). We benchmarked this method on prototypical ground-state proton transfer systems, including the benchmark gas-phase hydrogen abstraction reaction H + CH 4 → H 2 + CH 3 , malonaldehyde, and Z-3-amino-propenal (aminopropenal). Our results show that this approach is an order of magnitude faster than traditional instanton algorithms while maintaining excellent agreement with their tunneling rates. This development opens the door to studying proton transfer in larger systems with improved efficiency.
Most observed phase separation phenomena in complex oxides occur in systems with chemical dopants or structural defects, and theories have established the strong connection between phase separation and the random distribution of chemical dopants. Recent experiments on fabricated high-quality oxide superlattices also confirmed that the phase separation is suppressed in the clean systems without chemical disorders. Thus far, phase separation in strongly correlated oxides without the need of chemical dopants or structural defects has not been fully demonstrated. Here, we have built chemically ordered hybrid superlattices using prototypical SrRuO 3 and SrTiO 3 perovskite oxides. Contrary to previous understandings, we observe phase separation of two magnetic phases with different spin easy axes. We elucidate this phenomenon through first-principles calculations that the hybrid superlattices have a spontaneous structural instability, leading to a coexistence of ferromagnetic and antiferromagnetic phases. In this work, our findings provide an alternative pathway other than chemical doping to introduce phase separation in correlated oxides and imply that phase separation can exist in clean systems without the need of chemical disorders.
Analytical functional relationships describing homogeneous nucleation and crystallization in various supercooled liquids were developed. The time and temperature dependent relationships of nucleation and crystallization (intrinsic properties) are being used to relate glass forming tendency to extrinsic parameters such as cooling rate through computer simulation. Single oxide systems are being studied initially to aid in developing workable kinetic models and to indicate the primary materials parameters affecting glass formation. The theory and analytical expressions developed for simple systems is then extended to complex oxide systems. A thorough understanding of nucleation and crystallization kinetics of glass forming systems provides a priori knowledge of the ability of a given system to form a glass.
Edge delamination has caused severe concern in the design and analysis of advanced composite materials and structures. Due to its complex nature, very limited knowledge for the problem is currently available. It involves not only geometric and material discontinuities but also inherently coupled mode I, II and III fracture in the layered anisotropic system. Based on complex-variable stress potentials in the anisotropic elasticity theory and eigenfunction expansion, exact orders of the crack-tip stress singularity and complete field solutions are obtained. Results are given for edge delaminated, angle-ply composites subjected to uniform axial extension for illustrative purposes. Effects of geometric, lamination, and crack variables are determined.
The primary thrust of the research was to conduct fundamental research in the theories and methodologies for designing complex high-performance multivariable feedback control systems; and to conduct feasibiltiy studies in application areas of interest to NASA sponsors that point out advantages and shortcomings of available control system design methodologies.
Little theory exists in the field of software system measurement. Concepts such as complexity, coupling, cohesion or even size are very often subject to interpretation and appear to have inconsistent definitions in the literature. As a consequence, there is little guidance provided to the analyst attempting to define proper measures for specific problems. Many controversies in the literature are simply misunderstandings and stem from the fact that some people talk about different measurement concepts under the same label (complexity is the most common case). There is a need to define unambiguously the most important measurement concepts used in the measurement of software products. One way of doing so is to define precisely what mathematical properties characterize these concepts regardless of the specific software artifacts to which these concepts are applied. Such a mathematical framework could generate a consensus in the software engineering community and provide a means for better communication among researchers, better guidelines for analysis, and better evaluation methods for commercial static analyzers for practitioners. In this paper, we propose a mathematical framework which is generic, because it is not specific to any particular software artifact, and rigorous, because it is based on precise mathematical concepts. This framework defines several important measurement concepts (size, length, complexity, cohesion, coupling). It is not intended to be complete or fully objective; other frameworks could have been proposed and different choices could have been made. However, we believe that the formalism and properties we introduce are convenient and intuitive. In addition, we have reviewed the literature on this subject and compared it with our work. This framework contributes constructively to a firmer theoretical ground of software measurement.
With the advent of Rossi X-ray Timing Explorer (RXTE), which is capable of broad spectral coverage and fast timing, as well as other instruments which are increasingly being used in multi-wavelength campaigns (via both space-based and ground-based observations), we must demand more of our theoretical models. No current model mimics all facets of a system as complex as an x-ray binary. However, a modern theory should qualitatively reproduce - or at the very least not fundamentally disagree with - all of Cygnus X-l's most basic average properties: energy spectrum (viewed within a broader framework of black hole candidate spectral behavior), power spectrum (PSD), and time delays and coherence between variability in different energy bands. Below we discuss each of these basic properties in turn, and we assess the health of one of the currently popular theories: Comptonization of photons from a cold disk. We find that the data pose substantial challenges for this theory, as well as all other in currently discussed models.
Little theory exists in the field of software system measurement. Concepts such as complexity, coupling, cohesion or even size are very often subject to interpretation and appear to have inconsistent definitions in the literature. As a consequence, there is little guidance provided to the analyst attempting to define proper measures for specific problems. Many controversies in the literature are simply misunderstandings and stem from the fact that some people talk about different measurement concepts under the same label (complexity is the most common case). There is a need to define unambiguously the most important measurement concepts used in the measurement of software products. One way of doing so is to define precisely what mathematical properties characterize these concepts, regardless of the specific software artifacts to which these concepts are applied. Such a mathematical framework could generate a consensus in the software engineering community and provide a means for better communication among researchers, better guidelines for analysts, and better evaluation methods for commercial static analyzers for practitioners. In this paper, we propose a mathematical framework which is generic, because it is not specific to any particular software artifact and rigorous, because it is based on precise mathematical concepts. We use this framework to propose definitions of several important measurement concepts (size, length, complexity, cohesion, coupling). It does not intend to be complete or fully objective; other frameworks could have been proposed and different choices could have been made. However, we believe that the formalisms and properties we introduce are convenient and intuitive. This framework contributes constructively to a firmer theoretical ground of software measurement.
This project was co-led by Dr. Sheila McIlraith and Prof. Richard Fikes. Substantial research results and published papers describing those results were produced in multiple technology areas, including the following: 1) Monitoring a Complex Physical System using a Hybrid Dynamic Bayes Net; 2) A Formal Theory of Testing for Dynamical Systems; 3) Diagnosing Hybrid Systems Using a Bayesian Model Selection Approach.
VAPEPS is a computer program that utilizes statistical energy analysis (SEA) theory and SEA extrapolation methods to predict the vibroacoustic environments in complex systems.
This program has been funded by DoE/BES for twenty years. It has moved into and out of various subjects as it has developed, but it has retained its focus on complexity and complex systems. The project has evolved in the following way: Self-Assembly and Biomimetic Self-Assembly: All self-assembling systems depend upon a minimum of two types of interaction: a repulsion and an attraction. For the familiar molecular systems, attractive interactions are typically hydrogen bonds and electrostatic interactions. Repulsive interactions include steric effects, hydrophobic effects (in biological systems), and charge-charge repulsion. We have expanded this repertoire to include surface interactions, magnetic interactions, and others. I list these systems in the order in which we have explored them: i) A key emphasis in current work is in understanding how the movement of ions in a magnetic field (the Lorentz effect) interacts with catalytic systems. We have demonstrated that an acceleration in rate of reduction of CO 2 to CO can be accomplished by applying an external magnetic field. This acceleration is largely due to the application of the Lorentz effect on mass transport at the catalyst’s surface. ii) We have also extensively explored the influence of electrostatics, as exhibited in self-assembling systems, by tribocharging. iii) Another key system involves surface tension effects; examples include interactions between heavy particles floating at a liquid-air interface, and interacting by changes in surface area; interactions of bubbles and bubble rafts, behaviors of bubble trains in microfluidic networks, and behaviors of microorganisms in constraining environments. iv) This work has intentionally de-emphasized biological systems; but it does include some work on protein-ligand interactions and interactions among microorganisms. v) We have also explored applications of some of these effects, these explorations include bubble rafts as diffraction gratings, exploration of the structures that can be obtained by tribocharging and uses of these structures in exploring nucleation and melting of crystals. vi) Although not a major focus of this work, several other topics have emerged and offer opportunities for future work. These include the behavior of bubble trains and bubble rafts in microfluidic systems. A particularly interesting example is the formation of bubble trains that repeat in the alteration of large and small bubbles according to rules we do not presently understand, but are uniquely large-period oscillating systems. These systems offer a new route into understanding the instabilities of the type represented by oscillations. vii) We have also begun exploratory projects on magnetic levitation (especially to determine molecular density), and information storage (in molecules). Magnetic Levitation: Self-assembling and biomimetic systems require both attraction and repulsion. We have used electrostatics (tribocharging), interfacial free-energies (surface tension and related forces) and others. Potential uses include reconfigurable diffraction gratings and liquid lenses; exploration of mechanisms in tribocharging; tunneling in EGaIn junctions; and bubble trains (especially in micro-fluidic systems). Examples of systems representing these topics is included in the following papers: Complexity: Disks rotating at a water-air interface; Benard-Marangoni effects; Vortex-Crystals from spinning magnetic disks (Marangoni effects); EGaIn Electrode to study quantum tunneling; Self-Assembly of electrostatically-charged metallic spheres (electrets); Dynamically reconfigurable lens; Using computational designs of ligands for enzymes; Electrostatic self-assembly by tribocharging; Monodisperse bubble trains in microchannel systems; Inverted dripping faucet; Flames; Printing of micro-organisms to regenerate the “ink” of printing device; Using micro-organisms to move loads (“microoxen”); Motion of bacterial swarms near surfaces; Making monodisperse particles in microfluidic systems; Coding/decoding of information stored in droplet trains in microfluidic networks; Magnetic levitation; and Information storage. i) Tribocharging. The change in focus of this work on electrets from the fundamentals of charging to applications of these materials in studying self-assembly using electrostatic interactions. ii) Bubbles in Microchannels. The realization that systems of bubbles in microchannels represented a major opportunity to study complexity in a very tractable system, and the development of a semi-quantitative theory of this subject. iii) Flames. The growth of “flames” remains an exploratory subject for the research, although their currently relatively little active work involving it ongoing. iv) Systems with Microorganisms. The removal of work in biological systems from this project. Based on work supported in this program, we now have a significant project on the development of microfluidic tools for studying C. elegans (a nematode), but this work was not appropriate for a program focused on complexity, and we developed separate support for it. (It is, however, an example of successful seeding of a new area by BES.) The work on electrets has gone through a period in which a part of the program was the subject of a MURI; the focus of this work was to develop materials that did not charge electrostatically on friction or contact. The MURI is now over, and the work on dynamic self-assembly (supported by BES) is the major focus. “Flames” has also enjoyed synergistic support, in terms of a project supported by DARPA on flame suppression (in the absence of extinguishing agents, using acoustic and electrostatic interactions). This work was helpful in understanding some of the basics of flames, but is entirely distinct from the BES focus in complexity. A growing interest is in the Lorentz effect. The Lorentz effect is the force exerted on charged particles (electrons, ions, charged molecules) when they move through a perpendicular magnetic field. The Lorentz effect is almost ubiquitous in modern technology: examples of applications include electric motors, dynamos, cathode ray tubes, many batteries, and most systems that control electrical currents with magnetic forces. We have begun to explore the Lorentz effect in electrochemical systems and heterogeneous catalytic systems involving charged organic species and inorganic ions. This work is still at an early stage, but initial studies that Lorentz effects can be large when ions move through magnetic fields, or magnetic fields move in the presence of ions.
Mass transport within porous structures is a ubiquitous process in biological, geological, and technological systems. Despite the importance of these phenomena, there is no comprehensive theory that describes the complex and diverse transport behavior within porous environments. While the porous matrix itself is generally considered a static and passive participant, many porous environments are in fact dynamic, with fluctuating walls, pores that open and close, and dynamically changing cross-links. While diffusion has been measured in fluctuating structures, notably in model biological systems, it is rarely possible to isolate the effect of fluctuations because of the absence of control experiments involving an identical static counterpart, and it is generally impossible to observe the dynamics of the structure. In this paper, we present a direct comparison of the diffusion of nanoparticles of various sizes within a trackable, fluctuating porous matrix and a geometrically equivalent static matrix, in conditions spanning a range of regimes from obstructed to highly confined. The experimental system comprised a close-packed layer of colloidal spheres that were either immobilized to a planar surface or allowed to fluctuate locally, within the space defined by their nearest neighbors. Interestingly, the effective long-time diffusion coefficient was approximately 35–65% greater in the fluctuating porous matrix than in the static one (depending on the size of the nanoparticle probes), regardless of the geometric regime. This was explained by considering the enhancing effects of matrix fluctuations on the short-time diffusion coefficient and cooperative “gate-opening” motions of matrix particles and nanoparticle probes.
The goal of this award was to build a research program aimed at investigating puzzling complex phenomena in multiferroics, that are systems possessing electric and magnetic dipoles. We first emphasized the study of multiferroic nanostructures, that are 0D, 1D, 2D systems as well as superlattices and then also study multiferroics as a whole, i.e., bulks as well. In order to fully understand such complex systems, we also decided to study magnetic systems and ferroelectrics, both in their nanostructure and bulk forms. For that and in addition to use standard Density Functional Theory codes, we developed and used ab-initio tools that are able to model properties of large supercells (about a million atoms nowadays) at finite temperature and for any mechanical and boundary conditions. We also collaborated with experimentalists to fully understand the systems under study. The whole program resulted in 108 publications that are listed at the end of this report. In the following, I will put an emphasis on some publications before the last award period and also indicate a description of the last award period.
The development of systematic effective field theories (EFTs) for nuclear forces and advances in solving the nuclear many-body problem have greatly improved our understanding of dense nuclear matter and the structure of finite nuclei. For global nuclear calculations, density functional theories (DFTs) have been developed to reduce the complexity and computational cost required in describing nuclear systems. However, DFT often makes approximations and assumptions about terms included in the functional, which may introduce systematic uncertainties compared to microscopic calculations using EFTs. In this work, we investigate possible avenues of improving nuclear DFT using nonlinear relativistic mean-field (RMF) theory. We explore the impact of RMF model extensions by fitting the nonlinear RMF model to predictions of nuclear matter and selected closed-shell nuclei using four successful chiral EFT Hamiltonians. We find that these model extensions are impactful and important in capturing the physics present within chiral Hamiltonians, particularly for charge radii and neutron skins of closed-shell nuclei. However, there are additional effects that are not captured within the RMF model, particularly within the isoscalar sector of RMF theory. Additional model extensions and the reliability of the nonlinear RMF model are discussed.
X-ray free electron laser (XFEL) microcrystallography and synchrotron single-crystal crystallography are used to evaluate the role of organic substituent position on the optoelectronic properties of metal–organic chalcogenolates (MOChas). MOChas are crystalline 1D and 2D semiconducting hybrid materials that have varying optoelectronic properties depending on composition, topology, and structure. While MOChas have attracted much interest, small crystal sizes impede routine crystal structure determination. A series of constitutional isomers where the aryl thiol is functionalized by either methoxy or methyl ester are solved by small molecule serial femtosecond X-ray crystallography (smSFX) and single crystal rotational crystallography. While all the methoxy examples have a low quantum yield (0-1%), the methyl ester in the ortho position yields a high quantum yield of 22%. Here, the proximity of the oxygen atoms to the silver inorganic core correlates to a considerable enhancement of quantum yield. Four crystal structures are solved at a resolution range of 0.8–1.0 Å revealing a collapse of the 2D topology for functional groups in the 2- and 3- positions, resulting in needle-like crystals. Further analysis using density functional theory (DFT) and many-body perturbation theory (MBPT) enables the exploration of complex excitonic phenomena within easily prepared material systems.
The process of geometric parameter estimation to accuracies of one centimeter, i.e., multilateration, is defined and applications are listed. A brief functional explanation of the theory is presented. Next, various multilateration systems are described in order of increasing system complexity. Expected systems accuracy is discussed from a general point of view and a summary of the errors is listed. An outline of the design of a software processing system for multilateration, called MICRODOT, is presented next. The links of this software, which can be used for multilateration data simulations or operational data reduction, are examined on an individual basis. Functional flow diagrams are presented to aid in understanding the software capability. MICRODOT capability is described with respect to vehicle configurations, interstation coordinate reduction, geophysical parameter estimation, and orbit determination. Numerical results obtained from MICRODOT via data simulations are displayed both for hypothetical and real world vehicle/station configurations such as used in the GEOS-3 Project. These simulations show the inherent power of the multilateration procedure.