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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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At least 1,369 records · Page 76
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DOE OSTI2020

The Koopman Operator: Capabilities and Recent Advances

In this paper, we provide an introduction to the Koopman Operator (KO) designed to be accessible to those not already familiar with the field. Our aim is to expose domain experts and controls practitioners to the concept and the capabilities the KO provides in the interest of promoting wider KO use; as such, we deliberately focus more on the uses and computational aspects of the KO than on the wealth of analytical results in the literature. Those researchers may then be able to pose new applications-based research questions for the KO community. We begin by defining the KO and describing its key components. Secondly, we discuss computational methods used to calculate the KO in practice. Thirdly, we provide an overview of different uses for the KO and its associated capabilities. Finally, we discuss some open areas of research for future KO work.

koopman operator, dynamical systems, optimal contr↗
DOE OSTI2025

Power Flow Geometry and Approximation

Here, the power flow equations are important in numerous power systems problems of practical interest which consider alternating current power flow (ACPF) physics. Perhaps the most well studied being the alternating current optimal power flow problem (ACOPF), seeking to optimize the operation of an electric power system. Due to their non-linearity, problems which include the power flow equations are typically challenging, particularly in optimization. Interestingly, the set of solutions to the power flow equations forms a smooth manifold. As a result, differential geometry can be used to describe and analyze this set of equations. This approach has proven effective in several engineering applications (e.g., solving ACOPF and analyzing the solution space boundary). Central to the success of this approach is an understanding of the power flow manifold's geometry. In this work, we develop the geometric and topological properties of this manifold using concepts from differential geometry. After demonstrating the convenience of this manifold's representation as a function's graph, computational methods are emphasized: we develop retractions, error bounds for linear approximation, and formulas for evaluating the Riemannian metric (including associated objects such as geodesics and the curvature tensor). Scalar curvature and the second fundamental form play a new role in quantifying the quality of linear approximations, like the popular direct current approximation. All functions are implemented in Julia and available in an online repository. Proofs are included for completeness.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2023

RNAseq analysis of Cellvibrio japonicus during starch utilization differentiates between genes encoding carbohydrate active enzymes controlled by substrate detection or growth rate

ABSTRACT Bacterial utilization of starch is increasingly of interest as the importance and contributions of animal gut microbiomes become more defined. Consequently, identifying and characterizing the bacterial enzymes responsible for the degradation, transport, and metabolism of starch will enable developments in pharmaceutical, biotechnological, and culinary industries searching for novel prebiotics, carrier molecules, and low glycemic index sweeteners. The current challenge is that bacteria proficient at starch utilization often have hundreds of carbohydrate active enzymes, and it is unclear which are essential for starch utilization using only homology-based bioinformatics or computational methods. Complementary experimental data are also needed, especially to understand the regulation of bacterial starch utilization. We have completed an RNAseq analysis of the Gram-negative bacterium Cellvibrio japonicus and found that it has sophisticated regulation that includes substrate sensing and growth rate components for genes that encode starch-degrading enzymes. Among the 22 genes predicted to encode starch-active enzymes, C. japonicus has 10 alpha-amylases, 4 alpha-glucosidases, 2 pullulnases, and 2 cyclomaltodextrin glucanotransferases, 15 of which were up-regulated during exponential growth on starch and 8 up-regulated in stationary phase. Growth analyses with an enzyme secretion deficient mutant of C. japonicus suggested that secreted amylases are essential for this bacterium to degrade starch. Our approach of coupling a physiological growth assay with transcriptomic data provides a platform to identify targets for further genetic or biochemical analysis that can be broadly applied to other starch-utilizing bacteria. IMPORTANCE Understanding the bacterial metabolism of starch is important as this polysaccharide is a ubiquitous ingredient in foods, supplements, and medicines, all of which influence gut microbiome composition and health. Our RNAseq and growth data set provides a valuable resource to those who want to better understand the regulation of starch utilization in Gram-negative bacteria. These data are also useful as they provide an example of how to approach studying a starch-utilizing bacterium that has many putative amylases by coupling transcriptomic data with growth assays to overcome the potential challenges of functional redundancy. The RNAseq data can also be used as a part of larger meta-analyses to compare how C. japonicus regulates carbohydrate active enzymes, or how this bacterium compares to gut microbiome constituents in terms of starch utilization potential.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Optimal Experimental Design for Inverse Problems in the Presence of Observation Correlations

Optimal experimental design (OED) is the general formalism of sensor placement and decisions on the data collection strategy for engineered or natural experiments. This problem is prevalent in many critical fields such as battery design, numerical weather prediction, geosciences, environmental and urban studies. State-of-the-art computational methods for experimental design do not accommodate correlation structure in observational errors produced by many expensive-to-operate devices such as X-ray machines, radars, and satellites. Discarding evident data correlations leads to biased results, higher expenses, and waste of valuable resources. We present a general formulation of the OED formalism for model-constrained large-scale Bayesian linear inverse problems, where measurement errors are generally correlated. The proposed approach utilizes the Hadamard product of matrices to formulate the weighted-likelihood, and is valid for both finite as well as infinite-dimensional Bayesian inverse problems. Extensive numerical experiments are carried out for empirical verification of the proposed approach using an advection-diffusion model, where the objective is to optimally place a small set of sensors, under a limited budget, to predict the concentration of a contaminant in a closed and bounded domain.

Correlated observations↗
DOE OSTI2021

A.I. for nuclear physics

Nuclear science is concerned with the understanding of the nature of matter, its basic constituents and their interaction to form the elements and the properties we observe. This includes the forms of matter we see around us and also exotic forms such as those that existed in the first moments after the Big Bang and that exist today inside neutron stars. The techniques, tools, and expertise needed for nuclear physics (NP) research are therefore diverse in nature. State-of-the art accelerators are being developed to illuminate the dynamical basis of the core of the atom in terms of the fundamental constituents called quarks and gluons and to increase the number of isotopes with known properties. This scientific infrastructure is reaching scales and complexities that require computational methods for tasks such as anomaly detection in operational data. New methodologies are needed to detect anomalies and to optimize operating parameters, predict failures as well as to discover new optimization algorithms.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2023

Remembering the Work of Phillip L. Geissler: A Coda to His Scientific Trajectory

Phillip L. Geissler made important contributions to the statistical mechanics of biological polymers, heterogeneous materials, and chemical dynamics in aqueous environments. He devised analytical and computational methods that revealed the underlying organization of complex systems at the frontiers of biology, chemistry, and materials science. In this retrospective we celebrate his work at these frontiers.

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

Ab Initio Studies of Discharge Mechanism of MnO 2 in Deep-Cycled Rechargeable Zn/MnO 2 Batteries

Rechargeable alkaline Zn/MnO 2 batteries are an attractive solution for large-scale energy storage applications. Recently, Bi and Cu additives have been used to increase the cycle life and capacity of rechargeable Zn/MnO 2 batteries, with an equivalent of the full two-electron capacity realized for many cycles, in the absence of zinc. However, the mechanism of the effect of Bi and Cu on the performance of rechargeable Zn/MnO 2 batteries has not been investigated in detail. We apply first-principles density functional computational methods to study the discharge mechanisms of the unmodified and Bi/Cu-modified γ -MnO 2 electrodes in rechargeable alkaline Zn/MnO 2 batteries. Using the results of our calculations, we analyze the possible redox reaction pathways in the γ -MnO 2 electrode and identify the electrochemical processes leading to the formation of irreversible discharge reaction products, such as hausmannite and hetaerolite. Our study demonstrates the possibility of formation of intermediate Bi-Mn and Cu-Mn oxides in deep-cycled Bi/Cu-modified MnO 2 electrodes. The formation of intermediate Bi-Mn and Cu-Mn oxides could reduce the rate of accumulation of irreversible reaction products in the MnO 2 electrode and improve the rechargeability and cyclability of Zn/MnO 2 batteries.

25 ENERGY STORAGE↗
DOE OSTI2024

RGM: Random Geological Model Generation Package

This Fortran code is to accompany a manuscript to be submitted to Computers & Geosciences, a high-impact, peer-reviewed journal in computer methods for geosciences research. This Fortran code focuses on generation of synthetic geological models using a multi-randomization strategy. Generating high-fidelity synthetic geological models, including realistic seismic reflector migration images, faults, salt bodies, and relative geological time images, is the key for many supervised machine learning methods that aim to delineate faults and other geological properties of interest from seismic migration images. Our package contains two major functionalities: generating 2D synthetic random geological models and generating 3D synthetic random geological models. In each step of the generation process, we set random values for key properties of a geological model to improve the fidelity of the resulting geological model. The package also includes example codes on how to use the random geological model generation subroutines. We name this package RGM – Random Geological Model generation package.

Gao, Kai↗
DOE OSTI2024

Common Electric Power Transmission System Model JSON Schema Specification

The Common Electric Power Transmission System Model (CTM) is an intuitive, extensible, language-agnostic, and error-resistant specification of electric power network components parameter names and units, and relation between components, intended for use by the research community developing new computational methods for power systems operations and simulation. Power system datasets following the CTM specification can be read as dictionaries and manipulated in that form in most programming languages (e.g., Python, Julia, C++). This standard data structure in CTM makes it easy to work in multiple power systems domains (e.g., economic operation, reliability assessment, electricity markets, stability assessment, etc.) without requiring conversions between use-case-specific file formats with information loss in the process. This repository specifies CTM as a JSON Schema, provides documentation, derivate (code-generated) implementations of CTM, and example data and usage of the schema for important use cases.

Aravena Solis, Ignacio↗
DOE OSTI2020

AlphaBeta: computational inference of epimutation rates and spectra from high-throughput DNA methylation data in plants

Stochastic changes in DNA methylation (i.e., spontaneous epimutations) contribute to methylome diversity in plants. Here, we describe AlphaBeta, a computational method for estimating the precise rate of such stochastic events using pedigree-based DNA methylation data as input. We demonstrate how AlphaBeta can be employed to study transgenerationally heritable epimutations in clonal or sexually derived mutation accumulation lines, as well as somatic epimutations in long-lived perennials. Application of our method to published and new data reveals that spontaneous epimutations accumulate neutrally at the genome-wide scale, originate mainly during somatic development and that they can be used as a molecular clock for age-dating trees.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Metadynamics simulations reveal mechanisms of Na + and Ca 2+ transport in two open states of the channelrhodopsin chimera, C1C2

Cation conducting channelrhodopsins (ChRs) are a popular tool used in optogenetics to control the activity of excitable cells and tissues using light. ChRs with altered ion selectivity are in high demand for use in different cell types and for other specialized applications. However, a detailed mechanism of ion permeation in ChRs is not fully resolved. Here, we use complementary experimental and computational methods to uncover the mechanisms of cation transport and valence selectivity through the channelrhodopsin chimera, C1C2, in the high- and low-conducting open states. Electrophysiology measurements identified a single-residue substitution within the central gate, N297D, that increased Ca 2+ permeability vs. Na + by nearly two-fold at peak current, but less so at stationary current. We then developed molecular models of dimeric wild-type C1C2 and N297D mutant channels in both open states and calculated the PMF profiles for Na + and Ca 2+ permeation through each protein using well-tempered/multiple-walker metadynamics. Results of these studies agree well with experimental measurements and demonstrate that the pore entrance on the extracellular side differs from original predictions and is actually located in a gap between helices I and II. Cation transport occurs via a relay mechanism where cations are passed between flexible carboxylate sidechains lining the full length of the pore by sidechain swinging, like a monkey swinging on vines. In the mutant channel, residue D297 enhances Ca 2+ permeability by mediating the handoff between the central and cytosolic binding sites via direct coordination and sidechain swinging. We also found that altered cation binding affinities at both the extracellular entrance and central binding sites underly the distinct transport properties of the low-conducting open state. This work significantly advances our understanding of ion selectivity and permeation in cation channelrhodopsins and provides the insights needed for successful development of new ion-selective optogenetic tools.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Modulating ion-binding at macromolecular interfaces during (bio)mineralization: A snapshot review for calcium carbonate and calcium phosphate systems

Abstract Local environments have strict influence over (bio)mineralization in calcifying systems. This snapshot review discusses recent insights into the roles of Ca 2+ -macromolecule interactions on the nucleation of calcium carbonate and calcium phosphate minerals. Experimental findings combined with simulations/modeling are providing breakthrough information and raising important questions for future studies. The emerging picture is that both nucleation and growth are driven by local ordering of ions and water about the macromolecule interface, rather than broader properties or molecular class. Tuning macromolecular properties at the atomic scale thus provides opportunities for highly specific controls on mineralization; however, many limitations and challenges remain. We highlight studies employing in-situ atomic force microscopy (AFM) and transmission electron microscopy (TEM) to observe crystallization processes on or near macromolecular substrates. As the distribution and ability of these techniques increases, fundamental studies integrating experimental and computational methods will be crucial to inform a broad range of applications. Graphical abstract

Knight, Brenna M. (ORCID:0000000244000067)↗
DOE OSTI2025

Preliminary study of auto-differentiation algorithm in beam dynamics with stochastic process

Modern particle accelerator optimization requires sophisticated computational methods to address the inherently stochastic nature of beam dynamics. This research develops a framework applying AD to SDEs that specifically addresses beam dynamics challenges in particle accelerators, focusing on accurately modeling and optimizing beam behavior in regimes dominated by stochastic processes. By incorporating key physical phenomena such as synchrotron radiation, wakefield effects, and quantum excitation, the framework aims to provide auto differentiation on the figure of merit of the phase space evolution and beam dynamics. The methodology will enable effective optimization method in a dynamic system with stochastic process.

Accelerator Physics↗
DOE OSTI2019

Probing catalytic activity in defect sites in transition metal oxides and sulfides using cluster models: A combined experimental and theoretical approach

Our research program has combined experimental and computational methods to study a range of cluster models for heterogeneous catalytic materials. The focus of our studies has been transition metal oxide and sulfide clusters in non-traditional oxidation states, and their chemical and physical interactions with water, to model steps in the electrocatalytic or photocatalytic hydrogen evolution reaction (HER). In the closing year of this project, we have also begun to explore addition systems in preparation for future grant proposals.

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

Basic Research Needs for Transformative Manufacturing (Brochure)

Manufacturing is central to the nation’s prosperity and security. Manufacturing currently represents about 12% of the gross domestic product, provides nearly 13 million jobs, and accounts for about 25% of energy use. The nation’s economy relies heavily on wide-ranging manufacturing sectors - all of which share common challenges including data issues, lack of physics and chemistry-based models across scales, and resource constraints in a global environment. Furthermore, there are many hurdles that must be overcome to move basic science innovations to market. Addressing broad-ranging challenges demands a basic-science strategy that underpins applied research activities. This strategy would accelerate innovation and transform manufacturing. A Basic Research Needs workshop for Transformative Manufacturing was held in March 2020. The focus of the workshop was to identify the basic science research priorities that could accelerate innovation to transform manufacturing in the future. This was the first workshop of its kind to examine how basic energy science can drive manufacturing forward and innovate new ways to manufacture goods. Five Priority Research Directions were identified that address these science challenges: (1) innovative synthetic approaches to enable scalable assembly of matter, (2) computational methods and theoretical models to transform how manufacturing processes are controlled, (3) new characterization tools that can handle the necessary complexity, scales, and processing speeds to meet manufacturing needs, (4) new science to address opportunities relevant to sustainable and energy-efficient manufacturing, and (5) foundational approaches to co-design of materials, process, and products.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2020

Basic Research Needs for Transformative Manufacturing

This report is based on a Basic Research Needs workshop for Transformative Manufacturing, which was held March 9 - 11, 2020. The focus of the workshop was to identify the basic science research priorities that could accelerate innovation to transform manufacturing in the future. This was the first workshop of its kind to examine how basic energy science can drive manufacturing forward and innovate new ways to manufacture goods. Five Priority Research Directions were identified that address these science challenges: (1) innovative synthetic approaches to enable scalable assembly of matter, (2) computational methods and theoretical models to transform how manufacturing processes are controlled, (3) new characterization tools that can handle the necessary complexity, scales, and processing speeds to meet manufacturing needs, (4) new science to address opportunities relevant to sustainable and energy efficient manufacturing, and (5) foundational approaches to co-design of materials, process, and products.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2020

Roles of Carburization and Oxidation on Transition-Metal Catalyzed Surface Reactions

Many industrial chemical transformation processes are based on reactions catalyzed by transition metals. In some cases the nano-size particles used as catalysts are synthesized simultaneously or right before the initiation of the main catalytic reaction. Synthesis treatments involve complex processes such as reductions followed by calcinations in oxygenated environments coupled to the presence of gases used for the main reaction. Synthesis details are crucial because they have important consequences on the catalyst shape, size, and chemical composition, and may also affect the structure and composition of the catalyst support. All these effects may alter the main catalyzed reaction in unexpected ways. This work focuses on the synthesis of the overall catalytic system that includes catalyst and support taking place in parallel with the initial stages of the main catalyzed reaction. Two important processes are characterized: carburization and oxidation of the transition metal catalyst during synthesis or initial stages of the main reaction. The objective is to understand how the coking mechanism coupled to surface oxidation and changes in the substrate influence the dry reforming of methane taken as a model reaction. The approach uses first principles computational methods to investigate the catalyst synthesis and characterization and catalytic reaction mechanisms. These studies are complemented with experimental characterization done by the group of Dr. Renu Sharma at the National Institute of Standards and Technology (unfunded collaborator) using high resolution transmission electron microscopy. Specific goals are to identify the role of the synthesis process on the initial nanocatalyst structure and composition, and to determine how that structure and composition may evolve after being exposed to the reactants atmosphere. These studies facilitate a systematic analysis of conditions where the nanoparticle composition can be optimized regarding activity and stability. Moreover, the fundamental study of catalyst/support interactions yields valuable insights for other catalytic processes and is a first step toward controlled nanocatalyst synthesis.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Using Raman scattering to study reacting gas flow over a catalyst

l present a series of computational methods for analyzing and correcting Raman scattering from a reacting gas flow. My work focused on the laser diagnostic measurements of formaldehyde production over a silver catalyst, specifically the Raman spectroscopy component. This technique offers a non-intrusive, in situ way to measure the coupling between the gas phase and surface activity of a catalytic reaction at relevant industrial conditions. This report outlines the steps followed for correcting the non-idealities in the data due to both the detection optics and scattering mechanics. By implementing such refinement steps, l can generate an accurate 2D spatial map of the temperature profile, number densities for major species, and relative consumption of reactants throughout the reactor cell.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗