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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 1,711 records · Page 95
All sourcesNASA NTRSDOE OSTI
DOE OSTI2016

Structure and magnetic properties of new Be-substituted langasites A{sub 3}Ga{sub 3}Ge{sub 2}BeO{sub 14} (A=Pr, Nd, and Sm)

Langasites have been studied extensively in past for their functional properties and use in telecommunication. A thorough understanding of their ground state is limited by the difficulty in synthesizing new members belonging to this series due to the formation of competing phases such as the garnets. Three magnetic langasites A{sub 3}Ga{sub 3}Ge{sub 2}BeO{sub 14} (A=Pr, Nd, and Sm) and a non-magnetic lattice standard La{sub 3}Ga{sub 3}Ge{sub 2}BeO{sub 14} were synthesized using the ceramic method. These were further characterized by X-ray diffraction, magnetization, magnetic susceptibility and heat capacity measurements. All three langasites exhibit net antiferromagnetic interactions at low temperatures and no evidence of long range magnetic ordering was observed down to 0.350 K. - Graphical abstract: Kagome network formed by the magnetic ions in the new Be-langasites. The ground states of three new members were explored using different physical property measurements such as X-ray diffraction, magnetization, magnetic susceptibility and heat capacity (a–d show refinement patterns for the langasites). These can be added to the list of candidate spin liquid materials. - Highlights: • Four new langasites A{sub 3}Ga{sub 3}Ge{sub 2}BeO{sub 14} (A=La, Pr, Nd, and Sm) were synthesized. • These were characterized using physical and magnetic property measurements. • These langasites exhibit net antiferromagnetic interactions at low temperatures. • No evidence of long range magnetic ordering was observed down to 0.350 K. • Can be potential Spin liquid candidates.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2015

Unexpected Allosteric Network Contributes to LRH-1 Co-regulator Selectivity

Phospholipids (PLs) are unusual signaling hormones sensed by the nuclear receptor liver receptor homolog-1 (LRH-1), which has evolved a novel allosteric pathway to support appropriate interaction with co-regulators depending on ligand status. LRH-1 plays an important role in controlling lipid and cholesterol homeostasis and is a potential target for the treatment of metabolic and neoplastic diseases. Although the prospect of modulating LRH-1 via small molecules is exciting, the molecular mechanism linking PL structure to transcriptional co-regulator preference is unknown. Previous studies showed that binding to an activating PL ligand, such as dilauroylphosphatidylcholine, favors LRH-1's interaction with transcriptional co-activators to up-regulate gene expression. Both crystallographic and solution-based structural studies showed that dilauroylphosphatidylcholine binding drives unanticipated structural fluctuations outside of the canonical activation surface in an alternate activation function (AF) region, encompassing the β-sheet-H6 region of the protein. However, the mechanism by which dynamics in the alternate AF influences co-regulator selectivity remains elusive. In this work, we pair x-ray crystallography with molecular modeling to identify an unexpected allosteric network that traverses the protein ligand binding pocket and links these two elements to dictate selectivity. We show that communication between the alternate AF region and classical AF2 is correlated with the strength of the co-regulator interaction. This work offers the first glimpse into the conformational dynamics that drive this unusual PL-mediated nuclear hormone receptor activation.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS1976

General aviation design synthesis utilizing interactive computer graphics

Interactive computer graphics is a fast growing area of computer application, due to such factors as substantial cost reductions in hardware, general availability of software, and expanded data communication networks. In addition to allowing faster and more meaningful input/output, computer graphics permits the use of data in graphic form to carry out parametric studies for configuration selection and for assessing the impact of advanced technologies on general aviation designs. The incorporation of interactive computer graphics into a NASA developed general aviation synthesis program is described, and the potential uses of the synthesis program in preliminary design are demonstrated.

Galloway, T. L.↗
DOE OSTI2025

Integrating Ultra-Coarse-Grained Protein Models into Accessible Workflows for Multiscale Molecular Dynamics

To capture protein conformational transitions using molecular dynamics (MD), several simulation resolutions covering different spatial and temporal scales are typically needed. All-atom (AA) simulations provide fine resolution, but are computationally infeasible for large systems over longer durations. Coarse-grained (CG) and ultra-coarse-grained (UCG) models have a lower resolution and computational cost while still being able to conserve essential protein features. Prior work on a Multiscale Machinelearned Modeling Infrastructure (MuMMI) combined both AA and CG simulations to study RAS-RAF protein interactions, leveraging CG models for longer time scales and using AA to investigate unusual conformations in greater detail. However, MuMMI is still resource-intensive, and this study aims to maximize exploration of the protein conformational space while reducing computational cost. In this paper, we build on prior work that integrates UCG models based on heterogeneous elastic network modeling (hENM) into the MuMMI workflow. We demonstrate that UCG models enable accurate sampling of protein conformations, focusing on simulating RAS-RAF protein interactions. Using higher-resolution CG Martini simulation data, we can automatically refine intramolecular interactions in UCG models. We present a scalable Python package that uses fluctuations observed in higher-resolution CG Martini simulations to estimate bond coefficients of the UCG model. We built novel machine learning-based backmapping methods to recover more detailed CG Martini structures from UCG structures, using diffusion models to learn the mapping between scales. Finally, we present UCG-mini-MuMMI, an accessible and less compute-intensive version of MuMMI as a resource for the scientific community. Incorporating UCG models into MD studies is applicable to a broad range of systems and proteins, and our study offers insights into the advantages and limitations of these methods.

Chemical structure↗
DOE OSTI2015

Hydrogen-Bonding Network and OH Stretch Vibration of Cellulose: Comparison of Computational Modeling with Polarized IR and SFG Spectra

Hydrogen bonds play critical roles in noncovalent directional interactions determining the crystal structure of cellulose. Although diffraction studies accurately determined the coordinates of carbon and oxygen atoms in crystalline cellulose, the structural information on hydrogen atoms involved in hydrogen-bonding is still elusive. This could be complemented by vibrational spectroscopy; but the assignment of the OH stretch peaks has been controversial. In this study, we performed calculations using density functional theory with dispersion corrections (DFT-D2) for the cellulose Iβ crystal lattices with the experimentally determined carbon and oxygen coordinates. DFT-D2 calculations revealed that the OH stretch vibrations of cellulose are highly coupled and delocalized through intra- and interchain hydrogen bonds involving all OH groups in the crystal. Additionally, molecular dynamics (MD) simulations of a single cellulose microfibril showed that the conformations of OH groups exposed at the microfibril surface are not well-defined. Finally, comparison of the computation results with the experimentally determined IR dichroism of uniaxially aligned cellulose microfibrils and the peak positions of various cellulose crystals allowed unambiguous identification of OH stretch modes observed in the vibrational spectra of cellulose.

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

Changing the Remit to Address on an Ariba Network Invoice [Slides]

The process described in this presentation is optional but will be helpful to suppliers who use multiple remit to addresses in their interactions with LANL. After completing these steps, suppliers will be able to change the remit to address when generating an electronic invoice from the default value assigned by Ariba.

99 GENERAL AND MISCELLANEOUS↗
NASA NTRS1990

An online spacecraft environment interactions information system

This paper reviews the role that EnviroNET assumes as a contemporary system that scientists and engineers can use to share information on networks that are connected globally. Advantage is being taken to use this powerful communication tool for the space community to articulate the various anomalies that our space systems are experiencing. EnviroNET is being considered as a test bed for developing an expert system for diagnosing environmentally induced anomalies for spacecraft. The various offline activities in progress toward this objective are described.

Lauriente, Michael↗
NASA NTRS1992

A distributed system for visualizing and analyzing multivariate and multidisciplinary data

The Linked Windows Interactive Data System (Link Winds) is being developed with NASA support. The objective of this proposal is to adapt and apply that system in a complex network environment containing elements to be found by scientists working multidisciplinary teams on very large scale and distributed data sets. The proposed three year program will develop specific visualization and analysis tools, to be exercised locally and remotely in the Link Winds environment, to demonstrate visual data analysis, interdisciplinary data analysis and cooperative and interactive televisualization and analysis of data by geographically separated science teams. These demonstrations will involve at least two science disciplines with the aim of producing publishable results.

Jacobson, Allan S.↗
DOE OSTI2023

Many-Body Potential for Simulating Self-Assembly of Polymer-Grafted Nanoparticles in a Polymer Matrix

Many-body interactions between polymer-grafted nanoparticles (NPs) play a key role in promoting their assembly into low-dimensional structures within polymer melts, even when the particles are spherical and isotropically grafted. However, capturing such interactions in simulations of NP assembly is very challenging because explicit modeling of the polymer grafts and melt chains is highly computationally expensive, even using coarse-grained models. Here, we develop a many-body potential for describing the effective interactions between spherical polymer-grafted NPs in a polymer matrix through a machine-learning approach. The approach involves using permutationally invariant polynomials to fit two- and three-body interactions derived from the potential of mean force calculations. The potential developed here reduces the computational cost by several orders of magnitude, thereby, allowing us to explore assembly behavior over large length and time scales. We show that the potential not only reproduces previously known assembled phases such as 1D strings and 2D hexagonal sheets, which generally cannot be achieved using isotropic two-body potentials, but can also help discover interesting phases such as networks, clusters, and gels. We demonstrate how each of these assembly morphologies intrinsically arises from a competition between two- and three-body interactions. Our approach for deriving many-body effective potentials can be readily extended to other colloidal systems, enabling researchers to make accurate predictions of their behavior and dissect the role of individual interaction energy terms of the overall potential in the observed behavior.

36 MATERIALS SCIENCE↗
DOE OSTI2012

Inference of gene regulatory networks from genome-wide knockout fitness data

Motivation: Genome-wide fitness is an emerging type of highthroughput biological data generated for individual organisms by creating libraries of knockouts, subjecting them to broad ranges of environmental conditions, and measuring the resulting clone-specific fitnesses. Since fitness is an organism-scale measure of gene regulatory network behaviour, it may offer certain advantages when insights into such phenotypical and functional features are of primary interest over individual gene expression. Previous works have shown that genome-wide fitness data can be used to uncover novel gene regulatory interactions, when compared with results of more conventional gene expression analysis. Yet, to date, few algorithms have been proposed for systematically using genome-wide mutant fitness data for gene regulatory network inference. Results: In this article, we describe a model and propose an inference algorithm for using fitness data from knockout libraries to identify underlying gene regulatory networks. Unlike most prior methods, the presented approach captures not only structural, but also dynamical and non-linear nature of biomolecular systems involved. A state– space model with non-linear basis is used for dynamically describing gene regulatory networks. Network structure is then elucidated by estimating unknown model parameters. Unscented Kalman filter is used to cope with the non-linearities introduced in the model, which also enables the algorithm to run in on-line mode for practical use. Here, we demonstrate that the algorithm provides satisfying results for both synthetic data as well as empirical measurements of GAL network in yeast Saccharomyces cerevisiae and TyrR–LiuR network in bacteria Shewanella oneidensis.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2016

Comparing the accuracy of high-dimensional neural network potentials and the systematic molecular fragmentation method: A benchmark study for all-trans alkanes

Many approaches, which have been developed to express the potential energy of large systems, exploit the locality of the atomic interactions. A prominent example is the fragmentation methods in which the quantum chemical calculations are carried out for overlapping small fragments of a given molecule that are then combined in a second step to yield the system’s total energy. Here we compare the accuracy of the systematic molecular fragmentation approach with the performance of high-dimensional neural network (HDNN) potentials introduced by Behler and Parrinello. HDNN potentials are similar in spirit to the fragmentation approach in that the total energy is constructed as a sum of environment-dependent atomic energies, which are derived indirectly from electronic structure calculations. As a benchmark set, we use all-trans alkanes containing up to eleven carbon atoms at the coupled cluster level of theory. These molecules have been chosen because they allow to extrapolate reliable reference energies for very long chains, enabling an assessment of the energies obtained by both methods for alkanes including up to 10 000 carbon atoms. We find that both methods predict high-quality energies with the HDNN potentials yielding smaller errors with respect to the coupled cluster reference.

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

A large-scale, agent-based simulation of metropolitan freight movements with passenger and freight market interactions

This study summarizes the first stage in the implementation of an agent-based freight modeling system that has a global representation of agents and detailed modeling of a large-scale transportation network. The model is used to evaluate the transportation and energy impacts of goods movement across urban and national scales. The framework is implemented within POLARIS, a C++-based Planning and Operations Language for Agent-based Regional Integrated Simulation, which consists of an activity-based modeling (ABM) and dynamic traffic assignment (DTA) system that has robust features for passenger travel. This platform provides a tool to model interactions among consumers, producers, and the transportation system. The main objective of this initial implementation is to implement a freight model within POLARIS following an agent-based paradigm with behavioral and simulation methods. This paper presents the initial framework and illustrates the application of the model. Building upon earlier works, a parcel location assignment algorithm for business establishments in the population is documented, along with a method for estimating establishment production and consumption volumes. In addition to population generation, other features of the model include push-pull supply chains, multimodal path choice, choice of transportation logistics node, and dynamic traffic assignment. A module with e-commerce supply and demand was also developed to analyze the effects of e-commerce delivery on last-mile energy use and congestion.

agent-based freight↗
DOE OSTI2022

2022 LaserNetUS Users' Meeting

Organized and funded in 2018 through the US Department of Energy, Office of Fusion Energy Sciences (FES), LaserNetUS was created to provide vastly improved access to unique lasers for researchers. LaserNetUS is a network of ten high-power laser facilities, both academic and national laboratories, across the United States and Canada. These labs operate many of the premier mid- to large-scale high-intensity laser facilities in the US and Canada that are designed to be used in pioneering experimental studies in high energy density plasma and high field optical science. The network’s principal goal is to provide access to these state-of-the-art laser facilities to a broad range of researchers in the US and abroad. In its over four years of operation, LaserNetUS has awarded beamtime for over 60 user experiments to researchers from 25 different institutions. Over 400 user scientists, many of whom are students and post-docs, have participated in experiments at LaserNetUS facilities so far. The network now has over 1250 members. The LaserNetUS institutions are Colorado State University, Lawrence Berkeley National Lab, Lawrence Livermore National Lab, SLAC National Lab, The Ohio State University, University of Michigan, University of Nebraska-Lincoln, Institut National de la Recherche Scientifique, University of Rochester, and University of Texas at Austin. LaserNetUS hosted its first in-person Annual Users’ Meeting at Colorado State University in Fort Collins, CO, Aug 16-18, 2022. The meeting had 158 attendees, including 39 sponsored students and post-docs whose attendance and travel to the meeting were covered by DOE funds. Attendees included the 2018 Nobel Laureate in Physics, Donna Strickland. The program consisted of 5 plenary talks and several invited and contributed talks, a user community forum, a poster session, and built-in time for networking. The event focused on students and early career professionals. The poster session was held in combination with a reception to facilitate discussions and maximize interactions between the participants. The 39 sponsored students each presented a poster at the poster session, giving them valuable practice in sharing their research with others in the field. Many students and postdocs also gave talks during the main programming. Lunch and coffee breaks were provided for attendees for the duration of the conference on CSU’s campus. This allowed for networking among all participants. The building used to host the conference also had plenty of seating outside the auditorium, which was conducive to smaller one-on-one meetings and discussions between participants. There was also a lab tour of CSU’s Advanced Beam Laboratory. The day before and after the conference also included satellite meetings for the lab PIs and the Scientific Advisory Board. DOE support was used for rental of the auditorium and supporting rooms, student participation, 50% of the food costs, and transportation to the Advanced Beam Lab.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2017

Crosslinked anion exchange membranes with connected cations

The selective transport of ions has crucial importance in biological systems as well as modern-day energy devices, such as batteries and fuel cells, and water purification membranes. Control over ion movement can be exerted by ligation, ion channel dimensions, solvation, and electrostatic interactions. Polyelectrolyte hydrogels can provide aligned pathways for counter ion transport but lack mechanical integrity, while polyelectrolyte membranes typically suffer from the absence of an ion transport channel network. To develop polymer membranes for improved ion transport, we present the design of a novel material that combines the advantages of aligned pathways found in polyelectrolyte hydrogel and mechanical robustness in conventional membranes. The ionic species were organized via controlled copolymerization of a quaternizable monomer. Additionally, dimensional stability was then incorporated through a cast/crosslinking method to lock in the network of connected cationic groups. This strategy resulted in dramatically enhanced ion transport, as characterized by ionic conductivities (>80 mS/cm for Cl-, and approximate to 200 mS/cm for OH-).

Zhang, Wenxu↗
DOE OSTI2015

Agent-based model forecasts aging of the population of people who inject drugs in metropolitan Chicago and changing prevalence of hepatitis C infections

People who inject drugs (PWID) are at high risk for blood-borne pathogens transmitted during the sharing of contaminated injection equipment, particularly hepatitis C virus (HCV). HCV prevalence is influenced by a complex interplay of drug-use behaviors, social networks, and geography, as well as the availability of interventions, such as needle exchange programs. To adequately address this complexity in HCV epidemic forecasting, we have developed a computational model, the Agent-based Pathogen Kinetics model (APK). APK simulates the PWID population in metropolitan Chicago, including the social interactions that result in HCV infection. We used multiple empirical data sources on Chicago PWID to build a spatial distribution of an in silico PWID population and modeled networks among the PWID by considering the geography of the city and its suburbs. APK was validated against 2012 empirical data (the latest available) and shown to agree with network and epidemiological surveys to within 1%. For the period 2010–2020, APK forecasts a decline in HCV prevalence of 0.8% per year from 44(±2)% to 36(±5)%, although some sub-populations would continue to have relatively high prevalence, including Non-Hispanic Blacks, 48(±5)%. The rate of decline will be lowest in Non-Hispanic Whites and we find, in a reversal of historical trends, that incidence among non-Hispanic Whites would exceed incidence among Non-Hispanic Blacks (0.66 per 100 per years vs 0.17 per 100 person years). APK also forecasts an increase in PWID mean age from 35(±1) to 40(±2) with a corresponding increase from 59(±2)% to 80(±6)% in the proportion of the population >30 years old. Our research highlight the importance of analyzing sub-populations in disease predictions, the utility of computer simulation for analyzing demographic and health trends among PWID and serve as a tool for guiding intervention and prevention strategies in Chicago, and other major cities.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS2009

Workflow Agents vs. Expert Systems: Problem Solving Methods in Work Systems Design

During the 1980s, a community of artificial intelligence researchers became interested in formalizing problem solving methods as part of an effort called "second generation expert systems" (2nd GES). How do the motivations and results of this research relate to building tools for the workplace today? We provide an historical review of how the theory of expertise has developed, a progress report on a tool for designing and implementing model-based automation (Brahms), and a concrete example how we apply 2nd GES concepts today in an agent-based system for space flight operations (OCAMS). Brahms incorporates an ontology for modeling work practices, what people are doing in the course of a day, characterized as "activities." OCAMS was developed using a simulation-to-implementation methodology, in which a prototype tool was embedded in a simulation of future work practices. OCAMS uses model-based methods to interactively plan its actions and keep track of the work to be done. The problem solving methods of practice are interactive, employing reasoning for and through action in the real world. Analogously, it is as if a medical expert system were charged not just with interpreting culture results, but actually interacting with a patient. Our perspective shifts from building a "problem solving" (expert) system to building an actor in the world. The reusable components in work system designs include entire "problem solvers" (e.g., a planning subsystem), interoperability frameworks, and workflow agents that use and revise models dynamically in a network of people and tools. Consequently, the research focus shifts so "problem solving methods" include ways of knowing that models do not fit the world, and ways of interacting with other agents and people to gain or verify information and (ultimately) adapt rules and procedures to resolve problematic situations.

Clancey, William J.↗
DOE OSTI2016

Mixed alkali effect on the spectroscopic properties of alkali-alkaline earth oxide borate glasses

The mixed alkali and alkaline earth oxide borate glass with the composition xK{sub 2}O - (25-x) Li{sub 2}O-12.5BaO-12.5MgO-50B{sub 2}O{sub 3} (x = 0, 5, 10, 15, 20 and 25mol %) and doped with 1mol% CuO were prepared by the melt quenching technique. From the optical absorption spectra the optical band gap, electronic polarizability(α{sub 0}2-), interaction parameter (A), theoretical and experimental optical basicity (Λ) values were evaluated. From the Electron Paramagnetic Resonance (EPR) spectral data the number of spins (N) and susceptibility (χ) were evaluated. The values of (α{sub 0}2-), and (Λ) increases with increasing of K{sub 2}O content and electronic polarizability and interaction parameter show opposite behaviuor which may be due to the creation of non-bridging oxygens and expansion of borate network. The reciprocal of susceptibility (1/χ) and spin concentration (N) as a function of K{sub 2}O content, varied nonlinearly which may be due to creation of non-bridging oxygens in the present glass system. This may be attributed to mixed alkali effect (MAE).

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2019

Forecasting district-scale energy dynamics through integrating building network and long short-term memory learning algorithm

With the development of data-driven techniques, building energy prediction on a district level has attracted increasing attention in recent years for revealing energy use patterns and reduction potentials. However, data acquisition in large building groups is difficult and adjacent buildings also interact with each other. To reduce data cost and incorporate the inter-building impact with the data-driven building energy model, this study proposes a deep learning predictive approach that fuses the building network model with a long short-term memory learning model for district-scale building energy modeling. The building network was constructed based on correlations between the energy use intensity of buildings, which can significantly reduce the computational complexity of the deep learning models for energy dynamic prediction. Five typical building groups with energy use data from 2015 to 2018 on two institutional campuses were selected to perform the validation experiment with TensorFlow. Based on the prediction error assessments, the results suggest that for total building energy use intensity prediction, the proposed model can achieve a mean absolute percentage error of 6.66% and a root mean square error of 0.36 kWh/m 2 , compared to 12.05% and 0.63 kWh/m 2 of the conventional artificial neural network model and to 11.06% and 0.89 kWh/m 2 for the support vector regression model.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗