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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 631 records · Page 35

All sources NASA NTRS DOE OSTI

DOE OSTI2019

A nanofluidic ion regulation membrane with aligned cellulose nanofibers

The advancement of nanofluidic applications will require the identification of materials with high-conductivity nanoscale channels that can be readily obtained at massive scale. Inspired by the transpiration in mesostructured trees, we report a nanofluidic membrane consisting of densely packed cellulose nanofibers directly derived from wood. Numerous nanochannels are produced among an expansive array of one-dimensional cellulose nanofibers. The abundant functional groups of cellulose enable facile tuning of the surface charge density via chemical modification. The nanofiber-nanofiber spacing can also be tuned from ~2 to ~20 nm by structural engineering. The surface-charge-governed ionic transport region shows a high ionic conductivity plateau of ~2 mS cm -1 (up to 10 mM). The nanofluidic membrane also exhibits excellent mechanical flexibility, demonstrating stable performance even when the membrane is folded 150°. Combining the inherent advantages of cellulose, this novel class of membrane offers an environmentally responsible strategy for flexible and printable nanofluidic applications.

36 MATERIALS SCIENCE↗

DOE OSTI2020

Scanning Probe Microscopy in the Information Age

Scanning probe microscopy (SPM) has brought scientific exploration, visualization, and control to nanoscale. A plethora of measurement approaches and techniques devised around SPM enabled probing structure and functionalities crucial for virtually all areas of science. While high-resolution electron microscopy techniques preceded scanning probes, SPM effectively opened the door to probing the structure–property relationship on length scales spanning 100s of micrometers down to a single atom. As the complexity of the material systems and the scientific questions increased, so too did the SPM techniques. Substantial efforts have been dedicated toward the development of better instrumentation platforms, probes, and novel spectroscopic measurements; however, many opportunities related to data processing and acquisition in SPM are just being realized now. This chapter will describe the recent progress in data-driven SPM by giving a broad overview of the field, the foundation of the scanning tunneling microscope (STM) and the atomic force microscope (AFM), as well as a description behind the operating principles and dynamic modes. A comprehensive overview of the multi-frequency techniques, Band excitation, and general acquisition mode SPM is given, setting the context for the application of big data, machine learning, and artificial intelligence in the field of dynamic SPM.

Collins, Liam↗

DOE OSTI2020

BEEAM (Building Electrical Efficiency Analysis Model) [SWR-20-107]

Modern high-performance buildings exhibit an increasing number of building loads that use direct current (DC) electricity internally, rather than alternating current (AC), due to the advent of low-cost computing and advanced power electronics. Powering DC devices from the AC grid requires AC/DC power conversion, which introduces energy losses and reduces efficiency. As DC loads proliferate, the cumulative wasted energy associated with hundreds of millions of AC/DC converters has become one of the broadest energy savings opportunities in buildings. DC power distribution systems have been proposed as an elegant and transformative solution to the problem of DC devices. In a DC distribution system, the building's wires carry DC electricity, rather than AC; and a few centralized, highly efficient AC/DC converters replace the many smaller, less efficient converters that serve individual DC loads. Unfortunately, the trade-offs associated with DC distribution systems are not well understood. Reported energy savings associated with DC power distribution differ widely and have not been well validated. The Building Electrical Efficiency Analysis Model (BEEAM) is a Modelica library that simulates the efficiency of building electrical distribution systems using harmonic power flow. BEEAM can model a wide variety of building distribution topologies, including three-phase AC, single-phase AC, unipolar DC, bipolar DC, and hybrid networks under both balanced and unbalanced load conditions. BEEAM accurately models power electronic converter losses, provides granular estimates of losses throughout the distribution system, and properly models efficiency at part load conditions. Users can package BEEAM within a functional mockup unit (FMU), enabling co-simulation with other modeling platform, such as EnergyPlus. In summary, BEEAM provides a tool suite for fair and accurate comparison of the efficiency of building electrical distribution systems, including AC, DC, and hybrid systems.

Frank, Stephen↗

DOE OSTI2024

Multiplayer Engineering

INL engineers developed a special purpose software framework designed to establish real-time connections between multiple running Unity instances. The framework is developed in Unity, a game engine development platform. This framework programmatically attaches functions to engineering models, enabling users to interact with, observe, and make changes to virtual models. These interactions are broadcasted through websocket connections, and received by other engineers in real-time.

Woodruff, Nathan↗

DOE OSTI2012

Using a Simple Binomial Model to Assess Improvement in Predictive Capability: Sequential Bayesian Inference, Hypothesis Testing, and Power Analysis

We present a Bayesian statistical methodology for identifying improvement in predictive simulations, including an analysis of the number of (presumably expensive) simulations that will need to be made in order to establish with a given level of confidence that an improvement has been observed. Our analysis assumes the ability to predict (or postdict) the same experiments with legacy and new simulation codes and uses a simple binomial model for the probability, {theta}, that, in an experiment chosen at random, the new code will provide a better prediction than the old. This model makes it possible to do statistical analysis with an absolute minimum of assumptions about the statistics of the quantities involved, at the price of discarding some potentially important information in the data. In particular, the analysis depends only on whether or not the new code predicts better than the old in any given experiment, and not on the magnitude of the improvement. We show how the posterior distribution for {theta} may be used, in a kind of Bayesian hypothesis testing, both to decide if an improvement has been observed and to quantify our confidence in that decision. We quantify the predictive probability that should be assigned, prior to taking any data, to the possibility of achieving a given level of confidence, as a function of sample size. We show how this predictive probability depends on the true value of {theta} and, in particular, how there will always be a region around {theta} = 1/2 where it is highly improbable that we will be able to identify an improvement in predictive capability, although the width of this region will shrink to zero as the sample size goes to infinity. We show how the posterior standard deviation may be used, as a kind of 'plan B metric' in the case that the analysis shows that {theta} is close to 1/2 and argue that such a plan B should generally be part of hypothesis testing. All the analysis presented in the paper is done with a general beta-function prior for {theta}, enabling sequential analysis in which a small number of new simulations may be done and the resulting posterior for {theta} used as a prior to inform the next stage of power analysis.

42 ENGINEERING↗

DOE OSTI2017

Connected Equipment Maturity Model Version 1.0

The Connected Equipment Maturity Model (CEMM) evaluates the high-level functionality and characteristics that enable equipment to provide the four categories of energy-related services through communication with other entities (e.g., equipment, third parties, utilities, and users). The CEMM will help the U.S. Department of Energy, industry, energy efficiency organizations, and research institutions benchmark the current state of connected equipment and identify capabilities that may be attained to reach a more advanced, future state.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2016

VOLTTRON 2016

VOLTTRON is a flexible, reliable, and scalable platform for distributed control and sensing. VOLTTRON serves in four primary roles: •A reference platform for researchers to quickly develop control applications for transactive energy. •A reference platform with flexible data store support for energy analytics applications either in academia or in commercial enterprise. •A platform from which commercial enterprise can develop products without license issues and easily integrate into their product line. •An accelerator to drive industry adoption of transactive energy and advanced building energy analytics. Pacific Northwest National Laboratory, with funding from the U.S. Department of Energy’s Building Technologies Office, developed and maintains VOLTTRON as an open-source community project. VOLTTRON source code includes agent execution software; agents that perform critical services that enable and enhance VOLTTRON functionality; and numerous agents that utilize the platform to perform a specific function (fault detection, demand response, etc.). The platform supports energy, operational, and financial transactions between networked entities (equipment, organizations, buildings, grid, etc.) and enhance the control infrastructure of existing buildings through the use of open-source device communication, control protocols, and integrated analytics.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2018

γ-Valerolactone-Extracted Lignin to Porous Carbon Materials

Synthesis of multiphase materials from lignin, a biorefinery coproduct, offers limited success due to the inherent difficulty in controlling dispersion of these renewable hyperbranched macromolecules in the product or its intermediates. Effective use of the chemically reactive functionalities in lignin, however, enables tuning morphologies of the materials. Here, we bind a lignin oligomer with a rubbery macromolecule followed by thermal crosslinking to form a carbon precursor with phase contrasted morphology at submicron scale. The solvent-free mixing is conducted in a high-shear melt-mixer. With this, the carbon precursor is further modified with potassium hydroxide for a single-step carbonization to yield activated carbon with tunable pore structure. A typical precursor with 90% lignin yields porous carbon with 2120 m 2 /g surface area and a supercapacitor with 215 F/g capacitance. The results show a simple route towards manufacturing carbon-based energy-storage materials, eliminating the need for conventional template-synthesis.

36 MATERIALS SCIENCE↗

DOE OSTI2016

Basic Research Needs for Quantum Materials (Brochure)

In a world of technologies built on quantum materials, computers will work a million times faster than today’s supercomputers while using a fraction as much energy. Electricity will be generated, transmitted, and used with almost no losses. Smart building materials, fabrics, and electronic devices will change their properties on demand to satisfy our needs. The astounding effects of quantum mechanics will enable materials properties and functions that seem like science fiction today.

36 MATERIALS SCIENCE↗

DOE OSTI2020

Supercritical CO2 sterilization of N95 Masks

A preliminary investigation of the use of supercritical carbon dioxide for treating of 3M 1860 N95 masks was undertaken to evaluate a potential route to low-cost, scalable, sterilization of personal protective equipment for multiple reuse in hospital settings. Upon entering the supercritical regime, the normally distinct liquid and gaseous phases of CO 2 merge into a single homogeneous phase that has density, short-range order, and solvation capacity of a liquid, but the volume-filling and permeation properties that of a gas. This enables supercritical CO2 to function as a vehicle for delivery of biocidal agents such peracetic acid into microporous structures. The potentially adverse effect of a liquid-to-gas phase transition on mask filter media is avoided by conducting cleaning operations above 31 C, the critical temperature for carbon dioxide. A sample of fifteen 3M 1860 N95 masks was subjected to ten consecutive cycles of supercritical CO 2 cleaning to determine its effect on mask performance. These 15 masks, along with 5 control samples then underwent a battery of standardized tests at the CDC NIOSH NPPTL research facility in Pittsburgh, PA. The data from these tests strongly suggest (but do not prove) that supercritical carbon dioxide do not damage 3M 1860 N95 masks. Additional tests conducted during this project confirmed the compatibility of supercritical CO 2 with ventilator tubing that, like N95 masks, has been in short supply during portions of the COVID-19 pandemic and cannot be sterilized by conventional means. Finally, a control experiment was also conducted to examine the effect of supercritical CO 2 on a BSL-2 surrogate virus, vesicular stomatitis virus (VSV), Indiana serotype strain. In the absence of biocidal additives, supercritical CO 2 exhibited no measurable lethality against VSV. This surrogate virus experiment suggests that a biocidal additive such as peracetic acid will be necessary to achieve required sterilization metrics.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2017

Connected Equipment Maturity Model (V.1.0)

42 ENGINEERING↗

DOE OSTI2025

Self-Organization of Plasma-Material Interfaces

The primary goals of the project are a) improve the understanding of transport processes, chemical reactions and plasma-driven self-organization such as stratification and filamentation, formation of anode spots, liquid droplets ejection from cathodes, and plasma electrolysis, b) utilize and share among the project participants computational tools developed by the participants to understand plasma-based surface functionalization and plasma-enabled pattern nucleation in a wide range of scales from nano- to millimeters, and c) use experimental methods and facilities available at the University of Alabama in Huntsville (UAH) and Sandia National Laboratories (SNL) to understand and control plasma processes, reaction pathways and the electric nature of self-organization of the plasma-exposed interface structures.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2013

The New Modularization Framework for the FAST Wind Turbine CAE Tool

NREL has recently put considerable effort into improving the overall modularity of its FAST wind turbine aero-hydro-servo-elastic tool to (1) improve the ability to read, implement, and maintain source code; (2) increase module sharing and shared code development across the wind community; (3) improve numerical performance and robustness; and (4) greatly enhance flexibility and expandability to enable further developments of functionality without the need to recode established modules. The new FAST modularization framework supports module-independent inputs, outputs, states, and parameters; states in continuous-time, discrete-time, and in constraint form; loose and tight coupling; independent time and spatial discretizations; time marching, operating-point determination, and linearization; data encapsulation; dynamic allocation; and save/retrieve capability. This paper explains the features of the new FAST modularization framework, as well as the concepts and mathematical background needed to understand and apply it correctly. It is envisioned that the new modularization framework will transform FAST into a powerful, robust, and flexible wind turbine modeling tool with a large number of developers and a range of modeling fidelities across the aerodynamic, hydrodynamic, servo-dynamic, and structural-dynamic components.

17 WIND ENERGY↗

DOE OSTI2022

The DREAM Endstation at the Linac Coherent Light Source

Free-electron lasers (FEL), with their ultrashort pulses, ultrahigh intensities, and high repetition rates at short wavelength, have provided new approaches to Atomic and Molecular Optical Science. One such approach is following the birth of a photo electron to observe ion dynamics on an ultrafast timescale. Such an approach presents the opportunity to decipher the photon-initiated structural dynamics of an isolated atomic and molecular species. It is a fundamental step towards understanding single- and non-linear multi-photon processes and coherent electron dynamics in atoms and molecules, ultimately leading to coherent control following FEL research breakthroughs in pulse shaping and polarization control. A key aspect for exploring photoinduced quantum phenomena is visualizing the collective motion of electrons and nuclei in a single reaction process, as dynamics in atoms/ions proceed at femtosecond (10 –15 s) timescales while electronic dynamics take place in the attosecond timescale (10 –18 s). Here, we report on the design of a Dynamic Reaction Microscope (DREAM) endstation located at the second interaction point of the Time-Resolved Molecular and Optical (TMO) instrument at the Linac Coherent Light Source (LCLS) capable of following the photon–matter interactions by detecting ions and electrons in coincidence. The DREAM endstation takes advantage of the pulse properties and high repetition rate of LCLS-II to perform gas-phase soft X-ray experiments in a wide spectrum of scientific domains. With its design ability to detect multi-ions and electrons in coincidence while operating in step with the high repetition rate of LCLS-II, the DREAM endstation takes advantage of the inherent momentum conservation of reaction product ions with participating electrons to reconstruct the original X-ray photon–matter interactions. In this report, we outline in detail the design of the DREAM endstation and its functionality, with scientific opportunities enabled by this state-of-the-art instrument.

47 OTHER INSTRUMENTATION↗

DOE OSTI2012

Cell Growth on Different Types of Ultrananocrystalline Diamond Thin Films

Unique functional materials provide a platform as scaffolds for cell/tissue regeneration. Investigation of cell-materials’ chemical and biological interactions will enable the application of more functional materials in the area of bioengineering, which provides a pathway to the novel treatment for patients who suffer from tissue/organ damage and face the limitation of donation sources. Many studies have been made into tissue/organ regeneration. Development of new substrate materials as platforms for cell/tissue regeneration is a key research area. Studies discussed in this paper focus on the investigation of novel ultrananocrystalline diamond (UNCD) films as substrate/scaffold materials for developmental biology. Specially designed quartz dishes have been coated with different types of UNCD films and cells were subsequently seeded on those films. Results showed the cells’ growth on UNCD-coated culture dishes are similar to cell culture dishes with little retardation, indicating that UNCD films have no or little inhibition on cell proliferation and are potentially appealing as substrate/scaffold materials. The mechanisms of cell adhesion on UNCD surfaces are proposed based on the experimental results. The comparisons of cell cultures on diamond-powder-seeded culture dishes and on UNCD-coated dishes with matrix-assisted laser desorption/ionization—time-of-flight mass spectroscopy (MALDI-TOF MS) and X-ray photoelectron spectroscopy (XPS) analyses provided valuable data to support the mechanisms proposed to explain the adhesion and proliferation of cells on the surface of the UNCD platform.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2017

Proof Of Concept of Integrated Load Measurement in 3D Printed Structures

Currently, research on structural health monitoring systems is focused on direct integration of the system into a component or structure. The latter results in a so-called smart structure. One example of a smart structure is a component with integrated strain sensing for continuous load monitoring. Additive manufacturing, or 3D printing, now also enables such integration of functions inside components. As a proof-of-concept, the Fused Deposition Modeling (FDM) technique was used to integrate a strain sensing element inside polymer (ABS) tensile test samples. The strain sensing element consisted of a closed capillary filled with a fluid and connected to an externally mounted pressure sensor. The volumetric deformation of the integrated capillary resulted in pressure changes in the fluid. The obtained pressure measurements during tensile testing are reported in this paper and compared to state-of-the-art extensometer measurements. The sensitivity of the 3D printed pressure-based strain sensor is primarily a function of the compressibility of the capillary fluid. Air- and watertightness are of critical importance for the proper functioning of the 3D printed pressure-based strain sensor. Therefore, the best after-treatment procedure was selected on basis of a comparative analysis. The obtained pressure measurements are linear with respect to the extensometer readings, and the uncertainty on the strain measurement of a capillary filled with water (incompressible fluid) is ±3.1 µstrain, which is approximately three times less sensitive than conventional strain gauges (±1 µstrain), but 32 times more sensitive than the same sensor based on air (compressible fluid) (±101 µstrain).

42 ENGINEERING↗

DOE OSTI2022

PetroFit: A Python Package for Computing Petrosian Radii and Fitting Galaxy Light Profiles

PetroFit is an open-source Python package based on Astropy and Photutils that can calculate Petrosian profiles and fit galaxy images. It offers end-to-end tools for making accurate photometric measurements, estimating morphological properties, and fitting 2D models to galaxy images. Petrosian metric radii can be used for model parameter estimation and aperture photometry to provide accurate total fluxes. Correction tools are provided for improving Petrosian radii estimates affected by galaxy morphology. PetroFit also provides tools for sampling Astropy-based models (including custom profiles and multicomponent models) onto image grids and enables point-spread function convolution to account for the effects of seeing. These capabilities provide a robust means of modeling and fitting galaxy light profiles. We have made the PetroFit package publicly available on GitHub (PetroFit/petrofit) and PyPi (pip install petrofit).

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2026

Conjugation-based genome engineering enables rapid prototyping and bioproduction in non-model bacteria

Abstract Non-model bacteria offer unique metabolic capabilities for sustainable bioproduction, yet their limited genetic accessibility hinders systematic strain development. Here we present conjugation-based serine recombinase-assisted genome engineering (cSAGE), a broad-host-range platform that enables predictable, iterative genomic integration in transformation-resistant bacteria. cSAGE combines conjugative DNA delivery, standardized low-copy vectors, orthogonal recombinases, and modular genetic parts to support rapid pathway assembly and cross-host benchmarking. Using purple nonsulfur bacteria as a testbed, we integrate promoter engineering, multi-payload genome modification, and genome-scale metabolic modeling to empirically evaluate host-dependent pathway performance. Applying this workflow, we identify strain-specific differences in photosynthetic conversion of lignin-derived p -coumarate to the thermoplastic precursor p -vinylphenol. By enabling genome engineering and functional comparison across diverse bacteria using a single plasmid system, cSAGE provides a general framework for non-model strain prototyping and biotransformation discovery.

Guzman, Michael S. [Department of Chemical Enginee↗