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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 1,189 records · Page 66
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Status of the data acquisition, trigger, and slow control systems of the Mu2e experiment at Fermilab

The Mu2e experiment at the Fermilab will search for a coherent neutrinoless conversion of a muon into an electron in the field of an aluminum nucleus with a sensitivity improvement by a factor of 10,000 over existing limits. In this work, the Mu2e Trigger and Data Acquisition System (TDAQ) uses otsdaq framework as the online Data Acquisition System (DAQ) solution. Developed at Fermilab, otsdaq integrates several framework components — an artdaq-based DAQ, an art-based event processing, and an EPICS-based detector control system (DCS), and provides a uniform multi-user interface to its components through a web browser. Data streams from the Mu2e tracker and calorimeter are handled by the artdaq-based DAQ and processed by a one-level software trigger implemented within the art framework. Events accepted by the trigger have their data combined, post-trigger, with the separately read out data from the Mu2e Cosmic Ray Veto system. Foundation of the Mu2e DCS, EPICS – an Experimental Physics and Industrial Control System – is an open-source platform for monitoring, controlling, alarming, and archiving. A prototype of the TDAQ and the DCS systems has been built and tested over the last three years at Fermilab’s Feynman Computing Center, and now the production system installation is underway. This work presents their status and focus on the installation plans and procedures for racks, workstations, network switches, gateway computers, DAQ hardware, slow controls implementation, and testing.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2024

A Review of the Lawrence Livermore Nuclear Accident Dosimeter 1980s-present

A Nuclear Accident Dosimetry program is a federal requirement for all facilities that have the potential to have a criticality accident. Personnel Nuclear Accident Dosimeter (PNAD) theory and analytical procedures are driven by various scientific needs and interacting regulations. A brief history of the status of USA Department of Energy (DOE) nuclear accident dosimetry regulations, recommendations, and performance testing criteria are given. Then, the history of the Lawrence Livermore National Laboratory (LLNL) PNAD is explored, including changes in the physical dosimeter and adjustments of the analysis method through the last four decades. Finally, the performance of LLNL’s PNAD at criticality accident intercomparison training exercises since 2009 is explored. In general, reported neutron doses have been within or close to DOE-STD-1098 performance criteria while reported gamma doses have been outside of DOE-STD-1098 performance criteria. Reported total absorbed doses have varied in meeting ANSI/HPS N13.3 and ANSI/HPS N13.3 (R2019) performance criteria. Dosimetry staff retirement and turnover have left historical knowledge gaps, yet provided opportunities within the NAD program at LLNL. This review paper serves as an overview of the history and status of the NAD program. Brief technical, procedural and programmatic recommendations to improve LLNL’s NAD program are given. Technical recommendations include investigating orientation factors through modeling or empirical experimentation, investigating gamma dosimetry methods for high-dose scenarios, and exploring other dosimetric methods for simpler, quicker NAD analysis. Procedural recommendations include better documentation of conversion factor (activity-to-fluence and fluence-to-dose) derivations and spectrum uses, and updated analysis spreadsheets or simple Graphic User Interfaces for dose calculations. In conclusion, programmatic recommendations include formalized training for NAD analysts, and having multiple SMEs trained on the NAD program.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2023

CDB-AP: An application for coincidence Doppler broadening spectroscopy analysis

Coincidence Doppler Broadening (CDB) Positron Annihilation Spectroscopy (PAS) is a material analysis technique that can be used to non-destructively measure characteristics of structural defects in samples. Analyzing and comparing large datasets obtained using this technique, however, can be complicated and time intensive. The Coincidence Doppler Broadening Analysis Program (CDB-AP) is a graphical user interface that facilitates rapid analysis of many data files while using transparent processes. It is already used in three laboratories at Idaho National Laboratory and can be used in laboratories worldwide.

36 MATERIALS SCIENCE↗
DOE OSTI2025

4.0 MOOSE: Enabling massively parallel Multiphysics simulation

Approaching 18 years of existence, MOOSE—the Multiphysics Object-Oriented Simulation Environment—is being developed at a higher pace than ever before. With significant support from four research institutions across the globe, and dozens of new contributors, the capabilities of the framework are being expanded to meet modeling challenges in a wide variety of fields from nuclear system design, to geomechanics, to material science. This includes new development in equation discretization techniques, solver methods, meshing capabilities, application deployment, and user interface improvements. Applications built on MOOSE benefit from all these improvements.

22 - GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2021

UEMtomaton: A Source-Available Platform to Aid in Start-up of Ultrafast Electron Microscopy Labs

The steady rise in the number of ultrafast electron microscopy (UEM) labs, in addition to the opacity and lack of detailed descriptions of current approaches that would enable point-by-point construction, has created an opportunity for sharing common methods and instrumentation for (for example) automating data acquisition to assist in efficient lab start-up and to learn about common and robust protocols. In the spirit of open sharing of methods, we provide here a description of an entry-level method and user interface (UI) for automating UEM experiments, and we provide access to the source code and scripts (source-available) for ease of implementation or as a starting reference point for those entering or seeking to enter the field (https://github.com/CEMSFlannigan/UEMtomaton/releases/tag/v1.0). Core instrumentation and physical connections in the UEM lab at Minnesota are described. Interface communication schemes consisting of duo server-client pairs between critical components – the optical delay stage and the UEM digital camera – are presented, with emphasis placed on describing the logic and communications sequence designed to conduct automated series acquisitions. An application designed and programmed with C++/CLI as Windows Forms in Microsoft Visual Studio – dubbed UEMtomaton – is also presented. Key to the UI layout is centralization of the automation tasks and establishment of communication within the software rather than by interfacing with each individual workstation. It is our hope that this note provides useful insight for current and future UEM researchers, particularly with respect to generalizability and portability of the approach to emerging labs. Here, we note that while this basic, entry-level approach is certainly not the most sophisticated or comprehensive of those currently in use, we feel there is nevertheless value in clearly communicating a proven straightforward method to hopefully lower the barrier to entry into the field.

47 OTHER INSTRUMENTATION↗
DOE OSTI2020

Process design tools and techno-economic analysis for capacitive deionization

Capacitive deionization (CDI) devices use cyclical electrosorption on porous electrode surfaces to achieve water desalination. Process modeling and design of CDI systems requires accurate treatment of the coupling among input electrical forcing, input flow rates, and system responses including salt removal dynamics, water recovery, energy storage, and dissipation. Techno-economic analyses of CDI further require a method to calculate and compare between a produced commodity (e.g. desalted water) versus capital and operational costs of the system. In this work, we demonstrate a new modeling and analysis tool for CDI developed as an installable Matlab program that allows direct numerical simulation of CDI dynamics and calculation of key performance and cost parameters. The program is provided for free and is used to run open-source Simulink models. The Simulink environment sends information to the program and allows for a drag and drop design space where users can connect CDI cells to relevant periphery blocks such as grid energy, battery, solar panel, waste disposal, and maintenance/labor cost streams. The program allows for simulation of arbitrary current forcing and arbitrary flow rate forcing of one or more CDI cells. We employ validated well-mixed reactor formulations together with a non-linear circuit model formulation that can accommodate a variety of electric double layer sub-models (e.g. for charge efficiency). The program includes a graphical user interface (GUI) to specify CDI plant parameters, specify operating conditions, run individual tests or parameter batch-mode simulations, and plot relevant results. The techno-economic models convert among dimensional streams of species (e.g. feed, desalted water, and brine), energy, and cost and enable a variety of economic estimates including levelized water costs.

42 ENGINEERING↗
DOE OSTI2018

Internal wave energy flux from density perturbations in nonlinear stratifications

Internal gravity wave energy contributes significantly to the energy budget of the oceans, affecting mixing and the thermohaline circulation. Hence it is important to determine the internal wave energy flux $\boldsymbol{J}=p\,\boldsymbol{v}$ , where $p$ is the pressure perturbation field and $\boldsymbol{v}$ is the velocity perturbation field. However, the pressure perturbation field is not directly accessible in laboratory or field observations. Previously, a Green’s function based method was developed to calculate the instantaneous energy flux field from a measured density perturbation field $\unicode[STIX]{x1D70C}(x,z,t)$ , given a constant buoyancy frequency $N$ . Here we present methods for computing the instantaneous energy flux $\boldsymbol{J}(x,z,t)$ for an internal wave field with vertically varying background $N(z)$ , as in the oceans where $N(z)$ typically decreases by two orders of magnitude from the pycnocline to the deep ocean. Analytic methods are presented for computing $\boldsymbol{J}(x,z,t)$ from a density perturbation field for $N(z)$ varying linearly with $z$ and for $N^{2}(z)$ varying as $\tanh (z)$ . To generalize this approach to arbitrary $N(z)$ , we present a computational method for obtaining $\boldsymbol{J}(x,z,t)$ . The results for $\boldsymbol{J}(x,z,t)$ for the different cases agree well with results from direct numerical simulations of the Navier–Stokes equations. Our computational method can be applied to any density perturbation data using the MATLAB graphical user interface ‘EnergyFlux’.

Mechanics↗
DOE OSTI2025

Open Specy 1.0: Automated (Hyper)spectroscopy for Microplastics

Microplastic spectral analysis is one of the most time-consuming processes in studying microplastic pollution, often requiring days per sample. Researchers are transitioning to automated batch and hyperspectral image analysis techniques to enhance efficiency. Open Specy, initially aimed at manual single-spectrum analysis, has now integrated automated methods. This updated version, Open Specy 1.0, introduces several new features, including two algorithms for automated processing (smoothing and particle compression), an extensive library containing over 40,000 open-source Raman and FTIR spectra, and two machine learning classifiers (logistic regression and k medoids) developed from this library. Furthermore, it includes a revamped user interface, an R package, and a benchmark data set for testing future advancements in automated techniques. Researchers evaluated various configurations for hyperspectral smoothing, particle identification, compression, and splitting, to achieve combined recovery rates between 50 and 150% particle counts, identities, and sizes with a coefficient of variation (CV) of less than 40% (the accredited standard). Mean absorbance times the standard deviation provided a consistent particle identification. Hyperspectral smoothing led to a 96% combined recovery rate and reduced variability (CV = 38%) compared to the 86% recovery (CV = 83%) of nonsmoothed controls. Additionally, compressing spectra for particles was significantly faster (>3x) and showed similar accuracy but with reduced variability than processing each pixel individually. Key challenges persist in automating spectral analysis, particularly in refining particle splitting algorithms, and improving identification routines to minimize false positives and negatives. In conclusion, new methods in sample preparation for better stabilization and dispersion of particles could overcome some of these issues.

13 HYDRO ENERGY↗
DOE OSTI2024

Integration of pH Control into Chi.Bio Reactors and Demonstration with Small-Scale Enzymatic Poly(ethylene terephthalate) Hydrolysis

Small-scale bioreactors that are affordable and accessible would be of major benefit to the research community. In previous work, an open-source, automated bioreactor system was designed to operate up to the 30 mL scale with online optical monitoring, stirring, and temperature control, and this system, dubbed Chi.Bio, is now commercially available at a cost that is typically 1–2 orders of magnitude less than commercial bioreactors. In this work, we further expand the capabilities of the Chi.Bio system by enabling continuous pH monitoring and control through hardware and software modifications. For hardware modifications, we sourced low-cost, commercial pH circuits and made straightforward modifications to the Chi.Bio head plate to enable continuous pH monitoring. For software integration, we introduced closed-loop feedback control of the pH measured inside the Chi.Bio reactors and integrated a pH-control module into the existing Chi.Bio user interface. We demonstrated the utility of pH control through the small-scale depolymerization of the synthetic polyester, poly(ethylene terephthalate) (PET), using a benchmark cutinase enzyme, and compared this to 250 mL bioreactor hydrolysis reactions. The results in terms of PET conversion and rate, measured both by base addition and product release profiles, are statistically equivalent, with the Chi.Bio system allowing for a 20-fold reduction of purified enzyme required relative to the 250 mL bioreactor setup. Through inexpensive modifications, the ability to conduct pH control in Chi.Bio reactors widens the potential slate of biochemical reactions and biological cultivations for study in this system, and may also be adapted for use in other bioreactor platforms.

09 BIOMASS FUELS↗
DOE OSTI2025

CHARMM-GUI Bicelle Builder : An Extension of Membrane Builder for Modeling and Simulation of Bicelle Systems

Membrane mimetics, such as detergent micelles, nanodiscs, and amphipol complexes, which can provide membrane-like environments while retaining small and soluble features, have been utilized to study membrane proteins. A bicelle, composed of varying lipids and detergents, is a useful membrane mimetic because the lipid-to-detergent ratio, the q-value, can be adjusted to alter the properties of the aggregate, including the thickness and size of the bicelle. However, building a bicelle model for modeling and simulation studies requires nontrivial efforts, even for experts. We introduce CHARMM-GUI Bicelle Builder, a web-based platform that can generate various all-atom bicelle systems via a graphical user interface with all available lipids and detergents in Membrane Builder. To illustrate and validate Bicelle Builder with practical systems, we have modeled and simulated pure bicelles consisting of 1,2-dimyristoyl-sn-glycero-3-phosphocholine (DMPC) lipids with 1,2-dihexanoyl-sn-glycero-3-phosphocholine (C6DHPC) detergents and protein–bicelle complexes, composed of DMPC with C6DHPC, foscholine-10 (FOS10), and lysophosphatidylcholine-12 (LPC12) detergents. Our simulation results indicate that Bicelle Builder can generate reliable and robust bicelle models with and without proteins that retain DMPC bilayer characteristics. Bicelle Builder is expected to help researchers better understand not only bicelles themselves but also atomistic-level structures of protein–bicelle complexes that are often difficult to access through experimental approaches.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Nanopolysaccharide Builder: A User-Friendly Tool for Atomistic Models of Polysaccharide-Based Nanostructures

Here, we introduce Nanopolysaccharide Builder (NPB), a user-friendly software tool designed to construct polysaccharide nanostructures─mainly those based on cellulose, chitin, and chitosan─using experimental data or user-defined parameters. NPB enables the generation of cellulose and chitin allomorphs with customizable biochemical topologies and also facilitates the construction of large bundles that replicate nanostructures found in biological support systems, including plant cell walls and arthropod cuticles. The software outputs atomic Cartesian coordinates in Protein Data Bank (PDB) format and also provides atom connectivity files in PSF and PARM formats, ensuring seamless integration with major molecular dynamics (MD) engines such as NAMD, CHARMM, GROMACS, AMBER, OpenMM, and LAMMPS. Built on an interactive visualization framework, NPB features a graphical user interface (GUI) and supports both macOS and Linux operating systems. By enabling detailed atomic-scale studies of polysaccharide evolution in extracellular matrices and cell walls of algae, bacteria, fungi, and plants, NPB is poised to advance AI-guided research in sustainable chemical development and biomass utilization.

Wan, Zhangmin [Univ. of British Columbia, Vancouve↗
DOE OSTI2021

PSpecteR: A User-Friendly and Interactive Application for Visualizing Top-Down and Bottom-Up Proteomics Data in R

Visual examination of mass spectrometry data is necessary to assess data quality and to facilitate data exploration. Graphics provide the means to evaluate spectral properties, test alternative peptide/protein sequence matches, prepare annotated spectra for publication, and fine-tune parameters during wet lab procedures. Visual inspection of MS data is hindered by proprietary proteomics visualization software designed for particular workflows and academic software that lack visualization tools. We built PSpecteR, an open-source and interactive R Shiny web application to address these issues, with support for several steps of proteomics data processing, including: reading various mass spectrometry files, running open-source database search tools, labelling spectra with fragmentation patterns, testing post-translational modifications, plotting where identified fragments map to reference sequences, and visualizing algorithmic output and metadata. All figures, tables, and spectra are exportable within one easy-to-use graphical user interface. Our current software provides a flexible and modern R framework to support fast implementation of additional features. The open source code is readily available (https://github.com/EMSL-Computing/PSpecteR), and a PSpecteR Docker container (https://hub.docker.com/r/emslcomputing) is available for easy local installation.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗
DOE OSTI2025

Automated Strain Construction for Biosynthetic Pathway Screening in Yeast

Automation accelerates the Design-Build-Test-Learn (DBTL) cycle for synthetic biology; however, most strain construction pipelines lack robotic integration. Here, in this study, we present the workflow design and source code for a modular, integrated protocol that automates the Build step in Saccharomyces cerevisiae. We programmed the Hamilton Microlab VANTAGE to integrate off-deck hardware via its central robotic arm, enabling automated steps that increased throughput to 2,000 transformations per week. We developed a user interface with the Hamilton VENUS software to support on-demand parameter customization. As a proof of concept, we screened a gene library in an engineered yeast strain producing verazine, a key intermediate in the biosynthesis of steroidal alkaloids. Our pipeline rapidly identified pathway bottlenecks and genes that enhanced verazine production by 2.0- to 5-fold. This technical note provides resources for synthetic biologists designing yeast workflows for biofoundries to screen libraries for pathway discovery/optimization, combinatorial biosynthesis, and protein engineering.

automation↗
DOE OSTI2022

Neutral Loss Mass Spectral Data Enhances Molecular Similarity Analysis in $\mathrm{METLIN}$

We report Neutral loss (NL) spectral data presents a mirror of MS 2 data and is a valuable yet largely untapped resource for molecular discovery and similarity analysis. Tandem mass spectrometry (MS 2 ) data is effective for the identification of known molecules and the putative identification of novel, previously uncharacterized molecules (unknowns). Yet, MS 2 data alone is limited in characterizing structurally related molecules. To facilitate unknown identification and complement the METLIN-MS 2 fragment ion database for characterizing structurally related molecules, we have created a MS 2 to NL converter as a part of the METLIN platform. The converter has been used to transform METLIN’s MS 2 data into a neutral loss database (METLIN-NL) on over 860 000 individual molecular standards. The platform includes both the MS 2 to NL converter and a graphical user interface enabling comparative analyses between MS 2 and NL data. Examples of NL spectral data are shown with oxylipin analogues and two structurally related statin molecules to demonstrate NL spectra and their ability to help characterize structural similarity. Mirroring MS 2 data to generate NL spectral data offers a unique dimension for chemical and metabolite structure characterization.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Real-time 3D analysis during electron tomography using tomviz

The demand for high-throughput electron tomography is rapidly increasing in biological and material sciences. However, this 3D imaging technique is computationally bottlenecked by alignment and reconstruction which runs from hours to days. We demonstrate real-time tomography with dynamic 3D tomographic visualization to enable rapid interpretation of specimen structure immediately as data is collected on an electron microscope. Using geometrically complex chiral nanoparticles, we show volumetric interpretation can begin in less than 10 minutes and a high-quality tomogram is available within 30 minutes. Real-time tomography is integrated into tomviz, an open-source and cross-platform 3D data analysis tool that contains intuitive graphical user interfaces (GUI), to enable any scientist to characterize biological and material structure in 3D.

36 MATERIALS SCIENCE↗
DOE OSTI2020

A database of battery materials auto-generated using ChemDataExtractor

A database of battery materials is presented which comprises a total of 292,313 data records, with 214,617 unique chemical-property data relations between 17,354 unique chemicals and up to five material properties: capacity, voltage, conductivity, Coulombic efficiency and energy. 117,403 data are multivariate on a property where it is the dependent variable in part of a data series. The database was auto-generated by mining text from 229,061 academic papers using the chemistry-aware natural language processing toolkit, ChemDataExtractor version 1.5, which was modified for the specific domain of batteries. The collected data can be used as a representative overview of battery material information that is contained within text of scientific papers. Public availability of these data will also enable battery materials design and prediction via data-science methods. To the best of our knowledge, this is the first auto-generated database of battery materials extracted from a relatively large number of scientific papers. We also provide a Graphical User Interface (GUI) to aid the use of this database.

25 ENERGY STORAGE↗
DOE OSTI2017

GENFIRE: A generalized Fourier iterative reconstruction algorithm for high-resolution 3D imaging

Tomography has made a radical impact on diverse fields ranging from the study of 3D atomic arrangements in matter to the study of human health in medicine. Despite its very diverse applications, the core of tomography remains the same, that is, a mathematical method must be implemented to reconstruct the 3D structure of an object from a number of 2D projections. Here, we present the mathematical implementation of a tomographic algorithm, termed GENeralized Fourier Iterative REconstruction (GENFIRE), for high-resolution 3D reconstruction from a limited number of 2D projections. GENFIRE first assembles a 3D Fourier grid with oversampling and then iterates between real and reciprocal space to search for a global solution that is concurrently consistent with the measured data and general physical constraints. The algorithm requires minimal human intervention and also incorporates angular refinement to reduce the tilt angle error. We demonstrate that GENFIRE can produce superior results relative to several other popular tomographic reconstruction techniques through numerical simulations and by experimentally reconstructing the 3D structure of a porous material and a frozen-hydrated marine cyanobacterium. As a result, equipped with a graphical user interface, GENFIRE is freely available from our website and is expected to find broad applications across different disciplines.

36 MATERIALS SCIENCE↗