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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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The Plastic Parallel Pathways Platform (4P) combines life cycle assessment, agent-based modeling within a dynamic material flow analysis structure to compute the environmental impacts of different recycling options under various behavioral interventions.
A software for a multi-challenge power-flow grid optimization competition was developed. The platform brings together high performance computing clusters, webservers, databases, competition datasets, schedulers, evaluation codes, and a multitude of language compilers and optimization solvers to host the competition. The original video announcing the competition, from former Secretary Perry, at: https://www.youtube.com/watch?v=hZwX3P9vS8M
A suite of software tools used to interface with power electronic equipment for laboratory testing and device certification. They are typically used as equipment drivers with using the System Validation Platform (SVP) graphical user interface (GUI). Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525. SAND2021-1185 O
The platform of optimal experiment management, POEM, powered with automated machine learning to accelerate the discovery of optimal solutions, and automatically guide the design of experiments to be evaluated. POEM currently supports 1) random model explorations for experiment design, 2) sparse grid model explorations with Gaussian Polynomial Chaos surrogate model to accelerate experiment design ,3) time-dependent model sensitivity and uncertainty analysis to identify the importance features for experiment design, 4) model calibrations via Bayesian inference to integrate experiments to improve model performance, and 5) Bayesian optimization for optimal experimental design. In addition, POEM aims to simplify the process of experimental design for users, enabling them to analyze the data with minimal human intervention, and improving the technological output from research activities.
National Laboratory of the Rockies' Open Platform for Agile Trip Heuristics (NLR OpenPATH™) enables people to track their travel modes—by car, bus, bike, walking, etc.—and measure their associated energy use. Formerly known as e-mission, the NLR OpenPATH tool features continuous data collection and analysis via a smart phone app backed by a server and automated data processing. Its open nature enables transparent data collection and analysis while allowing for continuous improvement coupled with accessibility and adaptability by others. NLR OpenPATH empowers communities to collect and understand their own travel data while achieving place-based, locally relevant mobility goals.
SF-26-021 Adapt is a data processing platform for real-time data analysis, short term prediction of targets convective cells and tracking for archived data. It provides tools for downloading, processing, segmenting, projecting, analyzing, and visualizing storm cell data from weather radar. The pipeline includes cell detection, motion estimation using optical flow, cell property extraction, and persistence to NetCDF and SQLite/Parquet for guiding adaptive scanning.
ENPAX (ENergy Platform — Automated eXpenditures) is an open-source Python library that provides modular, bottom-up capital and operating expenditure (CAPEX/OPEX) models for energy technologies. Cost estimates are derived using system design characteristics, site specific details, power system considerations and infrastructure assumptions.
In this study, cell signaling is a dynamic and complex process. A typical signaling pathway may begin with activation of cell surface receptors, leading to activation kinase cascade that culminates in induction of mRNA and non-coding miRNA production in the nucleus, followed by modulation of mRNA expression by miRNAs in the cytosol, and end with production of proteins in response to the signaling pathway. Signaling pathways involve proteins, miRNA, and mRNAs, along with various forms of transient post-translational modifications, and detecting each type of signaling molecule requires categorically different sample preparation methods such as Western blotting for proteins, PCR for nucleic acids, and flow cytometry for post-translational modifications. Since we know that cells in populations behave heterogeneously1, especially in the cases of stem cells, cancer, and hematopoiesis, there is need for a new technology that provides capability to detect and quantify multiple categories of signaling molecules in intact single cells to provide a comprehensive view of the cell’s physiological state. In this technical brief, we describe our microfluidic platform with a portfolio of customized molecular assays that can detect nucleic acids, proteins, and post-translational modifications in single intact cells with >95% reduction in reagent requirement in under 8 hours.
There is a need to replace petroleum-derived with sustainable feedstocks for chemical production. Certain biomass feedstocks can meet this need as abundant, diverse, and renewable resources. Specific ionic liquids (ILs) can play a role in this process as promising candidates for chemical pretreatment and deconstruction of plant-based biomass feedstocks as they efficiently release carbohydrates which can be fermented. However, the most efficient pretreatment ILs are highly toxic to biological systems, such as microbial fermentations, and hinder subsequent bioprocessing of fermentative sugars obtained from IL-treated biomass. To generate strains capable of tolerating residual ILs present in treated feedstocks, a tolerance adaptive laboratory evolution (TALE) approach was developed and utilized to improve growth of two different Escherichia coli strains, DH1 and K-12 MG1655, in the presence of two different ionic liquids, 1-ethyl-3-methylimidazolium acetate ([C 2 C 1 Im][OAc] ) and 1-butyl-3-methylimidazolium chloride ([C 4 C 1 Im]Cl). For multiple parallel replicate populations of E. coli , cells were repeatedly passed to select for improved fitness over the course of approximately 40 days. Clonal isolates were screened and the best performing isolates were subjected to whole genome sequencing. The most prevalent mutations in tolerant clones occurred in transport processes related to the functions of mdtJI , a multidrug efflux pump, and yhdP , an uncharacterized transporter. Additional mutations were enriched in processes such as transcriptional regulation and nucleotide biosynthesis. Finally, the best-performing strains were compared to previously characterized tolerant strains and showed superior performance in tolerance of different IL and media combinations (i.e., cross tolerance) with robust growth at 8.5% (w/v) and detectable growth up to 11.9% (w/v) [C 2 C 1 Im][OAc]. The generated strains thus represent the best performing platform strains available for bioproduction utilizing IL-treated renewable substrates, and the TALE method was highly successful in overcoming the general issue of substrate toxicity and has great promise for use in tolerance engineering.
Abstract Many spectral responses in materials science, physics, and chemistry experiments can be characterized as resulting from the superposition of a number of more basic individual spectra. In this context, unmixing is defined as the problem of determining the individual spectra, given measurements of multiple spectra that are spatially resolved across samples, as well as the determination of the corresponding abundance maps indicating the local weighting of each individual spectrum. Matrix factorization is a popular linear unmixing technique that considers that the mixture model between the individual spectra and the spatial maps is linear. Here, we present a tutorial paper targeted at domain scientists to introduce linear unmixing techniques, to facilitate greater understanding of spectroscopic imaging data. We detail a matrix factorization framework that can incorporate different domain information through various parameters of the matrix factorization method. We demonstrate many domain-specific examples to explain the expressivity of the matrix factorization framework and show how the appropriate use of domain-specific constraints such as non-negativity and sum-to-one abundance result in physically meaningful spectral decompositions that are more readily interpretable. Our aim is not only to explain the off-the-shelf available tools, but to add additional constraints when ready-made algorithms are unavailable for the task. All examples use the scalable open source implementation from https://github.com/ramkikannan/nmflibrary that can run from small laptops to supercomputers, creating a user-wide platform for rapid dissemination and adoption across scientific disciplines.
5-hydroxymethyl furfural (HMF) and furfurals are DOE-listed platform chemicals that can be derived from the renewable carbon in the lignocellulosic biomasses and have the potential to replace petroleum-derived alternatives. High substrate cost and use of expensive solvents limit the economic feasibility of bio-based HMF production on an industrially relevant scale. The study presents an experimental optimized condition that maximizes the chemical-free production of HMF and furfurals without lowering the yield of total fermentable sugars from Saccharum bagasse. Hydrothermal pretreatment at 210 °C for 15 min yielded approximately 10%, 12%, and 46% of HMF, furfurals, and fermentable sugars per gram of dry biomass, respectively. Additionally, the study proposes a consolidated bioprocess model to produce and recover four high-value bioproducts i.e., HMF, furfurals, ethanol, and acetic acid based on the experimental results and evaluates its technoeconomic feasibility considering HMF as the main product. The minimum selling price (MSP) of HMF was estimated to be 930.6 USD/t which is competitive with its petroleum-derived precursor alternative p-xylene (1,113 USD/t). The sensitivity analysis performed for the process parameters suggests that pretreatment cost and revenues from coproducts immensely influence the MSP of HMF. The preliminary technoeconomic analysis performed on the consolidated bioprocess design indicates that additional revenue streams from diversified coproducts in biorefineries aid in lowering the MSP of high-value bioproducts.
We present a flexible, scalable, and low-noise design scheme for coupling free-space light into a silicon-on-insulator (SOI) electronic-photonic integrated circuit. The proposed scheme utilizes arrays of grating couplers with compact, inverse-designed power combining networks to couple a distributed optical collection area to a single output waveguide, forming a photonic antenna. Fabrication density compliance is maintained regardless of the antenna size, and the collection area can be scaled while maintaining a fixed noise floor. Using experimental grating array antennas fabricated in the GF45CLO platform, we demonstrate up to a 6.7× increase in the signal-to-noise ratio (SNR) of a lens-less monolithic free-space photonic receiver using a 4×4 grating array.
Next-generation sequencing (NGS) is emerging as a powerful tool for elucidating genetic information for a wide range of applications. Unfortunately, the surging popularity of NGS has not yet been accompanied by an improvement in automated techniques for preparing formatted sequencing libraries. To address this challenge, we have developed a prototype microfluidic system for preparing sequencer-ready DNA libraries for analysis by Illumina sequencing. Our system combines droplet-based digital microfluidic (DMF) sample handling with peripheral modules to create a fully-integrated, sample-in library-out platform. In this report, we use our automated system to prepare NGS libraries from samples of human and bacterial genomic DNA. E. coli libraries prepared on-device from 5 ng of total DNA yielded excellent sequence coverage over the entire bacterial genome, with .99% alignment to the reference genome, even genome coverage, and good quality scores. Furthermore, we produced a de novo assembly on a previously unsequenced multi-drug resistant Klebsiella pneumoniae strain BAA-2146 (KpnNDM). The new method described here is fast, robust, scalable, and automated. Our device for library preparation will assist in the integration of NGS technology into a wide variety of laboratories, including small research laboratories and clinical laboratories.
The immunoglobulin Fc region is a homodimer consisted of two sets of CH2 and CH3 domains and has been exploited to generate two-arm protein fusions with high expression yields, simplified purification processes and extended serum half-life. However, attempts to generate one-arm fusion proteins with monomeric Fc, with one set of CH2 and CH3 domains, are often plagued with challenges such as weakened binding to FcRn or partial monomer formation. Here, we demonstrate the generation of a stable IgG4 Fc monomer with a unique combination of mutations at the CH3-CH3 interface using rational design combined with in vitro evolution methodologies. In addition to size-exclusion chromatography and analytical ultracentrifugation, we used multi-angle light scattering (MALS) to show that the engineered Fc monomer exhibits excellent monodispersity. Furthermore, crystal structure analysis (PDB ID: 5HVW) reveals monomeric properties supported by disrupted interactions at the CH3-CH3 interface. Monomeric Fc fusions with Fab or scFv achieved FcRn binding and serum half-life comparable to wildtype IgG. These results demonstrate that this monomeric IgG4 Fc is a promising therapeutic platform to extend the serum half-life of proteins in a monovalent format.
Unmanned aerial vehicles (UAVs ) equipped with imaging sensors and integrated global navigation satellite system/inertial navigation system (GNSS/INS ) units are used for numerous applications. Deriving reliable 3D coordinates from such UAVs is contingent on accurate geometric calibration, which encompasses the estimation of mounting parameters and synchronization errors. Through a rigorous impact analysis of such systematic errors, this article proposes a direct approach for spatial and temporal calibration (estimating system parameters through a bundle adjustment procedure) of a GNSS/INS -assisted pushbroom scanner onboard a UAV platform. The calibration results show that the horizontal and vertical accuracies are within the ground sampling distance of the sensor. Unlike for frame camera systems, this article also shows that the indirect approach is not a feasible solution for pushbroom scanners due to their limited ability for decoupling system parameters. This finding provides further support that the direct approach is recommended for spatial and temporal calibration of UAV pushbroom scanner systems.
Maps of aspen ploidy (diploid or triploid) developed using National Ecological Observatory Network (NEON) Airborne Observation Platform visible to shortwave infrared imaging spectroscopy data that were acquired over the Upper East River, Colorado in 2018. Maps of aspen distribution, as well as other land cover types that were used to screen for aspen dominated pixels are also provided. Each image file is provided as a GeoTiff with internal tiling and LZW compression. For use of ploidy maps, it is necessary to mask out non-aspen and shaded pixels. Shaded pixels are provided in an associated data package. For full details, please see associated publication and methods description. This dataset is associated with the publication in Ecological Applications.
The purpose of this dataset is to support research aimed at understanding the coupling between hydrologic and biogeochemical processes at watershed scale, particularly the relationship between aboveground vegetation characteristics and subsurface soil properties. These data are intended to inform and calibrate models of catchment-scale biogeochemical fluxes, including rock-derived nutrient cycling, and they were procured to address the following questions: (1) What is the distribution of vegetation characteristics across the study catchments? (2) Are foliar concentrations of rock-derived nutrients related to underlying lithology and soil availability, or are these signals masked by biotic nutrient cycling and retention processes?This data package contains foliar elemental data collected during the 2018 National Ecological Observatory Networks (NEON) Airborne Observation Platform (AOP) imaging spectroscopy and lidar surveys in Gunnison County, Colorado. Folair samples were collected across the East River, Washington Gulch, Slate River, and Coal Creek watersheds and contain a mixture of vegetation including meadow, shrub, and tree foliar samples. The samples were processed using aqua regia digestion and analyzed for elemental determination on inductively coupled plasma optical emission spectrometry (ICP-OES).The data package includes: (1) raw foliar elemental data files in CSV and PDF formats, (2) quality control certificates in PDF format, and (3) an aggregated CSV file containing all elemental measurements compiled across samples. No specialized software is required to access or use these files.
Background: Extracellular vesicles released by prostate cancer present in seminal fluid, urine, and blood may represent a non-invasive means to identify and prioritize patients with intermediate risk and high risk of prostate cancer. We hypothesize that enumeration of circulating prostate microparticles (PMPs), a type of extracellular vesicle (EV), can identify patients with Gleason Score≥4+4 prostate cancer (PCa) in a manner independent of PSA. Patients and Methods: Plasmas from healthy volunteers, benign prostatic hyperplasia patients, and PCa patients with various Gleason score patterns were analyzed for PMPs. We used nanoscale flow cytometry to enumerate PMPs which were defined as submicron events (100-1000nm) immunoreactive to anti-PSMA mAb when compared to isotype control labeled samples. Levels of PMPs (counts/µL of plasma) were also compared to CellSearch CTC Subclasses in various PCa metastatic disease subtypes (treatment naïve, castration resistant prostate cancer) and in serially collected plasma sets from patients undergoing radical prostatectomy. Results: PMP levels in plasma as enumerated by nanoscale flow cytometry are effective in distinguishing PCa patients with Gleason Score≥8 disease, a highrisk prognostic factor, from patients with Gleason Score≤7 PCa, which carries an intermediate risk of PCa recurrence. PMP levels were independent of PSA and significantly decreased after surgical resection of the prostate, demonstrating its prognostic potential for clinical follow-up. CTC subclasses did not decrease after prostatectomy and were not effective in distinguishing localized PCa patients from metastatic PCa patients. Conclusions: PMP enumeration was able to identify patients with Gleason Score ≥8 PCa but not patients with Gleason Score 4+3 PCa, but offers greater confidence than CTC counts in identifying patients with metastatic prostate cancer. CTC Subclass analysis was also not effective for post-prostatectomy follow up and for distinguishing metastatic PCa and localized PCa patients. Nanoscale flow cytometry of PMPs presents an emerging biomarker platform for various stages of prostate cancer.