Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “ML T&E”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 271 records · Page 15
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Rapid characterization of MSW and RDF feedstocks for waste-to-energy process using LIBS and ML techniques

The heterogeneity in the composition of municipal solid wastes (MSW) poses significant challenges in the production of biofuel and bioproducts. This research aims to enhance the accuracy and efficiency of waste analysis and characterization by introducing a fast characterization approach for MSW-derived refuse-derived fuels (RDF) by combining Laser-Induced Breakdown Spectroscopy (LIBS) with advanced machine learning (ML) techniques. The approach combines data pre-processing of LIBS spectra of RDF, and the development of ML models trained on domain and theory-based spectral features for predicting process parameters. These models are adept at predicting key process parameters like High Heating Value (HHV), carbon content, and volatile matter. This approach can achieve an average RRMSE of 2.13% and R 2 of 0.98 or higher for all considered parameters on testing data. This work demonstrates significant potential for improving waste sorting, processing efficiency, and environmental compliance over traditional labor- and time-intensive laboratory waste analysis and characterization.

09 BIOMASS FUELS↗
DOE OSTI2026

Amazonian fog harbors viable microbes

Fog formation over tropical forests remains poorly characterized, despite its potential role in bioaerosol dispersion and ecosystem processes. Here, we analyzed fog samples collected at the Amazon Tall Tower Observatory using flow cytometry and culture-based techniques to characterize viable microbial communities. Microbial cell concentrations varied over an order of magnitude across 13 fog events, reaching up to 8 × 104 cells per ml of fog water. Flow cytometry consistently detected metabolically active cells, while culturing and mass spectrometry-based identification yielded eight viable bacterial species and seven fungal taxa. The bacteria Serratia marcescens, Ralstonia pickettii and Sphingomonas paucimobilis exhibited seasonal variations in prevalence. The fungal species identified were primarily mesophilic saprophytes and endophytes, commonly associated with soil and plant surfaces. Our findings indicate that fog harbors viable microbes, including Serratia marcescens and Ralstonia pickettii, which may imply a relevance of fog for microbial dispersal, colonization and nutrient cycling in the Amazon rainforest.

Godoi, Ricardo H. (ORCID:0000000247744870)↗
DOE OSTI2023

Agilent AgileBioFoundry CRADA (Final Report)

The mission of this CRADA with Agilent was to couple powerful MS platforms (QQQ, IM-QTOF-MS) with Agilent’s novel Ultra-High-Performance Liquid Chromatography (UHPLC) fast metabolomic workflows and perform ABF Machine Learning (ML) to generated datasets. Agilent transferred UHPLC methods to PNNL and LBNL and methods were implemented and demonstrated in both labs, achieving total acquisition times of < 10 min. Metabolites analyzed using Agilent’s shared methods included metabolites from central carbon metabolism, common across hosts, and metabolites unique to engineered strains. Standards were acquired in an UHPLC-Drift Tube Ion Mobility Mass Spectrometer (DTIMS) system for the first time within the context of ABF and methods were optimized based on Agilent’s protocols. Samples from ABF hosts Pseudomonas putida, Aspergillus pseudoterreus, Aspergillus niger and Rhodosporidium toruloides were analyzed using the UHPLC-DTIMS platform for a total of 276 runs. A data analysis workflow compatible with the Experimental Data Depot (EDD) and completely shareable was developed for the acquired UHPLC-DTIMS data. Samples were analyzed using a Data Independent Acquisition Approach (DIA), which for most of the standards provided more transitions therefore increasing detection confidence. Using the data acquired by PNNL, LBNL, and Agilent’s specifications from previous ML projects, SNL applied an ensemble ML strategy to pick the best performing model for automated LC-method selection. Finally, with the contribution of the participant labs and Agilent, SNL developed an Automated Method Selection (AMS) software tool to predict the best liquid chromatography method for analysis of any new molecules of interest. Samples with novel pathways and new metabolite targets of interest are generated at a high pace in the ABF. Therefore, our accomplishment in this CRADA improved the efficiency and accuracy of strain testing by developing and implementing fast analytical methods, robust processing tools, and software for predicting the best methods for UHPLC analysis.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Hydrogen permeability and stability of palladium films in a high pressure reactor

Palladium (Pd) thin films were fabricated by colloidal spray deposition (CSD) on substrates of porous yttrium stabilized zirconium oxide (YSZ). The films were sintered at 1140–1160 °C for 2–3 h in argon and had thickness of 5–11 μm. The hydrogen (H 2 ) permeation flux for the Pd film was measured with simulated feed gases (90% H 2 /He, syn-gas/steam, or syn-gas/steam with H 2 S) flowing on the film side and sweep gas (Ar) flowing on the substrate side. Here, the hydrogen flux with the Pd film was obtained by adjusting the flow rate and pressure of the gas. Hydrogen flux values of 121–173 cm 3 min -1 cm -2 were measured at 388–596 °C (feed: 90% H 2 /He at 200 mL min -1 ; sweep: Ar at 1400 mL min -1 ; and ΔP = ~170 psi), and the permeability was calculated and compared with literature values. Because Pd is known to be sensitive to some gases, the stability of Pd films was evaluated by examining the microstructures of samples after their exposure to gas mixtures containing CO, CO 2 , H 2 O, and H 2 S. From the results of stability tests in H 2 S-containing atmospheres, the Pd/Pd 4 S phase boundary was determined, and this measured boundary was compared to the Pd/Pd 4 S boundary calculated from the thermodynamic data in the literature.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Endophyte‐induced systemic spatial reprogramming of metabolism in Populus trichocarpa roots under drought

Beneficial, facultative endophytes help plants thrive in challenging environments by altering their host's metabolism, but how these cellular scale metabolic changes propagate to the systems biology scale is unknown. In this work, we employed a high-resolution chemical imaging approach to map metabolic changes at the Populus trichocarpa root-zone and cell-type levels combined with machine learning (ML) models to identify root metabolites and exudates that have predictive power over treatment class. We found that a nine-strain consortium of beneficial endophytes differentially altered the metabolome of droughted root tissues in a manner specific to cell type and root zone, with endophyte abundance showing a clear correlation to individual metabolites. Our study demonstrates that integrating spatial metabolomics with ML can reveal localized metabolic patterns linked to root–microbe interactions and generate novel hypotheses about underlying biological mechanisms.

Drought↗
DOE OSTI2026

Explosive nucleation and growth of Pb islands on Ge(111) below room temperature via collective diffusion

Nucleation is a fundamental process in nature controlling phase transitions and pattern formation. Classical nucleation is based on the gradual aggregation of diffusing atoms after a critical cluster size is reached. Contrary to these expectations, we have observed in real time the formation of perfect Pb(111) islands with more than 10 5 atoms emerging out of the compressed wetting layer within a few seconds during growth of Pb on Ge(111) below room temperature. Pb deposited on Ge(111) in a temperature range between −30 °C and 10 °C exhibited explosive nucleation of height-selected islands upon reaching a critical coverage of 1.33 ± 0.07 ML with respect to Ge(111). Island nucleation was fueled by the 2% compression of the Pb wetting layer at the critical coverage. The island areas grew linearly with time, exhibiting collective diffusion, where thousands of atoms follow correlated, non-random walk diffusion. The total growth rate was higher with increasing temperature. Density functional theory simulations of the chemical potential and binding sites of the Pb/Ge(111) system give insight into the role of the compression of the wetting layer and the strain within the growing Pb layers, which explain this nonclassical behavior of the system.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
NASA NTRS1976

A role for glucose in hypothermic hamsters

Hypothermic hamsters at a rectal temperature of 7 C showed a fivefold increase in survival times from 20 to 100.5 hr when infused with glucose which maintained a blood level at about 45 mg/100 ml. A potential role for osmotic effects of the infusion was tested and eliminated. There was no improvement in survival of 3-O-methylglucose or dextran 40-infused animals. The fact that death eventually occurs even in the glucose-infused animal after about 4 days and that oxygen consumption undergoes a slow decrement in that period suggests that hypothermic survival is not wholly substrate limited. Radioactive tracer showed that localization of the C-14 was greatest in brain tissue and diaphragm, intermediate in heart and kidney, and lowest in skeletal muscle and liver. The significance of the label at sites important to respiration and circulation was presented.

Resch, G. E.↗
NASA NTRS1993

The impact of U.S. continental outflow on ozone and aerosol distributions over the western Atlantic

Aircraft measurements of selected trace gas species, aerosols, and meteorological parameters were performed in the lower troposphere off the U.S. east coast during August and September 1989 as part of the NASA Global Tropospheric Experiment (GTE) Chemical Instrumentation Test and Evaluation (CITE 3) expedition. In this paper, we examine these data to assess the impact of continental outflow on western Atlantic O3 and small aerosol budgets. Results show that mixed layer (ML) O3 concentrations and small aerosol number densities (Np) were enhanced by factors of 3 and 6, respectively, within air masses of predominantly continental origin compared with clean maritime background air. These enhancements exhibited a marked altitude dependence, declining rapidly above the ML to the point where only slight to moderate differences in O3 and Np, respectively, were notable above 2.4 km. Within continentally influenced ML's, both O3 and Np were correlated with CO, exhibiting linear regression slopes averaging 0.4 ppbv (O3)/ppbv(CO) for O3 and 7.7 (particles/cc)/ppbv(CO) for Np and indicating a primarily anthropogenic origin for the observed enhancement of these species. Comparisons between profiles in continental and background maritime air masses suggest that photochemical production below 1.4-km altitude adds over 10% to western Atlantic tropospheric column O3 abundance in continental outflow regimes. For aerosols, eastward advection of low-level continental air contributes an average net flux of 2.8 metric tons of submicron (accumulation mode) particles per kilometer of shoreline per day to the western Atlantic troposphere.

Anderson, B. E.↗
DOE OSTI2020

Autotuning of Double-Dot Devices In Situ with Machine Learning

The current practice of manually tuning quantum dots (QDs) for qubit operation is a relatively time-consuming procedure that is inherently impractical for scaling up and applications. In this work, we report on the in situ implementation of a recently proposed autotuning protocol that combines machine learning (ML) with an optimization routine to navigate the parameter space. In particular, we show that a ML algorithm trained using exclusively simulated data to quantitatively classify the state of a double-QD device can be used to replace human heuristics in the tuning of gate voltages in real devices. Here, we demonstrate active feedback of a functional double-dot device operated at millikelvin temperatures and discuss success rates as a function of the initial conditions and the device performance. Modifications to the training network, fitness function, and optimizer are discussed as a path toward further improvement in the success rate when starting both near and far detuned from the target double-dot range.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
NASA NTRS2011

Extracting Zero-Gravity Surface Figure of a Mirror

The technical innovation involves refinement of the classic optical technique of averaging surface measurements made in different orientations with respect to gravity, so the effects of gravity cancel in the averaged image. Particularly for large, thin mirrors subject to substantial deformation, the further requirement is that mount forces must also cancel when averaged over measurement orientations. The zerogravity surface figure of a mirror in a hexapod mount is obtained by analyzing the summation of mount forces in the frame of the optic as surface metrology is averaged over multiple clockings. This is illustrated with measurements taken from the Space Interferometry Mission (SIM) PT-Ml mirror for both twofold and threefold clocking. The positive results of these measurements and analyses indicate that, from this perspective, a lighter mirror could be used; that is, one might place less reliance on the damping effects of the elliptic partial differential equations that describe the propagation of forces through glass. The advantage over prior art is relaxing the need for an otherwise substantial thickness of glass that might be needed to ensure accurate metrology in the absence of a detailed understanding and analysis of the mount forces. The general insights developed here are new, and provide the basic design principles on which mirror mount geometry may be chosen.

Bloemhof, Eric E.↗
DOE OSTI2025

A combined experimental and machine learning exploration of Ti 2-x Zr x MnCrFeNi high entropy Laves hydrides

A series of high entropy AB 2 -type Ti 2-x Zr x MnCrFeNi alloys (x = 0.6, 0.7, 0.8, 0.9, 1.0, 1.1 and 1.2) were synthesized to investigate their potential for hydrogen storage and chemical compression. The influence of the Ti/Zr ratio was explored in terms of structural, microstructural and thermodynamic properties. The storage capacity together with the reaction enthalpy and entropy changes of the synthesized high entropy alloys were compared to predictions from Machine Learning (ML) to investigate changes in these properties across the explored composition space. The results revealed that a decreasing Zr content consistently lowered the hydride formation enthalpy and increased the plateau pressure from 8 to >90 bar H 2 at 25 °C, in good agreement with ML predictions. Selected compositions (x = 1.0 and 1.2) demonstrated reversible hydrogen storage capability over 150 cycles, with capacities of 1.34–1.40 wt % H 2 and remarkable reaction kinetics (<4 min) at ambient temperature. These experimental and computational findings highlight the potential of this Laves-HEA system as tuneable, stable, and cost-effective materials suitable for long-term operations in stationary hydrogen storage and compression applications.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Design-driven optimization of low-cost reagent formulations for reproducible and high-yielding cell-free gene expression

Access to recombinant proteins is vital in basic science and biotechnology research. Cell-free gene expression systems provide one approach to address this need, but widespread utilization remains limited by the cost, complexity, and inconsistency of current platforms. To address these limitations, we carry out a multi-dimensional definitive screening design to reduce the number of reagent components and remove costly secondary energy substrates. From 1,231 different reagent formulations, we discover a simple and reproducible system based on 12 components. The optimized reagent formulation can produce 2.4 ± 0.3 g/L of protein product at the 15-µL scale (~$\$60$/gprotein) and 3.7 ± 0.2 g/L (~$\$39$/gprotein) at the 4-mL scale with oxygen supplementation. This provides an average 95% reduction in cost over previous cell-free reagent formulations. We further show that the optimized reagent formulation can produce nucleoside triphosphates from nitrogenous bases and ribose and that it is robust to failure across batches of cell lysates, users/locations, and in the synthesis of more than 20 different proteins. For example, we demonstrate the production of fifteen therapeutically relevant products, including full-length aglycosylated monoclonal antibodies. We anticipate that our optimized reagent formulation will democratize the use of cell-free systems for protein manufacturing and synthetic biology applications.

Biologics↗
NASA NTRSDate not supplied

Predicting Melt Properties Using Atomistic Simulations With A Highly Accurate Physically Informed Neural Network Interatomic Potential

The use of a recently developed machine learning (ML) interatomic potential for molecular dynamics simulations of aluminum melt properties will be presented. Such properties are critical for process modeling in additive manufacturing, including the melt pool size, solidification, and formation of solidification microstructures. Direct first-principles modeling of these processes is computationally prohibitive whereas simulations employing ML potentials combine the high accuracy of quantum-mechanical methods with high computational speeds. The physically-informed neural network (PINN) method used herein, integrates a high-dimensional regression implemented by an artificial neural network with a physics-based bond-order interatomic potential. PINN potentials can accurately reproduce many properties of aluminum in both crystalline-solid and liquid phases. We examine the accuracy of a PINN Al potential in predicting the density, self-diffusivity, viscosity, and the tension of the liquid surface and liquid-solid interfaces. Comparison with experimental data and ab initio molecular dynamics calculations shows very good agreement for all properties tested.

molecular dynamics↗
DOE OSTI2025

A scalable and autoclavable oxygen nanosensor platform for metabolic monitoring of Saccharomyces cerevisiae in a bioreactor and other in situ systems

Polymer-encapsulated dye nanoparticle sensors are a valuable approach to achieving in situ analyte measurements with luminescence; however, typical emulsion-based nanosensors are poorly suited for large-scale biological samples due to limitations of synthesis scalability and stability. Branched polyethylenimine (PEI) is a versatile polymer scaffold ideal for constructing nanoparticles with various covalently conjugated moieties due to their high density of reactive primary amines, high water solubility, and biological stability. In this work, we used branched polyethylenimine as a scaffold-based approach for making a stable and scalable ratiometric oxygen sensor. Pt (II) tetracarboxyporphine was used as an oxygen-sensing dye and coumarin 343 as a reference dye, all covalently linked to the PEI scaffold producing a product that could withstand sterilization procedures and easily be scaled. To minimize toxicity from the PEI scaffold, we conjugated it with 2000 MW PEG. The applicability of the sensors was demonstrated in a 200 mL Saccharomyces cerevisiae yeast culture, using orthogonal luminescent and electrochemical oxygen measurements to validate sensor response and measure the metabolic activity of the yeast in our culture. Further, this approach was able to match the sensitivity of our electrochemical measurements while improving upon drawbacks of other luminescent methods of oxygen detection, demonstrating effective monitoring for at least 20 h. Our scaffold-based approach is a modular and easily translatable technology that could be useful in various biotechnological applications.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS2001

Analysis of Ag/FEP Thermal Control Blanket Performance From Multiple Satellites

Materials performance data from operational spacecraft and spacecraft experiments has slowly accumulated over the years. Much of this data is obtained indirectly by analyzing temperature measurements telemetered to ground. Due to the Space Transportation System (STS) program, materials performance data has also been obtained by flying materials on satellites, or on the Space Shuttle itself, for limited periods of time, and then returning the materials to ground for post-flight examination. During the course of NASA contract NAS8-98213, the authors have extended the analysis of data reported for selected materials flown on a variety of spacecraft over the past 30 years. In this paper we discuss changes in two properties of silver- or aluminum-backed (metallized) FEP Teflon due to exposure to specific environmental factors on-orbit. First, the change in solar absorptance (alpha(sub s)) of metallized FEP Teflon as a function of particulate radiation will be discussed. Data providing the change in solar absorptance of metallized FEP as a function of days on orbit has been published for NTS-2 satellite, several NavStar Global Positioning Satellites (GPS), the SCATHA experiment, and the ML-101 satellite. The unique approach that we have taken is to calculate the absorbed radiation dose within the Ag/FEP for the various satellite orbits, and to plot the change in solar absorptance, alpha(sub s), as a function of the dose; the behavior agrees with the same data from laboratory tests. Second, the variation of the atomic oxygen induced material recession rate of metallized FEP will be discussed. Data from certain Space Shuttle flights, a Lockheed experiment [approximately 105 days in low Earth orbit (LEO)], and the Long Duration Exposure Facility allows the variation of the material recession rate of Ag/FEP to be estimated under conditions that include atomic oxygen exposure.

Pippin, Gary↗
NASA NTRS2004

Characterization of Two Microbial Isolates from Andean Lakes in Bolivia

We are currently investigating the biological population present in the highest and least explored perennial lakes on earth in the Bolivian and Chilean Andes, including several volcanic crater lakes of more than 6000 m elevation, in combination of microbiological and molecular biological methods. Our samples were collected in saline lakes of the Laguna Blanca Laguna Verde area in the Bolivian Altiplano and in the Licancabur volcano crater (27 deg. 47 min S/67 deg. 47 min. W) in the ongoing project studying high altitude lakes. The main goal of the project is to look for analogies with Martian paleolakes. These Bolivian lakes can be described as Andean lakes following the classification of Chong. We have attempted to isolate pure cultures and phylogenetically characterize prokaryotes that grew under laboratory conditions. Sediment samples taken from the Licancabur crater lake (LC), Laguna Verde (LV), and Laguna Blanca (LB) were analyzed and cultured using enriched liquid media under both aerobic and anaerobic conditions. All cultures were incubated at room temperature (15 to 20 C) and under light exposure. For the reported isolates, 36 hours incubation were necessary for reaching optimal optical densities to consider them viable cultures. Ten serial dilutions starting from 1% inoculum were required to obtain a suitable enriched cell culture to transfer into solid media. Cultures on solid medium were necessary to verify the formation of colonies in order to isolate pure cultures. Different solid media were prepared using several combinations of both trace minerals and carbohydrates sources in order to fit their nutrient requirements. The microorganisms formed individual colonies on solid media enriched with tryptone, yeast extract and sodium chloride. Cells morphology was studied by optical and electronic microscopy. Rodshape morphologies were observed in most cases. Total bacterial genomic DNA was isolated from 50 ml late-exponential phase culture by using the CTAB miniprep protocol. The 16S rRNA genes were amplified by PCR using both Bacteria- and Archaeauniversal primer sets: 27f and 1492r, 21f and 1492r respectively. Sequences of 16S rRNA gene were determined and initially compared with reference sequences contained in the EMBL nucleotide sequence database by using the BLAST program and were subsequently aligned with 16S rRNA reference sequences in the ARB package (http://www.mikro.biologie.tu-muenchen.de). Aligned sequences were inserted within a stable phylogenetic tree by using the ARB parsimony tool. In this work we report the morphology and phylogenetic characterization of two isolates belonged to Laguna Blanca sediments.

Demergasso, C.↗
NASA NTRS2007

The DaveMLTranslator: An Interface for DAVE-ML Aerodynamic Models

It can take weeks or months to incorporate a new aerodynamic model into a vehicle simulation and validate the performance of the model. The Dynamic Aerospace Vehicle Exchange Markup Language (DAVE-ML) has been proposed as a means to reduce the time required to accomplish this task by defining a standard format for typical components of a flight dynamic model. The purpose of this paper is to describe an object-oriented C++ implementation of a class that interfaces a vehicle subsystem model specified in DAVE-ML and a vehicle simulation. Using the DaveMLTranslator class, aerodynamic or other subsystem models can be automatically imported and verified at run-time, significantly reducing the elapsed time between receipt of a DAVE-ML model and its integration into a simulation environment. The translator performs variable initializations, data table lookups, and mathematical calculations for the aerodynamic build-up, and executes any embedded static check-cases for verification. The implementation is efficient, enabling real-time execution. Simple interface code for the model inputs and outputs is the only requirement to integrate the DaveMLTranslator as a vehicle aerodynamic model. The translator makes use of existing table-lookup utilities from the Langley Standard Real-Time Simulation in C++ (LaSRS++). The design and operation of the translator class is described and comparisons with existing, conventional, C++ aerodynamic models of the same vehicle are given.

Hill, Melissa A.↗
DOE OSTI2024

The activity of antimicrobial peptoids against multidrug-resistant ocular pathogens

Background: Ocular infections caused by antibiotic-resistant pathogens can result in partial or complete vision loss. The development of pan-resistant microbial strains poses a significant challenge for clinicians as there are limited antimicrobial options available. Synthetic peptoids, which are sequence-specific oligo-N-substituted glycines, offer potential as alternative antimicrobial agents to target multidrug-resistant bacteria. Methods: The antimicrobial activity of synthesised peptoids against multidrug-resistant (MDR) ocular pathogens was evaluated using the microbroth dilution method. Hemolytic propensity was assessed using mammalian erythrocytes. Peptoids were also incubated with proteolytic enzymes, after which their minimum inhibitory activity against bacteria was re-evaluated. Results: Several alkylated and brominated peptoids showed good inhibitory activity against multidrug-resistant Pseudomonas aeruginosa strains at concentrations of ≤15 μg mL -1 (≤12 µM). Similarly, most brominated compounds inhibited the growth of methicillin-resistant Staphylococcus aureus at 1.9 to 15 μg mL -1 (12 µM). The N-terminally alkylated peptoids caused less toxicity to erythrocytes. The peptoid denoted as TM5 had a high therapeutic index, being non-toxic to either erythrocytes or corneal epithelial cells, even at 15 to 22 times its MIC. Additionally, the peptoids were resistant to protease activity. Conclusions: Peptoids studied here demonstrated potent activity against various multidrug-resistant ocular pathogens. Their properties make them promising candidates for controlling vision-related morbidity associated with eye infections by antibiotic-resistant strains.

60 APPLIED LIFE SCIENCES↗