Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “met”

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 307 records · Page 17
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

AmeriFlux BASE data pipeline to support network growth and data sharing

Abstract AmeriFlux is a network of research sites that measure carbon, water, and energy fluxes between ecosystems and the atmosphere using the eddy covariance technique to study a variety of Earth science questions. AmeriFlux’s diversity of ecosystems, instruments, and data-processing routines create challenges for data standardization, quality assurance, and sharing across the network. To address these challenges, the AmeriFlux Management Project (AMP) designed and implemented the BASE data-processing pipeline. The pipeline begins with data uploaded by the site teams, followed by the AMP team’s quality assurance and quality control (QA/QC), ingestion of site metadata, and publication of the BASE data product. The semi-automated pipeline enables us to keep pace with the rapid growth of the network. As of 2022, the AmeriFlux BASE data product contains 3,130 site years of data from 444 sites, with standardized units and variable names of more than 60 common variables, representing the largest long-term data repository for flux-met data in the world. The standardized, quality-ensured data product facilitates multisite comparisons, model evaluations, and data syntheses.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2022

Laser-based ultrasound interrogation of surface and sub-surface features in advanced manufacturing materials

Abstract Structures formed by advanced manufacturing methods increasingly require nondestructive characterization to enable efficient fabrication and to ensure performance targets are met. This is especially important for aerospace, military, and high precision applications. Surface acoustic waves (SAW) generated by laser-based ultrasound can detect surface and sub-surface defects relevant for a broad range of advanced manufacturing processes, including laser powder bed fusion (LPBF). In particular, an all-optical SAW generation and detection configuration can effectively interrogate laser melt lines. Here we report on scattered acoustic energy from melt lines, voids, and surface features. Sub-surface voids are also characterized using X-ray Computed Tomography (CT). High resolution CT results are presented and compared with SAW measurements. Finite difference simulations inform experimental measurements and analysis.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Development and validation of a mathematical model of heart rate response to fluid perturbation

Physiological closed-loop controlled (PCLC) medical devices monitor and automatically adjust the patient’s condition by using physiological variables as feedback, ideally with minimal human intervention to achieve the target levels set by a clinician. PCLC devices present a challenge when it comes to evaluating their performance, where conducting large clinical trials can be expensive. Virtual physiological patients simulated by validated mathematical models can be utilized to obtain preclinical evidence of safety and assess the performance of the PCLC medical device during normal and worst-case conditions that are unlikely to happen in a limited clinical trial. A physiological variable that plays a major role during fluid resuscitation is heart rate (HR). For in silico assessment of PCLC medical devices regarding fluid perturbation, there is currently no mathematical model of HR validated in terms of its predictive capability performance. This paper develops and validates a mathematical model of HR response using data collected from sheep subjects undergoing hemorrhage and fluid infusion. The model proved to be accurate in estimating the HR response to fluid perturbation, where averaged between 21 calibration datasets, the fitting performance showed a normalized root mean square error (NRMSE) of 7.41 ± 2.8%. The model was also evaluated in terms of model predictive capability performance via a leave-one-out procedure (21 subjects) and an independent validation dataset (6 subjects). Two different virtual cohort generation tools were used in each validation analysis. The generated envelope of virtual subjects robustly met the defined acceptance criteria, in which 95% of the testing datasets presented simulated HR patterns that were within a deviation of 50% from the observed data. In addition, out of 16000 and 18522 simulated subjects for the leave one-out and independent datasets, the model was able to generate at least one virtual subject that was close to the real subject within an error margin of 9.56 ± 3.15% and 11.1 ± 1.22% NRMSE, respectively. In conclusion, the model can generate valid virtual HR physiological responses to fluid perturbation and be incorporated into future non-clinical simulated testing setups for assessing PCLC devices intended for fluid resuscitation.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Pan-cancer proteogenomic investigations identify post-transcriptional kinase targets

Identifying genomic alterations of cancer proteins has guided the development of targeted therapies, but proteomic analyses are required to validate and reveal new treatment opportunities. Herein, we develop a new algorithm, OPPTI, to discover overexpressed kinase proteins across 10 cancer types using global mass spectrometry proteomics data of 1,071 cases. OPPTI outperforms existing methods by leveraging multiple co-expressed markers to identify targets overexpressed in a subset of tumors. OPPTI-identified overexpression of ERBB2 and EGFR proteins correlates with genomic amplifications, while CDK4/6, PDK1, and MET protein overexpression frequently occur without corresponding DNA- and RNA-level alterations. Analyzing CRISPR screen data, we confirm expression-driven dependencies of multiple currently-druggable and new target kinases whose expressions are validated by immunochemistry. Identified kinases are further associated with up-regulated phosphorylation levels of corresponding signaling pathways. Collectively, our results reveal protein-level aberrations—sometimes not observed by genomics—represent cancer vulnerabilities that may be targeted in precision oncology.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2025

Digital Twin for Chemical Science: a case study on water interactions on the Ag(111) surface

Directly visualizing chemical trajectories offers insights into catalysis, gas-phase reactions and photoinduced dynamics. Tracking the transformation of chemical species is best achieved by coupling theory and experiment. Here we developed Digital Twin for Chemical Science (DTCS) v.01, which integrates theory, experiment and their bidirectional feedback loops into a unified platform for chemical characterization. DTCS addresses a core question: given a set of experimental conditions, what is the expected outcome and why? It consists of a forward solver that takes a chemical reaction network and predicts spectra under experimental conditions, and an inverse solver that infers kinetics from measured spectra. We applied DTCS to ambient-pressure X-ray photoelectron spectroscopy measurements of the Ag–H2O interface as an example. This approach enables real-time knowledge extraction and guides experiments until a stopping condition is met based on accuracy and degeneracy. As a step toward autonomous chemical characterization, DTCS provides mechanistic knowledge in a verified, standardized manner.

Chemistry↗
DOE OSTI2025

Sintering protonic zirconate cells with enhanced electrolysis stability and Faradaic efficiency

The emerging applications of steam electrolysis and electrochemical synthesis at 300–600 °C set stringent requirements on the stability of protonic ceramic cells, which cannot be met by Ce-rich electrolytes. A promising candidate is Ce-free BaZr 0.8 Y 0.2 O 3–δ , but its usage has long been hindered due to the high sintering temperatures required for protonic devices. Here we resolved the issue through a co-sintering process, in which the shrinkage stress of a readily sinterable support layer helps to densify the pure BaZr 0.8 Y 0.2 O 3–δ electrolyte membrane at low temperatures. This approach eliminates Ce and harmful sintering aids in the dense zirconate electrolyte membrane, thereby enhancing the Faradaic efficiency and electrochemical stability, especially under harsh operating conditions. Here, the protonic zirconate cells have exceptional performance and demonstrate stable high-steam pressure electrolysis up to 0.7 atm steam pressure, –2 A cm –2 current density and over 800 h of dynamic operation at 600 °C. Our processing breakthrough enables stabilized protonic cells for demanding applications in future energy infrastructure.

25 ENERGY STORAGE↗
DOE OSTI2025

A bipartite bacterial virulence factor targets the complement system and neutrophil activation

Abstract The complement system and neutrophils constitute the two main pillars of the host innate immune defense against infection by bacterial pathogens. Here, we identify T-Mac, a novel virulence factor of the periodontal pathogen Treponema denticola that allows bacteria to evade both defense systems. We show that T-Mac is expressed as a pre-protein that is cleaved into two functional units. The N-terminal fragment has two immunoglobulin-like domains and binds with high affinity to the major neutrophil chemokine receptors FPR1 and CXCR1, blocking N -formyl-Met-Leu-Phe- and IL-8-induced neutrophil chemotaxis and activation. The C-terminal fragment functions as a cysteine protease with a unique proteolytic activity and structure, which degrades several components of the complement system, such as C3 and C3b. Murine infection studies further reveal a critical T-Mac role in tissue damage and inflammation caused by bacterial infection. Collectively, these results disclose a novel innate immunity-evasion strategy, and open avenues for investigating the role of cysteine proteases and immunoglobulin-like domains of gram-positive and -negative bacterial pathogens.

Kurniyati, Kurni↗
DOE OSTI2024

Polyhydroxyalkanoates in emerging recycling technologies for a circular materials economy

Circular polymer systems, specifically polyesters operating through chemical and biological technologies, are approaching a critical moment of industrial adoption and scale-up feasibility. At the same time, polyhydroxyalkanoate (PHA) production, scale-up, and resulting material development is converging toward commodity applications. The current PHA end-of-life philosophy, however, focalizes leveraging inherent biodegradability to circumvent plastic waste accumulation. If indeed a substantial replacement of incumbent single-use plastics with PHA alternatives is to be met in commercial manufacture, we emphasize the importance of linking PHA development with feasible polymer recycling technologies. In other words, a PHA materials economy is significantly more carbon- and cost-favorable when efficient mechanical (reprocessing), chemical (deconstruction, depolymerization), or biological (enzymatic) recycling is prioritized over biodegradation or composting. In this perspective, we discuss strategies for PHA recyclable-by-design principles, guidable by developing machine learning tools, as well as material compatibility with closed-loop recycling technologies. Additionally, we posit compelling life-cycle assessment incentives for adopting polymer reclamation over competing pathways. Ultimately, we hope this narrative further inspires the alignment between PHA design with growing calls for a circular material economy.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Cycloalkane-rich sustainable aviation fuel production via hydrotreating lignocellulosic biomass-derived catalytic fast pyrolysis oils

Sustainable aviation fuel (SAF) produced from lignocellulosic biomass is emerging as an ideal alternative to conventional jet fuel for aviation sector decarbonization. Catalytic fast pyrolysis (CFP) can convert lignocellulosic biomass into relatively stable bio-oil that can be selectively transformed to various transportation fuels through hydroprocessing under conditions of different severities. In this contribution, two CFP oils produced from pine-based feedstocks over different types of catalysts (i.e., ZSM-5 and Pt/TiO 2 catalysts) were hydrotreated at 125 bar in a non-isothermal process with a maximum temperature of 385 °C over a sulfided NiMo/Al 2 O 3 catalyst to produce SAF with high cycloalkane concentrations of 89–92 wt%. Cycloalkanes are an important component of jet fuel with advantageous fuel properties, such as high energy density, low sooting, and potential for replacing aromatic hydrocarbons to provide good seal swelling properties. The hydrotreating process successfully converted 91–92% of the biogenic carbon in the CFP oil intermediates to liquid-phase hydrotreated products. Through distillation, 39–40 wt% of the hydrotreated oils were collected in the jet-fuel range as SAF fractions. The rest of the hydrotreated product could be valorized as fuels (e.g., diesel) or chemicals. The SAF fractions with oxygen contents below the detection limit (<0.01 wt%) met ASTM D7566 finished fuel blend and D4054 Tier 1 specifications with respect to density, lower heating value (LHV), volatility, flash point, and freeze point. These results indicate hydrotreating lignocellulosic biomass-derived CFP oil as a promising pathway to produce high-quality SAF rich in cycloalkanes. Continued research is required to increase the SAF yield by process improvements, such as increased CFP oil yields, and an enhanced production of SAF-range molecules via e.g., cracking of high-molecular weight compounds either during CFP or hydrotreating, as well as evaluation of a broader range of jet fuel properties and performance requirements.

09 BIOMASS FUELS↗
DOE OSTI2025

Photosynthesis of CO from CO 2 with an iron polypyridyl catalyst at a passivated silicon photoelectrode

A first-row transition metal catalyst, [Fe(tpy)(Mebim-py)(NCCH 3 )] 2+ (tpy = 2,2′:6′,2′′-terpyridine, Mebim-py = 1-methylbenzimidazol-2-ylidene-3-(2′-pyridine)) mediates CO 2 reduction to CO at passivated p-Si photoelectrodes with applied potentials 240 mV positive of the standard CO 2 /CO reduction potential. The molecular catalyst's selectivity for CO was retained under photoelectrochemical conditions, with negligible direct proton reduction promoted by the photoelectrode. The faradaic efficiency for CO (44 ± 6%) was slightly enhanced relative to the catalyst performance in the dark (33%). A photosynthetic cell based on this photocathode system, coupled with ferrocene oxidation at the anode, successfully operated at a cell voltage of −1.2 V. The photovoltage generated by illumination of p-Si–CH 3 met and surpassed the potential required for CO 2 reduction when coupled with ferrocene oxidation. By leveraging a low-overpotential CO 2 reduction electrocatalyst, a photo-assisted electrochemical efficiency of 0.15% and applied bias photon-to-current efficiency of 0.05% was achieved for this single-junction cell, ultimately storing 46 kJ mol −1 (11 kcal mol −1 ) of photon energy.

Carbon Dioxide Reduction↗
DOE OSTI2020

DUNE DAQ R&D integration in ProtoDUNE Single-Phase at CERN

The DAQ system of ProtoDUNE-SP successfully proved its design principles and met the requirements of the beam run of 2018. The technical design of the DAQ system for the DUNE experiment has major differences compared to the prototype due to different requirements placed on the detector, as well as a radically different location of operation. The single-phase prototype at CERN is a major integration facility for R&D aspects of the DUNE DAQ system. The facility allows for the exploration of additional data processing capabilities and optimization of the FELIX system, which is the chosen TPC readout solution for the DUNE single-phase detectors. One of the fundamental differences from the prototype is that the DUNE DAQ relies on self-triggering. Therefore, real-time processing of the data stream for hit and trigger primitive finding is essential for the requirement of continuous readout. The supernova burst trigger requires a large and fast buffering technique, where 3D XPoint persistent memory solutions are evaluated and integrated. In order to maximize resource utilization of the FELIX hosting servers, the elimination of the 100 Gb network communication stack is desired. This implies the design and development of a single-host application layer, which is a fundamental element of the self-triggering chain. This paper discusses the evaluation and integration of these developments for the DUNE DAQ, in the ProtoDUNE environment.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2021

Installation Quality Framework: Investment Return Approach for Energy Savings on Building Product Installation

A case study was conducted on 44 residential homes using both traditional house wrap and ZIP System systems to measure the overall airtightness and compare estimated energy usages. The labor, material, and overhead and profit (O&P) costs were analyzed and used to determine the optimal choice for long-term benefits in terms of cost and performance. The impact of insulation installation is considered a key factor in improving the strategy of reducing energy consumption. Improved installation practices can affect the airtightness of common wall assemblies to reduce the building energy performance gaps and provide insight on how to allocate resources better. A framework was developed to analyze operational costs and building energy performance to address how installation quality is a factor in the return of investment in building construction for heating and cooling systems within the thermal envelope. With this methodology, aggressive energy performance goals will be met while balancing the tradeoff between installation techniques and building systems efficiency based on the introduced probabilistic investment return (PIR) metric.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2023

Low-pass spectral analysis of time-resolved serial femtosecond crystallography data

Low-pass spectral analysis (LPSA) is a recently developed dynamics retrieval algorithm showing excellent retrieval properties when applied to model data affected by extreme incompleteness and stochastic weighting. In this work, we apply LPSA to an experimental time-resolved serial femtosecond crystallography (TR-SFX) dataset from the membrane protein bacteriorhodopsin (bR) and analyze its parametric sensitivity. While most dynamical modes are contaminated by nonphysical high-frequency features, we identify two dominant modes, which are little affected by spurious frequencies. The dynamics retrieved using these modes shows an isomerization signal compatible with previous findings. We employ synthetic data with increasing timing uncertainty, increasing incompleteness level, pixel-dependent incompleteness, and photon counting errors to investigate the root cause of the high-frequency contamination of our TR-SFX modes. By testing a range of methods, we show that timing errors comparable to the dynamical periods to be retrieved produce a smearing of dynamical features, hampering dynamics retrieval, but with no introduction of spurious components in the solution, when convergence criteria are met. Using model data, we are able to attribute the high-frequency contamination of low-order dynamical modes to the high levels of noise present in the data. Finally, we propose a method to handle missing observations that produces a substantial dynamics retrieval improvement from synthetic data with a significant static component. Reprocessing of the bR TR-SFX data using the improved method yields dynamical movies with strong isomerization signals compatible with previous findings.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Compact and efficient elastocaloric heat pumps—Is there a path forward?

Elastocaloric cooling holds promise for energy-efficient heat pumping near room temperature with low environmental impact. Its adoption is, however, impeded by disproportionally large sizes of actuators compared with the active material volume. Taking magnetocaloric cooling as the baseline, the value of no more than 10:1 actuator volume to active material volume should lead to both size- and cost-effective solutions that may potentially be competitive with vapor-compression devices. With the goal to establish performance metrics that can lead to informed actuator selection for specific regenerator requirements, we analyze a wide range of elastocaloric materials and actuator technologies to find the best matches. We find that actuation with magnetic shape memory alloys meets all requirements; however, this technology is currently in early developmental stages and such actuators are not widely commercially available. Another promising and easily accessible option is standard rotary electric motors in combination with rotary-to-linear transduction mechanisms. A theoretical analysis of two case studies of elastocaloric systems using rotary electric motors with a Scotch yoke mechanism demonstrates the usefulness of our approach. Actuator requirements are based on two different regenerator configurations: one starting from zero strain without any mechanical energy recovery and another with 2% pre-strain and mechanical energy recovery to reduce the power and torque required from the motor. Our results indicate that the 10:1 target actuator to active material volume ratio can be met and feasibly lowered further, demonstrating that the proposed method for selecting actuators makes compact and efficient elastocaloric systems possible.

42 ENGINEERING↗
DOE OSTI2020

Investigating shear flow through continuum gyrokinetic simulations of limiter biasing in the Texas Helimak

Previous limiter-biasing experiments on the Texas Helimak, a simple magnetized torus, have been inconclusive on the effect of flow shear on turbulence levels. To explore this, the first gyrokinetic simulations of limiter biasing in the Helimak using the plasma physics code Gkeyll have been carried out, and results are presented here. For the scenarios considered, turbulence is mostly driven by the interchange instability, which depends on gradients of steady state density profiles. An analysis of both experimental and simulation data demonstrates that shear rates are mostly less than than local linear growth rates, and not all requirements for shear stabilization are met. Yet, the mostly vertical shear flow has an important effect on bulk transport and experimental steady-state density profiles, and changes to the gradients correspond to changes in turbulence levels.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2022

The N3/TiO 2 interfacial structure is dependent on the pH conditions during sensitization

The electronic structure of the N3/TiO 2 interface can directly influence the performance of a dye sensitized solar cell (DSSC). Therefore, it is crucial to understand the parameters that control the dye’s orientation on the semiconductor’s surface. A typical step in DSSC fabrication is to submerge the nanoparticulate semiconductor film in a solution containing the dye, the sensitizing solution. The pH of the N3 sensitizing solution determines the distribution of the N3 protonation states that exist in solution. Altering the pH of the sensitizing solution changes the N3 protonation states that exist in solution and, subsequently, the N3 protonation states that anchor to the TiO 2 substrate. We utilize the surface specific technique of heterodyne detected vibrational sum frequency generation spectroscopy to determine the binding geometry of N3 on a TiO 2 surface as a function of the sensitizing solution pH conditions. It is determined that significant reorientation of the dye occurs in pH ≤ 2.0 conditions due to the lack of N3-dye carboxylate anchoring groups participating in adsorption to the TiO 2 substrate. Consequently, the change in molecular geometry is met with a change in the interfacial electronic structure that can hinder electron transfer in DSSC architectures.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Leaving in the lead: Priorities for perovskite photovoltaics

The need for moving electricity generation to a sustainable model requires the development of low cost ubiquitous photovoltaics (PVs) to harvest the planet’s primary energy source, the Sun. Building upon the successes of Si-based and CdTe-based PV technologies, PVs with lower-embodied energy and requiring lower carbon dioxide equivalent to produce will be required to meet long-term sustainability goals. In particular, thin-film technologies, such as high-efficiency metal halide perovskite (MHP) PV modules, provide avenues to reduced embodied energy, lower energy payback times, and enabling energy-dense tandems [H. M. Wikoff et al., Joule 6(7), 1710–1725 (2022) and V. Fthenakis, Renewable Sustainable Energy Rev. 13(9), 2746–2750 (2009)]. The ability to improve efficiency and lower energy payback time of next generation thin-film PV modules is a critical foundation for green H2 and electrification more broadly. In this regard, Pb-based MHP-PVs have separated themselves as a result of the high-efficiencies that can be realized across a range of electronic gaps. Questions regarding Pb-based MHP-PVs that are often asked, as the challenges of efficiency and reliability are met, revolve around the “problem” of the Pb content. Specifically, “does Pb toxicity preclude MHP-PV modules from being deployed at the TW scale?” To provide this sense of scale, in 2021, the United States burned 10.5 quads of coal, with 90% of that used for electricity generation. Given the energy content of coal of 29 MJ/kg and a residual lead content in that coal of 30 mg/kg, electricity generation from coal resulted in more lead emitted into the atmosphere than what would be required to produce over 2 TW of MHP-PV name plate capacity (assuming a 20% module efficiency and an ∼700 nm active layer). This amounts to more PV power than has been deployed across all PV technologies and geographies to date. This only includes US coal consumption; the rest of the world would be much larger. This example illustrates the scale of the material usage relative to the energy production. Imagine a power-generation technology that offsets these Pb emissions from coal and essentially sequesters this Pb content between two sheets of impermeable glass. Why should we let Pb’s history of misuse prevent it from being included in next generation PV modules that can enable a sustainable energy future?

14 SOLAR ENERGY↗
DOE OSTI2024

Consistent and reproducible computation of the glass transition temperature from molecular dynamics simulations

In many fields, from semiconductors for opto-electronic applications to ionic liquids (ILs) for separations, the glass transition temperature (Tg) of a material is a useful gauge for its potential use in practical settings. As a result, there is a great deal of interest in predicting Tg using molecular simulations. However, the uncertainty and variation in the trend shift method, a common approach in simulations to predict Tg, can be high. This is due to the need for human intervention in defining a fitting range for linear fits of density with temperature assumed for the liquid and glass phases across the simulated cooling. The definition of such fitting ranges then defines the estimate for the Tg as the intersection of linear fits. We eliminate this need for human intervention by leveraging the Shapiro–Wilk normality test and proposing an algorithm to define the fitting ranges and, consequently, Tg. Through this integration, we incorporate into our automated methodology that residuals must be normally distributed around zero for any fit, a requirement that must be met for any regression problem. Consequently, fitting ranges for realizing linear fits for each phase are statistically defined rather than visually inferred, obtaining an estimate for Tg without any human intervention. The method is also capable of finding multiple linear regimes across density vs temperature curves. We compare the predictions of our proposed method across multiple IL and semiconductor molecular dynamics simulation results from the literature and compare other proposed methods for automatically detecting Tg from density–temperature data. We believe that our proposed method would allow for more consistent predictions of Tg. We make this methodology available and open source through GitHub.

Chemistry↗