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Results for “Effectiveness evaluation”

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 397 records · Page 22
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

MALDI-MS screening of microbial colonies with isomer resolution to select fatty acid desaturase variants

Creating controlled lipid unsaturation locations in oleochemicals can be a key to many bioengineered products. However, evaluating the effects of modifications to the acyl-ACP desaturase on lipid unsaturation is not currently amenable to high-throughput assays, limiting the scale of redesign efforts to <200 variants. Here, we report a rapid MS assay for profiling the positions of double bonds on membrane lipids produced by Escherichia coli colonies after treatment with ozone gas. By MS measurement of the ozonolysis products of Δ6 and Δ8 isomers of membrane lipids from colonies expressing recombinant Thunbergia alata desaturase, we screened a randomly mutagenized library of the desaturase gene at 5 s per sample. Two variants with altered regiospecificity were isolated, indicated by an increase in 16:1 Δ8 proportion. We also demonstrated the ability of these desaturase variants to influence the membrane composition and fatty acid distribution of E. coli strains deficient in the native acyl-ACP desaturase gene, fabA. Lastly, we used the fabA deficient chassis to concomitantly express a non-native acyl- ACP desaturase and a medium-chain thioesterase from Umbellularia californica, demonstrating production of only saturated free fatty acids.

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

Global impacts of vegetation clumping on regulating land surface heat fluxes

The clumping index (CI) quantifies the non-random distribution of vegetation across space, which regulates the canopy radiative transfer processes and land surface carbon, water, and energy cycles. However, its impact on global surface energy budget, particularly sensible heat fluxes and surface temperature, is not well understood. Additionally, while there have been studies showing significant seasonal variations in CI, the impacts of these variations on surface energy fluxes remain unclear. In this study, we incorporated satellite-derived spatially and temporally explicit CI data into the Community Land Model version 5 (CLM5) to evaluate the effects of CI on global land energy fluxes. Our results showed that including CI increased the global mean sensible heat flux dissipated from ground by 3.9 W m -2 (~18%), while decreasing the global mean vegetation sensible heat flux by 4.9 W m -2 (~65%), resulting in a total sensible heat decrease of 1.0 W m -2 (~3%). In contrast, CI increased the global mean latent heat flux by 0.8 W m -2 (~2%), primarily due to increased evapotranspiration (up to 11 W m -2 ) in tropical regions. We also found considerable impacts of seasonal variations in CI, particularly on sensible heat fluxes from ground and vegetation in evergreen needleleaf forests and deciduous needleleaf forests. Using constant CI rather than considering seasonal variations resulted in significant overestimation and underestimation of the sensible heat fluxes from vegetation and ground, respectively, in boreal summer. In conclusion, these changes in surface energy fluxes caused by CI and its seasonal variations led to up to 1.7 and 0.5 K differences in simulated mean ground temperature. These findings highlight the importance of including CI and considering its seasonal variations in modeling land surface energy fluxes.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Can Wholesale Electricity Markets Achieve Resource Adequacy and High Clean Energy Generation Targets in the Presence of Self-Interested Actors?

Wholesale electricity markets are intended to incentivize system generation investments and operations outcomes that meet evolving system needs. In this work, we evaluate the effectiveness of wholesale market structures, rules and policies in achieving system resource adequacy (RA) and clean energy targets in the presence of self-interested generation investors using the Electricity Markets and Investment Suite Agent-based Simulation (EMIS-AS) model. Results highlight that both capacity markets and operating reserve demand curves (ORDCs) can help achieve a reliable system but with different RA compliance timelines and distribution of generation technologies. Structures with capacity markets tend to favor more capital-intensive peaking technologies while reducing wind and solar build-outs due to suppressed energy and clean energy market prices, particularly in the absence of strong clean energy targets. Conversely, ORDCs improve the commitment of available generation units, but this comes at the expense of higher system costs and renewable generation curtailment. We also find that well-calibrated static capacity demand curves can yield similar reliability and total cost compared to capacity market demand curves informed dynamically by resource adequacy while also yielding stable annual capacity prices. Different approaches to formulating ORDC curves can also yield key trade-offs, namely that a more efficient treatment of storage chronology results in lower ORDC curves and prices, yielding less investment and cost but at the expense of reliability. Finally, the effectiveness of wholesale electricity markets in practically achieving very high clean energy generation targets highly depends on the cost-competitiveness of clean energy technologies that can support critical balancing needs across multiple timescales.

capacity expansion↗
DOE OSTI2021

Investigation of GaAs surface treatments for ZnSe growth by molecular beam epitaxy without a buffer layer

Atomically clean and smooth surfaces are critical prerequisite for the epitaxial regrowth of dissimilar semiconductors. Using ZnSe/GaAs as a model system, epitaxial regrowth without a buffer layer after thermal cleaning with various As-fluxes, atomic Ga flux, and atomic hydrogen treatments to the GaAs substrates and the surfaces were investigated in this work via in-situ Auger electron spectroscopy (AES). The ZnSe epilayers grown on the pre-treated GaAs surfaces without a buffer layer were characterized by X-ray diffraction (XRD), photoluminescence (PL) and atomic force microscopy (AFM) to evaluate the effectiveness of the surface treatment methods. It was found that a high quality ZnSe layer can be achieved by atomic hydrogen surface treatment at 300°C without requiring GaAs buffer layer growth, which reveals a path for epitaxy growth avoiding high temperature treatments.

42 ENGINEERING↗
DOE OSTI2024

Policy impact on economic and environmental sustainability of anaerobic digestion: Industrial case study Insights

This paper thoroughly examines how policy incentives impact the economic and environmental sustainability of anaerobic digestion (AD) systems. It uses techno-economic and life cycle analyses, along with real industry data, to explore the entire AD process—from feedstock acceptance to digestate disposal. It evaluates the effects of various U.S. policy crediting programs on the economic viability of different AD pathways for treating sewage sludge and food waste. Furthermore, tipping fees are identified as the primary driver of profitability, while policy credits play a crucial role in enhancing economic feasibility, particularly for renewable natural gas production. However, future regulatory changes could reshape this economic landscape. All AD pathways are found to significantly reduce greenhouse gas emissions, though economic outcomes are highly sensitive to digestate disposal costs and feedstock tipping fees. Co-digestion with food waste is proposed as a strategy to reduce dependence on policy credits and improve long-term economic stability.

Anaerobic Digestion↗
DOE OSTI2022

A hierarchical stochastic modeling approach for representing point bar geometries and petrophysical property variations

The flow of fluids in point bars is affected by the existence of heterogeneities like shale drapes that are found on the surfaces of inclined heterolithic stratifications. In fact, these shale drapes can act as fluid flow baffles; therefore, developing a framework for modeling point bars and their associated heterogeneities is vital. In this study, a stochastic process-based modeling approach is presented for capturing the main point bar heterogeneities: accretion surfaces (i.e., the aerial heterogeneity) and inclined heterolithic stratifications (i.e., the vertical heterogeneity). The former was modeled using a sine-generation function and the latter, with a sigmoidal function after which they were combined into a 3D point bar model. To ensure proper modeling of petrophysical properties, we developed a more representative gridding scheme which generates curvilinear grids representative of the point bar geometry. This grid was then transformed into a rectilinear grid to allow for geostatistical simulation after which all petrophysical properties were mapped back into the original curvilinear grid. An essential element of this modeling approach is the stochastic representation of shale drapes at the interface between successive accretion surfaces. The workflow was tested using a real field dataset for the Cranfield field, Mississippi. The constructed model was then subjected to a flow simulation study mimicking a CO 2 storage scenario. Various sensitivities were simulated to evaluate the effect of heterogeneities on CO 2 flow within the point-bar. Results demonstrate the importance of representing point-bar related heterogeneity and the spatial distribution of shale drapes on CO 2 plume migration and storage.

58 GEOSCIENCES↗
DOE OSTI2026

Functionalized benzylamines from commercial kraft lignin

Benzylamines are key intermediates in pharmaceuticals, agrochemicals, and polymers, but their conventional production relies on benzyl chloride - a petroleum-derived compound with high toxicity and energy demands. Lignin, accounting for up to 30% of plant biomass, is the largest renewable source of aromatic carbon on Earth. However, its highly complex and recalcitrant structure poses a major barrier to efficient conversion into high-value chemicals. Here, in this study, we developed a catalytic approach to convert commercial kraft lignin into phenolic benzylamines through selective depolymerization and subsequent functionalization. We systematically evaluated the effects of three alcohol solvents, formic acid (FA), and a ruthenium-on‑carbon (Ru/C) catalyst on monophenol yield and selectivity. Up to 6.5 wt% monophenol yield was achieved using methanol (MeOH), FA, and Ru/C at 300 °C for 2 h. Quantum thermodynamic simulations based on the COSMO-RS model confirmed the superior solvation and reactivity of the MeOH + FA system, rationalizing observed product yield. The purified monophenolic products, primarily guaiacol and alkyl guaiacols, were then converted into functionalized benzylamines with >90% yield via a multicomponent Mannich reaction under mild conditions. Techno economic analysis (TEA) and life cycle assessment (LCA) underscore the importance of improving lignin depolymerization yields and expanding biorefinery scale. Solvent-only configurations outperform other options in both cost and emissions, with the methanol-only case performing the best ($\$$105 /kg and 26 kg CO 2e /kg) at a large-scale facility. This study establishes a scalable, bio-based pathway for producing benzylamines from commercial kraft lignin, advancing lignin valorization and offering a sustainable alternative to produce petrochemical-based benzylamines.

Catalytic reduction↗
DOE OSTI2021

Copper transformation, speciation, and detoxification in anoxic and suboxic freshwater sediments

The complex chemistry of copper (Cu) in freshwater sediments at low concentrations is not well understood. We evaluated the transformation processes of Cu added to freshwater sediments under suboxic and anoxic conditions. Freshwater sediments from three sources in Michigan with different characteristics (Spring Creek, River Raisin, and Maple Lake) were spiked with 30 or 60 mg kg -1 Cu and incubated under a nitrogen atmosphere. After 28-d, each treatment subset was amended with organic matter (OM) to promote anoxic conditions and evaluate its effects on Cu speciation. OM addition triggered a shift from suboxic to anoxic conditions, and sequential extractions showed that Cu accordingly shifted from acid-soluble to oxidizable fractions. Extended X-ray absorption fine-structure (EXAFS) spectroscopy revealed that Cu sulfides dominated all anoxic samples except for Spring Creek 30 mg kg -1 , where Cu(I) was predominantly complexed to thiol groups of OM. Covellite and chalcopyrite (CuFeS 2 ) were the predominant Cu species in nearly all anoxic samples, as determined by Raman spectroscopy, scanning electron microscopy, and X-ray absorption near-edge structure (XANES) spectroscopy. Copper reduction also occurred under suboxic conditions: for two of three sediments, around 80% had been reduced to Cu(I), while the remaining 20% persisted as Cu(II) complexed to OM. However, in the third coarsest (i.e., Spring Creek), around 50% of the Cu had been reduced, forming Cu(I)-OM complexes, while the remainder was Cu(II)-OM complexes. Toxicity tests showed that survival of H. azteca and D. magna were significantly lower in suboxic treatments. Anoxic sediments triggered a near-complete transformation of Cu to sulfide minerals, reducing its toxicity.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Ineffectiveness of ultrasound at low frequency for treating per- and polyfluoroalkyl substances in sewage sludge

Concerns have been raised about per- and polyfluoroalkyl substances (PFAS) in sewage sludge given the urgent need of finding suitable disposal methods for sludge. Here in this study, we evaluated the effect of ultrasonication on PFAS changes in sewage sludge. It was revealed that although ultrasonication at 20 kHz increased the soluble chemical oxygen demand (SCOD) of treated sewage sludge, this technique was ineffective for degrading perfluoroalkyl acids (PFAAs) and their precursors. Ultrasonic treatment for longer time (>15 min) led to concentration increase of perfluorooctanoic acid (PFOA), perfluoroheptanoic acid (PFHpA), and perfluorohexanoic acid (PFHxA) in the liquid phase, possibly due to their release from disrupted sludge flocs during cavitation. Adding permanganate (10 mM) to the ultrasonic system could also enhance the disruption of sludge particles, resulting in higher concentrations of PFOA and PFHxA in the solid phase and PFOA, PFHpA, PFHxA, and perfluorobutanesulfonic acid (PFBS) in the liquid phase. Overall, ultrasonic pretreatment at 20 kHz and 0.7 W/mL is unlikely to remove PFAS from sewage sludge. Instead, it could increase the risk of PFAS pollution upon final sludge disposal. Effective treatment technologies are thus demanded if PFAS in sludge are regulated.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Parametric analysis of anodic degradation mechanisms for fast charging lithium batteries with graphite anode

In this work, we report the impact of the temperature-driven synergistically-coupled anodic degradation mechanisms on the electrochemical performance of lithium batteries with graphite anode over multiple cycles. Temperature dependence of electrochemical reactions and damage mechanisms, such as solid electrolyte interface (SEI) growth, lithium plating/stripping, dead lithium storage/dissolution, and film cracking are incorporated into the degradation model. Results of a parametric analysis are presented, evaluating the effects of charging rates (1–6 C), operating temperatures (-15 – 45°C) and electrode design parameters, on the relative performance fade in the lithium-ion battery. Thermo-electrochemical process maps are developed to provide insights into the relationship between electrode performance and failure mechanisms. The simulation results predict a severe capacity loss due to lithium plating at low temperatures, which is further aggravated at high charging rates. A common strategy for mitigating lithium plating, through charging at high temperatures, also results in rapid capacity loss due to accelerated SEI formation. Simulation results are used to identify the combination of operating conditions and electrode design parameters that improve the electrochemical performance of the battery. These results demonstrate an opportunity to design safe and high-performance lithium-ion batteries, guided by anodic degradation models.

Battery design↗
DOE OSTI2024

Harnessing graph convolutional neural networks for identification of glassy states in metallic glasses

Graph Convolutional Neural Networks (GCNNs) have emerged as powerful tools for analyzing materials. In this study, we employ GCNNs to examine structural characteristics of CuZr metallic glasses (MGs) and identify their states. We use molecular dynamics to simulate the quenching process of CuZr, using cooling rates ranging from 10 9 to 10 15 K/s, to produce six unique glassy states. For each state, we create a dataset comprising 1,800 distinct samples. We evaluate the effectiveness of various GCNNs, including Graph Attention Neural Network (GANN), Graph Sample and AggreGatE (GraphSAGE), Graph Isomorphism Network (GIN), and Relational Graph Convolutional Neural Network (RGCN). GANN and GraphSAGE demonstrate comparable performance, achieving an overall accuracy of 81% in classifying the MG states. Furthermore, these results underscore the potential of GCNNs to detect subtle structural variances in disordered materials and point to broader application of deep learning in the analysis of MGs and other amorphous substances.

36 MATERIALS SCIENCE↗
DOE OSTI2025

A control-inspired approach for energy transition planning under uncertainty

As the global carbon footprint continues to grow, many countries are implementing carbon emission reduction policies which have incentivized the expansion of low-carbon and renewable technologies. However, the speed and scale of deployment falls short of that needed to meet climate goals. Energy system models serve as key tools for guiding investment decisions and helping policymakers evaluate the effects of various policies on the development of an energy system. This study focuses on the energy system of the United States and builds upon prior work by incorporating more geographic granularity to account for the trade of commodities and addresses transmission congestion through electricity price adjustments. Furthermore, real-world characteristics, such as delays in constructing new liquid fuel production and electricity generation facilities, are integrated using a sequential decision-making approach that better reflects how decisions can be updated as uncertainties unfold. Results demonstrate that stochastic programming combined with sequential decision-making produces energy transition pathways that are robust to multiple uncertain futures. Additionally, considering real-world characteristics significantly impacts the deployment of renewable technologies and the ability to meet carbon emission reduction goals while also reliably meeting demand. These findings highlight the importance of accounting for uncertainty and real-world characteristics to avoid overly optimistic projections in energy system planning.

energy systems↗
DOE OSTI2021

Simulated lightning strike investigation of CFRP comprising a novel Polyaniline/Phenol based electrically conductive resin matrix

Traditional carbon fiber reinforced plastics (CFRPs) have been reported to exhibit lower electrical conductivity in the through-thickness direction, and have since paved the path for developing new resin systems to improve the through-thickness electrical conductivity and functionality of CFRP laminates. This work designs and investigates a novel Polyaniline (PANI)/Phenol resin, which possesses high electrical conductivity and mechanical strength. The CFRP manufactured by this PANI/Phenol resin with an addition of up to (~23.30%) phenol resulted in 0.6 S/cm through-thickness conductivity and demonstrated flexural strength and modulus values of 477 MPa and 59.2 GPa, respectively. We further evaluate the effectiveness of lightning strike protection of PANI/Phenol-based conductive CFRP laminates with a simulated lightning strike test. In essence, this research reports on PANI/Phenol-based CFRP's effectiveness as a material for lightning suppression without applying traditional metal-based lightning strike protection (LSP) systems.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Degradation in interfacial shear strength of carbon fiber/ vinyl ester composites due to long-term exposure to seawater using push-out tests

Here, in this study, single fiber (~7-μm diameter) push-out tests are conducted to evaluate hygrothermal effects on the interfacial shear strength (IFSS) of carbon fiber/vinyl ester (CF/VE) composites. Hygrothermal conditioning is achieved by saturating samples in simulated seawater at 40 °C for two years. An investigation has been conducted on the preparation, validity, and interpretation of the push-out test results. First, the authors present a polishing methodology that results in thin films of CF/VE composites in the thickness range of 15–120 μm and produces an average 41.2% drop in IFSS due to long-term hygrothermal exposure. Using scanning electron microscopy (SEM), we show that during the push-out tests, the failure initiates locally at the zone of minimum bond strength at the bottom (away from the indenter), then propagates along the length of the interface. The influence of radial tensile stresses originating due to bending is found to be negligible. Using the SEM imaging of the pushed-out fibers, we validate the failure of the interface to be the primary source of failure. The associated results are found to depend on the thickness of the interface. We then reevaluate the results using the Weibull distribution, knowing that the failure mechanism is analogous to the weakest link theory. The results show a 25.5% drop in the IFSS of the CFVE composite, measured at an infinitesimal scale due to long-term to hygrothermal conditioning at 40 °C. A significant drop in IFSS was observed after reheating above glass transition temperature (T g ) and cooling.

36 MATERIALS SCIENCE↗
DOE OSTI2021

An innovative digital image correlation technique for in-situ process monitoring of composite structures in large scale additive manufacturing

As additive manufacturing (AM) continues to develop and become a standardized manufacturing method, there will be a continued need to provide in-situ monitoring during the manufacturing of polymer composite printed components. Thermal residual stress is a primary cause of failures such as interlayer disbonds or delamination, micro cracking, and dimensional instability, which can occur during or after the build. Here, we report a novel digital image correlation (DIC) adaptation to monitor thermal residual stresses during the entire print process for large-scale AM. In this work, DIC has been investigated (a) by the natural speckle produced by the polymer surface for correlation, (b) to monitor AM build, and (c) to evaluate the effect of thermal residual stress on warpage of the printed component. The natural speckle pattern of the AM material resulted in a respectable 3.57% error compared to the traditional painted speckle pattern of 3.05% error. DIC measured a 190% increase in vertical displacement at the edge of the wall compared to the center, indicating warpage during AM. This work is a step towards a non-intrusive residual stress measuring technique using DIC for large-scale AM.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Pathways to formulate lightweight and ultra-lightweight 3D printable cementitious composites

Here, this paper studies the pathways to formulate lightweight and ultra-lightweight 3D printable cementitious composites. A hybrid approach was proposed by combining the advantages of traditional chemical-induced foaming (foaming approach) and lightweight particulate inclusions (synthetic foam approach). A comprehensive experimental program was conducted to evaluate the effects of foaming agents and fly ash cenosphere (FAC) on the printability, microstructure, mechanical and thermal properties of 3D printed samples. The results showed that the hybrid approach could produce a mixture with a density as low as 470 kg/m 3 while ensuring good flowability and buildability owing to the lubricating effect of foaming and supporting skeleton formed by FAC. In addition, a three-step homogenization procedure was also developed to predict the effective elastic modulus and thermal conductivity of 3D printable cementitious composites and cementitious foam. The findings of the study highlighted the effectiveness of the hybrid approach in formulating 3D printable ultra-lightweight cementitious composites in thermal insulation and acoustic applications.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Corrosion of rebar in concrete. Part III: Artificial Neural Network analysis of chloride threshold data

Active corrosion of carbon steel in reinforced concrete occurs when the chloride ion concentration exceeds the chloride threshold (CT). CT is affected by many physical and chemical parameters including primary variables (pH, corrosion potential, breakdown potential, and temperature) and secondary variables (cemenet composition, concreete porosity, and water/cement ratio). A Kohonen-self organized map (KSOM) and regression artificial neural network (ANN) coupled methodology was developed to find the missing values of independent variables in the sparse database and for quantitatively evaluating the effects of these variables on CT values that are expressed in %TotalCl/cem (or %FreeCl/cem), and [Cl - ]/[OH - ].

36 MATERIALS SCIENCE↗