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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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Protein architecture and core residues in unwound α-helices provide insights to the transport function of plant AtCHX17
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How willing are different types of landowner to supply hardwood timber residues for bioenergy?
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Incorporating anaerobic co-digestion of steam exploded or ammonia fiber expansion pretreated sugarcane residues with manure into a sugarcane-based bioenergy-livestock nexus
The co-digestion of pretreated sugarcane lignocelluloses with dairy cow manure (DCM) as a bioenergy production and waste management strategy, for intensive livestock farms located in sugarcane regions, was investigated. Ammonia fiber expansion (AFEX) increased the nitrogen content and accelerated the biodegradability of sugarcane bagasse (SCB) and cane leaf matter (CLM) through the cleavage of lignin carbohydrate crosslinks, resulting in the highest specific methane yields (292–299 L CH4/kg VSadded), biogas methane content (57–59% v/v) and biodegradation rates, with or without co-digestion with DCM. To obtain comparable methane yields, untreated and steam exploded (StEx) SCB and CLM had to be co-digested with DCM, at mass ratios providing initial C/N ratios in the range of 18 to 35. Co-digestion with DCM improved the nutrient content of the solid digestates, providing digestates that could be used as biofertilizer to replace CLM that is removed from sugarcane fields during green harvesting.
Pyrolysis of forest residues: An approach to techno-economics for bio-fuel production
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Amplified effect of mild plastic anisotropy on residual stress and strain anisotropy
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Effects of shear-thinning fluids on residual oil formation in microfluidic pore networks
Two-phase immiscible displacement in porous media is controlled by capillary and viscous forces when gravitational effects are negligible. The relative importance of these forces is quantified through the dimensionless capillary number Ca and the viscosity ratio M between fluid phases. When the displacing fluid is Newtonian, the effects of Ca and M on the displacement patterns can be evaluated independently. However, when the injecting fluids exhibit shear-thinning viscosity behaviour the values of M and Ca are interdependent. Under these conditions, the effects on phase entrapment and the general displacement dynamics cannot be dissociated. In the particular case of shear-thinning aqueous polymer solutions, the degree of interdependence between M and Ca is determined by the polymer concentration. In this work, two-phase immiscible displacement experiments were performed in micromodels, using shear-thinning aqueous polymer solutions as displacing fluids, to investigate the effect of polymer concentration on the relationship between Ca and M, the recovery efficiency, and the size distribution of the trapped non-wetting fluid. Our results show that the differences in terms of magnitude and distribution of the trapped phase are related to the polymer concentration which influences the values of Ca and M.
Integrated modeling for residual stress and failure behavior in welded Grade 91 steel cladded with nickel alloy
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Effective residual stress prediction validated with neutron diffraction method for metal large-scale additive manufacturing
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On the residual stress relaxation in Inconel 718 superalloys at high temperature by real-time neutron diffraction
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Generator speed regulation in the presence of structural modes through adaptive control using residual mode filters
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Self-restrained testing for residual stress driven cracking in nickel-based alloys
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Automated detection of corrosion in used nuclear fuel dry storage canisters using residual neural networks
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Segmentation method comparison for residual fiber length measurement across tiled microscopy images
Fiber length distribution (FLD), in part, governs mechanical properties in discontinuous fiber composites, yet manual measurement methods limit the high-throughput characterization needed for materials design optimization. This study compares deep learning segmentation approaches for automated FLD measurement in large-field microscopy, evaluating how method choice affects the microstructural descriptors used in structure-property-processing relationships. A critical challenge is that high-resolution microscopy images (10,000×10,000 pixels) must be tiled for deep learning analysis, fragmenting fibers at boundaries. We demonstrate that segmentation method proves crucial for measurement accuracy. For example, instance segmentation with Slicing Aided Hyper Inference (SAHI) preserves individual fiber integrity across tiles while semantic segmentation prioritizes speed. Comparing against manual measurement of extracted carbon fibers, YOLOv11-SAHI matched manual ground truth (238 μm weighted mean) with 40x speedup (4.5 vs 167 minutes per image). U-Net provides rapid quantification although it is at the cost of reduced accuracy due only reliably measuring stand-alone fibers. Our comparative analysis reveals that instance segmentation with SAHI better preserves length measurements while semantic segmentation prioritizes speed, providing empirical guidance for method selection. The characterization provides essential inputs for mechanical property prediction models and inverse design workflows, accelerating composite materials development cycles.
Suppression of crack formation in wafer-scale amorphous SiNx films by residual hydrogen-ligands manipulation
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Techno-economic and life-cycle analysis of strategies for improving operability and biomass quality in catalytic fast pyrolysis of forest residues
Many of the challenges faced by the first commercial biorefineries were associated with feedstock handling, quality, and cost. Strategies are needed to enable further expansion of biorefineries and meet the growing demand for bio-based fuels and products. Here, we examine 2 key feedstock challenges and mitigation strategies in the context of a catalytic fast pyrolysis (CFP) biorefinery: (1) the operability of the feed system, which may be improved by modifying the minimum particle size fed to the reactor, and (2) the quality of the biomass, which may be improved by employing air classification to remove undesirable material and increase fuel yields. We conduct techno-economic analysis (TEA) and life-cycle analysis for these strategies, employing a discrete event simulation model for biomass preprocessing combined with a series of correlations developed from literature data and a rigorous CFP conversion model. Our results highlight the importance of balancing increased cost and material losses from preprocessing against improved operability and fuel yields. Economics and sustainability were optimized when operating at the lowest minimum particle size, emphasizing the importance of minimizing material losses while maintaining the operability of the process. Economically, additional costs and material losses from air classification could be acceptable due to improved biomass conversion, and an optimum air classification speed was identified; however, the fuel GHG emissions were minimized when air classification was not used. Valorizing material removed during preprocessing as a coproduct could improve economics and sustainability, decreasing the burden of material losses.