SEARCH · Engineering Papers
Results for “variables”
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.
Variable Laser Ignition Pathways in Al/Pt Reactive Multilayers across 10 Decades of Pulse Duration
Pulsed laser irradiation is used to investigate the local initiation of rapid, self-propagating formation reactions in Al/Pt multilayers. The single pulse direct laser ignition of these 1.6 μm thick freestanding foils was characterized over 10 decades of pulse duration (10 ms to 150 fs). Finite element, reactive heat transport modeling of the near-threshold conditions has identified three distinct ignition pathways. For milli- to microsecond pulses, ignition occurs following sufficient absorption of laser energy to enable diffusion of Al and Pt between layers such that the heat released from the corresponding exothermic reaction overcomes conductive losses outside the laser-irradiated zone. When pulse duration is decreased into the nanosecond regime, heat is concentrated near the surface such that the Al locally melts, and a portion of the top-most bilayers react initially. The favorable kinetics and additional heat enable ignition. Further reducing pulse duration to hundreds of femtoseconds leads to a third ignition pathway. In this work, while much of the energy from these pulses is lost to ablation, the remaining heat beneath the crater can be sufficiently concentrated to drive a transverse self-propagating reaction, wherein the heat released from mixing at each interface occurs under kinetic conditions capable of igniting the subsequent layer.
Overcoming Variability: A Reproducible Approach to SERS Detection of Nanodiamonds
Detonation nanodiamonds (DNDs) are formed at specific pressures and temperatures during explosions. Different explosives produce varied yields of DNDs within their detonation soot, with Composition B producing the highest yield. Raman spectroscopy (RS) is often used for the characterization of sp 2 - and sp 3 -hybridized carbon allotropes in carbonaceous materials because of distinct disorder and graphitic bands. Bulk diamond also gives a distinct Raman peak at 1332 cm –1 . Furthermore, as bulk diamond decreases in size to nanometer-sized species, the peak red-shifts and broadens, becoming increasingly difficult to detect with RS using visible excitations. Therefore, surface-enhanced Raman spectroscopy (SERS) was used to enhance the diamond peak of DNDs, enabling better detection and faster examination of DNDs within detonation soot. Previous literature of the SERS of DNDs delivered inconsistent results in spectral signatures and SERS substrates. Herein, refining of the methodology for the acquisition of SERS spectra of DNDs was achieved. Before any SERS experiments, the DNDs were first characterized with normal Raman (NR) and scanning electron microscopy. Two routes for SERS enhancement were evaluated: colloidal noble metal nanoparticles and evaporated silver films. Silver films produced the best signal enhancement of DNDs with the best signal-to-noise and peak enhancements observed at 20–30 nm thick silver films at 5% (∼300 μW) laser power. Consistent, reproducible SERS spectra were acquired of small aggregates of DNDs down to ∼500 nm. NR and SERS mapping analysis of DNDs before and after evaporation of silver films revealed the improvements in the detection capabilities of SERS compared with NR.
Complex Phase Behavior in Particle-Forming AB/AB;#8242; Diblock Copolymer Blends with Variable Core
Explore the source record for details and available documents.
Tuning Diblock Copolymer Particle Packing Symmetry with Variable Molecular Weight Core-Homopolymers
Not provided.
Quantification of Oxygen Vacancies in SrFe0.5Cr0.5O3−δ Thin Films: Correlating Lattice Expansion with Oxidation State Variability
Oxygen vacancies (VO), even in the dilute regime, can significantly impact the physical and chemical properties of complex oxides. It is however challenging to reliably detect and adequately quantify such defects in thin film samples where the VO concentration and distribution may further vary in response to interfacial strain. Here, we present a method to quantify VO concentrations in SrFe0.5Cr0.5O3−δ (SFCO) epitaxial thin films. Through coherent Bragg rod analysis, X-ray absorption spectroscopy, and theoretical modeling, we systematically correlate the c-axis lattice expansion detected in SFCO films with a VO concentration gradient. Our results reveal a nearly linear relationship between oxygen off-stoichiometry and out-of-plane lattice expansion in coherently strained SFCO films, with δ increasing from 0.32 to 0.52 and the lattice expanding by ∼1.0%. Moreover, a significant decrease in Cr oxidation state (from Cr5+ to Cr3+) is observed as the VO concentration increases, while the Fe oxidation state remains fixed at Fe3+. Our findings provide a reliable way to quantify oxygen stoichiometry in complex oxides, offering a pathway to design materials with precisely tailored structure–property relationships.
Shifting Valencies and Magnetic Responses in La-Based High-Entropy Oxide Perovskite Thin Films with Variable Mn Presence
Chemical disorder in compositionally complex perovskite oxides generates a broad distribution of exchange pathways and spin states, but the microscopic origin and spatial homogeneity of the resulting magnetic phases remain debated. Here, we tune the Mn fraction (x = 0.2–0.6) in epitaxial La(Cr, Mn, Fe, Co, Ni)O3 thin films and resolve the coupled evolution of valence, spin state, and magnetism using element-specific x-ray absorption spectroscopy and x-ray magnetic circular dichroism (XMCD). Mn enrichment drives an internal redistribution of charge, in which Mn evolves toward a Mn3+-rich mixed valence, while Co converts from predominantly Co3+ to high-spin Co2+. This valence/spin-state coupling amplifies the Mn- and Co-derived ferromagnetic response by nearly an order of magnitude while increasing the magnetic onset temperature to at least 250 K, whereas Fe and Cr remain essentially trivalent with weak dichroism. Depth-resolved low-energy muon spin spectroscopy (LE-μSR) shows magnetic homogeneity through the film thickness, with a secondary relaxation maximum near 25 K indicating a low-temperature dynamical crossover consistent with frustrated magnetism in a strongly disordered spin lattice.
First-Principles Insights into the Thermodynamics of Variable-Temperature Ammonia Synthesis on Transition-Metal-Doped Cu (100) and (111)
Ammonia (NH 3 ) is one of the most produced chemicals worldwide. NH 3 synthesis predominantly utilizes the Haber–Bosch (HB) process, requiring high temperatures and pressures. Despite significant process advances, ample opportunity remains for improving the rate, selectivity, catalyst stability, and energy efficiency. Inspired by a recently developed programmable heating and quenching (PHQ) technique, we present in this paper a first-principles screening of candidate single-atom alloy catalysts generated from doping (111) and (100) surfaces of copper (Cu), an ineffective HB catalyst in its pure form. We predict the thermodynamics of two rate-limiting reactions, N 2 dissociative adsorption and the final hydrogenation step leading up to NH 3 release, at 400 and 900 K. Thermodynamically, the former reaction is favored at low temperatures, while the latter is favored at high temperatures. Vanadium-, chromium-, and molybdenum-doped Cu surfaces, due to intermediate M–N covalent bonding character, emerge as appealing candidate catalysts for PHQ NH 3 synthesis, as they balance the thermodynamics of the above-mentioned reaction steps at their respective optimal temperatures.
Controlling Electronic Coupling of Acene Chromophores on Quantum Dot Surfaces through Variable-Concentration Ligand Exchange
Not Available
Greenhouse Gas Accounting Procedures in Low Carbon Fuel Policies Overlook the Spatial Variability of Miscanthus-Derived Sustainable Aviation Fuel
Low carbon fuel policies such as the U.S. Renewable Fuel Standard (RFS), Canada Clean Fuel Regulations (CFR), and California Low Carbon Fuel Standard (LCFS) as well as the 45Z tax credit are intended to reduce greenhouse gas (GHG) emissions from transportation. Cellulosic feedstocks, optimized biorefineries, and favorable farming locations can significantly reduce biofuel carbon intensity (CI). Despite advances in field-to-fuel GHG monitoring and flexibility in resource allocation within biorefineries (e.g., governing net electricity production), rigid CI accounting procedures in current policies may limit CI responsiveness across candidate sites and processing facilities. Here, this work examines a hypothetical biomass-to-sustainable aviation fuel (SAF) pathway using miscanthus and alcohol-to-jet (i) to demonstrate how GHG accounting requirements drive estimates of biofuel CIs and (ii) to explore potential CI and financial implications of scenario-specific life cycle assessment (LCA). Results demonstrate that GHG accounting using the CFR/LCFS can reasonably account for distinct levels of net electricity production by a biorefinery, but only the CFR yields similar CI sensitivity to spatially explicit factors (feedstock CI, grid electricity CI) as scenario-specific LCA: most GHG accounting frameworks do not capture CI variation across candidate sites in the United States. Ultimately, this work demonstrates the importance of LCA methodological specifications in low carbon fuel policies and tax credits.
Peak Ground Velocity Spatial Variability Revealed by Dense Seismic Array in Southern California
There are an infinite number of locations where seismic waves interact with Earth's surface, yet seismologists can only record a finite set of ground motions. This requires assumptions about how known measurements or predictions can be extrapolated to nearby locations. We test to what extent extrapolation is viable using an array of 1,108 geophones installed 10–20 m apart within a 0.36 km 2 study area for 1 month atop the San Jacinto Fault in Southern California. Measuring ground motions from 38 small local earthquakes, we observe peak ground velocity (PGV) variations up to 22% across the array. We find the basin structure consistently traps energy, amplifying the seismic velocities, and that the damaged region within the fault reduces the PGVs. Comparing surface and borehole measurements (148 m deep), we find PGVs recorded at the surface are 3–10 times greater than the measurements at depth. We attribute these differences to amplification from soft sediments within the basin. We show that by leveraging information from >1,000 measurements per earthquake the ground motion velocities can be tightly constrained. These results suggest the spatial extrapolation of PGVs in regions of known faults and basins, even across a small area, should be done with caution.
Subseasonal Variability of Elevated Dust Concentrations Over South Florida
Dust mass concentrations have been measured daily at Miami, Florida, in the summer months, and biweekly throughout the remaining months, since 1974. The 43-year record of dust mass concentrations indicate large daily, seasonal, and interannual variations, with most of the dust arriving within 5–8 episodes each summer. On average, dust arrives to Miami, Florida, 10 days after emission from North Africa, with measured concentrations depending on characteristics of the lower free-tropospheric winds due to the vast travel distance. Daily dust mass concentrations from July and August, the months that contribute the most to the annual mean, are used to characterize the synoptic conditions most favorable for dust transport. Two key regions are linked with the highest daily dust mass concentrations above Miami: (i) easterly winds, averaged over 850–500 mb, over the Tropical West Atlantic [15–25°N, 45–80°W], and (ii) southerly winds, similarly averaged, over the Florida Peninsula [20–30°N,75–80°W]. Winds within these two regions are enhanced when the North Atlantic subtropical high is displaced south and zonally elongated, relocating the western edge over Florida. A dust-transport-efficiency index, based on the maximum potential for dust to arrive above Miami with limited loss to deposition or mixing, identifies high-dust loading cases on the subseasonal scale. Monthly dust-transport-efficiency values agree well with the monthly dust trends over the 43-year time span. While seasonal dust loadings have been decreasing over Florida in the past decade, the transport efficiency has been increasing, possibly due to trends in the North Atlantic subtropical high.
Physically Interpretable Neural Networks for the Geosciences: Applications to Earth System Variability
Abstract Neural networks have become increasingly prevalent within the geosciences, although a common limitation of their usage has been a lack of methods to interpret what the networks learn and how they make decisions. As such, neural networks have often been used within the geosciences to most accurately identify a desired output given a set of inputs, with the interpretation of what the network learns used as a secondary metric to ensure the network is making the right decision for the right reason. Neural network interpretation techniques have become more advanced in recent years, however, and we therefore propose that the ultimate objective of using a neural network can also be the interpretation of what the network has learned rather than the output itself. We show that the interpretation of neural networks can enable the discovery of scientifically meaningful connections within geoscientific data. In particular, we use two methods for neural network interpretation called backward optimization and layerwise relevance propagation, both of which project the decision pathways of a network back onto the original input dimensions. To the best of our knowledge, LRP has not yet been applied to geoscientific research, and we believe it has great potential in this area. We show how these interpretation techniques can be used to reliably infer scientifically meaningful information from neural networks by applying them to common climate patterns. These results suggest that combining interpretable neural networks with novel scientific hypotheses will open the door to many new avenues in neural network‐related geoscience research.