SEARCH · Search NASA
Results for “analytical chemistry”
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.
Tough polycyclooctene nanoporous membranes from etchable block copolymers
Polycyclooctene-polylactide triblock copolymer synthesis and subsequent processingviasolvent casting, polylactide etching, and plasma etching to yield tunable and tough nanoporous membranes with high surface porosities and hydrophilic properties.
Surface phase diagrams from nested sampling
From nested sampling, we compute the partition function and, from that, the phase diagram of gas adsorbates, including their anharmonic and configurational degrees of freedom, on flat and stepped surfaces of the Lennard-Jones solid.
Effect of depth of discharge (DOD) on cycling in situ formed Li anodes
This study demonstrates that the stability of cyclingin situLi anodes depends on their depth of discharge (DOD). High DOD cycling results in unstable performance due to the accumulation of interfacial degradation at Li/LLZO interfaces.
Enhancing lithium metal batteries with a nano-silicon nitride-based solid electrolyte interface layer
Artificial nano Si 3 N 4 derived solid electrolyte interphase enables dendrite-free lithium cycling, effectively suppressing dendrite growth and delivering stable, long-term Li metal anode performance.
Exploiting ν-dependence of projected energy correlators in HICs
We extend the recently derived factorization formula for energy-energy correlators to study the analytic structure of general ν-point projected energy correlators in heavy ion collisions. The ν-point projected energy correlators (or, ν-correlators) are an analytically continued family of the integer N-point projected energy correlators, which probe correlations between N final-state particles. By tracking the largest separation (χ) between the N particles, in vacuum, their structure is closely related to the DGLAP splitting functions and exhibits a classical scaling behavior ∼ 1/χ which is modified by resummation through the anomalous dimensions. We show that, in a thermal medium, the ν-correlators display non-trivial angular scaling already at the leading order in perturbation theory. We find that for non-integer values, particularly ν < 1, medium-induced jet function is enhanced compared to ν > 1. This is particularly manifested in the ratios of ν-correlators with respect to the two-point energy correlator, which encodes intrinsic angular information for ν < 1 when compared to large ν values. Moreover, for small-ν values, the ν-correlators appear to saturate at ν = 0.01 . We further confirm our leading-order numerical computations against simulated events from JEWEL for the parton-level production cross-section. Finally, we qualitatively discuss the effect of BFKL resummation for various values of ν.
Corrosion kinetics of pure metals (Fe, Cr, Ni) and alloys (A709, SS316) in thermal and chemical purified molten chloride salt
This paper applied electrochemical methods to explore the corrosion mechanisms of metals and steels in purified molten chloride salt, especially under conditions dominated by cathodic diffusion limitations.
Identifying structure-function relationships to modulate crossover in nonaqueous redox flow batteries
QSPR analyses can be used to identify useful descriptors leading to statistical models for membrane crossover. This data-driven approach can be used to evaluate ROMs for asymmetric non-aqueous redox flow batteries.
Water-enhanced CO 2 capture with molecular salt sodium guanidinate
Solid-state amine absorbent materials, including those containing guanidine derivatives, have received tremendous attention as the world combats the challenges of climate change.
Advancements in 2D MXene-based supercapacitor electrodes: synthesis, mechanisms, electronic structure engineering, flexible wearable energy storage for real-world applications, and future prospects
Supercapacitors are widely recognized as a favorable option for energy storage due to their higher power density compared to batteries, despite their lower energy density.
The high-valent vanadium chemistry of isoindoline chelates
Isoindoline-based chelates, in particular bis(arylimino)isoindolines, have shown extensive metal binding chemistry. Although this chemistry has been explored for the middle and late transition metal ions, little work has been carried out on early transition metal complexes. In this article, we present the first examples of vanadium coordinated using four bis(arylimino)isoindolines, in which the aryl groups are pyrazole, indazole, benzimidazole, and pyridine (ligands 1–4 , respectively). We isolated five complexes using vanadyl sulfate or vanadyl acetylacetonate as the vanadium source. In all cases, the ligands bound in a meridional mode, and for four of the complexes, the vanadium ion was observed in the V(v) oxidation state. Three of the ligands ( 1–3 ) formed VO 2 complexes with vanadyl sulfate and vanadyl acetylacetonate, but the bis(pyridylimino)isoindoline (ligand 4 ) formed a V(v) oxosulfonato complex with the former starting material and a vanadyl V(iv) acetylacetonate with the latter starting material. All metal compounds were structurally elucidated by X-ray crystallographic methods, and we probed their electronic structures using DFT methods.
Broadening solid ionic conductor selection for sustainable and earth-abundant solid-state lithium metal batteries
We propose a universal solid electrolyte design that broadens the selection of ceramic LICs for solid-state lithium metal batteries, without requirements of electronic insulation or (electro)chemical stability.
PAL 2.0: a physics-driven bayesian optimization framework for material discovery
PAL 2.0 provides an efficient discovery tool for advanced functional materials, ameliorating a major bottleneck to enabling advances in next-generation energy, health, and sustainability technologies.
HANNA: hard-constraint neural network for consistent activity coefficient prediction
We introduce HANNA, the first hybrid neural network model that strictly complies with all thermodynamic consistency criteria for predicting activity coefficients and outperforms current benchmark methods in terms of accuracy and applicability.