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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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A collaborative study on the precision of the Markov chain Monte Carlo algorithms used for DNA profile interpretation
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The need to consider regional supply chains and water usage in H 2 –steel transition
The iron and steel industry is one of the largest contributors to U.S. and global greenhouse gas emissions. Hydrogen can act as a promising reducing agent and clean energy carrier to decarbonize this sector, and has received significant attention in terms of process modelling, techno-economic analysis, and life cycle assessment in recent years. Policy incentives, hydrogen storage and transportation, and water stress levels are key factors that require significantly more consideration in order to realize hydrogen’s potential to decarbonize this industry. This review demonstrates the need for a systematic understanding and critical assessment of these areas, and their profound impacts on the decarbonization of the iron and steel sector. Furthermore, hydrogen and water supply face competition from other hard-to-decarbonize sectors, which should be considered on national and regional levels. Lastly, future research should also consider the impact of other environmental factors and hydrogen leak when deploying hydrogen at scale for industrial decarbonization.
Prolyl endopeptidase-like is a (thio)esterase involved in mitochondrial respiratory chain function
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Efficiency estimates for electromicrobial production of branched-chain hydrocarbons
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CRISPR/dCas12a knock-down of Acidithiobacillus ferrooxidans electron transport chain bc1 complexes enables enhanced metal sulfide bioleaching
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A Markov chain Monte Carlo (MCMC) Bayesian inference approach to analyze apparent activation barriers and reaction orders from microreactor data
Statistical analysis of steady-state catalytic kinetic data is often limited by data sparsity due to the slow pace at which the data is collected. Data sparsity and limitations in statistical analysis make it difficult to differentiate between mechanistic models and catalytic sites. A Bayesian inference tool is reported for catalysis researchers to estimate error in the determination of reaction orders from steady state microreactor data. The benefits of a Bayesian inference approach are discussed, as an alternative to the more common frequentist approach. The approach incorporates prior knowledge of the system and the data collected to form an error estimate on reaction orders. We investigated the effects of three distinct data treatments—individual fitting of trials, pooled analysis, and constrained regression methods—on the precision and uncertainty of reaction order determinations. To assess the robustness of our findings, we conducted sensitivity analyses to evaluate the influence of Bayesian parameters on uncertainty estimation. Additionally, we utilized synthetic data to illustrate how data quality impacts the precision of uncertainty assessments. We show Bayesian analysis can obtain a more precise estimation of error with a sparse data set than a frequentist analysis. Finally, this work provides strong evidence that the adoption of Bayesian analysis of kinetic data may help researchers make more precise arguments as to the strength of their evidence for a particular mechanistic hypothesis, or in comparing across different catalysts.
Phase diagrams and microstructures of aqueous short alkyl chain polyethylene glycol ether carboxylate and carboxylic acid triblock surfactant solutions
The surfactant C 8 Eo 8 CH 2 COOH (Akypo LF2) and its salts have a small hydrophobic and a significantly longer hydrophilic part. As a consequence, there must be a significant steric constraint, once these surfactant molecules form micelles. In addition, the partially charged headgroups should bring some additional fine-tuning via electrostatic interactions to this "essentially non-ionic" surfactant. Experiments: Phase diagrams of binary mixtures of water and C 8 Eo 8 CH 2 COOH are established over large concentration and temperature ranges, also at different pHs and in the presence of sodium and calcium ions. Surface tensions and osmotic pressures are measured to understand the systems. To evaluate the microstructures, also Dynamic Light Scattering and Small-Angle X-ray Scattering are performed.
Influence of chain length of amido betaines and amine degree of diamines on the binary supramolecular assembly and viscosity dynamics of amido betaine/diamine coacervates
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Correlation between upstreamness and downstreamness in random global value chains
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The acyl chains of phosphoinositide PIP3 alter the structure and function of nuclear receptor steroi
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Polarized infrared radiative transfer in an optically anisotropic medium: A Markov chain solution for remote sensing of atmospheric suspended particles
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Rare earth elements: Sector allocations and supply chain considerations
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Synthesis, crystal structure, and magnetic properties of a one-dimensional chain antiferromagnet NiC2O4 center dot 2NH(3)
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