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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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Understanding airflow pattern and temperature distribution in domestic refrigerators – A review analyzing recent developments and bridging knowledge gaps
Refrigerators have become an essential appliance in every household, and they consume approximately 30% of total electricity among other domestic appliances such as clothes washers, dryers, and air conditioners. With the refrigerator’s comparatively high energy consumption compared with other appliances, existing research has mainly focused on improving the energy efficiency of refrigerators by changing the design of the compressor, heat exchanger, refrigerant, and insulation. However, previous studies have paid very little attention to the research and development of the temperature distribution in the refrigerator, which is a key parameter in determining energy consumption and food safety. Therefore, this review aims to present an overview of recent design developments to improve the temperature distribution and air circulation in domestic refrigerators, including static refrigerators and no-frost refrigerators. Herein, this review article discusses the various operation and design factors that can affect the air circulation and temperature uniformity of the refrigerator, including shelf arrangement, the compressor on/off cycle, thermostat settings, evaporator design, ambient conditions, door opening frequency, and product loading temperatures. Additionally, this review provides a summary of the advanced vapor compression cycle based refrigerators that are expected to provide better energy efficiency and independent temperature control in freezer and refrigerator compartments. This review elaborates on the significance of improving the performance of the domestic refrigerator in terms of temperature distribution and air circulation.
PCAfold: Python software to generate, analyze and improve PCA-derived low-dimensional manifolds
Not Available
STEMTooL: An Open Source Python Toolkit for Analyzing Electron Microscopy Datasets
Explore the source record for details and available documents.
Community-Driven Methods for Open and Reproducible Software Tools for Analyzing Datasets from Atom Probe Microscopy
Atom probe tomography, and related methods, probe the three-dimensional architecture of a material. The software tools that microscopists use, and how these tools are connected into workflows, makes a substantial contribution to the accuracy and precision of such a material characterization experiment. Typically, we adapt methods from other communities like mathematics, data science, computational geometry, artificial intelligence, or scientific computing. We also realize that improving on research data management is a challenge when it comes to align with the FAIR data stewardship principles. Faced with this global challenge, we are convinced that collaborating is useful. Here, we report the results and challenges with an inter-laboratory call for developing test cases for several types of atom probe software tools. The results support why defining detailed recipes of software workflows and sharing these recipes is necessary and rewarding: Open source tools and (meta)data exchange can help to make our day-to-day data processing tasks become more efficient, the training of new users and knowledge transfer become easier, and assist us with automated quantification of uncertainties to gain access to substantiated results.
Analyzing and Tuning the Chalcogen–Amine–Thiol Complexes for Tailoring of Chalcogenide Syntheses
Abstract not provided
Analyzing Structure–Activity Variations for Mn–Carbonyl Complexes in the Reduction of CO 2 to CO
Not Available
Analyzing the Intensities of K-Edge Transitions in X 2 Molecules (X = F, Cl, Br) for Use in Ligand K-Edge X-ray Absorption Spectroscopy
Not Available
Using Diffusion Maps to Analyze Reaction Dynamics for a Hydrogen Combustion Benchmark Dataset
Not Available
Analyzing Stabilities of Metal–Organic Frameworks: Correlation of Stability with Node Coordination to Linkers and Degree of Node Metal Hydrolysis
Not Available
ClipsMS: An Algorithm for Analyzing Internal Fragments Resulting from Top-Down Mass Spectrometry
Not provided.
A Curated Experimental Compilation Analyzed by Theory Is More than a Review
Macromolecules is an exceptional resource in the field of polymer science and now publishes more than 1000 original articles a year that set the standard for scientific rigor and creative insights. Over the years, these individual contributions have combined to build the foundation of polymer science, broadly and inclusively defined. In addition to the individual articles, many of which are being celebrated in this series of editorials, Macromolecules has published invaluable reviews and perspectives. These scholarly contributions integrate the insights and results from numerous sources into a unified whole and often recommend future directions for the field. Novices and experts alike benefit from these works that capture topics from emerging discoveries to long-pondered topics and everything in between. To explore the importance of Macromolecules’ reviews and perspectives, we considered their influence on the field and found the 1994 review by Fetters et al. entitled “Connection between Polymer Molecular Weight, Density, Chain Dimensions, and Melt Viscoelastic Properties”1 to be a singularity. This review expertly curates and compiles a trove of data to build robust correlations between molecular characteristics and macroscopic viscoelastic properties of polymer melts, in the context of the tube model of entanglements.
Differentiating Double-Layer, Psuedocapacitance, and Battery-like Mechanisms by Analyzing Impedance Measurements in Three Dimensions
Electrochemical energy storage arises from processes that are broadly categorized as capacitive, pseudocapacitive, or battery-like. Advanced charge-storing materials that are designed to deliver high capacity at a high rate often exhibit a multiplicity of such mechanisms, which complicates the understanding of their charge-storage behavior. In this paper, we apply a “3D Bode analysis” technique to identify key descriptors for fast Li-ion storage processes, where AC impedance data, such as the real capacitance ($C'$) or phase angle ($Φ$), are represented versus the frequency ($f$) and a third independent variable, the applied DC cell voltage. For double-layer processes, a near-constant $C'$ or $Φ$ is supported across the entire voltage range, and the decrease in these values shows a near-linear decrease at higher $f$. For pseudocapacitance, an increase in $C'$ is delivered, accompanied by high $C'$ retention at higher $f$ compared to double-layer processes. Interestingly, the lower $Φ$ values, where $C'$ is highest, suggest that this is a key descriptor for pseudocapacitance, where high-rate charge storage is still facilitated within a kinetically limited regime. For battery-like processes, a high $C'$ is only observed at the voltage at which the material stores charge, while outside that voltage, $C'$ is negligible. The three-dimensional (3D) Bode analysis allows charge-storage dynamics to be mapped out in great detail with more delineation between mechanisms compared to the more frequently deployed kinetic analyses derived from cyclic voltammetry.